Global warming of 1.5°C An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty Edited by Valérie Masson-Delmotte Panmao Zhai Co-Chair Working Group I Co-Chair Working Group I Hans-Otto Pörtner Debra Roberts Co-Chair Working Group II Co-Chair Working Group II Jim Skea Priyadarshi R. Shukla Co-Chair Working Group III Co-Chair Working Group III Anna Pirani Wilfran Moufouma-Okia Clotilde Péan Head of WGI TSU Head of Science Head of Operations Roz Pidcock Sarah Connors J. B. Robin Matthews Head of Communication Science Officer Science Officer Yang Chen Xiao Zhou Melissa I. Gomis Science Officer Science Assistant Graphics Officer Elisabeth Lonnoy Tom Maycock Melinda Tignor Tim Waterfield Project Assistant Science Editor Head of WGII TSU IT Officer Working Group I Technical Support Unit Please use the following reference to the whole report: IPCC, 2018: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)]. In Press. © 2019 Intergovernmental Panel on Climate Change. ISBN The designations employed and the presentation of material on maps do not imply the expression of any opinion whatsoever on the part of the Intergovernmental Panel on Climate Change concerning the legal status of any country, territory, city or area or of its authorities, or concerning the delimitation of its frontiers or boundaries. Front cover layout: Nigel Hawtin Front cover artwork: Time to Choose by Alisa Singer - www.environmentalgraphiti.org - © Intergovernmental Panel on Climate Change. The artwork was inspired by a graphic from the SPM (Figure SPM.1). ii Foreword and Preface Foreword Foreword This IPCC Special Report on Global Warming of 1.5°C was formally approved by the world’s governments in 2018 – the year of IPCC’s 30th anniversary celebrations. During its three decades of existence, the IPCC has shed light on climate change, contributing to the understanding of its causes and consequences and the options for risk management through adaptation and mitigation. In these three decades, global warming has continued unabated and we have witnessed an acceleration in sea- level rise. Emissions of greenhouse gases due to human activities, the root cause of global warming, continue to increase, year after year. Five years ago, the IPCC’s Fifth Assessment Report provided the scientific input into the Paris Agreement, which aims to strengthen the global response to the threat of climate change by holding the increase in the global average temperature to well below 2ºC above pre-industrial levels and to pursue efforts to limit the temperature increase to 1.5ºC above pre-industrial levels. Many countries considered that a level of global warming close to 2°C would not be safe and, at that time, there was only limited knowledge about the implications of a level of 1.5°C of warming for climate-related risks and in terms of the scale of mitigation ambition and its feasibility. Parties to the Paris Agreement therefore invited the IPCC to assess the impacts of global warming of 1.5°C above pre-industrial levels and the related emissions pathways that would achieve this enhanced global ambition. At the start of the Sixth Assessment cycle, governments, in a plenary IPCC session, decided to prepare three special reports, including this one, and expanded the scope of this special report by framing the assessment in the context of sustainable development and efforts to eradicate poverty. Sustainable development goals provide a new framework to consider climate action within the multiple dimensions of sustainability. This report is innovative in multiple ways. It shows the importance of integration across the traditional IPCC working groups and across disciplines within each chapter. Transitions, integrating adaptation and mitigation for each sector, are explored within six dimensions of feasibility, showing both low hanging fruits and barriers to overcome. It also provides scientific guidance on strategies to embed climate action within development strategies, and how to optimize choices that maximize benefits for multiple sustainable development dimensions and implement ethical and just transitions. In his address to the UN General Assembly in 2018, Secretary-General António Guterres quoted World Meteorological Organization (WMO) data showing that the past two decades have included eighteen of the twenty warmest years since record-keeping began in 1850. “Climate change is moving faster than we are,” said Secretary-General Guterres. “We must listen to the Earth’s best scientists,” he added. One month later the IPCC presented the Special Report on Global Warming of 1.5ºC, based on the assessment of around 6,000 peer-review publications, most of them published in the last few years. This Special Report confirms that climate change is already affecting people, ecosystems and livelihoods all around the world. It shows that limiting warming to 1.5ºC is possible within the laws of chemistry and physics but would require unprecedented transitions in all aspects of society. It finds that there are clear benefits to keeping warming to v Foreword Foreword 1.5ºC rather than 2ºC or higher. Every bit of warming matters. And it shows that limiting warming to 1.5ºC can go hand in hand with achieving other global goals such as the Sustainable Development Agenda. Every year matters and every choice matters. This Special Report also shows that recent trends in emissions and the level of international ambition indicated by nationally determined contributions, within the Paris Agreement, deviate from a track consistent with limiting warming to well below 2°C. Without increased and urgent mitigation ambition in the coming years, leading to a sharp decline in greenhouse gas emissions by 2030, global warming will surpass 1.5°C in the following decades, leading to irreversible loss of the most fragile ecosystems, and crisis after crisis for the most vulnerable people and societies. The Special Report on Global Warming of 1.5°C supports efforts by the WMO and United Nations Environment Programme for a comprehensive assessment of our understanding of climate change to help step up action to respond to climate change, achieve climate-resilient development and foster an integrated approach to the provision of climate services at all scales of governance. The IPCC worked in record time to deliver this report for the 24th Conference of Parties (COP24) to the United Nations Framework Convention on Climate Change (UNFCCC) and the Talanoa Dialogue. We would like to thank Hoesung Lee, Chair of the IPCC, for his leadership and guidance in the preparation of this Special Report. We commend the work undertaken by the authors of this Special Report and the many contributing authors and reviewers within a timeline of unprecedented severity; the leadership of the Co-Chairs of Working Groups I, II and III: Valérie Masson-Delmotte, Panmao Zhai, Hans-Otto Pörtner, Debra Roberts, Jim Skea and Priyadarshi R. Shukla; the oversight by the Bureau members of Working Groups I, II and III; and the implementation by the Technical Support Unit of Working Group I, supported by the Technical Support Units of Working Groups II and III. We are also grateful for the responsiveness of the international research community, who produced the knowledge assessed in the report, and thank the reviewers of the report for the thousands of comments that helped the authors strengthen the assessment. Every bit of warming matters, every year matters, every choice matters Petteri Taalas Joyce Msuya Secretary-General Acting Executive Director World Meteorological Organization United Nations Environment Programme vi Foreword Preface Preface This Special Report on Global Warming of 1.5°C, an IPCC Special Structure of the Report Report on the impacts of global warming of 1.5°C above pre- industrial levels and related global greenhouse gas emission This report consists of a short Summary for Policymakers, a pathways, in the context of strengthening the global response Technical Summary, five Chapters, and Annexes, as well as to the threat of climate change, sustainable development, online chapter Supplementary Material. and efforts to eradicate poverty, is the first publication in the Intergovernmental Panel on Climate Change (IPCC) Sixth Chapter 1 frames the context, knowledge base and assessment Assessment Report (AR6). The Report was jointly prepared by approaches used to understand the impacts of 1.5°C global Working Groups I, II and III. It is the first IPCC Report to be warming above pre-industrial levels and related global collectively produced by all three Working Groups, symbolizing greenhouse gas emission pathways, building on AR5, in the the new level of integration sought between Working Groups context of strengthening the global response to the threat during AR6. The Working Group I Technical Support Unit has of climate change, sustainable development, and efforts to been responsible for the logistical and technical support for eradicate poverty. The chapter provides an update on the the preparation of the Special Report. The Special Report current state of the climate system including the current level builds upon the IPCC’s Fifth Assessment Report (AR5) of warming. released in 2013–2014 and on relevant research subsequently published in the scientific, technical and socio-economic Chapter 2 assesses the literature on mitigation pathways literature. It has been prepared following IPCC principles and that limit or return global mean warming to 1.5°C (relative procedures, following AR5 guidance on calibrated language to the pre-industrial base period 1850–1900). Key questions for communicating the degree of certainty in key findings. addressed are: What types of mitigation pathways have been This Special Report is the first of three cross-Working Group developed that could be consistent with 1.5°C? What changes Special Reports to be published in AR6, accompanying the in emissions, energy and land use do they entail? What do three main Working Group Reports, the Synthesis Report they imply for climate policy and implementation, and what and a Refinement to the 2006 IPCC Guidelines for National impacts do they have on sustainable development? This Greenhouse Gas Inventories. chapter focuses on geophysical dimensions of feasibility and the technological and economic enabling conditions. Scope of the Report Chapter 3 builds on findings of AR5 and assesses new scientific evidence of changes in the climate system and the associated In its decision on the adoption of the Paris Agreement, the impacts on natural and human systems, with a specific focus Conference of Parties (COP) to the United Nations Framework on the magnitude and pattern of risks for global warming Convention on Climate Change (UNFCCC) at its 21st Session of 1.5°C above the pre-industrial period. It explores impacts in Paris, France (30 November to 11 December 2015), invited and risks for a range of natural and human systems, including the IPCC to provide a special report in 2018 on the impacts adaptation options, with a focus on how risk levels change of global warming of 1.5°C above pre-industrial levels and between today and worlds where global mean temperature related global greenhouse gas emission pathways. The Panel increases by 1.5°C and 2°C above pre-industrial levels. The accepted the invitation and placed the Report in the context chapter also revisits major categories of risk (Reasons for of strengthening the global response to the threat of climate Concern) based on the assessment of the new knowledge change, sustainable development, and efforts to eradicate available since AR5. poverty. Chapter 4 discusses how the global economy and socio- The broad scientific community has also responded to the technical and socio-ecological systems can transition to UNFCCC invitation. New knowledge and literature relevant to 1.5°C-consistent pathways and adapt to global warming of the topics of this report have been produced and published 1.5°C. In the context of systemic transitions across energy, worldwide. The Special Report is an assessment of the relevant land, urban and industrial systems, the chapter assesses state of knowledge, based on the scientific and technical adaptation and mitigation options, including carbon dioxide literature available and accepted for publication up to removal (CDR) measures, as well as the enabling conditions 15 May 2018. The Report draws on the findings of more than that would facilitate implementing the rapid and far-reaching 6,000 published articles. global response. Finally, Chapter 5 takes sustainable development, poverty eradication and reducing inequalities as the starting point and focus for analysis. It considers the complex interplay between vii Preface Preface sustainable development, including Sustainable Development Tania Guillén Bolaños, Daniel Huppmann, Kiane de Kleijne, Goals (SDGs) and climate actions related to a 1.5°C warmer Richard Millar and Chandni Singh. world. The chapter also examines synergies and trade- offs of adaptation and mitigation options with sustainable We would also like to thank the three Intergovernmental Panel development and the SDGs and offers insights into possible on Climate Change (IPCC) Vice-Chairs Ko Barrett, Thelma Krug, pathways, especially climate-resilient development pathways and Youba Sokona as well as the members of the WGI, WGII toward a 1.5°C warmer world. and WGIII Bureaux for their assistance, guidance, and wisdom throughout the preparation of the Report: Amjad Abdulla, Edvin Aldrian, Carlo Carraro, Diriba Korecha Dadi, Fatima Driouech, The Process Andreas Fischlin, Gregory Flato, Jan Fuglestvedt, Mark Howden, Nagmeldin G. E. Mahmoud, Carlos Mendez, Joy Jacqueline The Special Report on 1.5°C of the IPCC AR6 has been prepared Pereira, Ramón Pichs-Madruga, Andy Reisinger, Roberto Sánchez in accordance with the principles and procedures established Rodríguez, Sergey Semenov, Muhammad I. Tariq, Diana Ürge- by the IPCC and represents the combined efforts of leading Vorsatz, Carolina Vera, Pius Yanda, Noureddine Yassaa, and Taha experts in the field of climate change. A scoping meeting for Zatari. the SR1.5°C was held in Geneva, Switzerland, in August 2016, and the final outline was approved by the Panel at its 44th Our heartfelt thanks go to the hosts and organizers of the Session in October 2016 in Bangkok, Thailand. Governments scoping meeting, the four Special Report on 1.5°C Lead and IPCC observer organizations nominated 541 experts for Author Meetings and the 48th Session of the IPCC. We the author team. The team of 74 Coordinating Lead Authors gratefully acknowledge the support from the host countries and Lead Authors plus 17 Review Editors were selected and institutions: World Meteorological Organization, by the Working Group I, II and III Bureaux. In addition, 133 Switzerland; Ministry of Foreign Affairs, and the National Contributing Authors were invited by chapter teams to provide Institute for Space Research (INPE), Brazil; Met Office and technical information in the form of text, graphs or data for the University of Exeter, the United Kingdom; Swedish assessment. Report drafts prepared by the authors were Meteorological and Hydrological Institute (SMHI), Sweden; subject to two rounds of formal review and revision followed the Ministry of Environment Natural Resources Conservation by a final round of government comments on the Summary for and Tourism, the National Climate Change Committee in the Policymakers. The enthusiastic participation of the scientific Department of Meteorological Services and the Botswana community and governments to the review process resulted in Global Environmental Change Committee at the University of 42,001 written review comments submitted by 796 individual Botswana, Botswana; and Korea Meteorological Administration expert reviewers and 65 governments. (KMA) and Incheon Metropolitan City, the Republic of Korea. The support provided by governments and institutions, as well The 17 Review Editors monitored the review process to ensure as through contributions to the IPCC Trust Fund, is thankfully that all substantive review comments received appropriate acknowledged as it enabled the participation of the author consideration. The Summary for Policymakers was approved teams in the preparation of the Report. The efficient operation line-by-line at the joint meeting of Working Groups I, II and of the Working Group I Technical Support Unit was made III; it and the underlying chapters were then accepted at the possible by the generous financial support provided by the 48th Session of the IPCC from 01–06 October 2018 in Incheon, government of France and administrative and information Republic of Korea. technology support from the Université Paris Saclay (France), Institut Pierre Simon Laplace (IPSL) and the Laboratoire des Sciences du Climat et de l’Environnement (LSCE). We thank the Acknowledgements Norwegian Environment Agency for supporting the preparation of the graphics for the Summary for Policymakers. We thank We are very grateful for the expertise, rigour and dedication the UNEP Library, who supported authors throughout the shown throughout by the volunteer Coordinating Lead Authors drafting process by providing literature for the assessment. and Lead Authors, working across scientific disciplines in each chapter of the report, with essential help by the many We would also like to thank Abdalah Mokssit, Secretary of the Contributing Authors. The Review Editors have played a critical IPCC, and the staff of the IPCC Secretariat: Kerstin Stendahl, role in assisting the author teams and ensuring the integrity Jonathan Lynn, Sophie Schlingemann, Judith Ewa, Mxolisi of the review process. We express our sincere appreciation Shongwe, Jesbin Baidya, Werani Zabula, Nina Peeva, Joelle to all the expert and government reviewers. A special thanks Fernandez, Annie Courtin, Laura Biagioni and Oksana Ekzarho. goes to the Chapter Scientists of this report who went Thanks are due to Elhousseine Gouaini who served as the above and beyond what was expected of them: Neville Ellis, conference officer for the 48th Session of the IPCC. viii Preface Preface Finally, our particular appreciation goes to the Working Neogi and Joana Portugal Pereira from the WGIII Technical Group Technical Support Units whose tireless dedication, Support Unit. A special thanks goes to Kenny Coventry, professionalism and enthusiasm led the production of this Harmen Gudde, Irene Lorenzoni, and Stuart Jenkins for their Special Report. This Report could not have been prepared support with the figures in the Summary for Policymakers, without the commitment of members of the Working Group I as well as Nigel Hawtin for graphical support of the Report. Technical Support Unit, all new to the IPCC, who rose to In addition, the following contributions are gratefully the unprecedented Sixth Assessment Report challenge and acknowledged: Jatinder Padda (copy edit), Melissa Dawes were pivotal in all aspects of the preparation of the Report: (copy edit), Marilyn Anderson (index), Vincent Grégoire Yang Chen, Sarah Connors, Melissa Gomis, Elisabeth Lonnoy, (layout) and Sarah le Rouzic (intern). Robin Matthews, Wilfran Moufouma-Okia, Clotilde Péan, Roz Pidcock, Anna Pirani, Nicholas Reay, Tim Waterfield, The Special Report website has been developed by Habitat 7, and Xiao Zhou. Our warmest thanks go to the collegial and led by Jamie Herring, and the report content has been collaborative support provided by Marlies Craig, Andrew prepared and managed for the website by Nicholas Reay and Okem, Jan Petzold, Melinda Tignor and Nora Weyer from the Tim Waterfield. We gratefully acknowledge the UN Foundation for WGII Technical Support Unit and Bhushan Kankal, Suvadip supporting the website development. Valérie Masson-Delmotte Panmao Zhai IPCC Working Group I Co-Chair IPCC Working Group I Co-Chair Hans-Otto Pörtner Debra Roberts IPCC Working Group II Co-Chair IPCC Working Group II Co-Chair Priyadarshi R. Shukla Jim Skea IPCC Working Group III Co-Chair IPCC Working Group III Co-Chair ix Preface « Pour ce qui est de l’avenir, il ne s’agit pas de le prévoir, mais de le rendre possible. » Antoine de Saint Exupéry, Citadelle, 1948 xi Contents Front Matter Foreword ........................................................................................................................................................................................................................v Preface .......................................................................................................................................................................................................................... vii SPM Summary for Policymakers ..............................................................................................................................................................................3 TS Technical Summary .............................................................................................................................................................................................. 27 Chapters Chapter 1 Framing and Context ....................................................................................................................................................................................... 49 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development ...... 93 Chapter 3 Impacts of 1.5ºC Global Warming on Natural and Human Systems ......................................................175 Chapter 4 Strengthening and Implementing the Global Response ...............................................................................313 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities ......................................445 Annexes Annex I Glossary ......................................................................................................................................................................................541 Annex II Acronyms ...................................................................................................................................................................................563 Annex III Contributors to the IPCC Special Report on Global Warming of 1.5°C ................................................573 Annex IV Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C .....................................581 Index .............................................................................................................................................................................................................................601 Summary for Policymakers Summary for Policymakers SPM SPM SPM Summary for Policymakers Drafting Authors: Myles Allen (UK), Mustafa Babiker (Sudan), Yang Chen (China), Heleen de Coninck (Netherlands/EU), Sarah Connors (UK), Renée van Diemen (Netherlands), Opha Pauline Dube (Botswana), Kristie L. Ebi (USA), Francois Engelbrecht (South Africa), Marion Ferrat (UK/France), James Ford (UK/Canada), Piers Forster (UK), Sabine Fuss (Germany), Tania Guillén Bolaños (Germany/Nicaragua), Jordan Harold (UK), Ove Hoegh-Guldberg (Australia), Jean-Charles Hourcade (France), Daniel Huppmann (Austria), Daniela Jacob (Germany), Kejun Jiang (China), Tom Gabriel Johansen (Norway), Mikiko Kainuma (Japan), Kiane de Kleijne (Netherlands/EU), Elmar Kriegler (Germany), Debora Ley (Guatemala/Mexico), Diana Liverman (USA), Natalie Mahowald (USA), Valérie Masson-Delmotte (France), J. B. Robin Matthews (UK), Richard Millar (UK), Katja Mintenbeck (Germany), Angela Morelli (Norway/Italy), Wilfran Moufouma-Okia (France/Congo), Luis Mundaca (Sweden/Chile), Maike Nicolai (Germany), Chukwumerije Okereke (UK/Nigeria), Minal Pathak (India), Antony Payne (UK), Roz Pidcock (UK), Anna Pirani (Italy), Elvira Poloczanska (UK/Australia), Hans- Otto Pörtner (Germany), Aromar Revi (India), Keywan Riahi (Austria), Debra C. Roberts (South Africa), Joeri Rogelj (Austria/Belgium), Joyashree Roy (India), Sonia I. Seneviratne (Switzerland), Priyadarshi R. Shukla (India), James Skea (UK), Raphael Slade (UK), Drew Shindell (USA), Chandni Singh (India), William Solecki (USA), Linda Steg (Netherlands), Michael Taylor (Jamaica), Petra Tschakert (Australia/Austria), Henri Waisman (France), Rachel Warren (UK), Panmao Zhai (China), Kirsten Zickfeld (Canada). This Summary for Policymakers should be cited as: IPCC, 2018: Summary for Policymakers. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)]. In Press. 3 Summary for Policymakers Introduction This Report responds to the invitation for IPCC ‘... to provide a Special Report in 2018 on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways’ contained in the Decision of the 21st Conference of Parties of the United Nations Framework Convention on Climate Change to adopt the Paris Agreement.1 SPM The IPCC accepted the invitation in April 2016, deciding to prepare this Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty. This Summary for Policymakers (SPM) presents the key findings of the Special Report, based on the assessment of the available scientific, technical and socio-economic literature2 relevant to global warming of 1.5°C and for the comparison between global warming of 1.5°C and 2°C above pre-industrial levels. The level of confidence associated with each key finding is reported using the IPCC calibrated language.3 The underlying scientific basis of each key finding is indicated by references provided to chapter elements. In the SPM, knowledge gaps are identified associated with the underlying chapters of the Report. A. Understanding Global Warming of 1.5°C4 A.1 Human activities are estimated to have caused approximately 1.0°C of global warming5 above pre-industrial levels, with a likely range of 0.8°C to 1.2°C. Global warming is likely to reach 1.5°C between 2030 and 2052 if it continues to increase at the current rate. (high confidence) (Figure SPM.1) {1.2} A.1.1 Reflecting the long-term warming trend since pre-industrial times, observed global mean surface temperature (GMST) for the decade 2006–2015 was 0.87°C (likely between 0.75°C and 0.99°C)6 higher than the average over the 1850–1900 period (very high confidence). Estimated anthropogenic global warming matches the level of observed warming to within ±20% (likely range). Estimated anthropogenic global warming is currently increasing at 0.2°C (likely between 0.1°C and 0.3°C) per decade due to past and ongoing emissions (high confidence). {1.2.1, Table 1.1, 1.2.4} A.1.2 Warming greater than the global annual average is being experienced in many land regions and seasons, including two to three times higher in the Arctic. Warming is generally higher over land than over the ocean. (high confidence) {1.2.1, 1.2.2, Figure 1.1, Figure 1.3, 3.3.1, 3.3.2} A.1.3 Trends in intensity and frequency of some climate and weather extremes have been detected over time spans during which about 0.5°C of global warming occurred (medium confidence). This assessment is based on several lines of evidence, including attribution studies for changes in extremes since 1950. {3.3.1, 3.3.2, 3.3.3} 1 Decision 1/CP.21, paragraph 21. 2 The assessment covers literature accepted for publication by 15 May 2018. 3 Each finding is grounded in an evaluation of underlying evidence and agreement. A level of confidence is expressed using five qualifiers: very low, low, medium, high and very high, and typeset in italics, for example, medium confidence. The following terms have been used to indicate the assessed likelihood of an outcome or a result: virtually certain 99–100% probability, very likely 90–100%, likely 66–100%, about as likely as not 33–66%, unlikely 0–33%, very unlikely 0–10%, exceptionally unlikely 0–1%. Additional terms (extremely likely 95–100%, more likely than not >50–100%, more unlikely than likely 0–<50%, extremely unlikely 0–5%) may also be used when appropriate. Assessed likelihood is typeset in italics, for example, very likely. This is consistent with AR5. 4 See also Box SPM.1: Core Concepts Central to this Special Report. 5 Present level of global warming is defined as the average of a 30-year period centred on 2017 assuming the recent rate of warming continues. 6 This range spans the four available peer-reviewed estimates of the observed GMST change and also accounts for additional uncertainty due to possible short-term natural variability. {1.2.1, Table 1.1} 4 Summary for Policymakers A.2 Warming from anthropogenic emissions from the pre-industrial period to the present will persist for centuries to millennia and will continue to cause further long-term changes in the climate system, such as sea level rise, with associated impacts (high confidence), but these emissions alone are unlikely to cause global warming of 1.5°C (medium confidence). (Figure SPM.1) {1.2, 3.3, Figure 1.5} SPM A.2.1 Anthropogenic emissions (including greenhouse gases, aerosols and their precursors) up to the present are unlikely to cause further warming of more than 0.5°C over the next two to three decades (high confidence) or on a century time scale (medium confidence). {1.2.4, Figure 1.5} A.2.2 Reaching and sustaining net zero global anthropogenic CO2 emissions and declining net non-CO2 radiative forcing would halt anthropogenic global warming on multi-decadal time scales (high confidence). The maximum temperature reached is then determined by cumulative net global anthropogenic CO2 emissions up to the time of net zero CO2 emissions (high confidence) and the level of non-CO2 radiative forcing in the decades prior to the time that maximum temperatures are reached (medium confidence). On longer time scales, sustained net negative global anthropogenic CO2 emissions and/ or further reductions in non-CO2 radiative forcing may still be required to prevent further warming due to Earth system feedbacks and to reverse ocean acidification (medium confidence) and will be required to minimize sea level rise (high confidence). {Cross-Chapter Box 2 in Chapter 1, 1.2.3, 1.2.4, Figure 1.4, 2.2.1, 2.2.2, 3.4.4.8, 3.4.5.1, 3.6.3.2} A.3 Climate-related risks for natural and human systems are higher for global warming of 1.5°C than at present, but lower than at 2°C (high confidence). These risks depend on the magnitude and rate of warming, geographic location, levels of development and vulnerability, and on the choices and implementation of adaptation and mitigation options (high confidence). (Figure SPM.2) {1.3, 3.3, 3.4, 5.6} A.3.1 Impacts on natural and human systems from global warming have already been observed (high confidence). Many land and ocean ecosystems and some of the services they provide have already changed due to global warming (high confidence). (Figure SPM.2) {1.4, 3.4, 3.5} A.3.2 Future climate-related risks depend on the rate, peak and duration of warming. In the aggregate, they are larger if global warming exceeds 1.5°C before returning to that level by 2100 than if global warming gradually stabilizes at 1.5°C, especially if the peak temperature is high (e.g., about 2°C) (high confidence). Some impacts may be long-lasting or irreversible, such as the loss of some ecosystems (high confidence). {3.2, 3.4.4, 3.6.3, Cross-Chapter Box 8 in Chapter 3} A.3.3 Adaptation and mitigation are already occurring (high confidence). Future climate-related risks would be reduced by the upscaling and acceleration of far-reaching, multilevel and cross-sectoral climate mitigation and by both incremental and transformational adaptation (high confidence). {1.2, 1.3, Table 3.5, 4.2.2, Cross-Chapter Box 9 in Chapter 4, Box 4.2, Box 4.3, Box 4.6, 4.3.1, 4.3.2, 4.3.3, 4.3.4, 4.3.5, 4.4.1, 4.4.4, 4.4.5, 4.5.3} 5 Summary for Policymakers Cumulative emissions of CO2 and future non-CO2 radiative forcing determine the probability of limiting warming to 1.5°C a) Observed global temperature change and modeled SPM responses to stylized anthropogenic emission and forcing pathways Global warming relative to 1850-1900 (°C) 2.0 1.5 Observed monthly global mean surface temperature Estimated anthropogenic warming to date and 1.0 likely range Likely range of modeled responses to stylized pathways Global CO2 emissions reach net zero in 2055 while net non-CO2 radiative forcing is reduced aer 2030 (grey in b, c & d) 0.5 2017 Faster CO2 reductions (blue in b & c) result in a higher probability of limiting warming to 1.5°C No reduction of net non-CO2 radiative forcing (purple in d) results in a lower probability of limiting warming to 1.5°C 0 1960 1980 2000 2020 2040 2060 2080 2100 b) Stylized net global CO2 emission pathways c) Cumulative net CO2 emissions d) Non-CO2 radiative forcing pathways Billion tonnes CO2 per year (GtCO2/yr) Billion tonnes CO2 (GtCO2) Watts per square metre (W/m2) 60 CO2 emissions 50 3 000 3 decline from 2020 to reach net zero in Non-CO2 radiative forcing 40 2055 or 2040 reduced aer 2030 or 2 000 2 not reduced aer 2030 30 Cumulative CO2 emissions in pathways 20 1 000 reaching net zero in 1 2055 and 2040 10 0 0 0 1980 2020 2060 2100 1980 2020 2060 2100 1980 2020 2060 2100 Faster immediate CO2 emission reductions Maximum temperature rise is determined by cumulative net CO2 emissions and net non-CO2 limit cumulative CO2 emissions shown in radiative forcing due to methane, nitrous oxide, aerosols and other anthropogenic forcing agents. panel (c). Figure SPM.1 | Panel a: Observed monthly global mean surface temperature (GMST, grey line up to 2017, from the HadCRUT4, GISTEMP, Cowtan–Way, and NOAA datasets) change and estimated anthropogenic global warming (solid orange line up to 2017, with orange shading indicating assessed likely range). Orange dashed arrow and horizontal orange error bar show respectively the central estimate and likely range of the time at which 1.5°C is reached if the current rate of warming continues. The grey plume on the right of panel a shows the likely range of warming responses, computed with a simple climate model, to a stylized pathway (hypothetical future) in which net CO2 emissions (grey line in panels b and c) decline in a straight line from 2020 to reach net zero in 2055 and net non- CO2 radiative forcing (grey line in panel d) increases to 2030 and then declines. The blue plume in panel a) shows the response to faster CO2 emissions reductions (blue line in panel b), reaching net zero in 2040, reducing cumulative CO2 emissions (panel c). The purple plume shows the response to net CO2 emissions declining to zero in 2055, with net non-CO2 forcing remaining constant after 2030. The vertical error bars on right of panel a) show the likely ranges (thin lines) and central terciles (33rd – 66th percentiles, thick lines) of the estimated distribution of warming in 2100 under these three stylized pathways. Vertical dotted error bars in panels b, c and d show the likely range of historical annual and cumulative global net CO2 emissions in 2017 (data from the Global Carbon Project) and of net non-CO2 radiative forcing in 2011 from AR5, respectively. Vertical axes in panels c and d are scaled to represent approximately equal effects on GMST. {1.2.1, 1.2.3, 1.2.4, 2.3, Figure 1.2 and Chapter 1 Supplementary Material, Cross-Chapter Box 2 in Chapter 1} 6 Summary for Policymakers B. Projected Climate Change, Potential Impacts and Associated Risks B.1 Climate models project robust7 differences in regional climate characteristics between present-day and global warming of 1.5°C,8 and between 1.5°C and 2°C.8 These differences include increases in: mean temperature in most land and ocean regions (high confidence), hot extremes in most SPM inhabited regions (high confidence), heavy precipitation in several regions (medium confidence), and the probability of drought and precipitation deficits in some regions (medium confidence). {3.3} B.1.1 Evidence from attributed changes in some climate and weather extremes for a global warming of about 0.5°C supports the assessment that an additional 0.5°C of warming compared to present is associated with further detectable changes in these extremes (medium confidence). Several regional changes in climate are assessed to occur with global warming up to 1.5°C compared to pre-industrial levels, including warming of extreme temperatures in many regions (high confidence), increases in frequency, intensity, and/or amount of heavy precipitation in several regions (high confidence), and an increase in intensity or frequency of droughts in some regions (medium confidence). {3.2, 3.3.1, 3.3.2, 3.3.3, 3.3.4, Table 3.2} B.1.2 Temperature extremes on land are projected to warm more than GMST (high confidence): extreme hot days in mid-latitudes warm by up to about 3°C at global warming of 1.5°C and about 4°C at 2°C, and extreme cold nights in high latitudes warm by up to about 4.5°C at 1.5°C and about 6°C at 2°C (high confidence). The number of hot days is projected to increase in most land regions, with highest increases in the tropics (high confidence). {3.3.1, 3.3.2, Cross-Chapter Box 8 in Chapter 3} B.1.3 Risks from droughts and precipitation deficits are projected to be higher at 2°C compared to 1.5°C of global warming in some regions (medium confidence). Risks from heavy precipitation events are projected to be higher at 2°C compared to 1.5°C of global warming in several northern hemisphere high-latitude and/or high-elevation regions, eastern Asia and eastern North America (medium confidence). Heavy precipitation associated with tropical cyclones is projected to be higher at 2°C compared to 1.5°C global warming (medium confidence). There is generally low confidence in projected changes in heavy precipitation at 2°C compared to 1.5°C in other regions. Heavy precipitation when aggregated at global scale is projected to be higher at 2°C than at 1.5°C of global warming (medium confidence). As a consequence of heavy precipitation, the fraction of the global land area affected by flood hazards is projected to be larger at 2°C compared to 1.5°C of global warming (medium confidence). {3.3.1, 3.3.3, 3.3.4, 3.3.5, 3.3.6} B.2 By 2100, global mean sea level rise is projected to be around 0.1 metre lower with global warming of 1.5°C compared to 2°C (medium confidence). Sea level will continue to rise well beyond 2100 (high confidence), and the magnitude and rate of this rise depend on future emission pathways. A slower rate of sea level rise enables greater opportunities for adaptation in the human and ecological systems of small islands, low-lying coastal areas and deltas (medium confidence). {3.3, 3.4, 3.6} B.2.1 Model-based projections of global mean sea level rise (relative to 1986–2005) suggest an indicative range of 0.26 to 0.77 m by 2100 for 1.5°C of global warming, 0.1 m (0.04–0.16 m) less than for a global warming of 2°C (medium confidence). A reduction of 0.1 m in global sea level rise implies that up to 10 million fewer people would be exposed to related risks, based on population in the year 2010 and assuming no adaptation (medium confidence). {3.4.4, 3.4.5, 4.3.2} B.2.2 Sea level rise will continue beyond 2100 even if global warming is limited to 1.5°C in the 21st century (high confidence). Marine ice sheet instability in Antarctica and/or irreversible loss of the Greenland ice sheet could result in multi-metre rise in sea level over hundreds to thousands of years. These instabilities could be triggered at around 1.5°C to 2°C of global warming (medium confidence). (Figure SPM.2) {3.3.9, 3.4.5, 3.5.2, 3.6.3, Box 3.3} 7 Robust is here used to mean that at least two thirds of climate models show the same sign of changes at the grid point scale, and that differences in large regions are statistically significant. 8 Projected changes in impacts between different levels of global warming are determined with respect to changes in global mean surface air temperature. 7 Summary for Policymakers B.2.3 Increasing warming amplifies the exposure of small islands, low-lying coastal areas and deltas to the risks associated with sea level rise for many human and ecological systems, including increased saltwater intrusion, flooding and damage to infrastructure (high confidence). Risks associated with sea level rise are higher at 2°C compared to 1.5°C. The slower rate of sea level rise at global warming of 1.5°C reduces these risks, enabling greater opportunities for adaptation including SPM managing and restoring natural coastal ecosystems and infrastructure reinforcement (medium confidence). (Figure SPM.2) {3.4.5, Box 3.5} B.3 On land, impacts on biodiversity and ecosystems, including species loss and extinction, are projected to be lower at 1.5°C of global warming compared to 2°C. Limiting global warming to 1.5°C compared to 2°C is projected to lower the impacts on terrestrial, freshwater and coastal ecosystems and to retain more of their services to humans (high confidence). (Figure SPM.2) {3.4, 3.5, Box 3.4, Box 4.2, Cross-Chapter Box 8 in Chapter 3} B.3.1 Of 105,000 species studied,9 6% of insects, 8% of plants and 4% of vertebrates are projected to lose over half of their climatically determined geographic range for global warming of 1.5°C, compared with 18% of insects, 16% of plants and 8% of vertebrates for global warming of 2°C (medium confidence). Impacts associated with other biodiversity-related risks such as forest fires and the spread of invasive species are lower at 1.5°C compared to 2°C of global warming (high confidence). {3.4.3, 3.5.2} B.3.2 Approximately 4% (interquartile range 2–7%) of the global terrestrial land area is projected to undergo a transformation of ecosystems from one type to another at 1°C of global warming, compared with 13% (interquartile range 8–20%) at 2°C (medium confidence). This indicates that the area at risk is projected to be approximately 50% lower at 1.5°C compared to 2°C (medium confidence). {3.4.3.1, 3.4.3.5} B.3.3 High-latitude tundra and boreal forests are particularly at risk of climate change-induced degradation and loss, with woody shrubs already encroaching into the tundra (high confidence) and this will proceed with further warming. Limiting global warming to 1.5°C rather than 2°C is projected to prevent the thawing over centuries of a permafrost area in the range of 1.5 to 2.5 million km2 (medium confidence). {3.3.2, 3.4.3, 3.5.5} B.4 Limiting global warming to 1.5°C compared to 2°C is projected to reduce increases in ocean temperature as well as associated increases in ocean acidity and decreases in ocean oxygen levels (high confidence). Consequently, limiting global warming to 1.5°C is projected to reduce risks to marine biodiversity, fisheries, and ecosystems, and their functions and services to humans, as illustrated by recent changes to Arctic sea ice and warm-water coral reef ecosystems (high confidence). {3.3, 3.4, 3.5, Box 3.4, Box 3.5} B.4.1 There is high confidence that the probability of a sea ice-free Arctic Ocean during summer is substantially lower at global warming of 1.5°C when compared to 2°C. With 1.5°C of global warming, one sea ice-free Arctic summer is projected per century. This likelihood is increased to at least one per decade with 2°C global warming. Effects of a temperature overshoot are reversible for Arctic sea ice cover on decadal time scales (high confidence). {3.3.8, 3.4.4.7} B.4.2 Global warming of 1.5°C is projected to shift the ranges of many marine species to higher latitudes as well as increase the amount of damage to many ecosystems. It is also expected to drive the loss of coastal resources and reduce the productivity of fisheries and aquaculture (especially at low latitudes). The risks of climate-induced impacts are projected to be higher at 2°C than those at global warming of 1.5°C (high confidence). Coral reefs, for example, are projected to decline by a further 70–90% at 1.5°C (high confidence) with larger losses (>99%) at 2°C (very high confidence). The risk of irreversible loss of many marine and coastal ecosystems increases with global warming, especially at 2°C or more (high confidence). {3.4.4, Box 3.4} 9 Consistent with earlier studies, illustrative numbers were adopted from one recent meta-study. 8 Summary for Policymakers B.4.3 The level of ocean acidification due to increasing CO2 concentrations associated with global warming of 1.5°C is projected to amplify the adverse effects of warming, and even further at 2°C, impacting the growth, development, calcification, survival, and thus abundance of a broad range of species, for example, from algae to fish (high confidence). {3.3.10, 3.4.4} B.4.4 Impacts of climate change in the ocean are increasing risks to fisheries and aquaculture via impacts on the physiology, SPM survivorship, habitat, reproduction, disease incidence, and risk of invasive species (medium confidence) but are projected to be less at 1.5°C of global warming than at 2°C. One global fishery model, for example, projected a decrease in global annual catch for marine fisheries of about 1.5 million tonnes for 1.5°C of global warming compared to a loss of more than 3 million tonnes for 2°C of global warming (medium confidence). {3.4.4, Box 3.4} B.5 Climate-related risks to health, livelihoods, food security, water supply, human security, and economic growth are projected to increase with global warming of 1.5°C and increase further with 2°C. (Figure SPM.2) {3.4, 3.5, 5.2, Box 3.2, Box 3.3, Box 3.5, Box 3.6, Cross-Chapter Box 6 in Chapter 3, Cross-Chapter Box 9 in Chapter 4, Cross-Chapter Box 12 in Chapter 5, 5.2} B.5.1 Populations at disproportionately higher risk of adverse consequences with global warming of 1.5°C and beyond include disadvantaged and vulnerable populations, some indigenous peoples, and local communities dependent on agricultural or coastal livelihoods (high confidence). Regions at disproportionately higher risk include Arctic ecosystems, dryland regions, small island developing states, and Least Developed Countries (high confidence). Poverty and disadvantage are expected to increase in some populations as global warming increases; limiting global warming to 1.5°C, compared with 2°C, could reduce the number of people both exposed to climate-related risks and susceptible to poverty by up to several hundred million by 2050 (medium confidence). {3.4.10, 3.4.11, Box 3.5, Cross-Chapter Box 6 in Chapter 3, Cross-Chapter Box 9 in Chapter 4, Cross-Chapter Box 12 in Chapter 5, 4.2.2.2, 5.2.1, 5.2.2, 5.2.3, 5.6.3} B.5.2 Any increase in global warming is projected to affect human health, with primarily negative consequences (high confidence). Lower risks are projected at 1.5°C than at 2°C for heat-related morbidity and mortality (very high confidence) and for ozone-related mortality if emissions needed for ozone formation remain high (high confidence). Urban heat islands often amplify the impacts of heatwaves in cities (high confidence). Risks from some vector-borne diseases, such as malaria and dengue fever, are projected to increase with warming from 1.5°C to 2°C, including potential shifts in their geographic range (high confidence). {3.4.7, 3.4.8, 3.5.5.8} B.5.3 Limiting warming to 1.5°C compared with 2°C is projected to result in smaller net reductions in yields of maize, rice, wheat, and potentially other cereal crops, particularly in sub-Saharan Africa, Southeast Asia, and Central and South America, and in the CO2-dependent nutritional quality of rice and wheat (high confidence). Reductions in projected food availability are larger at 2°C than at 1.5°C of global warming in the Sahel, southern Africa, the Mediterranean, central Europe, and the Amazon (medium confidence). Livestock are projected to be adversely affected with rising temperatures, depending on the extent of changes in feed quality, spread of diseases, and water resource availability (high confidence). {3.4.6, 3.5.4, 3.5.5, Box 3.1, Cross-Chapter Box 6 in Chapter 3, Cross-Chapter Box 9 in Chapter 4} B.5.4 Depending on future socio-economic conditions, limiting global warming to 1.5°C compared to 2°C may reduce the proportion of the world population exposed to a climate change-induced increase in water stress by up to 50%, although there is considerable variability between regions (medium confidence). Many small island developing states could experience lower water stress as a result of projected changes in aridity when global warming is limited to 1.5°C, as compared to 2°C (medium confidence). {3.3.5, 3.4.2, 3.4.8, 3.5.5, Box 3.2, Box 3.5, Cross-Chapter Box 9 in Chapter 4} B.5.5 Risks to global aggregated economic growth due to climate change impacts are projected to be lower at 1.5°C than at 2°C by the end of this century10 (medium confidence). This excludes the costs of mitigation, adaptation investments and the benefits of adaptation. Countries in the tropics and Southern Hemisphere subtropics are projected to experience the largest impacts on economic growth due to climate change should global warming increase from 1.5°C to 2°C (medium confidence). {3.5.2, 3.5.3} 10 Here, impacts on economic growth refer to changes in gross domestic product (GDP). Many impacts, such as loss of human lives, cultural heritage and ecosystem services, are difficult to value and monetize. 9 Summary for Policymakers B.5.6 Exposure to multiple and compound climate-related risks increases between 1.5°C and 2°C of global warming, with greater proportions of people both so exposed and susceptible to poverty in Africa and Asia (high confidence). For global warming from 1.5°C to 2°C, risks across energy, food, and water sectors could overlap spatially and temporally, creating new and exacerbating current hazards, exposures, and vulnerabilities that could affect increasing numbers of people and regions SPM (medium confidence). {Box 3.5, 3.3.1, 3.4.5.3, 3.4.5.6, 3.4.11, 3.5.4.9} B.5.7 There are multiple lines of evidence that since AR5 the assessed levels of risk increased for four of the five Reasons for Concern (RFCs) for global warming to 2°C (high confidence). The risk transitions by degrees of global warming are now: from high to very high risk between 1.5°C and 2°C for RFC1 (Unique and threatened systems) (high confidence); from moderate to high risk between 1°C and 1.5°C for RFC2 (Extreme weather events) (medium confidence); from moderate to high risk between 1.5°C and 2°C for RFC3 (Distribution of impacts) (high confidence); from moderate to high risk between 1.5°C and 2.5°C for RFC4 (Global aggregate impacts) (medium confidence); and from moderate to high risk between 1°C and 2.5°C for RFC5 (Large-scale singular events) (medium confidence). (Figure SPM.2) {3.4.13; 3.5, 3.5.2} B.6 Most adaptation needs will be lower for global warming of 1.5°C compared to 2°C (high confidence). There are a wide range of adaptation options that can reduce the risks of climate change (high confidence). There are limits to adaptation and adaptive capacity for some human and natural systems at global warming of 1.5°C, with associated losses (medium confidence). The number and availability of adaptation options vary by sector (medium confidence). {Table 3.5, 4.3, 4.5, Cross- Chapter Box 9 in Chapter 4, Cross-Chapter Box 12 in Chapter 5} B.6.1 A wide range of adaptation options are available to reduce the risks to natural and managed ecosystems (e.g., ecosystem- based adaptation, ecosystem restoration and avoided degradation and deforestation, biodiversity management, sustainable aquaculture, and local knowledge and indigenous knowledge), the risks of sea level rise (e.g., coastal defence and hardening), and the risks to health, livelihoods, food, water, and economic growth, especially in rural landscapes (e.g., efficient irrigation, social safety nets, disaster risk management, risk spreading and sharing, and community- based adaptation) and urban areas (e.g., green infrastructure, sustainable land use and planning, and sustainable water management) (medium confidence). {4.3.1, 4.3.2, 4.3.3, 4.3.5, 4.5.3, 4.5.4, 5.3.2, Box 4.2, Box 4.3, Box 4.6, Cross-Chapter Box 9 in Chapter 4}. B.6.2 Adaptation is expected to be more challenging for ecosystems, food and health systems at 2°C of global warming than for 1.5°C (medium confidence). Some vulnerable regions, including small islands and Least Developed Countries, are projected to experience high multiple interrelated climate risks even at global warming of 1.5°C (high confidence). {3.3.1, 3.4.5, Box 3.5, Table 3.5, Cross-Chapter Box 9 in Chapter 4, 5.6, Cross-Chapter Box 12 in Chapter 5, Box 5.3} B.6.3 Limits to adaptive capacity exist at 1.5°C of global warming, become more pronounced at higher levels of warming and vary by sector, with site-specific implications for vulnerable regions, ecosystems and human health (medium confidence). {Cross-Chapter Box 12 in Chapter 5, Box 3.5, Table 3.5} 10 Summary for Policymakers How the level of global warming affects impacts and/or risks associated with the Reasons for Concern (RFCs) and selected natural, managed and human systems Five Reasons For Concern (RFCs) illustrate the impacts and risks of SPM different levels of global warming for people, economies and ecosystems Purple indicates very high across sectors and regions. risks of severe impacts/risks and the presence of significant irreversibility or Impacts and risks associated with the Reasons for Concern (RFCs) the persistence of climate-related hazards, combined with limited Very high ability to adapt due to the 2.0 M nature of the hazard or H H M High impacts/risks. 1.5 H Red indicates severe and M M widespread impacts/risks. 1.0 M 2006-2015 Moderate Yellow indicates that H M-H impacts/risks are detectable H and attributable to climate Undetectable 0 change with at least medium RFC1 RFC2 RFC3 RFC4 RFC5 Level of additional confidence. Unique and Extreme Distribution Global Large scale impact/risk due White indicates that no to climate change threatened weather of impacts aggregate singular impacts are detectable and systems events impacts events attributable to climate change. Impacts and risks for selected natural, managed and human systems H M H 2.0 M M H H M 1.5 M 1.0 M MVH H 2006-2015 M H H H VH H HH H M 0 Warm-water Mangroves Small-scale Arctic Terrestrial Coastal Fluvial Crop Tourism Heat-related corals low-latitude region ecosystems flooding flooding yields morbidity fisheries and mortality Confidence level for transition: L=Low, M=Medium, H=High and VH=Very high Figure SPM.2 | Five integrative reasons for concern (RFCs) provide a framework for summarizing key impacts and risks across sectors and regions, and were introduced in the IPCC Third Assessment Report. RFCs illustrate the implications of global warming for people, economies and ecosystems. Impacts and/or risks for each RFC are based on assessment of the new literature that has appeared. As in AR5, this literature was used to make expert judgments to assess the levels of global warming at which levels of impact and/or risk are undetectable, moderate, high or very high. The selection of impacts and risks to natural, managed and human systems in the lower panel is illustrative and is not intended to be fully comprehensive. {3.4, 3.5, 3.5.2.1, 3.5.2.2, 3.5.2.3, 3.5.2.4, 3.5.2.5, 5.4.1, 5.5.3, 5.6.1, Box 3.4} RFC1 Unique and threatened systems: ecological and human systems that have restricted geographic ranges constrained by climate-related conditions and have high endemism or other distinctive properties. Examples include coral reefs, the Arctic and its indigenous people, mountain glaciers and biodiversity hotspots. RFC2 Extreme weather events: risks/impacts to human health, livelihoods, assets and ecosystems from extreme weather events such as heat waves, heavy rain, drought and associated wildfires, and coastal flooding. RFC3 Distribution of impacts: risks/impacts that disproportionately affect particular groups due to uneven distribution of physical climate change hazards, exposure or vulnerability. RFC4 Global aggregate impacts: global monetary damage, global-scale degradation and loss of ecosystems and biodiversity. R10F CHe5r eL, aimrpgaec-ts coan lec osnionmgiuc lgaror wetvh erenfetrs :t oa crhea rnegleast iivne glyro lsasr dgoem, aesbtricu prto aduncdt (sGoDmPe).t Mimaensy iimrrepavcetrss, isbulceh c ahsa lnosgse osf ihnu msyasnt elimvess , tchualttu raarle h ecraituasged a nbdy egcloosbysatle mw asermrviicnegs,. aErxea dmiffipcleulst i ncltuod vea ludeis ai ntde mgroanteiotinze o. f the Greenland and Antarctic ice sheets. 11 Global mean surface temperature change Global mean surface temperature change relative to pre-industrial levels (0C) relative to pre-industrial levels (0C) Summary for Policymakers C. Emission Pathways and System Transitions Consistent with 1.5°C Global Warming C.1 In model pathways with no or limited overshoot of 1.5°C, global net anthropogenic CO2 emissions SPM decline by about 45% from 2010 levels by 2030 (40–60% interquartile range), reaching net zero around 2050 (2045–2055 interquartile range). For limiting global warming to below 2°C11 CO2 emissions are projected to decline by about 25% by 2030 in most pathways (10–30% interquartile range) and reach net zero around 2070 (2065–2080 interquartile range). Non-CO2 emissions in pathways that limit global warming to 1.5°C show deep reductions that are similar to those in pathways limiting warming to 2°C. (high confidence) (Figure SPM.3a) {2.1, 2.3, Table 2.4} C.1.1 CO2 emissions reductions that limit global warming to 1.5°C with no or limited overshoot can involve different portfolios of mitigation measures, striking different balances between lowering energy and resource intensity, rate of decarbonization, and the reliance on carbon dioxide removal. Different portfolios face different implementation challenges and potential synergies and trade-offs with sustainable development. (high confidence) (Figure SPM.3b) {2.3.2, 2.3.4, 2.4, 2.5.3} C.1.2 Modelled pathways that limit global warming to 1.5°C with no or limited overshoot involve deep reductions in emissions of methane and black carbon (35% or more of both by 2050 relative to 2010). These pathways also reduce most of the cooling aerosols, which partially offsets mitigation effects for two to three decades. Non-CO2 emissions12 can be reduced as a result of broad mitigation measures in the energy sector. In addition, targeted non-CO2 mitigation measures can reduce nitrous oxide and methane from agriculture, methane from the waste sector, some sources of black carbon, and hydrofluorocarbons. High bioenergy demand can increase emissions of nitrous oxide in some 1.5°C pathways, highlighting the importance of appropriate management approaches. Improved air quality resulting from projected reductions in many non-CO2 emissions provide direct and immediate population health benefits in all 1.5°C model pathways. (high confidence) (Figure SPM.3a) {2.2.1, 2.3.3, 2.4.4, 2.5.3, 4.3.6, 5.4.2} C.1.3 Limiting global warming requires limiting the total cumulative global anthropogenic emissions of CO2 since the pre- industrial period, that is, staying within a total carbon budget (high confidence).13 By the end of 2017, anthropogenic CO2 emissions since the pre-industrial period are estimated to have reduced the total carbon budget for 1.5°C by approximately 2200 ± 320 GtCO2 (medium confidence). The associated remaining budget is being depleted by current emissions of 42 ± 3 GtCO2 per year (high confidence). The choice of the measure of global temperature affects the estimated remaining carbon budget. Using global mean surface air temperature, as in AR5, gives an estimate of the remaining carbon budget of 580 GtCO2 for a 50% probability of limiting warming to 1.5°C, and 420 GtCO2 for a 66% probability (medium confidence).14 Alternatively, using GMST gives estimates of 770 and 570 GtCO2, for 50% and 66% probabilities,15 respectively (medium confidence). Uncertainties in the size of these estimated remaining carbon budgets are substantial and depend on several factors. Uncertainties in the climate response to CO2 and non-CO2 emissions contribute ±400 GtCO2 and the level of historic warming contributes ±250 GtCO2 (medium confidence). Potential additional carbon release from future permafrost thawing and methane release from wetlands would reduce budgets by up to 100 GtCO2 over the course of this century and more thereafter (medium confidence). In addition, the level of non-CO2 mitigation in the future could alter the remaining carbon budget by 250 GtCO2 in either direction (medium confidence). {1.2.4, 2.2.2, 2.6.1, Table 2.2, Chapter 2 Supplementary Material} C.1.4 Solar radiation modification (SRM) measures are not included in any of the available assessed pathways. Although some SRM measures may be theoretically effective in reducing an overshoot, they face large uncertainties and knowledge gaps 11 References to pathways limiting global warming to 2°C are based on a 66% probability of staying below 2°C. 12 Non-CO2 emissions included in this Report are all anthropogenic emissions other than CO2 that result in radiative forcing. These include short-lived climate forcers, such as methane, some fluorinated gases, ozone precursors, aerosols or aerosol precursors, such as black carbon and sulphur dioxide, respectively, as well as long-lived greenhouse gases, such as nitrous oxide or some fluorinated gases. The radiative forcing associated with non-CO2 emissions and changes in surface albedo is referred to as non-CO2 radiative forcing. {2.2.1} 13 There is a clear scientific basis for a total carbon budget consistent with limiting global warming to 1.5°C. However, neither this total carbon budget nor the fraction of this budget taken up by past emissions were assessed in this Report. 14 Irrespective of the measure of global temperature used, updated understanding and further advances in methods have led to an increase in the estimated remaining carbon budget of about 300 GtCO2 compared to AR5. (medium confidence) {2.2.2} 15 These estimates use observed GMST to 2006–2015 and estimate future temperature changes using near surface air temperatures. 12 Summary for Policymakers as well as substantial risks and institutional and social constraints to deployment related to governance, ethics, and impacts on sustainable development. They also do not mitigate ocean acidification. (medium confidence) {4.3.8, Cross-Chapter Box 10 in Chapter 4} SPM Global emissions pathway characteristics General characteristics of the evolution of anthropogenic net emissions of CO2, and total emissions of methane, black carbon, and nitrous oxide in model pathways that limit global warming to 1.5°C with no or limited overshoot. Net emissions are defined as anthropogenic emissions reduced by anthropogenic removals. Reductions in net emissions can be achieved through dierent portfolios of mitigation measures illustrated in Figure SPM.3b. Non-CO2 emissions relative to 2010 Global total net CO2 emissions Emissions of non-CO2 forcers are also reduced or limited in pathways limiting global warming Billion tonnes of CO2/yr to 1.5°C with no or limited overshoot, but 50 they do not reach zero globally. Methane emissions 40 In pathways limiting global warming to 1.5°C 1 with no or limited overshoot as well as in pathways with a higher overshoot, CO2 emissions 30 are reduced to net zero globally around 2050. 0 2020 2040 2060 2080 2100 20 Black carbon emissions 1 10 Four illustrative model pathways 0 0 2020 2040 2060 2080 2100 P1 P2 Nitrous oxide emissions -10 P3 1 -20 P4 0 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 2020 2040 2060 2080 2100 Timing of net zero CO2 Pathways limiting global warming to 1.5°C with no or limited overshoot Line widths depict the 5-95th Pathways with higher overshoot percentile and the 25-75th Pathways limiting global warming below 2°C percentile of scenarios (Not shown above) Figure SPM.3a | Global emissions pathway characteristics. The main panel shows global net anthropogenic CO2 emissions in pathways limiting global warming to 1.5°C with no or limited (less than 0.1°C) overshoot and pathways with higher overshoot. The shaded area shows the full range for pathways analysed in this Report. The panels on the right show non-CO2 emissions ranges for three compounds with large historical forcing and a substantial portion of emissions coming from sources distinct from those central to CO2 mitigation. Shaded areas in these panels show the 5–95% (light shading) and interquartile (dark shading) ranges of pathways limiting global warming to 1.5°C with no or limited overshoot. Box and whiskers at the bottom of the figure show the timing of pathways reaching global net zero CO2 emission levels, and a comparison with pathways limiting global warming to 2°C with at least 66% probability. Four illustrative model pathways are highlighted in the main panel and are labelled P1, P2, P3 and P4, corresponding to the LED, S1, S2, and S5 pathways assessed in Chapter 2. Descriptions and characteristics of these pathways are available in Figure SPM.3b. {2.1, 2.2, 2.3, Figure 2.5, Figure 2.10, Figure 2.11} 13 Summary for Policymakers Characteristics of four illustrative model pathways Different mitigation strategies can achieve the net emissions reductions that would be required to follow a pathway that limits global warming to 1.5°C with no or limited overshoot. All pathways use Carbon Dioxide Removal (CDR), but the amount varies across pathways, as do the relative contributions of Bioenergy with SPM Carbon Capture and Storage (BECCS) and removals in the Agriculture, Forestry and Other Land Use (AFOLU) sector. This has implications for emissions and several other pathway characteristics. Breakdown of contributions to global net CO2 emissions in four illustrative model pathways Fossil fuel and industry AFOLU BECCS Billion tonnes CO₂ per year (GtCO2/yr) Billion tonnes CO₂ per year (GtCO2/yr) Billion tonnes CO₂ per year (GtCO2/yr) Billion tonnes CO₂ per year (GtCO2/yr) 40 P1 40 P2 40 P3 40 P4 20 20 20 20 0 0 0 0 -20 -20 -20 -20 2020 2060 2100 2020 2060 2100 2020 2060 2100 2020 2060 2100 P1: A scenario in which social, P2: A scenario with a broad focus on P3: A middle-of-the-road scenario in P4: A resource- and energy-intensive business and technological innovations sustainability including energy which societal as well as technological scenario in which economic growth and result in lower energy demand up to intensity, human development, development follows historical globalization lead to widespread 2050 while living standards rise, economic convergence and patterns. Emissions reductions are adoption of greenhouse-gas-intensive especially in the global South. A international cooperation, as well as mainly achieved by changing the way in lifestyles, including high demand for downsized energy system enables shi‚s towards sustainable and healthy which energy and products are transportation fuels and livestock rapid decarbonization of energy supply. consumption patterns, low-carbon produced, and to a lesser degree by products. Emissions reductions are Afforestation is the only CDR option technology innovation, and reductions in demand. mainly achieved through technological considered; neither fossil fuels with CCS well-managed land systems with means, making strong use of CDR nor BECCS are used. limited societal acceptability for BECCS. through the deployment of BECCS. Global indicators P1 P2 P3 P4 Interquartile range Pathway classification No or limited overshoot No or limited overshoot No or limited overshoot Higher overshoot No or limited overshoot CO2 emission change in 2030 (% rel to 2010) -58 -47 -41 4 (-58,-40) in 2050 (% rel to 2010) -93 -95 -91 -97 (-107,-94) Kyoto-GHG emissions* in 2030 (% rel to 2010) -50 -49 -35 -2 (-51,-39) in 2050 (% rel to 2010) -82 -89 -78 -80 (-93,-81) Final energy demand** in 2030 (% rel to 2010) -15 -5 17 39 (-12,7) in 2050 (% rel to 2010) -32 2 21 44 (-11,22) Renewable share in electricity in 2030 (%) 60 58 48 25 (47,65) in 2050 (%) 77 81 63 70 (69,86) Primary energy from coal in 2030 (% rel to 2010) -78 -61 -75 -59 (-78, -59) in 2050 (% rel to 2010) -97 -77 -73 -97 (-95, -74) from oil in 2030 (% rel to 2010) -37 -13 -3 86 (-34,3) in 2050 (% rel to 2010) -87 -50 -81 -32 (-78,-31) from gas in 2030 (% rel to 2010) -25 -20 33 37 (-26,21) in 2050 (% rel to 2010) -74 -53 21 -48 (-56,6) from nuclear in 2030 (% rel to 2010) 59 83 98 106 (44,102) in 2050 (% rel to 2010) 150 98 501 468 (91,190) from biomass in 2030 (% rel to 2010) -11 0 36 -1 (29,80) in 2050 (% rel to 2010) -16 49 121 418 (123,261) from non-biomass renewables in 2030 (% rel to 2010) 430 470 315 110 (245,436) in 2050 (% rel to 2010) 833 1327 878 1137 (576,1299) Cumulative CCS until 2100 (GtCO2) 0 348 687 1218 (550,1017) of which BECCS (GtCO2) 0 151 414 1191 (364,662) Land area of bioenergy crops in 2050 (million km2) 0.2 0.9 2.8 7.2 (1.5,3.2) Agricultural CH4 emissions in 2030 (% rel to 2010) -24 -48 1 14 (-30,-11) in 2050 (% rel to 2010) -33 -69 -23 2 (-47,-24) Agricultural N2O emissions in 2030 (% rel to 2010) 5 -26 15 3 (-21,3) in 2050 (% rel to 2010) 6 -26 0 39 (-26,1) NOTE: Indicators have been selected to show global trends identified by the Chapter 2 assessment. * Kyoto-gas emissions are based on IPCC Second Assessment Report GWP-100 National and sectoral characteristics can differ substantially from the global trends shown above. ** Changes in energy demand are associated with improvements in energy efficiency and behaviour change 14 Summary for Policymakers Figure SPM.3b | Characteristics of four illustrative model pathways in relation to global warming of 1.5°C introduced in Figure SPM.3a. These pathways were selected to show a range of potential mitigation approaches and vary widely in their projected energy and land use, as well as their assumptions about future socio-economic developments, including economic and population growth, equity and sustainability. A breakdown of the global net anthropogenic CO2 emissions into the contributions in terms of CO2 emissions from fossil fuel and industry; agriculture, forestry and other land use (AFOLU); and bioenergy with carbon capture and storage (BECCS) is shown. AFOLU estimates reported here are not necessarily comparable with countries’ estimates. Further characteristics for each of these pathways are listed below each pathway. These pathways illustrate relative global differences in mitigation strategies, but do not represent central estimates, national strategies, and do not indicate requirements. For comparison, the right-most column shows the interquartile ranges across pathways with no or limited SPM overshoot of 1.5°C. Pathways P1, P2, P3 and P4 correspond to the LED, S1, S2 and S5 pathways assessed in Chapter 2 (Figure SPM.3a). {2.2.1, 2.3.1, 2.3.2, 2.3.3, 2.3.4, 2.4.1, 2.4.2, 2.4.4, 2.5.3, Figure 2.5, Figure 2.6, Figure 2.9, Figure 2.10, Figure 2.11, Figure 2.14, Figure 2.15, Figure 2.16, Figure 2.17, Figure 2.24, Figure 2.25, Table 2.4, Table 2.6, Table 2.7, Table 2.9, Table 4.1} C.2 Pathways limiting global warming to 1.5°C with no or limited overshoot would require rapid and far-reaching transitions in energy, land, urban and infrastructure (including transport and buildings), and industrial systems (high confidence). These systems transitions are unprecedented in terms of scale, but not necessarily in terms of speed, and imply deep emissions reductions in all sectors, a wide portfolio of mitigation options and a significant upscaling of investments in those options (medium confidence). {2.3, 2.4, 2.5, 4.2, 4.3, 4.4, 4.5} C.2.1 Pathways that limit global warming to 1.5°C with no or limited overshoot show system changes that are more rapid and pronounced over the next two decades than in 2°C pathways (high confidence). The rates of system changes associated with limiting global warming to 1.5°C with no or limited overshoot have occurred in the past within specific sectors, technologies and spatial contexts, but there is no documented historic precedent for their scale (medium confidence). {2.3.3, 2.3.4, 2.4, 2.5, 4.2.1, 4.2.2, Cross-Chapter Box 11 in Chapter 4} C.2.2 In energy systems, modelled global pathways (considered in the literature) limiting global warming to 1.5°C with no or limited overshoot (for more details see Figure SPM.3b) generally meet energy service demand with lower energy use, including through enhanced energy efficiency, and show faster electrification of energy end use compared to 2°C (high confidence). In 1.5°C pathways with no or limited overshoot, low-emission energy sources are projected to have a higher share, compared with 2°C pathways, particularly before 2050 (high confidence). In 1.5°C pathways with no or limited overshoot, renewables are projected to supply 70–85% (interquartile range) of electricity in 2050 (high confidence). In electricity generation, shares of nuclear and fossil fuels with carbon dioxide capture and storage (CCS) are modelled to increase in most 1.5°C pathways with no or limited overshoot. In modelled 1.5°C pathways with limited or no overshoot, the use of CCS would allow the electricity generation share of gas to be approximately 8% (3–11% interquartile range) of global electricity in 2050, while the use of coal shows a steep reduction in all pathways and would be reduced to close to 0% (0–2% interquartile range) of electricity (high confidence). While acknowledging the challenges, and differences between the options and national circumstances, political, economic, social and technical feasibility of solar energy, wind energy and electricity storage technologies have substantially improved over the past few years (high confidence). These improvements signal a potential system transition in electricity generation. (Figure SPM.3b) {2.4.1, 2.4.2, Figure 2.1, Table 2.6, Table 2.7, Cross-Chapter Box 6 in Chapter 3, 4.2.1, 4.3.1, 4.3.3, 4.5.2} C.2.3 CO2 emissions from industry in pathways limiting global warming to 1.5°C with no or limited overshoot are projected to be about 65–90% (interquartile range) lower in 2050 relative to 2010, as compared to 50–80% for global warming of 2°C (medium confidence). Such reductions can be achieved through combinations of new and existing technologies and practices, including electrification, hydrogen, sustainable bio-based feedstocks, product substitution, and carbon capture, utilization and storage (CCUS). These options are technically proven at various scales but their large-scale deployment may be limited by economic, financial, human capacity and institutional constraints in specific contexts, and specific characteristics of large-scale industrial installations. In industry, emissions reductions by energy and process efficiency by themselves are insufficient for limiting warming to 1.5°C with no or limited overshoot (high confidence). {2.4.3, 4.2.1, Table 4.1, Table 4.3, 4.3.3, 4.3.4, 4.5.2} C.2.4 The urban and infrastructure system transition consistent with limiting global warming to 1.5°C with no or limited overshoot would imply, for example, changes in land and urban planning practices, as well as deeper emissions reductions in transport and buildings compared to pathways that limit global warming below 2°C (medium confidence). Technical measures 15 Summary for Policymakers and practices enabling deep emissions reductions include various energy efficiency options. In pathways limiting global warming to 1.5°C with no or limited overshoot, the electricity share of energy demand in buildings would be about 55–75% in 2050 compared to 50–70% in 2050 for 2°C global warming (medium confidence). In the transport sector, the share of low-emission final energy would rise from less than 5% in 2020 to about 35–65% in 2050 compared to 25–45% for 2°C SPM of global warming (medium confidence). Economic, institutional and socio-cultural barriers may inhibit these urban and infrastructure system transitions, depending on national, regional and local circumstances, capabilities and the availability of capital (high confidence). {2.3.4, 2.4.3, 4.2.1, Table 4.1, 4.3.3, 4.5.2} C.2.5 Transitions in global and regional land use are found in all pathways limiting global warming to 1.5°C with no or limited overshoot, but their scale depends on the pursued mitigation portfolio. Model pathways that limit global warming to 1.5°C with no or limited overshoot project a 4 million km2 reduction to a 2.5 million km2 increase of non-pasture agricultural land for food and feed crops and a 0.5–11 million km2 reduction of pasture land, to be converted into a 0–6 million km2 increase of agricultural land for energy crops and a 2 million km2 reduction to 9.5 million km2 increase in forests by 2050 relative to 2010 (medium confidence).16 Land-use transitions of similar magnitude can be observed in modelled 2°C pathways (medium confidence). Such large transitions pose profound challenges for sustainable management of the various demands on land for human settlements, food, livestock feed, fibre, bioenergy, carbon storage, biodiversity and other ecosystem services (high confidence). Mitigation options limiting the demand for land include sustainable intensification of land-use practices, ecosystem restoration and changes towards less resource-intensive diets (high confidence). The implementation of land-based mitigation options would require overcoming socio-economic, institutional, technological, financing and environmental barriers that differ across regions (high confidence). {2.4.4, Figure 2.24, 4.3.2, 4.3.7, 4.5.2, Cross-Chapter Box 7 in Chapter 3} C.2.6 Additional annual average energy-related investments for the period 2016 to 2050 in pathways limiting warming to 1.5°C compared to pathways without new climate policies beyond those in place today are estimated to be around 830 billion USD2010 (range of 150 billion to 1700 billion USD2010 across six models17). This compares to total annual average energy supply investments in 1.5°C pathways of 1460 to 3510 billion USD2010 and total annual average energy demand investments of 640 to 910 billion USD2010 for the period 2016 to 2050. Total energy-related investments increase by about 12% (range of 3% to 24%) in 1.5°C pathways relative to 2°C pathways. Annual investments in low-carbon energy technologies and energy efficiency are upscaled by roughly a factor of six (range of factor of 4 to 10) by 2050 compared to 2015 (medium confidence). {2.5.2, Box 4.8, Figure 2.27} C.2.7 Modelled pathways limiting global warming to 1.5°C with no or limited overshoot project a wide range of global average discounted marginal abatement costs over the 21st century. They are roughly 3-4 times higher than in pathways limiting global warming to below 2°C (high confidence). The economic literature distinguishes marginal abatement costs from total mitigation costs in the economy. The literature on total mitigation costs of 1.5°C mitigation pathways is limited and was not assessed in this Report. Knowledge gaps remain in the integrated assessment of the economy-wide costs and benefits of mitigation in line with pathways limiting warming to 1.5°C. {2.5.2; 2.6; Figure 2.26} 16 The projected land-use changes presented are not deployed to their upper limits simultaneously in a single pathway. 17 Including two pathways limiting warming to 1.5°C with no or limited overshoot and four pathways with higher overshoot. 16 Summary for Policymakers C.3 All pathways that limit global warming to 1.5°C with limited or no overshoot project the use of carbon dioxide removal (CDR) on the order of 100–1000 GtCO2 over the 21st century. CDR would be used to compensate for residual emissions and, in most cases, achieve net negative emissions to return global warming to 1.5°C following a peak (high confidence). CDR deployment of several hundreds of GtCO2 is subject to multiple feasibility and sustainability constraints (high confidence). Significant near-term emissions reductions and measures to lower energy and land demand can SPM limit CDR deployment to a few hundred GtCO2 without reliance on bioenergy with carbon capture and storage (BECCS) (high confidence). {2.3, 2.4, 3.6.2, 4.3, 5.4} C.3.1 Existing and potential CDR measures include afforestation and reforestation, land restoration and soil carbon sequestration, BECCS, direct air carbon capture and storage (DACCS), enhanced weathering and ocean alkalinization. These differ widely in terms of maturity, potentials, costs, risks, co-benefits and trade-offs (high confidence). To date, only a few published pathways include CDR measures other than afforestation and BECCS. {2.3.4, 3.6.2, 4.3.2, 4.3.7} C.3.2 In pathways limiting global warming to 1.5°C with limited or no overshoot, BECCS deployment is projected to range from 0–1, 0–8, and 0–16 GtCO yr−12 in 2030, 2050, and 2100, respectively, while agriculture, forestry and land-use (AFOLU) related CDR measures are projected to remove 0–5, 1–11, and 1–5 GtCO2 yr−1 in these years (medium confidence). The upper end of these deployment ranges by mid-century exceeds the BECCS potential of up to 5 GtCO2 yr−1 and afforestation potential of up to 3.6 GtCO yr−12 assessed based on recent literature (medium confidence). Some pathways avoid BECCS deployment completely through demand-side measures and greater reliance on AFOLU-related CDR measures (medium confidence). The use of bioenergy can be as high or even higher when BECCS is excluded compared to when it is included due to its potential for replacing fossil fuels across sectors (high confidence). (Figure SPM.3b) {2.3.3, 2.3.4, 2.4.2, 3.6.2, 4.3.1, 4.2.3, 4.3.2, 4.3.7, 4.4.3, Table 2.4} C.3.3 Pathways that overshoot 1.5°C of global warming rely on CDR exceeding residual CO2 emissions later in the century to return to below 1.5°C by 2100, with larger overshoots requiring greater amounts of CDR (Figure SPM.3b) (high confidence). Limitations on the speed, scale, and societal acceptability of CDR deployment hence determine the ability to return global warming to below 1.5°C following an overshoot. Carbon cycle and climate system understanding is still limited about the effectiveness of net negative emissions to reduce temperatures after they peak (high confidence). {2.2, 2.3.4, 2.3.5, 2.6, 4.3.7, 4.5.2, Table 4.11} C.3.4 Most current and potential CDR measures could have significant impacts on land, energy, water or nutrients if deployed at large scale (high confidence). Afforestation and bioenergy may compete with other land uses and may have significant impacts on agricultural and food systems, biodiversity, and other ecosystem functions and services (high confidence). Effective governance is needed to limit such trade-offs and ensure permanence of carbon removal in terrestrial, geological and ocean reservoirs (high confidence). Feasibility and sustainability of CDR use could be enhanced by a portfolio of options deployed at substantial, but lesser scales, rather than a single option at very large scale (high confidence). (Figure SPM.3b) {2.3.4, 2.4.4, 2.5.3, 2.6, 3.6.2, 4.3.2, 4.3.7, 4.5.2, 5.4.1, 5.4.2; Cross-Chapter Boxes 7 and 8 in Chapter 3, Table 4.11, Table 5.3, Figure 5.3} C.3.5 Some AFOLU-related CDR measures such as restoration of natural ecosystems and soil carbon sequestration could provide co-benefits such as improved biodiversity, soil quality, and local food security. If deployed at large scale, they would require governance systems enabling sustainable land management to conserve and protect land carbon stocks and other ecosystem functions and services (medium confidence). (Figure SPM.4) {2.3.3, 2.3.4, 2.4.2, 2.4.4, 3.6.2, 5.4.1, Cross-Chapter Boxes 3 in Chapter 1 and 7 in Chapter 3, 4.3.2, 4.3.7, 4.4.1, 4.5.2, Table 2.4} 17 Summary for Policymakers D. Strengthening the Global Response in the Context of Sustainable Development and Efforts to Eradicate Poverty D.1 Estimates of the global emissions outcome of current nationally stated mitigation ambitions as SPM submitted under the Paris Agreement would lead to global greenhouse gas emissions18 in 2030 of 52–58 GtCO eq yr−12 (medium confidence). Pathways reflecting these ambitions would not limit global warming to 1.5°C, even if supplemented by very challenging increases in the scale and ambition of emissions reductions after 2030 (high confidence). Avoiding overshoot and reliance on future large-scale deployment of carbon dioxide removal (CDR) can only be achieved if global CO2 emissions start to decline well before 2030 (high confidence). {1.2, 2.3, 3.3, 3.4, 4.2, 4.4, Cross- Chapter Box 11 in Chapter 4} D.1.1 Pathways that limit global warming to 1.5°C with no or limited overshoot show clear emission reductions by 2030 (high confidence). All but one show a decline in global greenhouse gas emissions to below 35 GtCO2eq yr−1 in 2030, and half of available pathways fall within the 25–30 GtCO2eq yr−1 range (interquartile range), a 40–50% reduction from 2010 levels (high confidence). Pathways reflecting current nationally stated mitigation ambition until 2030 are broadly consistent with cost-effective pathways that result in a global warming of about 3°C by 2100, with warming continuing afterwards (medium confidence). {2.3.3, 2.3.5, Cross-Chapter Box 11 in Chapter 4, 5.5.3.2} D.1.2 Overshoot trajectories result in higher impacts and associated challenges compared to pathways that limit global warming to 1.5°C with no or limited overshoot (high confidence). Reversing warming after an overshoot of 0.2°C or larger during this century would require upscaling and deployment of CDR at rates and volumes that might not be achievable given considerable implementation challenges (medium confidence). {1.3.3, 2.3.4, 2.3.5, 2.5.1, 3.3, 4.3.7, Cross-Chapter Box 8 in Chapter 3, Cross-Chapter Box 11 in Chapter 4} D.1.3 The lower the emissions in 2030, the lower the challenge in limiting global warming to 1.5°C after 2030 with no or limited overshoot (high confidence). The challenges from delayed actions to reduce greenhouse gas emissions include the risk of cost escalation, lock-in in carbon-emitting infrastructure, stranded assets, and reduced flexibility in future response options in the medium to long term (high confidence). These may increase uneven distributional impacts between countries at different stages of development (medium confidence). {2.3.5, 4.4.5, 5.4.2} D.2 The avoided climate change impacts on sustainable development, eradication of poverty and reducing inequalities would be greater if global warming were limited to 1.5°C rather than 2°C, if mitigation and adaptation synergies are maximized while trade-offs are minimized (high confidence). {1.1, 1.4, 2.5, 3.3, 3.4, 5.2, Table 5.1} D.2.1 Climate change impacts and responses are closely linked to sustainable development which balances social well-being, economic prosperity and environmental protection. The United Nations Sustainable Development Goals (SDGs), adopted in 2015, provide an established framework for assessing the links between global warming of 1.5°C or 2°C and development goals that include poverty eradication, reducing inequalities, and climate action. (high confidence) {Cross-Chapter Box 4 in Chapter 1, 1.4, 5.1} D.2.2 The consideration of ethics and equity can help address the uneven distribution of adverse impacts associated with 1.5°C and higher levels of global warming, as well as those from mitigation and adaptation, particularly for poor and disadvantaged populations, in all societies (high confidence). {1.1.1, 1.1.2, 1.4.3, 2.5.3, 3.4.10, 5.1, 5.2, 5.3. 5.4, Cross- Chapter Box 4 in Chapter 1, Cross-Chapter Boxes 6 and 8 in Chapter 3, and Cross-Chapter Box 12 in Chapter 5} D.2.3 Mitigation and adaptation consistent with limiting global warming to 1.5°C are underpinned by enabling conditions, assessed in this Report across the geophysical, environmental-ecological, technological, economic, socio-cultural and institutional 18 GHG emissions have been aggregated with 100-year GWP values as introduced in the IPCC Second Assessment Report. 18 Summary for Policymakers dimensions of feasibility. Strengthened multilevel governance, institutional capacity, policy instruments, technological innovation and transfer and mobilization of finance, and changes in human behaviour and lifestyles are enabling conditions that enhance the feasibility of mitigation and adaptation options for 1.5°C-consistent systems transitions. (high confidence) {1.4, Cross-Chapter Box 3 in Chapter 1, 2.5.1, 4.4, 4.5, 5.6} SPM D.3 Adaptation options specific to national contexts, if carefully selected together with enabling conditions, will have benefits for sustainable development and poverty reduction with global warming of 1.5°C, although trade-offs are possible (high confidence). {1.4, 4.3, 4.5} D.3.1 Adaptation options that reduce the vulnerability of human and natural systems have many synergies with sustainable development, if well managed, such as ensuring food and water security, reducing disaster risks, improving health conditions, maintaining ecosystem services and reducing poverty and inequality (high confidence). Increasing investment in physical and social infrastructure is a key enabling condition to enhance the resilience and the adaptive capacities of societies. These benefits can occur in most regions with adaptation to 1.5°C of global warming (high confidence). {1.4.3, 4.2.2, 4.3.1, 4.3.2, 4.3.3, 4.3.5, 4.4.1, 4.4.3, 4.5.3, 5.3.1, 5.3.2} D.3.2 Adaptation to 1.5°C global warming can also result in trade-offs or maladaptations with adverse impacts for sustainable development. For example, if poorly designed or implemented, adaptation projects in a range of sectors can increase greenhouse gas emissions and water use, increase gender and social inequality, undermine health conditions, and encroach on natural ecosystems (high confidence). These trade-offs can be reduced by adaptations that include attention to poverty and sustainable development (high confidence). {4.3.2, 4.3.3, 4.5.4, 5.3.2; Cross-Chapter Boxes 6 and 7 in Chapter 3} D.3.3 A mix of adaptation and mitigation options to limit global warming to 1.5°C, implemented in a participatory and integrated manner, can enable rapid, systemic transitions in urban and rural areas (high confidence). These are most effective when aligned with economic and sustainable development, and when local and regional governments and decision makers are supported by national governments (medium confidence). {4.3.2, 4.3.3, 4.4.1, 4.4.2} D.3.4 Adaptation options that also mitigate emissions can provide synergies and cost savings in most sectors and system transitions, such as when land management reduces emissions and disaster risk, or when low-carbon buildings are also designed for efficient cooling. Trade-offs between mitigation and adaptation, when limiting global warming to 1.5°C, such as when bioenergy crops, reforestation or afforestation encroach on land needed for agricultural adaptation, can undermine food security, livelihoods, ecosystem functions and services and other aspects of sustainable development. (high confidence) {3.4.3, 4.3.2, 4.3.4, 4.4.1, 4.5.2, 4.5.3, 4.5.4} D.4 Mitigation options consistent with 1.5°C pathways are associated with multiple synergies and trade- offs across the Sustainable Development Goals (SDGs). While the total number of possible synergies exceeds the number of trade-offs, their net effect will depend on the pace and magnitude of changes, the composition of the mitigation portfolio and the management of the transition. (high confidence) (Figure SPM.4) {2.5, 4.5, 5.4} D.4.1 1.5°C pathways have robust synergies particularly for the SDGs 3 (health), 7 (clean energy), 11 (cities and communities), 12 (responsible consumption and production) and 14 (oceans) (very high confidence). Some 1.5°C pathways show potential trade-offs with mitigation for SDGs 1 (poverty), 2 (hunger), 6 (water) and 7 (energy access), if not managed carefully (high confidence). (Figure SPM.4) {5.4.2; Figure 5.4, Cross-Chapter Boxes 7 and 8 in Chapter 3} D.4.2 1.5°C pathways that include low energy demand (e.g., see P1 in Figure SPM.3a and SPM.3b), low material consumption, and low GHG-intensive food consumption have the most pronounced synergies and the lowest number of trade-offs with respect to sustainable development and the SDGs (high confidence). Such pathways would reduce dependence on CDR. In modelled pathways, sustainable development, eradicating poverty and reducing inequality can support limiting warming to 1.5°C (high confidence). (Figure SPM.3b, Figure SPM.4) {2.4.3, 2.5.1, 2.5.3, Figure 2.4, Figure 2.28, 5.4.1, 5.4.2, Figure 5.4} 19 Summary for Policymakers Indicative linkages between mitigation options and sustainable development using SDGs (The linkages do not show costs and benefits) Mitigation options deployed in each sector can be associated with potential positive effects (synergies) or negative effects (trade-offs) with the Sustainable Development Goals (SDGs). The degree to which this SPM potential is realized will depend on the selected portfolio of mitigation options, mitigation policy design, and local circumstances and context. Particularly in the energy-demand sector, the potential for synergies is larger than for trade-offs. The bars group individually assessed options by level of confidence and take into account the relative strength of the assessed mitigation-SDG connections. Length shows strength of connection Shades show level of confidence The overall size of the coloured bars depict the relative The shades depict the level of confidence of the potential for synergies and trade-offs between the sectoral assessed potential for Trade-offs/Synergies. mitigation options and the SDGs. Very High Low Energy Supply Energy Demand Land Trade-offs Synergies Trade-offs Synergies Trade-offs Synergies NO POVERTY SDG1 No Poverty ZERO HUNGER SDG2 Zero Hunger GOOD HEALTH SDG 3 AND WELL-BEING Good Health and Well-being QUALITY SDG 4 EDUCATION Quality Education GENDER SDG 5 EQUALITY Gender Equality CLEAN WATER SDG 6 AND SANITATION Clean Water and Sanitation AFFORDABLE AND SDG 7 CLEAN ENERGY Affordable and Clean Energy SDG 8 DECENT WORK AND ECONOMIC GROWTH Decent Work and Economic Growth SDG 9 INDUSTRY, INNOVATION AND INFRASTRUCTURE Industry, Innovation and Infrastructure REDUCED SDG 10 INEQUALITIES Reduced Inequalities SDG 11 SUSTAINABLE CITIES AND COMMUNITIES Sustainable Cities and Communities SDG 12 RESPONSIBLE CONSUMPTION Responsible AND PRODUCTION Consumption and Production LIFE SDG 14 BELOW WATER Life Below Water LIFE ON LAND SDG 15 Life on Land SDG 16 PEACE, JUSTICEAND STRONG Peace, Justice INSTITUTIONS and Strong Institutions PARTNERSHIPS SDG 17 FOR THE GOALS Partnerships for the Goals 20 Summary for Policymakers Figure SPM.4 | Potential synergies and trade-offs between the sectoral portfolio of climate change mitigation options and the Sustainable Development Goals (SDGs). The SDGs serve as an analytical framework for the assessment of the different sustainable development dimensions, which extend beyond the time frame of the 2030 SDG targets. The assessment is based on literature on mitigation options that are considered relevant for 1.5°C. The assessed strength of the SDG interactions is based on the qualitative and quantitative assessment of individual mitigation options listed in Table 5.2. For each mitigation option, the strength of the SDG-connection as well as the associated confidence of the underlying literature (shades of green and red) was assessed. The strength of positive connections (synergies) and negative connections (trade-offs) across all individual options within a sector (see Table 5.2) are aggregated into sectoral potentials for the whole mitigation portfolio. The (white) areas outside the bars, which indicate no interactions, have low confidence due to the uncertainty and limited number of studies SPM exploring indirect effects. The strength of the connection considers only the effect of mitigation and does not include benefits of avoided impacts. SDG 13 (climate action) is not listed because mitigation is being considered in terms of interactions with SDGs and not vice versa. The bars denote the strength of the connection, and do not consider the strength of the impact on the SDGs. The energy demand sector comprises behavioural responses, fuel switching and efficiency options in the transport, industry and building sector as well as carbon capture options in the industry sector. Options assessed in the energy supply sector comprise biomass and non-biomass renewables, nuclear, carbon capture and storage (CCS) with bioenergy, and CCS with fossil fuels. Options in the land sector comprise agricultural and forest options, sustainable diets and reduced food waste, soil sequestration, livestock and manure management, reduced deforestation, afforestation and reforestation, and responsible sourcing. In addition to this figure, options in the ocean sector are discussed in the underlying report. {5.4, Table 5.2, Figure 5.2} Information about the net impacts of mitigation on sustainable development in 1.5°C pathways is available only for a limited number of SDGs and mitigation options. Only a limited number of studies have assessed the benefits of avoided climate change impacts of 1.5°C pathways for the SDGs, and the co-effects of adaptation for mitigation and the SDGs. The assessment of the indicative mitigation potentials in Figure SPM.4 is a step further from AR5 towards a more comprehensive and integrated assessment in the future. D.4.3 1.5°C and 2°C modelled pathways often rely on the deployment of large-scale land-related measures like afforestation and bioenergy supply, which, if poorly managed, can compete with food production and hence raise food security concerns (high confidence). The impacts of carbon dioxide removal (CDR) options on SDGs depend on the type of options and the scale of deployment (high confidence). If poorly implemented, CDR options such as BECCS and AFOLU options would lead to trade-offs. Context-relevant design and implementation requires considering people’s needs, biodiversity, and other sustainable development dimensions (very high confidence). (Figure SPM.4) {5.4.1.3, Cross-Chapter Box 7 in Chapter 3} D.4.4 Mitigation consistent with 1.5°C pathways creates risks for sustainable development in regions with high dependency on fossil fuels for revenue and employment generation (high confidence). Policies that promote diversification of the economy and the energy sector can address the associated challenges (high confidence). {5.4.1.2, Box 5.2} D.4.5 Redistributive policies across sectors and populations that shield the poor and vulnerable can resolve trade-offs for a range of SDGs, particularly hunger, poverty and energy access. Investment needs for such complementary policies are only a small fraction of the overall mitigation investments in 1.5°C pathways. (high confidence) {2.4.3, 5.4.2, Figure 5.5} D.5 Limiting the risks from global warming of 1.5°C in the context of sustainable development and poverty eradication implies system transitions that can be enabled by an increase of adaptation and mitigation investments, policy instruments, the acceleration of technological innovation and behaviour changes (high confidence). {2.3, 2.4, 2.5, 3.2, 4.2, 4.4, 4.5, 5.2, 5.5, 5.6} D.5.1 Directing finance towards investment in infrastructure for mitigation and adaptation could provide additional resources. This could involve the mobilization of private funds by institutional investors, asset managers and development or investment banks, as well as the provision of public funds. Government policies that lower the risk of low-emission and adaptation investments can facilitate the mobilization of private funds and enhance the effectiveness of other public policies. Studies indicate a number of challenges, including access to finance and mobilization of funds. (high confidence) {2.5.1, 2.5.2, 4.4.5} D.5.2 Adaptation finance consistent with global warming of 1.5°C is difficult to quantify and compare with 2°C. Knowledge gaps include insufficient data to calculate specific climate resilience-enhancing investments from the provision of currently underinvested basic infrastructure. Estimates of the costs of adaptation might be lower at global warming of 1.5°C than for 2°C. Adaptation needs have typically been supported by public sector sources such as national and subnational government budgets, and in developing countries together with support from development assistance, multilateral development banks, and United Nations Framework Convention on Climate Change channels (medium confidence). More recently there is a 21 Summary for Policymakers growing understanding of the scale and increase in non-governmental organizations and private funding in some regions (medium confidence). Barriers include the scale of adaptation financing, limited capacity and access to adaptation finance (medium confidence). {4.4.5, 4.6} SPM D.5.3 Global model pathways limiting global warming to 1.5°C are projected to involve the annual average investment needs in the energy system of around 2.4 trillion USD2010 between 2016 and 2035, representing about 2.5% of the world GDP (medium confidence). {4.4.5, Box 4.8} D.5.4 Policy tools can help mobilize incremental resources, including through shifting global investments and savings and through market and non-market based instruments as well as accompanying measures to secure the equity of the transition, acknowledging the challenges related with implementation, including those of energy costs, depreciation of assets and impacts on international competition, and utilizing the opportunities to maximize co-benefits (high confidence). {1.3.3, 2.3.4, 2.3.5, 2.5.1, 2.5.2, Cross-Chapter Box 8 in Chapter 3, Cross-Chapter Box 11 in Chapter 4, 4.4.5, 5.5.2} D.5.5 The systems transitions consistent with adapting to and limiting global warming to 1.5°C include the widespread adoption of new and possibly disruptive technologies and practices and enhanced climate-driven innovation. These imply enhanced technological innovation capabilities, including in industry and finance. Both national innovation policies and international cooperation can contribute to the development, commercialization and widespread adoption of mitigation and adaptation technologies. Innovation policies may be more effective when they combine public support for research and development with policy mixes that provide incentives for technology diffusion. (high confidence) {4.4.4, 4.4.5}. D.5.6 Education, information, and community approaches, including those that are informed by indigenous knowledge and local knowledge, can accelerate the wide-scale behaviour changes consistent with adapting to and limiting global warming to 1.5°C. These approaches are more effective when combined with other policies and tailored to the motivations, capabilities and resources of specific actors and contexts (high confidence). Public acceptability can enable or inhibit the implementation of policies and measures to limit global warming to 1.5°C and to adapt to the consequences. Public acceptability depends on the individual’s evaluation of expected policy consequences, the perceived fairness of the distribution of these consequences, and perceived fairness of decision procedures (high confidence). {1.1, 1.5, 4.3.5, 4.4.1, 4.4.3, Box 4.3, 5.5.3, 5.6.5} D.6 Sustainable development supports, and often enables, the fundamental societal and systems transitions and transformations that help limit global warming to 1.5°C. Such changes facilitate the pursuit of climate-resilient development pathways that achieve ambitious mitigation and adaptation in conjunction with poverty eradication and efforts to reduce inequalities (high confidence). {Box 1.1, 1.4.3, Figure 5.1, 5.5.3, Box 5.3} D.6.1 Social justice and equity are core aspects of climate-resilient development pathways that aim to limit global warming to 1.5°C as they address challenges and inevitable trade-offs, widen opportunities, and ensure that options, visions, and values are deliberated, between and within countries and communities, without making the poor and disadvantaged worse off (high confidence). {5.5.2, 5.5.3, Box 5.3, Figure 5.1, Figure 5.6, Cross-Chapter Boxes 12 and 13 in Chapter 5} D.6.2 The potential for climate-resilient development pathways differs between and within regions and nations, due to different development contexts and systemic vulnerabilities (very high confidence). Efforts along such pathways to date have been limited (medium confidence) and enhanced efforts would involve strengthened and timely action from all countries and non-state actors (high confidence). {5.5.1, 5.5.3, Figure 5.1} D.6.3 Pathways that are consistent with sustainable development show fewer mitigation and adaptation challenges and are associated with lower mitigation costs. The large majority of modelling studies could not construct pathways characterized by lack of international cooperation, inequality and poverty that were able to limit global warming to 1.5°C. (high confidence) {2.3.1, 2.5.1, 2.5.3, 5.5.2} 22 Summary for Policymakers D.7 Strengthening the capacities for climate action of national and sub-national authorities, civil society, the private sector, indigenous peoples and local communities can support the implementation of ambitious actions implied by limiting global warming to 1.5°C (high confidence). International cooperation can provide an enabling environment for this to be achieved in all countries and for all people, in the context of sustainable development. International cooperation is a critical enabler for developing countries and vulnerable regions (high confidence). {1.4, 2.3, 2.5, 4.2, 4.4, 4.5, 5.3, 5.4, 5.5, SPM 5.6, 5, Box 4.1, Box 4.2, Box 4.7, Box 5.3, Cross-Chapter Box 9 in Chapter 4, Cross-Chapter Box 13 in Chapter 5} D.7.1 Partnerships involving non-state public and private actors, institutional investors, the banking system, civil society and scientific institutions would facilitate actions and responses consistent with limiting global warming to 1.5°C (very high confidence). {1.4, 4.4.1, 4.2.2, 4.4.3, 4.4.5, 4.5.3, 5.4.1, 5.6.2, Box 5.3}. D.7.2 Cooperation on strengthened accountable multilevel governance that includes non-state actors such as industry, civil society and scientific institutions, coordinated sectoral and cross-sectoral policies at various governance levels, gender- sensitive policies, finance including innovative financing, and cooperation on technology development and transfer can ensure participation, transparency, capacity building and learning among different players (high confidence). {2.5.1, 2.5.2, 4.2.2, 4.4.1, 4.4.2, 4.4.3, 4.4.4, 4.4.5, 4.5.3, Cross-Chapter Box 9 in Chapter 4, 5.3.1, 5.5.3, Cross-Chapter Box 13 in Chapter 5, 5.6.1, 5.6.3} D.7.3 International cooperation is a critical enabler for developing countries and vulnerable regions to strengthen their action for the implementation of 1.5°C-consistent climate responses, including through enhancing access to finance and technology and enhancing domestic capacities, taking into account national and local circumstances and needs (high confidence). {2.3.1, 2.5.1, 4.4.1, 4.4.2, 4.4.4, 4.4.5, 5.4.1 5.5.3, 5.6.1, Box 4.1, Box 4.2, Box 4.7}. D.7.4 Collective efforts at all levels, in ways that reflect different circumstances and capabilities, in the pursuit of limiting global warming to 1.5°C, taking into account equity as well as effectiveness, can facilitate strengthening the global response to climate change, achieving sustainable development and eradicating poverty (high confidence). {1.4.2, 2.3.1, 2.5.1, 2.5.2, 2.5.3, 4.2.2, 4.4.1, 4.4.2, 4.4.3, 4.4.4, 4.4.5, 4.5.3, 5.3.1, 5.4.1, 5.5.3, 5.6.1, 5.6.2, 5.6.3} 23 Summary for Policymakers Box SPM.1: Core Concepts Central to this Special Report Global mean surface temperature (GMST): Estimated global average of near-surface air temperatures over land and sea ice, and sea surface temperatures over ice-free ocean regions, with changes normally expressed as departures from a SPM value over a specified reference period. When estimating changes in GMST, near-surface air temperature over both land and oceans are also used.19 {1.2.1.1} Pre-industrial: The multi-century period prior to the onset of large-scale industrial activity around 1750. The reference period 1850–1900 is used to approximate pre-industrial GMST. {1.2.1.2} Global warming: The estimated increase in GMST averaged over a 30-year period, or the 30-year period centred on a particular year or decade, expressed relative to pre-industrial levels unless otherwise specified. For 30-year periods that span past and future years, the current multi-decadal warming trend is assumed to continue. {1.2.1} Net zero CO2 emissions: Net zero carbon dioxide (CO2) emissions are achieved when anthropogenic CO2 emissions are balanced globally by anthropogenic CO2 removals over a specified period. Carbon dioxide removal (CDR): Anthropogenic activities removing CO2 from the atmosphere and durably storing it in geological, terrestrial, or ocean reservoirs, or in products. It includes existing and potential anthropogenic enhancement of biological or geochemical sinks and direct air capture and storage, but excludes natural CO2 uptake not directly caused by human activities. Total carbon budget: Estimated cumulative net global anthropogenic CO2 emissions from the pre-industrial period to the time that anthropogenic CO2 emissions reach net zero that would result, at some probability, in limiting global warming to a given level, accounting for the impact of other anthropogenic emissions. {2.2.2} Remaining carbon budget: Estimated cumulative net global anthropogenic CO2 emissions from a given start date to the time that anthropogenic CO2 emissions reach net zero that would result, at some probability, in limiting global warming to a given level, accounting for the impact of other anthropogenic emissions. {2.2.2} Temperature overshoot: The temporary exceedance of a specified level of global warming. Emission pathways: In this Summary for Policymakers, the modelled trajectories of global anthropogenic emissions over the 21st century are termed emission pathways. Emission pathways are classified by their temperature trajectory over the 21st century: pathways giving at least 50% probability based on current knowledge of limiting global warming to below 1.5°C are classified as ‘no overshoot’; those limiting warming to below 1.6°C and returning to 1.5°C by 2100 are classified as ‘1.5°C limited-overshoot’; while those exceeding 1.6°C but still returning to 1.5°C by 2100 are classified as ‘higher-overshoot’. Impacts: Effects of climate change on human and natural systems. Impacts can have beneficial or adverse outcomes for livelihoods, health and well-being, ecosystems and species, services, infrastructure, and economic, social and cultural assets. Risk: The potential for adverse consequences from a climate-related hazard for human and natural systems, resulting from the interactions between the hazard and the vulnerability and exposure of the affected system. Risk integrates the likelihood of exposure to a hazard and the magnitude of its impact. Risk also can describe the potential for adverse consequences of adaptation or mitigation responses to climate change. Climate-resilient development pathways (CRDPs): Trajectories that strengthen sustainable development at multiple scales and efforts to eradicate poverty through equitable societal and systems transitions and transformations while reducing the threat of climate change through ambitious mitigation, adaptation and climate resilience. 19 Past IPCC reports, reflecting the literature, have used a variety of approximately equivalent metrics of GMST change. 24 Technical Summary TS Technical Summary TS Coordinating Lead Authors: Myles R. Allen (UK), Heleen de Coninck (Netherlands/EU), Opha Pauline Dube (Botswana), Ove Hoegh-Guldberg (Australia), Daniela Jacob (Germany), Kejun Jiang (China), Aromar Revi (India), Joeri Rogelj (Belgium/Austria), Joyashree Roy (India), Drew Shindell (USA), William Solecki (USA), Michael Taylor (Jamaica), Petra Tschakert (Australia/Austria), Henri Waisman (France) Lead Authors: Sharina Abdul Halim (Malaysia), Philip Antwi-Agyei (Ghana), Fernando Aragón–Durand (Mexico), Mustafa Babiker (Sudan), Paolo Bertoldi (Italy), Marco Bindi (Italy), Sally Brown (UK), Marcos Buckeridge (Brazil), Ines Camilloni (Argentina), Anton Cartwright (South Africa), Wolfgang Cramer (France/Germany), Purnamita Dasgupta (India), Arona Diedhiou (Ivory Coast/Senegal), Riyanti Djalante (Japan/Indonesia), Wenjie Dong (China), Kristie L. Ebi (USA), Francois Engelbrecht (South Africa), Solomone Fifita (Fiji), James Ford (UK/Canada), Piers Forster (UK), Sabine Fuss (Germany), Bronwyn Hayward (New Zealand), Jean-Charles Hourcade (France), Veronika Ginzburg (Russia), Joel Guiot (France), Collins Handa (Kenya), Yasuaki Hijioka (Japan), Stephen Humphreys (UK/Ireland), Mikiko Kainuma (Japan), Jatin Kala (Australia), Markku Kanninen (Finland), Haroon Kheshgi (USA), Shigeki Kobayashi (Japan), Elmar Kriegler (Germany), Debora Ley (Guatemala/Mexico), Diana Liverman (USA), Natalie Mahowald (USA), Reinhard Mechler (Germany), Shagun Mehrotra (USA/India), Yacob Mulugetta (UK/Ethiopia), Luis Mundaca (Sweden/Chile), Peter Newman (Australia), Chukwumerije Okereke (UK/Nigeria), Antony Payne (UK), Rosa Perez (Philippines), Patricia Fernanda Pinho (Brazil), Anastasia Revokatova (Russian Federation), Keywan Riahi (Austria), Seth Schultz (USA), Roland Séférian (France), Sonia I. Seneviratne (Switzerland), Linda Steg (Netherlands), Avelino G. Suarez Rodriguez (Cuba), Taishi Sugiyama (Japan), Adelle Thomas (Bahamas), Maria Virginia Vilariño (Argentina), Morgan Wairiu (Solomon Islands), Rachel Warren (UK), Guangsheng Zhou (China), Kirsten Zickfeld (Canada/Germany) 27 Technical Summary Contributing Authors: Michelle Achlatis (Australia/Greece), Lisa V. Alexander (Australia), Malcolm Araos (Maldives/ Canada), Stefan Bakker (Netherlands), Mook Bangalore (USA), Amir Bazaz (India), Ella Belfer (Canada), Tim Benton (UK), Peter Berry (Canada), Bishwa Bhaskar Choudhary (India), Christopher Boyer (USA), Lorenzo Brilli (Italy), Katherine Calvin (USA), William Cheung (Canada), Sarah Connors (France/UK), Joana Correia de Oliveira de Portugal Pereira (UK/ Portugal), Marlies Craig (South Africa), Dipak Dasgupta (India), Kiane de Kleijne (Netherlands/ EU), Maria del Mar Zamora Dominguez (Mexico), Michel den Elzen (Netherlands), Haile Eakin (USA), Oreane Edelenbosch (Netherlands/Italy), Neville Ellis (Australia), Johannes Emmerling (Italy/Germany), Jason Evans (Australia), Maria Figueroa (Denmark/Venezuela), Dominique Finon (France), Hubertus Fisher (Switzerland), Klaus Fraedrich (Germany), Jan Fuglestvedt (Norway), Anjani Ganase (Trinidad and Tobago), Thomas Gasser (Austria/ France), Jean Pierre Gattuso (France), Frédéric Ghersi (France), Nathan Gillett (Canada), Adriana Grandis (Brazil), Peter Greve (Germany/Austria), Tania Guillén Bolaños (Germany/ Nicaragua), Mukesh Gupta (India), Amaha Medhin Haileselassie (Ethiopia), Naota Hanasaki TS (Japan), Tomoko Hasegawa (Japan), Eamon Haughey (Ireland), Katie Hayes (Canada), Chenmin He (China), Edgar Hertwich (USA/Austria), Diana Hinge Salili (Vanuatu), Annette Hirsch (Australia/Switzerland), Lena Höglund-Isaksson (Austria/Sweden), Daniel Huppmann (Austria), Saleemul Huq (Bangladesh/UK), Rachel James (UK), Chris Jones (UK), Thomas Jung (Germany), Richard Klein (Netherlands/Germany), Gerhard Krinner (France), David Lawrence (USA), Tim Lenton (UK), Gunnar Luderer (Germany), Peter Marcotullio (USA), Anil Markandya (Spain/UK), Omar Massera (Mexico), David L. McCollum (Austria/USA), Kathleen McInnes (Australia), Malte Meinshausen (Australia/Germany), Katrin J. Meissner (Australia), Richard Millar (UK), Katja Mintenbeck (Germany), Dann Mitchell (UK), Alan C. Mix (USA), Dirk Notz (Germany), Leonard Nurse (Barbados), Andrew Okem (Nigeria), Lennart Olsson (Sweden), Carolyn Opio (Uganda), Michael Oppenheimer (USA), Karen Paiva Henrique (Brazil), Simon Parkinson (Canada), Shlomit Paz (Israel), Juliane Petersen (Germany), Jan Petzold (Germany), Maxime Plazzotta (France), Alexander Popp (Germany), Swantje Preuschmann (Germany), Pallav Purohit (Austria/India), Graciela Raga (Mexico/Argentina), Mohammad Feisal Rahman (Bangladesh), Andy Reisinger (New Zealand), Kevon Rhiney (Jamaica), Aurélien Ribes (France), Mark Richardson (USA/UK), Wilfried Rickels (Germany), Timmons Roberts (USA), Maisa Rojas (Chile), Harry Saunders (Canada/USA), Christina Schädel (USA/Switzerland), Hanna Scheuffele (Germany), Lisa Schipper (UK/Sweden), Carl-Friedrich Schleussner (Germany), Jörn Schmidt (Germany), Daniel Scott (Canada), Jana Sillmann (Germany/ Norway), Chandni Singh (India), Raphael Slade (UK), Christopher Smith (UK), Pete Smith (UK), Shreya Some (India), Gerd Sparovek (Brazil), Will Steffen (Australia), Kimberly Stephenson (Jamaica), Tannecia Stephenson (Jamaica), Pablo Suarez (Argentina), Mouhamadou B. Sylla (Senegal), Nenenteiti Teariki-Ruatu (Kiribati), Mark Tebboth (UK), Peter Thorne (Ireland/UK), Evelina Trutnevyte (Switzerland/Lithuania), Penny Urquhart (South Africa), Arjan van Rooij (Netherlands), Anne M. van Valkengoed (Netherlands), Robert Vautard (France), Richard Wartenburger (Germany/Switzerland), Michael Wehner (USA), Margaretha Wewerinke- Singh (Netherlands), Nora M. Weyer (Germany), Felicia Whyte (Jamaica), Lini Wollenberg (USA), Yang Xiu (China), Gary Yohe (USA), Xuebin Zhang (Canada), Wenji Zhou (Austria/ China), Robert B. Zougmoré (Burkina Faso/Mali) 28 Technical Summary Review Editors: Amjad Abdulla (Maldives), Rizaldi Boer (Indonesia), Ismail Elgizouli Idris (Sudan), Andreas Fischlin (Switzerland), Greg Flato (Canada), Jan Fuglestvedt (Norway), Xuejie Gao (China), Mark Howden (Australia), Svitlana Krakovska (Ukraine), Ramon Pichs Madruga (Cuba), Jose Antonio Marengo (Brazil/Peru), Rachid Mrabet (Morocco), Joy Pereira (Malaysia), Roberto Sanchez (Mexico), Roberto Schaeffer (Brazil), Boris Sherstyukov (Russian Federation), Diana Ürge-Vorsatz (Hungary) Chapter Scientists: Daniel Huppmann (Austria), Tania Guillén Bolaños (Germany/Nicaragua), Neville Ellis (Australia), Kiane de Kleijne (Netherlands/EU), Richard Millar (UK), Chandni Singh (India), Chris Smith (UK) TS This Technical Summary should be cited as: Allen, M.R., H. de Coninck, O.P. Dube, O. Hoegh-Guldberg, D. Jacob, K. Jiang, A. Revi, J. Rogelj, J. Roy, D. Shindell, W. Solecki, M. Taylor, P. Tschakert, H. Waisman, S. Abdul Halim, P. Antwi-Agyei, F. Aragón-Durand, M. Babiker, P. Bertoldi, M. Bindi, S. Brown, M. Buckeridge, I. Camilloni, A. Cartwright, W. Cramer, P. Dasgupta, A. Diedhiou, R. Djalante, W. Dong, K.L. Ebi, F. Engelbrecht, S. Fifita, J. Ford, P. Forster, S. Fuss, V. Ginzburg, J. Guiot, C. Handa, B. Hayward, Y. Hijioka, J.-C. Hourcade, S. Humphreys, M. Kainuma, J. Kala, M. Kanninen, H. Kheshgi, S. Kobayashi, E. Kriegler, D. Ley, D. Liverman, N. Mahowald, R. Mechler, S. Mehrotra, Y. Mulugetta, L. Mundaca, P. Newman, C. Okereke, A. Payne, R. Perez, P.F. Pinho, A. Revokatova, K. Riahi, S. Schultz, R. Séférian, S.I. Seneviratne, L. Steg, A.G. Suarez Rodriguez, T. Sugiyama, A. Thomas, M.V. Vilariño, M. Wairiu, R. Warren, K. Zickfeld, and G. Zhou, 2018: Technical Summary. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)]. In Press. 29 Technical Summary Table of Contents TS.1 Framing and Context .....................................................31 TS.2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development....................................................................32 TS.3 Impacts of 1.5ºC Global Warming on Natural and Human Systems .................................35 TS.4 Strengthening and Implementing the Global Response ......................................................40 TS TS.5 Sustainable Development, Poverty Eradication and Reducing Inequalities ....................44 30 Technical Summary TS.1 Framing and Context an overshoot. Overshoot pathways are characterized by the peak magnitude of the overshoot, which may have implications for impacts. All 1.5°C pathways involve limiting cumulative emissions This chapter frames the context, knowledge-base and assessment of long-lived greenhouse gases, including carbon dioxide and nitrous approaches used to understand the impacts of 1.5°C global warming oxide, and substantial reductions in other climate forcers (high above pre-industrial levels and related global greenhouse gas confidence). Limiting cumulative emissions requires either reducing emission pathways, building on the IPCC Fifth Assessment Report net global emissions of long-lived greenhouse gases to zero before (AR5), in the context of strengthening the global response to the the cumulative limit is reached, or net negative global emissions threat of climate change, sustainable development and efforts to (anthropogenic removals) after the limit is exceeded. {1.2.3, 1.2.4, eradicate poverty. Cross-Chapter Boxes 1 and 2} Human-induced warming reached approximately 1°C (likely) This report assesses projected impacts at a global average between 0.8°C and 1.2°C) above pre-industrial levels in 2017, warming of 1.5°C and higher levels of warming. Global warming increasing at 0.2°C (likely between 0.1°C and 0.3°C) per of 1.5°C is associated with global average surface temperatures decade (high confidence). Global warming is defined in this report fluctuating naturally on either side of 1.5°C, together with warming as an increase in combined surface air and sea surface temperatures substantially greater than 1.5°C in many regions and seasons (high TS averaged over the globe and over a 30-year period. Unless otherwise confidence), all of which must be considered in the assessment of specified, warming is expressed relative to the period 1850–1900, impacts. Impacts at 1.5°C of warming also depend on the emission used as an approximation of pre-industrial temperatures in AR5. pathway to 1.5°C. Very different impacts result from pathways For periods shorter than 30 years, warming refers to the estimated that remain below 1.5°C versus pathways that return to 1.5°C average temperature over the 30 years centred on that shorter after a substantial overshoot, and when temperatures stabilize at period, accounting for the impact of any temperature fluctuations 1.5°C versus a transient warming past 1.5°C (medium confidence). or trend within those 30 years. Accordingly, warming from pre- {1.2.3, 1.3} industrial levels to the decade 2006–2015 is assessed to be 0.87°C (likely between 0.75°C and 0.99°C). Since 2000, the estimated level Ethical considerations, and the principle of equity in particular, of human-induced warming has been equal to the level of observed are central to this report, recognizing that many of the impacts warming with a likely range of ±20% accounting for uncertainty due of warming up to and beyond 1.5°C, and some potential to contributions from solar and volcanic activity over the historical impacts of mitigation actions required to limit warming to period (high confidence). {1.2.1} 1.5°C, fall disproportionately on the poor and vulnerable (high confidence). Equity has procedural and distributive dimensions and Warming greater than the global average has already been requires fairness in burden sharing both between generations and experienced in many regions and seasons, with higher average between and within nations. In framing the objective of holding the warming over land than over the ocean (high confidence). Most increase in the global average temperature rise to well below 2°C land regions are experiencing greater warming than the global average, above pre-industrial levels, and to pursue efforts to limit warming to while most ocean regions are warming at a slower rate. Depending 1.5°C, the Paris Agreement associates the principle of equity with the on the temperature dataset considered, 20–40% of the global human broader goals of poverty eradication and sustainable development, population live in regions that, by the decade 2006–2015, had already recognising that effective responses to climate change require a experienced warming of more than 1.5°C above pre-industrial in at global collective effort that may be guided by the 2015 United least one season (medium confidence). {1.2.1, 1.2.2} Nations Sustainable Development Goals. {1.1.1} Past emissions alone are unlikely to raise global-mean Climate adaptation refers to the actions taken to manage temperature to 1.5°C above pre-industrial levels (medium impacts of climate change by reducing vulnerability and confidence), but past emissions do commit to other changes, exposure to its harmful effects and exploiting any potential such as further sea level rise (high confidence). If all benefits. Adaptation takes place at international, national and anthropogenic emissions (including aerosol-related) were reduced local levels. Subnational jurisdictions and entities, including urban to zero immediately, any further warming beyond the 1°C already and rural municipalities, are key to developing and reinforcing experienced would likely be less than 0.5°C over the next two to measures for reducing weather- and climate-related risks. Adaptation three decades (high confidence), and likely less than 0.5°C on a implementation faces several barriers including lack of up-to-date and century time scale (medium confidence), due to the opposing effects locally relevant information, lack of finance and technology, social of different climate processes and drivers. A warming greater than values and attitudes, and institutional constraints (high confidence). 1.5°C is therefore not geophysically unavoidable: whether it will Adaptation is more likely to contribute to sustainable development occur depends on future rates of emission reductions. {1.2.3, 1.2.4} when policies align with mitigation and poverty eradication goals (medium confidence). {1.1, 1.4} 1.5°C emission pathways are defined as those that, given current knowledge of the climate response, provide a one- Ambitious mitigation actions are indispensable to limit in-two to two-in-three chance of warming either remaining warming to 1.5°C while achieving sustainable development below 1.5°C or returning to 1.5°C by around 2100 following and poverty eradication (high confidence). Ill-designed responses, 31 Technical Summary however, could pose challenges especially – but not exclusively – for TS.2 Mitigation Pathways Compatible countries and regions contending with poverty and those requiring with 1.5°C in the Context of significant transformation of their energy systems. This report focuses Sustainable Development on ‘climate-resilient development pathways’, which aim to meet the goals of sustainable development, including climate adaptation and mitigation, poverty eradication and reducing inequalities. But any This chapter assesses mitigation pathways consistent with limiting feasible pathway that remains within 1.5°C involves synergies and warming to 1.5°C above pre-industrial levels. In doing so, it explores trade-offs (high confidence). Significant uncertainty remains as to the following key questions: What role do CO2 and non-CO2 emissions which pathways are more consistent with the principle of equity. play? {2.2, 2.3, 2.4, 2.6} To what extent do 1.5°C pathways involve {1.1.1, 1.4} overshooting and returning below 1.5°C during the 21st century? {2.2, 2.3} What are the implications for transitions in energy, land use and Multiple forms of knowledge, including scientific evidence, sustainable development? {2.3, 2.4, 2.5} How do policy frameworks narrative scenarios and prospective pathways, inform the affect the ability to limit warming to 1.5°C? {2.3, 2.5} What are the understanding of 1.5°C. This report is informed by traditional associated knowledge gaps? {2.6} evidence of the physical climate system and associated impacts and TS vulnerabilities of climate change, together with knowledge drawn The assessed pathways describe integrated, quantitative from the perceptions of risk and the experiences of climate impacts evolutions of all emissions over the 21st century associated and governance systems. Scenarios and pathways are used to with global energy and land use and the world economy. The explore conditions enabling goal-oriented futures while recognizing assessment is contingent upon available integrated assessment the significance of ethical considerations, the principle of equity, and literature and model assumptions, and is complemented by other the societal transformation needed. {1.2.3, 1.5.2} studies with different scope, for example, those focusing on individual sectors. In recent years, integrated mitigation studies have improved There is no single answer to the question of whether it the characterizations of mitigation pathways. However, limitations is feasible to limit warming to 1.5°C and adapt to the remain, as climate damages, avoided impacts, or societal co-benefits consequences. Feasibility is considered in this report as the of the modelled transformations remain largely unaccounted for, while capacity of a system as a whole to achieve a specific outcome. The concurrent rapid technological changes, behavioural aspects, and global transformation that would be needed to limit warming to uncertainties about input data present continuous challenges. (high 1.5°C requires enabling conditions that reflect the links, synergies confidence) {2.1.3, 2.3, 2.5.1, 2.6, Technical Annex 2} and trade-offs between mitigation, adaptation and sustainable development. These enabling conditions are assessed across many The Chances of Limiting Warming to 1.5°C dimensions of feasibility – geophysical, environmental-ecological, and the Requirements for Urgent Action technological, economic, socio-cultural and institutional – that may be considered through the unifying lens of the Anthropocene, Pathways consistent with 1.5°C of warming above pre-industrial acknowledging profound, differential but increasingly geologically levels can be identified under a range of assumptions about significant human influences on the Earth system as a whole. This economic growth, technology developments and lifestyles. framing also emphasises the global interconnectivity of past, present However, lack of global cooperation, lack of governance of the required and future human–environment relations, highlighting the need and energy and land transformation, and increases in resource-intensive opportunities for integrated responses to achieve the goals of the consumption are key impediments to achieving 1.5°C pathways. Paris Agreement. {1.1, Cross-Chapter Box 1} Governance challenges have been related to scenarios with high inequality and high population growth in the 1.5°C pathway literature. {2.3.1, 2.3.2, 2.5} Under emissions in line with current pledges under the Paris Agreement (known as Nationally Determined Contributions, or NDCs), global warming is expected to surpass 1.5°C above pre-industrial levels, even if these pledges are supplemented with very challenging increases in the scale and ambition of mitigation after 2030 (high confidence). This increased action would need to achieve net zero CO2 emissions in less than 15 years. Even if this is achieved, temperatures would only be expected to remain below the 1.5°C threshold if the actual geophysical response ends up being towards the low end of the currently estimated uncertainty range. Transition challenges as well as identified trade-offs can be reduced if global emissions peak before 2030 and marked emissions reductions compared to today are already achieved by 2030. {2.2, 2.3.5, Cross- Chapter Box 11 in Chapter 4} 32 Technical Summary Limiting warming to 1.5°C depends on greenhouse gas (GHG) 830 billion USD2010 (range of 150 billion to 1700 billion USD2010 emissions over the next decades, where lower GHG emissions in across six models). Total energy-related investments increase by about 2030 lead to a higher chance of keeping peak warming to 1.5°C 12% (range of 3% to 24%) in 1.5°C pathways relative to 2°C pathways. (high confidence). Available pathways that aim for no or limited (less Average annual investment in low-carbon energy technologies and than 0.1°C) overshoot of 1.5°C keep GHG emissions in 2030 to 25–30 energy efficiency are upscaled by roughly a factor of six (range of factor GtCO2e yr−1 in 2030 (interquartile range). This contrasts with median of 4 to 10) by 2050 compared to 2015, overtaking fossil investments estimates for current unconditional NDCs of 52–58 GtCO −12e yr in globally by around 2025 (medium confidence). Uncertainties and 2030. Pathways that aim for limiting warming to 1.5°C by 2100 after strategic mitigation portfolio choices affect the magnitude and focus a temporary temperature overshoot rely on large-scale deployment of required investments. {2.5.2} of carbon dioxide removal (CDR) measures, which are uncertain and entail clear risks. In model pathways with no or limited overshoot of Future Emissions in 1.5°C Pathways 1.5°C, global net anthropogenic CO2 emissions decline by about 45% from 2010 levels by 2030 (40–60% interquartile range), reaching net Mitigation requirements can be quantified using carbon budget zero around 2050 (2045–2055 interquartile range). For limiting global approaches that relate cumulative CO2 emissions to global mean warming to below 2°C with at least 66% probability CO2 emissions temperature increase. Robust physical understanding underpins are projected to decline by about 25% by 2030 in most pathways (10– this relationship, but uncertainties become increasingly relevant as a TS 30% interquartile range) and reach net zero around 2070 (2065–2080 specific temperature limit is approached. These uncertainties relate to interquartile range).1 {2.2, 2.3.3, 2.3.5, 2.5.3, Cross-Chapter Boxes 6 in the transient climate response to cumulative carbon emissions (TCRE), Chapter 3 and 9 in Chapter 4, 4.3.7} non-CO2 emissions, radiative forcing and response, potential additional Earth system feedbacks (such as permafrost thawing), and historical Limiting warming to 1.5°C implies reaching net zero CO2 emissions and temperature. {2.2.2, 2.6.1} emissions globally around 2050 and concurrent deep reductions in emissions of non-CO2 forcers, particularly methane (high Cumulative CO2 emissions are kept within a budget by reducing confidence). Such mitigation pathways are characterized by energy- global annual CO2 emissions to net zero. This assessment demand reductions, decarbonization of electricity and other fuels, suggests a remaining budget of about 420 GtCO2 for a two- electrification of energy end use, deep reductions in agricultural thirds chance of limiting warming to 1.5°C, and of about 580 emissions, and some form of CDR with carbon storage on land or GtCO2 for an even chance (medium confidence). The remaining sequestration in geological reservoirs. Low energy demand and low carbon budget is defined here as cumulative CO2 emissions from the demand for land- and GHG-intensive consumption goods facilitate start of 2018 until the time of net zero global emissions for global limiting warming to as close as possible to 1.5°C. {2.2.2, 2.3.1, 2.3.5, warming defined as a change in global near-surface air temperatures. 2.5.1, Cross-Chapter Box 9 in Chapter 4}. Remaining budgets applicable to 2100 would be approximately 100 GtCO2 lower than this to account for permafrost thawing and In comparison to a 2°C limit, the transformations required to limit potential methane release from wetlands in the future, and more warming to 1.5°C are qualitatively similar but more pronounced thereafter. These estimates come with an additional geophysical and rapid over the next decades (high confidence). 1.5°C implies uncertainty of at least ±400 GtCO2, related to non-CO2 response very ambitious, internationally cooperative policy environments that and TCRE distribution. Uncertainties in the level of historic warming transform both supply and demand (high confidence). {2.3, 2.4, 2.5} contribute ±250 GtCO2. In addition, these estimates can vary by ±250 GtCO2 depending on non-CO2 mitigation strategies as found in Policies reflecting a high price on emissions are necessary available pathways. {2.2.2, 2.6.1} in models to achieve cost-effective 1.5°C pathways (high confidence). Other things being equal, modelling studies suggest Staying within a remaining carbon budget of 580 GtCO2 implies the global average discounted marginal abatement costs for limiting that CO2 emissions reach carbon neutrality in about 30 years, warming to 1.5°C being about 3–4 times higher compared to 2°C reduced to 20 years for a 420 GtCO2 remaining carbon budget over the 21st century, with large variations across models and socio- (high confidence). The ±400 GtCO2 geophysical uncertainty range economic and policy assumptions. Carbon pricing can be imposed surrounding a carbon budget translates into a variation of this timing directly or implicitly by regulatory policies. Policy instruments, like of carbon neutrality of roughly ±15–20 years. If emissions do not start technology policies or performance standards, can complement explicit declining in the next decade, the point of carbon neutrality would need carbon pricing in specific areas. {2.5.1, 2.5.2, 4.4.5} to be reached at least two decades earlier to remain within the same carbon budget. {2.2.2, 2.3.5} Limiting warming to 1.5°C requires a marked shift in investment patterns (medium confidence). Additional annual average energy- Non-CO2 emissions contribute to peak warming and thus related investments for the period 2016 to 2050 in pathways limiting affect the remaining carbon budget. The evolution of warming to 1.5°C compared to pathways without new climate policies methane and sulphur dioxide emissions strongly influences beyond those in place today (i.e., baseline) are estimated to be around the chances of limiting warming to 1.5°C. In the near-term, a 1 Kyoto-GHG emissions in this statement are aggregated with GWP-100 values of the IPCC Second Assessment Report. 33 Technical Summary weakening of aerosol cooling would add to future warming, equivalence method) supply a share of 52–67% (interquartile range) but can be tempered by reductions in methane emissions (high of primary energy in 1.5°C pathways with no or limited overshoot; confidence). Uncertainty in radiative forcing estimates (particularly while the share from coal decreases to 1–7% (interquartile range), aerosol) affects carbon budgets and the certainty of pathway with a large fraction of this coal use combined with carbon capture categorizations. Some non-CO2 forcers are emitted alongside CO2, and storage (CCS). From 2020 to 2050 the primary energy supplied particularly in the energy and transport sectors, and can be largely by oil declines in most pathways (−39 to −77% interquartile range). addressed through CO2 mitigation. Others require specific measures, Natural gas changes by −13% to −62% (interquartile range), but for example, to target agricultural nitrous oxide (N2O) and methane some pathways show a marked increase albeit with widespread (CH4), some sources of black carbon, or hydrofluorocarbons (high deployment of CCS. The overall deployment of CCS varies widely confidence). In many cases, non-CO2 emissions reductions are similar across 1.5°C pathways with no or limited overshoot, with cumulative in 2°C pathways, indicating reductions near their assumed maximum CO2 stored through 2050 ranging from zero up to 300 GtCO2 potential by integrated assessment models. Emissions of N2O and (minimum–maximum range), of which zero up to 140 GtCO2 is stored NH3 increase in some pathways with strongly increased bioenergy from biomass. Primary energy supplied by bioenergy ranges from demand. {2.2.2, 2.3.1, 2.4.2, 2.5.3} 40–310 EJ yr−1 in 2050 (minimum-maximum range), and nuclear from 3–66 EJ yr−1 (minimum–maximum range). These ranges reflect both TS The Role of Carbon Dioxide Removal (CDR) uncertainties in technological development and strategic mitigation portfolio choices. {2.4.2} All analysed pathways limiting warming to 1.5°C with no or limited overshoot use CDR to some extent to neutralize 1.5°C pathways with no or limited overshoot include a rapid emissions from sources for which no mitigation measures decline in the carbon intensity of electricity and an increase have been identified and, in most cases, also to achieve in electrification of energy end use (high confidence). By 2050, net negative emissions to return global warming to 1.5°C the carbon intensity of electricity decreases to −92 to +11 gCO2 MJ −1 following a peak (high confidence). The longer the delay in (minimum–maximum range) from about 140 gCO2 MJ −1 in 2020, reducing CO2 emissions towards zero, the larger the likelihood and electricity covers 34–71% (minimum–maximum range) of final of exceeding 1.5°C, and the heavier the implied reliance on energy across 1.5°C pathways with no or limited overshoot from net negative emissions after mid-century to return warming to about 20% in 2020. By 2050, the share of electricity supplied by 1.5°C (high confidence). The faster reduction of net CO2 emissions renewables increases to 59–97% (minimum-maximum range) across in 1.5°C compared to 2°C pathways is predominantly achieved by 1.5°C pathways with no or limited overshoot. Pathways with higher measures that result in less CO2 being produced and emitted, and chances of holding warming to below 1.5°C generally show a faster only to a smaller degree through additional CDR. Limitations on decline in the carbon intensity of electricity by 2030 than pathways the speed, scale and societal acceptability of CDR deployment also that temporarily overshoot 1.5°C. {2.4.1, 2.4.2, 2.4.3} limit the conceivable extent of temperature overshoot. Limits to our understanding of how the carbon cycle responds to net negative Transitions in global and regional land use are found in all emissions increase the uncertainty about the effectiveness of CDR to pathways limiting global warming to 1.5°C with no or limited decline temperatures after a peak. {2.2, 2.3, 2.6, 4.3.7} overshoot, but their scale depends on the pursued mitigation portfolio (high confidence). Pathways that limit global warming to CDR deployed at scale is unproven, and reliance on such 1.5°C with no or limited overshoot project a 4 million km2 reduction technology is a major risk in the ability to limit warming to to a 2.5 million km2 increase of non-pasture agricultural land for food 1.5°C. CDR is needed less in pathways with particularly strong and feed crops and a 0.5–11 million km2 reduction of pasture land, emphasis on energy efficiency and low demand. The scale and to be converted into 0-6 million km2 of agricultural land for energy type of CDR deployment varies widely across 1.5°C pathways, crops and a 2 million km2 reduction to 9.5 million km2 increase in with different consequences for achieving sustainable forests by 2050 relative to 2010 (medium confidence). Land-use development objectives (high confidence). Some pathways rely transitions of similar magnitude can be observed in modelled 2°C more on bioenergy with carbon capture and storage (BECCS), while pathways (medium confidence). Such large transitions pose profound others rely more on afforestation, which are the two CDR methods challenges for sustainable management of the various demands on most often included in integrated pathways. Trade-offs with other land for human settlements, food, livestock feed, fibre, bioenergy, sustainability objectives occur predominantly through increased land, carbon storage, biodiversity and other ecosystem services (high energy, water and investment demand. Bioenergy use is substantial confidence). {2.3.4, 2.4.4} in 1.5°C pathways with or without BECCS due to its multiple roles in decarbonizing energy use. {2.3.1, 2.5.3, 2.6.3, 4.3.7} Demand-Side Mitigation and Behavioural Changes Properties of Energy and Land Transitions in 1.5°C Pathways Demand-side measures are key elements of 1.5°C pathways. Lifestyle choices lowering energy demand and the land- and The share of primary energy from renewables increases while GHG-intensity of food consumption can further support coal usage decreases across pathways limiting warming to achievement of 1.5°C pathways (high confidence). By 2030 and 1.5°C with no or limited overshoot (high confidence). By 2050, 2050, all end-use sectors (including building, transport, and industry) renewables (including bioenergy, hydro, wind, and solar, with direct- show marked energy demand reductions in modelled 1.5°C pathways, 34 Technical Summary comparable and beyond those projected in 2°C pathways. Sectoral TS.3 Impacts of 1.5ºC Global Warming models support the scale of these reductions. {2.3.4, 2.4.3, 2.5.1} on Natural and Human Systems Links between 1.5°C Pathways and Sustainable Development This chapter builds on findings of AR5 and assesses new scientific Choices about mitigation portfolios for limiting warming to evidence of changes in the climate system and the associated impacts 1.5°C can positively or negatively impact the achievement of on natural and human systems, with a specific focus on the magnitude other societal objectives, such as sustainable development and pattern of risks linked for global warming of 1.5°C above (high confidence). In particular, demand-side and efficiency temperatures in the pre-industrial period. Chapter 3 explores observed measures, and lifestyle choices that limit energy, resource, and impacts and projected risks to a range of natural and human systems, GHG-intensive food demand support sustainable development with a focus on how risk levels change from 1.5°C to 2°C of global (medium confidence). Limiting warming to 1.5°C can be achieved warming. The chapter also revisits major categories of risk (Reasons for synergistically with poverty alleviation and improved energy security Concern, RFC) based on the assessment of new knowledge that has and can provide large public health benefits through improved air become available since AR5. quality, preventing millions of premature deaths. However, specific mitigation measures, such as bioenergy, may result in trade-offs that 1.5°C and 2°C Warmer Worlds TS require consideration. {2.5.1, 2.5.2, 2.5.3} The global climate has changed relative to the pre-industrial period, and there are multiple lines of evidence that these changes have had impacts on organisms and ecosystems, as well as on human systems and well-being (high confidence). The increase in global mean surface temperature (GMST), which reached 0.87°C in 2006–2015 relative to 1850–1900, has increased the frequency and magnitude of impacts (high confidence), strengthening evidence of how an increase in GMST of 1.5°C or more could impact natural and human systems (1.5°C versus 2°C). {3.3, 3.4, 3.5, 3.6, Cross-Chapter Boxes 6, 7 and 8 in this chapter} Human-induced global warming has already caused multiple observed changes in the climate system (high confidence). Changes include increases in both land and ocean temperatures, as well as more frequent heatwaves in most land regions (high confidence). There is also high confidence that global warming has resulted in an increase in the frequency and duration of marine heatwaves. Further, there is substantial evidence that human-induced global warming has led to an increase in the frequency, intensity and/or amount of heavy precipitation events at the global scale (medium confidence), as well as an increased risk of drought in the Mediterranean region (medium confidence). {3.3.1, 3.3.2, 3.3.3, 3.3.4, Box 3.4} Trends in intensity and frequency of some climate and weather extremes have been detected over time spans during which about 0.5°C of global warming occurred (medium confidence). This assessment is based on several lines of evidence, including attribution studies for changes in extremes since 1950. {3.2, 3.3.1, 3.3.2, 3.3.3, 3.3.4} Several regional changes in climate are assessed to occur with global warming up to 1.5°C as compared to pre-industrial levels, including warming of extreme temperatures in many regions (high confidence), increases in frequency, intensity and/or amount of heavy precipitation in several regions (high confidence), and an increase in intensity or frequency of droughts in some regions (medium confidence). {3.3.1, 3.3.2, 3.3.3, 3.3.4, Table 3.2} There is no single ‘1.5°C warmer world’ (high confidence). In addition to the overall increase in GMST, it is important to consider the 35 Technical Summary size and duration of potential overshoots in temperature. Furthermore, and about 65 million fewer people being exposed to exceptional there are questions on how the stabilization of an increase in GMST of heatwaves, assuming constant vulnerability (medium confidence). 1.5°C can be achieved, and how policies might be able to influence the {3.3.1, 3.3.2, Cross-Chapter Box 8 in this chapter} resilience of human and natural systems, and the nature of regional and subregional risks. Overshooting poses large risks for natural and Limiting global warming to 1.5°C would limit risks of increases human systems, especially if the temperature at peak warming is in heavy precipitation events on a global scale and in several high, because some risks may be long-lasting and irreversible, such regions compared to conditions at 2°C global warming as the loss of some ecosystems (high confidence). The rate of change (medium confidence). The regions with the largest increases in heavy for several types of risks may also have relevance, with potentially precipitation events for 1.5°C to 2°C global warming include: several large risks in the case of a rapid rise to overshooting temperatures, high-latitude regions (e.g. Alaska/western Canada, eastern Canada/ even if a decrease to 1.5°C can be achieved at the end of the 21st Greenland/Iceland, northern Europe and northern Asia); mountainous century or later (medium confidence). If overshoot is to be minimized, regions (e.g., Tibetan Plateau); eastern Asia (including China and Japan); the remaining equivalent CO2 budget available for emissions is very and eastern North America (medium confidence). Tropical cyclones are small, which implies that large, immediate and unprecedented global projected to decrease in frequency but with an increase in the number efforts to mitigate greenhouse gases are required (high confidence). of very intense cyclones (limited evidence, low confidence). Heavy TS {3.2, 3.6.2, Cross-Chapter Box 8 in this chapter} precipitation associated with tropical cyclones is projected to be higher at 2°C compared to 1.5°C of global warming (medium confidence). Robust1 global differences in temperature means and extremes Heavy precipitation, when aggregated at a global scale, is projected to are expected if global warming reaches 1.5°C versus 2°C above be higher at 2°C than at 1.5°C of global warming (medium confidence) the pre-industrial levels (high confidence). For oceans, regional {3.3.3, 3.3.6} surface temperature means and extremes are projected to be higher at 2°C compared to 1.5°C of global warming (high confidence). Limiting global warming to 1.5°C is expected to substantially Temperature means and extremes are also projected to be higher at reduce the probability of extreme drought, precipitation deficits, 2°C compared to 1.5°C in most land regions, with increases being and risks associated with water availability (i.e., water stress) in 2–3 times greater than the increase in GMST projected for some some regions (medium confidence). In particular, risks associated regions (high confidence). Robust increases in temperature means and with increases in drought frequency and magnitude are projected to be extremes are also projected at 1.5°C compared to present-day values substantially larger at 2°C than at 1.5°C in the Mediterranean region (high confidence) {3.3.1, 3.3.2}. There are decreases in the occurrence (including southern Europe, northern Africa and the Near East) and of cold extremes, but substantial increases in their temperature, in southern Africa (medium confidence). {3.3.3, 3.3.4, Box 3.1, Box 3.2} particular in regions with snow or ice cover (high confidence) {3.3.1}. Risks to natural and human systems are expected to be lower Climate models project robust2 differences in regional climate at 1.5°C than at 2°C of global warming (high confidence). This between present-day and global warming up to 1.5°C3, and difference is due to the smaller rates and magnitudes of climate between 1.5°C and 2°C3 (high confidence), depending on the change associated with a 1.5°C temperature increase, including lower variable and region in question (high confidence). Large, robust frequencies and intensities of temperature-related extremes. Lower and widespread differences are expected for temperature rates of change enhance the ability of natural and human systems extremes (high confidence). Regarding hot extremes, the strongest to adapt, with substantial benefits for a wide range of terrestrial, warming is expected to occur at mid-latitudes in the warm season (with freshwater, wetland, coastal and ocean ecosystems (including coral increases of up to 3°C for 1.5°C of global warming, i.e., a factor of two) reefs) (high confidence), as well as food production systems, human and at high latitudes in the cold season (with increases of up to 4.5°C health, and tourism (medium confidence), together with energy at 1.5°C of global warming, i.e., a factor of three) (high confidence). systems and transportation (low confidence). {3.3.1, 3.4} The strongest warming of hot extremes is projected to occur in central and eastern North America, central and southern Europe, the Exposure to multiple and compound climate-related risks is Mediterranean region (including southern Europe, northern Africa and projected to increase between 1.5°C and 2°C of global warming the Near East), western and central Asia, and southern Africa (medium with greater proportions of people both exposed and susceptible to confidence). The number of exceptionally hot days are expected to poverty in Africa and Asia (high confidence). For global warming from increase the most in the tropics, where interannual temperature 1.5°C to 2°C, risks across energy, food, and water sectors could overlap variability is lowest; extreme heatwaves are thus projected to emerge spatially and temporally, creating new – and exacerbating current – earliest in these regions, and they are expected to already become hazards, exposures, and vulnerabilities that could affect increasing widespread there at 1.5°C global warming (high confidence). Limiting numbers of people and regions (medium confidence). Small island global warming to 1.5°C instead of 2°C could result in around 420 states and economically disadvantaged populations are particularly at million fewer people being frequently exposed to extreme heatwaves, risk (high confidence). {3.3.1, 3.4.5.3, 3.4.5.6, 3.4.11, 3.5.4.9, Box 3.5} 2 Robust is used here to mean that at least two thirds of climate models show the same sign of changes at the grid point scale, and that differences in large regions are statistically significant. 3 Projected changes in impacts between different levels of global warming are determined with respect to changes in global mean near-surface air temperature. 36 Technical Summary Global warming of 2°C would lead to an expansion of areas with Future risks at 1.5°C of global warming will depend on the significant increases in runoff, as well as those affected by flood mitigation pathway and on the possible occurrence of a hazard, compared to conditions at 1.5°C (medium confidence). transient overshoot (high confidence). The impacts on natural Global warming of 1.5°C would also lead to an expansion of the global and human systems would be greater if mitigation pathways land area with significant increases in runoff (medium confidence) and temporarily overshoot 1.5°C and return to 1.5°C later in the century, an increase in flood hazard in some regions (medium confidence) as compared to pathways that stabilize at 1.5°C without an overshoot compared to present-day conditions. {3.3.5} (high confidence). The size and duration of an overshoot would also affect future impacts (e.g., irreversible loss of some ecosystems) (high The probability of a sea-ice-free Arctic Ocean4 during summer confidence). Changes in land use resulting from mitigation choices is substantially higher at 2°C compared to 1.5°C of global could have impacts on food production and ecosystem diversity. {3.6.1, warming (medium confidence). Model simulations suggest that 3.6.2, Cross-Chapter Boxes 7 and 8 in this chapter} at least one sea-ice-free Arctic summer is expected every 10 years for global warming of 2°C, with the frequency decreasing to one Climate Change Risks for Natural and Human systems sea-ice-free Arctic summer every 100 years under 1.5°C (medium confidence). An intermediate temperature overshoot will have no long- Terrestrial and Wetland Ecosystems term consequences for Arctic sea ice coverage, and hysteresis is not TS expected (high confidence). {3.3.8, 3.4.4.7} Risks of local species losses and, consequently, risks of extinction are much less in a 1.5°C versus a 2°C warmer world Global mean sea level rise (GMSLR) is projected to be around (high confidence). The number of species projected to lose over 0.1 m (0.04 – 0.16 m) less by the end of the 21st century in a half of their climatically determined geographic range at 2°C global 1.5°C warmer world compared to a 2°C warmer world (medium warming (18% of insects, 16% of plants, 8% of vertebrates) is confidence). Projected GMSLR for 1.5°C of global warming has an projected to be reduced to 6% of insects, 8% of plants and 4% of indicative range of 0.26 – 0.77m, relative to 1986–2005, (medium vertebrates at 1.5°C warming (medium confidence). Risks associated confidence). A smaller sea level rise could mean that up to 10.4 million with other biodiversity-related factors, such as forest fires, extreme fewer people (based on the 2010 global population and assuming no weather events, and the spread of invasive species, pests and adaptation) would be exposed to the impacts of sea level rise globally diseases, would also be lower at 1.5°C than at 2°C of warming (high in 2100 at 1.5°C compared to at 2°C. A slower rate of sea level rise confidence), supporting a greater persistence of ecosystem services. enables greater opportunities for adaptation (medium confidence). {3.4.3, 3.5.2} There is high confidence that sea level rise will continue beyond 2100. Instabilities exist for both the Greenland and Antarctic ice sheets, which Constraining global warming to 1.5°C, rather than to 2°C could result in multi-meter rises in sea level on time scales of century and higher, is projected to have many benefits for terrestrial to millennia. There is medium confidence that these instabilities could and wetland ecosystems and for the preservation of their be triggered at around 1.5°C to 2°C of global warming. {3.3.9, 3.4.5, services to humans (high confidence). Risks for natural and 3.6.3} managed ecosystems are higher on drylands compared to humid lands. The global terrestrial land area projected to be affected by The ocean has absorbed about 30% of the anthropogenic ecosystem transformations (13%, interquartile range 8–20%) at 2°C carbon dioxide, resulting in ocean acidification and changes to is approximately halved at 1.5°C global warming to 4% (interquartile carbonate chemistry that are unprecedented for at least the range 2–7%) (medium confidence). Above 1.5°C, an expansion of last 65 million years (high confidence). Risks have been identified desert terrain and vegetation would occur in the Mediterranean for the survival, calcification, growth, development and abundance of biome (medium confidence), causing changes unparalleled in the last a broad range of marine taxonomic groups, ranging from algae to fish, 10,000 years (medium confidence). {3.3.2.2, 3.4.3.2, 3.4.3.5, 3.4.6.1, with substantial evidence of predictable trait-based sensitivities (high 3.5.5.10, Box 4.2} confidence). There are multiple lines of evidence that ocean warming and acidification corresponding to 1.5°C of global warming would Many impacts are projected to be larger at higher latitudes, impact a wide range of marine organisms and ecosystems, as well as owing to mean and cold-season warming rates above the sectors such as aquaculture and fisheries (high confidence). {3.3.10, global average (medium confidence). High-latitude tundra and 3.4.4} boreal forest are particularly at risk, and woody shrubs are already encroaching into tundra (high confidence) and will proceed with Larger risks are expected for many regions and systems for further warming. Constraining warming to 1.5°C would prevent the global warming at 1.5°C, as compared to today, with adaptation thawing of an estimated permafrost area of 1.5 to 2.5 million km2 required now and up to 1.5°C. However, risks would be larger at 2°C of over centuries compared to thawing under 2°C (medium confidence). warming and an even greater effort would be needed for adaptation to {3.3.2, 3.4.3, 3.4.4} a temperature increase of that magnitude (high confidence). {3.4, Box 3.4, Box 3.5, Cross-Chapter Box 6 in this chapter} 4 Ice free is defined for the Special Report as when the sea ice extent is less than 106 km2. Ice coverage less than this is considered to be equivalent to an ice-free Arctic Ocean for practical purposes in all recent studies. 37 Technical Summary Ocean Ecosystems (high confidence). A loss of 7–10% of rangeland livestock globally is projected for approximately 2°C of warming, with considerable Ocean ecosystems are already experiencing large-scale economic consequences for many communities and regions (medium changes, and critical thresholds are expected to be reached at confidence). {3.4.6, 3.6, Box 3.1, Cross-Chapter Box 6 in this chapter} 1.5°C and higher levels of global warming (high confidence). In the transition to 1.5°C of warming, changes to water temperatures Reductions in projected food availability are larger at 2°C are expected to drive some species (e.g., plankton, fish) to relocate than at 1.5°C of global warming in the Sahel, southern Africa, to higher latitudes and cause novel ecosystems to assemble (high the Mediterranean, central Europe and the Amazon (medium confidence). Other ecosystems (e.g., kelp forests, coral reefs) are confidence). This suggests a transition from medium to high risk of relatively less able to move, however, and are projected to experience regionally differentiated impacts on food security between 1.5°C and high rates of mortality and loss (very high confidence). For example, 2°C (medium confidence). Future economic and trade environments multiple lines of evidence indicate that the majority (70–90%) of and their response to changing food availability (medium confidence) warm water (tropical) coral reefs that exist today will disappear even are important potential adaptation options for reducing hunger risk if global warming is constrained to 1.5°C (very high confidence). in low- and middle-income countries. {Cross-Chapter Box 6 in this {3.4.4, Box 3.4} chapter} TS Current ecosystem services from the ocean are expected to be Fisheries and aquaculture are important to global food security reduced at 1.5°C of global warming, with losses being even but are already facing increasing risks from ocean warming greater at 2°C of global warming (high confidence). The risks and acidification (medium confidence). These risks are of declining ocean productivity, shifts of species to higher latitudes, projected to increase at 1.5°C of global warming and impact damage to ecosystems (e.g., coral reefs, and mangroves, seagrass key organisms such as fin fish and bivalves (e.g., oysters), and other wetland ecosystems), loss of fisheries productivity (at especially at low latitudes (medium confidence). Small-scale low latitudes), and changes to ocean chemistry (e.g., acidification, fisheries in tropical regions, which are very dependent on habitat hypoxia and dead zones) are projected to be substantially lower provided by coastal ecosystems such as coral reefs, mangroves, when global warming is limited to 1.5°C (high confidence). {3.4.4, seagrass and kelp forests, are expected to face growing risks at 1.5°C Box 3.4} of warming because of loss of habitat (medium confidence). Risks of impacts and decreasing food security are projected to become Water Resources greater as global warming reaches beyond 1.5°C and both ocean warming and acidification increase, with substantial losses likely for The projected frequency and magnitude of floods and droughts coastal livelihoods and industries (e.g., fisheries and aquaculture) in some regions are smaller under 1.5°C than under 2°C of (medium to high confidence). {3.4.4, 3.4.5, 3.4.6, Box 3.1, Box 3.4, warming (medium confidence). Human exposure to increased Box 3.5, Cross-Chapter Box 6 in this chapter} flooding is projected to be substantially lower at 1.5°C compared to 2°C of global warming, although projected changes create regionally Land use and land-use change emerge as critical features of differentiated risks (medium confidence). The differences in the risks virtually all mitigation pathways that seek to limit global among regions are strongly influenced by local socio-economic warming to 1.5°C (high confidence). Most least-cost mitigation conditions (medium confidence). {3.3.4, 3.3.5, 3.4.2} pathways to limit peak or end-of-century warming to 1.5°C make use of carbon dioxide removal (CDR), predominantly employing Risks of water scarcity are projected to be greater at 2°C than at significant levels of bioenergy with carbon capture and storage 1.5°C of global warming in some regions (medium confidence). (BECCS) and/or afforestation and reforestation (AR) in their portfolio Depending on future socio-economic conditions, limiting global of mitigation measures (high confidence). {Cross-Chapter Box 7 in warming to 1.5°C, compared to 2°C, may reduce the proportion of this chapter} the world population exposed to a climate change-induced increase in water stress by up to 50%, although there is considerable variability Large-scale deployment of BECCS and/or AR would have between regions (medium confidence). Regions with particularly a far-reaching land and water footprint (high confidence). large benefits could include the Mediterranean and the Caribbean Whether this footprint would result in adverse impacts, for example (medium confidence). Socio-economic drivers, however, are expected on biodiversity or food production, depends on the existence and to have a greater influence on these risks than the changes in climate effectiveness of measures to conserve land carbon stocks, measures (medium confidence). {3.3.5, 3.4.2, Box 3.5} to limit agricultural expansion in order to protect natural ecosystems, and the potential to increase agricultural productivity (medium Land Use, Food Security and Food Production Systems agreement). In addition, BECCS and/or AR would have substantial direct effects on regional climate through biophysical feedbacks, Limiting global warming to 1.5°C, compared with 2°C, is which are generally not included in Integrated Assessments Models projected to result in smaller net reductions in yields of maize, (high confidence). {3.6.2, Cross-Chapter Boxes 7 and 8 in this chapter} rice, wheat, and potentially other cereal crops, particularly in sub-Saharan Africa, Southeast Asia, and Central and South America; The impacts of large-scale CDR deployment could be greatly and in the CO2-dependent nutritional quality of rice and wheat reduced if a wider portfolio of CDR options were deployed, if a 38 Technical Summary holistic policy for sustainable land management were adopted, change should global warming increase from 1.5°C to 2°C (medium and if increased mitigation efforts were employed to strongly confidence). {3.5} limit the demand for land, energy and material resources, including through lifestyle and dietary changes (medium Global warming has already affected tourism, with increased confidence). In particular, reforestation could be associated with risks projected under 1.5°C of warming in specific geographic significant co-benefits if implemented in a manner than helps restore regions and for seasonal tourism including sun, beach and natural ecosystems (high confidence). {Cross-Chapter Box 7 in this snow sports destinations (very high confidence). Risks will be chapter} lower for tourism markets that are less climate sensitive, such as gaming and large hotel-based activities (high confidence). Risks for Human Health, Well-Being, Cities and Poverty coastal tourism, particularly in subtropical and tropical regions, will increase with temperature-related degradation (e.g., heat extremes, Any increase in global temperature (e.g., +0.5°C) is projected storms) or loss of beach and coral reef assets (high confidence). to affect human health, with primarily negative consequences {3.3.6, 3.4.4.12, 3.4.9.1, Box 3.4} (high confidence). Lower risks are projected at 1.5°C than at 2°C for heat-related morbidity and mortality (very high confidence), and Small Islands, and Coastal and Low-lying areas for ozone-related mortality if emissions needed for ozone formation TS remain high (high confidence). Urban heat islands often amplify the Small islands are projected to experience multiple inter- impacts of heatwaves in cities (high confidence). Risks for some related risks at 1.5°C of global warming that will increase with vector-borne diseases, such as malaria and dengue fever are projected warming of 2°C and higher levels (high confidence). Climate to increase with warming from 1.5°C to 2°C, including potential hazards at 1.5°C are projected to be lower compared to those at 2°C shifts in their geographic range (high confidence). Overall for vector- (high confidence). Long-term risks of coastal flooding and impacts on borne diseases, whether projections are positive or negative depends populations, infrastructures and assets (high confidence), freshwater on the disease, region and extent of change (high confidence). Lower stress (medium confidence), and risks across marine ecosystems (high risks of undernutrition are projected at 1.5°C than at 2°C (medium confidence) and critical sectors (medium confidence) are projected to confidence). Incorporating estimates of adaptation into projections increase at 1.5°C compared to present-day levels and increase further reduces the magnitude of risks (high confidence). {3.4.7, 3.4.7.1, at 2°C, limiting adaptation opportunities and increasing loss and 3.4.8, 3.5.5.8} damage (medium confidence). Migration in small islands (internally and internationally) occurs for multiple reasons and purposes, mostly Global warming of 2°C is expected to pose greater risks to urban for better livelihood opportunities (high confidence) and increasingly areas than global warming of 1.5°C (medium confidence). The owing to sea level rise (medium confidence). {3.3.2.2, 3.3.6–9, extent of risk depends on human vulnerability and the effectiveness 3.4.3.2, 3.4.4.2, 3.4.4.5, 3.4.4.12, 3.4.5.3, 3.4.7.1, 3.4.9.1, 3.5.4.9, of adaptation for regions (coastal and non-coastal), informal Box 3.4, Box 3.5} settlements and infrastructure sectors (such as energy, water and transport) (high confidence). {3.4.5, 3.4.8} Impacts associated with sea level rise and changes to the salinity of coastal groundwater, increased flooding and damage Poverty and disadvantage have increased with recent warming to infrastructure, are projected to be critically important in (about 1°C) and are expected to increase for many populations vulnerable environments, such as small islands, low-lying as average global temperatures increase from 1°C to 1.5°C coasts and deltas, at global warming of 1.5°C and 2°C (high and higher (medium confidence). Outmigration in agricultural- confidence). Localized subsidence and changes to river discharge can dependent communities is positively and statistically significantly potentially exacerbate these effects. Adaptation is already happening associated with global temperature (medium confidence). Our (high confidence) and will remain important over multi-centennial understanding of the links of 1.5°C and 2°C of global warming to time scales. {3.4.5.3, 3.4.5.4, 3.4.5.7, 5.4.5.4, Box 3.5} human migration are limited and represent an important knowledge gap. {3.4.10, 3.4.11, 5.2.2, Table 3.5} Existing and restored natural coastal ecosystems may be effective in reducing the adverse impacts of rising sea levels Key Economic Sectors and Services and intensifying storms by protecting coastal and deltaic regions (medium confidence). Natural sedimentation rates are Risks to global aggregated economic growth due to climate expected to be able to offset the effect of rising sea levels, given change impacts are projected to be lower at 1.5°C than at 2°C the slower rates of sea level rise associated with 1.5°C of warming by the end of this century (medium confidence). {3.5.2, 3.5.3} (medium confidence). Other feedbacks, such as landward migration of wetlands and the adaptation of infrastructure, remain important The largest reductions in economic growth at 2°C compared (medium confidence). {3.4.4.12, 3.4.5.4, 3.4.5.7} to 1.5°C of warming are projected for low- and middle-income countries and regions (the African continent, Southeast Asia, Increased Reasons for Concern India, Brazil and Mexico) (low to medium confidence). Countries in the tropics and Southern Hemisphere subtropics are projected to There are multiple lines of evidence that since AR5 the assessed experience the largest impacts on economic growth due to climate levels of risk increased for four of the five Reasons for Concern 39 Technical Summary (RFCs) for global warming levels of up to 2°C (high confidence). TS.4 Strengthening and Implementing The risk transitions by degrees of global warming are now: from high the Global Response to very high between 1.5°C and 2°C for RFC1 (Unique and threatened systems) (high confidence); from moderate to high risk between 1°C and 1.5°C for RFC2 (Extreme weather events) (medium confidence); from Limiting warming to 1.5°C above pre-industrial levels would moderate to high risk between 1.5°C and 2°C for RFC3 (Distribution of require transformative systemic change, integrated with impacts) (high confidence); from moderate to high risk between 1.5°C sustainable development. Such change would require the and 2.5°C for RFC4 (Global aggregate impacts) (medium confidence); upscaling and acceleration of the implementation of far- and from moderate to high risk between 1°C and 2.5°C for RFC5 reaching, multilevel and cross-sectoral climate mitigation (Large-scale singular events) (medium confidence). {3.5.2} and addressing barriers. Such systemic change would need to be linked to complementary adaptation actions, including 1. The category ‘Unique and threatened systems’ (RFC1) transformational adaptation, especially for pathways that display a transition from high to very high risk which is temporarily overshoot 1.5°C (medium evidence, high agreement) now located between 1.5°C and 2°C of global warming as {Chapter 2, Chapter 3, 4.2.1, 4.4.5, 4.5}. Current national pledges opposed to at 2.6°C of global warming in AR5, owing to new and on mitigation and adaptation are not enough to stay below the Paris TS multiple lines of evidence for changing risks for coral reefs, the Agreement temperature limits and achieve its adaptation goals. While Arctic and biodiversity in general (high confidence). {3.5.2.1} transitions in energy efficiency, carbon intensity of fuels, electrification and land-use change are underway in various countries, limiting 2. In ‘Extreme weather events’ (RFC2), the transition from warming to 1.5°C will require a greater scale and pace of change to moderate to high risk is now located between 1.0°C and transform energy, land, urban and industrial systems globally. {4.3, 4.4, 1.5°C of global warming, which is very similar to the AR5 Cross-Chapter Box 9 in this Chapter} assessment but is projected with greater confidence (medium confidence). The impact literature contains little information Although multiple communities around the world are about the potential for human society to adapt to extreme demonstrating the possibility of implementation consistent with weather events, and hence it has not been possible to locate 1.5°C pathways {Boxes 4.1-4.10}, very few countries, regions, the transition from ‘high’ to ‘very high’ risk within the context of cities, communities or businesses can currently make such assessing impacts at 1.5°C versus 2°C of global warming. There a claim (high confidence). To strengthen the global response, is thus low confidence in the level at which global warming could almost all countries would need to significantly raise their level lead to very high risks associated with extreme weather events in of ambition. Implementation of this raised ambition would the context of this report. {3.5} require enhanced institutional capabilities in all countries, including building the capability to utilize indigenous and 3. With respect to the ‘Distribution of impacts’ (RFC3) a local knowledge (medium evidence, high agreement). In developing transition from moderate to high risk is now located countries and for poor and vulnerable people, implementing the between 1.5°C and 2°C of global warming, compared with response would require financial, technological and other forms of between 1.6°C and 2.6°C global warming in AR5, owing to new support to build capacity, for which additional local, national and evidence about regionally differentiated risks to food security, international resources would need to be mobilized (high confidence). water resources, drought, heat exposure and coastal submergence However, public, financial, institutional and innovation capabilities (high confidence). {3.5} currently fall short of implementing far-reaching measures at scale in all countries (high confidence). Transnational networks that support 4. In ‘global aggregate impacts’ (RFC4) a transition from multilevel climate action are growing, but challenges in their scale-up moderate to high levels of risk is now located between remain. {4.4.1, 4.4.2, 4.4.4, 4.4.5, Box 4.1, Box 4.2, Box 4.7} 1.5°C and 2.5°C of global warming, as opposed to at 3.6°C of warming in AR5, owing to new evidence about global aggregate Adaptation needs will be lower in a 1.5°C world compared to economic impacts and risks to Earth’s biodiversity (medium a 2°C world (high confidence) {Chapter 3; Cross-Chapter Box 11 confidence). {3.5} in this chapter}. Learning from current adaptation practices and strengthening them through adaptive governance {4.4.1}, lifestyle 5. Finally, ‘large-scale singular events’ (RFC5), moderate risk and behavioural change {4.4.3} and innovative financing mechanisms is now located at 1°C of global warming and high risk is {4.4.5} can help their mainstreaming within sustainable development located at 2.5°C of global warming, as opposed to at 1.6°C practices. Preventing maladaptation, drawing on bottom-up approaches (moderate risk) and around 4°C (high risk) in AR5, because of new {Box 4.6} and using indigenous knowledge {Box 4.3} would effectively observations and models of the West Antarctic ice sheet (medium engage and protect vulnerable people and communities. While confidence). {3.3.9, 3.5.2, 3.6.3} adaptation finance has increased quantitatively, significant further expansion would be needed to adapt to 1.5°C. Qualitative gaps in the distribution of adaptation finance, readiness to absorb resources, and monitoring mechanisms undermine the potential of adaptation finance to reduce impacts. {Chapter 3, 4.4.2, 4.4.5, 4.6} 40 Technical Summary System Transitions existing agricultural systems generally reduces the emissions intensity of food production and offers strong synergies with rural development, The energy system transition that would be required to limit poverty reduction and food security objectives, but options to reduce global warming to 1.5°C above pre-industrial conditions is absolute emissions are limited unless paired with demand-side underway in many sectors and regions around the world measures. Technological innovation including biotechnology, with (medium evidence, high agreement). The political, economic, social adequate safeguards, could contribute to resolving current feasibility and technical feasibility of solar energy, wind energy and electricity constraints and expand the future mitigation potential of agriculture. storage technologies has improved dramatically over the past few {4.3.2, 4.4.4} years, while that of nuclear energy and carbon dioxide capture and storage (CCS) in the electricity sector have not shown similar Shifts in dietary choices towards foods with lower emissions improvements. {4.3.1} and requirements for land, along with reduced food loss and waste, could reduce emissions and increase adaptation options Electrification, hydrogen, bio-based feedstocks and substitution, (high confidence). Decreasing food loss and waste and changing and, in several cases, carbon dioxide capture, utilization and dietary behaviour could result in mitigation and adaptation (high storage (CCUS) would lead to the deep emissions reductions confidence) by reducing both emissions and pressure on land, with required in energy-intensive industries to limit warming to significant co-benefits for food security, human health and sustainable TS 1.5°C. However, those options are limited by institutional, economic and development {4.3.2, 4.4.5, 4.5.2, 4.5.3, 5.4.2}, but evidence of technical constraints, which increase financial risks to many incumbent successful policies to modify dietary choices remains limited. firms (medium evidence, high agreement). Energy efficiency in industry is more economically feasible and helps enable industrial system Mitigation and Adaptation Options and Other Measures transitions but would have to be complemented with greenhouse gas (GHG)-neutral processes or carbon dioxide removal (CDR) to make A mix of mitigation and adaptation options implemented in a energy-intensive industries consistent with 1.5°C (high confidence). participatory and integrated manner can enable rapid, systemic {4.3.1, 4.3.4} transitions – in urban and rural areas – that are necessary elements of an accelerated transition consistent with limiting Global and regional land-use and ecosystems transitions and warming to 1.5°C. Such options and changes are most effective associated changes in behaviour that would be required to when aligned with economic and sustainable development, limit warming to 1.5°C can enhance future adaptation and and when local and regional governments are supported by land-based agricultural and forestry mitigation potential. Such national governments {4.3.3, 4.4.1, 4.4.3}. Various mitigation transitions could, however, carry consequences for livelihoods options are expanding rapidly across many geographies. Although that depend on agriculture and natural resources {4.3.2, Cross- many have development synergies, not all income groups have so Chapter Box 6 in Chapter 3}. Alterations of agriculture and forest far benefited from them. Electrification, end-use energy efficiency systems to achieve mitigation goals could affect current ecosystems and increased share of renewables, amongst other options, are and their services and potentially threaten food, water and livelihood lowering energy use and decarbonizing energy supply in the built security. While this could limit the social and environmental feasibility environment, especially in buildings. Other rapid changes needed in of land-based mitigation options, careful design and implementation urban environments include demotorization and decarbonization of could enhance their acceptability and support sustainable development transport, including the expansion of electric vehicles, and greater use objectives (medium evidence, medium agreement). {4.3.2, 4.5.3} of energy-efficient appliances (medium evidence, high agreement). Technological and social innovations can contribute to limiting Changing agricultural practices can be an effective climate warming to 1.5°C, for example, by enabling the use of smart grids, adaptation strategy. A diversity of adaptation options exists, energy storage technologies and general-purpose technologies, such including mixed crop-livestock production systems which can be a as information and communication technology (ICT) that can be cost-effective adaptation strategy in many global agriculture systems deployed to help reduce emissions. Feasible adaptation options include (robust evidence, medium agreement). Improving irrigation efficiency green infrastructure, resilient water and urban ecosystem services, could effectively deal with changing global water endowments, urban and peri-urban agriculture, and adapting buildings and land use especially if achieved via farmers adopting new behaviours and water- through regulation and planning (medium evidence, medium to high efficient practices rather than through large-scale infrastructural agreement). {4.3.3, 4.4.3, 4.4.4} interventions (medium evidence, medium agreement). Well-designed adaptation processes such as community-based adaptation can be Synergies can be achieved across systemic transitions through effective depending upon context and levels of vulnerability. {4.3.2, several overarching adaptation options in rural and urban areas. 4.5.3} Investments in health, social security and risk sharing and spreading are cost-effective adaptation measures with high potential for scaling Improving the efficiency of food production and closing yield up (medium evidence, medium to high agreement). Disaster risk gaps have the potential to reduce emissions from agriculture, management and education-based adaptation have lower prospects of reduce pressure on land, and enhance food security and future scalability and cost-effectiveness (medium evidence, high agreement) mitigation potential (high confidence). Improving productivity of but are critical for building adaptive capacity. {4.3.5, 4.5.3} 41 Technical Summary Converging adaptation and mitigation options can lead to understanding about their effectiveness to limit global warming; and synergies and potentially increase cost-effectiveness, but a weak capacity to govern, legitimize, and scale such measures. Some multiple trade-offs can limit the speed of and potential for recent model-based analysis suggests SRM would be effective but that scaling up. Many examples of synergies and trade-offs exist in it is too early to evaluate its feasibility. Even in the uncertain case that all sectors and system transitions. For instance, sustainable water the most adverse side-effects of SRM can be avoided, public resistance, management (high evidence, medium agreement) and investment in ethical concerns and potential impacts on sustainable development green infrastructure (medium evidence, high agreement) to deliver could render SRM economically, socially and institutionally undesirable sustainable water and environmental services and to support urban (low agreement, medium evidence). {4.3.8, Cross-Chapter Box 10 in agriculture are less cost-effective than other adaptation options but this chapter} can help build climate resilience. Achieving the governance, finance and social support required to enable these synergies and to avoid Enabling Rapid and Far-Reaching Change trade-offs is often challenging, especially when addressing multiple objectives, and attempting appropriate sequencing and timing of The speed of transitions and of technological change required interventions. {4.3.2, 4.3.4, 4.4.1, 4.5.2, 4.5.3, 4.5.4} to limit warming to 1.5°C above pre-industrial levels has been observed in the past within specific sectors and technologies TS Though CO2 dominates long-term warming, the reduction of {4.2.2.1}. But the geographical and economic scales at which warming short-lived climate forcers (SLCFs), such as methane the required rates of change in the energy, land, urban, and black carbon, can in the short term contribute significantly to infrastructure and industrial systems would need to take place limiting warming to 1.5°C above pre-industrial levels. Reductions are larger and have no documented historic precedent (limited of black carbon and methane would have substantial co-benefits evidence, medium agreement). To reduce inequality and alleviate (high confidence), including improved health due to reduced air poverty, such transformations would require more planning and pollution. This, in turn, enhances the institutional and socio- stronger institutions (including inclusive markets) than observed in the cultural feasibility of such actions. Reductions of several warming past, as well as stronger coordination and disruptive innovation across SLCFs are constrained by economic and social feasibility (low evidence, actors and scales of governance. {4.3, 4.4} high agreement). As they are often co-emitted with CO2, achieving the energy, land and urban transitions necessary to limit warming to 1.5°C Governance consistent with limiting warming to 1.5°C and the would see emissions of warming SLCFs greatly reduced. {2.3.3.2, 4.3.6} political economy of adaptation and mitigation can enable and accelerate systems transitions, behavioural change, innovation and Most CDR options face multiple feasibility constraints, which technology deployment (medium evidence, medium agreement). differ between options, limiting the potential for any single For 1.5°C-consistent actions, an effective governance framework option to sustainably achieve the large-scale deployment would include: accountable multilevel governance that includes non- required in the 1.5°C-consistent pathways described in state actors, such as industry, civil society and scientific institutions; Chapter 2 (high confidence). Those 1.5°C pathways typically rely coordinated sectoral and cross-sectoral policies that enable collaborative on bioenergy with carbon capture and storage (BECCS), afforestation multi-stakeholder partnerships; strengthened global-to-local financial and reforestation (AR), or both, to neutralize emissions that are architecture that enables greater access to finance and technology; expensive to avoid, or to draw down CO2 emissions in excess of the addressing climate-related trade barriers; improved climate education carbon budget {Chapter 2}. Though BECCS and AR may be technically and greater public awareness; arrangements to enable accelerated and geophysically feasible, they face partially overlapping yet different behaviour change; strengthened climate monitoring and evaluation constraints related to land use. The land footprint per tonne of CO2 systems; and reciprocal international agreements that are sensitive removed is higher for AR than for BECCS, but given the low levels of to equity and the Sustainable Development Goals (SDGs). System current deployment, the speed and scales required for limiting warming transitions can be enabled by enhancing the capacities of public, private to 1.5°C pose a considerable implementation challenge, even if the and financial institutions to accelerate climate change policy planning issues of public acceptance and absence of economic incentives were and implementation, along with accelerated technological innovation, to be resolved (high agreement, medium evidence). The large potential deployment and upkeep. {4.4.1, 4.4.2, 4.4.3, 4.4.4} of afforestation and the co-benefits if implemented appropriately (e.g., on biodiversity and soil quality) will diminish over time, as forests Behaviour change and demand-side management can saturate (high confidence). The energy requirements and economic significantly reduce emissions, substantially limiting the costs of direct air carbon capture and storage (DACCS) and enhanced reliance on CDR to limit warming to 1.5°C {Chapter 2, 4.4.3}. weathering remain high (medium evidence, medium agreement). At the Political and financial stakeholders may find climate actions more cost- local scale, soil carbon sequestration has co-benefits with agriculture effective and socially acceptable if multiple factors affecting behaviour and is cost-effective even without climate policy (high confidence). Its are considered, including aligning these actions with people’s core potential feasibility and cost-effectiveness at the global scale appears values (medium evidence, high agreement). Behaviour- and lifestyle- to be more limited. {4.3.7} related measures and demand-side management have already led to emission reductions around the world and can enable significant Uncertainties surrounding solar radiation modification future reductions (high confidence). Social innovation through bottom- (SRM) measures constrain their potential deployment. These up initiatives can result in greater participation in the governance of uncertainties include: technological immaturity; limited physical systems transitions and increase support for technologies, practices 42 Technical Summary and policies that are part of the global response to limit warming to would help redirect capital away from potentially stranded assets 1.5°C . {Chapter 2, 4.4.1, 4.4.3, Figure 4.3} (medium evidence, medium agreement). {4.4.5} This rapid and far-reaching response required to keep warming Knowledge Gaps below 1.5°C and enhance the capacity to adapt to climate risks would require large increases of investments in low-emission Knowledge gaps around implementing and strengthening the infrastructure and buildings, along with a redirection of financial global response to climate change would need to be urgently flows towards low-emission investments (robust evidence, high resolved if the transition to a 1.5°C world is to become reality. agreement). An estimated mean annual incremental investment of Remaining questions include: how much can be realistically expected around 1.5% of global gross fixed capital formation (GFCF) for the from innovation and behavioural and systemic political and economic energy sector is indicated between 2016 and 2035, as well as about changes in improving resilience, enhancing adaptation and reducing 2.5% of global GFCF for other development infrastructure that could GHG emissions? How can rates of changes be accelerated and scaled also address SDG implementation. Though quality policy design and up? What is the outcome of realistic assessments of mitigation and effective implementation may enhance efficiency, they cannot fully adaptation land transitions that are compliant with sustainable substitute for these investments. {2.5.2, 4.2.1, 4.4.5} development, poverty eradication and addressing inequality? What are life-cycle emissions and prospects of early-stage CDR options? How TS Enabling this investment requires the mobilization and better can climate and sustainable development policies converge, and how integration of a range of policy instruments that include the can they be organised within a global governance framework and reduction of socially inefficient fossil fuel subsidy regimes and innovative financial system, based on principles of justice and ethics (including price and non-price national and international policy instruments. These ‘common but differentiated responsibilities and respective capabilities’ would need to be complemented by de-risking financial instruments (CBDR-RC)), reciprocity and partnership? To what extent would and the emergence of long-term low-emission assets. These instruments limiting warming to 1.5°C require a harmonization of macro-financial would aim to reduce the demand for carbon-intensive services and shift and fiscal policies, which could include financial regulators such as market preferences away from fossil fuel-based technology. Evidence central banks? How can different actors and processes in climate and theory suggest that carbon pricing alone, in the absence of governance reinforce each other, and hedge against the fragmentation sufficient transfers to compensate their unintended distributional cross- of initiatives? {4.1, 4.3.7, 4.4.1, 4.4.5, 4.6} sector, cross-nation effects, cannot reach the incentive levels needed to trigger system transitions (robust evidence, medium agreement). But, embedded in consistent policy packages, they can help mobilize incremental resources and provide flexible mechanisms that help reduce the social and economic costs of the triggering phase of the transition (robust evidence, medium agreement). {4.4.3, 4.4.4, 4.4.5} Increasing evidence suggests that a climate-sensitive realignment of savings and expenditure towards low-emission, climate-resilient infrastructure and services requires an evolution of global and national financial systems. Estimates suggest that, in addition to climate-friendly allocation of public investments, a potential redirection of 5% to 10% of the annual capital revenues5 is necessary for limiting warming to 1.5°C {4.4.5, Table 1 in Box 4.8}. This could be facilitated by a change of incentives for private day-to-day expenditure and the redirection of savings from speculative and precautionary investments towards long- term productive low-emission assets and services. This implies the mobilization of institutional investors and mainstreaming of climate finance within financial and banking system regulation. Access by developing countries to low-risk and low-interest finance through multilateral and national development banks would have to be facilitated (medium evidence, high agreement). New forms of public– private partnerships may be needed with multilateral, sovereign and sub-sovereign guarantees to de-risk climate-friendly investments, support new business models for small-scale enterprises and help households with limited access to capital. Ultimately, the aim is to promote a portfolio shift towards long-term low-emission assets that 5 Annual capital revenues are the paid interests plus the increase of the asset value. 43 Technical Summary TS.5 Sustainable Development, Poverty confidence). Many strategies for sustainable development enable Eradication and Reducing Inequalities transformational adaptation for a 1.5°C warmer world, provided attention is paid to reducing poverty in all its forms and to promoting equity and participation in decision-making (medium evidence, high This chapter takes sustainable development as the starting point and agreement). As such, sustainable development has the potential focus for analysis. It considers the broad and multifaceted bi-directional to significantly reduce systemic vulnerability, enhance adaptive interplay between sustainable development, including its focus on capacity, and promote livelihood security for poor and disadvantaged eradicating poverty and reducing inequality in their multidimensional populations (high confidence). {5.3.1} aspects, and climate actions in a 1.5°C warmer world. These fundamental connections are embedded in the Sustainable Development Goals Synergies between adaptation strategies and the SDGs are (SDGs). The chapter also examines synergies and trade-offs of expected to hold true in a 1.5°C warmer world, across sectors adaptation and mitigation options with sustainable development and and contexts (medium evidence, medium agreement). Synergies the SDGs and offers insights into possible pathways, especially climate- between adaptation and sustainable development are significant resilient development pathways towards a 1.5°C warmer world. for agriculture and health, advancing SDGs 1 (extreme poverty), 2 (hunger), 3 (healthy lives and well-being) and 6 (clean water) (robust TS Sustainable Development, Poverty and Inequality evidence, medium agreement). {5.3.2} Ecosystem- and community- in a 1.5°C Warmer World based adaptation, along with the incorporation of indigenous and local knowledge, advances synergies with SDGs 5 (gender equality), Limiting global warming to 1.5°C rather than 2°C above pre- 10 (reducing inequalities) and 16 (inclusive societies), as exemplified industrial levels would make it markedly easier to achieve many in drylands and the Arctic (high evidence, medium agreement). {5.3.2, aspects of sustainable development, with greater potential to Box 5.1, Cross-Chapter Box 10 in Chapter 4} eradicate poverty and reduce inequalities (medium evidence, high agreement). Impacts avoided with the lower temperature Adaptation strategies can result in trade-offs with and among limit could reduce the number of people exposed to climate risks and the SDGs (medium evidence, high agreement). Strategies that vulnerable to poverty by 62 to 457 million, and lessen the risks of advance one SDG may create negative consequences for other poor people to experience food and water insecurity, adverse health SDGs, for instance SDGs 3 (health) versus 7 (energy consumption) impacts, and economic losses, particularly in regions that already face and agricultural adaptation and SDG 2 (food security) versus SDGs 3 development challenges (medium evidence, medium agreement). (health), 5 (gender equality), 6 (clean water), 10 (reducing inequalities), {5.2.2, 5.2.3} Avoided impacts expected to occur between 1.5°C and 14 (life below water) and 15 (life on the land) (medium evidence, 2°C warming would also make it easier to achieve certain SDGs, such as medium agreement). {5.3.2} those that relate to poverty, hunger, health, water and sanitation, cities and ecosystems (SDGs 1, 2, 3, 6, 11, 14 and 15) (medium evidence, Pursuing place-specific adaptation pathways towards a 1.5°C high agreement). {5.2.3, Table 5.2 available at the end of the chapter} warmer world has the potential for significant positive outcomes for well-being in countries at all levels of development (medium Compared to current conditions, 1.5°C of global warming would evidence, high agreement). Positive outcomes emerge when nonetheless pose heightened risks to eradicating poverty, adaptation pathways (i) ensure a diversity of adaptation options based reducing inequalities and ensuring human and ecosystem well- on people’s values and the trade-offs they consider acceptable, (ii) being (medium evidence, high agreement). Warming of 1.5°C is maximize synergies with sustainable development through inclusive, not considered ‘safe’ for most nations, communities, ecosystems and participatory and deliberative processes, and (iii) facilitate equitable sectors and poses significant risks to natural and human systems as transformation. Yet such pathways would be difficult to achieve compared to the current warming of 1°C (high confidence). {Cross- without redistributive measures to overcome path dependencies, Chapter Box 12 in Chapter 5} The impacts of 1.5°C of warming would uneven power structures, and entrenched social inequalities (medium disproportionately affect disadvantaged and vulnerable populations evidence, high agreement). {5.3.3} through food insecurity, higher food prices, income losses, lost livelihood opportunities, adverse health impacts and population Mitigation and Sustainable Development displacements (medium evidence, high agreement). {5.2.1} Some of the worst impacts on sustainable development are expected to be The deployment of mitigation options consistent with 1.5°C felt among agricultural and coastal dependent livelihoods, indigenous pathways leads to multiple synergies across a range of people, children and the elderly, poor labourers, poor urban dwellers in sustainable development dimensions. At the same time, the African cities, and people and ecosystems in the Arctic and Small Island rapid pace and magnitude of change that would be required Developing States (SIDS) (medium evidence, high agreement). {5.2.1, to limit warming to 1.5°C, if not carefully managed, would lead Box 5.3, Chapter 3, Box 3.5, Cross-Chapter Box 9 in Chapter 4} to trade-offs with some sustainable development dimensions (high confidence). The number of synergies between mitigation Climate Adaptation and Sustainable Development response options and sustainable development exceeds the number of trade-offs in energy demand and supply sectors; agriculture, forestry Prioritization of sustainable development and meeting the and other land use (AFOLU); and for oceans (very high confidence). SDGs is consistent with efforts to adapt to climate change (high {Figure 5.2, Table 5.2 available at the end of the chapter} The 1.5°C 44 Technical Summary pathways indicate robust synergies, particularly for the SDGs 3 (health), evidence, high agreement). {5.4.1.2, Box 5.2} Targeted policies that 7 (energy), 12 (responsible consumption and production) and 14 promote diversification of the economy and the energy sector could (oceans) (very high confidence). {5.4.2, Figure 5.3} For SDGs 1 (poverty), ease this transition (medium evidence, high agreement). {5.4.1.2, 2 (hunger), 6 (water) and 7 (energy), there is a risk of trade-offs or Box 5.2} negative side effects from stringent mitigation actions compatible with 1.5°C of warming (medium evidence, high agreement). {5.4.2} Sustainable Development Pathways to 1.5°C Appropriately designed mitigation actions to reduce energy Sustainable development broadly supports and often enables demand can advance multiple SDGs simultaneously. Pathways the fundamental societal and systems transformations that compatible with 1.5°C that feature low energy demand show the would be required for limiting warming to 1.5°C above pre- most pronounced synergies and the lowest number of trade-offs industrial levels (high confidence). Simulated pathways that with respect to sustainable development and the SDGs (very high feature the most sustainable worlds (e.g., Shared Socio-Economic confidence). Accelerating energy efficiency in all sectors has synergies Pathways (SSP) 1) are associated with relatively lower mitigation and with SDGs 7 (energy), 9 (industry, innovation and infrastructure), adaptation challenges and limit warming to 1.5°C at comparatively 11 (sustainable cities and communities), 12 (responsible consumption lower mitigation costs. In contrast, development pathways with high and production), 16 (peace, justice and strong institutions), and fragmentation, inequality and poverty (e.g., SSP3) are associated with TS 17 (partnerships for the goals) (robust evidence, high agreement). comparatively higher mitigation and adaptation challenges. In such {5.4.1, Figure 5.2, Table 5.2} Low-demand pathways, which would pathways, it is not possible to limit warming to 1.5°C for the vast reduce or completely avoid the reliance on bioenergy with carbon majority of the integrated assessment models (medium evidence, capture and storage (BECCS) in 1.5°C pathways, would result in high agreement). {5.5.2} In all SSPs, mitigation costs substantially significantly reduced pressure on food security, lower food prices and increase in 1.5°C pathways compared to 2°C pathways. No pathway fewer people at risk of hunger (medium evidence, high agreement). in the literature integrates or achieves all 17 SDGs (high confidence). {5.4.2, Figure 5.3} {5.5.2} Real-world experiences at the project level show that the actual integration between adaptation, mitigation and sustainable The impacts of carbon dioxide removal options on SDGs depend development is challenging as it requires reconciling trade-offs across on the type of options and the scale of deployment (high sectors and spatial scales (very high confidence). {5.5.1} confidence). If poorly implemented, carbon dioxide removal (CDR) options such as bioenergy, BECCS and AFOLU would lead to trade- Without societal transformation and rapid implementation offs. Appropriate design and implementation requires considering of ambitious greenhouse gas reduction measures, pathways local people’s needs, biodiversity and other sustainable development to limiting warming to 1.5°C and achieving sustainable dimensions (very high confidence). {5.4.1.3, Cross-Chapter Box 7 in development will be exceedingly difficult, if not impossible, Chapter 3} to achieve (high confidence). The potential for pursuing such pathways differs between and within nations and regions, due to The design of the mitigation portfolios and policy instruments different development trajectories, opportunities and challenges (very to limit warming to 1.5°C will largely determine the overall high confidence). {5.5.3.2, Figure 5.1} Limiting warming to 1.5°C synergies and trade-offs between mitigation and sustainable would require all countries and non-state actors to strengthen their development (very high confidence). Redistributive policies contributions without delay. This could be achieved through sharing that shield the poor and vulnerable can resolve trade-offs for efforts based on bolder and more committed cooperation, with support a range of SDGs (medium evidence, high agreement). Individual for those with the least capacity to adapt, mitigate and transform mitigation options are associated with both positive and negative (medium evidence, high agreement). {5.5.3.1, 5.5.3.2} Current interactions with the SDGs (very high confidence). {5.4.1} However, efforts towards reconciling low-carbon trajectories and reducing appropriate choices across the mitigation portfolio can help to inequalities, including those that avoid difficult trade-offs associated maximize positive side effects while minimizing negative side effects with transformation, are partially successful yet demonstrate notable (high confidence). {5.4.2, 5.5.2} Investment needs for complementary obstacles (medium evidence, medium agreement). {5.5.3.3, Box 5.3, policies resolving trade-offs with a range of SDGs are only a small Cross-Chapter Box 13 in this chapter} fraction of the overall mitigation investments in 1.5°C pathways (medium evidence, high agreement). {5.4.2, Figure 5.4} Integration of Social justice and equity are core aspects of climate-resilient mitigation with adaptation and sustainable development compatible development pathways for transformational social change. with 1.5°C warming requires a systems perspective (high confidence). Addressing challenges and widening opportunities between {5.4.2, 5.5.2} and within countries and communities would be necessary to achieve sustainable development and limit warming to Mitigation consistent with 1.5°C of warming create high risks 1.5°C, without making the poor and disadvantaged worse off for sustainable development in countries with high dependency (high confidence). Identifying and navigating inclusive and socially on fossil fuels for revenue and employment generation (high acceptable pathways towards low-carbon, climate-resilient futures is a confidence). These risks are caused by the reduction of global demand challenging yet important endeavour, fraught with moral, practical and affecting mining activity and export revenues and challenges to rapidly political difficulties and inevitable trade-offs (very high confidence). decrease high carbon intensity of the domestic economy (robust {5.5.2, 5.5.3.3, Box 5.3} It entails deliberation and problem-solving 45 Technical Summary processes to negotiate societal values, well-being, risks and resilience and to determine what is desirable and fair, and to whom (medium evidence, high agreement). Pathways that encompass joint, iterative planning and transformative visions, for instance in Pacific SIDS like Vanuatu and in urban contexts, show potential for liveable and sustainable futures (high confidence). {5.5.3.1, 5.5.3.3, Figure 5.5, Box 5.3, Cross-Chapter Box 13 in this chapter} The fundamental societal and systemic changes to achieve sustainable development, eradicate poverty and reduce inequalities while limiting warming to 1.5°C would require meeting a set of institutional, social, cultural, economic and technological conditions (high confidence). The coordination and monitoring of policy actions across sectors and spatial scales is essential to support sustainable development in 1.5°C warmer TS conditions (very high confidence). {5.6.2, Box 5.3} External funding and technology transfer better support these efforts when they consider recipients’ context-specific needs (medium evidence, high agreement). {5.6.1} Inclusive processes can facilitate transformations by ensuring participation, transparency, capacity building and iterative social learning (high confidence). {5.5.3.3, Cross-Chapter Box 13, 5.6.3} Attention to power asymmetries and unequal opportunities for development, among and within countries, is key to adopting 1.5°C-compatible development pathways that benefit all populations (high confidence). {5.5.3, 5.6.4, Box 5.3} Re-examining individual and collective values could help spur urgent, ambitious and cooperative change (medium evidence, high agreement). {5.5.3, 5.6.5} 46 Chapters 1 Framing and Context Coordinating Lead Authors: Myles R. Allen (UK), Opha Pauline Dube (Botswana), William Solecki (USA) Lead Authors: Fernando Aragón-Durand (Mexico), Wolfgang Cramer (France/Germany), Stephen Humphreys (UK/ Ireland), Mikiko Kainuma (Japan), Jatin Kala (Australia), Natalie Mahowald (USA), Yacob Mulugetta (UK/Ethiopia), Rosa Perez (Philippines), Morgan Wairiu (Solomon Islands), Kirsten Zickfeld (Canada/ Germany) Contributing Authors: Purnamita Dasgupta (India), Haile Eakin (USA), Bronwyn Hayward (New Zealand), Diana Liverman (USA), Richard Millar (UK), Graciela Raga (Mexico/Argentina), Aurélien Ribes (France), Mark Richardson (USA/UK), Maisa Rojas (Chile), Roland Séférian (France), Sonia I. Seneviratne (Switzerland), Christopher Smith (UK), Will Steffen (Australia), Peter Thorne (Ireland/UK) Chapter Scientist: Richard Millar (UK) Review Editors: Ismail Elgizouli Idris (Sudan), Andreas Fischlin (Switzerland), Xuejie Gao (China) This chapter should be cited as: Allen, M.R., O.P. Dube, W. Solecki, F. Aragón-Durand, W. Cramer, S. Humphreys, M. Kainuma, J. Kala, N. Mahowald, Y. Mulugetta, R. Perez, M. Wairiu, and K. Zickfeld, 2018: Framing and Context. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)]. In Press. 49 Chapter 1 Framing and Context Table of Contents Executive Summary .....................................................................51 1.5 Assessment Frameworks and Emerging Methodologies that Integrate Climate Change Mitigation and Adaptation 1.1 Assessing the Knowledge Base 1 with Sustainable Development ..................................75 for a 1.5°C Warmer World ............................................53 1.5.1 Knowledge Sources and Evidence Box 1.1: The Anthropocene: Strengthening the Used in the Report .......................................................75 Global Response to 1.5°C Global Warming ............................54 1.5.2 Assessment Frameworks and Methodologies ...............76 1.1.1 Equity and a 1.5°C Warmer World ................................54 1.1.2 Eradication of Poverty ..................................................55 1.6 Confidence, Uncertainty and Risk ..............................77 1.1.3 Sustainable Development and a 1.5°C Warmer World ..............................................................55 1.7 Storyline of the Report .................................................77 1.2 Understanding 1.5°C: Reference Levels, Probability, Transience, Overshoot, and Stabilization .............................................................56 Frequently Asked Questions 1.2.1 Working Definitions of 1.5°C and 2°C Warming Relative to Pre-Industrial Levels ....................56 FAQ 1.1: Why are we Talking about 1.5°C? ........................ 79 1.2.2 Global versus Regional and Seasonal Warming ............59 FAQ 1.2: How Close are we to 1.5°C? ................................. 81 1.2.3 Definition of 1.5°C Pathways: Probability, Transience, Stabilization and Overshoot .......................59 Cross-Chapter Box 1: Scenarios and Pathways ......................62 References .....................................................................................83 1.2.4 Geophysical Warming Commitment .............................64 Cross-Chapter Box 2: Measuring Progress to Net Zero Emissions Combining Long-Lived and Short-Lived Climate Forcers ..........................................................................66 1.3 Impacts at 1.5°C and Beyond .....................................68 1.3.1 Definitions ....................................................................68 1.3.2 Drivers of Impacts ........................................................69 1.3.3 Uncertainty and Non-Linearity of Impacts ....................69 1.4 Strengthening the Global Response .........................70 1.4.1 Classifying Response Options .......................................70 1.4.2 Governance, Implementation and Policies ....................71 Cross-Chapter Box 3: Framing Feasibility: Key Concepts and Conditions for Limiting Global Temperature Increases to 1.5°C ..................................71 1.4.3 Transformation, Transformation Pathways, and Transition: Evaluating Trade-Offs and Synergies Between Mitigation, Adaptation and Sustainable Development Goals ............................73 Cross-Chapter Box 4: Sustainable Development and the Sustainable Development Goals ...............................73 50 Framing and Context Chapter 1 Executive Summary an overshoot. Overshoot pathways are characterized by the peak magnitude of the overshoot, which may have implications for impacts. All 1.5°C pathways involve limiting cumulative emissions This chapter frames the context, knowledge-base and assessment of long-lived greenhouse gases, including carbon dioxide and nitrous approaches used to understand the impacts of 1.5°C global warming oxide, and substantial reductions in other climate forcers (high above pre-industrial levels and related global greenhouse gas confidence). Limiting cumulative emissions requires either reducing emission pathways, building on the IPCC Fifth Assessment Report net global emissions of long-lived greenhouse gases to zero before 1 (AR5), in the context of strengthening the global response to the the cumulative limit is reached, or net negative global emissions threat of climate change, sustainable development and efforts to (anthropogenic removals) after the limit is exceeded. {1.2.3, 1.2.4, eradicate poverty. Cross-Chapter Boxes 1 and 2} Human-induced warming reached approximately 1°C (likely This report assesses projected impacts at a global average between 0.8°C and 1.2°C) above pre-industrial levels in 2017, warming of 1.5°C and higher levels of warming. Global warming increasing at 0.2°C (likely between 0.1°C and 0.3°C) per of 1.5°C is associated with global average surface temperatures decade (high confidence). Global warming is defined in this report fluctuating naturally on either side of 1.5°C, together with warming as an increase in combined surface air and sea surface temperatures substantially greater than 1.5°C in many regions and seasons (high averaged over the globe and over a 30-year period. Unless otherwise confidence), all of which must be considered in the assessment of specified, warming is expressed relative to the period 1850–1900, impacts. Impacts at 1.5°C of warming also depend on the emission used as an approximation of pre-industrial temperatures in AR5. pathway to 1.5°C. Very different impacts result from pathways For periods shorter than 30 years, warming refers to the estimated that remain below 1.5°C versus pathways that return to 1.5°C average temperature over the 30 years centred on that shorter after a substantial overshoot, and when temperatures stabilize at period, accounting for the impact of any temperature fluctuations 1.5°C versus a transient warming past 1.5°C (medium confidence). or trend within those 30 years. Accordingly, warming from pre- {1.2.3, 1.3} industrial levels to the decade 2006–2015 is assessed to be 0.87°C (likely between 0.75°C and 0.99°C). Since 2000, the estimated level Ethical considerations, and the principle of equity in particular, of human-induced warming has been equal to the level of observed are central to this report, recognizing that many of the impacts warming with a likely range of ±20% accounting for uncertainty due of warming up to and beyond 1.5°C, and some potential to contributions from solar and volcanic activity over the historical impacts of mitigation actions required to limit warming to period (high confidence). {1.2.1} 1.5°C, fall disproportionately on the poor and vulnerable (high confidence). Equity has procedural and distributive dimensions and Warming greater than the global average has already been requires fairness in burden sharing both between generations and experienced in many regions and seasons, with higher average between and within nations. In framing the objective of holding the warming over land than over the ocean (high confidence). Most increase in the global average temperature rise to well below 2°C land regions are experiencing greater warming than the global average, above pre-industrial levels, and to pursue efforts to limit warming to while most ocean regions are warming at a slower rate. Depending 1.5°C, the Paris Agreement associates the principle of equity with the on the temperature dataset considered, 20–40% of the global human broader goals of poverty eradication and sustainable development, population live in regions that, by the decade 2006–2015, had already recognising that effective responses to climate change require a experienced warming of more than 1.5°C above pre-industrial in at global collective effort that may be guided by the 2015 United least one season (medium confidence). {1.2.1, 1.2.2} Nations Sustainable Development Goals. {1.1.1} Past emissions alone are unlikely to raise global-mean Climate adaptation refers to the actions taken to manage temperature to 1.5°C above pre-industrial levels (medium impacts of climate change by reducing vulnerability and confidence), but past emissions do commit to other changes, exposure to its harmful effects and exploiting any potential such as further sea level rise (high confidence). If all benefits. Adaptation takes place at international, national and anthropogenic emissions (including aerosol-related) were reduced local levels. Subnational jurisdictions and entities, including urban to zero immediately, any further warming beyond the 1°C already and rural municipalities, are key to developing and reinforcing experienced would likely be less than 0.5°C over the next two to measures for reducing weather- and climate-related risks. Adaptation three decades (high confidence), and likely less than 0.5°C on a implementation faces several barriers including lack of up-to-date and century time scale (medium confidence), due to the opposing effects locally relevant information, lack of finance and technology, social of different climate processes and drivers. A warming greater than values and attitudes, and institutional constraints (high confidence). 1.5°C is therefore not geophysically unavoidable: whether it will Adaptation is more likely to contribute to sustainable development occur depends on future rates of emission reductions. {1.2.3, 1.2.4} when policies align with mitigation and poverty eradication goals (medium confidence). {1.1, 1.4} 1.5°C emission pathways are defined as those that, given current knowledge of the climate response, provide a one- Ambitious mitigation actions are indispensable to limit in-two to two-in-three chance of warming either remaining warming to 1.5°C while achieving sustainable development below 1.5°C or returning to 1.5°C by around 2100 following and poverty eradication (high confidence). Ill-designed responses, 51 Chapter 1 Framing and Context however, could pose challenges especially – but not exclusively – for countries and regions contending with poverty and those requiring significant transformation of their energy systems. This report focuses on ‘climate-resilient development pathways’, which aim to meet the goals of sustainable development, including climate adaptation and mitigation, poverty eradication and reducing inequalities. But any 1 feasible pathway that remains within 1.5°C involves synergies and trade-offs (high confidence). Significant uncertainty remains as to which pathways are more consistent with the principle of equity. {1.1.1, 1.4} Multiple forms of knowledge, including scientific evidence, narrative scenarios and prospective pathways, inform the understanding of 1.5°C. This report is informed by traditional evidence of the physical climate system and associated impacts and vulnerabilities of climate change, together with knowledge drawn from the perceptions of risk and the experiences of climate impacts and governance systems. Scenarios and pathways are used to explore conditions enabling goal-oriented futures while recognizing the significance of ethical considerations, the principle of equity, and the societal transformation needed. {1.2.3, 1.5.2} There is no single answer to the question of whether it is feasible to limit warming to 1.5°C and adapt to the consequences. Feasibility is considered in this report as the capacity of a system as a whole to achieve a specific outcome. The global transformation that would be needed to limit warming to 1.5°C requires enabling conditions that reflect the links, synergies and trade-offs between mitigation, adaptation and sustainable development. These enabling conditions are assessed across many dimensions of feasibility – geophysical, environmental-ecological, technological, economic, socio-cultural and institutional – that may be considered through the unifying lens of the Anthropocene, acknowledging profound, differential but increasingly geologically significant human influences on the Earth system as a whole. This framing also emphasises the global interconnectivity of past, present and future human–environment relations, highlighting the need and opportunities for integrated responses to achieve the goals of the Paris Agreement. {1.1, Cross-Chapter Box 1} 52 Framing and Context Chapter 1 1.1 Assessing the Knowledge Base non-climatic factors (IPCC, 2014a). Global economic growth has been for a 1.5°C Warmer World accompanied by increased life expectancy and income in much of the world; however, in addition to environmental degradation and pollution, many regions remain characterised by significant poverty Human influence on climate has been the dominant cause of observed and severe inequality in income distribution and access to resources, warming since the mid-20th century, while global average surface amplifying vulnerability to climate change (Dryzek, 2016; Pattberg temperature warmed by 0.85°C between 1880 and 2012, as reported and Zelli, 2016; Bäckstrand et al., 2017; Lövbrand et al., 2017). World 1 in the IPCC Fifth Assessment Report, or AR5 (IPCC, 2013b). Many population continues to rise, notably in hazard-prone small and regions of the world have already greater regional-scale warming, medium-sized cities in low- and moderate-income countries (Birkmann with 20–40% of the global population (depending on the temperature et al., 2016). The spread of fossil-fuel-based material consumption and dataset used) having experienced over 1.5°C of warming in at least changing lifestyles is a major driver of global resource use, and the one season (Figure 1.1; Chapter 3 Section 3.3.2.1). Temperature rise main contributor to rising greenhouse gas (GHG) emissions (Fleurbaey to date has already resulted in profound alterations to human and et al., 2014). natural systems, including increases in droughts, floods, and some other types of extreme weather; sea level rise; and biodiversity loss – The overarching context of this report is this: human influence has these changes are causing unprecedented risks to vulnerable persons become a principal agent of change on the planet, shifting the world and populations (IPCC, 2012a, 2014a; Mysiak et al., 2016; Chapter out of the relatively stable Holocene period into a new geological 3 Sections 3.4.5–3.4.13). The most affected people live in low and era, often termed the Anthropocene (Box 1.1). Responding to climate middle income countries, some of which have experienced a decline change in the Anthropocene will require approaches that integrate in food security, which in turn is partly linked to rising migration and multiple levels of interconnectivity across the global community. poverty (IPCC, 2012a). Small islands, megacities, coastal regions, and high mountain ranges are likewise among the most affected (Albert This chapter is composed of seven sections linked to the remaining et al., 2017). Worldwide, numerous ecosystems are at risk of severe four chapters of the report. This introductory Section 1.1 situates the impacts, particularly warm-water tropical reefs and Arctic ecosystems basic elements of the assessment within the context of sustainable (IPCC, 2014a). development; considerations of ethics, equity and human rights; and the problem of poverty. Section 1.2 focuses on understanding 1.5°C, global This report assesses current knowledge of the environmental, technical, versus regional warming, 1.5°C pathways, and associated emissions. economic, financial, socio-cultural, and institutional dimensions of a Section 1.3 frames the impacts at 1.5°C and beyond on natural and 1.5°C warmer world (meaning, unless otherwise specified, a world human systems. The section on strengthening the global response (1.4) in which warming has been limited to 1.5°C relative to pre-industrial frames responses, governance and implementation, and trade-offs levels). Differences in vulnerability and exposure arise from numerous and synergies between mitigation, adaptation, and the Sustainable Figure 1.1 | Human experience of present-day warming. Different shades of pink to purple indicated by the inset histogram show estimated warming for the season that has warmed the most at a given location between the periods 1850–1900 and 2006–2015, during which global average temperatures rose by 0.91°C in this dataset (Cowtan and Way, 2014) and 0.87°C in the multi-dataset average (Table 1.1 and Figure 1.3). The density of dots indicates the population (in 2010) in any 1° × 1° grid box. The underlay shows national Sustainable Development Goal (SDG) Global Index Scores indicating performance across the 17 SDGs. Hatching indicates missing SDG index data (e.g., Greenland). The histogram shows the population (in 2010) living in regions experiencing different levels of warming (at 0.25°C increments). See Supplementary Material 1.SM for further details. 53 Chapter 1 Framing and Context Development Goals (SDGs) under transformation, transformation and adaptation with sustainable development. Section 1.6 defines pathways, and transition. Section 1.5 provides assessment frameworks approaches used to communicate confidence, uncertainty and risk, and emerging methodologies that integrate climate change mitigation while 1.7 presents the storyline of the whole report. Box 1.1 | The Anthropocene: Strengthening the Global Response to 1.5°C Global Warming 1 Introduction The concept of the Anthropocene can be linked to the aspiration of the Paris Agreement. The abundant empirical evidence of the unprecedented rate and global scale of impact of human influence on the Earth System (Steffen et al., 2016; Waters et al., 2016) has led many scientists to call for an acknowledgement that the Earth has entered a new geological epoch: the Anthropocene (Crutzen and Stoermer, 2000; Crutzen, 2002; Gradstein et al., 2012). Although rates of change in the Anthropocene are necessarily assessed over much shorter periods than those used to calculate long-term baseline rates of change, and therefore present challenges for direct comparison, they are nevertheless striking. The rise in global CO2 concentration since 2000 is about 20 ppm per decade, which is up to 10 times faster than any sustained rise in CO2 during the past 800,000 years (Lüthi et al., 2008; Bereiter et al., 2015). AR5 found that the last geological epoch with similar atmospheric CO2 concentration was the Pliocene, 3.3 to 3.0 Ma (Masson-Delmotte et al., 2013). Since 1970 the global average temperature has been rising at a rate of 1.7°C per century, compared to a long-term decline over the past 7,000 years at a baseline rate of 0.01°C per century (NOAA, 2016; Marcott et al., 2013). These global-level rates of human-driven change far exceed the rates of change driven by geophysical or biosphere forces that have altered the Earth System trajectory in the past (e.g., Summerhayes, 2015; Foster et al., 2017); even abrupt geophysical events do not approach current rates of human-driven change. The Geological Dimension of the Anthropocene and 1.5°C Global Warming The process of formalising the Anthropocene is on-going (Zalasiewicz et al., 2017), but a strong majority of the Anthropocene Working Group (AWG) established by the Subcommission on Quaternary Stratigraphy of the International Commission on Stratigraphy have agreed that: (i) the Anthropocene has a geological merit; (ii) it should follow the Holocene as a formal epoch in the Geological Time Scale; and, (iii) its onset should be defined as the mid-20th century. Potential markers in the stratigraphic record include an array of novel manufactured materials of human origin, and “these combined signals render the Anthropocene stratigraphically distinct from the Holocene and earlier epochs” (Waters et al., 2016). The Holocene period, which itself was formally adopted in 1885 by geological science community, began 11,700 years ago with a more stable warm climate providing for emergence of human civilisation and growing human-nature interactions that have expanded to give rise to the Anthropocene (Waters et al., 2016). The Anthropocene and the Challenge of a 1.5° C Warmer World The Anthropocene can be employed as a “boundary concept” (Brondizio et al., 2016) that frames critical insights into understanding the drivers, dynamics and specific challenges in responding to the ambition of keeping global temperature well below 2°C while pursuing efforts towards and adapting to a 1.5°C warmer world. The United Nations Framework Convention on Climate Change (UNFCCC) and its Paris Agreement recognize the ability of humans to influence geophysical planetary processes (Chapter 2, Cross-Chapter Box 1 in this chapter). The Anthropocene offers a structured understanding of the culmination of past and present human–environmental relations and provides an opportunity to better visualize the future to minimize pitfalls (Pattberg and Zelli, 2016; Delanty and Mota, 2017), while acknowledging the differentiated responsibility and opportunity to limit global warming and invest in prospects for climate-resilient sustainable development (Harrington, 2016) (Chapter 5). The Anthropocene also provides an opportunity to raise questions regarding the regional differences, social inequities, and uneven capacities and drivers of global social–environmental changes, which in turn inform the search for solutions as explored in Chapter 4 of this report (Biermann et al., 2016). It links uneven influences of human actions on planetary functions to an uneven distribution of impacts (assessed in Chapter 3) as well as the responsibility and response capacity to, for example, limit global warming to no more than a 1.5°C rise above pre-industrial levels. Efforts to curtail greenhouse gas emissions without incorporating the intrinsic interconnectivity and disparities associated with the Anthropocene world may themselves negatively affect the development ambitions of some regions more than others and negate sustainable development efforts (see Chapter 2 and Chapter 5). 1.1.1 Equity and a 1.5°C Warmer World 2014; Olsson et al., 2014; Porter et al., 2014; Stavins et al., 2014). The aim of the Paris Agreement under the UNFCCC to ‘pursue The AR5 suggested that equity, sustainable development, and efforts to limit’ the rise in global temperatures to 1.5°C above pre- poverty eradication are best understood as mutually supportive industrial levels raises ethical concerns that have long been central and co-achievable within the context of climate action and are to climate debates (Fleurbaey et al., 2014; Kolstad et al., 2014). underpinned by various other international hard and soft law The Paris Agreement makes particular reference to the principle instruments (Denton et al., 2014; Fleurbaey et al., 2014; Klein et al., of equity, within the context of broader international goals of 54 Framing and Context Chapter 1 sustainable development and poverty eradication. Equity is a long- Much of this literature is still new and evolving (Holz et al., 2017; standing principle within international law and climate change law Dooley et al., 2018; Klinsky and Winkler, 2018), permitting the in particular (Shelton, 2008; Bodansky et al., 2017). present report to examine some broader equity concerns raised both by possible failure to limit warming to 1.5°C and by the range The AR5 describes equity as having three dimensions: intergenerational of ambitious mitigation efforts that may be undertaken to achieve (fairness between generations), international (fairness between that limit. Any comparison between 1.5°C and higher levels of states), and national (fairness between individuals) (Fleurbaey et al., warming implies risk assessments and value judgements and cannot 1 2014). The principle is generally agreed to involve both procedural straightforwardly be reduced to a cost-benefit analysis (Kolstad et justice (i.e., participation in decision making) and distributive justice al., 2014). However, different levels of warming can nevertheless be (i.e., how the costs and benefits of climate actions are distributed) understood in terms of their different implications for equity – that (Kolstad et al., 2014; Savaresi, 2016; Reckien et al., 2017). Concerns is, in the comparative distribution of benefits and burdens for specific regarding equity have frequently been central to debates around states, persons, or generations, and in terms of their likely impacts mitigation, adaptation and climate governance (Caney, 2005; on sustainable development and poverty (see especially Sections Schroeder et al., 2012; Ajibade, 2016; Reckien et al., 2017; Shue, 2.3.4.2, 2.5, 3.4.5–3.4.13, 3.6, 5.4.1, 5.4.2, 5.6 and Cross-Chapter 2018). Hence, equity provides a framework for understanding the boxes 6 in Chapter 3 and 12 in Chapter 5). asymmetries between the distributions of benefits and costs relevant to climate action (Schleussner et al., 2016; Aaheim et al., 2017). 1.1.2 Eradication of Poverty Four key framing asymmetries associated with the conditions of a This report assesses the role of poverty and its eradication in the 1.5°C warmer world have been noted (Okereke, 2010; Harlan et al., context of strengthening the global response to the threat of 2015; Ajibade, 2016; Savaresi, 2016; Reckien et al., 2017) and are climate change and sustainable development. A wide range of reflected in the report’s assessment. The first concerns differential definitions for poverty exist. The AR5 discussed ‘poverty’ in terms contributions to the problem: the observation that the benefits from of its multidimensionality, referring to ‘material circumstances’ industrialization have been unevenly distributed and those who (e.g., needs, patterns of deprivation, or limited resources), as well benefited most historically also have contributed most to the current as to economic conditions (e.g., standard of living, inequality, or climate problem and so bear greater responsibility (Shue, 2013; economic position), and/or social relationships (e.g., social class, McKinnon, 2015; Otto et al., 2017; Skeie et al., 2017). The second dependency, lack of basic security, exclusion, or lack of entitlement; asymmetry concerns differential impact: the worst impacts tend to Olsson et al., 2014). The UNDP now uses a Multidimensional Poverty fall on those least responsible for the problem, within states, between Index and estimates that about 1.5 billion people globally live in states, and between generations (Fleurbaey et al., 2014; Shue, 2014; multidimensional poverty, especially in rural areas of South Asia and Ionesco et al., 2016). The third is the asymmetry in capacity to shape Sub-Saharan Africa, with an additional billion at risk of falling into solutions and response strategies, such that the worst-affected states, poverty (UNDP, 2016). groups, and individuals are not always well represented (Robinson and Shine, 2018). Fourth, there is an asymmetry in future response A large and rapidly growing body of knowledge explores the capacity: some states, groups, and places are at risk of being left connections between climate change and poverty. Climatic behind as the world progresses to a low-carbon economy (Fleurbaey variability and climate change are widely recognized as factors that et al., 2014; Shue, 2014; Humphreys, 2017). may exacerbate poverty, particularly in countries and regions where poverty levels are high (Leichenko and Silva, 2014). The AR5 noted A sizeable and growing literature exists on how best to that climate change-driven impacts often act as a threat multiplier operationalize climate equity considerations, drawing on other in that the impacts of climate change compound other drivers of concepts mentioned in the Paris Agreement, notably its explicit poverty (Olsson et al., 2014). Many vulnerable and poor people are reference to human rights (OHCHR, 2009; Caney, 2010; Adger et dependent on activities such as agriculture that are highly susceptible al., 2014; Fleurbaey et al., 2014; IBA, 2014; Knox, 2015; Duyck to temperature increases and variability in precipitation patterns et al., 2018; Robinson and Shine, 2018). Human rights comprise (Shiferaw et al., 2014; Miyan, 2015). Even modest changes in rainfall internationally agreed norms that align with the Paris ambitions of and temperature patterns can push marginalized people into poverty poverty eradication, sustainable development, and the reduction of as they lack the means to recover from associated impacts. Extreme vulnerability (Caney, 2010; Fleurbaey et al., 2014; OHCHR, 2015). events, such as floods, droughts, and heat waves, especially when In addition to defining substantive rights (such as to life, health, they occur in series, can significantly erode poor people’s assets and and shelter) and procedural rights (such as to information and further undermine their livelihoods in terms of labour productivity, participation), human rights instruments prioritise the rights of housing, infrastructure and social networks (Olsson et al., 2014). marginalized groups, children, vulnerable and indigenous persons, and those discriminated against on grounds such as gender, race, 1.1.3 Sustainable Development and a 1.5°C age or disability (OHCHR, 2017). Several international human Warmer World rights obligations are relevant to the implementation of climate actions and consonant with UNFCCC undertakings in the areas AR5 (IPCC, 2014c) noted with high confidence that ‘equity is an of mitigation, adaptation, finance, and technology transfer (Knox, integral dimension of sustainable development’ and that ‘mitigation 2015; OHCHR, 2015; Humphreys, 2017). and adaptation measures can strongly affect broader sustainable 55 Chapter 1 Framing and Context development and equity objectives’ (Fleurbaey et al., 2014). Limiting on continental scales (Deser et al., 2012) and primarily affects the global warming to 1.5°C would require substantial societal and historical period, particularly that prior to the early 20th century when technological transformations, dependent in turn on global and data is sparse and of less certain quality. Most practical mitigation regional sustainable development pathways. A range of pathways, and adaptation decisions do not depend on quantifying historical both sustainable and not, are explored in this report, including warming to this level of precision, but a consistent working definition implementation strategies to understand the enabling conditions and is necessary to ensure consistency across chapters and figures. We 1 challenges required for such a transformation. These pathways and adopt definitions that are as consistent as possible with key findings connected strategies are framed within the context of sustainable of AR5 with respect to historical warming. development, and in particular the United Nations 2030 Agenda for Sustainable Development (UN, 2015b) and Cross-Chapter Box 4 on This report defines ‘warming’, unless otherwise qualified, as an SDGs (in this chapter). The feasibility of staying within 1.5°C depends increase in multi-decade global mean surface temperature (GMST) upon a range of enabling conditions with geophysical, environmental– above pre-industrial levels. Specifically, warming at a given point ecological, technological, economic, socio-cultural, and institutional in time is defined as the global average of combined land surface dimensions. Limiting warming to 1.5°C also involves identifying air and sea surface temperatures for a 30-year period centred on technology and policy levers to accelerate the pace of transformation that time, expressed relative to the reference period 1850–1900 (see Chapter 4). Some pathways are more consistent than others with (adopted for consistency with Box SPM.1 Figure 1 of IPCC (2014a)) the requirements for sustainable development (see Chapter 5). Overall, ‘as an approximation of pre-industrial levels’, excluding the impact of the three-pronged emphasis on sustainable development, resilience, natural climate fluctuations within that 30-year period and assuming and transformation provides Chapter 5 an opportunity to assess any secular trend continues throughout that period, extrapolating the conditions of simultaneously reducing societal vulnerabilities, into the future if necessary. There are multiple ways of accounting addressing entrenched inequalities, and breaking the circle of poverty. for natural fluctuations and trends (e.g., Foster and Rahmstorf, 2011; Haustein et al., 2017; Medhaug et al., 2017; Folland et al., 2018; The feasibility of any global commitment to a 1.5°C pathway depends, Visser et al., 2018), but all give similar results. A major volcanic in part, on the cumulative influence of the nationally determined eruption might temporarily reduce observed global temperatures, contributions (NDCs), committing nation states to specific GHG but would not reduce warming as defined here (Bethke et al., 2017). emission reductions. The current NDCs, extending only to 2030, do Likewise, given that the level of warming is currently increasing at not limit warming to 1.5°C. Depending on mitigation decisions after 0.3°C–0.7°C per 30 years (likely range quoted in Kirtman et al., 2013 2030, they cumulatively track toward a warming of 3°-4°C above and supported by Folland et al., 2018), the level of warming in 2017 pre-industrial temperatures by 2100, with the potential for further was 0.15°C–0.35°C higher than average warming over the 30-year warming thereafter (Rogelj et al., 2016a; UNFCCC, 2016). The analysis period 1988–2017. of pathways in this report reveals opportunities for greater decoupling of economic growth from GHG emissions. Progress towards limiting In summary, this report adopts a working definition of ‘1.5°C relative warming to 1.5°C requires a significant acceleration of this trend. AR5 to pre-industrial levels’ that corresponds to global average combined concluded that climate change constrains possible development paths, land surface air and sea surface temperatures either 1.5°C warmer that synergies and trade-offs exist between climate responses and than the average of the 51-year period 1850–1900, 0.87°C warmer socio-economic contexts, and that opportunities for effective climate than the 20-year period 1986–2005, or 0.63°C warmer than the responses overlap with opportunities for sustainable development, decade 2006–2015. These offsets are based on all available published noting that many existing societal patterns of consumption are global datasets, combined and updated, which show that 1986– intrinsically unsustainable (Fleurbaey et al., 2014). 2005 was 0.63°C warmer than 1850–1900 (with a 5–95% range of 0.57°C–0.69°C based on observational uncertainties alone), and 2006–2015 was 0.87°C warmer than 1850–1900 (with a likely range of 0.75°C–0.99°C, also accounting for the possible impact of natural 1.2 Understanding 1.5°C: Reference fluctuations). Where possible, estimates of impacts and mitigation Levels, Probability, Transience, pathways are evaluated relative to these more recent periods. Note Overshoot, and Stabilization that the 5–95% intervals often quoted in square brackets in AR5 correspond to very likely ranges, while likely ranges correspond to 1.2.1 Working Definitions of 1.5°C and 2°C 17–83%, or the central two-thirds, of the distribution of uncertainty. Warming Relative to Pre-Industrial Levels 1.2.1.1 Definition of global average temperature What is meant by ‘the increase in global average temperature… above pre-industrial levels’ referred to in the Paris Agreement depends on The IPCC has traditionally defined changes in observed GMST as a the choice of pre-industrial reference period, whether 1.5°C refers to weighted average of near-surface air temperature (SAT) changes total warming or the human-induced component of that warming, over land and sea surface temperature (SST) changes over the oceans and which variables and geographical coverage are used to define (Morice et al., 2012; Hartmann et al., 2013), while modelling studies global average temperature change. The cumulative impact of these have typically used a simple global average SAT. For ambitious definitional ambiguities (e.g., Hawkins et al., 2017; Pfleiderer et al., mitigation goals, and under conditions of rapid warming or declining 2018) is comparable to natural multi-decadal temperature variability sea ice (Berger et al., 2017), the difference can be significant. Cowtan 56 Framing and Context Chapter 1 et al. (2015) and Richardson et al. (2016) show that the use of of incomplete observation coverage (Rohde et al., 2013; Cowtan and blended SAT/SST data and incomplete coverage together can give Way, 2014; Jones, 2016). The main impact of statistical infilling is to approximately 0.2°C less warming from the 19th century to the increase estimated warming to date by about 0.1°C (Richardson et present relative to the use of complete global-average SAT (Stocker al., 2018 and Table 1.1). et al., 2013, Figure TFE8.1 and Figure 1.2). However, Richardson et al. (2018) show that this is primarily an issue for the interpretation of We adopt a working definition of warming over the historical period the historical record to date, with less absolute impact on projections based on an average of the four available global datasets that are 1 of future changes, or estimated emissions budgets, under ambitious supported by peer-reviewed publications: the three datasets used in the mitigation scenarios. AR5, updated (Karl et al., 2015), together with the Cowtan-Way infilled dataset (Cowtan and Way, 2014). A further two datasets, Berkeley The three GMST reconstructions used in AR5 differ in their treatment Earth (Rohde et al., 2013) and that of the Japan Meteorological Agency of missing data. GISTEMP (Hansen et al., 2010) uses interpolation (JMA), are provided in Table 1.1. This working definition provides an to infer trends in poorly observed regions like the Arctic (although updated estimate of 0.86°C for the warming over the period 1880– even this product is spatially incomplete in the early record), while 2012 based on a linear trend. This quantity was quoted as 0.85°C in NOAAGlobalTemp (Vose et al., 2012) and HadCRUT (Morice et al., the AR5. Hence the inclusion of the Cowtan-Way dataset does not 2012) are progressively closer to a simple average of available introduce any inconsistency with the AR5, whereas redefining GMST observations. Since the AR5, considerable effort has been devoted to represent global SAT could increase this figure by up to 20% (Table to more sophisticated statistical modelling to account for the impact 1.1, blue lines in Figure 1.2 and Richardson et al., 2016). Figure 1.2 | Evolution of global mean surface temperature (GMST) over the period of instrumental observations. Grey shaded line shows monthly mean GMST in the HadCRUT4, NOAAGlobalTemp, GISTEMP and Cowtan-Way datasets, expressed as departures from 1850–1900, with varying grey line thickness indicating inter-dataset range. All observational datasets shown represent GMST as a weighted average of near surface air temperature over land and sea surface temperature over oceans. Human- induced (yellow) and total (human- and naturally-forced, orange) contributions to these GMST changes are shown calculated following Otto et al. (2015) and Haustein et al. (2017). Fractional uncertainty in the level of human-induced warming in 2017 is set equal to ±20% based on multiple lines of evidence. Thin blue lines show the modelled global mean surface air temperature (dashed) and blended surface air and sea surface temperature accounting for observational coverage (solid) from the CMIP5 historical ensemble average extended with RCP8.5 forcing (Cowtan et al., 2015; Richardson et al., 2018). The pink shading indicates a range for temperature fluctuations over the Holocene (Marcott et al., 2013). Light green plume shows the AR5 prediction for average GMST over 2016–2035 (Kirtman et al., 2013). See Supplementary Material 1.SM for further details. 1.2.1.2 Choice of reference period in the HadCRUT4 dataset, average temperatures over 1850–1879, prior to the largest eruptions, are less than 0.01°C from the average Any choice of reference period used to approximate ‘pre- for 1850–1900. Temperatures rose by 0.0°C–0.2°C from 1720– industrial’ conditions is a compromise between data coverage 1800 to 1850–1900 (Hawkins et al., 2017), but the anthropogenic and representativeness of typical pre-industrial solar and volcanic contribution to this warming is uncertain (Abram et al., 2016; Schurer forcing conditions. This report adopts the 51-year reference period, et al., 2017). The 18th century represents a relatively cool period in 1850–1900 inclusive, assessed as an approximation of pre-industrial the context of temperatures since the mid-Holocene (Marcott et al., levels in AR5 (Box TS.5, Figure 1 of Field et al., 2014). The years 2013; Lüning and Vahrenholt, 2017; Marsicek et al., 2018), which is 1880–1900 are subject to strong but uncertain volcanic forcing, but indicated by the pink shaded region in Figure 1.2. 57 Chapter 1 Framing and Context Projections of responses to emission scenarios, and associated is similar to the estimated externally driven warming. When solar, impacts, may use a more recent reference period, offset by historical volcanic and ENSO-related variability is taken into account following observations, to avoid conflating uncertainty in past and future the procedure of Foster and Rahmstorf (2011), there is no indication changes (e.g., Hawkins et al., 2017; Millar et al., 2017b; Simmons of average temperatures in either 1986–2005 or 2006–2015 being et al., 2017). Two recent reference periods are used in this report: substantially biased by short-term variability (see Supplementary 1986–2005 and 2006–2015. In the latter case, when using a single Material 1.SM.2). The temperature difference between these two 1 decade to represent a 30-year average centred on that decade, it reference periods (0.21°C–0.27°C over 15 years across available is important to consider the potential impact of internal climate datasets) is also consistent with the AR5 assessment of the current variability. The years 2008–2013 were characterised by persistent warming rate of 0.3°C–0.7°C over 30 years (Kirtman et al., 2013). cool conditions in the Eastern Pacific (Kosaka and Xie, 2013; Medhaug et al., 2017), related to both the El Niño-Southern Oscillation (ENSO) On the definition of warming used here, warming to the decade and, potentially, multi-decadal Pacific variability (e.g., England et al., 2006–2015 comprises an estimate of the 30-year average centred 2014), but these were partially compensated for by El Niño conditions on this decade, or 1996–2025, assuming the current trend continues in 2006 and 2015. Likewise, volcanic activity depressed temperatures and that any volcanic eruptions that might occur over the final seven in 1986–2005, partly offset by the very strong El Niño event in 1998. years are corrected for. Given this element of extrapolation, we use Figure 1.2 indicates that natural variability (internally generated and the AR5 near-term projection to provide a conservative uncertainty externally driven) had little net impact on average temperatures range. Combining the uncertainty in observed warming to 1986– over 2006–2015, in that the average temperature of the decade 2005 (±0.06°C) with the likely range in the current warming trend as Table 1.1 | Observed increase in global average surface temperature in various datasets. Numbers in square brackets correspond to 5–95% uncertainty ranges from individual datasets, encompassing known sources of observational uncertainty only. Diagnostic 1850–1900 1850–1900 1986–2005 1850–1900 1850–1900 / dataset to (1) to (2) to (3) to (4) to (5) Trend (6) Trend (6) 2006–2015 1986–2005 2006–2015 1981–2010 1998–2017 1880–2012 1880–2015 0.84 0.60 0.22 0.62 0.83 0.83 0.88 HadCRUT4.6 [0.79–0.89] [0.57–0.66] [0.21–0.23] [0.58–0.67] [0.78–0.88] [0.77–0.90] [0.83–0.95] NOAAGlobalTemp 0.86 0.62 0.22 0.63 0.85 0.85 0.91 (7) GISTEMP (7) 0.89 0.65 0.23 0.66 0.88 0.89 0.94 0.91 0.65 0.26 0.65 0.88 0.88 0.93 Cowtan-Way [0.85–0.99] [0.60–0.72] [0.25–0.27] [0.60–0.72] [0.82–0.96] [0.79–0.98] [0.85–1.03] Average (8) 0.87 0.63 0.23 0.64 0.86 0.86 0.92 Berkeley (9) 0.98 0.73 0.25 0.73 0.97 0.97 1.02 JMA (9) 0.82 0.59 0.17 0.60 0.81 0.82 0.87 ERA-Interim N/A N/A 0.26 N/A N/A N/A N/A JRA-55 N/A N/A 0.23 N/A N/A N/A N/A CMIP5 global 0.99 0.62 0.38 0.62 0.89 0.81 0.86 SAT (10) [0.65–1.37] [0.38–0.94] [0.24–0.62] [0.34–0.93] [0.62–1.29] [0.58–1.31] [0.63–1.39] CMIP5 SAT/SST 0.86 0.50 0.34 0.48 0.75 0.68 0.74 blend-masked [0.54–1.18] [0.31–0.79] [0.19–0.54] [0.26–0.79] [0.52–1.11] [0.45–1.08] [0.51–1.14] Notes: 1) Most recent reference period used in this report. 2) Most recent reference period used in AR5. 3) Difference between recent reference periods. 4) Current WMO standard reference periods. 5) Most recent 20-year period. 6) Linear trends estimated by a straight-line fit, expressed in degrees yr−1 multiplied by 133 or 135 years respectively, with uncertainty ranges incorporating observational uncertainty only. 7) To estimate changes in the NOAAGlobalTemp and GISTEMP datasets relative to the 1850–1900 reference period, warming is computed relative to 1850–1900 using the HadCRUT4.6 dataset and scaled by the ratio of the linear trend 1880–2015 in the NOAAGlobalTemp or GISTEMP dataset with the corresponding linear trend computed from HadCRUT4. 8) Average of diagnostics derived – see (7) – from four peer-reviewed global datasets, HadCRUT4.6, NOAA, GISTEMP & Cowtan-Way. Note that differences between averages may not coincide with average differences because of rounding. 9) No peer-reviewed publication available for these global combined land–sea datasets. 10) CMIP5 changes estimated relative to 1861–80 plus 0.02°C for the offset in HadCRUT4.6 from 1850–1900. CMIP5 values are the mean of the RCP8.5 ensemble, with 5–95% ensemble range. They are included to illustrate the difference between a complete global surface air temperature record (SAT) and a blended surface air and sea surface temperature (SST) record accounting for incomplete coverage (masked), following Richardson et al. (2016). Note that 1986–2005 temperatures in CMIP5 appear to have been depressed more than observed temperatures by the eruption of Mount Pinatubo. 58 Framing and Context Chapter 1 assessed by AR5 (±0.2°C/30 years), assuming these are uncorrelated, for observational and forcing uncertainty and internal variability. and using observed warming relative to 1850–1900 to provide the Applying their method to the average of the four datasets shown in central estimate (no evidence of bias from short-term variability), Figure 1.2 gives an average level of human-induced warming in 2017 gives an assessed warming to the decade 2006–2015 of 0.87°C with of 1.04°C. They also estimate a human-induced warming trend over a ±0.12°C likely range. This estimate has the advantage of traceability the past 20 years of 0.17°C (0.13°C–0.33°C) per decade, consistent to the AR5, but more formal methods of quantifying externally driven with estimates of the total observed trend of Foster and Rahmstorf warming (e.g., Bindoff et al., 2013; Jones et al., 2016; Haustein et (2011) (0.17° ± 0.03°C per decade, uncertainty in linear trend only), 1 al., 2017; Ribes et al., 2017), which typically give smaller ranges of Folland et al. (2018) and Kirtman et al. (2013) (0.3°C–0.7°C over 30 uncertainty, may be adopted in the future. years, or 0.1°C–0.23°C per decade, likely range), and a best-estimate warming rate over the past five years of 0.215°C/decade (Leach et al., 1.2.1.3 Total versus human-induced warming and 2018). Drawing on these multiple lines of evidence, human-induced warming rates warming is assessed to have reached 1.0°C in 2017, having increased by 0.13°C from the mid-point of 2006–2015, with a likely range Total warming refers to the actual temperature change, irrespective of 0.8°C to 1.2°C (reduced from 5–95% to account for additional of cause, while human-induced warming refers to the component forcing and model uncertainty), increasing at 0.2°C per decade (with of that warming that is attributable to human activities. Mitigation a likely range of 0.1°C to 0.3°C per decade: estimates of human- studies focus on human-induced warming (that is not subject to induced warming given to 0.1°C precision only). internal climate variability), while studies of climate change impacts typically refer to total warming (often with the impact of internal Since warming is here defined in terms of a 30-year average, corrected variability minimised through the use of multi-decade averages). for short-term natural fluctuations, when warming is considered to be at 1.5°C, global temperatures would fluctuate equally on either side In the absence of strong natural forcing due to changes in solar or of 1.5°C in the absence of a large cooling volcanic eruption (Bethke et volcanic activity, the difference between total and human-induced al., 2017). Figure 1.2 indicates there is a substantial chance of GMST in warming is small: assessing empirical studies quantifying solar and a single month fluctuating over 1.5°C between now and 2020 (or, by volcanic contributions to GMST from 1890 to 2010, AR5 (Figure 10.6 2030, for a longer period: Henley and King, 2017), but this would not of Bindoff et al., 2013) found their net impact on warming over the constitute temperatures ‘reaching 1.5°C’ on our working definition. full period to be less than plus or minus 0.1°C. Figure 1.2 shows that Rogelj et al. (2017) show limiting the probability of annual GMST the level of human-induced warming has been indistinguishable from exceeding 1.5°C to less than one-year-in-20 would require limiting total observed warming since 2000, including over the decade 2006– warming, on the definition used here, to 1.31°C or lower. 2015. Bindoff et al. (2013) assessed the magnitude of human-induced warming over the period 1951–2010 to be 0.7°C (likely between 1.2.2 Global versus Regional and Seasonal Warming 0.6°C and 0.8°C), which is slightly greater than the 0.65°C observed warming over this period (Figures 10.4 and 10.5) with a likely range Warming is not observed or expected to be spatially or seasonally of ±14%. The key surface temperature attribution studies underlying uniform (Collins et al., 2013). A 1.5°C increase in GMST will be this finding (Gillett et al., 2013; Jones et al., 2013; Ribes and Terray, associated with warming substantially greater than 1.5°C in many 2013) used temperatures since the 19th century to constrain human- land regions, and less than 1.5°C in most ocean regions. This is induced warming, and so their results are equally applicable to the illustrated by Figure 1.3, which shows an estimate of the observed attribution of causes of warming over longer periods. Jones et al. change in annual and seasonal average temperatures between (2016) show (Figure 10) human-induced warming trends over the the 1850–1900 pre-industrial reference period and the decade period 1905–2005 to be indistinguishable from the corresponding 2006–2015 in the Cowtan-Way dataset. These regional changes are total observed warming trend accounting for natural variability using associated with an observed GMST increase of 0.91°C in the dataset spatio-temporal detection patterns from 12 out of 15 CMIP5 models shown here, or 0.87°C in the four-dataset average (Table 1.1). This and from the multi-model average. Figures from Ribes and Terray observed pattern reflects an on-going transient warming: features (2013), show the anthropogenic contribution to the observed linear such as enhanced warming over land may be less pronounced, but still warming trend 1880–2012 in the HadCRUT4 dataset (0.83°C in Table present, in equilibrium (Collins et al., 2013). This figure illustrates the 1.1) to be 0.86°C using a multi-model average global diagnostic, with magnitude of spatial and seasonal differences, with many locations, a 5–95% confidence interval of 0.72°C–1.00°C (see figure 1.SM.6). particularly in Northern Hemisphere mid-latitude winter (December– In all cases, since 2000 the estimated combined contribution of solar February), already experiencing regional warming more than double and volcanic activity to warming relative to 1850–1900 is found to be the global average. Individual seasons may be substantially warmer, less than ±0.1°C (Gillett et al., 2013), while anthropogenic warming or cooler, than these expected changes in the long-term average. is indistinguishable from, and if anything slightly greater than, the total observed warming, with 5–95% confidence intervals typically 1.2.3 Definition of 1.5°C Pathways: Probability, around ±20%. Transience, Stabilization and Overshoot Haustein et al. (2017) give a 5–95% confidence interval for Pathways considered in this report, consistent with available literature human-induced warming in 2017 of 0.87°C–1.22°C, with a best on 1.5°C, primarily focus on the time scale up to 2100, recognising estimate of 1.02°C, based on the HadCRUT4 dataset accounting that the evolution of GMST after 2100 is also important. Two broad 59 Chapter 1 Framing and Context 1 Figure 1.3 | Spatial and seasonal pattern of present-day warming: Regional warming for the 2006–2015 decade relative to 1850–1900 for the annual mean (top), the average of December, January, and February (bottom left) and for June, July, and August (bottom right). Warming is evaluated by regressing regional changes in the Cowtan and Way (2014) dataset onto the total (combined human and natural) externally forced warming (yellow line in Figure 1.2). See Supplementary Material 1.SM for further details and versions using alternative datasets. The definition of regions (green boxes and labels in top panel) is adopted from the AR5 (Christensen et al., 2013). categories of 1.5°C pathways can be used to characterise mitigation out 1.5°C pathways with no or limited (<0.1°C) overshoot in many options and impacts: pathways in which warming (defined as 30-year instances and pursues efforts to ensure that when the term ‘1.5°C averaged GMST relative to pre-industrial levels, see Section 1.2.1) pathway’ is used, the associated overshoot is made explicit where remains below 1.5°C throughout the 21st century, and pathways relevant. In Chapter 2, the classification of pathways is based on one in which warming temporarily exceeds (‘overshoots’) 1.5°C and modelling approach to avoid ambiguity, but probabilities of exceeding returns to 1.5°C either before or soon after 2100. Pathways in which 1.5°C are checked against other approaches to verify that they lie warming exceeds 1.5°C before 2100, but might return to that level in within this approximate range. All these absolute probabilities are some future century, are not considered 1.5°C pathways. imprecise, depend on the information used to constrain them, and hence are expected to evolve in the future. Imprecise probabilities Because of uncertainty in the climate response, a ‘prospective’ can nevertheless be useful for decision-making, provided the mitigation pathway (see Cross-Chapter Box 1 in this chapter), in which imprecision is acknowledged (Hall et al., 2007; Kriegler et al., 2009; emissions are prescribed, can only provide a level of probability of Simpson et al., 2016). Relative and rank probabilities can be assessed warming remaining below a temperature threshold. This probability much more consistently: approaches may differ on the absolute cannot be quantified precisely since estimates depend on the method probability assigned to individual outcomes, but typically agree on used (Rogelj et al., 2016b; Millar et al., 2017b; Goodwin et al., 2018; which outcomes are more probable. Tokarska and Gillett, 2018). This report defines a ‘1.5°C pathway’ as a pathway of emissions and associated possible temperature Importantly, 1.5°C pathways allow a substantial (up to one-in-two) responses in which the majority of approaches using presently chance of warming still exceeding 1.5°C. An ‘adaptive’ mitigation available information assign a probability of approximately one-in- pathway in which emissions are continuously adjusted to achieve two to two-in-three to warming remaining below 1.5°C or, in the case a specific temperature outcome (e.g., Millar et al., 2017b) reduces of an overshoot pathway, to warming returning to 1.5°C by around uncertainty in the temperature outcome while increasing uncertainty 2100 or earlier. Recognizing the very different potential impacts and in the emissions required to achieve it. It has been argued (Otto et risks associated with high-overshoot pathways, this report singles al., 2015; Xu and Ramanathan, 2017) that achieving very ambitious 60 Framing and Context Chapter 1 temperature goals will require such an adaptive approach to time. Hence every year’s delay before initiating emission reductions mitigation, but very few studies have been performed taking this decreases by approximately two years the remaining time available approach (e.g., Jarvis et al., 2012). to reach zero emissions on a pathway still remaining below 1.5°C (Allen and Stocker, 2013; Leach et al., 2018). Figure 1.4 illustrates categories of (a) 1.5°C pathways and associated (b) annual and (c) cumulative emissions of CO2. It also shows (d) 1.2.3.2 Pathways temporarily exceeding 1.5°C an example of a ‘time-integrated impact’ that continues to increase 1 even after GMST has stabilised, such as sea level rise. This schematic With the pathways in this category, also referred to as overshoot assumes for the purposes of illustration that the fractional contribution pathways, GMST rises above 1.5°C relative to pre-industrial before of non-CO2 climate forcers to total anthropogenic forcing (which is peaking and returning to 1.5°C around or before 2100 (Figure 1.4, currently increasing, Myhre et al., 2017) is approximately constant blue lines), subsequently either stabilising or continuing to fall. This from now on. Consequently, total human-induced warming is allows initially slower or delayed emission reductions, but lowering proportional to cumulative CO2 emissions (solid line in c), and GMST GMST requires net negative global CO2 emissions (net anthropogenic stabilises when emissions reach zero. This is only the case in the most removal of CO2; Figure 1.4b). Cooling, or reduced warming, through ambitious scenarios for non-CO2 mitigation (Leach et al., 2018). A sustained reductions of net non-CO2 climate forcing (Cross-Chapter simple way of accounting for varying non-CO2 forcing in Figure 1.4 Box 2 in this chapter) is also required, but their role is limited because would be to note that every 1 W m−2 increase in non-CO2 forcing emissions of most non-CO2 forcers cannot be reduced to below zero. between now and the decade or two immediately prior to the time Hence the feasibility and availability of large-scale CO2 removal of peak warming reduces cumulative CO2 emissions consistent with limits the possible rate and magnitude of temperature decline. In the same peak warming by approximately 1100 GtCO2, with a range this report, overshoot pathways are referred to as 1.5°C pathways, of 900-1500 GtCO2 (using values from AR5: Myhre et al., 2013; Allen but qualified by the amount of the temperature overshoot, which et al., 2018; Jenkins et al., 2018; Cross-Chapter Box 2 in this chapter). can have a substantial impact on irreversible climate change impacts (Mathesius et al., 2015; Tokarska and Zickfeld, 2015). 1.2.3.1 Pathways remaining below 1.5°C 1.2.3.3 Impacts at 1.5°C warming associated with different In this category of 1.5°C pathways, human-induced warming either pathways: transience versus stabilisation rises monotonically to stabilise at 1.5°C (Figure 1.4, brown lines) or peaks at or below 1.5°C and then declines (yellow lines). Figure Figure 1.4 also illustrates time scales associated with different 1.4b demonstrates that pathways remaining below 1.5°C require net impacts. While many impacts scale with the change in GMST itself, annual CO2 emissions to peak and decline to near zero or below, some (such as those associated with ocean acidification) scale with depending on the long-term adjustment of the carbon cycle and the change in atmospheric CO2 concentration, indicated by the non-CO2 emissions (Bowerman et al., 2013; Wigley, 2018). Reducing fraction of cumulative CO2 emissions remaining in the atmosphere emissions to zero corresponds to stabilizing cumulative CO2 emissions (dotted lines in Figure 1.4c). Others may depend on the rate of (Figure 1.4c, solid lines) and falling concentrations of CO2 in the change of GMST, while ‘time-integrated impacts’, such as sea level atmosphere (panel c dashed lines) (Matthews and Caldeira, 2008; rise, shown in Figure 1.4d continue to increase even after GMST has Solomon et al., 2009), which is required to stabilize GMST if non-CO2 stabilised. climate forcings are constant and positive. Stabilizing atmospheric greenhouse gas concentrations would result in continued warming Hence impacts that occur when GMST reaches 1.5°C could be very (see Section 1.2.4). different depending on the pathway to 1.5°C. CO2 concentrations will be higher as GMST rises past 1.5°C (transient warming) than when If emission reductions do not begin until temperatures are close to GMST has stabilized at 1.5°C, while sea level and, potentially, global the proposed limit, pathways remaining below 1.5°C necessarily mean precipitation (Pendergrass et al., 2015) would both be lower involve much faster rates of net CO2 emission reductions (Figure 1.4, (see Figure 1.4). These differences could lead to very different impacts green lines), combined with rapid reductions in non-CO2 forcing and on agriculture, on some forms of extreme weather (e.g., Baker et al., these pathways also reach 1.5°C earlier. Note that the emissions 2018), and on marine and terrestrial ecosystems (e.g., Mitchell et al., associated with these schematic temperature pathways may not 2017 and Boxes 3.1 and 3.2). Sea level would be higher still if GMST correspond to feasible emission scenarios, but they do illustrate the returns to 1.5°C after an overshoot (Figure 1.4 d), with potentially fact that the timing of net zero emissions does not in itself determine significantly different impacts in vulnerable regions. Temperature peak warming: what matters is total cumulative emissions up to that overshoot could also cause irreversible impacts (see Chapter 3). 61 Chapter 1 Framing and Context 1 Figure 1.4 | Different 1.5°C pathways1: Schematic illustration of the relationship between (a) global mean surface temperature (GMST) change; (b) annual rates of CO2 emissions, assuming constant fractional contribution of non-CO2 forcing to total human-induced warming; (c) total cumulative CO2 emissions (solid lines) and the fraction thereof remaining in the atmosphere (dashed lines; these also indicates changes in atmospheric CO2 concentrations); and (d) a time-integrated impact, such as sea level rise, that continues to increase even after GMST has stabilized. Colours indicate different 1.5°C pathways. Brown: GMST remaining below and stabilizing at 1.5°C in 2100; Green: a delayed start but faster emission reductions pathway with GMST remaining below and reaching 1.5°C earlier; Blue: a pathway temporarily exceeding 1.5°C, with temperatures reduced to 1.5°C by net negative CO2 emissions after temperatures peak; and Yellow: a pathway peaking at 1.5°C and subsequently declining. Temperatures are anchored to 1°C above pre-industrial in 2017; emissions–temperature relationships are computed using a simple climate model (Myhre et al., 2013; Millar et al., 2017a; Jenkins et al., 2018) with a lower value of the Transient Climate Response (TCR) than used in the quantitative pathway assessments in Chapter 2 to illustrate qualitative differences between pathways: this figure is not intended to provide quantitative information. The time-integrated impact is illustrated by the semi-empirical sea level rise model of Kopp et al. (2016). Cross-Chapter Box 1 | Scenarios and Pathways Contributing Authors: Mikiko Kainuma (Japan), Kristie L. Ebi (USA), Sabine Fuss (Germany), Elmar Kriegler (Germany), Keywan Riahi (Austria), Joeri Rogelj (Austria/Belgium), Petra Tschakert (Australia/Austria), Rachel Warren (UK) Climate change scenarios have been used in IPCC assessments since the First Assessment Report (Leggett et al., 1992). The SRES scenarios (named after the IPCC Special Report on Emissions Scenarios published in 2000; IPCC, 2000), consist of four scenarios that do not take into account any future measures to limit greenhouse gas (GHG) emissions. Subsequently, many policy scenarios have been developed based upon them (Morita et al., 2001). The SRES scenarios are superseded by a set of scenarios based on the Representative Concentration Pathways (RCPs) and Shared Socio-Economic Pathways (SSPs) (Riahi et al., 2017). The RCPs comprise a set of four GHG concentration trajectories that jointly span a large range of plausible human-caused climate forcing ranging from 2.6 W m−2 (RCP2.6) to 8.5 W m−2 (RCP8.5) by the end of the 21st century (van Vuuren et al., 2011). They were used to develop climate projections in the Coupled Model Intercomparison Project Phase 5 (CMIP5; Taylor et al., 2012) and were assessed in the IPCC Fifth Assessment Report (AR5). Based on the CMIP5 ensemble, RCP2.6, provides a better than two-in-three chance of staying below 2°C and a median warming of 1.6°C relative to 1850–1900 in 2100 (Collins et al., 2013). The SSPs were developed to complement the RCPs with varying socio-economic challenges to adaptation and mitigation. SSP-based scenarios were developed for a range of climate forcing levels, including the end-of-century forcing levels of the RCPs (Riahi et al., 2017) and a level below RCP2.6 to explore pathways limiting warming to 1.5°C above pre-industrial levels (Rogelj et al., 2018). The SSP-based 1.5°C pathways are assessed in Chapter 2 of this report. These scenarios offer an integrated perspective on socio-economic, energy- system (Bauer et al., 2017), land use (Popp et al., 2017), air pollution (Rao et al., 2017) and, GHG emissions developments (Riahi et al., 1 An animated version of Figure 1.4 will be embedded in the web-based version of this Special Report 62 Framing and Context Chapter 1 Cross-Chapter Box 1 (continued) 2017). Because of their harmonised assumptions, scenarios developed with the SSPs facilitate the integrated analysis of future climate impacts, vulnerabilities, adaptation and mitigation. Scenarios and Pathways in this Report This report focuses on pathways that could limit the increase of global mean surface temperature (GMST) to 1.5°C above pre-industrial 1 levels and pathways that align with the goals of sustainable development and poverty eradication. The pace and scale of mitigation and adaptation are assessed in the context of historical evidence to determine where unprecedented change is required (see Chapter 4). Other scenarios are also assessed, primarily as benchmarks for comparison of mitigation, impacts, and/or adaptation requirements. These include baseline scenarios that assume no climate policy; scenarios that assume some kind of continuation of current climate policy trends and plans, many of which are used to assess the implications of the nationally determined contributions (NDCs); and scenarios holding warming below 2°C above pre-industrial levels. This report assesses the spectrum from global mitigation scenarios to local adaptation choices – complemented by a bottom-up assessment of individual mitigation and adaptation options, and their implementation (policies, finance, institutions, and governance, see Chapter 4). Regional, national, and local scenarios, as well as decision-making processes involving values and difficult trade-offs are important for understanding the challenges of limiting GMST increase to 1.5°C and are thus indispensable when assessing implementation. Different climate policies result in different temperature pathways, which result in different levels of climate risks and actual climate impacts with associated long-term implications. Temperature pathways are classified into continued warming pathways (in the cases of baseline and reference scenarios), pathways that keep the temperature increase below a specific limit (like 1.5°C or 2°C), and pathways that temporarily exceed and later fall to a specific limit (overshoot pathways). In the case of a temperature overshoot, net negative CO2 emissions are required to remove excess CO2 from the atmosphere (Section 1.2.3). In a ‘prospective’ mitigation pathway, emissions (or sometimes concentrations) are prescribed, giving a range of GMST outcomes because of uncertainty in the climate response. Prospective pathways are considered ‘1.5°C pathways’ in this report if, based on current knowledge, the majority of available approaches assign an approximate probability of one-in-two to two-in-three to temperatures either remaining below 1.5°C or returning to 1.5°C either before or around 2100. Most pathways assessed in Chapter 2 are prospective pathways, and therefore even ‘1.5°C pathways’ are also associated with risks of warming higher than 1.5°C, noting that many risks increase non-linearly with increasing GMST. In contrast, the ‘risks of warming of 1.5°C’ assessed in Chapter 3 refer to risks in a world in which GMST is either passing through (transient) or stabilized at 1.5°C, without considering probabilities of different GMST levels (unless otherwise qualified). To stay below any desired temperature limit, mitigation measures and strategies would need to be adjusted as knowledge of the climate response is updated (Millar et al., 2017b; Emori et al., 2018). Such pathways can be called ‘adaptive’ mitigation pathways. Given there is always a possibility of a greater-than-expected climate response (Xu and Ramanathan, 2017), adaptive mitigation pathways are important to minimise climate risks, but need also to consider the risks and feasibility (see Cross-Chapter Box 3 in this chapter) of faster-than-expected emission reductions. Chapter 5 includes assessments of two related topics: aligning mitigation and adaptation pathways with sustainable development pathways, and transformative visions for the future that would support avoiding negative impacts on the poorest and most disadvantaged populations and vulnerable sectors. Definitions of Scenarios and Pathways Climate scenarios and pathways are terms that are sometimes used interchangeably, with a wide range of overlapping definitions (Rosenbloom, 2017). A ‘scenario’ is an internally consistent, plausible, and integrated description of a possible future of the human–environment system, including a narrative with qualitative trends and quantitative projections (IPCC, 2000). Climate change scenarios provide a framework for developing and integrating projections of emissions, climate change, and climate impacts, including an assessment of their inherent uncertainties. The long-term and multi-faceted nature of climate change requires climate scenarios to describe how socio-economic trends in the 21st century could influence future energy and land use, resulting emissions and the evolution of human vulnerability and exposure. Such driving forces include population, GDP, technological innovation, governance and lifestyles. Climate change scenarios are used for analysing and contrasting climate policy choices. The notion of a ‘pathway’ can have multiple meanings in the climate literature. It is often used to describe the temporal evolution of a set of scenario features, such as GHG emissions and socio-economic development. As such, it can describe individual scenario components or sometimes be used interchangeably with the word ‘scenario’. For example, the RCPs describe GHG concentration trajectories (van Vuuren et al., 2011) and the SSPs are a set of narratives of societal futures augmented by quantitative projections of socio-economic determinants such as population, GDP and urbanization (Kriegler et al., 2012; O’Neill et al., 2014). Socio-economic 63 Chapter 1 Framing and Context Cross-Chapter Box 1 (continued) driving forces consistent with any of the SSPs can be combined with a set of climate policy assumptions (Kriegler et al., 2014) that together would lead to emissions and concentration outcomes consistent with the RCPs (Riahi et al., 2017). This is at the core of the scenario framework for climate change research that aims to facilitate creating scenarios integrating emissions and development pathways dimensions (Ebi et al., 2014; van Vuuren et al., 2014). 1 In other parts of the literature, ‘pathway’ implies a solution-oriented trajectory describing a pathway from today’s world to achieving a set of future goals. Sustainable Development Pathways describe national and global pathways where climate policy becomes part of a larger sustainability transformation (Shukla and Chaturvedi, 2013; Fleurbaey et al., 2014; van Vuuren et al., 2015). The AR5 presented climate-resilient pathways as sustainable development pathways that combine the goals of adaptation and mitigation (Denton et al., 2014), more broadly defined as iterative processes for managing change within complex systems in order to reduce disruptions and enhance opportunities associated with climate change (IPCC, 2014a). The AR5 also introduced the notion of climate-resilient development pathways, with a more explicit focus on dynamic livelihoods, multi-dimensional poverty, structural inequalities, and equity among poor and non-poor people (Olsson et al., 2014). Adaptation pathways are understood as a series of adaptation choices involving trade-offs between short-term and long-term goals and values (Reisinger et al., 2014). They are decision-making processes sequenced over time with the purpose of deliberating and identifying socially salient solutions in specific places (Barnett et al., 2014; Wise et al., 2014; Fazey et al., 2016). There is a range of possible pathways for transformational change, often negotiated through iterative and inclusive processes (Harris et al., 2017; Fazey et al., 2018; Tàbara et al., 2018). 1.2.4 Geophysical Warming Commitment composition. It is therefore not relevant to the warming commitment from past emissions alone. It is frequently asked whether limiting warming to 1.5°C is ‘feasible’ (Cross-Chapter Box 3 in this chapter). There are many dimensions to The ZEC, although based on equally idealised assumptions, allows this question, including the warming ‘commitment’ from past emissions for a clear separation of the response to past emissions from the of greenhouse gases and aerosol precursors. Quantifying commitment effects of future emissions. The magnitude and sign of the ZEC from past emissions is complicated by the very different behaviour of depend on the mix of GHGs and aerosols considered. For CO2, which different climate forcers affected by human activity: emissions of long- takes hundreds of thousands of years to be fully removed from the lived greenhouse gases such as CO2 and nitrous oxide (N2O) have a atmosphere by natural processes following its emission (Eby et al., very persistent impact on radiative forcing (Myhre et al., 2013), lasting 2009; Ciais et al., 2013), the multi-century warming commitment from over a century (in the case of N2O) to hundreds of thousands from emissions to date in addition to warming already observed of years (for CO2). The radiative forcing impact of short-lived climate is estimated to range from slightly negative (i.e., a slight cooling forcers (SLCFs) such as methane (CH4) and aerosols, in contrast, relative to present-day) to slightly positive (Matthews and Caldeira, persists for at most about a decade (in the case of methane) down to 2008; Lowe et al., 2009; Gillett et al., 2011; Collins et al., 2013). only a few days. These different behaviours must be taken into account Some studies estimate a larger ZEC from CO2, but for cumulative in assessing the implications of any approach to calculating aggregate emissions much higher than those up to present day (Frölicher et al., emissions (Cross-Chapter Box 2 in this chapter). 2014; Ehlert and Zickfeld, 2017). The ZEC from past CO2 emissions is small because the continued warming effect from ocean thermal Geophysical warming commitment is defined as the unavoidable inertia is approximately balanced by declining radiative forcing due future warming resulting from physical Earth system inertia. Different to CO2 uptake by the ocean (Solomon et al., 2009; Goodwin et al., variants are discussed in the literature, including (i) the ‘constant 2015; Williams et al., 2017). Thus, although present-day CO2-induced composition commitment’ (CCC), defined by Meehl et al. (2007) as warming is irreversible on millennial time scales (without human the further warming that would result if atmospheric concentrations intervention such as active carbon dioxide removal or solar radiation of GHGs and other climate forcers were stabilised at the current level; modification; Section 1.4.1), past CO2 emissions do not commit to and (ii) and the ‘zero emissions commitment’ (ZEC), defined as the substantial further warming (Matthews and Solomon, 2013). further warming that would still occur if all future anthropogenic emissions of greenhouse gases and aerosol precursors were Sustained net zero anthropogenic emissions of CO2 and declining net eliminated instantaneously (Meehl et al., 2007; Collins et al., 2013). anthropogenic non-CO2 radiative forcing over a multi-decade period would halt anthropogenic global warming over that period, although The CCC is primarily associated with thermal inertia of the ocean it would not halt sea level rise or many other aspects of climate system (Hansen et al., 2005), and has led to the misconception that adjustment. The rate of decline of non-CO2 radiative forcing must be substantial future warming is inevitable (Matthews and Solomon, sufficient to compensate for the ongoing adjustment of the climate 2013). The CCC takes into account the warming from past emissions, system to this forcing (assuming it remains positive) due to ocean but also includes warming from future emissions (declining but still thermal inertia. It therefore depends on deep ocean response time non-zero) that are required to maintain a constant atmospheric scales, which are uncertain but of order centuries, corresponding to 64 Framing and Context Chapter 1 decline rates of non-CO2 radiative forcing of less than 1% per year. In measures affecting aerosol loading (e.g., Fernández et al., 2017). the longer term, Earth system feedbacks such as the release of carbon If present-day emissions of all GHGs (short- and long-lived) and from melting permafrost may require net negative CO2 emissions to aerosols (including sulphate, nitrate and carbonaceous aerosols) are maintain stable temperatures (Lowe and Bernie, 2018). eliminated (Figure 1.5, yellow lines) GMST rises over the following decade, driven by the removal of negative aerosol radiative forcing. For warming SLCFs, meaning those associated with positive radiative This initial warming is followed by a gradual cooling driven by the forcing such as methane, the ZEC is negative. Eliminating emissions decline in radiative forcing of short-lived greenhouse gases (Matthews 1 of these substances results in an immediate cooling relative to the and Zickfeld, 2012; Collins et al., 2013). Peak warming following present (Figure 1.5, magenta lines) (Frölicher and Joos, 2010; Matthews elimination of all emissions was assessed at a few tenths of a degree in and Zickfeld, 2012; Mauritsen and Pincus, 2017). Cooling SLCFs (those AR5, and century-scale warming was assessed to change only slightly associated with negative radiative forcing) such as sulphate aerosols relative to the time emissions are reduced to zero (Collins et al., 2013). create a positive ZEC, as elimination of these forcers results in rapid New evidence since AR5 suggests a larger methane forcing (Etminan increase in radiative forcing and warming (Figure 1.5, green lines) et al., 2016) but no revision in the range of aerosol forcing (although (Matthews and Zickfeld, 2012; Mauritsen and Pincus, 2017; Samset this remains an active field of research, e.g., Myhre et al., 2017). This et al., 2018). Estimates of the warming commitment from eliminating revised methane forcing estimate results in a smaller peak warming aerosol emissions are affected by large uncertainties in net aerosol and a faster temperature decline than assessed in AR5 (Figure 1.5, radiative forcing (Myhre et al., 2013, 2017) and the impact of other yellow line). Figure 1.5 | Warming commitment from past emissions of greenhouse gases and aerosols: Radiative forcing (top) and global mean surface temperature change (bottom) for scenarios with different combinations of greenhouse gas and aerosol precursor emissions reduced to zero in 2020. Variables were calculated using a simple climate–carbon cycle model (Millar et al., 2017a) with a simple representation of atmospheric chemistry (Smith et al., 2018). The bars on the right-hand side indicate the median warming in 2100 and 5–95% uncertainty ranges (also indicated by the plume around the yellow line) taking into account one estimate of uncertainty in climate response, effective radiative forcing and carbon cycle sensitivity, and constraining simple model parameters with response ranges from AR5 combined with historical climate observations (Smith et al., 2018). Temperatures continue to increase slightly after elimination of CO2 emissions (blue line) in response to constant non-CO2 forcing. The dashed blue line extrapolates one estimate of the current rate of warming, while dotted blue lines show a case where CO2 emissions are reduced linearly to zero assuming constant non-CO2 forcing after 2020. Under these highly idealized assumptions, the time to stabilize temperatures at 1.5°C is approximately double the time remaining to reach 1.5°C at the current warming rate. 65 Chapter 1 Framing and Context Expert judgement based on the available evidence (including model rate of deceleration starting immediately. Applying a similar approach simulations, radiative forcing and climate sensitivity) suggests that if to the multi-dataset average GMST used in this report gives an all anthropogenic emissions were reduced to zero immediately, any assessed likely range for the date at which warming reaches 1.5°C further warming beyond the 1°C already experienced would likely be of 2030 to 2052. The lower bound on this range, 2030, is supported less than 0.5°C over the next two to three decades, and also likely by multiple lines of evidence, including the AR5 assessment for the less than 0.5°C on a century time scale. likely range of warming (0.3°C–0.7°C) for the period 2016–2035 1 relative to 1986–2005. The upper bound, 2052, is supported by fewer Since most sources of emissions cannot, in reality, be brought to lines of evidence, so we have used the upper bound of the 5–95% zero instantaneously due to techno-economic inertia, the current confidence interval given by the Leach et al. (2018) method applied to rate of emissions also constitutes a conditional commitment to the multi-dataset average GMST, expressed as the upper limit of the future emissions and consequent warming depending on achievable likely range, to reflect the reliance on a single approach. Results are rates of emission reductions. The current level and rate of human- sensitive both to the confidence level chosen and the number of years induced warming determines both the time left before a temperature used to estimate the current rate of anthropogenic warming (5 years threshold is exceeded if warming continues (dashed blue line used here, to capture the recent acceleration due to rising non-CO2 in Figure 1.5) and the time over which the warming rate must be forcing). Since the rate of human-induced warming is proportional reduced to avoid exceeding that threshold (approximately indicated to the rate of CO2 emissions (Matthews et al., 2009; Zickfeld et al., by the dotted blue line in Figure 1.5). Leach et al. (2018) use a central 2009) plus a term approximately proportional to the rate of increase estimate of human-induced warming of 1.02°C in 2017, increasing in non-CO2 radiative forcing (Gregory and Forster, 2008; Allen et al., at 0.215°C per decade (Haustein et al., 2017), to argue that it will 2018; Cross-Chapter Box 2 in this chapter), these time scales also take 13–32 years (one-standard-error range) to reach 1.5°C if the provide an indication of minimum emission reduction rates required current warming rate continues, allowing 25–64 years to stabilise if a warming greater than 1.5°C is to be avoided (see Figure 1.5, temperatures at 1.5°C if the warming rate is reduced at a constant Supplementary Material 1.SM.6 and FAQ 1.2). Cross-Chapter Box 2 | Measuring Progress to Net Zero Emissions Combining Long-Lived and Short- Lived Climate Forcers Contributing Authors: Piers Forster (UK), Myles R. Allen (UK), Elmar Kriegler (Germany), Joeri Rogelj (Austria/Belgium), Seth Schultz (USA), Drew Shindell (USA), Kirsten Zickfeld (Canada/Germany) Emissions of many different climate forcers will affect the rate and magnitude of climate change over the next few decades (Myhre et al., 2013). Since these decades will determine when 1.5°C is reached or whether a warming greater than 1.5°C is avoided, understanding the aggregate impact of different forcing agents is particularly important in the context of 1.5°C pathways. Paragraph 17 of Decision 1 of the 21st Conference of the Parties on the adoption of the Paris Agreement specifically states that this report is to identify aggregate greenhouse gas emission levels compatible with holding the increase in global average temperatures to 1.5°C above pre-industrial levels (see Chapter 2). This request highlights the need to consider the implications of different methods of aggregating emissions of different gases, both for future temperatures and for other aspects of the climate system (Levasseur et al., 2016; Ocko et al., 2017). To date, reporting of GHG emissions under the UNFCCC has used Global Warming Potentials (GWPs) evaluated over a 100-year time horizon (GWP100) to combine multiple climate forcers. IPCC Working Group 3 reports have also used GWP100 to represent multi-gas pathways (Clarke et al., 2014). For reasons of comparability and consistency with current practice, Chapter 2 in this Special Report continues to use this aggregation method. Numerous other methods of combining different climate forcers have been proposed, such as the Global Temperature-change Potential (GTP; Shine et al., 2005) and the Global Damage Potential (Tol et al., 2012; Deuber et al., 2013). Climate forcers fall into two broad categories in terms of their impact on global temperature (Smith et al., 2012): long-lived GHGs, such as CO2 and nitrous oxide (N2O), whose warming impact depends primarily on the total cumulative amount emitted over the past century or the entire industrial epoch; and short-lived climate forcers (SLCFs), such as methane and black carbon, whose warming impact depends primarily on current and recent annual emission rates (Reisinger et al., 2012; Myhre et al., 2013; Smith et al., 2013; Strefler et al., 2014). These different dependencies affect the emissions reductions required of individual forcers to limit warming to 1.5°C or any other level. Natural processes that remove CO2 permanently from the climate system are so slow that reducing the rate of CO2-induced warming to zero requires net zero global anthropogenic CO2 emissions (Archer and Brovkin, 2008; Matthews and Caldeira, 2008; Solomon et al., 66 Framing and Context Chapter 1 Cross-Chapter Box 2 (continued) 2009), meaning almost all remaining anthropogenic CO2 emissions must be compensated for by an equal rate of anthropogenic carbon dioxide removal (CDR). Cumulative CO2 emissions are therefore an accurate indicator of CO2-induced warming, except in periods of high negative CO2 emissions (Zickfeld et al., 2016), and potentially in century-long periods of near-stable temperatures (Bowerman et al., 2011; Wigley, 2018). In contrast, sustained constant emissions of a SLCF such as methane, would (after a few decades) be consistent with constant methane concentrations and hence very little additional methane-induced warming (Allen et al., 2018; Fuglestvedt et al., 1 2018). Both GWP and GTP would equate sustained SLCF emissions with sustained constant CO2 emissions, which would continue to accumulate in the climate system, warming global temperatures indefinitely. Hence nominally ‘equivalent’ emissions of CO2 and SLCFs, if equated conventionally using GWP or GTP, have very different temperature impacts, and these differences are particularly evident under ambitious mitigation characterizing 1.5°C pathways. Since the AR5, a revised usage of GWP has been proposed (Lauder et al., 2013; Allen et al., 2016), denoted GWP* (Allen et al., 2018), that addresses this issue by equating a permanently sustained change in the emission rate of an SLCF or SLCF-precursor (in tonnes-per-year), or other non-CO2 forcing (in watts per square metre), with a one-off pulse emission (in tonnes) of a fixed amount of CO2. Specifically, GWP* equates a 1 tonne-per-year increase in emission rate of an SLCF with a pulse emission of GWPH x H tonnes of CO2, where GWPH is the conventional GWP of that SLCF evaluated over time GWPH for SLCFs decreases with increasing time H, GWPH x H for SLCFs is less dependent on the choice of time horizon. Similarly, a permanent 1 W m −2 increase in radiative forcing has a similar temperature impact as the cumulative emission of H/AGWPH tonnes of CO2, where AGWPH is the Absolute Global Warming Potential of CO2 (Shine et al., 2005; Myhre et al., 2013; Allen et al., 2018). This indicates approximately how future changes in non- CO2 radiative forcing affect cumulative CO2 emissions consistent with any given level of peak warming. When combined using GWP*, cumulative aggregate GHG emissions are closely proportional to total GHG-induced warming, while the annual rate of GHG-induced warming is proportional to the annual rate of aggregate GHG emissions (see Cross-Chapter Box 2, Figure 1). This is not the case when emissions are aggregated using GWP or GTP, with discrepancies particularly pronounced when SLCF emissions are falling. Persistent net zero CO2-equivalent emissions containing a residual positive forcing contribution from SLCFs and aggregated using GWP100 or GTP would result in a steady decline of GMST. Net zero global emissions aggregated using GWP* (which corresponds to zero net emissions of CO2 and other long-lived GHGs like nitrous oxide, combined with near-constant SLCF forcing – see Figure 1.5) results in approximately stable GMST (Allen et al., 2018; Fuglestvedt et al., 2018 and Cross-Chapter Box 2, Figure 1, below). Whatever method is used to relate emissions of different greenhouse gases, scenarios achieving stable GMST well below 2°C require both near-zero net emissions of long-lived greenhouse gases and deep reductions in warming SLCFs (Chapter 2), in part to compensate for the reductions in cooling SLCFs that are expected to accompany reductions in CO2 emissions (Rogelj et al., 2016b; Hienola et al., 2018). Understanding the implications of different methods of combining emissions of different climate forcers is, however, helpful in tracking progress towards temperature stabilisation and ‘balance between anthropogenic emissions by sources and removals by sinks of greenhouse gases’ as stated in Article 4 of the Paris Agreement. Fuglestvedt et al. (2018) and Tanaka and O’Neill (2018) show that when, and even whether, aggregate GHG emissions need to reach net zero before 2100 to limit warming to 1.5°C depends on the scenario, aggregation method and mix of long-lived and short-lived climate forcers. The comparison of the impacts of different climate forcers can also consider more than their effects on GMST (Johansson, 2012; Tol et al., 2012; Deuber et al., 2013; Myhre et al., 2013; Cherubini and Tanaka, 2016). Climate impacts arise from both magnitude and rate of climate change, and from other variables such as precipitation (Shine et al., 2015). Even if GMST is stabilised, sea level rise and associated impacts will continue to increase (Sterner et al., 2014), while impacts that depend on CO2 concentrations such as ocean acidification may begin to reverse. From an economic perspective, comparison of different climate forcers ideally reflects the ratio of marginal economic damages if used to determine the exchange ratio of different GHGs under multi-gas regulation (Tol et al., 2012; Deuber et al., 2013; Kolstad et al., 2014). Emission reductions can interact with other dimensions of sustainable development (see Chapter 5). In particular, early action on some SLCFs (including actions that may warm the climate, such as reducing sulphur dioxide emissions) may have considerable societal co-benefits, such as reduced air pollution and improved public health with associated economic benefits (OECD, 2016; Shindell et al., 2016). Valuation of broadly defined social costs attempts to account for many of these additional non-climate factors along with climate-related impacts (Shindell, 2015; Sarofim et al., 2017; Shindell et al., 2017). See Chapter 4, Section 4.3.6, for a discussions of mitigation options, noting that mitigation priorities for different climate forcers depend on multiple economic and social criteria that vary between sectors, regions and countries. 67 Chapter 1 Framing and Context Cross-Chapter Box 2 (continued) 1 Cross-Chapter Box 2, Figure 1 | Implications of different approaches to calculating aggregate greenhouse gas emissions on a pathway to net zero. (a) Aggregate emissions of well-mixed greenhouse gases (WMGHGs) under the RCP2.6 mitigation scenario expressed as CO2-equivalent using GWP100 (blue); GTP100 (green) and GWP* (yellow). Aggregate WMGHG emissions appear to fall more rapidly if calculated using GWP* than using either GWP or GTP, primarily because GWP* equates a falling methane emission rate with negative CO2 emissions, as only active CO2 removal would have the same impact on radiative forcing and GMST as a reduction in methane emission rate. (b) Cumulative emissions of WMGHGs combined as in panel (a) (blue, green and yellow lines & left hand axis) and warming response to combined emissions (black dotted line and right hand axis, Millar et al. (2017a). The temperature response under ambitious mitigation is closely correlated with cumulative WMGHG emissions aggregated using GWP*, but with neither emission rate nor cumulative emissions if aggregated using GWP or GTP. At a global warming of 1.5°C, some seasons will be substantially 1.3 Impacts at 1.5°C and Beyond warmer than 1.5°C above pre-industrial (Seneviratne et al., 2016). Therefore, most regional impacts of a global mean warming of 1.5°C 1.3.1 Definitions will be different from those of a regional warming by 1.5°C. Consistent with the AR5 (IPCC, 2014a), ‘impact’ in this report refers The impacts of 1.5°C global warming will vary in both space and to the effects of climate change on human and natural systems. time (Ebi et al., 2016). For many regions, an increase in global Impacts may include the effects of changing hazards, such as the mean temperature by 1.5°C or 2°C implies substantial increases frequency and intensity of heat waves. ‘Risk’ refers to potential in the occurrence and/or intensity of some extreme events (Fischer negative impacts of climate change where something of value is at and Knutti, 2015; Karmalkar and Bradley, 2017; King et al., 2017; stake, recognizing the diversity of values. Risks depend on hazards, Chevuturi et al., 2018), resulting in different impacts (see Chapter exposure, vulnerability (including sensitivity and capacity to respond) 3). By comparing impacts at 1.5°C versus those at 2°C, this report and likelihood. Climate change risks can be managed through efforts discusses the ‘avoided impacts’ by maintaining global temperature to mitigate climate change forcers, adaptation of impacted systems, increase at or below 1.5°C as compared to 2°C, noting that these and remedial measures (Section 1.4.1). also depend on the pathway taken to 1.5°C (see Section 1.2.3 and Cross-Chapter Box 8 in Chapter 3 on 1.5°C warmer worlds). Many In the context of this report, regional impacts of global warming at impacts take time to observe, and because of the warming trend, 1.5°C and 2°C are assessed in Chapter 3. The ‘warming experience at impacts over the past 20 years were associated with a level of human- 1.5°C’ is that of regional climate change (temperature, rainfall, and induced warming that was, on average, 0.1°C–0.23°C colder than other changes) at the time when global average temperatures, as its present level, based on the AR5 estimate of the warming trend defined in Section 1.2.1, reach 1.5°C above pre-industrial (the same over this period (Section 1.2.1 and Kirtman et al., 2013). Attribution principle applies to impacts at any other global mean temperature). studies (e.g., van Oldenborgh et al., 2017) can address this bias, but Over the decade 2006–2015, many regions have experienced higher informal estimates of ‘recent impact experience’ in a rapidly warming than average levels of warming and some are already now 1.5°C or world necessarily understate the temperature-related impacts of the more warmer with respect to the pre-industrial period (Figure 1.3). current level of warming. 68 Framing and Context Chapter 1 1.3.2 Drivers of Impacts succession and other processes, rendering attribution of impacts at lower levels of warming difficult in certain situations. The same Impacts of climate change are due to multiple environmental drivers magnitude of warming can be lethal during one phase of the life besides rising temperatures, such as rising atmospheric CO2, shifting of an organism and irrelevant during another. Many ecosystems rainfall patterns (Lee et al., 2018), rising sea levels, increasing ocean (notably forests, coral reefs and others) undergo long-term acidification, and extreme events, such as floods, droughts, and heat successional processes characterised by varying levels of resilience waves (IPCC, 2014a). Changes in rainfall affect the hydrological cycle to environmental change over time. Organisms and ecosystems may 1 and water availability (Schewe et al., 2014; Döll et al., 2018; Saeed adapt to environmental change to a certain degree, through changes et al., 2018). Several impacts depend on atmospheric composition, in physiology, ecosystem structure, species composition or evolution. increasing atmospheric carbon dioxide levels leading to changes in Large-scale shifts in ecosystems may cause important feedbacks, plant productivity (Forkel et al., 2016), but also to ocean acidification in terms of changing water and carbon fluxes through impacted (Hoegh-Guldberg et al., 2007). Other impacts are driven by changes ecosystems – these can amplify or dampen atmospheric change at in ocean heat content such as the destabilization of coastal ice sheets regional to continental scale. Of particular concern is the response of and sea level rise (Bindoff et al., 2007; Chen et al., 2017), whereas most of the world’s forests and seagrass ecosystems, which play key impacts due to heat waves depend directly on ambient air or ocean roles as carbon sinks (Settele et al., 2014; Marbà et al., 2015). temperature (Matthews et al., 2017). Impacts can be direct, such as coral bleaching due to ocean warming, and indirect, such as reduced Some ambitious efforts to constrain atmospheric greenhouse gas tourism due to coral bleaching. Indirect impacts can also arise from concentrations may themselves impact ecosystems. In particular, mitigation efforts such as changed agricultural management (Section changes in land use, potentially required for massively enhanced 3.6.2) or remedial measures such as solar radiation modification production of biofuels (either as simple replacement of fossil fuels, or (Section 4.3.8, Cross-Chapter Box 10 in Chapter 4). as part of bioenergy with carbon capture and storage, BECCS) impact all other land ecosystems through competition for land (e.g., Creutzig, Impacts may also be triggered by combinations of factors, including 2016) (see Cross-Chapter Box 7 in Chapter 3, Section 3.6.2.1). ‘impact cascades’ (Cramer et al., 2014) through secondary consequences of changed systems. Changes in agricultural water Human adaptive capacity to a 1.5°C warmer world varies markedly availability caused by upstream changes in glacier volume are a for individual sectors and across sectors such as water supply, public typical example. Recent studies also identify compound events health, infrastructure, ecosystems and food supply. For example, den- (e.g., droughts and heat waves), that is, when impacts are induced sity and risk exposure, infrastructure vulnerability and resilience, gov- by the combination of several climate events (AghaKouchak et al., ernance, and institutional capacity all drive different impacts across 2014; Leonard et al., 2014; Martius et al., 2016; Zscheischler and a range of human settlement types (Dasgupta et al., 2014; Revi et al., Seneviratne, 2017). 2014; Rosenzweig et al., 2018). Additionally, the adaptive capacity of communities and human settlements in both rural and urban areas, There are now techniques to attribute impacts formally to especially in highly populated regions, raises equity, social justice and anthropogenic global warming and associated rainfall changes sustainable development issues. Vulnerabilities due to gender, age, (Rosenzweig et al., 2008; Cramer et al., 2014; Hansen et al., 2016), level of education and culture act as compounding factors (Arora- taking into account other drivers such as land-use change (Oliver and Jonsson, 2011; Cardona et al., 2012; Resurrección, 2013; Olsson et Morecroft, 2014) and pollution (e.g., tropospheric ozone; Sitch et al., al., 2014; Vincent et al., 2014). 2007). There are multiple lines of evidence that climate change has observable and often severely negative effects on people, especially 1.3.3 Uncertainty and Non-Linearity of Impacts where climate-sensitive biophysical conditions and socio-economic and political constraints on adaptive capacities combine to create Uncertainties in projections of future climate change and impacts high vulnerabilities (IPCC, 2012a, 2014a; World Bank, 2013). The come from a variety of different sources, including the assumptions character and severity of impacts depend not only on the hazards made regarding future emission pathways (Moss et al., 2010), the (e.g., changed climate averages and extremes) but also on the inherent limitations and assumptions of the climate models used for vulnerability (including sensitivities and adaptive capacities) of the projections, including limitations in simulating regional climate different communities and their exposure to climate threats. These variability (James et al., 2017), downscaling and bias-correction impacts also affect a range of natural and human systems, such methods (Ekström et al., 2015), the assumption of a linear scaling as terrestrial, coastal and marine ecosystems and their services; of impacts with GMST used in many studies (Lewis et al., 2017; King agricultural production; infrastructure; the built environment; human et al., 2018b), and in impact models (e.g., Asseng et al., 2013). The health; and other socio-economic systems (Rosenzweig et al., 2017). evolution of climate change also affects uncertainty with respect to impacts. For example, the impacts of overshooting 1.5°C and Sensitivity to changing drivers varies markedly across systems stabilization at a later stage compared to stabilization at 1.5°C and regions. Impacts of climate change on natural and managed without overshoot may differ in magnitude (Schleussner et al., 2016). ecosystems can imply loss or increase in growth, biomass or diversity at the level of species populations, interspecific relationships such as AR5 (IPCC, 2013b) and World Bank (2013) underscored the non- pollination, landscapes or entire biomes. Impacts occur in addition linearity of risks and impacts as temperature rises from 2°C to 4°C of to the natural variation in growth, ecosystem dynamics, disturbance, warming, particularly in relation to water availability, heat extremes, 69 Chapter 1 Framing and Context bleaching of coral reefs, and more. Recent studies (Schleussner et al., includes changes that could reduce emissions in the short-term but 2016; James et al., 2017; Barcikowska et al., 2018; King et al., 2018a) could lock in technology choices or practices that include significant assess the impacts of 1.5°C versus 2°C warming, with the same trade-offs for effectiveness of future adaptation and other forms of message of non-linearity. The resilience of ecosystems, meaning mitigation (Chapters 2 and 4). their ability either to resist change or to recover after a disturbance, may change, and often decline, in a non-linear way. An example Carbon dioxide removal (CDR) or ‘negative emissions’ activities 1 are reef ecosystems, with some studies suggesting that reefs will are considered in this report as distinct from the above mitigation change, rather than disappear entirely, and with particular species activities. While most mitigation activities focus on reducing the showing greater tolerance to coral bleaching than others (Pörtner amount of carbon dioxide or other greenhouse gases emitted, et al., 2014). A key issue is therefore whether ecosystems such as CDR aims to reduce concentrations already in the atmosphere. coral reefs survive an overshoot scenario, and to what extent they Technologies for CDR are mostly in their infancy despite their would be able to recover after stabilization at 1.5°C or higher levels importance to ambitious climate change mitigation pathways (Minx of warming (see Box 3.4). et al., 2017). Although some CDR activities such as reforestation and ecosystem restoration are well understood, the feasibility of massive-scale deployment of many CDR technologies remains an open question (IPCC, 2014b; Leung et al., 2014) (Chapters 2 and 4). 1.4 Strengthening the Global Response Technologies for the active removal of other greenhouse gases, such as methane, are even less developed, and are briefly discussed in This section frames the implementation options, enabling conditions Chapter 4. (discussed further in Cross-Chapter Box 3 on feasibility in this chapter), capacities and types of knowledge and their availability Climate change adaptation refers to the actions taken to manage (Blicharska et al., 2017) that can allow institutions, communities the impacts of climate change (IPCC, 2014a). The aim is to reduce and societies to respond to the 1.5°C challenge in the context of vulnerability and exposure to the harmful effects of climate change sustainable development and the Sustainable Development Goals (e.g., sea level rise, more intense extreme weather events or food (SDGs). It also addresses other relevant international agreements insecurity). It also includes exploring the potential beneficial such as the Sendai Framework for Disaster Risk Reduction. Equity and opportunities associated with climate change (for example, longer ethics are recognised as issues of importance in reducing vulnerability growing seasons or increased yields in some regions). Different and eradicating poverty. adaptation pathways can be undertaken. Adaptation can be incremental, or transformational, meaning fundamental attributes The connection between the enabling conditions for limiting global of the system are changed (Chapter 3 and 4). There can be limits warming to 1.5°C and the ambitions of the SDGs are complex across to ecosystem-based adaptation or the ability of humans to adapt scale and multi-faceted (Chapter 5). Climate mitigation–adaptation (Chapter 4). If there is no possibility for adaptive actions that can linkages, including synergies and trade-offs, are important when be applied to avoid an intolerable risk, these are referred to as considering opportunities and threats for sustainable development. hard adaptation limits, while soft adaptation limits are identified The IPCC AR5 acknowledged that ‘adaptation and mitigation when there are currently no options to avoid intolerable risks, but have the potential to both contribute to and impede sustainable they are theoretically possible (Chapter 3 and 4). While climate development, and sustainable development strategies and choices change is a global issue, impacts are experienced locally. Cities and have the potential to both contribute to and impede climate change municipalities are at the frontline of adaptation (Rosenzweig et al., responses’ (Denton et al., 2014). Climate mitigation and adaptation 2018), focusing on reducing and managing disaster risks due to measures and actions can reflect and enforce specific patterns extreme and slow-onset weather and climate events, installing flood of development and governance that differ amongst the world’s and drought early warning systems, and improving water storage regions (Gouldson et al., 2015; Termeer et al., 2017). The role of and use (Chapters 3 and 4 and Cross-Chapter Box 12 in Chapter 5). limited adaptation and mitigation capacity, limits to adaptation and Agricultural and rural areas, including often highly vulnerable remote mitigation, and conditions of mal-adaptation and mal-mitigation are and indigenous communities, also need to address climate-related assessed in this report (Chapters 4 and 5). risks by strengthening and making more resilient agricultural and other natural resource extraction systems. 1.4.1 Classifying Response Options Remedial measures are distinct from mitigation or adaptation, as Key broad categories of responses to the climate change problem are the aim is to temporarily reduce or offset warming (IPCC, 2012b). framed here. Mitigation refers to efforts to reduce or prevent the One such measure is solar radiation modification (SRM), also referred emission of greenhouse gases, or to enhance the absorption of gases to as solar radiation management in the literature, which involves already emitted, thus limiting the magnitude of future warming deliberate changes to the albedo of the Earth system, with the net (IPCC, 2014b). Mitigation requires the use of new technologies, effect of increasing the amount of solar radiation reflected from the clean energy sources, reduced deforestation, improved sustainable Earth to reduce the peak temperature from climate change (The Royal agricultural methods, and changes in individual and collective Society, 2009; Smith and Rasch, 2013; Schäfer et al., 2015). It should behaviour. Many of these may provide substantial co-benefits for air be noted that while some radiation modification measures, such as quality, biodiversity and sustainable development. Mal-mitigation cirrus cloud thinning (Kristjánsson et al., 2016), aim at enhancing 70 Framing and Context Chapter 1 outgoing long-wave radiation, SRM is used in this report to refer to between different levels of government, and the capacity to raise all direct interventions on the planetary radiation budget. This report financing and support for both technological and human resource does not use the term ‘geo-engineering’ because of inconsistencies development. For example, Lövbrand et al. (2017), argue that the in the literature, which uses this term to cover SRM, CDR or both, voluntary pledges submitted by states and non-state actors to meet whereas this report explicitly differentiates between CDR and SRM. the conditions of the Paris Agreement will need to be more firmly Large-scale SRM could potentially be used to supplement mitigation coordinated, evaluated and upscaled. in overshoot scenarios to keep the global mean temperature below 1 1.5°C and temporarily reduce the severity of near-term impacts (e.g., Barriers for transitioning from climate change mitigation and MacMartin et al., 2018). The impacts of SRM (both biophysical and adaptation planning to practical policy implementation include societal), costs, technical feasibility, governance and ethical issues finance, information, technology, public attitudes, social values associated need to be carefully considered (Schäfer et al., 2015; and practices (Whitmarsh et al., 2011; Corner and Clarke, 2017), Section 4.3.8 and Cross-Chapter Box 10 in Chapter 4). and human resource constraints. Institutional capacity to deploy available knowledge and resources is also needed (Mimura et al., 1.4.2 Governance, Implementation and Policies 2014). Incorporating strong linkages across sectors, devolution of power and resources to sub-national and local governments with A challenge in creating the enabling conditions of a 1.5°C warmer the support of national government, and facilitating partnerships world is the governance capacity of institutions to develop, implement among public, civic, private sectors and higher education institutions and evaluate the changes needed within diverse and highly (Leal Filho et al., 2018) can help in the implementation of identified interlinked global social-ecological systems (Busby, 2016) (Chapter response options (Chapter 4). Implementation challenges of 1.5°C 4). Policy arenas, governance structures and robust institutions are pathways are larger than for those that are consistent with limiting key enabling conditions for transformative climate action (Chapter warming to well below 2°C, particularly concerning scale and speed 4). It is through governance that justice, ethics and equity within of the transition and the distributional impacts on ecosystems and the adaptation–mitigation–sustainable development nexus can be socio-economic actors. Uncertainties in climate change at different addressed (von Stechow et al., 2016) (Chapter 5). scales and capacities to respond combined with the complexities of coupled social and ecological systems point to a need for diverse and Governance capacity includes a wide range of activities and efforts adaptive implementation options within and among different regions needed by different actors to develop coordinated climate mitigation involving different actors. The large regional diversity between highly and adaptation strategies in the context of sustainable development, carbon-invested economies and emerging economies are important taking into account equity, justice and poverty eradication. Significant considerations for sustainable development and equity in pursuing governance challenges include the ability to incorporate multiple efforts to limit warming to 1.5°C. Key sectors, including energy, food stakeholder perspectives in the decision-making process to reach systems, health, and water supply, also are critical to understanding meaningful and equitable decisions, interactions and coordination these connections. Cross-Chapter Box 3 | Framing Feasibility: Key Concepts and Conditions for Limiting Global Temperature Increases to 1.5°C Contributing Authors: William Solecki (USA), Anton Cartwright (South Africa), Wolfgang Cramer (France/Germany), James Ford (UK/Canada), Kejun Jiang (China), Joana Portugal Pereira (UK/Portugal), Joeri Rogelj (Austria/Belgium), Linda Steg (Netherlands), Henri Waisman (France) This Cross-Chapter Box describes the concept of feasibility in relation to efforts to limit global warming to 1.5°C in the context of sustainable development and efforts to eradicate poverty and draws from the understanding of feasibility emerging within the IPCC (IPCC, 2017). Feasibility can be assessed in different ways, and no single answer exists as to the question of whether it is feasible to limit warming to 1.5°C. This implies that an assessment of feasibility would go beyond a ‘yes’ or a ‘no’. Rather, feasibility provides a frame to understand the different conditions and potential responses for implementing adaptation and mitigation pathways, and options compatible with a 1.5°C warmer world. This report assesses the overall feasibility of limiting warming to 1.5°C, and the feasibility of adaptation and mitigation options compatible with a 1.5°C warmer world, in six dimensions: Geophysical: What global emission pathways could be consistent with conditions of a 1.5°C warmer world? What are the physical potentials for adaptation? Environmental-ecological: What are the ecosystem services and resources, including geological storage capacity and related rate of needed land-use change, available to promote transformations, and to what extent are they compatible with enhanced resilience? Technological: What technologies are available to support transformation? Economic: What economic conditions could support transformation? 71 Chapter 1 Framing and Context Cross-Chapter Box 3 (continued) Socio-cultural: What conditions could support transformations in behaviour and lifestyles? To what extent are the transformations socially acceptable and consistent with equity? Institutional: What institutional conditions are in place to support transformations, including multi-level governance, institutional capacity, and political support? 1 Assessment of feasibility in this report starts by evaluating the unavoidable warming from past emissions (Section 1.2.4) and identifying mitigation pathways that would lead to a 1.5°C world, which indicates that rapid and deep deviations from current emission pathways are necessary (Chapter 2). In the case of adaptation, an assessment of feasibility starts from an evaluation of the risks and impacts of climate change (Chapter 3). To mitigate and adapt to climate risks, system-wide technical, institutional and socio-economic transitions would be required, as well as the implementation of a range of specific mitigation and adaptation options. Chapter 4 applies various indicators categorised in these six dimensions to assess the feasibility of illustrative examples of relevant mitigation and adaptation options (Section 4.5.1). Such options and pathways have different effects on sustainable development, poverty eradication and adaptation capacity (Chapter 5). The six feasibility dimensions interact in complex and place-specific ways. Synergies and trade-offs may occur between the feasibility dimensions, and between specific mitigation and adaptation options (Section 4.5.4). The presence or absence of enabling conditions would affect the options that comprise feasibility pathways (Section 4.4), and can reduce trade-offs and amplify synergies between options. Sustainable development, eradicating poverty and reducing inequalities are not only preconditions for feasible transformations, but the interplay between climate action (both mitigation and adaptation options) and the development patterns to which they apply may actually enhance the feasibility of particular options (see Chapter 5). The connections between the feasibility dimensions can be specified across three types of effects (discussed below). Each of these dimensions presents challenges and opportunities in realizing conditions consistent with a 1.5°C warmer world. Systemic effects: Conditions that have embedded within them system-level functions that could include linear and non-linear connections and feedbacks. For example, the deployment of technology and large installations (e.g., renewable or low carbon energy mega-projects) depends upon economic conditions (costs, capacity to mobilize investments for R&D), social or cultural conditions (acceptability), and institutional conditions (political support; e.g., Sovacool et al., 2015). Case studies can demonstrate system-level interactions and positive or negative feedback effects between the different conditions (Jacobson et al., 2015; Loftus et al., 2015). This suggests that each set of conditions and their interactions need to be considered to understand synergies, inequities and unintended consequences. Dynamic effects: Conditions that are highly dynamic and vary over time, especially under potential conditions of overshoot or no overshoot. Some dimensions might be more time sensitive or sequential than others (i.e., if conditions are such that it is no longer geophysically feasible to avoid overshooting 1.5°C, the social and institutional feasibility of avoiding overshoot will be no longer relevant). Path dependencies, risks of legacy lock-ins related to existing infrastructures, and possibilities of acceleration permitted by cumulative effects (e.g., dramatic cost decreases driven by learning-by-doing) are all key features to be captured. The effects can play out over various time scales and thus require understanding the connections between near-term (meaning within the next several years to two decades) and long-term implications (meaning over the next several decades) when assessing feasibility conditions. Spatial effects: Conditions that are spatially variable and scale dependent, according to context-specific factors such as regional- scale environmental resource limits and endowment; economic wealth of local populations; social organisation, cultural beliefs, values and worldviews; spatial organisation, including conditions of urbanisation; and financial and institutional and governance capacity. This means that the conditions for achieving the global transformation required for a 1.5°C world will be heterogeneous and vary according to the specific context. On the other hand, the satisfaction of these conditions may depend upon global-scale drivers, such as international flows of finance, technologies or capacities. This points to the need for understanding feasibility to capture the interplay between the conditions at different scales. With each effect, the interplay between different conditions influences the feasibility of both pathways (Chapter 2) and options (Chapter 4), which in turn affect the likelihood of limiting warming to 1.5°C. The complexity of these interplays triggers unavoidable uncertainties, requiring transformations that remain robust under a range of possible futures that limit warming to 1.5°C. 72 Framing and Context Chapter 1 1.4.3 Transformation, Transformation Pathways, chosen could act to synergistically enhance mitigation, adaptation and Transition: Evaluating Trade-Offs and and sustainable development, or they may result in trade-offs Synergies Between Mitigation, Adaptation which positively impact some aspects and negatively impact others. and Sustainable Development Goals Climate change is expected to decrease the likelihood of achieving the Sustainable Development Goals (SDGs). While some strategies Embedded in the goal of limiting warming to 1.5°C is the limiting warming towards 1.5°C are expected to significantly increase opportunity for intentional societal transformation (see Box 1.1 the likelihood of meeting those goals while also providing synergies 1 on the Anthropocene). The form and process of transformation are for climate adaptation and mitigation (Chapter 5). varied and multifaceted (Pelling, 2011; O’Brien et al., 2012; O’Brien and Selboe, 2015; Pelling et al., 2015). Fundamental elements of Dramatic transformations required to achieve the enabling conditions 1.5°C-related transformation include a decoupling of economic for a 1.5°C warmer world could impose trade-offs on dimensions growth from energy demand and CO2 emissions; leap-frogging of development (IPCC, 2014d; Olsson et al., 2014). Some choices development to new and emerging low-carbon, zero-carbon and of adaptation methods also could adversely impact development carbon-negative technologies; and synergistically linking climate (Olsson et al., 2014). This report recognizes the potential for adverse mitigation and adaptation to global scale trends (e.g., global trade impacts and focuses on finding the synergies between limiting and urbanization) that will enhance the prospects for effective warming, sustainable development, and eradicating poverty, thus climate action, as well as enhanced poverty reduction and greater highlighting pathways that do not constrain other goals, such as equity (Tschakert et al., 2013; Rogelj et al., 2015; Patterson et al., sustainable development and eradicating poverty. 2017) (Chapters 4 and 5). The connection between transformative climate action and sustainable development illustrates a complex The report is framed to address these multiple goals simultaneously coupling of systems that have important spatial and time scale lag and assesses the conditions to achieve a cost-effective and socially effects and implications for process and procedural equity, including acceptable solution, rather than addressing these goals piecemeal intergenerational equity and for non-human species (Cross-Chapter (von Stechow et al., 2016) (Section 4.5.4 and Chapter 5), although Box 4 in this chapter, Chapter 5). Adaptation and mitigation transition there may be different synergies and trade-offs between a 2°C (von pathways highlight the importance of cultural norms and values, Stechow et al., 2016) and 1.5°C warmer world (Kainuma et al., sector-specific context, and proximate (i.e., occurrence of an extreme 2017). Climate-resilient development pathways (see Cross-Chapter event) drivers that when acting together enhance the conditions for Box 12 in Chapter 5 and Glossary) are trajectories that strengthen societal transformation (Solecki et al., 2017; Rosenzweig et al., 2018) sustainable development, including mitigating and adapting to (Chapters 4 and 5). climate change and efforts to eradicate poverty while promoting fair and cross-scalar resilience in a changing climate. They take into Diversity and flexibility in implementation choices exist for adaptation, account dynamic livelihoods; the multiple dimensions of poverty, mitigation (including carbon dioxide removal, CDR) and remedial structural inequalities; and equity between and among poor and measures (such as solar radiation modification, SRM), and a potential non-poor people (Olsson et al., 2014). Climate-resilient development for trade-offs and synergies between these choices and sustainable pathways can be considered at different scales, including cities, rural development (IPCC, 2014d; Olsson et al., 2014). The responses areas, regions or at global level (Denton et al., 2014; Chapter 5). Cross-Chapter Box 4 | Sustainable Development and the Sustainable Development Goals Contributing Authors: Diana Liverman (USA), Mustafa Babiker (Sudan), Purnamita Dasgupta (India), Riyanti Djanlante (Japan/Indonesia), Stephen Humphreys (UK/Ireland), Natalie Mahowald (USA), Yacob Mulugetta (UK/Ethiopia), Virginia Villariño (Argentina), Henri Waisman (France) Sustainable development is most often defined as ‘development that meets the needs of the present without compromising the ability of future generations to meet their own needs’ (WCED, 1987) and includes balancing social well-being, economic prosperity and environmental protection. The AR5 used this definition and linked it to climate change (Denton et al., 2014). The most significant step since AR5 is the adoption of the UN Sustainable Development Goals, and the emergence of literature that links them to climate (von Stechow et al., 2015; Wright et al., 2015; Epstein and Theuer, 2017; Hammill and Price-Kelly, 2017; Kelman, 2017; Lofts et al., 2017; Maupin, 2017; Gomez-Echeverri, 2018). In September 2015, the UN endorsed a universal agenda – ‘Transforming our World: the 2030 Agenda for Sustainable Development’ – which aims ‘to take the bold and transformative steps which are urgently needed to shift the world onto a sustainable and resilient path’. Based on a participatory process, the resolution in support of the 2030 agenda adopted 17 non-legally-binding Sustainable Development Goals (SDGs) and 169 targets to support people, prosperity, peace, partnerships and the planet (Kanie and Biermann, 2017). 73 Chapter 1 Framing and Context Cross-Chapter Box 4 (continued) The SDGs expanded efforts to reduce poverty and other deprivations under the UN Millennium Development Goals (MDGs). There were improvements under the MDGs between 1990 and 2015, including reducing overall poverty and hunger, reducing infant mortality, and improving access to drinking water (UN, 2015a). However, greenhouse gas emissions increased by more than 50% from 1990 to 2015, and 1.6 billion people were still living in multidimensional poverty with persistent inequalities in 2015 (Alkire et al., 2015). 1 The SDGs raise the ambition for eliminating poverty, hunger, inequality and other societal problems while protecting the environment. They have been criticised: as too many and too complex, needing more realistic targets, overly focused on 2030 at the expense of longer-term objectives, not embracing all aspects of sustainable development, and even contradicting each other (Horton, 2014; Death and Gabay, 2015; Biermann et al., 2017; Weber, 2017; Winkler and Satterthwaite, 2017). Climate change is an integral influence on sustainable development, closely related to the economic, social and environmental dimensions of the SDGs. The IPCC has woven the concept of sustainable development into recent assessments, showing how climate change might undermine sustainable development, and the synergies between sustainable development and responses to climate change (Denton et al., 2014). Climate change is also explicit in the SDGs. SDG13 specifically requires ‘urgent action to address climate change and its impacts’. The targets include strengthening resilience and adaptive capacity to climate-related hazards and natural disasters; integrating climate change measures into national policies, strategies and planning; and improving education, awareness- raising and human and institutional capacity. Targets also include implementing the commitment undertaken by developed-country parties to the UNFCCC to the goal of mobilizing jointly 100 billion USD annually by 2020 and operationalizing the Green Climate Fund, as well as promoting mechanisms for raising capacity for effective climate change-related planning and management in least developed countries and Small Island Developing States, including focusing on women, youth and local and marginalised communities. SDG13 also acknowledges that the UNFCCC is the primary international, intergovernmental forum for negotiating the global response to climate change. Climate change is also mentioned in SDGs beyond SDG13, for example in goal targets 1.5, 2.4, 11.B, 12.8.1 related to poverty, hunger, cities and education respectively. The UNFCCC addresses other SDGs in commitments to ‘control, reduce or prevent anthropogenic emissions of greenhouse gases […] in all relevant sectors, including the energy, transport, industry, agriculture, forestry and waste management sectors’ (Art4, 1(c)) and to work towards ‘the conservation and enhancement, as appropriate, of […] biomass, forests and oceans as well as other terrestrial, coastal and marine ecosystems’ (Art4, 1(d)). This corresponds to SDGs that seek clean energy for all (Goal 7), sustainable industry (Goal 9) and cities (Goal 11) and the protection of life on land and below water (14 and 15). The SDGs and UNFCCC also differ in their time horizons. The SDGs focus primarily on 2030 whereas the Paris Agreement sets out that ‘Parties aim […] to achieve a balance between anthropogenic emissions by sources and removals by sinks of greenhouse gases in the second half of this century’. The IPCC decision to prepare this report on the impacts of 1.5°C and associated emission pathways explicitly asked for the assessment to be in the context of sustainable development and efforts to eradicate poverty. Chapter 1 frames the interaction between sustainable development, poverty eradication and ethics and equity. Chapter 2 assesses how risks and synergies of individual mitigation measures interact with 1.5°C pathways within the context of the SDGs and how these vary according to the mix of measures in alternative mitigation portfolios (Section 2.5). Chapter 3 examines the impacts of 1.5°C global warming on natural and human systems with comparison to 2°C and provides the basis for considering the interactions of climate change with sustainable development in Chapter 5. Chapter 4 analyses strategies for strengthening the response to climate change, many of which interact with sustainable development. Chapter 5 takes sustainable development, eradicating poverty and reducing inequalities as its focal point for the analysis of pathways to 1.5°C and discusses explicitly the linkages between achieving SDGs while eradicating poverty and reducing inequality. 74 Framing and Context Chapter 1 Cross-Chapter Box 4 (continued) 1 Cross-Chapter Box 4, Figure 1 | Climate action is number 13 of the UN Sustainable Development Goals. 1.5 Assessment Frameworks and Emerging 1.5.1 Knowledge Sources and Evidence Methodologies that Integrate Climate Used in the Report Change Mitigation and Adaptation with Sustainable Development This report is based on a comprehensive assessment of documented evidence of the enabling conditions to pursuing efforts to limit the This report employs information and data that are global in scope global average temperature rise to 1.5°C and adapting to this level and include region-scale analysis. It also includes syntheses of of warming in the overarching context of the Anthropocene (Delanty municipal, sub-national, and national case studies. Global level and Mota, 2017). Two sources of evidence are used: peer-reviewed statistics including physical and social science data are used, as scientific literature and ‘grey’ literature in accordance with procedure well as detailed and illustrative case study material of particular on the use of literature in IPCC reports (IPCC, 2013a, Annex 2 to conditions and contexts. The assessment provides the state of Appendix A), with the former being the dominant source. Grey knowledge, including an assessment of confidence and uncertainty. literature is largely used on key issues not covered in peer-reviewed The main time scale of the assessment is the 21st century and the literature. time is separated into the near-, medium-, and long-term. Near-term refers to the coming decade, medium-term to the period 2030–2050, The peer-reviewed literature includes the following sources: 1) while long-term refers to 2050–2100. Spatial and temporal contexts knowledge regarding the physical climate system and human-induced are illustrated throughout, including: assessment tools that include changes, associated impacts, vulnerabilities, and adaptation options, dynamic projections of emission trajectories and the underlying established from work based on empirical evidence, simulations, energy and land transformation (Chapter 2); methods for assessing modelling, and scenarios, with emphasis on new information since observed impacts and projected risks in natural and managed the publication of the IPCC AR5 to the cut-off date for this report ecosystems and at 1.5°C and higher levels of warming in natural and (15th of May 2018); 2) humanities and social science theory and managed ecosystems and human systems (Chapter 3); assessments knowledge from actual human experiences of climate change of the feasibility of mitigation and adaptation options (Chapter 4); risks and vulnerability in the context of social-ecological systems, and linkages of the Shared Socioeconomic Pathways (SSPs) and development, equity, justice, and governance, and from indigenous Sustainable Development Goals (SDGs) (Cross-Chapter Boxes 1 and knowledge systems; and 3) mitigation pathways based on climate 4 in this chapter, Chapter 2 and Chapter 5). projections into the future. 75 Chapter 1 Framing and Context The grey literature category extends to empirical observations, Global climate warming has already reached approximately 1°C interviews, and reports from government, industry, research institutes, (see Section 1.2.1) relative to pre-industrial conditions, and thus conference proceedings and international or other organisations. ‘climate at 1.5°C global warming’ corresponds to approximately Incorporating knowledge from different sources, settings and the addition of only half a degree of warming compared to the information channels while building awareness at various levels will present day, comparable to the warming that has occurred since advance decision-making and motivate implementation of context- the 1970s (Bindoff et al., 2013). Methods used in the attribution of 1 specific responses to 1.5°C warming (Somanathan et al., 2014). observed changes associate with this recent warming are therefore The assessment does not assess non-written evidence and does not also applicable to assessments of future changes in climate at 1.5°C use oral evidence, media reports or newspaper publications. With warming, especially in cases where no climate model simulations or important exceptions, such as China, published knowledge from analyses are available. the most vulnerable parts of the world to climate change is limited (Czerniewicz et al., 2017). Impacts of 1.5°C global warming can be assessed in part from regional and global climate changes that have already been detected 1.5.2 Assessment Frameworks and Methodologies and attributed to human influence (e.g., Schleussner et al., 2017) and are components of the climate system that are most responsive to Climate models and associated simulations current and projected future forcing. For this reason, when specific projections are missing for 1.5°C global warming, some of the The multiple sources of climate model information used in this assessments of climate change provided in Chapter 3 (Section 3.3) assessment are provided in Chapter 2 (Section 2.2) and Chapter build upon joint assessments of (i) changes that were observed and 3 (Section 3.2). Results from global simulations, which have also attributed to human influence up to the present, that is, for 1°C been assessed in previous IPCC reports and that are conducted as global warming and (ii) projections for higher levels of warming (e.g., part of the World Climate Research Programme (WCRP) Coupled 2°C, 3°C or 4°C) to assess the changes at 1.5°C. Such assessments Models Intercomparison Project (CMIP) are used. The IPCC AR4 and are for transient changes only (see Chapter 3, Section 3.3). Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) reports were mostly based on Besides quantitative detection and attribution methods, assessments simulations from the CMIP3 experiment, while the AR5 was mostly can also be based on indigenous and local knowledge (see Chapter 4, based on simulations from the CMIP5 experiment. The simulations Box 4.3). While climate observations may not be available to assess of the CMIP3 and CMIP5 experiments were found to be very impacts from a scientific perspective, local community knowledge similar (e.g., Knutti and Sedláček, 2012; Mueller and Seneviratne, can also indicate actual impacts (Brinkman et al., 2016; Kabir et al., 2014). In addition to the CMIP3 and CMIP5 experiments, results 2016). The challenge is that a community’s perception of loss due from coordinated regional climate model experiments (e.g., the to the impacts of climate change is an area that requires further Coordinated Regional Climate Downscaling Experiment, CORDEX) research (Tschakert et al., 2017). have been assessed and are available for different regions (Giorgi and Gutowski, 2015). For instance, assessments based on publications Costs and benefits analysis from an extension of the IMPACT2C project (Vautard et al., 2014; Jacob and Solman, 2017) are newly available for 1.5°C projections. Cost–benefit analyses are common tools used for decision-making, Recently, simulations from the ‘Half a degree Additional warming, whereby the costs of impacts are compared to the benefits from Prognosis and Projected Impacts’ (HAPPI) multimodel experiment different response actions (IPCC, 2014a, b). However, for the have been performed to specifically assess climate changes at 1.5°C case of climate change, recognising the complex inter-linkages vs 2°C global warming (Mitchell et al., 2016). The HAPPI protocol of the Anthropocene, cost–benefit analysis tools can be difficult consists of coupled land–atmosphere initial condition ensemble to use because of disparate impacts versus costs and complex simulations with prescribed sea surface temperatures (SSTs); sea ice, interconnectivity within the global social-ecological system (see GHG and aerosol concentrations; and solar and volcanic activity that Box 1.1 and Cross-Chapter Box 5 in Chapter 2). Some costs are coincide with three forced climate states: present-day (2006–2015) relatively easily quantifiable in monetary terms but not all. Climate (see Section 1.2.1) and future (2091–2100) either with 1.5°C or 2°C change impacts human lives and livelihoods, culture and values, and global warming (prescribed by modified SSTs). whole ecosystems. It has unpredictable feedback loops and impacts on other regions (IPCC, 2014a), giving rise to indirect, secondary, Detection and attribution of change in climate and impacted systems tertiary and opportunity costs that are typically extremely difficult to quantify. Monetary quantification is further complicated by the fact Formalized scientific methods are available to detect and attribute that costs and benefits can occur in different regions at very different impacts of greenhouse gas forcing on observed changes in climate times, possibly spanning centuries, while it is extremely difficult if not (e.g., Hegerl et al., 2007; Seneviratne et al., 2012; Bindoff et al., 2013) impossible to meaningfully estimate discount rates for future costs and impacts of climate change on natural and human systems (e.g., and benefits. Thus standard cost–benefit analyses become difficult Stone et al., 2013; Hansen and Cramer, 2015; Hansen et al., 2016). to justify (IPCC, 2014a; Dietz et al., 2016) and are not used as an The reader is referred to these sources, as well as to the AR5 for more assessment tool in this report. background on these methods. 76 Framing and Context Chapter 1 1.6 Confidence, Uncertainty and Risk always problematic, but in the context of robust decision-making, many near-term policies that are needed to keep open the option of limiting warming to 1.5°C may be the same, regardless of the actual This report relies on the IPCC’s uncertainty guidance provided in probability that the goal will be met (Knutti et al., 2015). Mastrandrea et al. (2011) and sources given therein. Two metrics for qualifying key findings are used: 1 Confidence: Five qualifiers are used to express levels of confidence 1.7 Storyline of the Report in key findings, ranging from very low, through low, medium, high, to very high. The assessment of confidence involves at least The storyline of this report (Figure 1.6) includes a set of interconnected two dimensions, one being the type, quality, amount or internal components. The report consists of five chapters (plus Supplementary consistency of individual lines of evidence, and the second being Material for Chapters 1 through 4), a Technical Summary and a the level of agreement between different lines of evidence. Very Summary for Policymakers. It also includes a set of boxes to elucidate high confidence findings must either be supported by a high level specific or cross-cutting themes, as well as Frequently Asked of agreement across multiple lines of mutually independent and Questions for each chapter, a Glossary, and several other Annexes. individually robust lines of evidence or, if only a single line of evidence is available, by a very high level of understanding underlying that At a time of unequivocal and rapid global warming, this report evidence. Findings of low or very low confidence are presented only emerges from the long-term temperature goal of the Paris Agreement if they address a topic of major concern. – strengthening the global response to the threat of climate change by pursuing efforts to limit warming to 1.5°C through reducing Likelihood: A calibrated language scale is used to communicate emissions to achieve a balance between anthropogenic emissions by assessed probabilities of outcomes, ranging from exceptionally sources and removals by sinks of greenhouse gases. The assessment unlikely (<1%), extremely unlikely (<5%), very unlikely (<10%), focuses first, in Chapter 1, on how 1.5°C is defined and understood, unlikely (<33%), about as likely as not (33–66%), likely (>66%), very what is the current level of warming to date, and the present likely (>90%), extremely likely (>95%) to virtually certain (>99%). trajectory of change. The framing presented in Chapter 1 provides the These terms are normally only applied to findings associated with basis through which to understand the enabling conditions of a 1.5°C high or very high confidence. Frequency of occurrence within a model warmer world and connections to the SDGs, poverty eradication, and ensemble does not correspond to actual assessed probability of equity and ethics. outcome unless the ensemble is judged to capture and represent the full range of relevant uncertainties. In Chapter 2, scenarios of a 1.5°C warmer world and the associated pathways are assessed. The pathways assessment builds upon Three specific challenges arise in the treatment of uncertainty and the AR5 with a greater emphasis on sustainable development in risk in this report. First, the current state of the scientific literature on mitigation pathways. All pathways begin now and involve rapid 1.5°C means that findings based on multiple lines of robust evidence and unprecedented societal transformation. An important framing for which quantitative probabilistic results can be expressed may be device for this report is the recognition that choices that determine few in number, and those that do exist may not be the most policy- emissions pathways, whether ambitious mitigation or ‘no policy’ relevant. Hence many key findings are expressed using confidence scenarios, do not occur independently of these other changes and qualifiers alone. are, in fact, highly interdependent. Second, many of the most important findings of this report are Projected impacts that emerge in a 1.5°C warmer world and beyond conditional because they refer to ambitious mitigation scenarios, are dominant narrative threads of the report and are assessed in potentially involving large-scale technological or societal Chapter 3. The chapter focuses on observed and attributable global transformation. Conditional probabilities often depend strongly on and regional climate changes and impacts and vulnerabilities. The how conditions are specified, such as whether temperature goals projected impacts have diverse and uneven spatial, temporal, human, are met through early emission reductions, reliance on negative economic, and ecological system-level manifestations. Central to the emissions, or through a low climate response. Whether a certain assessment is the reporting of impacts at 1.5°C and 2°C, potential risk is considered high at 1.5°C may therefore depend strongly on impacts avoided through limiting warming to 1.5°C, and, where how 1.5°C is specified, whereas a statement that a certain risk may possible, adaptation potential and limits to adaptive capacity. be substantially higher at 2°C relative to 1.5°C may be much more robust. Response options and associated enabling conditions emerge next, in Chapter 4. Attention is directed to exploring questions of adaptation Third, achieving ambitious mitigation goals will require active, and mitigation implementation, integration, and transformation in goal-directed efforts aiming explicitly for specific outcomes and a highly interdependent world, with consideration of synergies and incorporating new information as it becomes available (Otto et trade-offs. Emission pathways, in particular, are broken down into al., 2015). This shifts the focus of uncertainty from the climate policy options and instruments. The role of technological choices, outcome itself to the level of mitigation effort that may be required institutional capacity and global-scale trends like urbanization and to achieve it. Probabilistic statements about human decisions are changes in ecosystems are assessed. 77 Chapter 1 Framing and Context Chapter 5 covers linkages between achieving the SDGs and a 1.5°C Progress along these pathways involves inclusive processes, warmer world and turns toward identifying opportunities and institutional integration, adequate finance and technology, and challenges of transformation. This is assessed within a transition to attention to issues of power, values, and inequalities to maximize climate-resilient development pathways and connection between the the benefits of pursuing climate stabilisation at 1.5°C and the goals evolution towards 1.5°C, associated impacts, and emission pathways. of sustainable development at multiple scales of human and natural Positive and negative effects of adaptation and mitigation response systems from global, regional, national to local and community 1 measures and pathways for a 1.5°C warmer world are examined. levels. Figure 1.6 | Schematic of report storyline. 78 Framing and Context Chapter 1 Frequently Asked Questions FAQ 1.1 | Why are we Talking about 1.5°C? Summary: Climate change represents an urgent and potentially irreversible threat to human societies and the planet. In recognition of this, the overwhelming majority of countries around the world adopted the Paris Agree- ment in December 2015, the central aim of which includes pursuing efforts to limit global temperature rise 1 to 1.5°C. In doing so, these countries, through the United Nations Framework Convention on Climate Change (UNFCCC), also invited the IPCC to provide a Special Report on the impacts of global warming of 1.5°C above pre- industrial levels and related global greenhouse gas emissions pathways. At the 21st Conference of the Parties (COP21) in December 2015, 195 nations adopted the Paris Agreement2. The first instrument of its kind, the landmark agreement includes the aim to strengthen the global response to the threat of climate change by ‘holding the increase in the global average temperature to well below 2°C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5°C above pre-industrial levels’. The first UNFCCC document to mention a limit to global warming of 1.5°C was the Cancun Agreement, adopted at the sixteenth COP (COP16) in 2010. The Cancun Agreement established a process to periodically review the ‘adequacy of the long-term global goal (LTGG) in the light of the ultimate objective of the Convention and the overall progress made towards achieving the LTGG, including a consideration of the implementation of the commitments under the Convention’. The definition of LTGG in the Cancun Agreement was ‘to hold the increase in global average temperature below 2°C above pre-industrial levels’. The agreement also recognised the need to consider ‘strengthening the long-term global goal on the basis of the best available scientific knowledge…to a global average temperature rise of 1.5°C’. Beginning in 2013 and ending at the COP21 in Paris in 2015, the first review period of the long-term global goal largely consisted of the Structured Expert Dialogue (SED). This was a fact-finding, face-to-face exchange of views between invited experts and UNFCCC delegates. The final report of the SED3 concluded that ‘in some regions and vulnerable ecosystems, high risks are projected even for warming above 1.5°C’. The SED report also suggested that Parties would profit from restating the temperature limit of the long-term global goal as a ‘defence line’ or ‘buffer zone’, instead of a ‘guardrail’ up to which all would be safe, adding that this new understanding would ‘probably also favour emission pathways that will limit warming to a range of temperatures below 2°C’. Specifically on strengthening the temperature limit of 2°C, the SED’s key message was: ‘While science on the 1.5°C warming limit is less robust, efforts should be made to push the defence line as low as possible’. The findings of the SED, in turn, fed into the draft decision adopted at COP21. With the adoption of the Paris Agreement, the UNFCCC invited the IPCC to provide a Special Report in 2018 on ‘the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emissions pathways’. The request was that the report, known as SR1.5, should not only assess what a 1.5°C warmer world would look like but also the different pathways by which global temperature rise could be limited to 1.5°C. In 2016, the IPCC accepted the invitation, adding that the Special Report would also look at these issues in the context of strengthening the global response to the threat of climate change, sustainable development and efforts to eradicate poverty. The combination of rising exposure to climate change and the fact that there is a limited capacity to adapt to its impacts amplifies the risks posed by warming of 1.5°C and 2°C. This is particularly true for developing and island countries in the tropics and other vulnerable countries and areas. The risks posed by global warming of 1.5°C are greater than for present-day conditions but lower than at 2°C. (continued on next page) 2 Paris Agreement FCCC/CP/2015/10/Add.1 https://unfccc.int/documents/9097 3 Structured Expert Dialogue (SED) final report FCCC/SB/2015/INF.1 https://unfccc.int/documents/8707 79 Chapter 1 Framing and Context FAQ 1.1 (continued) 1 FAQ 1.1, Figure 1 | Timeline of notable dates in preparing the IPCC Special Report on Global Warming of 1.5°C (blue) embedded within processes and milestones of the United Nations Framework Convention on Climate Change (UNFCCC; grey), including events that may be relevant for discussion of temperature limits. 80 Framing and Context Chapter 1 Frequently Asked Questions FAQ 1.2 | How Close are we to 1.5°C? Summary: Human-induced warming has already reached about 1°C above pre-industrial levels at the time of writ- ing of this Special Report. By the decade 2006–2015, human activity had warmed the world by 0.87°C (±0.12°C) compared to pre-industrial times (1850–1900). If the current warming rate continues, the world would reach 1 human-induced global warming of 1.5°C around 2040. Under the 2015 Paris Agreement, countries agreed to cut greenhouse gas emissions with a view to ‘holding the increase in the global average temperature to well below 2°C above pre-industrial levels and pursuing efforts to limit the temperature increase to 1.5°C above pre-industrial levels’. While the overall intention of strengthening the global response to climate change is clear, the Paris Agreement does not specify precisely what is meant by ‘global average temperature’, or what period in history should be considered ‘pre-industrial’. To answer the question of how close are we to 1.5°C of warming, we need to first be clear about how both terms are defined in this Special Report. The choice of pre-industrial reference period, along with the method used to calculate global average temperature, can alter scientists’ estimates of historical warming by a couple of tenths of a degree Celsius. Such differences become important in the context of a global temperature limit just half a degree above where we are now. But provided consistent definitions are used, they do not affect our understanding of how human activity is influencing the climate. In principle, ‘pre-industrial levels’ could refer to any period of time before the start of the industrial revolution. But the number of direct temperature measurements decreases as we go back in time. Defining a ‘pre-industrial’ reference period is, therefore, a compromise between the reliability of the temperature information and how representative it is of truly pre-industrial conditions. Some pre-industrial periods are cooler than others for purely natural reasons. This could be because of spontaneous climate variability or the response of the climate to natural perturbations, such as volcanic eruptions and variations in the sun’s activity. This IPCC Special Report on Global Warming of 1.5°C uses the reference period 1850–1900 to represent pre-industrial temperature. This is the earliest period with near-global observations and is the reference period used as an approximation of pre- industrial temperatures in the IPCC Fifth Assessment Report. Once scientists have defined ‘pre-industrial’, the next step is to calculate the amount of warming at any given time relative to that reference period. In this report, warming is defined as the increase in the 30-year global average of combined air temperature over land and water temperature at the ocean surface. The 30-year timespan accounts for the effect of natural variability, which can cause global temperatures to fluctuate from one year to the next. For example, 2015 and 2016 were both affected by a strong El Niño event, which amplified the underlying human-caused warming. In the decade 2006–2015, warming reached 0.87°C (±0.12°C) relative to 1850–1900, predominantly due to human activity increasing the amount of greenhouse gases in the atmosphere. Given that global temperature is currently rising by 0.2°C (±0.1°C) per decade, human-induced warming reached 1°C above pre-industrial levels around 2017 and, if this pace of warming continues, would reach 1.5°C around 2040. While the change in global average temperature tells researchers about how the planet as a whole is changing, looking more closely at specific regions, countries and seasons reveals important details. Since the 1970s, most land regions have been warming faster than the global average, for example. This means that warming in many regions has already exceeded 1.5°C above pre-industrial levels. Over a fifth of the global population live in regions that have already experienced warming in at least one season that is greater than 1.5°C above pre- industrial levels. (continued on next page) 81 Chapter 1 Framing and Context FAQ 1.2 (continued) FAQ1.2:How close are we to 1.5°C? Human-induced warming reached approximately 1°C above pre-industrial levels in 2017 1 2.00 1.75 Current warming rate 1.50 1.25 2017 1.00 Human-induced warming 0.75 Climate uncertainty for 1.5°C pathway 0.50 Observed 0.25 warming 0.00 1960 1980 2000 2020 2040 2060 2080 2100 FAQ 1.2, Figure 1 | Human-induced warming reached approximately 1°C above pre-industrial levels in 2017. At the present rate, global temperatures would reach 1.5°C around 2040. Stylized 1.5°C pathway shown here involves emission reductions beginning immediately, and CO2 emissions reaching zero by 2055. 82 Global temperature change relative to 1850-1900 (°C) Framing and Context Chapter 1 References Aaheim, A., T. Wei, and B. 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Science Advances, 3(6), e1700263, doi:10.1126/sciadv.1700263. 91 Mitigation Pathways Compatible with 1.5°C in the Context 2 of Sustainable Development Coordinating Lead Authors: Joeri Rogelj (Austria/Belgium), Drew Shindell (USA), Kejun Jiang (China) Lead Authors: Solomone Fifita (Fiji), Piers Forster (UK), Veronika Ginzburg (Russia), Collins Handa (Kenya), Haroon Kheshgi (USA), Shigeki Kobayashi (Japan), Elmar Kriegler (Germany), Luis Mundaca (Sweden/Chile), Roland Séférian (France), Maria Virginia Vilariño (Argentina) Contributing Authors: Katherine Calvin (USA), Joana Correia de Oliveira de Portugal Pereira (UK/Portugal), Oreane Edelenbosch (Netherlands/Italy), Johannes Emmerling (Italy/Germany), Sabine Fuss (Germany), Thomas Gasser (Austria/France), Nathan Gillett (Canada), Chenmin He (China), Edgar Hertwich (USA/Austria), Lena Höglund-Isaksson (Austria/Sweden), Daniel Huppmann (Austria), Gunnar Luderer (Germany), Anil Markandya (Spain/UK), David L. McCollum (USA/Austria), Malte Meinshausen (Australia/Germany), Richard Millar (UK), Alexander Popp (Germany), Pallav Purohit (Austria/India), Keywan Riahi (Austria), Aurélien Ribes (France), Harry Saunders (Canada/USA), Christina Schädel (USA/Switzerland), Chris Smith (UK), Pete Smith (UK), Evelina Trutnevyte (Switzerland/Lithuania), Yang Xiu (China), Wenji Zhou (Austria/China), Kirsten Zickfeld (Canada/Germany) Chapter Scientists: Daniel Huppmann (Austria), Chris Smith (UK) Review Editors: Greg Flato (Canada), Jan Fuglestvedt (Norway), Rachid Mrabet (Morocco), Roberto Schaeffer (Brazil) This chapter should be cited as: Rogelj, J., D. Shindell, K. Jiang, S. Fifita, P. Forster, V. Ginzburg, C. Handa, H. Kheshgi, S. Kobayashi, E. Kriegler, L. Mundaca, R. Séférian, and M.V. Vilariño, 2018: Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)]. In Press. 93 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Table of Contents Executive Summary .....................................................................95 2.6 Knowledge Gaps ...........................................................157 2.6.1 Geophysical Understanding........................................157 2.1 Introduction to Mitigation Pathways and the Sustainable Development Context ....................98 2.6.2 Integrated Assessment Approaches ............................158 2.1.1 Mitigation Pathways Consistent with 1.5°C .................98 2.6.3 Carbon Dioxide Removal (CDR) ..................................158 2.1.2 The Use of Scenarios ...................................................98 2.1.3 New Scenario Information since AR5 ...........................99 2.1.4 Utility of Integrated Assessment Models (IAMs) Frequently Asked Questions in the Context of this Report ......................................100 FAQ 2.1: What Kind of Pathways Limit Warming to 1.5°C and are we on Track? ...........................................159 2 2.2 Geophysical Relationships and Constraints .........101 FAQ 2.2: What do Energy Supply and Demand 2.2.1 Geophysical Characteristics of Mitigation Pathways ..101 have to do with Limiting Warming to 1.5°C? .....................161 2.2.2 The Remaining 1.5°C Carbon Budget .........................104 2.3 Overview of 1.5°C Mitigation Pathways ...............108 References ...................................................................................163 2.3.1 Range of Assumptions Underlying 1.5°C Pathways ....109 2.3.2 Key Characteristics of 1.5°C Pathways .......................112 2.3.3 Emissions Evolution in 1.5°C Pathways ......................115 2.3.4 CDR in 1.5°C Pathways ..............................................118 Box 2.1: Bioenergy and BECCS Deployment in Integrated Assessment Modelling ....................................124 2.3.5 Implications of Near-Term Action in 1.5°C Pathways ..126 2.4 Disentangling the Whole-System Transformation ..............................................................129 2.4.1 Energy System Transformation ...................................129 2.4.2 Energy Supply .............................................................130 2.4.3 Energy End-Use Sectors ..............................................136 2.4.4 Land-Use Transitions and Changes in the Agricultural Sector ................................................144 2.5 Challenges, Opportunities and Co-Impacts of Transformative Mitigation Pathways ................148 2.5.1 Policy Frameworks and Enabling Conditions ..............148 Cross-Chapter Box 5 | Economics of 1.5°C Pathways and the Social Cost of Carbon ...............................................150 2.5.2 Economic and Investment Implications of 1.5°C Pathways ....................................................................152 2.5.3 Sustainable Development Features of 1.5°C Pathways ......................................................156 94 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 Executive Summary Limiting warming to 1.5°C depends on greenhouse gas (GHG) emissions over the next decades, where lower GHG emissions in 2030 lead to a higher chance of keeping peak warming to 1.5°C This chapter assesses mitigation pathways consistent with limiting (high confidence). Available pathways that aim for no or limited (less warming to 1.5°C above pre-industrial levels. In doing so, it explores than 0.1°C) overshoot of 1.5°C keep GHG emissions in 2030 to 25–30 the following key questions: What role do CO2 and non-CO2 emissions GtCO2e yr −1 in 2030 (interquartile range). This contrasts with median play? {2.2, 2.3, 2.4, 2.6} To what extent do 1.5°C pathways involve estimates for current unconditional NDCs of 52–58 GtCO2e yr −1 in overshooting and returning below 1.5°C during the 21st century? {2.2, 2030. Pathways that aim for limiting warming to 1.5°C by 2100 after 2.3} What are the implications for transitions in energy, land use and a temporary temperature overshoot rely on large-scale deployment sustainable development? {2.3, 2.4, 2.5} How do policy frameworks of carbon dioxide removal (CDR) measures, which are uncertain and affect the ability to limit warming to 1.5°C? {2.3, 2.5} What are the entail clear risks. In model pathways with no or limited overshoot of associated knowledge gaps? {2.6} 1.5°C, global net anthropogenic CO2 emissions decline by about 45% from 2010 levels by 2030 (40–60% interquartile range), reaching net The assessed pathways describe integrated, quantitative zero around 2050 (2045–2055 interquartile range). For limiting global evolutions of all emissions over the 21st century associated warming to below 2°C with at least 66% probability CO2 emissions 2 with global energy and land use and the world economy. The are projected to decline by about 25% by 2030 in most pathways (10– assessment is contingent upon available integrated assessment 30% interquartile range) and reach net zero around 2070 (2065–2080 literature and model assumptions, and is complemented by other interquartile range).1 {2.2, 2.3.3, 2.3.5, 2.5.3, Cross-Chapter Boxes 6 in studies with different scope, for example, those focusing on individual Chapter 3 and 9 in Chapter 4, 4.3.7} sectors. In recent years, integrated mitigation studies have improved the characterizations of mitigation pathways. However, limitations Limiting warming to 1.5°C implies reaching net zero CO2 remain, as climate damages, avoided impacts, or societal co-benefits emissions globally around 2050 and concurrent deep reductions of the modelled transformations remain largely unaccounted for, while in emissions of non-CO2 forcers, particularly methane (high concurrent rapid technological changes, behavioural aspects, and confidence). Such mitigation pathways are characterized by energy- uncertainties about input data present continuous challenges. (high demand reductions, decarbonization of electricity and other fuels, confidence) {2.1.3, 2.3, 2.5.1, 2.6, Technical Annex 2} electrification of energy end use, deep reductions in agricultural emissions, and some form of CDR with carbon storage on land or The Chances of Limiting Warming to 1.5°C sequestration in geological reservoirs. Low energy demand and low and the Requirements for Urgent Action demand for land- and GHG-intensive consumption goods facilitate limiting warming to as close as possible to 1.5°C. {2.2.2, 2.3.1, 2.3.5, Pathways consistent with 1.5°C of warming above pre-industrial 2.5.1, Cross-Chapter Box 9 in Chapter 4}. levels can be identified under a range of assumptions about economic growth, technology developments and lifestyles. In comparison to a 2°C limit, the transformations required to limit However, lack of global cooperation, lack of governance of the required warming to 1.5°C are qualitatively similar but more pronounced energy and land transformation, and increases in resource-intensive and rapid over the next decades (high confidence). 1.5°C implies consumption are key impediments to achieving 1.5°C pathways. very ambitious, internationally cooperative policy environments that Governance challenges have been related to scenarios with high transform both supply and demand (high confidence). {2.3, 2.4, 2.5} inequality and high population growth in the 1.5°C pathway literature. {2.3.1, 2.3.2, 2.5} Policies reflecting a high price on emissions are necessary in models to achieve cost-effective 1.5°C pathways (high Under emissions in line with current pledges under the Paris confidence). Other things being equal, modelling studies suggest Agreement (known as Nationally Determined Contributions, the global average discounted marginal abatement costs for limiting or NDCs), global warming is expected to surpass 1.5°C above warming to 1.5°C being about 3–4 times higher compared to 2°C pre-industrial levels, even if these pledges are supplemented over the 21st century, with large variations across models and socio- with very challenging increases in the scale and ambition of economic and policy assumptions. Carbon pricing can be imposed mitigation after 2030 (high confidence). This increased action directly or implicitly by regulatory policies. Policy instruments, like would need to achieve net zero CO2 emissions in less than 15 years. technology policies or performance standards, can complement explicit Even if this is achieved, temperatures would only be expected to remain carbon pricing in specific areas. {2.5.1, 2.5.2, 4.4.5} below the 1.5°C threshold if the actual geophysical response ends up being towards the low end of the currently estimated uncertainty range. Limiting warming to 1.5°C requires a marked shift in investment Transition challenges as well as identified trade-offs can be reduced if patterns (medium confidence). Additional annual average energy- global emissions peak before 2030 and marked emissions reductions related investments for the period 2016 to 2050 in pathways limiting compared to today are already achieved by 2030. {2.2, 2.3.5, Cross- warming to 1.5°C compared to pathways without new climate policies Chapter Box 11 in Chapter 4} beyond those in place today (i.e., baseline) are estimated to be around 1 Kyoto-GHG emissions in this statement are aggregated with GWP-100 values of the IPCC Second Assessment Report. 95 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development 830 billion USD2010 (range of 150 billion to 1700 billion USD2010 aerosol) affects carbon budgets and the certainty of pathway across six models). Total energy-related investments increase by about categorizations. Some non-CO2 forcers are emitted alongside CO2, 12% (range of 3% to 24%) in 1.5°C pathways relative to 2°C pathways. particularly in the energy and transport sectors, and can be largely Average annual investment in low-carbon energy technologies and addressed through CO2 mitigation. Others require specific measures, energy efficiency are upscaled by roughly a factor of six (range of factor for example, to target agricultural nitrous oxide (N2O) and methane of 4 to 10) by 2050 compared to 2015, overtaking fossil investments (CH4), some sources of black carbon, or hydrofluorocarbons (high globally by around 2025 (medium confidence). Uncertainties and confidence). In many cases, non-CO2 emissions reductions are similar strategic mitigation portfolio choices affect the magnitude and focus in 2°C pathways, indicating reductions near their assumed maximum of required investments. {2.5.2} potential by integrated assessment models. Emissions of N2O and NH3 increase in some pathways with strongly increased bioenergy Future Emissions in 1.5°C Pathways demand. {2.2.2, 2.3.1, 2.4.2, 2.5.3} Mitigation requirements can be quantified using carbon budget The Role of Carbon Dioxide Removal (CDR) approaches that relate cumulative CO2 emissions to global mean 2 temperature increase. Robust physical understanding underpins All analysed pathways limiting warming to 1.5°C with no this relationship, but uncertainties become increasingly relevant as a or limited overshoot use CDR to some extent to neutralize specific temperature limit is approached. These uncertainties relate to emissions from sources for which no mitigation measures the transient climate response to cumulative carbon emissions (TCRE), have been identified and, in most cases, also to achieve non-CO2 emissions, radiative forcing and response, potential additional net negative emissions to return global warming to 1.5°C Earth system feedbacks (such as permafrost thawing), and historical following a peak (high confidence). The longer the delay in emissions and temperature. {2.2.2, 2.6.1} reducing CO2 emissions towards zero, the larger the likelihood of exceeding 1.5°C, and the heavier the implied reliance on Cumulative CO2 emissions are kept within a budget by reducing net negative emissions after mid-century to return warming to global annual CO2 emissions to net zero. This assessment 1.5°C (high confidence). The faster reduction of net CO2 emissions suggests a remaining budget of about 420 GtCO2 for a two- in 1.5°C compared to 2°C pathways is predominantly achieved by thirds chance of limiting warming to 1.5°C, and of about 580 measures that result in less CO2 being produced and emitted, and GtCO2 for an even chance (medium confidence). The remaining only to a smaller degree through additional CDR. Limitations on carbon budget is defined here as cumulative CO2 emissions from the the speed, scale and societal acceptability of CDR deployment also start of 2018 until the time of net zero global emissions for global limit the conceivable extent of temperature overshoot. Limits to our warming defined as a change in global near-surface air temperatures. understanding of how the carbon cycle responds to net negative Remaining budgets applicable to 2100 would be approximately emissions increase the uncertainty about the effectiveness of CDR to 100 GtCO2 lower than this to account for permafrost thawing and decline temperatures after a peak. {2.2, 2.3, 2.6, 4.3.7} potential methane release from wetlands in the future, and more thereafter. These estimates come with an additional geophysical CDR deployed at scale is unproven, and reliance on such uncertainty of at least ±400 GtCO2, related to non-CO2 response technology is a major risk in the ability to limit warming to and TCRE distribution. Uncertainties in the level of historic warming 1.5°C. CDR is needed less in pathways with particularly strong contribute ±250 GtCO2. In addition, these estimates can vary by emphasis on energy efficiency and low demand. The scale and ±250 GtCO2 depending on non-CO2 mitigation strategies as found in type of CDR deployment varies widely across 1.5°C pathways, available pathways. {2.2.2, 2.6.1} with different consequences for achieving sustainable development objectives (high confidence). Some pathways rely Staying within a remaining carbon budget of 580 GtCO2 implies more on bioenergy with carbon capture and storage (BECCS), while that CO2 emissions reach carbon neutrality in about 30 years, others rely more on afforestation, which are the two CDR methods reduced to 20 years for a 420 GtCO2 remaining carbon budget most often included in integrated pathways. Trade-offs with other (high confidence). The ±400 GtCO2 geophysical uncertainty range sustainability objectives occur predominantly through increased land, surrounding a carbon budget translates into a variation of this timing energy, water and investment demand. Bioenergy use is substantial of carbon neutrality of roughly ±15–20 years. If emissions do not start in 1.5°C pathways with or without BECCS due to its multiple roles in declining in the next decade, the point of carbon neutrality would need decarbonizing energy use. {2.3.1, 2.5.3, 2.6.3, 4.3.7} to be reached at least two decades earlier to remain within the same carbon budget. {2.2.2, 2.3.5} Properties of Energy and Land Transitions in 1.5°C Pathways Non-CO2 emissions contribute to peak warming and thus The share of primary energy from renewables increases while affect the remaining carbon budget. The evolution of coal usage decreases across pathways limiting warming to methane and sulphur dioxide emissions strongly influences 1.5°C with no or limited overshoot (high confidence). By 2050, the chances of limiting warming to 1.5°C. In the near-term, a renewables (including bioenergy, hydro, wind, and solar, with direct- weakening of aerosol cooling would add to future warming, equivalence method) supply a share of 52–67% (interquartile range) but can be tempered by reductions in methane emissions (high of primary energy in 1.5°C pathways with no or limited overshoot; confidence). Uncertainty in radiative forcing estimates (particularly while the share from coal decreases to 1–7% (interquartile range), 96 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 with a large fraction of this coal use combined with carbon capture Links between 1.5°C Pathways and Sustainable Development and storage (CCS). From 2020 to 2050 the primary energy supplied by oil declines in most pathways (−39 to −77% interquartile range). Choices about mitigation portfolios for limiting warming to Natural gas changes by −13% to −62% (interquartile range), but 1.5°C can positively or negatively impact the achievement of some pathways show a marked increase albeit with widespread other societal objectives, such as sustainable development deployment of CCS. The overall deployment of CCS varies widely (high confidence). In particular, demand-side and efficiency across 1.5°C pathways with no or limited overshoot, with cumulative measures, and lifestyle choices that limit energy, resource, and CO2 stored through 2050 ranging from zero up to 300 GtCO2 GHG-intensive food demand support sustainable development (minimum–maximum range), of which zero up to 140 GtCO2 is stored (medium confidence). Limiting warming to 1.5°C can be achieved from biomass. Primary energy supplied by bioenergy ranges from synergistically with poverty alleviation and improved energy security 40–310 EJ yr−1 in 2050 (minimum-maximum range), and nuclear from and can provide large public health benefits through improved air 3–66 EJ yr−1 (minimum–maximum range). These ranges reflect both quality, preventing millions of premature deaths. However, specific uncertainties in technological development and strategic mitigation mitigation measures, such as bioenergy, may result in trade-offs that portfolio choices. {2.4.2} require consideration. {2.5.1, 2.5.2, 2.5.3} 2 1.5°C pathways with no or limited overshoot include a rapid decline in the carbon intensity of electricity and an increase in electrification of energy end use (high confidence). By 2050, the carbon intensity of electricity decreases to −92 to +11 gCO2 MJ −1 (minimum–maximum range) from about 140 gCO MJ−12 in 2020, and electricity covers 34–71% (minimum–maximum range) of final energy across 1.5°C pathways with no or limited overshoot from about 20% in 2020. By 2050, the share of electricity supplied by renewables increases to 59–97% (minimum-maximum range) across 1.5°C pathways with no or limited overshoot. Pathways with higher chances of holding warming to below 1.5°C generally show a faster decline in the carbon intensity of electricity by 2030 than pathways that temporarily overshoot 1.5°C. {2.4.1, 2.4.2, 2.4.3} Transitions in global and regional land use are found in all pathways limiting global warming to 1.5°C with no or limited overshoot, but their scale depends on the pursued mitigation portfolio (high confidence). Pathways that limit global warming to 1.5°C with no or limited overshoot project a 4 million km2 reduction to a 2.5 million km2 increase of non-pasture agricultural land for food and feed crops and a 0.5–11 million km2 reduction of pasture land, to be converted into 0-6 million km2 of agricultural land for energy crops and a 2 million km2 reduction to 9.5 million km2 increase in forests by 2050 relative to 2010 (medium confidence). Land-use transitions of similar magnitude can be observed in modelled 2°C pathways (medium confidence). Such large transitions pose profound challenges for sustainable management of the various demands on land for human settlements, food, livestock feed, fibre, bioenergy, carbon storage, biodiversity and other ecosystem services (high confidence). {2.3.4, 2.4.4} Demand-Side Mitigation and Behavioural Changes Demand-side measures are key elements of 1.5°C pathways. Lifestyle choices lowering energy demand and the land- and GHG-intensity of food consumption can further support achievement of 1.5°C pathways (high confidence). By 2030 and 2050, all end-use sectors (including building, transport, and industry) show marked energy demand reductions in modelled 1.5°C pathways, comparable and beyond those projected in 2°C pathways. Sectoral models support the scale of these reductions. {2.3.4, 2.4.3, 2.5.1} 97 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development 2.1 Introduction to Mitigation Pathways and scenarios (Section 2.3.1). These societal choices must then be linked the Sustainable Development Context to the drivers of climate change, including emissions of well-mixed greenhouse gases and aerosol and ozone precursors as well as land- use and land-cover changes. Deliberate solar radiation modification is This chapter assesses the literature on mitigation pathways to limit or not included in these scenarios (see Cross-Chapter Box 10 in Chapter 4). return global mean warming to 1.5°C (relative to the pre-industrial base period 1850–1900). Key questions addressed are: What types of Plausible developments need to be anticipated in many facets of the mitigation pathways have been developed that could be consistent key sectors of energy and land use. Within energy, these scenarios with 1.5°C? What changes in emissions, energy and land use do they consider energy resources like biofuels, energy supply and conversion entail? What do they imply for climate policy and implementation, and technologies, energy consumption, and supply and end-use efficiency. what impacts do they have on sustainable development? In terms of Within land use, agricultural productivity, food demand, terrestrial feasibility (see Cross-Chapter Box 3 in Chapter 1), this chapter focuses carbon management, and biofuel production are all considered. on geophysical dimensions and technological and economic enabling Climate policies are also considered, including carbon pricing and factors. Social and institutional dimensions as well as additional technology policies such as research and development funding and 2 aspects of technical feasibility are covered in Chapter 4. subsidies. The scenarios incorporate regional differentiation in sectoral and policy development. The climate changes resulting from such Mitigation pathways are typically designed to reach a predefined scenarios are derived using models that typically incorporate physical climate target alone. Minimization of mitigation expenditures, but understanding of the carbon cycle and climate response derived from not climate-related damages or sustainable development impacts, complex geophysical models evaluated against observations (Sections is often the basis for these pathways to the desired climate target 2.2 and 2.6). (see Cross-Chapter Box 5 in this chapter for additional discussion). However, there are interactions between mitigation and multiple other The temperature response to a given emission pathway (see glossary) is sustainable development goals (see Sections 1.1 and 5.4) that provide uncertain and therefore quantified in terms of a probabilistic outcome. both challenges and opportunities for climate action. Hence there are Chapter 1 assesses the climate objectives of the Paris Agreement in substantial efforts to evaluate the effects of the various mitigation terms of human-induced warming, thus excluding potential impacts pathways on sustainable development, focusing in particular on of natural forcing such as volcanic eruptions or solar output changes aspects for which integrated assessment models (IAMs) provide or unforced internal variability. Temperature responses in this chapter relevant information (e.g., land-use changes and biodiversity, food are assessed using simple geophysically based models that evaluate security, and air quality). More broadly, there are efforts to incorporate the anthropogenic component of future temperature change and do climate change mitigation as one of multiple objectives that, in general, not incorporate internal natural variations and are thus fit for purpose reflect societal concerns more completely and could potentially provide in the context of this assessment (Section 2.2.1). Hence a scenario benefits at lower costs than simultaneous single-objective policies that is consistent with 1.5°C may in fact lead to either a higher or (e.g., Clarke et al., 2014). For example, with carefully selected policies, lower temperature change, but within quantified and generally well- universal energy access can be achieved while simultaneously reducing understood bounds (see also Chapter 1, Section 1.2.3). Consistency air pollution and mitigating climate change (McCollum et al., 2011; with avoiding a human-induced temperature change limit must Riahi et al., 2012; IEA, 2017d). This chapter thus presents both the therefore also be defined probabilistically, with likelihood values pathways and an initial discussion of their context within sustainable selected based on risk-avoidance preferences. Responses beyond development objectives (Section 2.5), with the latter, along with equity global mean temperature are not typically evaluated in such models and ethical issues, discussed in more detail in Chapter 5. and are assessed in Chapter 3. As described in Cross-Chapter Box 1 in Chapter 1, scenarios are 2.1.2 The Use of Scenarios comprehensive, plausible, integrated descriptions of possible futures based on specified, internally consistent underlying assumptions, Variations in scenario assumptions and design define to a large with pathways often used to describe the clear temporal evolution of degree which questions can be addressed with a specific scenario specific scenario aspects or goal-oriented scenarios. We include both set, for example, the exploration of implications of delayed climate these usages of ‘pathways’ here. mitigation action. In this assessment, the following classes of 1.5°C- and 2°C-consistent scenarios are of particular interest to the topics 2.1.1 Mitigation Pathways Consistent with 1.5°C addressed in this chapter: (i) scenarios with the same climate target over the 21st century but varying socio-economic assumptions Emissions scenarios need to cover all sectors and regions over the (Sections 2.3 and 2.4), (ii) pairs of scenarios with similar socio- 21st century to be associated with a climate change projection out to economic assumptions but with forcing targets aimed at 1.5°C and 2°C 2100. Assumptions regarding future trends in population, consumption (Section 2.3), and (iii) scenarios that follow the Nationally Determined of goods and services (including food), economic growth, behaviour, Contributions or NDCs2 until 2030 with much more stringent mitigation technology, policies and institutions are all required to generate action thereafter (Section 2.3.5). 2 Current pledges include those from the United States although they have stated their intention to withdraw in the future. 98 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 Characteristics of these pathways, such as emissions reduction rates, (see Supplementary Material 2.SM.1.3), examining sensitivity to time of peaking, and low-carbon energy deployment rates, can be assumptions regarding: assessed as being consistent with 1.5°C. However, they cannot be • socio-economic drivers and developments including energy and assessed as ‘requirements’ for 1.5°C, unless a targeted analysis food demand as, for example, characterized by the Shared Socio- is available that specifically asked whether there could be other Economic Pathways (SSPs; Cross-Chapter Box 1 in Chapter 1) 1.5°C-consistent pathways without the characteristics in question. AR5 • near-term climate policies describing different levels of strengthening already assessed such targeted analyses, for example, asking which the NDCs technologies are important in order to keep open the possibility of • the use of bioenergy and the availability and desirability of carbon limiting warming to 2°C (Clarke et al., 2014). By now, several such dioxide removal (CDR) technologies targeted analyses are also available for questions related to 1.5°C (Luderer et al., 2013; Rogelj et al., 2013b; Bauer et al., 2018; Strefler A large number of these scenarios were collected in a scenario database et al., 2018b; van Vuuren et al., 2018). This assessment distinguishes established for the assessment of this Special Report (Supplementary between ‘consistent’ and the much stronger concept of required Material 2.SM.1.3). Mitigation pathways were classified by four characteristics of 1.5°C pathways wherever possible. factors: consistency with a temperature increase limit (as defined by Chapter 1), whether they temporarily overshoot that limit, the extent 2 Ultimately, society will adjust the choices it makes as new information of this potential overshoot, and the likelihood of falling within these becomes available and technical learning progresses, and these bounds. adjustments can be in either direction. Earlier scenario studies have shown, however, that deeper emissions reductions in the near term Specifically, they were put into classes that either kept surface hedge against the uncertainty of both climate response and future temperature increases below a given threshold throughout the 21st technology availability (Luderer et al., 2013; Rogelj et al., 2013b; Clarke century or returned to a value below 1.5°C above pre-industrial levels et al., 2014). Not knowing what adaptations might be put in place in at some point before 2100 after temporarily exceeding that level earlier the future, and due to limited studies, this chapter examines prospective – referred to as an overshoot (OS). Both groups were further separated rather than iteratively adaptive mitigation pathways (Cross-Chapter based on the probability of being below the threshold and the degree Box 1 in Chapter 1). Societal choices illustrated by scenarios may also of overshoot, respectively (Table 2.1). Pathways are uniquely classified, influence what futures are envisioned as possible or desirable and with 1.5°C-related classes given higher priority than 2°C classes in hence whether those come into being (Beck and Mahony, 2017). cases where a pathway would be applicable to either class. 2.1.3 New Scenario Information since AR5 The probability assessment used in the scenario classification is based on simulations using two reduced-complexity carbon cycle, atmospheric In this chapter, we extend the AR5 mitigation pathway assessment composition, and climate models: the ‘Model for the Assessment of based on new scenario literature. Updates in understanding of Greenhouse Gas-Induced Climate Change’ (MAGICC) (Meinshausen climate sensitivity, transient climate response, radiative forcing, and et al., 2011a), and the ‘Finite Amplitude Impulse Response’ (FAIRv1.3) the cumulative carbon budget consistent with 1.5°C are discussed in model (Smith et al., 2018). For the purpose of this report, and to facilitate Sections 2.2. comparison with AR5, the range of the key carbon cycle and climate parameters for MAGICC and its setup are identical to those used in Mitigation pathways developed with detailed process-based AR5 WGIII (Clarke et al., 2014). For each mitigation pathway, MAGICC integrated assessment models (IAMs) covering all sectors and regions and FAIR simulations provide probabilistic estimates of atmospheric over the 21st century describe an internally consistent and calibrated concentrations, radiative forcing and global temperature outcomes until (to historical trends) way to get from current developments to 2100. However, the classification uses MAGICC probabilities directly for meeting long-term climate targets like 1.5°C (Clarke et al., 2014). The traceability with AR5 and because this model is more established in the overwhelming majority of available 1.5°C pathways were generated literature. Nevertheless, the overall uncertainty assessment is based on by such IAMs, and these pathways can be directly linked to climate results from both models, which are considered in the context of the outcomes and their consistency with the 1.5°C goal evaluated. The latest radiative forcing estimates and observed temperatures (Etminan AR5 similarly relied upon such studies, which were mainly discussed in et al., 2016; Smith et al., 2018) (Section 2.2 and Supplementary Material Chapter 6 of Working Group III (WGIII) (Clarke et al., 2014). 2.SM.1.1). The comparison of these lines of evidence shows high agreement in the relative temperature response of pathways, with Since the AR5, several new, integrated multimodel studies have medium agreement on the precise absolute magnitude of warming, appeared in the literature that explore specific characteristics of introducing a level of imprecision in these attributes. Consideration of scenarios more stringent than the lowest scenario category assessed the combined evidence here leads to medium confidence in the overall in AR5 that was assessed to limit warming below 2°C with greater geophysical characteristics of the pathways reported here. than 66% likelihood (Rogelj et al., 2015b, 2018; Akimoto et al., 2017; Marcucci et al., 2017; Su et al., 2017; Bauer et al., 2018; Bertram et In addition to the characteristics of the above-mentioned classes, al., 2018; Grubler et al., 2018; Holz et al., 2018b; Kriegler et al., 2018a; four illustrative pathway archetypes have been selected and are used Liu et al., 2018; Luderer et al., 2018; Strefler et al., 2018a; van Vuuren throughout this chapter to highlight specific features of and variations et al., 2018; Vrontisi et al., 2018; Zhang et al., 2018). Those scenarios across 1.5°C pathways. These are chosen in particular to illustrate the explore 1.5°C-consistent pathways from multiple perspectives spectrum of CO2 emissions reduction patterns consistent with 1.5°C, 99 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Table 2.1 | Classification of pathways that this chapter draws upon, along with the number of available pathways in each class. The definition of each class is based on probabilities derived from the MAGICC model in a setup identical to AR5 WGIII (Clarke et al., 2014), as detailed in Supplementary Material 2.SM.1.4. Pathway group Pathway Class Pathway Selection Criteria and Description Number of Number of Scenarios Scenarios Pathways limiting peak warming to below 1.5°C during the entire 21st century Below-1.5°C 9 with 50–66% likelihood* Pathways limiting median warming to below 1.5°C in 2100 and with a 1.5°C or 1.5°C-low-OS 50–67% probability of temporarily overshooting that level earlier, generally 44 90 1.5°C-consistent** implying less than 0.1°C higher peak warming than Below-1.5°C pathways Pathways limiting median warming to below 1.5°C in 2100 and with a greater 1.5°C-high-OS than 67% probability of temporarily overshooting that level earlier, generally 37 implying 0.1–0.4°C higher peak warming than Below-1.5°C pathways Pathways limiting peak warming to below 2°C during the entire 21st century Lower-2°C 74 2°C or with greater than 66% likelihood 132 2 2°C-consistent Pathways assessed to keep peak warming to below 2°C during the entire Higher-2°C 58 21st century with 50–66% likelihood * No pathways were available that achieve a greater than 66% probability of limiting warming below 1.5°C during the entire 21st century based on the MAGICC model projections. ** This chapter uses the term 1.5°C-consistent pathways to refer to pathways with no overshoot, with limited (low) overshoot, and with high overshoot. However, the Summary for Policymakers focusses on pathways with no or limited (low) overshoot. ranging from very rapid and deep near-term decreases, facilitated a specific country or region (Giannakidis et al., 2018). Sector-specific by efficiency and demand-side measures that lead to limited CDR pathways are assessed in relation to integrated pathways because they requirements, to relatively slower but still rapid emissions reductions cannot be directly linked to 1.5°C by themselves if they do not extend that lead to a temperature overshoot and necessitate large CDR to 2100 or do not include all GHGs or aerosols from all sectors. deployment later in the century (Section 2.3). AR5 found sectoral 2°C decarbonization strategies from IAMs to be 2.1.4 Utility of Integrated Assessment Models consistent with sector-specific studies (Clarke et al., 2014). A growing (IAMs) in the Context of this Report body of literature on 100%-renewable energy scenarios has emerged (e.g., see Creutzig et al., 2017; Jacobson et al., 2017), which goes IAMs lie at the basis of the assessment of mitigation pathways in this beyond the wide range of IAM projections of renewable energy shares chapter, as much of the quantitative global scenario literature is derived in 1.5°C and 2°C pathways. While the representation of renewable with such models. IAMs combine insights from various disciplines in a energy resource potentials, technology costs and system integration in single framework, resulting in a dynamic description of the coupled IAMs has been updated since AR5, leading to higher renewable energy energy–economy–land-climate system that cover the largest sources deployments in many cases (Luderer et al., 2017; Pietzcker et al., 2017), of anthropogenic greenhouse gas (GHG) emissions from different none of the IAM projections identify 100% renewable energy solutions sectors. Many of the IAMs that contributed mitigation scenarios to this for the global energy system as part of cost-effective mitigation assessment include a process-based description of the land system in pathways (Section 2.4.2). Bottom-up studies find higher mitigation addition to the energy system (e.g., Popp et al., 2017), and several have potentials in the industry, buildings, and transport sectors in 2030 than been extended to cover air pollutants (Rao et al., 2017) and water use realized in selected 2°C pathways from IAMs (UNEP 2017), indicating (Hejazi et al., 2014; Fricko et al., 2016; Mouratiadou et al., 2016). Such the possibility to strengthen sectoral decarbonization strategies until integrated pathways hence allow the exploration of the whole-system 2030 beyond the integrated 1.5°C pathways assessed in this chapter transformation, as well as the interactions, synergies, and trade- (Luderer et al., 2018). offs between sectors, and, increasingly, questions beyond climate mitigation (von Stechow et al., 2015). The models do not, however, fully Detailed, process-based IAMs are a diverse set of models ranging account for all constraints that could affect realization of pathways from partial equilibrium energy–land models to computable general (see Chapter 4). equilibrium models of the global economy, from myopic to perfect foresight models, and from models with to models without endogenous Section 2.3 assesses the overall characteristics of 1.5°C pathways technological change (Supplementary Material 2.SM.1.2). The IAMs based on fully integrated pathways, while Sections 2.4 and 2.5 describe used in this chapter have limited to no coverage of climate impacts. underlying sectoral transformations, including insights from sector- They typically use GHG pricing mechanisms to induce emissions specific assessment models and pathways that are not derived from reductions and associated changes in energy and land uses consistent IAMs. Such models provide detail in their domain of application and with the imposed climate goal. The scenarios generated by these make exogenous assumptions about cross-sectoral or global factors. models are defined by the choice of climate goals and assumptions They often focus on a specific sector, such as the energy (Bruckner et about near-term climate policy developments. They are also shaped al., 2014; IEA, 2017a; Jacobson, 2017; OECD/IEA and IRENA, 2017), by assumptions about mitigation potentials and technologies as well buildings (Lucon et al., 2014) or transport (Sims et al., 2014) sector, or as baseline developments such as, for example, those represented by 100 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 different Shared Socio-Economic Pathways (SSPs), especially those 1.5°C-consistent pathways available in the database overshoot 1.5°C pertaining to energy and food demand (Riahi et al., 2017). See Section around mid-century before peaking and then reducing temperatures 2.3.1 for discussion of these assumptions. Since the AR5, the scenario so as to return below that level in 2100. However, because of literature has greatly expanded the exploration of these dimensions. numerous geophysical uncertainties and model dependencies (Section This includes low-demand scenarios (Grubler et al., 2018; van Vuuren 2.2.1.1, Supplementary Material 2.SM.1.1), absolute temperature et al., 2018), scenarios taking into account a larger set of sustainable characteristics of the various pathway categories are more difficult to development goals (Bertram et al., 2018), scenarios with restricted distinguish than relative features (Figure 2.1, Supplementary Material availability of CDR technologies (Bauer et al., 2018; Grubler et al., 2018; 2.SM.1.1), and actual probabilities of overshoot are imprecise. However, Holz et al., 2018b; Kriegler et al., 2018a; Strefler et al., 2018b; van Vuuren all lines of evidence available for temperature projections indicate a et al., 2018), scenarios with near-term action dominated by regulatory probability greater than 50% of overshooting 1.5°C by mid-century in policies (Kriegler et al., 2018a) and scenario variations across the all but the most stringent pathways currently available (Supplementary SSPs (Riahi et al., 2017; Rogelj et al., 2018). IAM results depend upon Material 2.SM.1.1, 2.SM.1.4). multiple underlying assumptions, for example, the extent to which global markets and economies are assumed to operate frictionless Most 1.5°C-consistent pathways exhibit a peak in temperature by mid- and policies are cost-optimized, assumptions about technological century whereas 2°C-consistent pathways generally peak after 2050 2 progress and availability and costs of mitigation and CDR measures, (Supplementary Material 2.SM.1.4). The peak in median temperature assumptions about underlying socio-economic developments and in the various pathway categories occurs about ten years before future energy, food and materials demand, and assumptions about reaching net zero CO2 emissions due to strongly reduced annual the geographic and temporal pattern of future regulatory and carbon CO2 emissions and deep reductions in CH4 emissions (Section 2.3.3). pricing policies (see Supplementary Material 2.SM.1.2 for additional The two reduced-complexity climate models used in this assessment discussion on IAMs and their limitations). suggest that virtually all available 1.5°C-consistent pathways peak and then decline global mean temperature, but with varying rates of temperature decline after the peak (Figure 2.1). The estimated decadal rates of temperature change by the end of the century are 2.2 Geophysical Relationships and Constraints smaller than the amplitude of the climate variability as assessed in AR5 (1 standard deviation of about ±0.1°C), which hence complicates the Emissions pathways can be characterized by various geophysical detection of a global peak and decline of warming in observations on characteristics, such as radiative forcing (Masui et al., 2011; Riahi et time scales of one to two decades (Bindoff et al., 2013). In comparison, al., 2011; Thomson et al., 2011; van Vuuren et al., 2011b), atmospheric many pathways limiting warming to 2°C or higher by 2100 still have concentrations (van Vuuren et al., 2007, 2011a; Clarke et al., 2014) or noticeable increasing trends at the end of the century, and thus imply associated temperature outcomes (Meinshausen et al., 2009; Rogelj continued warming. et al., 2011; Luderer et al., 2013). These attributes can be used to derive geophysical relationships for specific pathway classes, such as By 2100, the difference between 1.5°C- and 2°C-consistent pathways cumulative CO2 emissions compatible with a specific level of warming, becomes clearer compared to mid-century, not only for the temperature also known as ‘carbon budgets’ (Meinshausen et al., 2009; Rogelj et al., response (Figure 2.1) but also for atmospheric CO2 concentrations. In 2011; Stocker et al., 2013; Friedlingstein et al., 2014a), the consistent 2100, the median CO2 concentration in 1.5°C-consistent pathways is contributions of non-CO2 GHGs and aerosols to the remaining carbon below 2016 levels (Le Quéré et al., 2018), whereas it remains higher budget (Bowerman et al., 2011; Rogelj et al., 2015a, 2016b), or to by about 5–10% compared to 2016 in the 2°C-consistent pathways. temperature outcomes (Lamarque et al., 2011; Bowerman et al., 2013; Rogelj et al., 2014b). This section assesses geophysical relationships for 2.2.1.1 Geophysical uncertainties: non-CO2 forcing agents both CO2 and non-CO2 emissions (see glossary). Impacts of non-CO2 climate forcers on temperature outcomes are 2.2.1 Geophysical Characteristics of Mitigation Pathways particularly important when evaluating stringent mitigation pathways (Weyant et al., 2006; Shindell et al., 2012; Rogelj et al., 2014b, 2015a; This section employs the pathway classification introduced in Section Samset et al., 2018). However, many uncertainties affect the role of 2.1, with geophysical characteristics derived from simulations with non-CO2 climate forcers in stringent mitigation pathways. the MAGICC reduced-complexity carbon cycle and climate model and supported by simulations with the FAIR reduced-complexity model A first uncertainty arises from the magnitude of the radiative forcing (Section 2.1). Within a specific category and between models, there attributed to non-CO2 climate forcers. Figure 2.2 illustrates how, for remains a large degree of variance. Most pathways exhibit a temperature one representative 1.5°C-consistent pathway (SSP2-1.9) (Fricko et al., overshoot which has been highlighted in several studies focusing on 2017; Rogelj et al., 2018), the effective radiative forcings as estimated stringent mitigation pathways (Huntingford and Lowe, 2007; Wigley by MAGICC and FAIR can differ (see Supplementary Material 2.SM1.1 et al., 2007; Nohara et al., 2015; Rogelj et al., 2015d; Zickfeld and for further details). This large spread in non-CO2 effective radiative Herrington, 2015; Schleussner et al., 2016; Xu and Ramanathan, forcings leads to considerable uncertainty in the predicted temperature 2017). Only very few of the scenarios collected in the database for response. This uncertainty ultimately affects the assessed temperature this report hold the average future warming projected by MAGICC outcomes for pathway classes used in this chapter (Section 2.1) and below 1.5°C during the entire 21st century (Table 2.1, Figure 2.1). Most also affects the carbon budget (Section 2.2.2). Figure 2.2 highlights 101 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development 2 Figure 2.1 | Pathways classification overview. (a) Average global mean temperature increase relative to 2010 as projected by FAIR and MAGICC in 2030, 2050 and 2100; (b) response of peak warming to cumulative CO2 emissions until net zero by MAGICC (red) and FAIR (blue); (c) decadal rate of average global mean temperature change from 2081 to 2100 as a function of the annual CO2 emissions averaged over the same period as given by FAIR (transparent squares) and MAGICC (filled circles). In panel (a), horizontal lines at 0.63°C and 1.13°C are indicative of the 1.5°C and 2°C warming thresholds with the respect to 1850–1900, taking into account the assessed historical warming of 0.87°C ±0.12°C between the 1850–1900 and 2006–2015 periods (Chapter 1, Section 1.2.1). In panel (a), vertical lines illustrate both the physical and the scenario uncertainty as captured by MAGICC and FAIR and show the minimal warming of the 5th percentile of projected warming and the maximal warming of the 95th percentile of projected warming per scenario class. Boxes show the interquartile range of mean warming across scenarios, and thus represent scenario uncertainty only. the important role of methane emissions reduction in this scenario, in interactions, leading to warming (Myhre et al., 2013; Samset et al., agreement with the recent literature focussing on stringent mitigation 2018). A multimodel analysis (Myhre et al., 2017) and a study based pathways (Shindell et al., 2012; Rogelj et al., 2014b, 2015a; Stohl et al., on observational constraints (Malavelle et al., 2017) largely support 2015; Collins et al., 2018). the AR5 best estimate and uncertainty range of aerosol forcing. The partitioning of total aerosol radiative forcing between aerosol For mitigation pathways that aim at halting and reversing radiative precursor emissions is important (Ghan et al., 2013; Jones et al., forcing increase during this century, the aerosol radiative forcing is a 2018; Smith et al., 2018) as this affects the estimate of the mitigation considerable source of uncertainty (Figure 2.2) (Samset et al., 2018; potential from different sectors that have aerosol precursor emission Smith et al., 2018). Indeed, reductions in SO2 (and NOx) emissions sources. The total aerosol effective radiative forcing change in stringent largely associated with fossil-fuel burning are expected to reduce the mitigation pathways is expected to be dominated by the effects from cooling effects of both aerosol radiative interactions and aerosol cloud the phase-out of SO2, although the magnitude of this aerosol-warming 102 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 effect depends on how much of the present-day aerosol cooling is attributable to SO2, particularly the cooling associated with aerosol– cloud interaction (Figure 2.2). Regional differences in the linearity of aerosol–cloud interactions (Carslaw et al., 2013; Kretzschmar et al., 2017) make it difficult to separate the role of individual precursors. Precursors that are not fully mitigated will continue to affect the Earth system. If, for example, the role of nitrate aerosol cooling is at the strongest end of the assessed IPCC AR5 uncertainty range, future temperature increases may be more modest if ammonia emissions continue to rise (Hauglustaine et al., 2014). Figure 2.2 shows that there are substantial differences in the evolution of estimated effective radiative forcing of non-CO2 forcers between MAGICC and FAIR. These forcing differences result in MAGICC simulating a larger warming trend in the near term compared to both 2 the FAIR model and the recent observed trends of 0.2°C per decade reported in Chapter 1 (Figure 2.1, Supplementary Material 2.SM.1.1, Chapter 1, Section 1.2.1.3). The aerosol effective forcing is stronger in MAGICC compared to either FAIR or the AR5 best estimate, though it is still well within the AR5 uncertainty range (Supplementary Material 2.SM.1.1.1). A recent revision (Etminan et al., 2016) increases the Figure 2.2 | Changes and uncertainties in effective radiative forcings (ERF) methane forcing by 25%. This revision is used in the FAIR but not in the for one 1.5°C-consistent pathway (SSP2-19) as estimated by MAGICC AR5 setup of MAGICC that is applied here. Other structural differences and FAIR. The lines are indicative of the total effective radiative forcing from all exist in how the two models relate emissions to concentrations that anthropogenic sources (solid lines) and for non-CO2 agents only (dashed lines), as contribute to differences in forcing (see Supplementary Material represented by MAGICC (red) and FAIR (blue) relative to 2010, respectively. Vertical bars show the mean radiative forcing as predicted by MAGICC and FAIR of relevant 2.SM.1.1.1). non-CO2 agents for year 2030, 2050 and 2100. The vertical lines give the uncertainty (1 standard deviation) of the ERFs for the represented species. Non-CO2 climate forcers exhibit a greater geographical variation in radiative forcings than CO2, which leads to important uncertainties in the temperature response (Myhre et al., 2013). This uncertainty increases the relative uncertainty of the temperature pathways associated with et al., 2017) suggest that the lower bound of ECS could be revised low emission scenarios compared to high emission scenarios (Clarke upwards, which would decrease the chances of limiting warming et al., 2014). It is also important to note that geographical patterns below 1.5°C in assessed pathways. However, such a reassessment has of temperature change and other climate responses, especially those been challenged (Lewis and Curry, 2018), albeit from a single line of related to precipitation, depend significantly on the forcing mechanism evidence. Nevertheless, it is premature to make a major revision to the (Myhre et al., 2013; Shindell et al., 2015; Marvel et al., 2016; Samset et lower bound. The evidence for a possible revision of the upper bound al., 2016) (see also Chapter 3, Section 3.6.2.2). on ECS is less clear, with cases argued from different lines of evidence for both decreasing (Lewis and Curry, 2015, 2018; Cox et al., 2018) 2.2.1.2 Geophysical uncertainties: climate and Earth system and increasing (Brown and Caldeira, 2017) the bound presented in the feedbacks literature. The tools used in this chapter employ ECS ranges consistent with the AR5 assessment. The MAGICC ECS distribution has not been Climate sensitivity uncertainty impacts future projections as well as selected to explicitly reflect this but is nevertheless consistent (Rogelj carbon-budget estimates (Schneider et al., 2017). AR5 assessed the et al., 2014a). The FAIR model used here to estimate carbon budgets equilibrium climate sensitivity (ECS) to be likely in the 1.5°–4.5°C explicitly constructs log-normal distributions of ECS and transient range, extremely unlikely less than 1°C and very unlikely greater climate response based on a multi-parameter fit to the AR5 assessed than 6°C. The lower bound of this estimate is lower than the range ranges of climate sensitivity and individual historic effective radiative of CMIP5 models (Collins et al., 2013). The evidence for the 1.5°C forcings (Smith et al., 2018) (Supplementary Material 2.SM.1.1.1). lower bound on ECS in AR5 was based on analysis of energy-budget changes over the historical period. Work since AR5 has suggested Several feedbacks of the Earth system, involving the carbon cycle, non- that the climate sensitivity inferred from such changes has been CO2 GHGs and/or aerosols, may also impact the future dynamics of the lower than the 2 × CO2 climate sensitivity for known reasons (Forster, coupled carbon–climate system’s response to anthropogenic emissions. 2016; Gregory and Andrews, 2016; Rugenstein et al., 2016; Armour, These feedbacks are caused by the effects of nutrient limitation (Duce et 2017; Ceppi and Gregory, 2017; Knutti et al., 2017; Proistosescu and al., 2008; Mahowald et al., 2017), ozone exposure (de Vries et al., 2017), Huybers, 2017). Both a revised interpretation of historical estimates fire emissions (Narayan et al., 2007) and changes associated with and other lines of evidence based on analysis of climate models with natural aerosols (Cadule et al., 2009; Scott et al., 2018). Among these the best representation of today’s climate (Sherwood et al., 2014; Earth system feedbacks, the importance of the permafrost feedback’s Zhai et al., 2015; Tan et al., 2016; Brown and Caldeira, 2017; Knutti influence has been highlighted in recent studies. Combined evidence 103 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development from both models (MacDougall et al., 2015; Burke et al., 2017; Lowe Matthews et al., 2009; Zickfeld et al., 2009; IPCC, 2013a). However, and Bernie, 2018) and field studies (like Schädel et al., 2014; Schuur et because the projected changes in non-CO2 climate forcers tend to al., 2015) shows high agreement that permafrost thawing will release amplify future warming, CO2-only carbon budgets overestimate the both CO2 and CH4 as the Earth warms, amplifying global warming. This total net cumulative carbon emissions compatible with 1.5°C or 2°C thawing could also release N2O (Voigt et al., 2017a, b). Field, laboratory (Friedlingstein et al., 2014a; Rogelj et al., 2016b; Matthews et al., 2017; and modelling studies estimate that the vulnerable fraction in Mengis et al., 2018; Tokarska et al., 2018). permafrost is about 5–15% of the permafrost soil carbon (~5300–5600 GtCO2 in Schuur et al., 2015) and that carbon emissions are expected to Since the AR5, many estimates of the remaining carbon budget for occur beyond 2100 because of system inertia and the large proportion 1.5°C have been published (Friedlingstein et al., 2014a; MacDougall of slowly decomposing carbon in permafrost (Schädel et al., 2014). et al., 2015; Peters, 2016; Rogelj et al., 2016b, 2018; Matthews et al., Published model studies suggest that a large part of the carbon release 2017; Millar et al., 2017; Goodwin et al., 2018b; Kriegler et al., 2018b; to the atmosphere is in the form of CO2 (Schädel et al., 2016), while the Lowe and Bernie, 2018; Mengis et al., 2018; Millar and Friedlingstein, amount of CH4 released by permafrost thawing is estimated to be much 2018; Schurer et al., 2018; Séférian et al., 2018; Tokarska and Gillett, smaller than that CO2. Cumulative CH4 release by 2100 under RCP2.6 2018; Tokarska et al., 2018). These estimates cover a wide range as a 2 ranges from 0.13 to 0.45 Gt of methane (Burke et al., 2012; Schneider result of differences in the models used, and of methodological choices, von Deimling et al., 2012, 2015), with fluxes being the highest in the as well as physical uncertainties. Some estimates are exclusively model- middle of the century because of maximum thermokarst lake extent by based while others are based on observations or on a combination of mid-century (Schneider von Deimling et al., 2015). both. Remaining carbon budgets limiting warming below 1.5°C or 2°C that are derived from Earth system models of intermediate complexity The reduced complexity climate models employed in this assessment (MacDougall et al., 2015; Goodwin et al., 2018a), IAMs (Luderer et al., do not take into account permafrost or non-CO2 Earth system 2018; Rogelj et al., 2018), or are based on Earth-system model results feedbacks, although the MAGICC model has a permafrost module that (Lowe and Bernie, 2018; Séférian et al., 2018; Tokarska and Gillett, can be enabled. Taking the current climate and Earth system feedbacks 2018) give remaining carbon budgets of the same order of magnitude understanding together, there is a possibility that these models as the IPCC AR5 Synthesis Report (SYR) estimates (IPCC, 2014a). would underestimate the longer-term future temperature response to This is unsurprising as similar sets of models were used for the AR5 stringent emission pathways (Section 2.2.2). (IPCC, 2013b). The range of variation across models stems mainly from either the inclusion or exclusion of specific Earth system feedbacks 2.2.2 The Remaining 1.5°C Carbon Budget (MacDougall et al., 2015; Burke et al., 2017; Lowe and Bernie, 2018) or different budget definitions (Rogelj et al., 2018). 2.2.2.1 Carbon budget estimates In contrast to the model-only estimates discussed above and employed Since the AR5, several approaches have been proposed to estimate in the AR5, this report additionally uses observations to inform its carbon budgets compatible with 1.5°C or 2°C. Most of these evaluation of the remaining carbon budget. Table 2.2 shows that the approaches indirectly rely on the approximate linear relationship assessed range of remaining carbon budgets consistent with 1.5°C between peak global mean temperature and cumulative emissions or 2°C is larger than the AR5 SYR estimate and is part way towards of carbon (the transient climate response to cumulative emissions of estimates constrained by recent observations (Millar et al., 2017; carbon, TCRE) (Collins et al., 2013; Friedlingstein et al., 2014a; Rogelj et Goodwin et al., 2018a; Tokarska and Gillett, 2018). Figure 2.3 illustrates al., 2016b), whereas others base their estimates on equilibrium climate that the change since AR5 is, in very large part, due to the application sensitivity (Schneider et al., 2017). The AR5 employed two approaches of a more recent observed baseline to the historic temperature change to determine carbon budgets. Working Group I (WGI) computed and cumulative emissions; here adopting the baseline period of 2006– carbon budgets from 2011 onwards for various levels of warming 2015 (see Chapter 1, Section 1.2.1). AR5 SYR Figures SPM.10 and 2.3 relative to the 1861–1880 period using RCP8.5 (Meinshausen et al., already illustrated the discrepancy between models and observations, 2011b; Stocker et al., 2013), whereas WGIII estimated their budgets but did not apply this as a correction to the carbon budget because they from a set of available pathways that were assessed to have a >50% were being used to illustrate the overall linear relationship between probability to exceed 1.5°C by mid-century, and return to 1.5°C or warming and cumulative carbon emissions in the CMIP5 models since below in 2100 with greater than 66% probability (Clarke et al., 2014). 1870, and were not specifically designed to quantify residual carbon These differences made AR5 WGI and WGIII carbon budgets difficult to budgets relative to the present for ambitious temperature goals. The compare as they are calculated over different time periods, are derived AR5 SYR estimate was also dependent on a subset of Earth system from a different sets of multi-gas and aerosol emission scenarios, models illustrated in Figure 2.3 of this report. Although, as outlined and use different concepts of carbon budgets (exceedance for WGI, below and in Table 2.2, considerably uncertainties remain, there is high avoidance for WGIII) (Rogelj et al., 2016b; Matthews et al., 2017). agreement across various lines of evidence assessed in this report that the remaining carbon budget for 1.5°C or 2°C would be larger than Carbon budgets can be derived from CO2-only experiments as well the estimates at the time of the AR5. However, the overall remaining as from multi-gas and aerosol scenarios. Some published estimates budget for 2100 is assessed to be smaller than that derived from the of carbon budgets compatible with 1.5°C or 2°C refer to budgets recent observational-informed estimates, as Earth system feedbacks for CO2-induced warming only, and hence do not take into account such as permafrost thawing reduce the budget applicable to centennial the contribution of non-CO2 climate forcers (Allen et al., 2009; scales (see Section 2.2.2.2). 104 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 2 Figure 2.3 | Temperature changes from 1850–1900 versus cumulative CO2 emissions since 1st January 1876. Solid lines with dots reproduce the globally averaged near-surface air temperature response to cumulative CO2 emissions plus non-CO2 forcers as assessed in Figure SPM10 of WGI AR5, except that points marked with years relate to a particular year, unlike in WGI AR5 Figure SPM.10, where each point relates to the mean over the previous decade. The AR5 data was derived from 15 Earth system models and 5 Earth system models of Intermediate Complexity for the historic observations (black) and RCP8.5 scenario (red), and the red shaded plume shows the range across the models as presented in the AR5. The purple shaded plume and the line are indicative of the temperature response to cumulative CO2 emissions and non-CO2 warming adopted in this report. The non-CO2 warming contribution is averaged from the MAGICC and FAIR models, and the purple shaded range assumes the AR5 WGI TCRE distribution (Supplementary Material 2.SM.1.1.2). The 2010 observation of surface temperature change (0.97°C based on 2006–2015 mean compared to 1850–1900, Chapter 1, Section 1.2.1) and cumulative carbon dioxide emissions from 1876 to the end of 2010 of 1,930 GtCO2 (Le Quéré et al., 2018) is shown as a filled purple diamond. The value for 2017 based on the latest cumulative carbon emissions up to the end of 2017 of 2,220 GtCO2 (Version 1.3 accessed 22 May 2018) and a surface temperature anomaly of 1.1°C based on an assumed temperature increase of 0.2°C per decade is shown as a hollow purple diamond. The thin blue line shows annual observations, with CO2 emissions from Le Quéré et al. (2018) and estimated globally averaged near-surface temperature from scaling the incomplete coverage and blended HadCRUT4 dataset in Chapter 1. The thin black line shows the CMIP5 multimodel mean estimate with CO2 emissions also from (Le Quéré et al., 2018). The thin black line shows the GMST historic temperature trends from Chapter 1, which give lower temperature changes up to 2006–2015 of 0.87°C and would lead to a larger remaining carbon budget. The dotted black lines illustrate the remaining carbon budget estimates for 1.5°C given in Table 2.2. Note these remaining budgets exclude possible Earth system feedbacks that could reduce the budget, such as CO2 and CH4 release from permafrost thawing and tropical wetlands (see Section 2.2.2.2). 2.2.2.2 CO2 and non-CO2 contributions to the remaining approximately consistent with a global mean temperature increase carbon budget of 1.5°C relative to pre-industrial levels. For this level of additional warming, remaining carbon budgets have been estimated (Table 2.2, A remaining carbon budget can be estimated from calculating the Supplementary Material 2.SM.1.1.2). amount of CO2 emissions consistent (given a certain value of TCRE) with an allowable additional amount of warming. Here, the allowable The remaining carbon budget calculation presented in the Table warming is the 1.5°C warming threshold minus the current warming 2.2 and illustrated in Figure 2.3 does not consider additional Earth taken as the 2006–2015 average, with a further amount removed to system feedbacks such as permafrost thawing. These are uncertain account for the estimated non-CO2 temperature contribution to the but estimated to reduce the remaining carbon budget by an order of remaining warming (Peters, 2016; Rogelj et al., 2016b). This assessment magnitude of about 100 GtCO2 and more thereafter. Accounting for uses the TCRE range from AR5 WGI (Collins et al., 2013) supported such feedbacks would make the carbon budget more applicable for by estimates of non-CO2 contributions that are based on published 2100 temperature targets, but would also increase uncertainty (Table methods and integrated pathways (Friedlingstein et al., 2014a; Allen et 2.2 and see below). Excluding such feedbacks, the assessed range for al., 2016, 2018; Peters, 2016; Smith et al., 2018). Table 2.2 and Figure the remaining carbon budget is estimated to be 840, 580, and 420 2.3 show the assessed remaining carbon budgets and key uncertainties GtCO2 for the 33rd, 50th and, 67th percentile of TCRE, respectively, for a set of additional warming levels relative to the 2006–2015 period with a median non-CO2 warming contribution and starting from 1 (see Supplementary Material 2.SM.1.1.2 for details). With an assessed January 2018 onward. Consistent with the approach used in the historical warming of 0.87°C ± 0.12°C from 1850–1900 to 2006–2015 IPCC Fifth Assessment Report (IPCC, 2013b), the latter estimates (Chapter 1, Section 1.2.1), 0.63°C of additional warming would be use global near-surface air temperatures both over the ocean and 105 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development over land to estimate global surface temperature change since pre- arises from a weakening of aerosol cooling and continued emissions industrial. The global warming from the pre-industrial period until the of non-CO2 GHGs (Sections 2.2.1, 2.3.3). This non-CO2 contribution 2006–2015 reference period is estimated to amount to 0.97°C with at the time of net zero CO2 emissions varies by about ±0.1°C across an uncertainty range of about ±0.1°C (see Chapter 1, Section 1.2.1). scenarios, resulting in a carbon budget uncertainty of about ±250 Three methodological improvements lead to these estimates of the GtCO2, and takes into account marked reductions in methane emissions remaining carbon budget being about 300 GtCO2 larger than those (Section 2.3.3). If these reductions are not achieved, remaining carbon reported in Table 2.2 of the IPCC AR5 SYR (IPCC, 2014a) (medium budgets are further reduced. Uncertainties in the non-CO2 forcing and confidence). The AR5 used 15 Earth System Models (ESM) and 5 temperature response are asymmetric and can influence the remaining Earth-system Models of Intermediate Complexity (EMIC) to derive an carbon budget by −400 to +200 GtCO2, with the uncertainty in aerosol estimate of the remaining carbon budget. Their approach hence made radiative forcing being the largest contributing factor (Table 2.2). The implicit assumptions about the level of warming to date, the future MAGICC and FAIR models in their respective parameter setups and contribution of non-CO2 emissions, and the temperature response model versions used to assess the non-CO2 warming contribution give to CO2 (TCRE). In this report, each of these aspects are considered noticeable different non-CO2 effective radiative forcing and warming explicitly. When estimating global warming until the 2006–2015 for the same scenarios while both being within plausible ranges of 2 reference period as a blend of near-surface air temperature over land future response (Figure 2.2 and Supplementary Material 2.SM.1.1, and sea-ice regions, and sea-surface temperature over open ocean, 2.SM.1.2). For this assessment, it is premature to assess the accuracy by averaging the four global mean surface temperature time series of their results, so it is assumed that both are equally representative listed in Chapter 1 Section 1.2.1, the global warming would amount of possible futures. Their non-CO2 warming estimates are therefore to 0.87°C ±0.1°C. Using the latter estimate of historical warming and averaged for the carbon budget assessment and their differences used projecting global warming using global near-surface air temperatures to guide the uncertainty assessment of the role of non-CO2 forcers. from model projections leads to remaining carbon budgets for limiting Nevertheless, the findings are robust enough to give high confidence global warming to 1.5°C of 1080, 770, and 570 GtCO2 for the 33rd, that the changing emissions of non-CO2 forcers (particularly the 50th, and 67th percentile of TCRE, respectively. Note that future reduction in cooling aerosol precursors) cause additional near-term research and ongoing observations over the next years will provide a warming and reduce the remaining carbon budget compared to the better indication as to how the 2006–2015 base period compares with CO2-only budget. the long-term trends and might affect the budget estimates. Similarly, improved understanding in Earth system feedbacks would result in a TCRE uncertainty directly impacts carbon budget estimates (Peters, better quantification of their impacts on remaining carbon budgets for 2016; Matthews et al., 2017; Millar and Friedlingstein, 2018). Based 1.5°C and 2°C. on multiple lines of evidence, AR5 WGI assessed a likely range for TCRE of 0.2°–0.7°C per 1000 GtCO2 (Collins et al., 2013). The TCRE After TCRE uncertainty, a major additional source of uncertainty is the of the CMIP5 Earth system models ranges from 0.23°C to 0.66°C magnitude of non-CO2 forcing and its contribution to the temperature per 1000 GtCO2 (Gillett et al., 2013). At the same time, studies using change between the present day and the time of peak warming. observational constraints find best estimates of TCRE of 0.35°–0.41°C Integrated emissions pathways can be used to ensure consistency per 1000 GtCO2 (Matthews et al., 2009; Gillett et al., 2013; Tachiiri et between CO2 and non-CO2 emissions (Bowerman et al., 2013; Collins al., 2015; Millar and Friedlingstein, 2018). This assessment continues et al., 2013; Clarke et al., 2014; Rogelj et al., 2014b, 2015a; Tokarska et to use the assessed AR5 TCRE range under the working assumption al., 2018). Friedlingstein et al. (2014a) used pathways with limited to that TCRE is normally distributed (Stocker et al., 2013). Observation- no climate mitigation to find a variation due to non-CO2 contributions based estimates have reported log-normal distributions of TCRE (Millar of about ±33% for a 2°C carbon budget. Rogelj et al. (2016b) showed and Friedlingstein, 2018). Assuming a log-normal instead of normal no particular bias in non-CO2 radiative forcing or warming at the time distribution of the assessed AR5 TCRE range would result in about a of exceedance of 2°C or at peak warming between scenarios with 200 GtCO2 increase for the median budget estimates but only about increasing emissions and strongly mitigated scenarios (consistent half at the 67th percentile, while historical temperature uncertainty with Stocker et al., 2013). However, clear differences of the non- and uncertainty in recent emissions contribute ±150 and ±50 GtCO2 CO2 warming contribution at the time of deriving a 2°C-consistent to the uncertainty, respectively (Table 2.2). carbon budget were reported for the four RCPs. Although the spread in non-CO2 forcing across scenarios can be smaller in absolute terms Calculating carbon budgets from the TCRE requires the assumption at lower levels of cumulative emissions, it can be larger in relative that the instantaneous warming in response to cumulative CO2 terms compared to the remaining carbon budget (Stocker et al., 2013; emissions equals the long-term warming or, equivalently, that Friedlingstein et al., 2014a; Rogelj et al., 2016b). Tokarska and Gillett the residual warming after CO2 emissions cease is negligible. The (2018) find no statistically significant differences in 1.5°C-consistent magnitude of this residual warming, referred to as the zero-emission cumulative emissions budgets when calculated for different RCPs from commitment, ranges from slightly negative (i.e., a slight cooling) consistent sets of CMIP5 simulations. to slightly positive for CO2 emissions up to present-day (Chapter 1, Section 1.2.4) (Lowe et al., 2009; Frölicher and Joos, 2010; Gillett et The mitigation pathways assessed in this report indicate that emissions al., 2011; Matthews and Zickfeld, 2012). The delayed temperature of non-CO2 forcers contribute an average additional warming of around change from a pulse CO2 emission introduces uncertainties in emission 0.15°C relative to 2006–2015 at the time of net zero CO2 emissions, budgets, which have not been quantified in the literature for budgets reducing the remaining carbon budget by roughly 320 GtCO2. This consistent with limiting warming to 1.5°C. As a consequence, this 106 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 uncertainty does not affect our carbon budget estimates directly but ocean thermal and carbon cycle inertia (Herrington and Zickfeld, 2014; it is included as an additional factor in the assessed Earth system Krasting et al., 2014; Zickfeld et al., 2016). This asymmetrical behaviour feedback uncertainty (as detailed below) of roughly 100 GtCO2 on makes carbon budgets path-dependent in the case of a budget and/or decadal time scales presented in Table 2.2. temperature overshoot (MacDougall et al., 2015). Although potentially large for scenarios with large overshoot (MacDougall et al., 2015), this Remaining carbon budgets are further influenced by Earth system path-dependence of carbon budgets has not been well quantified for feedbacks not accounted for in CMIP5 models, such as the permafrost 1.5°C- and 2°C-consistent scenarios and as such remains an important carbon feedback (Friedlingstein et al., 2014b; MacDougall et al., 2015; knowledge gap. This assessment does not explicitly account for path Burke et al., 2017; Lowe and Bernie, 2018), and their influence on dependence but takes it into consideration for its overall confidence the TCRE. Lowe and Bernie (2018) used a simple climate sensitivity assessment. scaling approach to estimate that Earth system feedbacks (such as CO2 released by permafrost thawing or methane released by wetlands) This assessment finds a larger remaining budget from the 2006–2015 could reduce carbon budgets for 1.5°C and 2°C by roughly 100 base period than the 1.5°C and 2°C remaining budgets inferred from GtCO2 on centennial time scales. Their findings are based on an older AR5 from the start of 2011, which were approximately 1000 GtCO2 understanding of Earth system feedbacks (Arneth et al., 2010). This for the 2°C (66% of model simulations) and approximately 400 GtCO2 2 estimate is broadly supported by more recent analysis of individual for the 1.5°C budget (66% of model simulations). In contrast, this feedbacks. Schädel et al. (2014) suggest an upper bound of 24.4 PgC assessment finds approximately 1600 GtCO2 for the 2°C (66th TCRE (90 GtCO2) emitted from carbon release from permafrost over the next percentile) and approximately 860 GtCO2 for the 1.5°C budget (66th forty years for a RCP4.5 scenario. Burke et al. (2017) use a single model TCRE percentile) from 2011. However, these budgets are not directly to estimate permafrost emissions between 0.3 and 0.6 GtCO -12 y from equivalent as AR5 reported budgets for fractions of CMIP5 simulations the point of 1.5°C stabilization, which would reduce the budget by and other lines of evidence, while this report uses the assessed range around 20 GtCO2 by 2100. Comyn-Platt et al. (2018) include carbon of TCRE and an assessment of the non-CO2 contribution at net zero CO2 and methane emissions from permafrost and wetlands and suggest the emissions to provide remaining carbon budget estimates at various 1.5°C remaining carbon budget is reduced by 116 GtCO2. Additionally, percentiles of TCRE. Furthermore, AR5 did not specify remaining Mahowald et al. (2017) find there is possibility of 0.5–1.5 GtCO y-12 budgets to carbon neutrality as we do here, but budgets until the time being released from aerosol-biogeochemistry changes if aerosol the temperature limit of interest was reached, assuming negligible zero emissions cease. In summary, these additional Earth system feedbacks emission commitment and taking into account the non-CO2 forcing at taken together are assessed to reduce the remaining carbon budget that point in time. applicable to 2100 by an order of magnitude of 100 GtCO2, compared to the budgets based on the assumption of a constant TCRE presented In summary, although robust physical understanding underpins the in Table 2.2 (limited evidence, medium agreement), leading to overall carbon budget concept, relative uncertainties become larger as a medium confidence in their assessed impact. After 2100, the impact specific temperature limit is approached. For the budget, applicable of additional Earth system feedbacks is expected to further reduce the to the mid-century, the main uncertainties relate to the TCRE, non-CO2 remaining carbon budget (medium confidence). emissions, radiative forcing and response. For 2100, uncertain Earth system feedbacks such as permafrost thawing would further reduce The uncertainties presented in Table 2.2 cannot be formally combined, the available budget. The remaining budget is also conditional upon but current understanding of the assessed geophysical uncertainties the choice of baseline, which is affected by uncertainties in both suggests at least a ±50% possible variation for remaining carbon historical emissions, and in deriving the estimate of globally averaged budgets for 1.5°C-consistent pathways. By the end of 2017, human-induced warming. As a result, only medium confidence can be anthropogenic CO2 emissions since the pre-industrial period are assigned to the assessed remaining budget values for 1.5°C and 2.0°C estimated to have amounted to approximately 2200 ±320 GtCO2 and their uncertainty. (medium confidence) (Le Quéré et al., 2018). When put in the context of year-2017 CO2 emissions (about 42 GtCO2 yr -1, ±3 GtCO2 yr -1, high confidence) (Le Quéré et al., 2018), a remaining carbon budget of 580 GtCO2 (420 GtCO2) suggests meeting net zero global CO2 emissions in about 30 years (20 years) following a linear decline starting from 2018 (rounded to the nearest five years), with a variation of ±15–20 years due to the geophysical uncertainties mentioned above (high confidence). The remaining carbon budgets assessed in this section are consistent with limiting peak warming to the indicated levels of additional warming. However, if these budgets are exceeded and the use of CDR (see Sections 2.3 and 2.4) is envisaged to return cumulative CO2 emissions to within the carbon budget at a later point in time, additional uncertainties apply because the TCRE is different under increasing and decreasing atmospheric CO2 concentrations due to 107 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Table 2.2 | The assessed remaining carbon budget and its uncertainties. Shaded blue horizontal bands illustrate the uncertainty in historical temperature increase from the 1850–1900 base period until the 2006–2015 period as estimated from global near-surface air temperatures, which impacts the additional warming until a specific temperature limit like 1.5°C or 2°C relative to the 1850–1900 period. Shaded grey cells indicate values for when historical temperature increase is estimated from a blend of near-surface air temperatures over land and sea ice regions and sea-surface temperatures over oceans. Additional Approximate Remaining Carbon Budget Warming Warming (Excluding Additional since since Earth System Feedbacks*(5)) Key Uncertainties and Variations*(4) 2006–2015 1850–1900 [GtCO2 from 1.1.2018] *(2) [°C]*(1) [°C]*(1) Non-CO2 Non-CO2 TCRE Historical Recent Earth System Percentiles of TCRE scenario forcing and distribution temperature emissions Feedbacks *(3) variation response uncertainty uncertainty uncertainty *(5) *(6) uncertainty *(7) *(1) *(8) 33rd 50th 67th [GtCO ] [GtCO ] [GtCO2] [GtCO2] [GtCO2] [GtCO2 2 2] 0.3 290 160 80 2 0.4 530 350 230 Budgets on the left are 0.5 770 530 380 reduced by 0.53 ~1.5°C 840 580 420 about –100 ±250 –400 to +200 +100 to +200 ±250 ±20 0.6 1010 710 530 on centennial time scales 0.63 1080 770 570 0.7 1240 900 680 0.78 1440 1040 800 0.8 1480 1080 830 0.9 1720 1260 980 1 1960 1450 1130 1.03 ~2°C 2030 1500 1170 1.1 2200 1630 1280 1.13 2270 1690 1320 1.2 2440 1820 1430 Notes: *(1) Chapter 1 has assessed historical warming between the 1850–1900 and 2006–2015 periods to be 0.87°C with a ±0.12°C likely (1-standard deviation) range, and global near-surface air temperature to be 0.97°C. The temperature changes from the 2006–2015 period are expressed in changes of global near-surface air temperature. *(2) Historical CO2 emissions since the middle of the 1850–1900 historical base period (mid-1875) are estimated at 1940 GtCO2 (1640–2240 GtCO2, one standard deviation range) until end 2010. Since 1 January 2011, an additional 290 GtCO2 (270–310 GtCO2, one sigma range) has been emitted until the end of 2017 (Le Quéré et al., 2018). *(3) TCRE: transient climate response to cumulative emissions of carbon, assessed by AR5 to fall likely between 0.8–2.5°C/1000 PgC (Collins et al., 2013), considering a normal distribution consistent with AR5 (Stocker et al., 2013). Values are rounded to the nearest 10 GtCO2. *(4) Focussing on the impact of various key uncertainties on median budgets for 0.53°C of additional warming. *(5) Earth system feedbacks include CO2 released by permafrost thawing or methane released by wetlands, see main text. *(6) Variations due to different scenario assumptions related to the future evolution of non-CO2 emissions. *(7) The distribution of TCRE is not precisely defined. Here the influence of assuming a lognormal instead of a normal distribution shown. *(8) Historical emissions uncertainty reflects the uncertainty in historical emissions since 1 January 2011. 2.3 Overview of 1.5°C Mitigation Pathways Since the AR5, an extensive body of literature has appeared on integrated pathways consistent with 1.5°C (Section 2.1) (Rogelj et al., 2015b, 2018; Limiting global mean temperature increase at any level requires global Akimoto et al., 2017; Löffler et al., 2017; Marcucci et al., 2017; Su et al., CO2 emissions to become net zero at some point in the future (Zickfeld 2017; Bauer et al., 2018; Bertram et al., 2018; Grubler et al., 2018; Holz et al., 2009; Collins et al., 2013). At the same time, limiting the residual et al., 2018b; Kriegler et al., 2018a; Liu et al., 2018; Luderer et al., 2018; warming of short-lived non-CO2 emissions can be achieved by reducing Strefler et al., 2018a; van Vuuren et al., 2018; Vrontisi et al., 2018; Zhang their annual emissions as much as possible (Section 2.2, Cross-Chapter et al., 2018). These pathways have global coverage and represent all Box 2 in Chapter 1). This would require large-scale transformations of GHG-emitting sectors and their interactions. Such integrated pathways the global energy–agriculture–land-economy system, affecting the allow the exploration of the whole-system transformation, and hence way in which energy is produced, agricultural systems are organized, provide the context in which the detailed sectoral transformations and food, energy and materials are consumed (Clarke et al., 2014). This assessed in Section 2.4 of this chapter are taking place. section assesses key properties of pathways consistent with limiting global mean temperature to 1.5°C relative to pre-industrial levels, The overwhelming majority of published integrated pathways have including their underlying assumptions and variations. been developed by global IAMs that represent key societal systems 108 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 and their interactions, like the energy system, agriculture and land use, future population levels, secular trends in economic growth and and the economy (see Section 6.2 in Clarke et al., 2014). Very often income convergence, behavioural change and technological progress. these models also include interactions with a representation of the These dimensions have been recently explored in the context of geophysical system, for example, by including spatially explicit land the SSPs (Kriegler et al., 2012; O’Neill et al., 2014), which provide models or carbon cycle and climate models. The complex features of narratives (O’Neill et al., 2017) and quantifications (Crespo Cuaresma, these subsystems are approximated and simplified in these models. 2017; Dellink et al., 2017; KC and Lutz, 2017; Leimbach et al., 2017; IAMs are briefly introduced in Section 2.1 and important knowledge Riahi et al., 2017) of different world futures across which scenario gaps identified in Section 2.6. An overview to the use, scope and dimensions are varied to explore differential challenges to adaptation limitations of IAMs is provided in Supplementary Material 2.SM.1.2. and mitigation (Cross-Chapter Box 1 in Chapter 1). This framework is increasingly adopted by IAMs to systematically explore the impact The pathway literature is assessed in two ways in this section. First, of socio-economic assumptions on mitigation pathways (Riahi et al., various insights on specific questions reported by studies can be assessed 2017), including 1.5°C-consistent pathways (Rogelj et al., 2018). The to identify robust or divergent findings. Second, the combined body of narratives describe five worlds (SSP1–5) with different socio-economic scenarios can be assessed to identify salient features of pathways in line predispositions to mitigate and adapt to climate change (Table 2.3). As with a specific climate goal across a wide range of models. The latter a result, population and economic growth projections can vary strongly 2 can be achieved by assessing pathways available in the database to across integrated scenarios, including available 1.5°C-consistent this assessment (Section 2.1, Supplementary Material 2.SM.1.2–4). The pathways (Figure 2.4). For example, based on alternative future ensemble of scenarios available to this assessment is an ensemble of fertility, mortality, migration and educational assumptions, population opportunity: it is a collection of scenarios from a diverse set of studies projections vary between 8.5 and 10.0 billion people by 2050 and that was not developed with a common set of questions and a statistical between 6.9 and 12.6 billion people by 2100 across the SSPs. An analysis of outcomes in mind. This means that ranges can be useful to important factor for these differences is future female educational identify robust and sensitive features across available scenarios and attainment, with higher attainment leading to lower fertility rates and contributing modelling frameworks, but do not lend themselves to a therefore decreased population growth up to a level of 1 billion people statistical interpretation. To understand the reasons underlying the ranges, by 2050 (Lutz and KC, 2011; Snopkowski et al., 2016; KC and Lutz, an assessment of the underlying scenarios and studies is required. To this 2017). Consistent with population development, GDP per capita also end, this section highlights illustrative pathway archetypes that help to varies strongly in SSP baselines, ranging from about 20 to more than clarify the variation in assessed ranges for 1.5°C-consistent pathways. 50 thousand USD2010 per capita in 2050 (in purchasing power parity values, PPP), in part driven by assumptions on human development, 2.3.1 Range of Assumptions Underlying 1.5°C Pathways technological progress and development convergence between and within regions (Crespo Cuaresma, 2017; Dellink et al., 2017; Leimbach Earlier assessments have highlighted that there is no single pathway to et al., 2017). Importantly, none of the GDP projections in the mitigation achieve a specific climate objective (e.g., Clarke et al., 2014). Pathways pathway literature assessed in this chapter included the feedback of depend on the underlying development processes, and societal climate damages on economic growth (Hsiang et al., 2017). choices, which affect the drivers of projected future baseline emissions. Furthermore, societal choices also affect climate change solutions in Baseline projections for energy-related GHG emissions are sensitive to pathways, like the technologies that are deployed, the scale at which economic growth assumptions, while baseline projections for land-use they are deployed, or whether solutions are globally coordinated. emissions are more directly affected by population growth (assuming A key finding is that 1.5°C-consistent pathways could be identified unchanged land productivity and per capita demand for agricultural under a considerable range of assumptions in model studies despite products) (Kriegler et al., 2016). SSP-based modelling studies of the tightness of the 1.5°C emissions budget (Figures 2.4, 2.5) (Rogelj mitigation pathways have identified high challenges to mitigation et al., 2018). for worlds with a focus on domestic issues and regional security combined with high population growth (SSP3), and for worlds with The AR5 provided an overview of how differences in model structure rapidly growing resource and fossil-fuel intensive consumption (SSP5) and assumptions can influence the outcome of transformation (Riahi et al., 2017). No model could identify a 2°C-consistent pathway pathways (Section 6.2 in Clarke et al., 2014, as well as Table A.II.14 for SSP3, and high mitigation costs were found for SSP5. This picture in Krey et al., 2014b) and this was further explored by the modelling translates to 1.5°C-consistent pathways that have to remain within community in recent years with regard to, e.g., socio-economic drivers even tighter emissions constraints (Rogelj et al., 2018). No model (Kriegler et al., 2016; Marangoni et al., 2017; Riahi et al., 2017), found a 1.5°C-consistent pathway for SSP3 and some models could not technology assumptions (Bosetti et al., 2015; Creutzig et al., 2017; identify 1.5°C-consistent pathways for SSP5 (2 of 4 models, compared Pietzcker et al., 2017), and behavioural factors (van Sluisveld et al., to 1 of 4 models for 2°C-consistent pathways). The modelling analysis 2016; McCollum et al., 2017). also found that the effective control of land-use emissions becomes even more critical in 1.5°C-consistent pathways. Due to high inequality 2.3.1.1 Socio-economic drivers and the demand for levels in SSP4, land use can be less well managed. This caused 2 of energy and land in 1.5°C pathways 3 models to no longer find an SSP4-based 1.5°C-consistent pathway even though they identified SSP4-based 2°C-consistent pathways at There is deep uncertainty about the ways humankind will use energy relatively moderate mitigation costs (Riahi et al., 2017). Rogelj et al. and land in the 21st century. These ways are intricately linked to (2018) further reported that all six participating models identified 109 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Table 2.3 | Key Characteristics of the Five Shared Socio-Economic Pathways (SSPs) (O’Neill et al., 2017). Socio-Economic Socio-Economic Challenges to Adaptation Challenges to Mitigation Low Medium High SSP5: Fossil-fuelled development SSP3: Regional rivalry • low population • high population • very high economic growth per capita • low economic growth per capita • high human development • low human development • high technological progress • low technological progress High • ample fossil fuel resources • resource-intensive lifestyles • very resource intensive lifestyles • resource-constrained energy and food demand • high energy and food demand per capita per capita • economic convergence and global cooperation • focus on regional food and energy security • regionalization and lack of global cooperation SSP2: Middle of the road 2 • medium population • medium and uneven economic growth • medium and uneven human development Medium • medium and uneven technological progress • resource-intensive lifestyles • medium and uneven energy and food demand per capita • limited global cooperation and economic convergence SSP1: Sustainable development SSP4: Inequality • low population • Medium to high population • high economic growth per capita • Unequal low to medium economic • high human development growth per capita • high technological progress • Unequal low to medium human development Low • environmentally oriented technological and • unequal technological progress: high in globalized behavioural change high-tech sectors, slow in domestic sectors • resource-efficient lifestyles • unequal lifestyles and energy /food consumption: • low energy and food demand per capita resource intensity depending on income • economic convergence and global cooperation • Globally connected elite, disconnected domestic work forces 1.5°C-consistent pathways in a sustainability oriented world (SSP1) and and high energy demand scenario (S5, based on SSP5) developed with four of six models found 1.5°C-consistent pathways for middle-of-the- the REMIND-MAgPIE model (Kriegler et al., 2017), and a middle-of- road developments (SSP2). These results show that 1.5°C-consistent the-road scenario (S2, based on SSP2) developed with the MESSAGE- pathways can be identified under a broad range of assumptions, but GLOBIOM model (Fricko et al., 2017). In addition, we include a scenario that lack of global cooperation (SSP3), high inequality (SSP4) and/or with low energy demand (LED) (Grubler et al., 2018), which reflects high population growth (SSP3) that limit the ability to control land use recent literature with a stronger focus on demand-side measures emissions, and rapidly growing resource-intensive consumption (SSP5) (Bertram et al., 2018; Grubler et al., 2018; Liu et al., 2018; van Vuuren are key impediments. et al., 2018). Pathways LED, S1, S2, and S5 are referred to as P1, P2, P3, and P4 in the Summary for Policymakers. Figure 2.4 compares the range of underlying socio-economic developments as well as energy and food demand in available 2.3.1.2 Mitigation options in 1.5°C pathways 1.5°C-consistent pathways with the full set of published scenarios that were submitted to this assessment. While 1.5°C-consistent In the context of 1.5°C pathways, the portfolio of mitigation options pathways broadly cover the full range of population and economic available to the model becomes an increasingly important factor. IAMs growth developments (except for the high population development include a wide variety of mitigation options, as well as measures that in SSP3-based scenarios), they tend to cluster on the lower end for achieve CDR from the atmosphere (Krey et al., 2014a, b) (see Chapter 4, energy and food demand. They still encompass, however, a wide range Section 4.3 for a broad assessment of available mitigation measures). of developments from decreasing to increasing demand levels relative For the purpose of this assessment, we elicited technology availability to today. For the purpose of this assessment, a set of four illustrative in models that submitted scenarios to the database as summarized 1.5°C-consistent pathway archetypes were selected to show the in Supplementary Material 2.SM.1.2, where a detailed picture of the variety of underlying assumptions and characteristics (Figure 2.4). They technology variety underlying available 1.5°C-consistent pathways comprise three 1.5°C-consistent pathways based on the SSPs (Rogelj is provided. Modelling choices on whether a particular mitigation et al., 2018): a sustainability oriented scenario (S1 based on SSP1) measure is included are influenced by an assessment of its global developed with the AIM model (Fujimori, 2017), a fossil-fuel intensive mitigation potential, the availability of data and literature describing 110 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 (a) (b) S1 S2 S5 LED All scenarios 1.5C pathways (c) (d) 2 Figure 2.4 | Range of assumptions about socio-economic drivers and projections for energy and food demand in the pathways available to this assessment. 1.5°C-consistent pathways are blue, other pathways grey. Trajectories for the illustrative 1.5°C-consistent archetypes used in this Chapter (LED, S1, S2, S5; referred to as P1, P2, P3, and P4 in the Summary for Policymakers.) are highlighted. S1 is a sustainability oriented scenario, S2 is a middle-of-the-road scenario, and S5 is a fossil-fuel intensive and high energy demand scenario. LED is a scenario with particularly low energy demand. Population assumptions in S2 and LED are identical. Panels show (a) world population, (b) gross world product in purchasing power parity values, (c) final energy demand, and (d) food demand. its techno-economic characteristics and future prospects, and the 2018; Holz et al., 2018b; Kriegler et al., 2018a; Liu et al., 2018; Rogelj et computational challenge of representing the measure, e.g., in terms of al., 2018; Strefler et al., 2018b; van Vuuren et al., 2018). However, there required spatio-temporal and process detail. are a few potentially disruptive technologies that are typically not yet well covered in IAMs and that have the potential to alter the shape of This elicitation (Supplementary Material 2.SM.1.2) confirms that mitigation pathways beyond the ranges in the IAM-based literature. IAMs cover most supply-side mitigation options on the process level, Those are also included in Supplementary Material 2.SM.1.2. The while many demand-side options are treated as part of underlying configuration of carbon-neutral energy systems projected in mitigation assumptions, which can be varied (Clarke et al., 2014). In recent years, pathways can vary widely, but they all share a substantial reliance there has been increasing attention on improving the modelling on bioenergy under the assumption of effective land-use emissions of integrating variable renewable energy into the power system control. There are other configurations with less reliance on bioenergy (Creutzig et al., 2017; Luderer et al., 2017; Pietzcker et al., 2017) and that are not yet comprehensively covered by global mitigation pathway of behavioural change and other factors influencing future demand modelling. One approach is to dramatically reduce and electrify energy for energy and food (van Sluisveld et al., 2016; McCollum et al., 2017; demand for transportation and manufacturing to levels that make Weindl et al., 2017), including in the context of 1.5°C-consistent residual non-electric fuel use negligible or replaceable by limited pathways (Grubler et al., 2018; van Vuuren et al., 2018). The literature amounts of electrolytic hydrogen. Such an approach is presented in on the many diverse CDR options only recently started to develop a first-of-its kind low-energy-demand scenario (Grubler et al., 2018) strongly (Minx et al., 2017) (see Chapter 4, Section 4.3.7 for a detailed which is part of this assessment. Other approaches rely less on energy assessment), and hence these options are only partially included in demand reductions, but employ cheap renewable electricity to push IAM analyses. IAMs mostly incorporate afforestation and bioenergy the boundaries of electrification in the industry and transport sectors with carbon capture and storage (BECCS) and only in few cases also (Breyer et al., 2017; Jacobson, 2017). In addition, these approaches include direct air capture with CCS (DACCS) (Chen and Tavoni, 2013; deploy renewable-based Power-2-X (read: Power to “x”) technologies Marcucci et al., 2017; Strefler et al., 2018b). to substitute residual fossil-fuel use (Brynolf et al., 2018). An important element of carbon-neutral Power-2-X applications is the combination Several studies have either directly or indirectly explored the of hydrogen generated from renewable electricity and CO2 captured dependence of 1.5°C-consistent pathways on specific (sets of) from the atmosphere (Zeman and Keith, 2008). Alternatively, algae mitigation and CDR technologies (Bauer et al., 2018; Grubler et al., are considered as a bioenergy source with more limited implications 111 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development for land use and agricultural systems than energy crops (Williams and and a variety of ancillary policies to safeguard other sustainable Laurens, 2010; Walsh et al., 2016; Greene et al., 2017). development goals (Bertram et al., 2018; van Vuuren et al., 2018). A further discussion of policy implications of 1.5°C-consistent pathways Furthermore, a range of measures could radically reduce agricultural is provided in Section 2.5.1, while a general discussion of policies and and land-use emissions and are not yet well-covered in IAM modelling. options to strengthen action are subject of Chapter 4, Section 4.4. This includes plant-based proteins (Joshi and Kumar, 2015) and cultured meat (Post, 2012) with the potential to substitute for livestock products 2.3.2 Key Characteristics of 1.5°C Pathways at much lower GHG footprints (Tuomisto and Teixeira de Mattos, 2011). Large-scale use of synthetic or algae-based proteins for animal feed 1.5°C-consistent pathways are characterized by a rapid phase out could free pasture land for other uses (Madeira et al., 2017; Pikaar et al., of CO2 emissions and deep emissions reductions in other GHGs and 2018). Novel technologies such as methanogen inhibitors and vaccines climate forcers (Section 2.2.2 and 2.3.3). This is achieved by broad (Wedlock et al., 2013; Hristov et al., 2015; Herrero et al., 2016; Subharat transformations in the energy; industry; transport; buildings; and et al., 2016) as well as synthetic and biological nitrification inhibitors agriculture, forestry and other land-use (AFOLU) sectors (Section 2.4) (Subbarao et al., 2013; Di and Cameron, 2016) could substantially (Bauer et al., 2018; Grubler et al., 2018; Holz et al., 2018b; Kriegler 2 reduce future non-CO2 emissions from agriculture if commercialized et al., 2018b; Liu et al., 2018; Luderer et al., 2018; Rogelj et al., successfully. Enhancing carbon sequestration in soils (Paustian et al., 2018; van Vuuren et al., 2018; Zhang et al., 2018). Here we assess 2016; Frank et al., 2017; Zomer et al., 2017) can provide the dual benefit 1.5°C-consistent pathways with and without overshoot during of CDR and improved soil quality. A range of conservation, restoration the 21st century. One study also explores pathways overshooting and land management options can also increase terrestrial carbon 1.5°C for longer than the 21st century (Akimoto et al., 2017), but uptake (Griscom et al., 2017). In addition, the literature discusses these are not considered 1.5°C-consistent pathways in this report CDR measures to permanently sequester atmospheric carbon in rocks (Chapter 1, Section 1.1.3). This subsection summarizes robust and (mineralization and enhanced weathering, see Chapter 4, Section varying properties of 1.5°C-consistent pathways regarding system 4.3.7) as well as carbon capture and usage in long-lived products like transformations, emission reductions and overshoot. It aims to provide plastics and carbon fibres (Mazzotti et al., 2005; Hartmann et al., 2013). an introduction to the detailed assessment of the emissions evolution Progress in the understanding of the technical viability, economics and (Section 2.3.3), CDR deployment (Section 2.3.4), energy (Section 2.4.1, sustainability of these ways to achieve and maintain carbon neutral 2.4.2), industry (2.4.3.1), buildings (2.4.3.2), transport (2.4.3.3) and energy and land use can affect the characteristics, costs and feasibility land-use transformations (Section 2.4.4) in 1.5°C-consistent pathways. of 1.5°C-consistent pathways significantly. Throughout Sections 2.3 and 2.4, pathway properties are highlighted with four 1.5°C-consistent pathway archetypes (LED, S1, S2, S5; referred 2.3.1.3 Policy assumptions in 1.5°C pathways to as P1, P2, P3, and P4 in the Summary for Policymakers) covering a wide range of different socio-economic and technology assumptions Besides assumptions related to socio-economic drivers and mitigation (Figure 2.5, Section 2.3.1). technology, scenarios are also subject to assumptions about the mitigation policies that can be put in place. Mitigation policies can 2.3.2.1 Variation in system transformations underlying 1.5°C either be applied immediately in scenarios or follow staged or delayed pathways approaches. Policies can span many sectors (e.g., economy-wide carbon pricing), or policies can be applicable to specific sectors only (like the Be it for the energy, transport, buildings, industry, or AFOLU sector, energy sector) with other sectors (e.g., the agricultural or the land-use the literature shows that multiple options and choices are available in sector) treated differently. These variations can have an important each of these sectors to pursue stringent emissions reductions (Section impact on the ability of models to generate scenarios compatible with 2.3.1.2, Supplementary Material 2.SM.1.2, Chapter 4, Section 4.3). stringent climate targets like 1.5°C (Luderer et al., 2013; Rogelj et al., Because the overall emissions total under a pathway is limited by a 2013b; Bertram et al., 2015b; Kriegler et al., 2018a; Michaelowa et al., geophysical carbon budget (Section 2.2.2), choices in one sector affect 2018). In the scenario ensemble available to this assessment, several the efforts that are required from others (Clarke et al., 2014). A robust variations of near-term mitigation policy implementation can be found: feature of 1.5°C-consistent pathways, as highlighted by the set of immediate and cross-sectoral global cooperation from 2020 onward pathway archetypes in Figure 2.5, is a virtually full decarbonization of the towards a global climate objective, a phase-in of globally coordinated power sector around mid-century, a feature shared with 2°C-consistent mitigation policy from 2020 to 2040, and a more short-term oriented pathways. The additional emissions reductions in 1.5°C-consistent and regionally diverse global mitigation policy, following NDCs until compared to 2°C-consistent pathways come predominantly from the 2030 (Kriegler et al., 2018a; Luderer et al., 2018; McCollum et al., 2018; transport and industry sectors (Luderer et al., 2018). Emissions can be Rogelj et al., 2018; Strefler et al., 2018b). For example, the above- apportioned differently across sectors, for example, by focussing on mentioned SSP quantifications assume regionally scattered mitigation reducing the overall amount of CO2 produced in the energy end-use policies until 2020, and vary in global convergence thereafter (Kriegler sectors, and using limited contributions of CDR by the AFOLU sector et al., 2014a; Riahi et al., 2017). The impact of near-term policy choices (afforestation and reforestation, S1 and LED pathways in Figure 2.5) on 1.5°C-consistent pathways is discussed in Section 2.3.5. The (Grubler et al., 2018; Holz et al., 2018b; van Vuuren et al., 2018), or literature has also explored 1.5°C-consistent pathways that build on by being more lenient about the amount of CO2 that continues to a portfolio of policy approaches until 2030, including the combination be produced in the above-mentioned end-use sectors (both by 2030 of regulatory policies and carbon pricing (Kriegler et al., 2018a), and mid-century) and strongly relying on technological CDR options 112 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 2 Figure 2.5 | Evolution and break down of global anthropogenic CO2 emissions until 2100. The top-left panel shows global net CO2 emissions in Below-1.5°C, 1.5°C-low-overshoot (OS), and 1.5°C-high-OS pathways, with the four illustrative 1.5°C-consistent pathway archetypes of this chapter highlighted. Ranges at the bottom of the top-left panel show the 10th–90th percentile range (thin line) and interquartile range (thick line) of the time that global CO2 emissions reach net zero per pathway class, and for all pathways classes combined. The top-right panel provides a schematic legend explaining all CO2 emissions contributions to global CO2 emissions. The bottom row shows how various CO2 contributions are deployed and used in the four illustrative pathway archetypes (LED, S1, S2, S5, referred to as P1, P2, P3, and P4 in the Summary for Policymakers) used in this chapter (see Section 2.3.1.1). Note that the S5 scenario reports the building and industry sector emissions jointly. Green-blue areas hence show emissions from the transport sector and the joint building and industry demand sector, respectively. like BECCS (S2 and S5 pathways in Figure 2.5) (Luderer et al., 2018; exceeding this remaining carbon budget at some point in time would Rogelj et al., 2018). Major drivers of these differences are assumptions give a one-in-three (one-in-two) chance that the 1.5°C limit is overshot about energy and food demand and the stringency of near-term climate (Table 2.2). For comparison, around 290 ± 20 (1 standard deviation policy (see the difference between early action in the scenarios S1, range) GtCO2 have been emitted in the years 2011–2017, with annual LED and more moderate action until 2030 in the scenarios S2, S5). CO2 emissions in 2017 around 42 ± 3 GtCO2 yr −1 (Jackson et al., 2017; Furthermore, the carbon budget in each of these pathways depends Le Quéré et al., 2018). Committed fossil-fuel emissions from existing also on the non-CO2 mitigation measures implemented in each of them, fossil-fuel infrastructure as of 2010 have been estimated at around particularly for agricultural emissions (Sections 2.2.2, 2.3.3) (Gernaat et 500 ± 200 GtCO2 (with about 200 GtCO2 already emitted through al., 2015). Those pathways differ not only in terms of their deployment 2017) (Davis and Caldeira, 2010). Coal-fired power plants contribute of mitigation and CDR measures (Sections 2.3.4 and 2.4), but also in the largest part. Committed emissions from existing coal-fired power terms of the resulting temperature overshoot (Figure 2.1). Furthermore, plants built through the end of 2016 are estimated to add up to roughly they have very different implications for the achievement of sustainable 200 GtCO2, and a further 100–150 GtCO2 from coal-fired power plants development objectives, as further discussed in Section 2.5.3. under construction or planned (González-Eguino et al., 2017; Edenhofer et al., 2018). However, there has been a marked slowdown of planned 2.3.2.2 Pathways keeping warming below 1.5°C or temporarily coal-power projects in recent years, and some estimates indicate that overshooting it the committed emissions from coal plants that are under construction or planned have halved since 2015 (Shearer et al., 2018). Despite these This subsection explores the conditions that would need to be fulfilled uncertainties, the committed fossil-fuel emissions are assessed to to stay below 1.5°C warming without overshoot. As discussed in Section already amount to more than two thirds (half) of the remaining carbon 2.2.2, to keep warming below 1.5°C with a two-in-three (one-in-two) budget. chance, the cumulative amount of CO2 emissions from 2018 onwards need to remain below a carbon budget of 420 (580) GtCO2; accounting An important question is to what extent the nationally determined for the effects of additional Earth system feedbacks until 2100 reduces contributions (NDCs) under the Paris Agreement are aligned with the this estimate by 100 GtCO2. Based on the current state of knowledge, remaining carbon budget. It was estimated that the NDCs, if successfully 113 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development implemented, imply a total of 400–560 GtCO2 emissions over the of 650–1270 GtCO2 for the period 2018–2100 (5th–95th percentile; 2018–2030 period (considering both conditional and unconditional median 950 GtCO2) in 1.5°C pathways with no or limited overshoot. NDCs) (Rogelj et al., 2016a). Thus, following an NDC trajectory would The lower end of the range is close to what emerges from a scenario already exhaust 95–130% (70–95%) of the remaining two-in-three of transformative change that halves CO2 emissions every decade (one-in-two) 1.5°C carbon budget (unadjusted for additional Earth from 2020 to 2050 (Rockström et al., 2017). All these estimates are system feedbacks) by 2030. This would leave no time (0–9 years) to above the remaining carbon budget for a one-in-two chance of limiting bring down global emissions from NDC levels of around 40 GtCO yr−12 warming below 1.5°C without overshoot, including the low end of the in 2030 (Fawcett et al., 2015; Rogelj et al., 2016a) to net zero (further hypothetical sensitivity analysis of Kriegler et al. (2018b), who assumes discussion in Section 2.3.5). 75 Gt AFOLU CO2 emissions adding to a total of 575 GtCO2 gross CO2 emissions. As almost no cases have been identified that keep gross CO2 Most 1.5°C-consistent pathways show more stringent emissions emissions within the remaining carbon budget for a one-in-two chance reductions by 2030 than implied by the NDCs (Section 2.3.5) The lower of limiting warming to 1.5°C, and based on current understanding of end of those pathways reach down to below 20 GtCO2 yr −1 in 2030 the geophysical response and its uncertainties, the available evidence (Section 2.3.3, Table 2.4), less than half of what is implied by the NDCs. indicates that avoiding overshoot of 1.5°C will require some type of 2 Whether such pathways will be able to limit warming to 1.5°C without CDR in a broad sense, e.g., via net negative AFOLU CO2 emissions overshoot will depend on whether cumulative net CO2 emissions over (medium confidence). (Table 2.2). the 21st century can be kept below the remaining carbon budget at any time. Net global CO2 emissions are derived from the gross amount Net CO2 emissions can fall below gross CO2 emissions, if CDR is of CO2 that humans annually emit into the atmosphere reduced by the brought into the mix. Studies have looked at mitigation and CDR amount of anthropogenic CDR in each year. New research has looked in combination to identify strategies for limiting warming to 1.5°C more closely at the amount and the drivers of gross CO2 emissions (Sanderson et al., 2016; Ricke et al., 2017). CDR, which may include from fossil-fuel combustion and industrial processes (FFI) in deep net negative AFOLU CO2 emissions, is deployed by all 1.5°C-consistent mitigation pathways (Luderer et al., 2018), and found that the larger pathways available to this assessment, but the scale of deployment part of remaining CO2 emissions come from direct fossil-fuel use in and choice of CDR measures varies widely (Section 2.3.4). Furthermore, the transport and industry sectors, while residual energy supply sector no CDR technology has been deployed at scale yet, and all come with emissions (mostly from the power sector) are limited by a rapid approach concerns about their potential (Fuss et al., 2018), feasibility (Nemet et to net zero CO2 emissions until mid-century. The 1.5°C pathways with al., 2018) and/or sustainability (Smith et al., 2015; Fuss et al., 2018) (see no or limited (<0.1°C) overshoot that were reported in the scenario Sections 2.3.4, 4.3.2 and 4.3.7 and Cross-Chapter Box 7 in Chapter 3 database project remaining FFI CO2 emissions of 610–1260 GtCO2 over for further discussion). CDR can have two very different functions in the period 2018–2100 (5th–95th percentile range; median: 880 GtCO2). 1.5°C-consistent pathways. If deployed in the first half of the century, Kriegler et al. (2018b) conducted a sensitivity analysis that explores the before net zero CO2 emissions are reached, it neutralizes some of the four central options for reducing fossil-fuel emissions: lowering energy remaining CO2 emissions year by year and thus slows the accumulation demand, electrifying energy services, decarbonizing the power sector of CO2 in the atmosphere. In this first function it can be used to remain and decarbonizing non-electric fuel use in energy end-use sectors. By within the carbon budget and avoid overshoot. If CDR is deployed in the exploring these options to their extremes, they found a lowest value second half of the century after carbon neutrality has been established, of 500 GtCO2 (2018–2100) gross fossil-fuel CO2 emissions for the it can still be used to neutralize some residual emissions from other hypothetical case of aligning the strongest assumptions for all four sectors, but also to create net negative emissions that actively draw mitigation options. The two lines of evidence and the fact that available down the cumulative amount of CO2 emissions to return below a 1.5°C pathways cover a wide range of assumptions (Section 2.3.1) 1.5°C warming level. In the second function, CDR enables temporary give a robust indication of a lower limit of about 500 GtCO2 remaining overshoot. The literature points to strong limitations to upscaling fossil-fuel and industry CO2 emissions in the 21st century. CDR (limiting its first abovementioned function) and to sustainability constraints (limiting both abovementioned functions) (Fuss et al., To compare these numbers with the remaining carbon budget, CO2 2018; Minx et al., 2018; Nemet et al., 2018). Large uncertainty hence emissions from agriculture, forestry and other land use (AFOLU) need exists about what amount of CDR could actually be available before to be taken into account. In many of the 1.5°C-consistent pathways, mid-century. Kriegler et al. (2018b) explore a case limiting CDR to AFOLU CO2 emissions reach zero at or before mid-century and then 100 GtCO2 until 2050, and the 1.5°C pathways with no or limited turn to negative values (Table 2.4). This means human changes to the overshoot available in the report’s database project 40–260 GtCO2 land lead to atmospheric carbon being stored in plants and soils. This CDR until the point of carbon neutrality (5th to 95th percentile; median needs to be distinguished from the natural CO2 uptake by land, which is 110 GtCO2). Because gross CO2 emissions in most cases exceed the not accounted for in the anthropogenic AFOLU CO2 emissions reported remaining carbon budget by several hundred GtCO2 and given the limits in the pathways. Given the difference in estimating the ‘anthropogenic’ to CDR deployment until 2050, most of the 1.5°C-consistent pathways sink between countries and the global integrated assessment and available to this assessment are overshoot pathways. However, the carbon modelling community (Grassi et al., 2017), the AFOLU CO2 scenario database also contains nine non-overshoot pathways that estimates included here are not necessarily directly comparable with remain below 1.5°C throughout the 21st century (Table 2.1). countries’ estimates at global level. The cumulated amount of AFOLU CO2 emissions until the time they reach zero combine with the fossil-fuel and industry CO2 emissions to give a total amount of gross emissions 114 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 2.3.3 Emissions Evolution in 1.5°C Pathways highlighting the more accelerated reductions in 1.5°C-consistent compared to 2°C-consistent pathways. This section assesses the salient temporal evolutions of climate forcers over the 21st century. It uses the classification of 1.5°C pathways Appropriate emissions benchmark values also depend on the presented in Section 2.1, which includes a Below-1.5°C class, as well acceptable or desired portfolio of mitigation measures, representing as other classes with varying levels of projected overshoot (1.5°C-low- clearly identified trade-offs and choices (Sections 2.3.4, 2.4, and 2.5.3) OS and 1.5°C-high-OS). First, aggregate-GHG benchmarks for 2030 (Luderer et al., 2013; Rogelj et al., 2013a; Clarke et al., 2014; Krey et al., are assessed. Subsequent sections assess long-lived climate forcers 2014a; Strefler et al., 2018b). For example, lower 2030 GHG emissions (LLCF) and short-lived climate forcers (SLCF) separately because they correlate with a lower dependence on the future availability and contribute in different ways to near-term, peak and long-term warming desirability of CDR (Strefler et al., 2018b). On the other hand, pathways (Section 2.2, Cross-Chapter Box 2 in Chapter 1). that assume or anticipate only limited deployment of CDR during the 21st century imply lower emissions benchmarks over the coming Estimates of aggregated GHG emissions in line with specific policy decades, which are achieved in models through further reducing choices are often compared to near-term benchmark values from CO2 emissions in the coming decades. The pathway archetypes mitigation pathways to explore their consistency with long-term used in the chapter illustrate this further (Figure 2.6). Under middle- 2 climate goals (Clarke et al., 2014; UNEP, 2016, 2017; UNFCCC, 2016). of-the-road assumptions of technological and socioeconomic Benchmark emissions or estimates of peak years derived from IAMs development, pathway S2 suggests emission benchmarks of 34, 12 provide guidelines or milestones that are consistent with achieving a and −8 GtCO2e yr −1 in the years 2030, 2050, and 2100, respectively. given temperature level. While they do not set mitigation requirements In contrast, a pathway that further limits overshoot and aims at in a strict sense, exceeding these levels in a given year almost invariably eliminating the reliance on negative emissions technologies like increases the mitigation challenges afterwards by increasing the rates BECCS as well as CCS (here labelled as the LED pathway) shows of change and increasing the reliance on speculative technologies, deeper emissions reductions in 2030 to limit the cumulative amount including the possibility that its implementation becomes unachievable of CO2 until net zero global CO2 emissions (carbon neutrality). The LED (see Cross-Chapter Box 3 in Chapter 1 for a discussion of feasibility pathway here suggests emission benchmarks of 25, 9 and 2 GtCO2e yr −1 concepts) (Luderer et al., 2013; Rogelj et al., 2013b; Clarke et al., 2014; in the years 2030, 2050, and 2100, respectively. However, a pathway Fawcett et al., 2015; Riahi et al., 2015; Kriegler et al., 2018a). These that allows and plans for the successful large-scale deployment of trade-offs are particularly pronounced in 1.5°C pathways and are BECCS by and beyond 2050 (S5) shows a shift in the opposite direction. discussed in Section 2.3.5. This section assesses Kyoto-GHG emissions The variation within and between the abovementioned ranges of in 2030 expressed in CO2 equivalent (CO2e) emissions using 100-year 2030 GHG benchmarks hence depends strongly on societal choices global warming potentials.3 and preferences related to the acceptability and availability of certain technologies. Appropriate benchmark values of aggregated GHG emissions depend on a variety of factors. First and foremost, they are determined by the Overall these variations do not strongly affect estimates of the desired likelihood to keep warming below 1.5°C and the extent to which 1.5°C-consistent timing of global peaking of GHG emissions. Both projected temporary overshoot is to be avoided (Sections 2.2, 2.3.2, Below-1.5°C and 1.5°C-low-OS pathways show minimum–maximum and 2.3.5). For instance, median aggregated 2030 GHG emissions are ranges in 2030 that do not overlap with 2020 ranges, indicating the about 10 GtCO2e yr −1 lower in 1.5°C-low-OS compared to 1.5°C-high- global GHG emissions peaked before 2030 in these pathways. Also, OS pathways, with respective interquartile ranges of 26–31 and 36–49 2020 and 2030 GHG emissions in 1.5°C-high-OS pathways only GtCO2e yr −1 (Table 2.4). These ranges correspond to about 25–30 and overlap outside their interquartile ranges. 35–48 GtCO −12e yr in 2030, respectively, when aggregated with 100- year Global Warming Potentials from the IPCC Second Assessment Kyoto-GHG emission reductions are achieved by reductions in CO2 Report. The limited evidence available for pathways aiming to limit and non-CO2 GHGs. The AR5 identified two primary factors that warming below 1.5°C without overshoot or with limited amounts of influence the depth and timing of reductions in non-CO2 Kyoto-GHG CDR (Grubler et al., 2018; Holz et al., 2018b; van Vuuren et al., 2018) emissions: (i) the abatement potential and costs of reducing the indicates that under these conditions consistent emissions in 2030 emissions of these gases and (ii) the strategies that allow making would fall at the lower end and below the above mentioned ranges. trade-offs between them (Clarke et al., 2014). Many studies indicate Due to the small number of 1.5°C pathways with no overshoot in the low-cost, near-term mitigation options in some sectors for non-CO2 report’s database (Table 2.4) and the potential for a downward bias in gases compared to supply-side measures for CO2 mitigation (Clarke et the selection of underlying scenario assumptions, the headline range al., 2014). A large share of this potential is hence already exploited in for 1.5°C pathways with no or limited overshoot is also assessed to mitigation pathways in line with 2°C. At the same time, by mid-century be of the order of 25–30 GtCO2e yr −1. Ranges for the 1.5°C-low-OS and beyond, estimates of further reductions of non-CO2 Kyoto-GHGs – and Lower-2°C classes only overlap outside their interquartile ranges, in particular CH4 and N2O – are hampered by the absence of mitigation 3 In this chapter GWP-100 values from the IPCC Fourth Assessement Report are used because emissions of fluorinated gases in the integrated pathways have been reported in this metric to the database. At a global scale, switching between GWP-100 values of the Second, Fourth or Fifth IPCC Assessment Reports could result in variations in aggregated Kyoto-GHG emissions of about ±5% in 2030 (UNFCCC, 2016). 115 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development options in the current generation of IAMs, which are hence not able very different implication for sustainable development (Section 2.5.3). to reduce residual emissions of sources linked to livestock production and fertilizer use (Clarke et al., 2014; Gernaat et al., 2015) (Sections All 1.5°C pathways see global CO2 emissions embark on a steady 2.3.1.2, 2.4.4, Supplementary Material 2.SM.1.2). Therefore, while net decline to reach (near) net zero levels around 2050, with 1.5°C-low- CO2 emissions are projected to be markedly lower in 1.5°C-consistent OS pathways reaching net zero CO2 emissions around 2045–2055 compared to 2°C-consistent pathways, this is much less the case for (Table 2.4; Figure 2.5). Near-term differences between the various methane (CH4) and nitrous-oxide (N2O) (Figures 2.6–2.7). This results pathway classes are apparent, however. For instance, Below-1.5°C and in reductions of CO2 being projected to take up the largest share of 1.5°C-low-OS pathways show a clear shift towards lower CO2 emissions emissions reductions when moving between 1.5°C-consistent and in 2030 relative to other 1.5°C and 2°C pathway classes, although in all 2°C-consistent pathways (Rogelj et al., 2015b, 2018; Luderer et al., 1.5°C classes reductions are clear (Figure 2.6). These lower near-term 2018). If additional non-CO2 mitigation measures are identified and emissions levels are a direct consequence of the former two pathway adequately included in IAMs, they are expected to further contribute to classes limiting cumulative CO2 emissions until carbon neutrality in mitigation efforts by lowering the floor of residual non-CO2 emissions. order to aim for a higher probability of limiting peak warming to 1.5°C However, the magnitude of these potential contributions has not been (Section 2.2.2 and 2.3.2.2). In some cases, 1.5°C-low-OS pathways 2 assessed as part of this report. achieve net zero CO2 emissions one or two decades later, contingent on 2030 CO2 emissions in the lower quartile of the literature range, that As a result of the interplay between residual CO2 and non-CO −1 2 emissions is, below about 18 GtCO2 yr . Median year-2030 global CO2 emissions and CDR, global GHG emissions reach net zero levels at different times are of the order of 5–10 GtCO2 yr −1 lower in Below-1.5°C compared in different 1.5°C-consistent pathways. Interquartile ranges of the to 1.5°C-low-OS pathways, which are in turn lower than 1.5°C-high- years in which 1.5°C-low-OS and 1.5°C-high-OS reach net zero GHG OS pathways (Table 2.4). Below-1.5°C and 1.5°C-low-OS pathways emissions range from 2060 to 2080 (Table 2.4). A seesaw characteristic combined show a decline in global net anthropogenic CO2 emissions can be found between near-term emissions reductions and the timing of about 45% from 2010 levels by 2030 (40–60% interquartile range). of net zero GHG emissions. This is because pathways with limited Lower-2°C pathways show CO2 emissions declining by about 25% by emissions reductions in the next one to two decades require net 2030 in most pathways (10–30% interquartile range). The 1.5°C-high- negative CO2 emissions later on (see earlier). Most 1.5°C-high-OS OS pathways show emissions levels that are broadly similar to the pathways lead to net zero GHG emissions in approximately the third 2°C-consistent pathways in 2030. quarter of this century, because all of them rely on significant amounts of annual net negative CO2 emissions in the second half of the The development of CO2 emissions in the second half of the century in century to decline temperatures after overshoot (Table 2.4). However, 1.5°C pathways is characterized by the need to stay or return within in pathways that aim at limiting overshoot as much as possible or a carbon budget. Figure 2.6 shows net CO2 and N2O emissions from more slowly decline temperatures after their peak, emissions reach various sources in 2050 and 2100 in 1.5°C pathways in the literature. the point of net zero GHG emissions slightly later or at times never. Virtually all 1.5°C pathways obtain net negative CO2 emissions at some Early emissions reductions in this case reduce the requirement for net point during the 21st century, but the extent to which net negative negative CO2 emissions. Estimates of 2030 GHG emissions in line with emissions are relied upon varies substantially (Figure 2.6, Table 2.4). the current NDCs overlap with the highest quartile of 1.5°C-high-OS This net withdrawal of CO2 from the atmosphere compensates for pathways (Cross-Chapter Box 9 in Chapter 4). residual long-lived non-CO2 GHG emissions that also accumulate in the atmosphere (like N2O) or cancels some of the build-up of CO2 due 2.3.3.1 Emissions of long-lived climate forcers to earlier emissions to achieve increasingly higher likelihoods that warming stays or returns below 1.5°C (see Section 2.3.4 for a discussion Climate effects of long-lived climate forcers (LLCFs) are dominated by of various uses of CDR). Even non-overshoot pathways that aim at CO2, with smaller contributions of N2O and some fluorinated gases achieving temperature stabilization would hence deploy a certain (Myhre et al., 2013; Blanco et al., 2014). Overall net CO2 emissions amount of net negative CO2 emissions to offset any accumulating in pathways are the result of a combination of various anthropogenic long-lived non-CO2 GHGs. The 1.5°C overshoot pathways display contributions (Figure 2.5) (Clarke et al., 2014): (i) CO2 produced by fossil- significantly larger amounts of annual net negative CO2 emissions in fuel combustion and industrial processes, (ii) CO2 emissions or removals the second half of the century. The larger the overshoot the more net from the agriculture, forestry and other land use (AFOLU) sector, (iii) negative CO2 emissions are required to return temperatures to 1.5°C CO2 capture and sequestration (CCS) from fossil fuels or industrial by the end of the century (Table 2.4, Figure 2.1). activities before it is released to the atmosphere, (iv) CO2 removal by technological means, which in current pathways is mainly achieved N2O emissions decline to a much lesser extent than CO2 in currently by BECCS and AFOLU-related CDR, although other options could available 1.5°C pathways (Figure 2.6). Current IAMs have limited be conceivable (see Chapter 4, Section 4.3.7). Pathways apply these emissions-reduction potentials (Gernaat et al., 2015) (Sections 2.3.1.2, four contributions in different configurations (Figure 2.5) depending 2.4.4, Supplementary Material 2.SM.1.2), reflecting the difficulty of on societal choices and preferences related to the acceptability and eliminating N2O emission from agriculture (Bodirsky et al., 2014). availability of certain technologies, the timing and stringency of near- Moreover, the reliance of some pathways on significant amounts of term climate policy, and the ability to limit the demand that drives bioenergy after mid-century (Section 2.4.2) coupled to a substantial baseline emissions (Marangoni et al., 2017; Riahi et al., 2017; Grubler use of nitrogen fertilizer (Popp et al., 2017) also makes reducing N2O et al., 2018; Rogelj et al., 2018; van Vuuren et al., 2018), and come with emissions harder (for example, see pathway S5 in Figure 2.6). As 116 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 2 Figure 2.6 | Annual global emissions characteristics for 2020, 2030, 2050, 2100. Data are shown for (a) Kyoto-GHG emissions, and (b) global total CO2 emissions, (c) CO2 emissions from the agriculture, forestry and other land use (AFOLU) sector, (d) global N2O emissions, and (e) CO2 emissions from fossil fuel use and industrial processes. The latter is also split into (f) emissions from the energy supply sector (electricity sector and refineries) and (g) direct emissions from fossil-fuel use in energy demand sectors (industry, buildings, transport) (bottom row). Horizontal black lines show the median, boxes show the interquartile range, and whiskers the minimum–maximum range. Icons indicate the four pathway archetypes used in this chapter. In case less than seven data points are available in a class, the minimum–maximum range and single data points are shown. Kyoto-GHG, emissions in the top panel are aggregated with AR4 GWP-100 and contain CO2, CH4, N2O, HFCs, PFCs, and SF6. NF3 is typically not reported by IAMs. Scenarios with year-2010 Kyoto-GHG emissions outside the range assessed by IPCC AR5 WGIII assessed are excluded (IPCC, 2014b). 117 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development a result, sizeable residual N2O emissions are currently projected to 80% being suggested (Stohl et al., 2015; Klimont et al., 2017). Because continue throughout the century, and measures to effectively mitigate the dominant sources of certain aerosol mixtures are emitted during them will be of continued relevance for 1.5°C societies. Finally, the the combustion of fossil fuels, the rapid phase-out of unabated fossil reduction of nitrogen use and N2O emissions from agriculture is already fuels to avoid CO2 emissions would also result in removal of these a present-day concern due to unsustainable levels of nitrogen pollution either warming or cooling SLCF air-pollutant species. Furthermore, (Bodirsky et al., 2012). Section 2.4.4 provides a further assessment of SLCFs are also reduced by efforts to reduce particulate air pollution. the agricultural non-CO2 emissions reduction potential. For example, year-2050 SO2 emissions (precursors of sulphate aerosol) in 1.5°C-consistent pathways are about 75–85% lower than their 2010 2.3.3.2 Emissions of short-lived climate forcers and levels. Some caveats apply, for example, if residential biomass use fluorinated gases would be encouraged in industrialised countries in stringent mitigation pathways without appropriate pollution control measures, aerosol SLCFs include shorter-lived GHGs like CH4 and some fluorinated gases concentrations could also increase (Sand et al., 2015; Stohl et al., 2015). as well as particles (aerosols), their precursors and ozone precursors. SLCFs are strongly mitigated in 1.5°C pathways, as is the case for Emissions of fluorinated gases (IPCC/TEAP, 2005; US EPA, 2013; Velders 2 2°C pathways (Figure 2.7). SLCF emissions ranges of 1.5°C and 2°C et al., 2015; Purohit and Höglund-Isaksson, 2017) in 1.5°C-consistent pathway classes strongly overlap, indicating that the main incremental pathways are reduced by roughly 75–80% relative to 2010 levels mitigation contribution between 1.5°C and 2°C pathways comes from (interquartile range across 1.5°C-consistent pathways) in 2050, CO2 (Luderer et al., 2018; Rogelj et al., 2018). CO2 and SLCF emissions with no clear differences between the classes. Although unabated reductions are connected in situations where SLCF and CO2 are hydrofluorocarbon (HFC) emissions have been projected to increase co-emitted by the same process, for example, with coal-fired power (Velders et al., 2015), the Kigali Amendment recently added HFCs to plants (Shindell and Faluvegi, 2010) or within the transport sector the basket of gases controlled under the Montreal Protocol (Höglund- (Fuglestvedt et al., 2010). Many CO2-targeted mitigation measures Isaksson et al., 2017). As part of the larger group of fluorinated in industry, transport and agriculture (Sections 2.4.3–4) hence also gases, HFCs are also assumed to decline in 1.5°C-consistent reduce non-CO2 forcing (Rogelj et al., 2014b; Shindell et al., 2016). pathways. Projected reductions by 2050 of fluorinated gases under 1.5°C-consistent pathways are deeper than published estimates of Despite the fact that methane has a strong warming effect (Myhre what a full implementation of the Montreal Protocol including its et al., 2013; Etminan et al., 2016), current 1.5°C-consistent pathways Kigali Amendment would achieve (Höglund-Isaksson et al., 2017), still project significant emissions of CH4 by 2050, indicating only a which project roughly a halving of fluorinated gas emissions in 2050 limited CH4 mitigation potential in IAM analyses (Gernaat et al., 2015) compared to 2010. Assuming the application of technologies that (Sections 2.3.1.2, 2.4.4, Table 2.SM.2). The AFOLU sector contributes an are currently commercially available and at least to a limited extent important share of the residual CH4 emissions until mid-century, with already tested and implemented, potential fluorinated gas emissions its relative share increasing from slightly below 50% in 2010 to around reductions of more than 90% have been estimated (Höglund-Isaksson 55–70% in 2030, and 60–80% in 2050 in 1.5°C-consistent pathways et al., 2017). (interquartile range across 1.5°C-consistent pathways for projections). Many of the proposed measures to target CH4 (Shindell et al., 2012; There is a general agreement across 1.5°C-consistent pathways that Stohl et al., 2015) are included in 1.5°C-consistent pathways (Figure until 2030 forcing from the warming SLCFs is reduced less strongly 2.7), though not all (Sections 2.3.1.2, 2.4.4, Table 2.SM.2). A detailed than the net cooling forcing from aerosol effects, compared to 2010. assessment of measures to further reduce AFOLU CH4 emissions has As a result, the net forcing contributions from all SLCFs combined are not been conducted. projected to increase slightly by about 0.2–0.3 W m−2, compared to 2010. Also, by the end of the century, about 0.1–0.3 W m−2 of SLCF Overall reductions of SLCFs can have effects of either sign on forcing is generally currently projected to remain in 1.5°C-consistent temperature depending on the balance between cooling and warming scenarios (Figure 2.8). This is similar to developments in 2°C-consistent agents. The reduction in SO2 emissions is the dominant single effect as pathways (Rose et al., 2014b; Riahi et al., 2017), which show median it weakens the negative total aerosol forcing. This means that reducing forcing contributions from these forcing agents that are generally no all SLCF emissions to zero would result in a short-term warming, more than 0.1 W m−2 higher. Nevertheless, there can be additional gains although this warming is unlikely to be more than 0.5°C (Section 2.2 from targeted deeper reductions of CH4 emissions and tropospheric and Figure 1.5 (Samset et al., 2018)). Because of this effect, suggestions ozone precursors, with some scenarios projecting less than 0.1 W m−2 have been proposed that target the warming agents only (referred to forcing from SLCFs by 2100. as short-lived climate pollutants or SLCPs instead of the more general short-lived climate forcers; e.g., Shindell et al., 2012), though aerosols 2.3.4 CDR in 1.5°C Pathways are often emitted in varying mixtures of warming and cooling species (Bond et al., 2013). Black carbon (BC) emissions reach similar levels Deep mitigation pathways assessed in AR5 showed significant across 1.5°C-consistent and 2°C-consistent pathways available in the deployment of CDR, in particular through BECCS (Clarke et al., 2014). literature, with interquartile ranges of emissions reductions across This has led to increased debate about the necessity, feasibility and pathways of 16–34% and 48–58% in 2030 and 2050, respectively, desirability of large-scale CDR deployment, sometimes also called relative to 2010 (Figure 2.7). Recent studies have identified further ‘negative emissions technologies’ in the literature (Fuss et al., 2014; reduction potentials for the near term, with global reductions of about Anderson and Peters, 2016; Williamson, 2016; van Vuuren et al., 118 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 Table 2.4 | Emissions in 2030, 2050 and 2100 in 1.5°C and 2°C scenario classes and absolute annual rates of change between 2010–2030, 2020–2030 and 2030–2050, respectively. Values show median and interquartile range across available scenarios (25th and 75th percentile given in brackets). If fewer than seven scenarios are available (*), the minimum–maximum range is given instead. Kyoto-GHG emissions are aggregated with GWP-100 values from IPCC AR4. Emissions in 2010 for total net CO2, CO2 from fossil-fuel use and industry, and AFOLU CO2 are estimated at 38.5, 33.4, and 5 GtCO2 yr −1, respectively (Le Quéré et al., 2018). Percentage reduction numbers included in headline statement C.1 in the Summary for Policymakers are computed relative to 2010 emissions in each individual pathway, and hence differ slightly from a case where reductions are computed relative to the historical 2010 emissions reported above. A difference is reported in estimating the ‘anthropogenic’ sink by countries or the global carbon modelling community (Grassi et al., 2017), and AFOLU CO2 estimates reported here are thus not necessarily comparable with countries’ estimates. Scenarios with year-2010 Kyoto-GHG emissions outside the range assessed by IPCC AR5 WGIII are excluded (IPCC, 2014b), as are scenario duplicates that would bias ranges towards a single study. Annual emissions/sequestration Absolute Annual Change Timing of (GtCO yr-12 ) (GtCO –1 2/yr ) Global Zero Name Category # 2030 2050 2100 2010–2030 2020–2030 2030–2050 Year Total CO2 Below-1.5°C 5* 13.4 (15.4, 11.4) –3.0 (1.7, –10.6) –8.0 (–2.6, –14.2) –1.2 (–1.0, –1.3) –2.5 (–1.8, –2.8) –0.8 (–0.7, –1.2) 2044 (2037, 2054) (net) 1.5°C-low-OS 37 20.8 (22.2, 18.0) –0.4 (2.7, –2.0) –10.8 (–8.1, –14.3) –0.8 (–0.7, –1.0) –1.7 (–1.4, –2.3) –1.0 (–0.8, –1.2) 2050 (2047, 2055) 1.5°C with no 20.3 –10.2 2050 42 –0.5 (2.2, –2.8) –0.9 (–0.7, –1.1) –1.8 (–1.5, –2.3) –1.0 (–0.8, –1.2) 2 or limited OS (22.0, 15.9) (–7.6, –14.2) (2046, 2055) 1.5°C-high-OS 36 29.1 (36.4, 26.0) 1.0 (6.3, –1.2) –13.8 (–11.1, –16.4) –0.4 (0.0, –0.6) –1.1 (–0.5, –1.5) –1.3 (–1.1, –1.8) 2052 (2049, 2059) Lower-2°C 54 28.9 (33.7, 24.5) 9.9 (13.1, 6.5) –5.1 (–2.6, –10.3) –0.4 (–0.2, –0.6) –1.1 (–0.8, –1.6) –0.9 (–0.8, –1.2) 2070 (2063, 2079) 2085 Higher-2°C 54 33.5 (35.0, 31.0) 17.9 (19.1, 12.2) –3.3 (0.6, –11.5) –0.2 (–0.0, –0.4) –0.7 (–0.5, –0.9) –0.8 (–0.6, –1.0) (2070, post–2100) CO2 from Below-1.5°C 5* 18.0 (21.4, 13.8) 10.5 (20.9, 0.3) 8.3 (11.6, 0.1) –0.7 (–0.6, –1) –1.5 (–0.9, –2.2) –0.4 (0, –0.7) - fossil fuels 1.5°C-low-OS 37 22.1 (24.4, 18.7) 10.3 (14.1, 7.8) 5.6 (8.1, 2.6) –0.5 (–0.4, –0.6) –1.3 (–0.9, –1.7) –0.6 (–0.5, –0.7) - and industry (gross) 1.5°C with no 21.6 42 10.3 (13.8, 7.7) 6.1 (8.4, 2.6) –0.5 (–0.4, –0.7) –1.3 (–0.9, –1.8) –0.6 (–0.4, –0.7) - or limited OS (24.2, 18.0) 1.5°C-high-OS 36 27.8 (37.1, 25.6) 13.1 (17.0, 11.6) 6.6 (8.8, 2.8) –0.2 (0.2, –0.3) –0.8 (–0.2, –1.1) –0.7 (–0.6, –1.0) - Lower-2°C 54 27.7 (31.5, 23.5) 15.4 (19.0, 11.1) 7.2 (10.4, 3.7) –0.2 (–0.0, –0.4) –0.8 (–0.5, –1.2) –0.6 (–0.5, –0.8) - Higher-2°C 54 31.3 (33.4, 28.7) 19.2 (22.6, 17.1) 8.1 (10.9, 5.0) –0.1 (0.1, –0.2) –0.5 (–0.2, –0.7) –0.6 (–0.5, –0.7) - CO2 from Below-1.5°C 5* 16.4 (18.2, 13.5) 1.0 (7.0, 0) –2.7 (0, –9.8) –0.8 (–0.7, –1) –1.8 (–1.2, –2.2) –0.6 (–0.5, –0.9) - fossil fuels 1.5°C-low-OS 37 20.6 (22.2, 17.5) 3.2 (5.6, –0.6) –8.5 (–4.1, –11.6) –0.6 (–0.5, –0.7) –1.4 (–1.1, –1.8) –0.8 (–0.7, –1.1) - and industry (net) 1.5°C with no 20.1 –8.3 42 3.0 (5.6, 0.0) –0.6 (–0.5, –0.8) –1.4 (–1.1, –1.9) –0.8 (–0.7, –1.1) - or limited OS (22.1, 16.8) (–3.5, –10.8) 1.5°C-high-OS 36 26.9 (34.7, 25.3) 4.2 (10.0, 1.2) –10.7 (–6.9, –13.2) –0.3 (0.1, –0.3) –0.9 (–0.3, –1.2) –1.2 (–0.9, –1.5) - Lower-2°C 54 28.2 (31.0, 23.1) 11.8 (14.1, 6.2) –3.1 (–0.7, –6.4) –0.2 (–0.1, –0.4) –0.8 (–0.5, –1.2) –0.8 (–0.7, –1.0) - Higher-2°C 54 31.0 (33.0, 28.7) 17.0 (19.3, 13.1) –2.9 (3.3, –8.0) –0.1 (0.1, –0.2) –0.5 (–0.2, –0.7) –0.7 (–0.5, –1.0) - CO2 from Below-1.5°C 5* –2.2 (–0.3, –4.8) –4.4 (–1.2, –11.1) –4.4 (–2.6, –5.3) –0.3 (–0.2, –0.4) –0.5 (–0.4, –0.8) –0.1 (0, –0.4) - AFOLU 1.5°C-low-OS 37 –0.1 (0.8, –1.0) –2.3 (–0.6, –4.1) –2.4 (–1.2, –4.2) –0.2 (–0.2, –0.3) –0.4 (–0.3, –0.5) –0.1 (–0.1, –0.2) - 1.5°C with no 42 –0.1 (0.7, –1.3) –2.6 (–0.6, –4.5) –2.6 (–1.3, –4.2) –0.2 (–0.2, –0.3) –0.4 (–0.3, –0.5) –0.1 (–0.1, –0.2) - or limited OS 1.5°C-high-OS 36 1.2 (2.7, 0.1) –2.1 (–0.3, –5.4) –2.4 (–1.5, –5.0) –0.1 (–0.1, –0.3) –0.2 (–0.1, –0.5) –0.2 (–0.0, –0.3) - Lower-2°C 54 1.4 (2.8, 0.3) –1.4 (–0.5, –2.7) –2.4 (–1.3, –4.2) –0.2 (–0.1, –0.2) –0.3 (–0.2, –0.4) –0.1 (–0.1, –0.2) - Higher-2°C 54 1.5 (2.7, 0.8) –0.0 (1.9, –1.6) –1.3 (0.1, –3.9) –0.2 (–0.1, –0.2) –0.2 (–0.1, –0.4) –0.1 (–0.0, –0.1) - Bioenergy Below-1.5°C 5* 0.4 (1.1, 0) 3.4 (8.3, 0) 5.7 (13.4, 0) 0 (0.1, 0) 0 (0.1, 0) 0.2 (0.4, 0) - combined 1.5°C-low-OS 36 0.3 (1.1, 0.0) 4.6 (6.4, 3.8) 12.4 (15.6, 7.6) 0.0 (0.1, 0.0) 0.0 (0.1, 0.0) 0.2 (0.3, 0.2) - with carbon capture 1.5°C with no 41 0.4 (1.0, 0.0) 4.5 (6.3, 3.4) 12.4 (15.0, 6.4) 0.0 (0.1, 0.0) 0.0 (0.1, 0.0) 0.2 (0.3, 0.2) - and storage or limited OS (BECCS) 1.5°C-high-OS 36 0.1 (0.4, 0.0) 6.8 (9.5, 3.7) 14.9 (16.3, 12.1) 0.0 (0.0, 0.0) 0.0 (0.0, 0.0) 0.3 (0.4, 0.2) - Lower-2°C 54 0.1 (0.3, 0.0) 3.6 (4.6, 1.8) 9.5 (12.1, 6.9) 0.0 (0.0, 0.0) 0.0 (0.0, 0.0) 0.2 (0.2, 0.1) - Higher-2°C 10.8 - 47 0.1 (0.2, 0.0) 3.0 (4.9, 1.6) 0.0 (0.0, 0.0) 0.0 (0.0, 0.0) 0.1 (0.2, 0.1) (15.3, 8.2) [46] Kyoto Below-1.5°C 2066 5* 22.1 (22.8, 20.7) 2.7 (8.1, –3.5) –2.6 (2.7, –10.7) –1.4 (–1.3, –1.5) –2.9 (–2.1, –3.3) –0.9 (–0.7, –1.3) GHG (AR4) (2044, post–2100) [GtCO2e] 1.5°C-low-OS 31 27.9 (31.1, 26.0) 7.0 (9.9, 4.5) –3.8 (–2.1, –7.9) –1.1 (–0.9, –1.2) –2.3 (–1.8, –2.8) –1.1 (–0.9, –1.2) 2068 (2061, 2080) 1.5°C with no 36 27.4 (30.9, 24.7) 6.5 (9.6, 4.2) –3.7 (–1.8, –7.8) –1.1 (–1.0, –1.3) –2.4 (–1.9, –2.9) –1.1 (–0.9, –1.2) 2067 (2061, 2084) or limited OS 1.5°C-high-OS 32 40.4 (48.9, 36.3) 8.4 (12.3, 6.2) –8.5 (–5.7, –1.3 (–0.6, –1.8) –1.5 (–1.3, –2.1) 2063 (2058, 2067) –0.5 (–0.0, –0.7) –11.2) Lower-2°C post–2100 46 39.6 (45.1, 35.7) 18.3 (20.4, 15.2) 2.1 (4.2, –2.4) –0.5 (–0.1, –0.7) –1.5 (–0.9, –2.2) –1.1 (–0.9, –1.2) (2090 post–2100) Higher-2°C post–2100 42 45.3 (48.5, 39.3) 25.9 (27.9, 23.3) 5.2 (11.5, –4.8) –0.2 (–0.0, –0.6) –1.0 (–0.6, –1.2) –1.0 (–0.7, –1.2) (2085 post–2100) 119 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development 2 Figure 2.7 | Global characteristics of a selection of short-lived non-CO2 emissions until mid-century for five pathway classes used in this chapter. Data are shown for (a) methane (CH4), (b) fluorinated gases (F-gas), (c) black carbon (BC), and (d) sulphur dioxide (SO2) emissions. Boxes with different colours refer to different scenario classes. Icons on top the ranges show four illustrative pathway archetypes that apply different mitigation strategies for limiting warming to 1.5°C. Boxes show the interquartile range, horizontal black lines the median, and whiskers the minimum–maximum range. F-gases are expressed in units of CO2-equivalence computed with 100-year Global Warming Potentials reported in IPCC AR4. Figure 2.8 | Estimated aggregated effective radiative forcing of SLCFs for 1.5°C and 2°C pathway classes in 2010, 2020, 2030, 2050, and 2100, as estimated by the FAIR model (Smith et al., 2018). Aggregated short-lived climate forcer (SLCF) radiative forcing is estimated as the difference between total anthropogenic radiative forcing and the sum of CO2 and N2O radiative forcing over time, and is expressed relative to 1750. Symbols indicate the four pathways archetypes used in this chapter. Horizontal black lines indicate the median, boxes the interquartile range, and whiskers the minimum–maximum range per pathway class. Because very few pathways fall into the Below-1.5°C class, only the minimum–maximum is provided here. 120 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 2017a; Obersteiner et al., 2018). Most CDR technologies remain largely several of these measures are increasingly investigated and compared unproven to date and raise substantial concerns about adverse side- in the literature, but large uncertainties remain, in particular concerning effects on environmental and social sustainability (Smith et al., 2015; the feasibility and impact of large-scale deployment of CDR measures Dooley and Kartha, 2018). A set of key questions emerge: how strongly (The Royal Society, 2009; Smith et al., 2015; Psarras et al., 2017; Fuss do 1.5°C-consistent pathways rely on CDR deployment and what types et al., 2018) (see Chapter 4.3.7). There are also proposals to remove of CDR measures are deployed at which scale? How does this vary methane, nitrous oxide and halocarbons via photocatalysis from the across available 1.5°C-consistent pathways and on which factors does atmosphere (Boucher and Folberth, 2010; de Richter et al., 2017), but it depend? How does CDR deployment compare between 1.5°C- and a broader assessment of their effectiveness, cost and sustainability 2°C-consistent pathways and how does it compare with the findings impacts is lacking to date. at the time of the AR5? How does CDR deployment in 1.5°C-consistent pathways relate to questions about availability, policy implementation Only some of these approaches have so far been considered in IAMs and sustainable development implications that have been raised (see Section 2.3.1.2). The mitigation scenario literature up to AR5 about CDR technologies? The first three questions are assessed in this mostly included BECCS and, to a more limited extent, afforestation section with the goal to provide an overview and assessment of CDR and reforestation (Clarke et al., 2014). Since then, some 2°C- and deployment in the 1.5°C pathway literature. The fourth question is only 1.5°C-consistent pathways including additional CDR measures such 2 touched upon here and is addressed in greater depth in Chapter 4, as DACCS (Chen and Tavoni, 2013; Marcucci et al., 2017; Lehtilä and Section 4.3.7, which assesses the rapidly growing literature on costs, Koljonen, 2018; Strefler et al., 2018b) and soil carbon sequestration potentials, availability and sustainability implications of individual (Frank et al., 2017) have become available. Other, more speculative CDR measures (Minx et al., 2017, 2018; Fuss et al., 2018; Nemet approaches, in particular ocean-based CDR and removal of non-CO2 et al., 2018). In addition, Section 2.3.5 assesses the relationship gases, have not yet been taken up by the literature on mitigation between delayed mitigation action and increased CDR reliance. CDR pathways. See Supplementary Material 2.SM.1.2 for an overview on deployment is intricately linked to the land-use transformation in the coverage of CDR measures in models which contributed pathways 1.5°C-consistent pathways. This transformation is assessed in Section to this assessment. Chapter 4.3.7 assesses the potential, costs, and 2.4.4. Bioenergy and BECCS impacts on sustainable land management sustainability implications of the full range of CDR measures. are further assessed in Chapter 3, Section 3.6.2 and Cross-Chapter Box 7 in Chapter 3. Ultimately, a comprehensive assessment of the land Integrated assessment modelling has not yet explored land conservation, implication of land-based CDR measures will be provided in the IPCC restoration and management options to remove carbon dioxide from AR6 Special Report on Climate Change and Land (SRCCL). the atmosphere in sufficient depth, despite land management having a potentially considerable impact on the terrestrial carbon stock (Erb et 2.3.4.1 CDR technologies and deployment levels in 1.5°C al., 2018). Moreover, associated CDR measures have low technological pathways requirements, and come with potential environmental and social co-benefits (Griscom et al., 2017). Despite the evolving capabilities of A number of approaches to actively remove carbon-dioxide from IAMs in accounting for a wider range of CDR measures, 1.5°C-consistent the atmosphere are increasingly discussed in the literature (Minx pathways assessed here continue to predominantly rely on BECCS and et al., 2018) (see also Chapter 4, Section 4.3.7). Approaches under afforestation/reforestation (see Supplementary Material 2.SM.1.2). consideration include the enhancement of terrestrial and coastal However, IAMs with spatially explicit land-use modelling include a full carbon storage in plants and soils such as afforestation and accounting of land-use change emissions comprising carbon stored reforestation (Canadell and Raupach, 2008), soil carbon enhancement in the terrestrial biosphere and soils. Net CDR in the AFOLU sector, (Paustian et al., 2016; Frank et al., 2017; Zomer et al., 2017), and other including but not restricted to afforestation and reforestation, can thus conservation, restoration, and management options for natural and in principle be inferred by comparing AFOLU CO2 emissions between managed land (Griscom et al., 2017) and coastal ecosystems (McLeod a baseline scenario and a 1.5°C-consistent pathway from the same et al., 2011). Biochar sequestration (Woolf et al., 2010; Smith, 2016; model and study. However, baseline AFOLU CO2 emissions can not only Werner et al., 2018) provides an additional route for terrestrial carbon be reduced by CDR in the AFOLU sector but also by measures to reduce storage. Other approaches are concerned with storing atmospheric deforestation and preserve land carbon stocks. The pathway literature carbon dioxide in geological formations. They include the combination and pathway data available to this assessment do not yet allow of biomass use for energy production with carbon capture and storage separating the two contributions. As a conservative approximation, the (BECCS) (Obersteiner et al., 2001; Keith and Rhodes, 2002; Gough additional net negative AFOLU CO2 emissions below the baseline are and Upham, 2011) and direct air capture with storage (DACCS) using taken as a proxy for AFOLU CDR in this assessment. Because this does chemical solvents and sorbents (Zeman and Lackner, 2004; Keith et not include CDR that was deployed before reaching net zero AFOLU al., 2006; Socolow et al., 2011). Further approaches investigate the CO2 emissions, this approximation is a lower-bound for terrestrial CDR mineralization of atmospheric carbon dioxide (Mazzotti et al., 2005; in the AFOLU sector (including all mitigation-policy-related factors that Matter et al., 2016), including enhanced weathering of rocks (Schuiling lead to net negative AFOLU CO2 emissions). and Krijgsman, 2006; Hartmann et al., 2013; Strefler et al., 2018a). A fourth group of approaches is concerned with the sequestration The scale and type of CDR deployment in 1.5°C-consistent pathways of carbon dioxide in the oceans, for example by means of ocean varies widely (Figure 2.9 and 2.10). Overall CDR deployment over the alkalinization (Kheshgi, 1995; Rau, 2011; Ilyina et al., 2013; Lenton et 21st century is substantial in most of the pathways, and deployment al., 2018). The costs, CDR potential and environmental side effects of levels cover a wide range, on the order of 100–1000 Gt CO2 in 1.5°C 121 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development pathways with no or limited overshoot (730 [260–1030] GtCO2, for food consumption freeing up sufficient land areas for afforestation median and 5th–95th percentile range). Both BECCS (480 [0–1000] and reforestation (Haberl et al., 2011; van Vuuren et al., 2018). Some GtCO2 in 1.5°C pathways with no or limited overshoot) and AFOLU pathways use neither BECCS nor afforestation but still rely on CDR CDR measures including afforestation and reforestation (210 [10- through considerable net negative CO2 emissions in the AFOLU sector 540] GtCO2 in 1.5°C pathways with no or limited overshoot) can play around mid-century (Holz et al., 2018b). We conclude that the role of a major role,4 but for both cases pathways exist where they play no BECCS as a dominant CDR measure in deep mitigation pathways has role at all. This shows the flexibility in substituting between individual been reduced since the time of the AR5. This is related to three factors: CDR measures, once a portfolio of options becomes available. The high a larger variation of underlying assumptions about socio-economic end of the CDR deployment range is populated by high overshoot drivers (Riahi et al., 2017; Rogelj et al., 2018) and associated energy pathways, as illustrated by pathway archetype S5 based on SSP5 (Grubler et al., 2018) and food demand (van Vuuren et al., 2018); (fossil-fuelled development, see Section 2.3.1.1) and characterized the incorporation of a larger portfolio of mitigation and CDR options by very large BECCS deployment to return warming to 1.5°C by 2100 (Marcucci et al., 2017; Grubler et al., 2018; Lehtilä and Koljonen, (Kriegler et al., 2017). In contrast, the low end is populated by a few 2018; Liu et al., 2018; van Vuuren et al., 2018); and targeted analysis pathways with no or limited overshoot that limit CDR to on the order of of deployment limits for (specific) CDR measures (Holz et al., 2018b; 2 100–200 GtCO2 over the 21st century, coming entirely from terrestrial Kriegler et al., 2018a; Strefler et al., 2018b), including the availability CDR measures with no or small use of BECCS. These are pathways of bioenergy (Bauer et al., 2018), CCS (Krey et al., 2014a; Grubler et with very low energy demand facilitating the rapid phase-out of al., 2018) and afforestation (Popp et al., 2014b, 2017). As additional fossil fuels and process emissions that exclude BECCS and CCS use CDR measures are being built into IAMs, the prevalence of BECCS is (Grubler et al., 2018) and/or pathways with rapid shifts to sustainable expected to be further reduced. Figure 2.9 | Cumulative CDR deployment in 1.5°C-consistent pathways in the literature as reported in the database collected for this assessment until 2050 (panel a) and until 2100 (panel b). Total CDR comprises all forms of CDR, including AFOLU CDR and BECCS, and, in a few pathways, other CDR measures like DACCS. It does not include CCS combined with fossil fuels (which is not a CDR technology as it does not result in active removal of CO2 from the atmosphere). AFOLU CDR has not been reported directly and is hence represented by means of a proxy: the additional amount of net negative CO2 emissions in the AFOLU sector compared to a baseline scenario (see text for a discussion). ‘Compensatory CO2’ depicts the cumulative amount of CDR that is used to neutralize concurrent residual CO2 emissions. ‘Net negative CO2’ describes the additional amount of CDR that is used to produce net negative CO2 emissions, once residual CO2 emissions are neutralized. The two quantities add up to total CDR for individual pathways (not for percentiles and medians, see Footnote 4). As discussed in Section 2.3.2, CDR can be used in two ways in carbon budget, and because many pathways in the literature do not mitigation pathways: (i) to move more rapidly towards the point of restrict exceeding this budget prior to 2100, the relative weight of carbon neutrality and maintain it afterwards in order to stabilize global the net negative emissions component of CDR increases compared to mean temperature rise, and (ii) to produce net negative CO2 emissions, 2°C-consistent pathways. The amount of compensatory CDR remains drawing down anthropogenic CO2 in the atmosphere in order to decline roughly the same over the century. This is the net effect of stronger global mean temperature after an overshoot peak (Kriegler et al., 2018b; deployment of compensatory CDR until mid-century to accelerate Obersteiner et al., 2018). Both uses are important in 1.5°C-consistent the approach to carbon neutrality and less compensatory CDR in the pathways (Figure 2.9 and 2.10). Because of the tighter remaining 1.5°C second half of the century due to deeper mitigation of end-use sectors 4 The median and percentiles of the sum of two quantities is in general not equal to the sum of the medians and percentiles, respectively, of the two quantitites. 122 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 Legend All amounts over 2018-2100 period Total amount of CO2 produced by the economy CDR compensating Amount not emitted residual CO2 due to Fossil CCS emissions Gross CO2 emissions: total amount of CO2 emissions BECCS Maximum (peak) CO2 emissions being vented into the atmosphere peak amount emitted into the atmosphere during the 21st century after subtracting AFOLU CDR CDR (relates to peak warming) Net CO2 emissions: net negative CO amount that remains emitted 2 over the 2018-2100 period after subtracting CDR (relates to year-2100 warming) 1500 2 1000 500 0 Pathway class: S1 S2 S5 LED Median warming: 1.5°C-low-OS 1.5°C-low-OS 1.5°C-high-OS 1.5°C-low-OS estimated by MAGICC peak : 1.5°C peak : 1.6°C peak : 1.8°C peak : 1.5°C (AR5 setup) year-2100 : 1.3°C year-2100 : 1.3°C year-2100 : 1.3°C year-2100 : 1.4°C Figure 2.10 | Accounting of cumulative CO2 emissions for the four 1.5°C-consistent pathway archetypes. See top panel for explanation of the bar plots. Total CDR is the difference between gross (red horizontal bar) and net (purple horizontal bar) cumulative CO2 emissions over the period 2018–2100, and it is equal to the sum of the BECCS (grey) and AFOLU CDR (green) contributions. Cumulative net negative emissions are the difference between peak (orange horizontal bar) and net (purple) cumulative CO2 emissions. The blue shaded area depicts the estimated range of the remaining carbon budget for a two-in-three to one-in-two chance of staying below1.5°C. The grey shaded area depicts the range when accounting for additional Earth system feedbacks. in 1.5°C-consistent pathways (Luderer et al., 2018). Comparing median 1–11, and 1–5 GtCO −12 yr (see above for the definition of the ranges) levels, end-of-century net cumulative CO2 emissions are roughly in 2030, 2050, and 2100, respectively. In contrast to BECCS, AFOLU 600 GtCO2 smaller in 1.5°C compared to 2°C-consistent pathways, CDR is more strongly deployed in non-overshoot than overshoot with approximately two thirds coming from further reductions of gross pathways. This indicates differences in the timing of the two CDR CO2 emissions and the remaining third from increased CDR deployment. approaches. Afforestation is scaled up until around mid-century, when As a result, median levels of total CDR deployment in 1.5°C-consistent the time of carbon neutrality is reached in 1.5°C-consistent pathways, pathways are larger than in 2°C-consistent pathways (Figure 2.9), but while BECCS is projected to be used predominantly in the 2nd half with marked variations in each pathway class. of the century (Figure 2.5). This reflects the fact that afforestation is a readily available CDR technology, while BECCS is more costly and Ramp-up rates of individual CDR measures in 1.5°C-consistent much less mature a technology. As a result, the two options contribute pathways are provided in Table 2.4. BECCS deployment is still differently to compensating concurrent CO2 emissions (until 2050) limited in 2030, but ramps up to median levels of 3 (Below-1.5°C), and to producing net negative CO2 emissions (post-2050). BECCS 5 (1.5°C-low-OS) and 7 GtCO yr−12 (1.5°C-high-OS) in 2050, and to 6 deployment is particularly strong in pathways with high overshoots (Below-1.5°C), 12 (1.5°C-low-OS) and 15 GtCO2 yr −1 (1.5°C-high-OS) but can also feature in pathways with low overshoot (see Figure 2.5 in 2100, respectively. In 1.5°C pathways with no or limited overshoot, and 2.10). Annual deployment levels until mid-century are not found this amounts to 0–1, 0–8, and 0–16 GtCO yr−12 in 2030, 2050, and to be significantly different between 2°C-consistent pathways and 2100, respectively (ranges refer to the union of the min-max range 1.5°C-consistent pathways with no or low overshoot. This suggests of the Below-1.5°C and the interquartile range of the 1.5°C-low-OS similar implementation challenges for ramping up BECCS deployment class; see Table 2.4). Net CDR in the AFOLU sector reaches slightly at the rates projected in the pathways (Honegger and Reiner, 2018; lower levels in 2050, and stays more constant until 2100. In 1.5°C Nemet et al., 2018). The feasibility and sustainability of upscaling CDR pathways with no or limited overshoot, AFOLU CDR amounts to 0–5, at these rates is assessed in Chapter 4.3.7. 123 Cumulated CO2 2018−2100 (GtCO2) Remaining 1.5°C carbon budget Remaining 1.5°C carbon budget accounting for addtional from 2018 onwards Earth-system feedbacks range: TCRE 50% and TCRE67% Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Concerns have been raised that building expectations about large- availability. Using GHG benchmarks in climate policy makes implicit scale CDR deployment in the future can lead to an actual reduction assumptions about CDR availability (Fuss et al., 2014; van Vuuren of near-term mitigation efforts (Geden, 2015; Anderson and Peters, et al., 2017a). At the same time, the literature also shows that rapid 2016; Dooley and Kartha, 2018). The pathway literature confirms that and stringent mitigation as well as large-scale CDR deployment occur CDR availability influences the shape of mitigation pathways critically simultaneously in 1.5°C pathways due to the tight remaining carbon (Krey et al., 2014a; Holz et al., 2018b; Kriegler et al., 2018a; Strefler budget (Luderer et al., 2018). Thus, an emissions gap is identified even et al., 2018b). Deeper near-term emissions reductions are required to for high CDR availability (Strefler et al., 2018b), contradicting a wait- reach the 1.5°C–2°C target range if CDR availability is constrained. As and-see approach. There are significant trade-offs between near-term a result, the least-cost benchmark pathways to derive GHG emissions action, overshoot and reliance on CDR deployment in the long-term gap estimates (UNEP, 2017) are dependent on assumptions about CDR which are assessed in Section 2.3.5. Box 2.1 | Bioenergy and BECCS Deployment in Integrated Assessment Modelling 2 Bioenergy can be used in various parts of the energy sector of IAMs, including for electricity, liquid fuel, biogas, and hydrogen production. It is this flexibility that makes bioenergy and bioenergy technologies valuable for the decarbonization of energy use (Klein et al., 2014; Krey et al., 2014a; Rose et al., 2014a; Bauer et al., 2017, 2018). Most bioenergy technologies in IAMs are also available in combination with CCS (BECCS). Assumed capture rates differ between technologies, for example, about 90% for electricity and hydrogen production and about 40–50% for liquid fuel production. Decisions about bioenergy deployment in IAMs are based on economic considerations to stay within a carbon budget that is consistent with a long-term climate goal. IAMs consider both the value of bioenergy in the energy system and the value of BECCS in removing CO2 from the atmosphere. Typically, if bioenergy is strongly limited, BECCS technologies with high capture rates are favoured. If bioenergy is plentiful IAMs tend to choose biofuel technologies with lower capture rates but high value for replacing fossil fuels in transport (Kriegler et al., 2013a; Bauer et al., 2018). Most bioenergy use in IAMs is combined with CCS if available (Rose et al., 2014a). If CCS is unavailable, bioenergy use remains largely unchanged or even increases due to the high value of bioenergy for the energy transformation (Bauer et al., 2018). As land impacts are tied to bioenergy use, the exclusion of BECCS from the mitigation portfolio will not automatically remove the trade-offs with food, water and other sustainability objectives due to the continued and potentially increased use of bioenergy. IAMs assume bioenergy to be supplied mostly from second generation biomass feedstocks such as dedicated cellulosic crops (for example Miscanthus or poplar) as well as agricultural and forest residues. Detailed process IAMs include land-use models that capture competition for land for different uses (food, feed, fiber, bioenergy, carbon storage, biodiversity protection) under a range of dynamic factors including socio-economic drivers, productivity increases in crop and livestock systems, food demand, and land, environmental, biodiversity, and carbon policies. Assumptions about these factors can vary widely between different scenarios (Calvin et al., 2014; Popp et al., 2017; van Vuuren et al., 2018). IAMs capture a number of potential environmental impacts from bioenergy production, in particular indirect land-use change emissions from land conversion and nitrogen and water use for bioenergy production (Kraxner et al., 2013; Bodirsky et al., 2014; Bonsch et al., 2014; Obersteiner et al., 2016; Humpenöder et al., 2018). The impact of bioenergy production on soil degradation is an area of active IAM development and was not comprehensively accounted for in the mitigation pathways assessed in this report (but is, for example, in Frank et al., 2017). Whether bioenergy has large adverse impacts on environmental and societal goals depends in large parts on the governance of land use (Haberl et al., 2013; Erb et al., 2016b; Obersteiner et al., 2016; Humpenöder et al., 2018). Here IAMs often make idealized assumptions about effective land management, such as full protection of the land carbon stock by conservation measures and a global carbon price, respectively, but variations on these assumptions have also been explored (Calvin et al., 2014; Popp et al., 2014a). 2.3.4.2 Sustainability implications of CDR deployment in 1.5°C environmental side effects of CDR deployment in 1.5°C-consistent pathways pathways is provided in this section. Chapter 4, Section 4.3.7 then contrasts CDR deployment in 1.5°C-consistent pathways with other Strong concerns about the sustainability implications of large-scale branches of literature on limitations of CDR. Integrated modelling aims CDR deployment in deep mitigation pathways have been raised in the to explore a range of developments compatible with specific climate literature (Williamson and Bodle, 2016; Boysen et al., 2017b; Dooley and goals and often does not include the full set of broader environmental Kartha, 2018; Heck et al., 2018), and a number of important knowledge and societal concerns beyond climate change. This has given rise to gaps have been identified (Fuss et al., 2016). An assessment of the the concept of sustainable development pathways (Cross-Chapter Box literature on implementation constraints and sustainable development 1 in Chapter 1) (van Vuuren et al., 2015), and there is an increasing implications of CDR measures is provided in Chapter 4, Section 4.3.7 and body of work to extend integrated modelling to cover a broader range the Cross-chapter Box 7 in Chapter 3. An initial discussion of potential of sustainable development goals (Section 2.6). However, only some 124 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 of the available 1.5°C-consistent pathways were developed within a allow unabated carbon storage on the same patch of land. If wood larger sustainable development context (Bertram et al., 2018; Grubler harvest and subsequent processing or burial are taken into account, et al., 2018; Rogelj et al., 2018; van Vuuren et al., 2018). As discussed this finding can change. There are also synergies between the various in Section 2.3.4.1, those pathways are characterized by low energy uses of land, which are not reflected in the depicted pathways. Trees and/or food demand effectively limiting fossil-fuel substitution and can grow on agricultural land (Zomer et al., 2016), and harvested alleviating land competition, respectively. They also include regulatory wood can be used with BECCS and pyrolysis systems (Werner et al., policies for deepening early action and ensuring environmental 2018). The pathways show a very substantial land demand for the two protection (Bertram et al., 2018). Overall sustainability implications of CDR measures combined, up to the magnitude of the current global 1.5°C-consistent pathways are assessed in Section 2.5.3 and Chapter cropland area. This is achieved in IAMs in particular by a conversion of 5, Section 5.4. pasture land freed by intensification of livestock production systems, pasture intensification and/or demand changes (Weindl et al., 2017), Individual CDR measures have different characteristics and therefore and to a more limited extent, cropland for food production, as well would carry different risks for their sustainable deployment at scale as expansion into natural land. However, pursuing such large-scale (Smith et al., 2015). Terrestrial CDR measures, BECCS and enhanced changes in land use would pose significant food supply, environmental weathering of rock powder distributed on agricultural lands require and governance challenges, concerning both land management and 2 land. Those land-based measures could have substantial impacts tenure (Unruh, 2011; Erb et al., 2012, 2016b; Haberl et al., 2013; on environmental services and ecosystems (Cross-Chapter Box 7 in Haberl, 2015; Buck, 2016), particularly if synergies between land Chapter 3) (Smith and Torn, 2013; Boysen et al., 2016; Heck et al., 2016; uses, the relevance of dietary changes for reducing land demand, and Krause et al., 2017). Measures like afforestation and bioenergy with co-benefits with other sustainable development objectives are not and without CCS that directly compete with other land uses could have fully recognized. A general discussion of the land-use transformation in significant impacts on agricultural and food systems (Creutzig et al., 1.5°C-consistent pathways is provided in Section 2.4.4. 2012, 2015; Calvin et al., 2014; Popp et al., 2014b, 2017; Kreidenweis et al., 2016; Boysen et al., 2017a; Frank et al., 2017; Stevanović et al., An important consideration for CDR which moves carbon from the 2017; Strapasson et al., 2017; Humpenöder et al., 2018). BECCS using atmosphere to the geological, oceanic or terrestrial carbon pools is the dedicated bioenergy crops could substantially increase agricultural permanence of carbon stored in these different pools (Matthews and water demand (Bonsch et al., 2014; Séférian et al., 2018) and nitrogen Caldeira, 2008; NRC, 2015; Fuss et al., 2016; Jones et al., 2016) (see fertilizer use (Bodirsky et al., 2014). DACCS and BECCS rely on CCS and also Chapter 4, Section 4.3.7 for a discussion). Terrestrial carbon can would require safe storage space in geological formations, including be returned to the atmosphere on decadal time scales by a variety of management of leakage risks (Pawar et al., 2015) and induced mechanisms, such as soil degradation, forest pest outbreaks and forest seismicity (Nicol et al., 2013). Some approaches like DACCS have high fires, and therefore requires careful consideration of policy frameworks energy demand (Socolow et al., 2011). Most of the CDR measures to manage carbon storage, for example, in forests (Gren and Aklilu, currently discussed could have significant impacts on either land, 2016). There are similar concerns about outgassing of CO2 from ocean energy, water, or nutrients if deployed at scale (Smith et al., 2015). storage (Herzog et al., 2003), unless it is transformed to a substance However, actual trade-offs depend on a multitude factors (Haberl et that does not easily exchange with the atmosphere, for example, ocean al., 2011; Erb et al., 2012; Humpenöder et al., 2018), including the alkalinity or buried marine biomass (Rau, 2011). Understanding of the modalities of CDR deployment (e.g., on marginal vs. productive land) assessment and management of the potential risk of CO2 release from (Bauer et al., 2018), socio-economic developments (Popp et al., 2017), geological storage of CO2 has improved since the IPCC Special Report dietary choices (Stehfest et al., 2009; Popp et al., 2010; van Sluisveld et on Carbon Dioxide Capture and Storage (IPCC, 2005) with experience al., 2016; Weindl et al., 2017; van Vuuren et al., 2018), yield increases, and the development of management practices in geological storage livestock productivity and other advances in agricultural technology projects, including risk management to prevent sustentative leakage (Havlik et al., 2013; Valin et al., 2013; Havlík et al., 2014; Weindl et al., (Pawar et al., 2015). Estimates of leakage risk have been updated to 2015; Erb et al., 2016b), land policies (Schmitz et al., 2012; Calvin et al., include scenarios of unregulated drilling and limited wellbore integrity 2014; Popp et al., 2014a), and governance of land use (Unruh, 2011; (Choi et al., 2013) and find that about 70% of stored CO2 would still Buck, 2016; Honegger and Reiner, 2018). be retained after 10,000 years in these circumstances (Alcalde et al., 2018). The literature on the potential environmental impacts from the Figure 2.11 shows the land requirements for BECCS and afforestation leakage of CO2 – and approaches to minimize these impacts should in the selected 1.5°C-consistent pathway archetypes, including the LED a leak occur – has also grown and is reviewed by Jones et al. (2015). (Grubler et al., 2018) and S1 pathways (Fujimori, 2017; Rogelj et al., To the extent that non-permanence of terrestrial and geological carbon 2018) following a sustainable development paradigm. As discussed, storage is driven by socio-economic and political factors, there are these land-use patterns are heavily influenced by assumptions about, parallels to questions of fossil-fuel reservoirs remaining in the ground among other things, future population levels, crop yields, livestock (Scott et al., 2015). production systems, and food and livestock demand, which all vary between the pathways (Popp et al., 2017) (Section 2.3.1.1). In pathways that allow for large-scale afforestation in addition to BECCS, land demand for afforestation can be larger than for BECCS (Humpenöder et al., 2014). This follows from the assumption in the modelled pathways that, unlike bioenergy crops, forests are not harvested to 125 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development 2 Figure 2.11 | Land-use changes in 2050 and 2100 in the illustrative 1.5°C-consistent pathway archetypes (Fricko et al., 2017; Fujimori, 2017; Kriegler et al., 2017; Grubler et al., 2018; Rogelj et al., 2018). Changes in land for food crops, energy crops, forest, pasture and other natural land are shown, compared to 2010. 2.3.5 Implications of Near-Term Action in 1.5°C Pathways is further supported by estimates of committed emissions due to fossil fuel-based infrastructure (Seto et al., 2016; Edenhofer et al., 2018). Less CO2 emission reductions in the near term would require steeper and deeper reductions in the longer term in order to meet specific All available 1.5°C pathways that explore consistent mitigation action warming targets afterwards (Riahi et al., 2015; Luderer et al., 2016a). from 2020 onwards peak global Kyoto-GHG emissions in the next This is a direct consequence of the quasi-linear relationship between decade and already decline Kyoto-GHG emissions to below 2010 levels the total cumulative amount of CO2 emitted into the atmosphere and by 2030. The near-term emissions development in these pathways global mean temperature rise (Matthews et al., 2009; Zickfeld et al., can be compared with estimated emissions in 2030 implied by the 2009; Collins et al., 2013; Knutti and Rogelj, 2015). Besides this clear Nationally Determined Contributions (NDCs) submitted by Parties geophysical trade-off over time, delaying GHG emissions reductions to the Paris Agreement (Figure 2.12). Altogether, the unconditional over the coming years also leads to economic and institutional lock-in (conditional) NDCs are assessed to result in global Kyoto-GHG into carbon-intensive infrastructure, that is, the continued investment emissions on the order of 52–58 (50–54) GtCO2e yr−1 in 2030 (e.g., in and use of carbon-intensive technologies that are difficult or costly den Elzen et al., 2016; Fujimori et al., 2016; UNFCCC, 2016; Rogelj et to phase-out once deployed (Unruh and Carrillo-Hermosilla, 2006; al., 2017; Rose et al., 2017b; Benveniste et al., 2018; Vrontisi et al., Jakob et al., 2014; Erickson et al., 2015; Steckel et al., 2015; Seto et al., 2018; see Cross-Chapter Box 11 in Chapter 4 for detailed assessment). 2016; Michaelowa et al., 2018). Studies show that to meet stringent In contrast, 1.5°C pathways with limited overshoot available to this climate targets despite near-term delays in emissions reductions, assessment show an interquartile range of about 26–31 (median 28) models prematurely retire carbon-intensive infrastructure, in particular GtCO e yr−1 in 203052 (Table 2.4, Section 2.3.3). Based on these ranges, coal without CCS (Bertram et al., 2015a; Johnson et al., 2015). The AR5 this report assesses the emissions gap for a two-in-three chance of reports that delaying mitigation action leads to substantially higher limiting warming to 1.5°C to be 26 (19–29) and 28 (22–33) GtCO2e rates of emissions reductions afterwards, a larger reliance on CDR (median and interquartile ranges) for conditional and unconditional technologies in the long term, and higher transitional and long-term NDCs, respectively (Cross-Chapter Box 11, applying GWP-100 values economic impacts (Clarke et al., 2014). The literature mainly focuses from the IPCC Second Assessment Report). on delayed action until 2030 in the context of meeting a 2°C goal (den Elzen et al., 2010; van Vuuren and Riahi, 2011; Kriegler et al., The later emissions peak and decline, the more CO2 will have 2013b; Luderer et al., 2013, 2016a; Rogelj et al., 2013b; Riahi et al., accumulated in the atmosphere. Peak cumulated CO2 emissions – 2015; OECD/IEA and IRENA, 2017). However, because of the smaller and consequently peak temperatures – increase with higher 2030 carbon budget consistent with limiting warming to 1.5°C and the emissions levels (Figure 2.12). Current NDCs (Cross-Chapter Box 11 in absence of a clearly declining long-term trend in global emissions Chapter 4) are estimated to lead to CO2 emissions of about 400–560 to date, these general insights apply equally, or even more so, to the GtCO2 from 2018 to 2030 (Rogelj et al., 2016a). Available 1.5°C- and more stringent mitigation context of 1.5°C-consistent pathways. This 2°C-consistent pathways with 2030 emissions in the range estimated 5 Note that aggregated Kyoto-GHG emissions implied by the NDCs from Cross-Chapter Box 11 in Chapter 4 and Kyoto-GHG ranges from the pathway classes in Chapter 2 are only approximately comparable, because this chapter applies GWP-100 values from the IPCC Fourth Assessment Report while the NDC Cross-Chapter Box 11 applies GWP-100 values from the IPCC Second Assessment Report. At a global scale, switching between GWP-100 values of the Second to the Fourth IPCC Assessment Report would result in an increase in estimated aggregated Kyoto-GHG emissions of no more than about 3% in 2030 (UNFCCC, 2016). 126 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 for the NDCs rely on an assumed swift and widespread deployment of post-2030 transition, and the assessment of carbon budgets in Section CDR after 2030, and show peak cumulative CO2 emissions from 2018 2.2.2, global warming is assessed to exceed 1.5°C if emissions stay at of about 800–1000 GtCO2, above the remaining carbon budget for a the levels implied by the NDCs until 2030 (Figure 2.12). The chances one-in-two chance of remaining below 1.5°C. These emissions reflect of remaining below 1.5°C in these circumstances remain conditional that no pathway is able to project a phase-out of CO2 emissions starting upon geophysical properties that are uncertain, but these Earth from year-2030 NDC levels of about 40 GtCO −12 yr (Fawcett et al., 2015; system response uncertainties would have to serendipitously align Rogelj et al., 2016a) to net zero in less than about 15 years. Based on beyond current median estimates in order for current NDCs to become the implied emissions until 2030, the high challenges of the assumed consistent with limiting warming to 1.5°C. (a) Below 1.5C 1.5C Low OS 1000 1.5C High OS NDC pathways 1.8 900 2 1.7 800 700 1.6 Kriegler et al., 2018a 600 1.5 NDC 500 NDC range range 1.4 15 20 25 30 35 40 45 50 55 60 40015 20 25 30 35 40 45 50 55 60 Kyoto gas emissions in 2030 (GtCO2 eq yr-) Kyoto gas emissions in 2030 (GtCO eq yr-2 ) Figure 2.12 | Median global warming estimated by MAGICC (panel a) and peak cumulative CO2 emissions (panel b) in 1.5°C-consistent pathways in the SR1.5 scenario database, as a function of CO2-equivalent emissions (based on AR4 GWP-100) of Kyoto-GHGs in 2030. Pathways that were forced to go through the NDCs or a similarly high emissions point in 2030 by design are highlighted by yellow marker edges (see caption of Figure 2.13 and text for further details on the design of these pathways). The combined range of global Kyoto-GHG emissions in 2030 for the conditional and unconditional NDCs assessed in Cross-Chapter Box 11 is shown by the grey shaded area (adjusted to AR4 GWPs for comparison). As a second line of evidence, peak cumulative CO2 emissions derived from a 1.5°C pathway sensitivity analysis (Kriegler et al., 2018b) are shown by grey circles in the right-hand panel. Circles show gross fossil-fuel and industry emissions of the sensitivity cases, increased by assumptions about the contributions from AFOLU (5 GtCO2 yr −1 until 2020, followed by a linear phase out until 2040) and non-CO2 Kyoto-GHGs (median non-CO2 contribution from 1.5°C-consistent pathways available in the database: 10 GtCO e yr−12 in 2030), and reduced by assumptions about CDR deployment until the time of net zero CO2 emissions (limiting case for CDR deployment assumed in (Kriegler et al., 2018b) (logistic growth to 1, 4, 10 GtCO yr−12 in 2030, 2040, and 2050, respectively, leading to approximately 100 GtCO2 of CDR by mid-century). It is unclear whether following NDCs until 2030 would still allow found in least-cost pathways starting from 2020). An IAM comparison global mean temperature to return to 1.5°C by 2100 after a temporary study found increasing challenges to implementing pathways with the overshoot, due to the uncertainty associated with the Earth system same end-of-century carbon budgets after following NDCs until 2030 response to net negative emissions after a peak (Section 2.2). Available (Luderer et al., 2018). The majority of model experiments (four out of IAM studies are working with reduced-form carbon cycle–climate seven) failed to produce NDC pathways that would return cumulative models like MAGICC, which assume a largely symmetric Earth- CO2 emissions over the 2016–2100 period to 200 GtCO2, indicating system response to positive and net negative CO2 emissions. The IAM limitations to the availability and timing of CDR. The few such findings on returning warming to 1.5°C from NDCs after a temporary pathways that were identified show highly disruptive features in 2030 temperature overshoot are hence all conditional on this assumption. (including abrupt transitions from moderate to very large emissions Two types of pathways with 1.5°C-consistent action starting in 2030 reduction and low carbon energy deployment rates) indicating a high have been considered in the literature (Luderer et al., 2018) (Figure risk that the required post-2030 transformations are too steep and 2.13): pathways aiming to obtain the same end-of-century carbon abrupt to be achieved by the mitigation measures in the models (high budget as 1.5°C-consistent pathways starting in 2020 despite higher confidence). NDC pathways aiming for a cumulative 2016–2100 CO2 emissions until 2030, and pathways assuming the same mitigation emissions budget of 800 GtCO2 were more readily obtained (Luderer et stringency after 2030 as in 1.5°C-consistent pathways starting in al., 2018), and some were classified as 1.5°C-high-OS pathways in this 2020 (approximated by using the same global price of emissions as assessment (Section 2.1). 127 Median global warming since preindustrial (oC) Peak Cumulative CO2 Emissions from 2018 (GtCO2) Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Variations in global CO2 emissions Legend over next decade Data from the same model for a 50 the set of three pathways with b near-term emissions variations 0.2 40 MAGICC P B 30 0.1 FAIR A Change relative to pathway with deep A CO2 reductions20 from 2020 0 10 P 2020 2040 2060 2080 2100 Other pathways with a similar design 0 2 Range of below-1.5°C−10 B and 1.5°C-low-OS pathways −20 2010 2020 2030 2040 2050 2060 2070 2080 2090 2100 Year c 1500 d 0.8 0.6 1000 0.4 500 0.2 0 0 −0.2 2030 2050 2100 2020−2030 2030−2050 2050−2100 e f 1400 2 1200 1.5 1000 1 800 0.5 600 Remaining 1.5°C carbon budget 400 0 200 −0.5 2030 2050 2100 2020−2030 2030−2050 2050−2100 Figure 2.13 | Comparison of 1.5°C-consistent pathways starting action as of 2020 (A; light-blue diamonds) with pathways following the NDCs until 2030 and aiming to limit warming to 1.5°C thereafter. The 1.5°C pathways that follow the NDCs until 2030 either aim for the same cumulative CO2 emissions by 2100 as the pathways that start action as of 2020 (B; red diamonds) or assume the same mitigation stringency as reflected by the price of emissions in associated least-cost 1.5°C-consistent pathways starting from 2020 (P; black diamonds). Panels show (a) the underlying emissions pathways, (b) additional warming in the delay scenarios compared to 2020 action case, (c) cumulated CDR, (d) CDR ramp-up rates, (e) cumulated gross CO2 emissions from fossil-fuel combustion and industrial (FFI) processes over the 2018–2100 period, and (f) gross FFI CO2 emissions reductions rates. Scenario pairs or triplets (circles and diamonds) with 2020 and 2030 action variants were calculated by six (out of seven) models in the ADVANCE study symbols (Luderer et al., 2018) and five of them (passing near-term plausibility checks) are shown by symbols. Only two of five models could identify pathways with post-2030 action leading to a 2016–2100 carbon budget of about 200 GtCO2 (red). The range of all 1.5°C pathways with no and low overshoot is shown by the boxplots. 128 Cumulative FF & Ind CO2 emissions from 2018 (GtCO ) Cumulative CDR (GtCO ) Net CO2 emissions (GtCO2/yr)2 2 Additional global mean temperature rise (°C) Annual average FF & Ind CO Annual average CDR addition2 emissions reductions (GtCO /yr]) (GtCO2/yr)2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 NDC pathways that apply a post-2030 price of emissions as found in and fall below levels in line with current NDCs by 2030. For example, least-cost pathways starting from 2020 show infrastructural carbon Strefler et al. (2018b) find that CDR deployment levels in the second lock-in as a result of following NDCs instead of least-cost action until half of the century can be halved in 1.5°C-consistent pathways with 2030. A key finding is that carbon lock-ins persist long after 2030, with similar CO2 emissions reductions rates during the 2030–2050 period the majority of additional CO2 emissions occurring during the 2030– if CO2 emissions by 2030 are reduced by an additional 30% compared 2050 period. Luderer et al. (2018) find 90 (80–120) GtCO2 additional to NDC levels. Kriegler et al. (2018a) investigate a global rollout of emissions until 2030, growing to 240 (190–260) GtCO2 by 2050 and selected regulatory policies and moderate carbon pricing policies. 290 (200–200) GtCO2 by 2100. As a result, peak warming is about 0.2°C They show that additional reductions of about 10 GtCO2e yr −1 can be higher and not all of the modelled pathways return warming to 1.5°C achieved in 2030 compared to the current NDCs. Such a 20% reduction by the end of the century. There is a four sided trade-off between (i) of year-2030 emissions compared to current NDCs would effectively near-term ambition, (ii) degree of overshoot, (iii) transitional challenges lower the disruptiveness of post-2030 action. The strengthening of during the 2030–2050 period, and (iv) the amount of CDR deployment short-term policies in deep mitigation pathways has hence been required during the century (Figure 2.13) (Holz et al., 2018b; Strefler identified as a way of bridging options to keep the Paris climate goals et al., 2018b). Transition challenges, overshoot, and CDR requirements within reach (Bertram et al., 2015b; IEA, 2015a; Spencer et al., 2015; can be significantly reduced if global emissions peak before 2030 Kriegler et al., 2018a). 2 2.4 Disentangling the Whole-System 2.4.1 Energy System Transformation Transformation The energy system links energy supply (Section 2.4.2) with energy Mitigation pathways map out prospective transformations of the demand (Section 2.4.3) through final energy carriers, including energy, land and economic systems over this century (Clarke et al., electricity and liquid, solid or gaseous fuels, that are tailored to 2014). There is a diversity of potential pathways consistent with 1.5°C, their end-uses. To chart energy-system transformations in mitigation yet they share some key characteristics summarized in Table 2.5. To pathways, four macro-level decarbonization indicators associated with explore characteristics of 1.5°C pathways in greater detail, this section final energy are useful: limits on the increase of final energy demand, focuses on changes in energy supply and demand, and changes in the reductions in the carbon intensity of electricity, increases in the share AFOLU sector. of final energy provided by electricity, and reductions in the carbon Table 2.5 | Overview of Key Characteristics of 1.5°C Pathways. 1.5°C Pathway Supporting Information Reference Characteristic Rapid and profound near-term Strong upscaling of renewables and sustainable biomass and reduction of unabated (no CCS) fossil fuels, Section 2.4.1 decarbonisation of energy supply along with the rapid deployment of CCS, lead to a zero-emission energy supply system by mid-century. Section 2.4.2 Greater mitigation efforts All end-use sectors show marked demand reductions beyond the reductions projected for 2°C pathways. Demand Section 2.4.3 on the demand side reductions from IAMs for 2030 and 2050 lie within the potential assessed by detailed sectoral bottom-up assessments. Switching from fossil fuels to Section 2.4.3.2 Both in the transport and the residential sector, electricity covers markedly larger shares of total demand by mid-century. electricity in end-use sectors Section 2.4.3.3 Comprehensive emission Virtually all 1.5°C-consistent pathways decline net annual CO2 emissions between 2020 and 2030, reaching carbon reductions are implemented neutrality around mid-century. In 2030, below-1.5°C and 1.5°C-low-OS pathways show maximum net CO2 emissions Section 2.3.4 in the coming decade of 18 and 28 GtCO yr−12 , respectively. GHG emissions in these scenarios are not higher than 34 GtCO2e yr −1 in 2030. Additional reductions, on top of Both CO2 and the non-CO2 GHGs and aerosols are strongly reduced by 2030 and until 2050 in 1.5°C pathways. reductions from both CO2 and The greatest difference to 2°C pathways, however, lies in additional reductions of CO2, as the non-CO mitigation Section 2.3.1.2non-CO2 required for 2°C, 2 potential that is currently included in integrated pathways is mostly already fully deployed for reaching a 2°C pathway. are mainly from CO2 Low-carbon investments in the energy supply side (energy production and refineries) are projected to average Considerable shifts in 1.6–3.8 trillion 2010USD yr−1 globally to 2050. Investments in fossil fuels decline, with investments in unabated coal Section 2.5.2 investment patterns halted by 2030 in most available 1.5°C-consistent projections, while the literature is less conclusive for investments in unabated gas and oil. Energy demand investments are a critical factor for which total estimates are uncertain. Options are available to Synergies can be maximized, and risks of trade-offs limited or avoided through an informed choice of mitigation align 1.5°C pathways with Section 2.5.3 strategies. Particularly pathways that focus on a lowering of demand show many synergies and few trade-offs. sustainable development By 2050, 1.5°C pathways project deployment of BECCS at a scale of 3–7 GtCO yr−12 (range of medians across CDR at scale before mid-century 1.5°C pathway classes), depending on the level of energy demand reductions and mitigation in other sectors. Section 2.3.3, 2.3.4.1 Some 1.5°C pathways are available that do not use BECCS, but only focus terrestrial CDR in the AFOLU sector. 129 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development intensity of final energy other than electricity (referred to in this section The largest differences between 1.5°C and 2°C pathways are seen in the as the carbon intensity of the residual fuel mix). Figure 2.14 shows first half of the century (Figure 2.14), where 1.5°C pathways generally changes of these four indicators for the pathways in the scenario show lower energy demand, a faster electrification of energy end-use, database (Section 2.1.3 and Supplementary Material 2.SM.1.3) for and a faster decarbonization of the carbon intensity of electricity and 1.5°C and 2°C pathways (Table 2.1). the residual fuel mix. There are very few pathways in the Below-1.5°C class (Figure 2.14). Those scenarios that are available, however, show Pathways in both the 1.5°C and 2°C classes (Figure 2.14) generally a faster decline in the carbon intensity of electricity generation and show rapid transitions until mid-century, with a sustained but slower residual fuel mix by 2030 than most pathways that are projected to evolution thereafter. Both show an increasing share of electricity temporarily overshoot 1.5°C and return by 2100 (or 2°C pathways). accompanied by a rapid decline in the carbon intensity of electricity. The Below-1.5°C pathways also appear to differentiate themselves Both also show a generally slower decline in the carbon intensity of from the other pathways as early as 2030 through reductions in final the residual fuel mix, which arises from the decarbonization of liquids, energy demand and increases in electricity share (Figure 2.14). gases and solids provided to industry, residential and commercial activities, and the transport sector. 2 Figure 2.14 | Decomposition of transformation pathways into (a) energy demand, (b) carbon intensity of electricity, (c) the electricity share in final energy, and (d) the carbon intensity of the residual (non-electricity) fuel mix. Box plots show median, interquartile range and full range of pathways. Pathway temperature classes (Table 2.1) and illustrative pathway archetypes are indicated in the legend. Values following the class labels give the number of available pathways in each class. 2.4.2 Energy Supply 2.4.2.1 Evolution of primary energy contributions over time Several energy supply characteristics are evident in 1.5°C pathways By mid-century, the majority of primary energy comes from non-fossil- assessed in this section: (i) growth in the share of energy derived fuels (i.e., renewables and nuclear energy) in most 1.5°C pathways from low-carbon-emitting sources (including renewables, nuclear and (Table 2.6). Figure 2.15 shows the evolution of primary energy supply fossil fuel with CCS) and a decline in the overall share of fossil fuels over this century across 1.5°C pathways, and in detail for the four without CCS (Section 2.4.2.1), (ii) rapid decline in the carbon intensity illustrative pathway archetypes highlighted in this chapter. Note that of electricity generation simultaneous with further electrification of this section reports primary energy using the direct equivalent method energy end-use (Section 2.4.2.2), and (iii) the growth in the use of CCS on the basis of lower heating values (Bruckner et al., 2014). applied to fossil and biomass carbon in most 1.5°C pathways (Section 2.4.2.3). 130 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 2 Figure 2.15 | Primary energy supply for the four illustrative pathway archetypes plus the IEA’s Faster Transition Scenario (OECD/IEA and IRENA, 2017) (panel a), and their relative location in the ranges for pathways limiting warming to 1.5°C with no or limited overshoot (panel b). The category ‘Other renewables’ includes primary energy sources not covered by the other categories, for example, hydro and geothermal energy. The number of pathways that have higher primary energy than the scale in the bottom panel are indicated by the numbers above the whiskers. Black horizontal dashed lines indicates the level of primary energy supply in 2015 (IEA, 2017e). Box plots in the lower panel show the minimum–maximum range (whiskers), interquartile range (box), and median (vertical thin black line). Symbols in the lower panel show the four pathway archetypes S1 (white square), S2 (yellow square), S5 (black square), LED (white disc), as well as the IEA–(red disc). Pathways with no or limited overshoot included the Below-1.5°C and 1.5°C-low-OS classes. The share of energy from renewable sources (including biomass, hydro, for nuclear fission by the end of the century, while others project about solar, wind and geothermal) increases in all 1.5°C pathways with no or 95 EJ yr−1 of nuclear power in 2100 (Figure 2.15). limited overshoot, with the renewable energy share of primary energy reaching 38–88% in 2050 (Table 2.6), with an interquartile range of The share of primary energy provided by total fossil fuels decreases from 52–67%. The magnitude and split between bioenergy, wind, solar, 2020 to 2050 in all 1.5°C pathways, but trends for oil, gas and coal differ and hydro differ between pathways, as can be seen in the illustrative (Table 2.6). By 2050, the share of primary energy from coal decreases pathway archetypes in Figure 2.15. Bioenergy is a major supplier of to 0–11% across 1.5°C pathways with no or limited overshoot, with primary energy, contributing to both electricity and other forms of an interquartile range of 1–7%. From 2020 to 2050 the primary energy final energy such as liquid fuels for transportation (Bauer et al., 2018). supplied by oil changes by −93 to −9% (interquartile range −77 to In 1.5°C pathways, there is a significant growth in bioenergy used in −39%); natural gas changes by −88 to +85% (interquartile range combination with CCS for pathways where it is included (Figure 2.15). −62 to −13%), with varying levels of CCS. Pathways with higher use of coal and gas tend to deploy CCS to control their carbon emissions Nuclear power increases its share in most 1.5°C pathways with no or (see Section 2.4.2.3). As the energy transition is accelerated by several limited overshoot by 2050, but in some pathways both the absolute decades in 1.5°C pathways compared to 2°C pathways, residual fossil- capacity and share of power from nuclear generators decrease (Table fuel use (i.e., fossil fuels not used for electricity generation) without 2.15). There are large differences in nuclear power between models CCS is generally lower in 2050 than in 2°C pathways, while combined and across pathways (Kim et al., 2014; Rogelj et al., 2018). One of hydro, solar, and wind power deployment is generally higher than in the reasons for this variation is that the future deployment of nuclear 2°C pathways (Figure 2.15). can be constrained by societal preferences assumed in narratives underlying the pathways (O’Neill et al., 2017; van Vuuren et al., 2017b). In addition to the 1.5°C pathways included in the scenario database Some 1.5°C pathways with no or limited overshoot no longer see a role (Supplementary Material 2.SM.1.3), there are other analyses in the 131 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development literature including, for example, sector-based analyses of energy challenges related to its land use and impact on food supply (Burns demand and supply options. Even though they were not necessarily and Nicholson, 2017) (assessed in greater detail in Sections 2.3.4.2, developed in the context of the 1.5°C target, they explore in greater 4.3.7 and 5.4). These analyses could, provided their assumptions prove detail some options for deep reductions in GHG emissions. For example, plausible, expand the range of 1.5°C pathways. there are analyses of transitions to up to 100% renewable energy by 2050 (Creutzig et al., 2017; Jacobson et al., 2017), which describe In summary, the share of primary energy from renewables increases what is entailed for a renewable energy share largely from solar and while that from coal decreases across 1.5°C pathways (high wind (and electrification) that is above the range of 1.5°C pathways confidence). This statement is true for all 1.5°C pathways in the available in the database, although there have been challenges to the scenario database and associated literature (Supplementary Material assumptions used in high-renewable analyses (e.g., Clack et al., 2017). 2.SM.1.3), and is consistent with the additional studies mentioned There are also analyses that result in a large role for nuclear energy above, an increase in energy supply from lower-carbon-intensity in mitigation of GHGs (Hong et al., 2015; Berger et al., 2017a, b; Xiao energy supply, and a decrease in energy supply from higher-carbon- and Jiang, 2018). BECCS could also contribute a larger share, but faces intensity energy supply. 2 Table 2.6 | Global primary energy supply of 1.5°C pathways from the scenario database (Supplementary Material 2.SM.1.3). Values given for the median (maximum, minimum) across the full range of 85 available 1.5°C pathways. Growth Factor = [(primary energy supply in 2050)/(primary energy supply in 2020) − 1] Median Primary Energy Supply (EJ) Share in Primary Energy (%) Count Growth (factor) (max, min) 2020 2030 2050 2020 2030 2050 2020-2050 Below- 565.33 464.50 553.23 –0.05 total primary 50 NA NA NA 1.5°C and (619.70, 483.22) (619.87, 237.37) (725.40, 289.02) (0.48, –0.51) 1.5°C- 87.14 146.96 291.33 14.90 29.08 60.24 low-OS renewables 50 2.37 (6.71, 0.91)(101.60, 60.16) (203.90, 87.75) (584.78, 176.77) (20.39, 10.60) (62.15, 18.24) (87.89, 38.03) pathways 60.41 77.07 152.30 10.17 17.22 27.29 1.71 biomass 50 (70.03, 40.54) (113.02, 44.42) (311.72, 40.36) (13.66, 7.14) (35.61, 9.08) (54.10, 10.29) (5.56, –0.42) 26.35 62.58 146.23 4.37 13.67 27.98 non-biomass 50 4.28 (13.46, 1.45) (36.57, 17.78) (114.41, 25.79) (409.94, 53.79) (7.19, 3.01) (26.54, 5.78) (61.61, 12.04) 10.93 40.14 121.82 1.81 9.73 21.13 wind & solar 44 10.00 (53.70, 3.71) (20.16, 2.61) (82.66, 7.05) (342.77, 27.95) (3.66, 0.45) (19.56, 1.54) (51.52, 4.48) 10.91 16.26 24.51 2.10 3.52 4.49 nuclear 50 1.24 (5.01, –0.64) (18.55, 8.52) (36.80, 6.80) (66.30, 3.09) (3.37, 1.45) (9.61, 1.32) (12.84, 0.44) 462.95 310.36 183.79 82.53 66.58 32.79 fossil 50 –0.59 (–0.21, –0.89) (520.41, 376.30) (479.13, 70.14) (394.71, 54.86) (86.65, 77.73) (77.30, 29.55) 60.84, 8.58) 136.89 44.03 24.15 25.63 coal 50 9.62 (20.65, 1.31) 5.08 (11.43, 0.15) –0.83 (–0.57, –0.99) (191.02, 83.23) (127.98, 5.97) (71.12, 0.92) (30.82, 17.19) 132.95 112.51 76.03 23.10 22.52 13.23 gas 50 –0.40 (0.85, –0.88) (152.80, 105.01) (173.56, 17.30) (199.18, 14.92) (28.39, 18.09) (35.05, 7.08) (34.83, 3.68) 197.26 156.16 69.94 34.81 31.24 12.89 oil 50 –0.66 (–0.09, –0.93) (245.15, 151.02) (202.57, 38.94) (167.52, 15.07) (42.24, 29.00) (39.84, 16.41) (27.04, 2.89) 1.5°C- 594.96 559.04 651.46 total primary 35 NA NA NA 0.13 (0.59, –0.27) high-OS (636.98, 510.55) (749.05, 419.28) (1012.50, 415.31) 89.84 135.12 323.21 15.08 23.65 62.16 renewables 35 2.68 (4.81, 1.17) (98.60, 66.57) (159.84, 87.93) (522.82, 177.66) (18.58, 11.04) (29.32, 13.78) (86.26, 28.47) 62.59 69.05 160.16 10.30 13.64 23.79 biomass 35 1.71 (3.71, 0.19) (73.03, 48.42) (98.27, 56.54) (310.10, 71.17) (14.23, 8.03) (16.37, 9.03) (45.79, 10.64) 28.46 59.81 164.91 4.78 10.23 31.17 non-biomass 35 6.10 (10.63, 1.38) (36.58, 17.60) (92.12, 27.39) (329.69, 55.72) (6.64, 2.84) (16.59, 4.49) (45.86, 9.87) 11.32 40.31 139.20 26.01 wind & solar 26 1.95 (3.66, 0.32) 7.31 (11.61, 1.83) 16.06 (63.34, 3.13) (20.17, 1.91) (65.50, 8.14) (275.47, 30.92) (38.79, 6.33) 10.94 16.12 22.98 4.17 nuclear 35 1.86 (2.37, 1.45) 2.99 (5.57, 1.20) 1.49 (7.22, –0.64) (14.27, 8.52) (41.73, 6.80) (115.80, 3.09) (13.60, 0.43) 497.30 397.76 209.80 83.17 73.87 33.58 fossil 35 –0.56 (0.12, –0.91) (543.29, 407.49) (568.91, 300.63) (608.39, 43.87) (86.59, 79.39) (82.94, 68.00) (60.09, 7.70) 155.65 70.99 18.95 25.94 14.53 coal 35 4.14 (13.30, 0.05) –0.87 (–0.30, –1.00) (193.55, 118.40) (176.99, 19.15) (134.69, 0.36) (30.82, 19.10) (26.35, 3.64) 138.01 147.43 97.71 23.61 25.79 15.67 gas 35 –0.31 (0.99, –0.88) (169.50, 107.07) (208.55, 76.45) (265.66, 15.96) (27.35, 19.26) (32.73, 14.69) (33.80, 2.80) 195.02 198.50 126.20 32.21 33.27 18.61 oil 35 –0.34 (0.06, –0.87) (236.40, 154.66) (319.80, 102.10) (208.04, 24.68) (38.87, 28.07) (50.12, 24.35) (27.30, 4.51) 132 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 Table 2.6 (continued) Median Primary Energy Supply (EJ) Share in Primary Energy (%) Count Growth (factor) (max, min) 2020 2030 2050 2020 2030 2050 2020-2050 Two above 582.12 502.81 580.78 total primary 85 - - - 0.03 (0.59, –0.51) classes (636.98, 483.22) (749.05, 237.37) (1012.50, 289.02) combined 87.70 139.48 293.80 15.03 27.90 60.80 renewables 85 2.62 (6.71, 0.91) (101.60, 60.16) (203.90, 87.75) (584.78, 176.77) (20.39, 10.60) (62.15, 13.78) (87.89, 28.47) 61.35 75.28 154.13 10.27 14.38 26.38 biomass 85 1.71 (5.56, –0.42) (73.03, 40.54) (113.02, 44.42) (311.72, 40.36) (14.23, 7.14) (35.61, 9.03) (54.10, 10.29) 26.35 61.60 157.37 4.40 11.87 28.60 non-biomass 85 4.63 (13.46, 1.38) (36.58, 17.60) (114.41, 25.79) (409.94, 53.79) (7.19, 2.84) (26.54, 4.49) (61.61, 9.87) 10.93 40.17 125.31 22.10 wind & solar 70 1.81 (3.66, 0.32) 8.24 (19.56, 1.54) 11.64 (63.34, 3.13) (20.17, 1.91) (82.66, 7.05) (342.77, 27.95) (51.52, 4.48) 10.93 16.22 24.48 4.22 nuclear 85 1.97 (3.37, 1.45) 3.27 (9.61, 1.20) 1.34 (7.22, –0.64) (18.55, 8.52) (41.73, 6.80) (115.80, 3.09) (13.60, 0.43) 489.52 343.48 198.58 83.05 69.19 33.06 2 fossil 85 –0.58 (0.12, –0.91) (543.29, 376.30) (568.91, 70.14) (608.39, 43.87) (86.65, 77.73) (82.94, 29.55) (60.84, 7.70) 147.09 49.46 23.84 25.72 10.76 coal 85 4.99 (13.30, 0.05) –0.85 (–0.30, –1.00) (193.55, 83.23) (176.99, 5.97) (134.69, 0.36) (30.82, 17.19) (26.35, 1.31) 135.58 127.99 88.97 23.28 24.02 13.46 gas 85 –0.37 (0.99, –0.88) (169.50, 105.01) (208.55, 17.30) (265.66, 14.92) (28.39, 18.09) (35.05, 7.08) (34.83, 2.80) 195.02 175.69 93.48 33.79 32.01 16.22 oil 85 –0.54 (0.06, –0.93) (245.15, 151.02) (319.80, 38.94) (208.04, 15.07) (42.24, 28.07) (50.12, 16.41) (27.30, 2.89) Table 2.7 | Global electricity generation of 1.5°C pathways from the scenarios database. (Supplementary Material 2.SM.1.3). Values given for the median (maximum, minimum) values across the full range across 89 available 1.5°C pathways. Growth Factor = [(primary energy supply in 2050)/(primary energy supply in 2020) – 1]. Median Electricity Generation (EJ) Share in Electricity Generation (%) Growth (factor) (max, min) Count 2020 2030 2050 2020 2030 2050 2020–2050 TBelow total 98.45 115.82 215.58 50 NA NA NA 1.15 (2.55, 0.28) -1.5°C and generation (113.98, 83.53) (152.40, 81.28) (354.48, 126.96) 1.5°C- 26.28 63.30 145.50 26.32 53.68 77.12 low-OS renewables 50 4.48 (10.88, 2.65)(41.80, 18.50) (111.70, 32.41) (324.26, 90.66) (41.84, 18.99) (79.67, 37.30) (96.65, 58.89) pathways 4.29 20.35 8.77 biomass 50 2.02 (7.00, 0.76) 1.97 (6.87, 0.82) 3.69 (13.29, 0.73) 6.42 (38.14, –0.93) (11.96, 0.79) (39.28, 0.24) (30.28, 0.10) 24.21 57.12 135.04 24.38 49.88 64.68 non-biomass 50 4.64 (10.64, 1.45) (35.72, 17.70) (101.90, 25.79) (323.91, 53.79) (40.43, 17.75) (78.27, 29.30) (96.46, 41.78) 8.91 39.04 19.10 wind & solar 50 1.66 (6.60, 0.38) 1.62 (7.90, 0.38) 8.36 (41.72, 0.53) 26.31 (169.66, 5.23) (48.04, 0.60) (208.97, 2.68) (60.11, 1.65) 10.84 15.46 21.97 12.09 14.33 8.10 nuclear 50 0.71 (4.97, –0.64) (18.55, 8.52) (36.80, 6.80) (64.72, 3.09) (18.34, 8.62) (31.63, 5.24) (27.53, 1.02) 59.43 36.51 14.81 61.32 30.04 fossil 50 8.61 (25.18, 0.00) –0.74 (0.01, –1.00) (68.75, 39.48) (66.07, 2.25) (57.76, 0.00) (67.40, 47.26) (52.86, 1.95) 31.02 8.83 1.38 32.32 coal 50 7.28 (27.29, 0.00) 0.82 (7.53, 0.00) –0.96 (–0.56, –1.00) (42.00, 14.40) (34.11, 0.00) (17.39, 0.00) 40.38, 17.23) 24.70 22.59 12.79 24.39 20.18 gas 50 6.93 (24.87, 0.00) –0.47 (1.27, –1.00) (32.46, 13.44) (42.08, 2.01) (53.17, 0.00) (35.08, 11.80) (37.23, 1.75) 2.48 2.82 oil 50 1.89 (7.56, 0.24) 0.10 (8.78, 0.00) 1.95 (5.67, 0.21) 0.05 (3.80, 0.00) –0.92 (0.36, –1.00) (13.36, 1.12) (11.73, 1.01) 1.5°C- total 101.44 125.26 251.50 35 NA NA NA 1.38 (2.19, 0.39) high-OS generation (113.96, 88.55) (177.51, 89.60) (363.10, 140.65) 26.38 53.32 173.29 28.37 42.73 82.39 renewables 35 5.97 (8.68, 2.37) (31.83, 18.26) (86.85, 30.06) (273.92, 84.69) (32.96, 17.38) (65.73, 25.11) (94.66, 35.58) 10.49 3.75 biomass 35 1.23 (6.47, 0.66) 2.14 (7.23, 0.86) 1.22 (7.30, 0.63) 1.59 (6.73, 0.72) 7.93 (33.32, –0.81) (40.32, 0.21) (28.09, 0.08) 24.56 47.96 144.13 26.77 40.07 69.72 non-biomass 35 5.78 (8.70, 1.38) (30.70, 17.60) (85.83, 27.39) (271.17, 55.72) (31.79, 16.75) (64.96, 23.10) (94.58, 27.51) Table 2.7 (continued next page) 133 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Table 2.7 (continued) Median Electricity Generation (EJ) Share in Electricity Generation (%) Count Growth (factor) (max, min) 2020 2030 2050 2020 2030 2050 2020-2050 1.5°C- 8.95 65.08 25.88 wind & solar 35 2.24 (5.07, 0.42) 2.21 (5.25, 0.41) 7.48 (27.90, 0.99) 30.70 (106.95, 4.87) high-OS (36.52, 1.18) (183.38, 13.79) (61.24, 8.71) 10.84 16.12 22.91 10.91 14.65 11.19 nuclear 35 1.49 (7.22, –0.64) (14.08, 8.52) (41.73, 6.80) (115.80, 3.09) (13.67, 8.62) (23.51, 5.14) (39.61, 1.12) 62.49 48.08 11.84 61.58 42.02 fossil 35 6.33 (33.19, 0.27) –0.80 (0.54, –0.99) (76.76, 49.09) (87.54, 30.99) (118.12, 0.78) (71.03, 54.01) (59.48, 24.27) 32.37 16.22 1.18 32.39 14.23 coal 35 0.55 (12.87, 0.00) –0.96 (0.01, –1.00) (46.20, 26.00) (43.12, 1.32) (46.72, 0.01) (40.88, 24.41) (29.93, 1.19) 26.20 26.45 10.66 26.97 22.29 gas 35 5.29 (32.59, 0.26) –0.57 (1.63, –0.97) (41.20, 20.11) (51.99, 16.45) (67.94, 0.76) (39.20, 19.58) (43.43, 14.03) oil 35 1.51 (6.28, 1.12) 0.61 (7.54, 0.36) 0.04 (7.47, 0.00) 1.51 (6.27, 1.01) 0.55 (6.20, 0.26) 0.02 (3.31, 0.00) –0.99 (0.98, –1.00) 2 Two above total 100.09 120.01 224.78 85 NA NA NA 1.31 (2.55, 0.28) classes generation (113.98, 83.53) (177.51, 81.28) (363.10, 126.96) combined 26.38 59.50 153.72 27.95 51.51 77.52 renewables 85 5.08 (10.88, 2.37) (41.80, 18.26) (111.70, 30.06) (324.26, 84.69) (41.84, 17.38) (79.67, 25.11) (96.65, 35.58) 3.55 16.32 8.02 biomass 85 1.52 (7.00, 0.66) 1.55 (7.30, 0.63) 2.77 (13.29, 0.72) 6.53 (38.14, –0.93) (11.96, 0.79) (40.32, 0.21) (30.28, 0.08) 24.48 55.68 136.40 25.00 47.16 66.75 non-biomass 85 4.75 (10.64, 1.38) (35.72, 17.60) (101.90, 25.79) (323.91, 53.79) (40.43, 16.75) (78.27, 23.10) (96.46, 27.51) 8.95 43.20 1.67 8.15 19.70 wind & solar 85 1.66 (6.60, 0.38) 28.02 (169.66, 4.87) (48.04, 0.60) (208.97, 2.68) (7.90, 0.38) (41.72, 0.53) (61.24, 1.65) 10.84 15.49 22.64 10.91 14.34 8.87 nuclear 85 1.21 (7.22, –0.64) (18.55, 8.52) (41.73, 6.80) (115.80, 3.09) (18.34, 8.62) (31.63, 5.14) (39.61, 1.02) 61.35 38.41 14.10 61.55 33.96 fossil 85 8.05 (33.19, 0.00) –0.76 (0.54, –1.00) (76.76, 39.48) (87.54, 2.25) (118.12, 0.00) (71.03, 47.26) (59.48, 1.95) 32.37 10.41 1.29 32.39 coal 85 8.95 (29.93, 0.00) 0.59 (12.87, 0.00) –0.96 (0.01, –1.00) (46.20, 14.40) (43.12, 0.00) (46.72, 0.00) (40.88, 17.23) 24.70 25.00 11.92 24.71 21.03 gas 85 6.78 (32.59, 0.00) –0.52 (1.63, –1.00) (41.20, 13.44) (51.99, 2.01) (67.94, 0.00) (39.20, 11.80) (43.43, 1.75) 1.82 2.04 oil 85 0.92 (7.56, 0.24) 0.08 (8.78, 0.00) 0.71 (6.20, 0.21) 0.04 (3.80, 0.00) –0.97 (0.98, –1.00) (13.36, 1.12) (11.73, 1.01) 2.4.2.2 Evolution of electricity supply over time In summary, 1.5°C pathways include a rapid decline in the carbon intensity of electricity and an increase in electrification of energy end- Electricity supplies an increasing share of final energy, reaching use (high confidence). This is the case across all 1.5°C pathways and 34–71% in 2050, across 1.5°C pathways with no or limited overshoot their associated literature (Supplementary Material 2.SM.1.3), with (Figure 2.14), extending the historical increases in electricity share pathway trends that extend those seen in past decades, and results seen over the past decades (Bruckner et al., 2014). From 2020 to 2050, that are consistent with additional analyses (see Section 2.4.2.2). the quantity of electricity supplied in most 1.5°C pathways with no or limited overshoot more than doubles (Table 2.7). By 2050, the carbon 2.4.2.3 Deployment of carbon capture and storage intensity of electricity has fallen rapidly to −92 to +11 gCO −12 MJ electricity across 1.5°C pathways with no or limited overshoot from Studies have shown the importance of CCS for deep mitigation pathways a value of around 140 gCO MJ−12 (range: 88–181 gCO2 MJ −1) in 2020 (Krey et al., 2014a; Kriegler et al., 2014b), based on its multiple roles to (Figure 2.14). A negative contribution to carbon intensity is provided by limit fossil-fuel emissions in electricity generation, liquids production, BECCS in most pathways (Figure 2.16). and industry applications along with the projected ability to remove CO2 from the atmosphere when combined with bioenergy. This remains By 2050, the share of electricity supplied by renewables increases from a valid finding for those 1.5°C and 2°C pathways that do not radically 23% in 2015 (IEA, 2017b) to 59–97% across 1.5°C pathways with no reduce energy demand or do not offer carbon-neutral alternatives to or limited overshoot. Wind, solar, and biomass together make a major liquids and gases that do not rely on bioenergy. contribution in 2050, although the share for each spans a wide range across 1.5°C pathways (Figure 2.16). Fossil fuels on the other hand There is a wide range of CCS that is deployed across 1.5°C pathways have a decreasing role in electricity supply, with their share falling to (Figure 2.17). A few 1.5°C pathways with very low energy demand 0–25% by 2050 (Table 2.7). do not include CCS at all (Grubler et al., 2018). For example, the LED pathway has no CCS, whereas other pathways, such as the S5 pathway, 134 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 2 Figure 2.16 | Electricity generation for the four illustrative pathway archetypes plus the IEA’s Faster Transition Scenario (IEA, 2017d) (panel a), and their relative location in the ranges for pathways limiting warming to 1.5°C with no or limited overshoot (panel b). The category ‘Other renewables’ includes electricity generation not covered by the other categories, for example, hydro and geothermal. The number of pathways that have higher primary energy than the scale in the bottom panel are indicated by the numbers above the whiskers. Black horizontal dashed lines indicate the level of primary energy supply in 2015 (IEA, 2017e). Box plots in the lower panel show the minimum–maximum range (whiskers), interquartile range (box), and median (vertical thin black line). Symbols in the lower panel show the four pathway archetypes – S1 (white square), S2 (yellow square), S5 (black square), LED (white disc) – as well as the IEA’s Faster Transition Scenario (red disc). Pathways with no or limited overshoot included the Below- 1.5°C and 1.5°C-low-OS classes. rely on a large amount of BECCS to get to net-zero carbon emissions. The quantity of CO2 stored via CCS over this century in 1.5°C pathways The cumulative fossil and biomass CO2 stored through 2050 ranges from with no or limited overshoot ranges from zero to more than 1,200 zero to 300 GtCO2 across 1.5°C pathways with no or limited overshoot, GtCO2, (Figure 2.17). The IPCC Special Report on Carbon Dioxide with zero up to 140 GtCO2 from biomass captured and stored. Some Capture and Storage (IPCC, 2005) found that that, worldwide, it is pathways have very low fossil-fuel use overall, and consequently little likely that there is a technical potential of at least about 2,000 GtCO2 CCS applied to fossil fuels. In 1.5°C pathways where the 2050 coal use of storage capacity in geological formations. Furthermore, the IPCC remains above 20 EJ yr−1 in 2050, 33–100% is combined with CCS. (2005) recognized that there could be a much larger potential for While deployment of CCS for natural gas and coal vary widely across geological storage in saline formations, but the upper limit estimates pathways, there is greater natural gas primary energy connected to are uncertain due to lack of information and an agreed methodology. CCS than coal primary energy connected to CCS in many pathways Since IPCC (2005), understanding has improved and there have been (Figure 2.17). detailed regional surveys of storage capacity (Vangkilde-Pedersen et al., 2009; Ogawa et al., 2011; Wei et al., 2013; Bentham et al., CCS combined with fossil-fuel use remains limited in some 1.5°C 2014; Riis and Halland, 2014; Warwick et al., 2014; NETL, 2015) and pathways (Rogelj et al., 2018), as the limited 1.5°C carbon budget improvement and standardization of methodologies (e.g., Bachu et al. penalizes CCS if it is assumed to have incomplete capture rates or if 2007a, b). Dooley (2013) synthesized published literature on both the fossil fuels are assumed to continue to have significant lifecycle GHG global geological storage resource as well as the potential demand emissions (Pehl et al., 2017). However, high capture rates are technically for geologic storage in mitigation pathways, and found that the achievable now at higher cost, although efforts to date have focussed cumulative demand for CO2 storage was small compared to a practical on reducing the costs of capture (IEAGHG, 2006; NETL, 2013). storage capacity estimate (as defined by Bachu et al., 2007a) of 3,900 GtCO2 worldwide. Differences remain, however, in estimates of storage capacity due to, for example, the potential storage limitations of 135 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development 2 Figure 2.17 | CCS deployment in 1.5°C and 2°C pathways for (a) biomass, (b) coal and (c) natural gas (EJ of primary energy) and (d) the cumulative quantity of fossil (including from, e.g., cement production) and biomass CO2 stored via CCS (in GtCO2 stored). TBox plots show median, interquartile range and full range of pathways in each temperature class. Pathway temperature classes (Table 2.1), illustrative pathway archetypes, and the IEA’s Faster Transition Scenario (IEA WEM) (OECD/IEA and IRENA, 2017) are indicated in the legend. subsurface pressure build-up (Szulczewski et al., 2014) and assumptions 2.4.3 Energy End-Use Sectors on practices that could manage such issues (Bachu, 2015). Kearns et al. (2017) constructed estimates of global storage capacity of 8,000 to Since the power sector is almost decarbonized by mid-century in both 55,000 GtCO2 (accounting for differences in detailed regional and local 1.5°C and 2°C pathways, major differences come from CO2 emission estimates), which is sufficient at a global level for this century, but reductions in end-use sectors. Energy-demand reductions are key found that at a regional level, robust demand for CO2 storage exceeds and common features in 1.5˚C pathways, and they can be achieved their lower estimate of regional storage available for some regions. by efficiency improvements and various specific demand-reduction However, storage capacity is not solely determined by the geological measures. Another important feature is end-use decarbonization setting, and Bachu (2015) describes storage engineering practices including by electrification, although the potential and challenges in that could further extend storage capacity estimates. In summary, each end-use sector vary significantly. the storage capacity of all of these global estimates is larger than the cumulative CO2 stored via CCS in 1.5°C pathways over this century. In the following sections, the potential and challenges of CO2 emission reductions towards 1.5°C and 2°C- consistent pathways are discussed There is uncertainty in the future deployment of CCS given the for each end-use energy sector (industry, buildings, and transport). limited pace of current deployment, the evolution of CCS technology For this purpose, two types of pathways are analysed and compared: that would be associated with deployment, and the current lack of IAM (integrated assessment modelling) studies and sectoral (detailed) incentives for large-scale implementation of CCS (Bruckner et al., 2014; studies. IAM data are extracted from the database that was compiled Clarke et al., 2014; Riahi et al., 2017). Given the importance of CCS in for this assessment (see Supplementary Material 2.SM.1.3), and the most mitigation pathways and its current slow pace of improvement, sectoral data are taken from a recent series of publications; ‘Energy the large-scale deployment of CCS as an option depends on the further Technology Perspectives’ (ETP) (IEA, 2014, 2015b, 2016a, 2017a), the development of the technology in the near term. Chapter 4 discusses IEA/IRENA report (OECD/IEA and IRENA, 2017), and the Shell Sky report how progress on CCS might be accelerated. (Shell International B.V., 2018). The IAM pathways are categorized according to their temperature rise in 2100 and the overshoot of temperature during the century (see Table 2.1 in Section 2.1). Since the number of Below-1.5°C pathways is small, the following analyses 136 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 focus only on the features of the 1.5°C-low-OS and 1.5°C-high-OS pathways (hereafter denoted together as 1.5°C overshoot pathways or IAM-1.5DS-OS) and 2°C-consistent pathways (IAM-2DS). In order to show the diversity of IAM pathways, we again show specific data from the four illustrative pathways archetypes used throughout this chapter (see Sections 2.1 and 2.3). IEA ETP-B2DS (‘Beyond 2 Degrees’) and ETP-2DS are pathways with a 50% chance of limiting temperature rise below 1.75°C and 2°C by 2100, respectively (IEA, 2017a). The IEA-66%2DS pathway keeps global mean temperature rise below 2°C, not just in 2100 but also over the course of the 21st century, with a 66% chance of being below 2°C by 2100 (OECD/IEA and IRENA, 2017). The comparison of CO2 emission trajectories between ETP-B2DS and IAM-1.5DS-OS show that these are consistent up to 2060 (Figure 2.18). IEA scenarios assume Figure 2.18 | Comparison of CO2 emission trajectories of sectoral pathways (IEA ETP-B2DS, ETP-2DS, IEA-66%2DS, Shell-Sky) with the ranges of IAM pathway (2DS 2 that only a very low level of BECCS is deployed to help offset emissions are 2°C-consistent pathways and 1.5DS-OS are1.5°C overshoot pathways). The CO2 in difficult-to-decarbonize sectors, and that global energy-related CO2 emissions shown here are the energy-related emissions, including industrial process emissions do not turn net negative at any time but stay at zero from emissions. 2060 to 2100 (IEA, 2017a). Therefore, although its temperature rise in 2100 is below 1.75°C rather than below 1.5°C, this scenario can give information related to a 1.5°C overshoot pathway up to 2050. Figure 2.19 shows the structure of global final energy demand in 2030 The trajectory of IEA-66%2DS (also referred to in other publications as and 2050, indicating the trend toward electrification and fossil fuel IEA’s ‘Faster Transition Scenario’) lies between IAM-1.5DS-OS and IAM- usage reduction. This trend is more significant in 1.5°C pathways than 2DS pathway ranges, and IEA-2DS stays in the range of 2°C-consistent 2°C pathways. Electrification continues throughout the second half of IAM pathways. The Shell-Sky scenario aims to hold the temperature the century, leading to a 3.5- to 6-fold increase in electricity demand rise to well below 2°C, but it is a delayed action pathway relative to (interquartile range; median 4.5) by the end of the century relative to others, as can be seen in Figure 2.18. today (Grubler et al., 2018; Luderer et al., 2018). Since the electricity sector is completely decarbonized by mid-century in 1.5°C pathways Energy-demand reduction measures are key to reducing CO2 emissions (see Figure 2.20), electrification is the primary means to decarbonize from end-use sectors for low-carbon pathways. The upstream energy energy end-use sectors. reductions can be from several times to an order of magnitude larger than the initial end-use demand reduction. There are interdependencies The CO2 emissions 6 of end-use sectors and carbon intensity are shown among the end-use sectors and between energy-supply and end-use in Figure 2.20. The projections of IAMs and IEA studies show rather sectors, which elevate the importance of a wide, systematic approach. different trends, especially in the carbon intensity. These differences As shown in Figure 2.19, global final energy consumption grows by 30% come from various factors, including the deployment of CCS, the and 10% from 2010 to 2050 for 2°C-consistent and 1.5°C overshoot level of fuel switching and efficiency improvements, and the effect pathways from IAMs, respectively, while much higher growth of 75% is of structural and behavioural changes. IAM projections are generally projected for reference scenarios. The ranges within a specific pathway optimistic for the industry sectors, but not for buildings and transport class are due to a variety of factors as introduced in Section 2.3.1, as sectors. Although GDP increases by a factor of 3.4 from 2010 to 2050, well as differences between modelling frameworks. The important the total energy consumption of end-use sectors grows by only about energy efficiency and conservation improvements that facilitate many 30% and 20% in 1.5°C overshoot and 2°C-consistent pathways, of the 1.5°C pathways raise the issue of potential rebound effects respectively. However, CO2 emissions would need to be reduced further (Saunders, 2015), which, while promoting development, can make to achieve the stringent temperature limits. Figure 2.20 shows that the the achievement of low-energy demand futures more difficult than reduction in CO2 emissions of end-use sectors is larger and more rapid modelling studies anticipate (see Sections 2.5 and 2.6). in 1.5°C overshoot than 2°C-consistent pathways, while emissions from the power sector are already almost zero in 2050 in both sets Final energy demand is driven by demand in energy services for of pathways, indicating that supply-side emissions reductions are mobility, residential and commercial activities (buildings), and almost fully exploited already in 2°C-consistent pathways (see Figure manufacturing. Projections of final energy demand depend heavily on 2.20) (Rogelj et al., 2015b, 2018; Luderer et al., 2016b). The emission assumptions about socio-economic futures as represented by the SSPs reductions in end-use sectors are largely made possible by efficiency (Bauer et al., 2017) (see Sections 2.1, 2.3 and 2.5). The structure of this improvements, demand reduction measures and electrification, but demand drives the composition of final energy use in terms of energy the level of emissions reductions varies across end-use sectors. While carriers (electricity, liquids, gases, solids, hydrogen etc.). the carbon intensity of the industry and buildings sectors decreases 6 This section reports ‘direct’ CO2 emissions as reported for pathways in the database for the report. As shown below, the emissions from electricity are nearly zero around 2050, so the impact of indirect emissions on the whole emission contributions of each sector is very small in 2050. 137 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Energy consumption and CO2 emissions of Demand-side 700 Final Energy 60 Carbon Intensity a c 600 50 2010 level 40 500 30 400 20 2010 level 300 10 200 0 30 b Carbon Emissions 25 20 2DS 1.5DS-OS 2DS 1.5DS-OS 2010 level 2030 2050 15 10 Max IAM-archetypes Sectoral 2 5 75% Percentile S1 Shell-Sky 0 Median S2 IEA-66%2DS 25% Percentile S5 IEA-2DS Min LED IEA-B2DS 2DS 1.5DS-OS 2DS 1.5DS-OS 2030 2050 400 d Electricity Liquid 120 Coal Biomass 100 300 80 200 60 40 100 20 2010 level 0 0 2DS 1.5DS 2DS 1.5DS 2DS 1.5DS 2DS 1.5DS 2DS 1.5DS 2DS 1.5DS 2DS 1.5DS 2DS 1.5DS 2030 2050 2030 2050 2030 2050 2030 2050 Figure 2.19 | (a) Global final energy, (b) direct CO2 emissions from the all energy demand sectors, (c) carbon intensity, and (d) structure of final energy (electricity, liquid fuel, coal, and biomass). The squares and circles indicate the IAM archetype pathways and diamonds indicate the data of sectoral scenarios. The red dotted line indicates the 2010 level. H2DS = Higher-2°C, L2DS = Lower-2°C, 1.5DS-H = 1.5°C-high-OS, 1.5DS-L = 1.5°C-low-OS. The label 1.5DS combines both high and low overshoot 1.5°C-consistent pathway. See Section 2.1 for descriptions. to a very low level of around 10 gCO2 MJ -1, the carbon intensity of pulp and paper industries accounted for close to 66% of final energy transport becomes the highest of any sector by 2040 due to its higher demand and 72% of direct industry-sector emissions in 2014 (IEA, reliance on oil-based fuels. In the following subsections, the potential 2017a). In terms of end-uses, the bulk of energy in manufacturing and challenges of CO2 emission reduction in each end-use sector are industries is required for process heating and steam generation, discussed in detail. while most electricity (but smaller shares of total final energy) is used for mechanical work (Banerjee et al., 2012; IEA, 2017a). 2.4.3.1 Industry As shown in Figure 2.21, a major share of the additional emission The industry sector is the largest end-use sector, both in terms of reductions required for 1.5°C-overshoot pathways compared to final energy demand and GHG emissions. Its direct CO2 emissions those in 2°C-consistent pathways comes from industry. Final energy, currently account for about 25% of total energy-related and process CO2 emissions, and carbon intensity are consistent in IAM and CO2 emissions, and emissions have increased at an average annual sectoral studies, but in IAM-1.5°C-overshoot pathways the share of rate of 3.4% between 2000 and 2014, significantly faster than total electricity is higher than IEA-B2DS (40% vs. 25%) and hydrogen is CO2 emissions (Hoesly et al., 2018). In addition to emissions from also considered to have a share of about 5% versus 0%. In 2050, final the combustion of fossil fuels, non-energy uses of fossil fuels in the energy is increased by 30% and 5% compared with the 2010 level petrochemical industry and metal smelting, as well as non-fossil fuel (red dotted line) for 1.5°C-overshoot and 2°C-consistent pathways, process emissions (e.g., from cement production) contribute a small respectively, but CO2 emissions are decreased by 80% and 50% amount (~5%) to the sector’s CO2 emissions inventory. Material and carbon intensity by 80% and 60%, respectively. This additional industries are particularly energy and emissions intensive: together, decarbonization is brought by switching to low-carbon fuels and CCS the steel, non-ferrous metals, chemicals, non-metallic minerals, and deployment. 138 Final Energy (EJ) CO2 Emissions (GtCO2) Final Energy Consumption (EJ) 2DS- H2DS L2DS 1.5DS- 1.5DS-H Sectoral 1.5DS-L Sectoral 2DS- H2DS L2DS 1.5DS- Sectoral 1.5DS-H 1.5DS-L Sectoral Carbon Intensity (gCO2/MJ) 2DS- H2DS Sectoral L2DS 1.5DS- 1.5DS-H 1.5DS-L Sectoral 2DS- Sectoral H2DS L2DS 1.5DS- 1.5DS-H 1.5DS-L Sectoral Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 2 Figure 2.20 | Comparison of (a) direct CO2 emissions and (b) carbon intensity of the power and energy end-use sectors (industry, buildings, and transport sectors) between IAMs and sectoral studies (IEA-ETP and IEA/IRENA). Diamond markers in panel (b) show data for IEA-ETP scenarios (2DS and B2DS), and IEA/IRENA scenario (66%2DS). Note: for the data from IAM studies, there is rather large variation of projections for each indicator. Please see the details in the following figures in each end- use sector section. Industry Sector 300 (a) Final Energy (c) Carbon Intensity 60 250 2010 level 200 40 150 2010 level 20 100 50 0 15 (b) Carbon Emissions 10 2DS 1.5DS-OS 2DS 1.5DS-OS 2030 2050 2010 level 5 Max IAM-archetypes Sectoral 75% Percentile S1 Shell-Sky Median S2 IEA-66%2DS 0 25% Percentile S5 IEA-2DS Min LED IEA-B2DS 2DS 1.5DS-OS 2DS 1.5DS-OS 2030 2050 150 (d) Electricity 50 Biomass 125 40 100 30 75 20 50 10 25 0 2DS 1.5DS-OS 2DS 1.5DS-OS 2DS 1.5DS-OS 2DS 1.5DS-OS 2030 2050 2030 2050 Figure 2.21 | Comparison of (a) final energy, (b) direct CO2 emissions, (c) carbon intensity, (d) electricity and biomass consumption in the industry sector between IAM and sectoral studies. The squares and circles indicate the IAM archetype pathways and diamonds the data of sectoral scenarios. The red dotted line indicates the 2010 level. H2DS = Higher-2°C, L2DS = Lower-2°C, 1.5DS-H = 1.5°C-high-OS, 1.5DS-L = 1.5°C-low-OS. The label 1.5DS combines both high and low overshoot 1.5°C-consistent pathways. Section 2.1 for descriptions. 139 Electricity consumption (EJ) (CO2 Emissions (GtCO2) Final Energy Consumption (EJ) 2DS- 2DS- H2DS H2DS L2DS L2DS Lore 1.5DS- 1.5DS- H1.5DS 1.5DS-H L1.5DS 1.5DS-L Sectoral Sectoral 2DS- 2DS- H2DS-50 H2DS L2DS-66 L2DS 1.5DS- 1.5DS- H1.5DS 1.5DS-H L1.5DS 1.5DS-L Sectoral Sectoral Biomass consumption (EJ) Carbon Intensity (gCO2/MJ) 2DS- 2DS- H2DS H2DS L2DS L2DS 1.5DS- 1.5DS- H1.5DS 1.5DS-H L1.5DS 1.5DS-L Sectoral Sectoral 2DS- 2DS- H2DS-50 H2DS L2DS-66 L2DS 1.5DS- 1.5DS- H1.5DS 1.5DS-H L1.5DS 1.5DS-L Sectoral Sectoral Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Broadly speaking, the industry sector’s mitigation measures can century, CO2 emissions per unit of electricity are projected to decrease be categorized in terms of the following five strategies: (i) reducing to near zero in both sets of pathways (see Figure 2.20). An accelerated demand, (ii) energy efficiency, (iii) increasing electrification of energy electrification of the industry sector thus becomes an increasingly demand, (iv) reducing the carbon content of non-electric fuels, and powerful mitigation option. In the IAM pathways, the share of electricity (v) deploying innovative processes and application of CCS. IEA ETP increases up to 30% by 2050 in 1.5°C-overshoot pathways (Figure estimates the relative contribution of different measures for CO2 2.21) from 20% in 2010. Some industrial fuel uses are substantially emission reduction in their B2DS scenario compared with their reference more difficult to electrify than others, and electrification would have scenario in 2050 as follows: energy efficiency 42%, innovative process other effects on the process, including impacts on plant design, cost and CCS 37%, switching to low-carbon fuels and feedstocks 13% and and available process integration options (IEA, 2017a).7 material efficiency (include efficient production and use to contribute to demand reduction) 8%. The remainder of this section delves more In 1.5°C-overshoot pathways, the carbon intensity of non-electric fuels deeply into the potential mitigation contributions of these strategies as consumed by industry decreases to 16 gCO MJ−12 by 2050, compared well as their limitations. to 25 gCO −12 MJ in 2°C-consistent pathways. Considerable carbon intensity reductions are already achieved by 2030, largely via a rapid 2 Reduction in the use of industrial materials, while delivering similar phase-out of coal. Biomass becomes an increasingly important energy services, or improving the quality of products could help to reduce carrier in the industry sector in deep-decarbonization pathways, but energy demand and overall system-level CO2 emissions. Strategies primarily in the longer term (in 2050, biomass accounts for only 10% include using materials more intensively, extending product lifetimes, of final energy consumption even in 1.5°C-overshoot pathways). In increasing recycling, and increasing inter-industry material synergies, addition, hydrogen plays a considerable role as a substitute for fossil- such as clinker substitution in cement production (Allwood et al., 2013; based non-electric energy demands in some pathways. IEA, 2017a). Related to material efficiency, use of fossil-fuel feedstocks could shift to lower-carbon feedstocks, such as from oil to natural gas Without major deployment of new sustainability-oriented low-carbon and biomass, and end-uses could shift to more sustainable materials, industrial processes, the 1.5°C-overshoot target is difficult to achieve. such as biomass-based materials, reducing the demand for energy- Bringing such technologies and processes to commercial deployment intensive materials (IEA, 2017a). requires significant investment in research and development. Some examples of innovative low-carbon process routes include: new Reaping energy efficiency potentials hinges critically on advanced steelmaking processes such as upgraded smelt reduction and upgraded management practices, such as energy management systems, in direct reduced iron, inert anodes for aluminium smelting, and full oxy- industrial facilities as well as targeted policies to accelerate adoption of fuelling kilns for clinker production in cement manufacturing (IEA, the best available technology (see Section 2.5). Although excess energy, 2017a). usually as waste heat, is inevitable, recovering and reusing this waste heat under economically and technically viable conditions benefits CCS plays a major role in decarbonizing the industry sector in the the overall energy system. Furthermore, demand-side management context of 1.5°C and 2°C pathways, especially in industries with strategies could modulate the level of industrial activity in line with higher process emissions, such as cement, iron and steel industries. the availability of resources in the power system. This could imply a In 1.5°C-overshoot pathways, CCS in industry reaches 3 GtCO2 yr −1 shift away from peak demand and as power supply decarbonizes, this by 2050, albeit with strong variations across pathways. Given the demand-shaping potential could shift some load to times with high projected long-lead times and need for technological innovation, early portions of low-carbon electricity generation (IEA, 2017a). scale-up of industry-sector CCS is essential to achieving the stringent temperature target. Development and demonstration of such projects In the industry sector, energy demand increases more than 40% has been slow, however. Currently, only two large-scale industrial CCS between 2010 and 2050 in baseline scenarios. However, in the projects outside of oil and gas processing are in operation (Global 1.5°C-overshoot and 2°C-consistent pathways from IAMs, the increase CCS Institute, 2016). The estimated current cost8 of CO2 avoided (in is only 30% and 5%, respectively (Figure 2.21). These energy-demand USD2015) ranges from $20–27 tCO −12 for gas processing and bio- reductions encompass both efficiency improvements in production and ethanol production, and $60–138 tCO −12 for fossil fuel-fired power reductions in material demand, as most IAMs do not discern these two generation up to $104–188 tCO −12 for cement production (Irlam, 2017). factors. 2.4.3.2 Buildings CO2 emissions from industry increase by 30% in 2050 compared to 2010 in baseline scenarios. By contrast, these emissions are reduced In 2014, the buildings sector accounted for 31% of total global final by 80% and 50% relative to 2010 levels in 1.5°C-overshoot and energy use, 54% of final electricity demand, and 8% of energy-related 2°C-consistent pathways from IAMs, respectively (Figure 2.21). By mid- CO2 emissions (excluding indirect emissions due to electricity). When 7 Electrification can be linked with the heating and drying process by electric boilers and electro-thermal processes, and also with low-temperature heat demand by heat pumps. In the iron and steel industry, hydrogen produced by electrolysis can be used as a reduction agent of iron instead of coke. Excess resources, such as black liquor, will provide the opportunity to increase the systematic efficiency to use for electricity generation. 8 These are first-of-a-kind (FOAK) cost data. 140 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 Buildings Sector 250 (a) Final Energy 60 (c) Carbon Intensity 50 200 40 150 30 2010 level 20 2010 level 100 10 50 0 7 (b) Carbon Emissions 6 5 2DS 1.5DS-OS 2DS 1.5DS-OS 4 2030 2050 2010 level 3 2 Max IAM-archetypes Sectoral 1 75% Percentile S1 Shell-Sky Median S2 IEA-66%2DS 0 225% Percentile S5 IEA-2DS Min LED IEA-B2DS 2DS 1.5DS-OS 2DS 1.5DS-OS 2030 2050 175 (d) Electricity 50 Biomass 150 40 125 30 100 20 75 50 10 25 0 2DS 1.5DS-OS 2DS 1.5DS-OS 2DS 1.5DS-OS 2DS 1.5DS-OS 2030 2050 2030 2050 Figure 2.22 | Comparison of (a) final energy, (b) direct CO2 emissions, (c) carbon intensity, (d) electricity and biomass consumption in the buildings sector between IAM and sectoral studies. The squares and circles indicate the IAM archetype pathways and diamonds the data of sectoral scenarios. The red dotted line indicates the 2010 level. H2DS = Higher-2°C, L2DS = Lower-2°C, 1.5DS-H = 1.5°C-high-OS, 1.5DS-L = 1.5°C-low-OS. The label 1.5DS combines both high and low overshoot 1.5°C-consistent pathways. Section 2.1 for descriptions. upstream electricity generation is taken into account, buildings were with 50% in 2°C-consistent pathways (Figure 2.22). Electrification responsible for 23% of global energy-related CO2 emissions, with one- contributes to the reduction of direct CO2 emissions by replacing third of those from direct fossil fuel consumption (IEA, 2017a). carbon-intensive fuels, like oil and coal. Furthermore, when combined with a rapid decarbonization of the power system (see Section 2.4.1) it Past growth of energy consumption has been mainly driven by also enables further reduction of indirect CO2 emissions from electricity. population and economic growth, with improved access to electricity, Sectoral bottom-up models generally estimate lower electrification and higher use of electrical appliances and space cooling resulting potentials for the buildings sector in comparison to global IAMs (see from increasing living standards, especially in developing countries Figure 2.22). Besides CO2 emissions, increasing global demand for (Lucon et al., 2014). These trends will continue in the future and in air conditioning in buildings may also lead to increased emissions of 2050, energy consumption is projected to increase by 20% and 50% HFCs in this sector over the next few decades. Although these gases compared to 2010 in the IAM-1.5°C-overshoot and 2°C-consistent are currently a relatively small proportion of annual GHG emissions, pathways, respectively (Figure 2.22). However, sectoral studies (IEA- their use in the air conditioning sector is expected to grow rapidly over ETP scenarios) show different trends. Energy consumption in 2050 the next few decades if alternatives are not adopted. However, their decreases compared to 2010 in ETP-B2DS, and the reduction rate of projected future impact can be significantly mitigated through better CO2 emissions is higher than in IAM pathways (Figure 2.22). Mitigation servicing and maintenance of equipment and switching of cooling options are often more widely covered in sectoral studies (Lucon et al., gases (Shah et al., 2015; Purohit and Höglund-Isaksson, 2017). 2014), leading to greater reductions in energy consumption and CO2 emissions. IEA-ETP (IEA, 2017a) analysed the relative importance of various technology measures toward the reduction of energy and CO2 Emissions reductions are driven by a clear tempering of energy emissions in the buildings sector. The largest energy savings potential demand and a strong electrification of the buildings sector. The share is in heating and cooling demand, largely due to building envelope of electricity in 2050 is 60% in 1.5°C-overshoot pathways, compared improvements and high efficiency and renewable equipment. In the 141 Electricity consumption (EJ) CO Emissions (GtCO2) Final Energy Consumption (EJ)2 2DS- 2DS- H2DS H2DS L2DS L2DS 1.5DS- 1.5DS- 1.5DS-H 1.5DS-H 1.5DS-L 1.5DS-L Sectoral Sectoral 2DS- 2DS- H2DS H2DS L2DS L2DS 1.5DS- 1.5DS- 1.5DS-H 1.5DS-H 1.5DS-L 1.5DS-L Sectoral Sectoral Biomass consumption (EJ) Carbon Intensity (gCO2/MJ) 2DS- 2DS- H2DS H2DS L2DS L2DS 1.5DS- 1.5DS- 1.5DS-H 1.5DS-H 1.5DS-L 1.5DS-L Sectoral Sectoral 2DS- 2DS- H2DS H2DS L2DS L2DS 1.5DS- 1.5DS- 1.5DS-H 1.5DS-H 1.5DS-L 1.5DS-L Sectoral Sectoral Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development ETP-B2DS, energy demand for space heating and cooling is 33% lower structural changes in this sector. The former contributes to reduction in 2050 than in the reference scenario, and these reductions account of CO2 emissions and the latter to reduction of energy consumption. for 54% of total reductions from the reference scenario. Energy savings from shifts to high-performance lighting, appliances, and water heating Deep emissions reductions in the transport sector would be achieved by equipment account for a further 24% of the total reduction. The long- several means. Technology-focused measures such as energy efficiency term, strategic shift away from fossil-fuel use in buildings, alongside and fuel-switching are two of these. Structural changes that avoid or the rapid uptake of energy efficient, integrated and renewable shift transport activity are also important. While the former solutions energy technologies (with clean power generation), leads to a drastic (technologies) always tend to figure into deep decarbonization reduction of CO2 emissions. In ETP-B2DS, the direct CO2 emissions are pathways in a major way, this is not always the case with the latter, 79% lower than the reference scenario in 2050, and the remaining especially in IAM pathways. Comparing different types of global emissions come mainly from the continued use of natural gas. transport models, Yeh et al. (2016) find that sectoral (intensive) studies generally envision greater mitigation potential from structural changes The buildings sector is characterized by very long-living infrastructure, in transport activity and modal choice. Though, even there, it is primarily and immediate steps are hence important to avoid lock-in of inefficient the switching of passengers and freight from less- to more-efficient 2 carbon and energy-intensive buildings. This applies both to new buildings travel modes (e.g., cars, trucks and airplanes to buses and trains) that is in developing countries where substantial new construction is expected the main strategy; other actions, such as increasing vehicle load factors in the near future and to retrofits of existing building stock in developed (occupancy rates) and outright reductions in travel demand (e.g., as regions. This represents both a significant risk and opportunity for a result of integrated transport, land-use and urban planning), figure mitigation.9 A recent study highlights the benefits of deploying the most much less prominently. Whether these dynamics accurately reflect the advanced renovation technologies, which would avoid lock-in into less actual mitigation potential of structural changes in transport activity efficient measures (Güneralp et al., 2017). Aside from the effect of building and modal choice is a point of investigation. According to the recent envelope measures, adoption of energy-efficient technologies such as IEA-ETP scenarios, the share of avoid (reduction of mobility demand) heat pumps and, more recently, light-emitting diodes is also important and shift (shifting to more efficient modes) measures in the reduction of for the reduction of energy and CO2 emissions (IEA, 2017a). Consumer CO2 emissions from the reference to B2DS scenarios in 2050 amounts choices, behaviour and building operation can also significantly affect to 20% (IEA, 2017a). energy consumption (see Chapter 4, Section 4.3). The potential and strategies to reduce energy consumption and CO2 2.4.3.3 Transport emissions differ significantly among transport modes. In ETP-B2DS, the shares of energy consumption and CO2 emissions in 2050 for each Transport accounted for 28% of global final energy demand and 23% mode are rather different (see Table 2.8), indicating the challenge of global energy-related CO2 emissions in 2014. Emissions increased by of decarbonizing heavy-duty vehicles (HDV, trucks), aviation, and 2.5% annually between 2010 and 2015, and over the past half century shipping. The reduction of CO2 emissions in the whole sector from the sector has witnessed faster emissions growth than any other. The the reference scenario to ETP-B2DS is 60% in 2050, with varying transport sector is the least diversified energy end-use sector; the contributions per mode (Table 2.8). Since there is no silver bullet for sector consumed 65% of global oil final energy demand, with 92% of this deep decarbonization, every possible measure would be required transport final energy demand consisting of oil products (IEA, 2017a), to achieve this stringent emissions outcome. The contribution of suggesting major challenges for deep decarbonization. various measures for the CO2 emission reduction from the reference scenario to the IEA-B2DS in 2050 can be decomposed to efficiency Final energy, CO2 emissions, and carbon intensity for the transport improvement (29%), biofuels (36%), electrification (15%), and avoid/ sector are shown in Figure 2.23. The projections of IAMs are more shift (20%) (IEA, 2017a). It is noted that the share of electrification pessimistic than IEA-ETP scenarios, though both clearly project deep becomes larger compared with older studies, reflected by the recent cuts in energy consumption and CO2 emissions by 2050. For example, growth of electric vehicle sales worldwide. Another new trend is the 1.5°C-overshoot pathways from IAMs project a reduction of 15% in allocation of biofuels to each mode of transport. In IEA-B2DS, the total energy consumption between 2015 and 2050, while ETP-B2DS projects amount of biofuels consumed in the transport sector is 24EJ10 in 2060, a reduction of 30% (Figure 2.23). Furthermore, IAM pathways are and allocated to LDV (light-duty vehicles, 17%), HDV (35%), aviation generally more pessimistic in the projections of CO2 emissions and (28%), and shipping (21%), that is, more biofuels is allocated to the carbon intensity reductions. In AR5 (Clarke et al., 2014; Sims et al., difficult-to-decarbonize modes (see Table 2.8). 2014), similar comparisons between IAMs and sectoral studies were performed and these were in good agreement with each other. Since In road transport, incremental vehicle improvements (including the AR5, two important changes can be identified: rapid growth of engines) are relevant, especially in the short to medium term. Hybrid electric vehicle sales in passenger cars, and more attention towards electric vehicles are also instrumental to enabling the transition from 9 In this section, we only discuss the direct emissions from the sector, but the selection of building materials has a significant impact on the reduction of energy and emissions during production, such as shift from the steel and concrete to wood-based materials. 10 This is estimated for the biofuels produced in a “sustainable manner” from non-food crop feedstocks, which are capable of delivering significant lifecycle GHG emissions savings compared with fossil fuel alternatives, and which do not directly compete with food and feed crops for agricultural land or cause adverse sustainability impacts. 142 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 Table 2.8 | Transport sector indicators by mode in 2050 (IEA, 2017a). Share of energy consumption, biofuel consumption, CO2 emissions, and reduction of energy consumption and CO2 emissions from 2014. (CO2 emissions are well- to-wheel emissions, including the emission during the fuel production.), LDV: light duty vehicle, HDV: heavy duty vehicle. Share of Each Mode (%) Reduction from 2014 (%) Energy Biofuel CO2 Energy CO2 LDV 36 17 30 51 81 HDV 33 35 36 8 56 Rail 6 - –1 –136 107 Aviation 12 28 14 14 56 Shipping 17 21 21 26 29 internal combustion engine vehicles to electric vehicles, especially transport modes. Both modes would need to pursue highly ambitious plug-in hybrid electric vehicles. Electrification is a powerful measure to efficiency improvements and use of low-carbon fuels. In the near and 2 decarbonize short-distance vehicles (passenger cars and two and three medium term, this would be advanced biofuels while in the long term wheelers) and the rail sector. In road freight transport (trucks), systemic it could be hydrogen as direct use for shipping or an intermediate improvements (e.g., in supply chains, logistics, and routing) would be product for synthetic fuels for both modes (IEA, 2017a). effective measures in conjunction with efficiency improvement of vehicles. Shipping and aviation are more challenging to decarbonize, The share of low-carbon fuels in the total transport fuel mix while their demand growth is projected to be higher than other increases to 10% and 16% by 2030 and to 40% and 58% by 2050 Transport Sector (a) Final Energy 80 (c) Carbon Intensity 200 2010 level 60 150 40 100 2010 level 20 50 0 14 (b) Carbon Emissions 12 10 2DS 1.5DS-OS 2DS 1.5DS-OS 8 2030 20502010 level 6 4 Max IAM-archetypes Sectoral 2 75% Percentile S1 Shell-Sky Median 0 S2 IEA-66%2DS25% Percentile S5 IEA-2DS Min LED IEA-B2DS 2DS 1.5DS-OS 2DS 1.5DS-OS 2030 2050 89 40 (d) 61 68 Electricity 40 Biofuel 30 30 20 20 10 10 0 0 2DS 1.5DS-OS 2DS 1.5DS-OS 2DS 1.5DS-OS 2DS 1.5DS-OS 2030 2050 2030 2050 Figure 2.23 | Comparison of (a) final energy, (b) direct CO2 emissions, (c) carbon intensity, (d) electricity and biofuel consumption in the transport sector between IAM and sectoral studies. The squares and circles indicate the IAM archetype pathways and diamonds the data of sectoral scenarios. The red dotted line indicates the 2010 level. H2DS = Higher-2°C, L2DS = Lower-2°C, 1.5DS-H = 1.5°C-high-OS, 1.5DS-L = 1.5°C-low-OS. The label 1.5DS combines both high and low overshoot 1.5°C-consistent pathways. Section 2.1 for descriptions. 143 Electricity consumption (EJ) (CO2 Emissions (GtCO2) Final Energy Consumption (EJ) 2DS- 2DS- H2DS H2DS L2DS L2DS 1.5DS- 1.5DS- 1.5DS-H 1.5DS-H 1.5DS-L 1.5DS-L Sectoral Sectoral 2DS- 2DS- H2DS H2DS L2DS L2DS 1.5DS- 1.5DS- 1.5DS-H 1.5DS-H 1.5DS-L 1.5DS-L Sectoral Sectoral Biomass consumption (EJ) Carbon Intensity (gCO2/MJ) 2DS- 2DS- H2DS H2DS L2DS L2DS 1.5DS- 1.5DS- 1.5DS-H 1.5DS-H 1.5DS-L 1.5DS-L Sectoral Sectoral 2DS- 2DS- H2DS H2DS L2DS L2DS 1.5DS- 1.5DS- 1.5DS-H 1.5DS-H 1.5DS-L 1.5DS-L Sectoral Sectoral Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development in 1.5°C-overshoot pathways from IAMs and the IEA-B2DS pathway, at present only tangentially explored by the SSPs. Further assessments respectively. The IEA-B2DS scenario is on the more ambitious side, of AFOLU mitigation options are provided in other parts of this report especially in the share of electricity. Hence, there is wide variation and in the IPCC Special Report on Climate Change and Land (SRCCL). among scenarios, including the IAM pathways, regarding changes Chapter 4 provides an assessment of bioenergy (including feedstocks, in the transport fuel mix over the first half of the century. As seen in see Section 4.3.1), livestock management (Section 4.3.1), reducing Figure 2.23, the projections of energy consumption, CO2 emissions and rates of deforestation and other land-based mitigation options (as carbon intensity are quite different between IAM and ETP scenarios. mitigation and adaptation option, see Section 4.3.2), and BECCS, These differences can be explained by more weight on efficiency afforestation and reforestation options (including the bottom-up improvements and avoid/shift decreasing energy consumption, and literature of their sustainable potential, mitigation cost and side the higher share of biofuels and electricity accelerating the speed of effects, Section 4.3.7). Chapter 3 discusses impacts land-based CDR decarbonization in ETP scenarios. Although biofuel consumption and (Cross-Chapter Box 7 in Chapter 3). Chapter 5 assesses the sustainable electric vehicle sales have increased significantly in recent years, the development implications of AFOLU mitigation, including impacts on growth rates projected in these pathways would be unprecedented biodiversity (Section 5.4). Finally, the SRCCL will undertake a more and far higher than has been experienced to date. comprehensive assessment of land and climate change aspects. For 2 the sake of complementarity, this section focusses on the magnitude The 1.5°C pathways require an acceleration of the mitigation solutions and pace of land transitions in 1.5°C pathways, as well as on the already featured in 2°C-consistent pathways (e.g., more efficient implications of different AFOLU mitigation strategies for different land vehicle technologies operating on lower-carbon fuels), as well as types. The interactions with other societal objectives and potential those having received lesser attention in most global transport limitations of identified AFOLU measures link to these large-scale decarbonization pathways up to now (e.g., mode-shifting and travel evolutions, but these are assessed elsewhere (see above). demand management). Current-generation, global pathways generally do not include these newer transport sector developments, whereby Land-use changes until mid-century occur in the large majority of technological solutions are related to shifts in traveller’s behaviour. SSP pathways, both under stringent mitigation and in absence of mitigation (Figure 2.24). In the latter case, changes are mainly due 2.4.4 Land-Use Transitions and Changes to socio-economic drivers like growing demands for food, feed and in the Agricultural Sector wood products. General transition trends can be identified for many land types in 1.5°C pathways, which differ from those in baseline The agricultural and land system described together under the umbrella scenarios and depend on the interplay with mitigation in other of the AFOLU (agriculture, forestry, and other land use) sector plays sectors (Figure 2.24) (Popp et al., 2017; Riahi et al., 2017; Rogelj et an important role in 1.5°C pathways (Clarke et al., 2014; Smith and al., 2018). Mitigation that demands land mainly occurs at the expense Bustamante, 2014; Popp et al., 2017). On the one hand, its emissions of agricultural land for food and feed production. Additionally, some need to be limited over the course of this century to be in line with biomass is projected to be grown on marginal land or supplied from pathways limiting warming to 1.5°C (see Sections 2.2-3). On the other residues and waste, but at lower shares. Land for second-generation hand, the AFOLU system is responsible for food and feed production; energy crops (such as Miscanthus or poplar) expands by 2030 for wood production for pulp and construction; for the production of and 2050 in all available pathways that assume a cost-effective biomass that is used for energy, CDR or other uses; and for the supply of achievement of a 1.5°C temperature goal in 2100 (Figure 2.24), but non-provisioning (ecosystem) services (Smith and Bustamante, 2014). the scale depends strongly on underlying socio-economic assumptions Meeting all demands together requires changes in land use, as well as (see later discussion of land pathway archetypes). Reducing rates of in agricultural and forestry practices, for which a multitude of potential deforestation restricts agricultural expansion, and forest cover can options have been identified (Smith and Bustamante, 2014; Popp et expand strongly in 1.5°C and 2°C pathways alike compared to its al., 2017) (see also Supplementary Material 2.SM.1.2 and Chapter 4, extent in no-climate-policy baselines due to reduced deforestation and Section 4.3.1, 4.3.2 and 4.3.7). afforestation and reforestation measures. However, the extent to which forest cover expands varies highly across models in the literature, This section assesses the transformation of the AFOLU system, mainly with some models projecting forest cover to stay virtually constant or making use of pathways from IAMs (see Section 2.1) that are based on decline slightly. This is due to whether afforestation and reforestation is quantifications of the SSPs and that report distinct land-use evolutions included as a mitigation technology in these pathways and interactions in line with limiting warming to 1.5°C (Calvin et al., 2017; Fricko et with other sectors. al., 2017; Fujimori, 2017; Kriegler et al., 2017; Popp et al., 2017; Riahi et al., 2017; van Vuuren et al., 2017b; Doelman et al., 2018; Rogelj As a consequence of other land-use changes, pasture land is generally et al., 2018). The SSPs were designed to vary mitigation challenges projected to be reduced compared to both baselines in which no climate (O’Neill et al., 2014) (Cross-Chapter Box 1 in Chapter 1), including change mitigation action is undertaken and 2°C-consistent pathways. for the AFOLU sector (Popp et al., 2017; Riahi et al., 2017). The SSP Furthermore, cropland for food and feed production decreases in pathway ensemble hence allows for a structured exploration of AFOLU most 1.5°C pathways, both compared to a no-climate baseline and transitions in the context of climate change mitigation in line with relative to 2010. These reductions in agricultural land for food and feed 1.5°C, taking into account technological and socio-economic aspects. production are facilitated by intensification on agricultural land and in Other considerations, like food security, livelihoods and biodiversity, livestock production systems (Popp et al., 2017), as well as changes are also of importance when identifying AFOLU strategies. These are in consumption patterns (Frank et al., 2017; Fujimori, 2017) (see 144 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 2 Figure 2.24 | Overview of land-use change transitions in 2030 and 2050, relative to 2010 based on pathways based on the Shared Socio-Economic Pathways (SSPs) (Popp et al., 2017; Riahi et al., 2017; Rogelj et al., 2018). Grey: no-climate-policy baseline; green: 2.6 W m−2 pathways; blue: 1.9 W m−2 pathways. Pink: 1.9 W m−2 pathways grouped per underlying socio-economic assumption (from left to right: SSP1 sustainability, SSP2 middle-of-the-road, SSP5 fossil-fuelled development). Ranges show the minimum–maximum range across the SSPs. Single pathways are shown with plus signs. Illustrative archetype pathways are highlighted with distinct icons. Each panel shows the changes for a different land type. The 1.9 and 2.6 W m−2 pathways are taken as proxies for 1.5°C and 2°C pathways, respectively. The 2.6 W m−2 pathways are mostly consistent with the Lower-2°C and Higher-2°C pathway classes. The 1.9 W m−2 pathways are consistent with the 1.5°C-low-OS (mostly SSP1 and SSP2) and 1.5°C-high-OS (SSP5) pathway classes. In 2010, pasture was estimated to cover about 3–3.5 103 Mha, food and feed crops about 1.5–1.6 103 Mha, energy crops about 0–14 Mha and forest about 3.7–4.2 103 Mha, across the models that reported SSP pathways (Popp et al., 2017). When considering pathways limiting warming to 1.5°C with no or limited overshoot, the full set of scenarios shows a conversion of 50–1100 Mha of pasture into 0–600 Mha for energy crops, a 200 Mha reduction to 950 Mha increase forest, and a 400 Mha decrease to a 250 Mha increase in non-pasture agricultural land for food and feed crops by 2050 relative to 2010. The large range across the literature and the understanding of the variations across models and assumptions leads to medium confidence in the size of these ranges. also Chapter 4, Section 4.3.2 for an assessment of these mitigation in pasture and potentially strong increases in forest cover imply a options). For example, in a scenario based on rapid technological reversed dynamic compared to historical and baseline trends. This progress (Kriegler et al., 2017), global average cereal crop yields in suggests that distinct policy and government measures would be 2100 are assumed to be above 5 tDM ha−1 yr−1 in mitigation scenarios needed to achieve forest increases, particularly in a context of projected aiming at limiting end-of-century radiative forcing to 4.5 or 2.6 W m−2, increased bioenergy use. compared to 4 tDM ha−1 yr−1 in the SSP5 baseline to ensure the same food production. Similar improvements are present in 1.5°C variants Changes in the AFOLU sector are driven by three main factors: demand of such scenarios. Historically, cereal crop yields are estimated at changes, efficiency of production, and policy assumptions (Smith et 1 tDM ha−1 yr−1 and about 3 tDM ha−1 yr−1 in 1965 and 2010, al., 2013; Popp et al., 2017). Demand for agricultural products and respectively (calculations based on FAOSTAT, 2018). For aggregate other land-based commodities is influenced by consumption patterns energy crops, models assume 4.2–8.9 tDM ha−1 yr−1 in 2010, increasing (including dietary preferences and food waste affecting demand for to about 6.9–17.4 tDM ha−1 yr−1 in 2050, which fall within the range food and feed) (Smith et al., 2013; van Vuuren et al., 2018), demand for found in the bottom-up literature yet depend on crop, climatic zone, forest products for pulp and construction (including less wood waste), land quality and plot size (Searle and Malins, 2014). and demand for biomass for energy production (Lambin and Meyfroidt, 2011; Smith and Bustamante, 2014). Efficiency of agricultural and The pace of projected land transitions over the coming decades can forestry production relates to improvements in agricultural and forestry differ strongly between 1.5°C and baseline scenarios without climate practices (including product cascades, by-products and more waste- and change mitigation and from historical trends (Table 2.9). However, residue-based biomass for energy production), agricultural and forestry there is uncertainty in the sign and magnitude of these future land- yield increases, and intensification of livestock production systems use changes (Prestele et al., 2016; Popp et al., 2017; Doelman et al., leading to higher feed efficiency and changes in feed composition 2018). The pace of projected cropland changes overlaps with historical (Havlík et al., 2014; Weindl et al., 2015). Policy assumptions relate to trends over the past four decades, but in several cases also goes well the level of land protection, the treatment of food waste, policy choices beyond this range. By the 2030–2050 period, the projected reductions about the timing of mitigation action (early vs late), the choice and 145 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Table 2.9 | Annual pace of land-use change in baseline, 2°C and 1.5°C pathways. All values in Mha yr−1. The 2.6 W m−2 pathways are mostly consistent with the Lower-2°C and Higher-2°C pathway classes. The 1.9 W m−2 pathways are broadly consistent with the 1.5°C-low-OS (mostly SSP1 and SSP2) and 1.5°C-high-OS (SSP5) pathway classes. Baseline projections reflect land-use developments projected by integrated assessment models under the assumptions of the Shared Socio-Economic Pathways (SSPs) in absence of climate policies (Popp et al., 2017; Riahi et al., 2017; Rogelj et al., 2018). Values give the full range across SSP scenarios. According to the Food and Agriculture Organization of the United Nations (FAOSTAT, 2018), 4.9 billion hectares (approximately 40% of the land surface) was under agricultural use in 2005, either as cropland (1.5 billion hectares) or pasture (3.4 billion hectares). FAO data in the table are equally from FAOSTAT (2018). Annual Pace of Land-Use Change [Mha yr–1] Land Type Pathway Time Window Historical 2010–2030 2030–2050 1970–1990 1990–2010 Pasture 1.9 W m–2 [–14.6/3.0] [–28.7/–5.2] 8.7 0.9 2.6 W m–2 [–9.3/4.1] [–21.6/0.4] Permanent meadows Permanent meadows Baseline [–5.1/14.1] [–9.6/9.0] and pastures (FAO) and pastures (FAO) Cropland for food, 1.9 W m–2 [–12.7/9.0] [–18.5/0.1] 2 feed and material 2.6 W m–2 [–12.9/8.3] [–16.8/2.3] Baseline [–5.3/9.9] [–2.7/6.7] Cropland for energy 1.9 W m–2 [0.7/10.5] [3.9/34.8] 2.6 W m–2 [0.2/8.8] [2.0/22.9] Baseline [0.2/4.2] [–0.2/6.1] Total cropland (Sum 1.9 W m–2 [–6.8/12.8] [–5.8/26.7] 4.6 0.9 of cropland for food 2.6 W m–2 [–8.4/9.3] [–7.1/17.8] Arable land and Arable land and and feed & energy) Baseline [–3.0/11.3] [0.6/11.0] Permanent crops Permanent crops Forest 1.9 W m–2 [–4.8/23.7] [0.0/34.3] N.A. –5.6 2.6 W m–2 [–4.7/22.2] [–2.4/31.7] Forest (FAO) Forest (FAO) Baseline [–13.6/3.3] [–6.5/4.3] preference of land-based mitigation options (for example, the inclusion land-related GHG emissions (especially related to deforestation) of afforestation and reforestation as mitigation options), interactions has been shown by several studies (Calvin et al., 2017; Fricko et al., with other sectors (Popp et al., 2017), and trade (Schmitz et al., 2012; 2017; Fujimori, 2017). Ultimately, there are also interactions between Wiebe et al., 2015). these three factors and the wider society and economy, for example, if CDR technologies that are not land-based are deployed (like direct A global study (Stevanović et al., 2017) reported similar GHG reduction air capture – DACCS, see Chapter 4, Section 4.3.7) or if other sectors potentials for both production-side (agricultural production measures over- or underachieve their projected mitigation contributions (Clarke in combination with reduced deforestation) and consumption-side et al., 2014). Variations in these drivers can lead to drastically different (diet change in combination with lower shares of food waste) measures land-use implications (Popp et al., 2014b) (Figure 2.24). on the order of 40% in 210011 (compared to a baseline scenario without land-based mitigation). Lower consumption of livestock Stringent mitigation pathways inform general GHG dynamics in products by 2050 could also substantially reduce deforestation and the AFOLU sector. First, CO2 emissions from deforestation can be cumulative carbon losses (Weindl et al., 2017). On the supply side, abated at relatively low carbon prices if displacement effects in minor productivity growth in extensive livestock production systems other regions (Calvin et al., 2017) or other land-use types with high is projected to lead to substantial CO2 emission abatement, but the carbon density (Calvin et al., 2014; Popp et al., 2014a; Kriegler et emission-saving potential of productivity gains in intensive systems is al., 2017) can be avoided. However, efficiency and costs of reducing limited, mainly due to trade-offs with soil carbon stocks (Weindl et al., rates of deforestation strongly depend on governance performance, 2017). In addition, even within existing livestock production systems, a institutions and macroeconomic factors (Wang et al., 2016). Secondly, transition from extensive to more productive systems bears substantial besides CO2 reductions, the land system can play an important role GHG abatement potential, while improving food availability (Gerber et for overall CDR efforts (Rogelj et al., 2018) via BECCS, afforestation al., 2013; Havlík et al., 2014). Many studies highlight the capability of and reforestation, or a combination of options. The AFOLU sector also agricultural intensification for reducing GHG emissions in the AFOLU provides further potential for active terrestrial carbon sequestration, sector or even enhancing terrestrial carbon stocks (Valin et al., 2013; for example, via land restoration, improved management of forest and Popp et al., 2014a; Wise et al., 2014). Also the importance of immediate agricultural land (Griscom et al., 2017), or biochar applications (Smith, and global land-use regulations for a comprehensive reduction of 2016) (see also Chapter 4, Section 4.3.7). These options have so far 11 Land-based mitigation options on the supply and the demand side are assessed in 4.3.2, and CDR options with a land component in 4.3.7. Chapter 5 (Section 5.4) assesses the implications of land-based mitigation for related SDGs, e.g., food security. 146 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 Figure 2.25 | Agricultural emissions in transformation pathways. Global agricultural (a) CH4 and (b) N2O emissions. Box plots show median, interquartile range and full range. Classes are defined in Section 2.1. 2 not been extensively integrated in the mitigation pathway literature policy assumptions), and can apply these in different configurations. (see Supplementary Material 2.SM.1.2), but in theory their availability For example, among the four illustrative archetypes used in this would impact the deployment of other CDR technologies, like BECCS chapter (Section 2.1), the LED and S1 pathways focus on generally (Section 2.3.4) (Strefler et al., 2018a). These interactions will be low resource and energy consumption (including healthy diets with discussed further in the SRCCL. low animal-calorie shares and low food waste) as well as significant agricultural intensification in combination with high levels of nature Residual agricultural non-CO2 emissions of CH4 and N2O play an protection. Under such assumptions, comparably small amounts of important role for temperature stabilization pathways, and their relative land are needed for land-demanding mitigation activities such as importance increases in stringent mitigation pathways in which CO2 is BECCS and afforestation and reforestation, leaving the land footprint reduced to net zero emissions globally (Gernaat et al., 2015; Popp et al., for energy crops in 2050 virtually the same compared to 2010 levels for 2017; Stevanović et al., 2017; Rogelj et al., 2018), for example, through the LED pathway. In contrast, future land-use developments can look their impact on the remaining carbon budget (Section 2.2). Although very different under the resource- and energy-intensive S5 pathway agricultural non-CO2 emissions show marked reduction potentials that includes less healthy diets with high animal shares and high in 2°C-consistent pathways, complete elimination of these emission shares of food waste (Tilman and Clark, 2014; Springmann et al., 2016) sources does not occur in IAMs based on the evolution of agricultural combined with a strong orientation towards technology solutions to practice assumed in integrated models (Figure 2.25) (Gernaat et al., compensate for high reliance on fossil-fuel resources and associated 2015). Methane emissions in 1.5°C pathways are reduced through high levels of GHG emissions in the baseline. In such pathways, climate improved agricultural management (e.g., improved management of change mitigation strategies strongly depend on the availability of water in rice production, manure and herds, and better livestock quality CDR through BECCS (Humpenöder et al., 2014). As a consequence, the through breeding and improved feeding practices) as well as dietary S5 pathway sources significant amounts of biomass through bioenergy shifts away from emissions-intensive livestock products. Similarly, crop expansion in combination with agricultural intensification. Also, N2O emissions decrease due to improved N-efficiency and manure further policy assumptions can strongly affect land-use developments, management (Frank et al., 2018). However, high levels of bioenergy highlighting the importance for land use of making appropriate production can also result in increased N2O emissions (Kriegler et policy choices. For example, within the SSP set, some pathways rely al., 2017), highlighting the importance of appropriate management strongly on a policy to incentivize afforestation and reforestation for approaches (Davis et al., 2013). Residual agricultural emissions can be CDR together with BECCS, which results in an expansion of forest area further reduced by limiting demand for GHG-intensive foods through and a corresponding increase in terrestrial carbon stock. Finally, the shifts to healthier and more sustainable diets (Tilman and Clark, 2014; variety of pathways illustrates how policy choices in the AFOLU and Erb et al., 2016b; Springmann et al., 2016) and reductions in food waste other sectors strongly affect land-use developments and associated (Bajželj et al., 2014; Muller et al., 2017; Popp et al., 2017) (see also sustainable development interactions (Chapter 5, Section 5.4) in 1.5°C Chapter 4 and SRCCL). Finally, several mitigation measures that could pathways. affect these agricultural non-CO2 emissions are not, or only to a limited degree, considered in the current integrated pathway literature (see The choice of strategy or mitigation portfolio impacts the GHG Supplementary Material 2.SM.1.2). Such measures (like plant-based dynamics of the land system and other sectors (see Section 2.3), as well and synthetic proteins, methane inhibitors and vaccines in livestock, as the synergies and trade-offs with other environmental and societal alternate wetting and drying in paddy rice, or nitrification inhibitors) objectives (see Section 2.5.3 and Chapter 5, Section 5.4). For example, are very diverse and differ in their development or deployment stages. AFOLU developments in 1.5°C pathways range from strategies Their potentials have not been explicitly assessed here. that differ by almost an order of magnitude in their projected land requirements for bioenergy (Figure 2.24), and some strategies would Pathways consistent with 1.5°C rely on one or more of the three allow an increase in forest cover over the 21st century compared to strategies highlighted above (demand changes, efficiency gains, and strategies under which forest cover remains approximately constant. 147 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development High agricultural yields and application of intensified animal husbandry, challenges and opportunities identified in this section are further implementation of best-available technologies for reducing non-CO2 elaborated Chapter 4 (e.g., policy choice and implementation) and emissions, or lifestyle changes including a less-meat-intensive diet and Chapter 5 (e.g., sustainable development). The assessment indicates less CO2-intensive transport modes, have been identified as allowing unprecedented policy and geopolitical challenges. for such a forest expansion and reduced footprints from bioenergy without compromising food security (Frank et al., 2017; Doelman et al., 2.5.1 Policy Frameworks and Enabling Conditions 2018; van Vuuren et al., 2018). Moving from a 2°C to a 1.5°C pathway implies bold integrated policies The IAMs used in the pathways underlying this assessment (Popp that enable higher socio-technical transition speeds, larger deployment et al., 2017; Riahi et al., 2017; Rogelj et al., 2018) do not include all scales, and the phase-out of existing systems that may lock in potential land-based mitigation options and side-effects, and their emissions for decades (high confidence) (Geels et al., 2017; Kuramochi results are hence subject to uncertainty. For example, recent research et al., 2017; Rockström et al., 2017; Vogt-Schilb and Hallegatte, 2017; has highlighted the potential impact of forest management practices Kriegler et al., 2018a; Michaelowa et al., 2018). This requires higher on land carbon content (Erb et al., 2016a; Naudts et al., 2016) and levels of transformative policy regimes in the near term, which allow 2 the uncertainty surrounding future crop yields (Haberl et al., 2013; deep decarbonization pathways to emerge and a net zero carbon Searle and Malins, 2014) and water availability (Liu et al., 2014). energy–economy system to emerge in the 2040–2060 period (Rogelj These aspects are included in IAMs in varying degrees but were not et al., 2015b; Bataille et al., 2016b). This enables accelerated levels assessed in this report. Furthermore, land-use modules of some IAMs of technological deployment and innovation (Geels et al., 2017; IEA, can depict spatially resolved climate damages to agriculture (Nelson et 2017a; Grubler et al., 2018) and assumes more profound behavioural, al., 2014), but this option was not used in the SSP quantifications (Riahi economic and political transformation (Sections 2.3, 2.4 and 4.4). et al., 2017). Damages (e.g., due to ozone exposure or varying indirect Despite inherent levels of uncertainty attached to modelling studies fertilization due to atmospheric N and Fe deposition (e.g., Shindell et (e.g., related to climate and carbon cycle response), studies stress the al., 2012; Mahowald et al., 2017) are also not included. Finally, this urgency for transformative policy efforts to reduce emissions in the assessment did not look into the literature of agricultural sector models short term (Riahi et al., 2015; Kuramochi et al., 2017; Rogelj et al., which could provide important additional detail and granularity to the 2018). discussion presented here.12 This limits their ability to capture the full mitigation potentials and benefits between scenarios. An in-depth The available literature indicates that mitigation pathways in line assessment of these aspects lies outside the scope of this Special with 1.5°C pathways would require stringent and integrated policy Report. However, their existence affects the confidence assessment of interventions (very high confidence). Higher policy ambition often the AFOLU transition in 1.5°C pathways. takes the form of stringent economy-wide emission targets (and resulting peak-and-decline of emissions), larger coverage of NDCs to Despite the limitations of current modelling approaches, there is high more gases and sectors (e.g., land-use, international aviation), much agreement and robust evidence across models and studies that the lower energy and carbon intensity rates than historically seen, carbon AFOLU sector plays an important role in stringent mitigation pathways. prices much higher than the ones observed in real markets, increased The findings from these multiple lines of evidence also result in high climate finance, global coordinated policy action, and implementation confidence that AFOLU mitigation strategies can vary significantly of additional initiatives (e.g., by non-state actors) (Sections 2.3, 2.4 and based on preferences and policy choices, facilitating the exploration of 2.5.2). The diversity (beyond explicit carbon pricing) and effectiveness strategies that can achieve multiple societal objectives simultaneously of policy portfolios are of prime importance, particularly in the short- (see also Section 2.5.3). At the same time, given the many uncertainties term (Mundaca and Markandya, 2016; Kuramochi et al., 2017; OECD, and limitations, only low to medium confidence can be attributed by 2017; Kriegler et al., 2018a; Michaelowa et al., 2018). For instance, this assessment to the more extreme AFOLU developments found in deep decarbonization pathways in line with a 2˚C target (covering the pathway literature, and low to medium confidence to the level of 74% of global energy-system emissions) include a mix of stringent residual non-CO2 emissions. regulation (e.g., building codes, minimum performance standards), carbon pricing mechanisms and R&D (research and development) innovation policies (Bataille et al., 2016a). Explicit carbon pricing, direct regulation and public investment to enable innovation are 2.5 Challenges, Opportunities and Co-Impacts critical for deep decarbonization pathways (Grubb et al., 2014). of Transformative Mitigation Pathways Effective planning (including compact city measures) and integrated regulatory frameworks are also key drivers in the IEA-ETP B2DS study This section examines aspects other than climate outcomes of 1.5°C for the transport sector (IEA, 2017a). Effective urban planning can mitigation pathways. Focus is given to challenges and opportunities reduce GHG emissions from urban transport between 20% and 50% related to policy regimes, price of carbon and co-impacts, including (Creutzig, 2016). Comprehensive policy frameworks would be needed sustainable development issues, which can be derived from the existing if the decarbonization of the power system is pursued while increasing integrated pathway literature. Attention is also given to uncertainties end-use electrification (including transport) (IEA, 2017a). Technology and critical assumptions underpinning mitigation pathways. The policies (e.g., feed-in-tariffs), financing instruments, carbon pricing 12 For example, the GLEAM (http://www.fao.org/gleam/en/) model from the UN Food and Agricultural Organisation (FAO). 148 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 and system integration management driving the rapid adoption of 1.5˚C pathways. On the contrary, none of the IAMs contained in the renewable energy technologies are critical for the decarbonization SR1.5 database could produce a 1.5°C pathway under SSP3-SPA3 of electricity generation (Bruckner et al., 2014; Luderer et al., 2014; assumptions. Preventing elements include, for instance, climate Creutzig et al., 2017; Pietzcker et al., 2017). Likewise, low-carbon and policy fragmentation, limited control of land-use emissions, heavy resilient investments are facilitated by a mix of coherent policies, reliance on fossil fuels, unsustainable consumption and marked including fiscal and structural reforms (e.g., labour markets), public inequalities (Rogelj et al., 2018). Dietary aspects of the SSPs are also procurement, carbon pricing, stringent standards, information schemes, critical: climate-friendly diets were contained in ‘sustainability’ (SSP1) technology policies, fossil-fuel subsidy removal, climate risk disclosure, and meat-intensive diets in SSP3 and SSP5 (Popp et al., 2017). CDR and land-use and transport planning (OECD, 2017). Pathways in which requirements are reduced under ‘sustainability’ related assumptions CDR options are restricted emphasize the strengthening of near-term (Strefler et al., 2018b). These are major policy-related reasons for why policy mixes (Luderer et al., 2013; Kriegler et al., 2018a). Together with SSP1-SPA1 translates into relatively low mitigation challenges whereas the decarbonization of the supply side, ambitious policies targeting SSP3-SPA3 and SSP5-SPA5 entail futures that pose the highest socio- fuel switching and energy efficiency improvements on the demand technical and economic challenges. SSPs/SPAs assumptions indicate side play a major role across mitigation pathways (Clarke et al., 2014; that policy-driven pathways that encompass accelerated change away Kriegler et al., 2014b; Riahi et al., 2015; Kuramochi et al., 2017; Brown from fossil fuels, large-scale deployment of low-carbon energy supplies, 2 and Li, 2018; Rogelj et al., 2018; Wachsmuth and Duscha, 2018). improved energy efficiency and sustainable consumption lifestyles reduce the risks of climate targets becoming unreachable (Clarke et The combined evidence suggests that aggressive policies addressing al., 2014; Riahi et al., 2015, 2017; Marangoni et al., 2017; Rogelj et al., energy efficiency are central in keeping 1.5°C within reach and lowering 2017, 2018; Strefler et al., 2018b). energy system and mitigation costs (high confidence) (Luderer et al., 2013; Rogelj et al., 2013b, 2015b; Grubler et al., 2018). Demand-side Policy assumptions that lead to weak or delayed mitigation action from policies that increase energy efficiency or limit energy demand at a what would be possible in a fully cooperative world strongly influence higher rate than historically observed are critical enabling factors for the achievability of mitigation targets (high confidence) (Luderer et al., reducing mitigation costs in stringent mitigation pathways across the 2013; Rogelj et al., 2013b; OECD, 2017; Holz et al., 2018a; Strefler et al., board (Luderer et al., 2013; Rogelj et al., 2013b, 2015b; Clarke et al., 2018b). Such regimes also include current NDCs (Fawcett et al., 2015; 2014; Bertram et al., 2015a; Bataille et al., 2016b). Ambitious sector- Aldy et al., 2016; Rogelj et al., 2016a, 2017; Hof et al., 2017; van Soest et specific mitigation policies in industry, transportation and residential al., 2017), which have been reported to make achieving a 2°C pathway sectors are needed in the short run for emissions to peak in 2030 unattainable without CDR (Strefler et al., 2018b). Not strengthening (Méjean et al., 2018). Stringent demand-side policies (e.g., tightened NDCs would make it very challenging to keep 1.5°C within reach (see efficiency standards for buildings and appliances) driving the expansion, Section 2.3 and Cross-Chapter Box 11 in Chapter 4). One multimodel efficiency and provision of high-quality energy services are essential inter-comparison study (Luderer et al., 2016b, 2018) explored the effects to meet a 1.5˚C mitigation target while reducing the reliance on CDR on 1.5°C pathways assuming the implementation of current NDCs (Grubler et al., 2018). A 1.5˚C pathway for the transport sector is possible until 2030 and stringent reductions thereafter. It finds that delays in using a mix of additional and stringent policy actions preventing (or globally coordinated actions lead to various models reaching no 1.5°C reducing) the need for transport, encouraging shifts towards efficient pathways during the 21st century. Transnational emission reduction modes of transport, and improving vehicle-fuel efficiency (Gota et al., initiatives (TERIs) outside the UNFCCC have also been assessed and 2018). Stringent demand-side policies also reduce the need for CCS found to overlap (70–80%) with NDCs and be inadequate to bridge (Wachsmuth and Duscha, 2018). Even in the presence of weak near the gap between NDCs and a 2°C pathway (Roelfsema et al., 2018). term policy frameworks, increased energy efficiency lowers mitigation Weak and fragmented short-term policy efforts use up a large share of costs noticeably compared to pathways with reference energy intensity the long-term carbon budget before 2030–2050 (Bertram et al., 2015a; (Bertram et al., 2015a). Common issues in the literature relate to the van Vuuren et al., 2016) and increase the need for the full portfolio rebound effect, the potential overestimation of the effectiveness of mitigation measures, including CDR (Clarke et al., 2014; Riahi of energy efficiency policy, and policies to counteract the rebound et al., 2015; Xu and Ramanathan, 2017). Furthermore, fragmented (Saunders, 2015; van den Bergh, 2017; Grubler et al., 2018) (Sections policy scenarios also exhibit ‘carbon leakage’ via energy and capital 2.4 and 4.4). markets (Arroyo-Currás et al., 2015; Kriegler et al., 2015b). A lack of integrated policy portfolios can increase the risks of trade-offs between SSP-based modelling studies underline that socio-economic and mitigation approaches and sustainable development objectives (see climate policy assumptions strongly influence mitigation pathway Sections 2.5.3 and 5.4). However, more detailed analysis is needed characteristics and the economics of achieving a specific climate about realistic (less disruptive) policy trajectories until 2030 that can target (very high confidence) (Bauer et al., 2017; Guivarch and Rogelj, strengthen near-term mitigation action and meaningfully decrease 2017; Riahi et al., 2017; Rogelj et al., 2018). SSP assumptions related post-2030 challenges (see Chapter 4, Section 4.4). to economic growth and energy intensity are critical determinants of projected CO2 emissions (Marangoni et al., 2017). A multimodel Whereas the policy frameworks and enabling conditions identified inter-comparison study found that mitigation challenges in line with above pertain to the ‘idealized’ dimension of mitigation pathways, a 1.5˚C target vary substantially across SSPs and policy assumptions aspects related to 1.5°C mitigation pathways in practice are of prime (Rogelj et al., 2018). Under SSP1-SPA1 (sustainability) and SSP2-SPA2 importance. For example, issues related to second-best stringency (middle-of-the-road), the majority of IAMs were capable of producing levels, international cooperation, public acceptance, distributional 149 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development consequences, multilevel governance, non-state actions, compliance al., 2017; Rockström et al., 2017). Such co-processes are complex and levels, capacity building, rebound effects, linkages across highly go beyond the role of policy (including carbon pricing) and comprise heterogeneous policies, sustained behavioural change, finance and the role of citizens, businesses, stakeholder groups or governments, intra- and inter-generational issues need to be considered (see Chapter as well as the interplay of institutional and socio-political dimensions 4, Section 4.4) (Bataille et al., 2016a; Mundaca and Markandya, 2016; (Michaelowa et al., 2018; Veland et al., 2018). It is argued that large Baranzini et al., 2017; MacDougall et al., 2017; van den Bergh, 2017; system transformations, similar to those in 1.5°C pathways, require Vogt-Schilb and Hallegatte, 2017; Chan et al., 2018; Holz et al., 2018a; prioritizing an evolutionary and behavioural framework in economic Klinsky and Winkler, 2018; Michaelowa et al., 2018; Patterson et al., theory rather than an optimization or equilibrium framework as is 2018). Furthermore, policies interact with a wide portfolio of pre- common in current IAMs (Grubb et al., 2014; Patt, 2017). Accumulated existing policy instruments that address multiple areas (e.g., technology know-how, accelerated innovation and public investment play a key markets, economic growth, poverty alleviation, climate adaptation) and role in (rapid) transitions (see Sections 4.2 and 4.4) (Geels et al., 2017; deal with various market failures (e.g., information asymmetries) and Michaelowa et al., 2018). behavioural aspects (e.g., heuristics) that prevent or hinder mitigation actions (Kolstad et al., 2014; Mehling and Tvinnereim, 2018). The socio- In summary, the emerging literature supports the AR5 on the need for 2 technical transition literature points to multiple complexities in real- integrated, robust and stringent policy frameworks targeting both the world settings that prevent reaching ‘idealized’ policy conditions but supply and demand-side of energy-economy systems (high confidence). at the same time can still accelerate transformative change through Continuous ex-ante policy assessments provide learning opportunities other co-evolutionary processes of technology and society (Geels et for both policy makers and stakeholders. Cross-Chapter Box 5 | Economics of 1.5°C Pathways and the Social Cost of Carbon Contributing Authors: Luis Mundaca (Sweden/Chile), Mustafa Babiker (Sudan), Johannes Emmerling (Italy/Germany), Sabine Fuss (Germany), Jean-Charles Hourcade (France), Elmar Kriegler (Germany), Anil Markandya (Spain/UK), Joyashree Roy (India), Drew Shindell (USA) Two approaches have been commonly used to assess alternative emissions pathways: cost-effectiveness analysis (CEA) and cost–benefit analysis (CBA). CEA aims at identifying emissions pathways minimising the total mitigation costs of achieving a given warming or GHG limit (Clarke et al., 2014). CBA has the goal to identify the optimal emissions trajectory minimising the discounted flows of abatement expenditures and monetized climate change damages (Boardman et al., 2006; Stern, 2007). A third concept, the Social Cost of Carbon (SCC) measures the total net damages of an extra metric ton of CO2 emissions due to the associated climate change (Nordhaus, 2014; Pizer et al., 2014; Rose et al., 2017a). Negative and positive impacts are monetized, discounted and the net value is expressed as an equivalent loss of consumption today. The SCC can be evaluated for any emissions pathway under policy consideration (Rose, 2012; NASEM, 2016, 2017). Along the optimal trajectory determined by CBA, the SCC equals the discounted value of the marginal abatement cost of a metric ton of CO2 emissions. Equating the present value of future damages and marginal abatement costs includes a number of critical value judgements in the formulation of the social welfare function (SWF), particularly in how non-market damages and the distribution of damages across countries and individuals and between current and future generations are valued (Kolstad et al., 2014). For example, since climate damages accrue to a larger extent farther in the future and can persist for many years, assumptions and approaches to determine the social discount rate (normative ‘prescriptive’ vs. positive ‘descriptive’) and social welfare function (e.g., discounted utilitarian SWF vs. undiscounted prioritarian SWF) can heavily influence CBA outcomes and associated estimates of SCC (Kolstad et al., 2014; Pizer et al., 2014; Adler and Treich, 2015; Adler et al., 2017; NASEM, 2017; Nordhaus, 2017; Rose et al., 2017a). In CEA, the marginal abatement cost of carbon is determined by the climate goal under consideration. It equals the shadow price of carbon associated with the goal which in turn can be interpreted as the willingness to pay for imposing the goal as a political constraint. Emissions prices are usually expressed in carbon (equivalent) prices using the GWP-100 metric as the exchange rate for pricing emissions of non-CO2 GHGs controlled under internationally climate agreements (like CH4, N2O and fluorinated gases, see Cross-Chapter Box 2 in Chapter 1).13 Since policy goals like the goals of limiting warming to 1.5°C or well below 2°C do not directly result from a money metric trade-off between mitigation and damages, associated shadow prices can differ from the SCC in a CBA. In CEA, value judgments are to a large extent concentrated in the choice of climate goal and related implications, while more explicit assumptions about social values are required to perform CBA. For example, in CEA assumptions about the social discount rate no longer affect the overall abatement levels now set by the climate goal, but the choice and timing of investments in individual measures to reach these levels. 13 Also other metrics to compare emissions have been suggested and adopted by governments nationally (Kandlikar, 1995; Marten et al., 2015; Shindell, 2015; IWG, 2016). 150 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 Cross Chapter Box 5 (continued) Although CBA-based and CEA-based assessment are both subject to large uncertainty about socio-techno-economic trends, policy developments and climate response, the range of estimates for the SCC along an optimal trajectory determined by CBA is far wider than for estimates of the shadow price of carbon in CEA-based approaches. In CBA, the value judgments about inter- and intra- generational equity combined with uncertainties in the climate damage functions assumed, including their empirical basis, are important (Pindyck, 2013; Stern, 2013; Revesz et al., 2014). In a CEA-based approach, the value judgments about the aggregate welfare function matter less, and uncertainty about climate response and impacts can be tied into various climate targets and related emissions budgets (Clarke et al., 2014). The CEA- and CBA-based carbon cost estimates are derived with a different set of tools. They are all summarised as integrated assessment models (IAMs) but in fact are of very different nature (Weyant, 2017). Detailed process IAMs such as AIM (Fujimori, 2017), GCAM (Thomson et al., 2011; Calvin et al., 2017), IMAGE (van Vuuren et al., 2011b, 2017b), MESSAGE-GLOBIOM (Riahi et al., 2011; Havlík et al., 2014; Fricko et al., 2017), REMIND-MAgPIE (Popp et al., 2010; Luderer et al., 2013; Kriegler et al., 2017) and WITCH (Bosetti et al., 2006, 2008, 2009) include a process-based representation of energy and land systems, but in most 2 cases lack a comprehensive representation of climate damages, and are typically used for CEA. Diagnostic analyses across CBA- IAMs indicate important dissimilarities in modelling assembly, implementation issues and behaviour (e.g., parametric uncertainty, damage responses, income sensitivity) that need to be recognized to better understand SCC estimates (Rose et al., 2017a). CBA-IAMs such as DICE (Nordhaus and Boyer, 2000; Nordhaus, 2013, 2017), PAGE (Hope, 2006) and FUND (Tol, 1999; Anthoff and Tol, 2009) attempt to capture the full feedback from climate response to socio-economic damages in an aggregated manner, but are usually much more stylised than detailed process IAMs. In a nutshell, the methodological framework for estimating SCC involves projections of population growth, economic activity and resulting emissions; computations of atmospheric composition and global mean temperatures as a result of emissions; estimations of physical impacts of climate changes; monetization of impacts (positive and negative) on human welfare; and the discounting of the future monetary value of impacts to year of emission (Kolstad et al., 2014; Revesz et al., 2014; NASEM, 2017; Rose et al., 2017a). There has been a discussion in the literature to what extent CBA- IAMs underestimate the SCC due to, for example, a limited treatment or difficulties in addressing damages to human well-being, labour productivity, value of capital stock, ecosystem services and the risks of catastrophic climate change for future generations (Ackerman and Stanton, 2012; Revesz et al., 2014; Moore and Diaz, 2015; Stern, 2016). However, there has been progress in ‘bottom- up’ empirical analyses of climate damages (Hsiang et al., 2017), the insights of which could be integrated into these models (Dell et al., 2014). Most of the models used in Chapter 2 on 1.5°C mitigation pathways are detailed process IAMs and thus deal with CEA. An important question is how results from CEA- and CBA-type approaches can be compared and synthesized. Such synthesis needs to be done with care, since estimates of the shadow price of carbon under the climate goal and SCC estimates from CBA might not be directly comparable due to different tools, approaches and assumptions used to derive them. Acknowledging this caveat, the SCC literature has identified a range of factors, assumptions and value judgements that support SCC values above $100 tCO −12 that are also found as net present values of the shadow price of carbon in 1.5°C pathways. These factors include accounting for tipping points in the climate system (Lemoine and Traeger, 2014; Cai et al., 2015; Lontzek et al., 2015), a low social discount rate (Nordhaus, 2007a; Stern, 2007) and inequality aversion (Schmidt et al., 2013; Dennig et al., 2015; Adler et al., 2017). The SCC and the shadow price of carbon are not merely theoretical concepts but used in regulation (Pizer et al., 2014; Revesz et al., 2014; Stiglitz et al., 2017). As stated by the report of the High-Level Commission on Carbon Pricing (Stiglitz et al., 2017), in the real world there is a distinction to be made between the implementable and efficient explicit carbon prices and the implicit (notional) carbon prices to be retained for policy appraisal and the evaluation of public investments, as is already done in some jurisdictions such as the USA, UK and France. Since 2008, the U.S. government has used SCC estimates to assess the benefits and costs related to CO2 emissions resulting from federal policymaking (NASEM, 2017; Rose et al., 2017a). The use of the SCC for policy appraisals is, however, not straightforward in an SDG context. There are suggestions that a broader range of polluting activities than only CO2 emissions, for example emissions of air pollutants, and a broader range of impacts than only climate change, such as impacts on air quality, health and sustainable development in general (see Chapter 5 for a detailed discussion), would need to be included in social costs (Sarofim et al., 2017; Shindell et al., 2017a). Most importantly, a consistent valuation of the SCC in a sustainable development framework would require accounting for the SDGs in the social welfare formulation (see Chapter 5). 151 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development 2.5.2 Economic and Investment Implications of 1.5°C a higher degree of technology granularity and that entail more Pathways flexibility regarding mitigation response often produce relatively lower mitigation costs than those that show less flexibility from a technology 2.5.2.1 Price of carbon emissions perspective (Bertram et al., 2015a; Kriegler et al., 2015a). Pathways providing high estimates often have limited flexibility of substituting The price of carbon assessed here is fundamentally different from the fossil fuels with low-carbon technologies and the associated need concepts of optimal carbon price in a cost–benefit analysis, or the social to compensate fossil-fuel emissions with CDR. The price of carbon is cost of carbon (see Cross-Chapter Box 5 in this chapter and Chapter also sensitive to the non-availability of BECCS (Bauer et al., 2018). 3, Section 3.5.2). Under a cost-effectiveness analysis (CEA) modelling Furthermore, and due to the treatment of future price anticipation, framework, prices for carbon (mitigation costs) reflect the stringency of recursive-dynamic modelling approaches (with ‘myopic anticipation’) mitigation requirements at the margin (i.e., cost of mitigating one extra exhibit higher prices in the short term but modest increases in the long unit of emission). Explicit carbon pricing is briefly addressed here to the term compared to optimization modelling frameworks with ‘perfect extent it pertains to the scope of Chapter 2. For detailed policy issues foresight’ that show exponential pricing trajectories (Guivarch and about carbon pricing see Section 4.4.5. Rogelj, 2017). The chosen social discount rate in CEA studies (range 2 of 2–8% per year in the reported data, varying over time and sectors) Based on data available for this special report, the price of carbon can also affect the choice and timing of investments in mitigation varies substantially across models and scenarios, and their values measures (Clarke et al., 2014; Kriegler et al., 2015b; Weyant, 2017). increase with mitigation efforts (see Figure 2.26) (high confidence). However, the impacts of varying discount rates on 1.5°C (and 2°C) For instance, undiscounted values under a Higher-2°C pathway range mitigation strategies can only be assessed to a limited degree. The from 15–220 USD2010 tCO −1 −12-eq in 2030, 45–1050 USD2010 tCO2-eq above highlights the importance of sampling bias in pathway analysis in 2050, 120–1100 USD2010 tCO −12-eq in 2070 and 175–2340 USD2010 ensembles towards outcomes derived from models which are more tCO −12-eq in 2100. On the contrary, estimates for a Below-1.5°C flexible, have more mitigation options and cheaper cost assumptions pathway range from 135–6050 USD2010 tCO −12-eq in 2030, 245–14300 and thus can provide feasible pathways in contrast to other who are USD2010 tCO −12-eq in 2050, 420–19300 USD2010 tCO −1 2-eq in 2070 unable to do so (Tavoni and Tol, 2010; Clarke et al., 2014; Bertram et and 690–30100 USD2010 tCO −12-eq in 2100. Values for 1.5°C-low-OS al., 2015a; Kriegler et al., 2015a; Guivarch and Rogelj, 2017). All CEA- pathway are relatively higher than 1.5°C-high-OS pathway in 2030, based IAM studies reveal no unique path for the price of emissions but the difference decreases over time, particularly between 2050 and (Bertram et al., 2015a; Kriegler et al., 2015b; Akimoto et al., 2017; Riahi 2070. This is because in 1.5°C-high-OS pathways there is relatively et al., 2017). less mitigation activity in the first half of the century, but more in the second half. The low energy demand (LED, P1 in the Summary for Socio-economic conditions and policy assumptions also influence the Policymakers) scenario exhibits the lowest values across the illustrative price of carbon (very high confidence) (Bauer et al., 2017; Guivarch and pathway archetypes. As a whole, the global average discounted price Rogelj, 2017; Hof et al., 2017; Riahi et al., 2017; Rogelj et al., 2018). A of emissions across 1.5°C- and 2°C pathways differs by a factor of multimodel study (Riahi et al., 2017) estimated the average discounted four across models (assuming a 5% annual discount rate, comparing to price of carbon (2010–2100, 5% discount rate) for a 2°C target to Below-1.5°C and 1.5°C-low-OS pathways). If 1.5°C-high-OS pathways be nearly three times higher in the SSP5 marker than in the SSP1 (with peak warming 0.1–0.4°C higher than 1.5°C) or pathways with marker. Another multimodel study (Rogelj et al., 2018) estimated the very large land-use sinks are also considered, the differential value is average discounted price of carbon (2020–2100, 5%) to be 35–65% reduced to a limited degree, from a factor 4 to a factor 3. The increase lower in SSP1 compared to SSP2 in 1.5°C pathways. Delayed near- in mitigation costs between 1.5°C and 2°C pathways is based on a term mitigation policies and measures, including the limited extent of direct comparison of pathway pairs from the same model and the international global cooperation, result in increases in total economic same study in which the 1.5°C pathway assumes a significantly smaller mitigation costs and corresponding prices of carbon (Luderer et al., carbon budget compared to the 2°C pathway (e.g., 600 GtCO2 smaller 2013; Clarke et al., 2014). This is because stronger efforts are required in the CD-LINKS and ADVANCE studies). This assumption is the main in the period after the delay to counterbalance the higher emissions driver behind the increase in the price of carbon (Luderer et al., 2018; in the near term. Staged accession scenarios also produce higher McCollum et al., 2018).14 mitigation costs than immediate action mitigation scenarios under the same stringency level of emissions (Kriegler et al., 2015b). The wide range of values depends on numerous aspects, including methodologies, projected energy service demands, mitigation targets, It has been long argued that an explicit carbon pricing mechanism fuel prices and technology availability (high confidence) (Clarke et al., (whether via a tax or cap-and-trade scheme) can theoretically achieve 2014; Kriegler et al., 2015b; Rogelj et al., 2015c; Riahi et al., 2017; cost-effective emission reductions (Nordhaus, 2007b; Stern, 2007; Stiglitz et al., 2017). The characteristics of the technology portfolio, Aldy and Stavins, 2012; Goulder and Schein, 2013; Somanthan et al., particularly in terms of investment costs and deployment rates, play a 2014; Weitzman, 2014; Tol, 2017). Whereas the integrated assessment key role (Luderer et al., 2013, 2016a; Clarke et al., 2014; Bertram et al., literature is mostly focused on the role of carbon pricing to reduce 2015a; Riahi et al., 2015; Rogelj et al., 2015c). Models that encompass emissions (Clarke et al., 2014; Riahi et al., 2017; Weyant, 2017), there 14 Unlike AR5, which only included cost-effective scenarios for estimating discounted average carbon prices for 2015–2100 (also using a 5% discount rate) (see Clarke et al., 2014, p.450), please note that values shown in Figure 2.26b include delays or technology constraint cases (see Sections 2.1 and 2.3). 152 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 is an emerging body of studies (including bottom-up approaches) that focuses on the interaction and performance of various policy mixes (e.g., regulation, subsidies, standards). Assuming global implementation of a mix of regionally existing best-practice policies (mostly regulatory policies in the electricity, industry, buildings, transport and agricultural sectors) and moderate carbon pricing (between 5–20 USD2010 tCO −12 in 2025 in most world regions and average prices around 25 USD2010 tCO −12 in 2030), early action mitigation pathways are generated that reduce global CO2 emissions by an additional 10 GtCO2e in 2030 compared to the NDCs (Kriegler et al., 2018a) (see Section 2.3.5). Furthermore, a mix of stringent energy efficiency policies (e.g., minimum performance standards, building codes) combined with a carbon tax (rising from 10 USD2010 tCO −12 in 2020 to 27 USD2010 tCO −1 2 in 2040) is more cost-effective than a carbon tax alone (from 20 to 53 USD2010 tCO −12 ) to generate a 1.5°C pathway for the U.S. electric sector (Brown 2 and Li, 2018). Likewise, a policy mix encompassing a moderate carbon price (7 USD2010 tCO −12 in 2015) combined with a ban on new coal- based power plants and dedicated policies addressing renewable electricity generation capacity and electric vehicles reduces efficiency losses compared with an optimal carbon pricing in 2030 (Bertram et al., 2015b). One study estimates the carbon prices in high energy-intensive pathways to be 25–50% higher than in low energy-intensive pathways that assume ambitious regulatory instruments, economic incentives (in addition to a carbon price) and voluntary initiatives (Méjean et al., 2018). A bottom-up approach shows that stringent minimum performance standards (MEPS) for appliances (e.g., refrigerators) can effectively complement explicit carbon pricing, as tightened MEPS can achieve ambitious efficiency improvements that cannot be assured by carbon prices of 100 USD2010 tCO −12 or higher (Sonnenschein et al., Figure 2.26 | Global price of carbon emissions consistent with mitigation 2018). In addition, the revenue recycling effect of carbon pricing can pathways. Panels show (a) undiscounted price of carbon (2030–2100) and (b) average reduce mitigation costs by displacing distortionary taxes (Baranzini et price of carbon (2030–2100) discounted at a 5% discount rate to 2020 in USD2010. al., 2017; OECD, 2017; McFarland et al., 2018; Sands, 2018; Siegmeier AC: Annually compounded. NPV: Net present value. Median values in floating black line. The number of pathways included in box plots is indicated in the legend. Number of et al., 2018), and the reduction of capital tax (compared to a labour pathways outside the figure range is noted at the top. tax) can yield greater savings in welfare costs (Sands, 2018). The effect on public budgets is particularly important in the near term; however, it can decline in the long term as carbon neutrality is achieved (Sands, et al., 2013; Bowen et al., 2014; Gupta and Harnisch, 2014; Marangoni 2018). The literature indicates that explicit carbon pricing is relevant and Tavoni, 2014; OECD/IEA and IRENA, 2017). but needs to be complemented with other policies to drive the required changes in line with 1.5°C cost-effective pathways (low to medium Global energy-system investments in the year 2016 are estimated at evidence, high agreement) (see Chapter 4, Section 4.4.5) (Stiglitz et al., approximately 1.7 trillion USD2010 (approximately 2.2% of global GDP 2017; Mehling and Tvinnereim, 2018; Méjean et al., 2018; Michaelowa and 10% of gross capital formation), of which 0.23 trillion USD2010 et al., 2018). was for incremental end-use energy efficiency and the remainder for supply-side capacity installations (IEA, 2017c). There is some uncertainty In summary, new analyses are consistent with AR5 and show surrounding this number because not all entities making investments that the price of carbon increases significantly if a higher level of report them publicly, and model-based estimates show an uncertainty stringency is pursued (high confidence). Values vary substantially range of about ±15% (McCollum et al., 2018). Notwithstanding, the across models, scenarios and socio-economic, technology and policy trend for global energy investments has been generally upward over assumptions. While an explicit carbon pricing mechanism is central the last two decades: increasing about threefold between 2000 and to prompt mitigation scenarios compatible with 1.5°C pathways, a 2012, then levelling off for three years before declining in both 2015 complementary mix of stringent policies is required. and 2016 as a result of the oil price collapse and simultaneous capital cost reductions for renewables (IEA, 2017c). 2.5.2.2 Investments Estimates of demand-side investments, either in total or for incremental Realizing the transformations towards a 1.5°C world would require a efficiency efforts, are more uncertain, mainly due to a lack of reliable major shift in investment patterns (McCollum et al., 2018). Literature on statistics and definitional issues about what exactly is counted towards global climate change mitigation investments is relatively sparse, with a demand-side investment and what the reference should be for most detailed literature having focused on 2°C pathways (McCollum estimating incremental efficiency (McCollum et al., 2013). Grubler and 153 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Wilson (2014) use two working definitions (a broader and a narrower projected to average 0.8–2.9 trillion USD2010 yr−1 globally to 2050 one) to provide a first-order estimate of historical end-use technology in 1.5°C pathways, overtaking fossil investments globally already by investments in total. The broad definition defines end-use technologies around 2025 (McCollum et al., 2018). The bulk of these investments as the technological systems purchasable by final consumers in order are projected to be for clean electricity generation, particularly solar to provide a useful service, for example, heating and air conditioning and wind power (0.09–1.0 trillion USD2010 yr−1 and 0.1–0.35 trillion systems, cars, freezers, or aircraft. The narrow definition sets the boundary USD2010 yr−1, respectively) as well as nuclear power (0.1–0.25 trillion at the specific energy-using components or subsystems of the larger end- USD2010 yr−1). Third, the precise apportioning of these investments use technologies (e.g., compressor, car engine, heating element). Based depends on model assumptions and societal preferences related to on these two definitions, demand-side energy investments for the year mitigation strategies and policy choices (see Sections 2.1 and 2.3). 2005 were estimated about 1–3.5 trillion USD2010 (central estimate 1.7 Investments for electricity transmission and distribution and storage trillion USD2010) using the broad definition and 0.1–0.6 trillion USD2010 are also scaled up in 1.5°C pathways (0.3–1.3 trillion USD2010 yr−1), (central estimate 0.3 trillion USD2010) using the narrower definition. given their widespread electrification of the end-use sectors (see Due to these definitional issues, demand-side investment projections are Section 2.4). Meanwhile, 1.5°C pathways see a reduction in annual uncertain, often underreported, and difficult to compare. Global IAMs investments for fossil-fuel extraction and unabated fossil electricity 2 often do not fully and explicitly represent all the various measures that generation (to 0.3–0.85 trillion USD2010 yr −1 on average over the could improve end-use efficiency. 2016–2050 period). Investments in unabated coal are halted by 2030 in most 1.5°C projections, while the literature is less conclusive for Research carried out by six global IAM teams found that 1.5°C-consistent investments in unabated gas (McCollum et al., 2018). This illustrates climate policies would require a marked upscaling of energy system how mitigation strategies vary between models, but in the real world supply-side investments (resource extraction, power generation, fuel should be considered in terms of their societal desirability (see Section conversion, pipelines/transmission, and energy storage) between 2.5.3). Furthermore, some fossil investments made over the next few now and mid-century, reaching levels of between 1.6–3.8 trillion years – or those made in the last few – will likely need to be retired prior USD2010 yr−1 globally on average over the 2016–2050 timeframe to fully recovering their capital investment or before the end of their (McCollum et al., 2018) (Figure 2.27). How these investment needs operational lifetime (Bertram et al., 2015a; Johnson et al., 2015; OECD/ compare to those in a policy baseline scenario is uncertain: they could IEA and IRENA, 2017). How the pace of the energy transition will be be higher, much higher, or lower. Investments in the policy baselines affected by such dynamics, namely with respect to politics and society, from these same models are 1.6–2.7 trillion USD2010 yr−1. Much is not well captured by global IAMs at present. Modelling studies hinges on the reductions in energy demand growth embodied in the have, however, shown how the reliability of institutions influences 1.5°C pathways, which require investing in energy efficiency. Studies investment risks and hence climate mitigation investment decisions suggest that annual supply-side investments by mid-century could be (Iyer et al., 2015), finding that a lack of regulatory credibility or policy lowered by around 10% (McCollum et al., 2018) and in some cases up commitment fails to stimulate low-carbon investments (Bosetti and to 50% (Grubler et al., 2018) if strong policies to limit energy demand Victor, 2011; Faehn and Isaksen, 2016). growth are successfully implemented. However, the degree to which these supply-side reductions would be partially offset by an increase in Low-carbon supply-side investment needs are projected to be largest in demand-side investments is unclear. OECD countries and those of developing Asia. The regional distribution of investments in 1.5°C pathways estimated by the multiple models Some trends are robust across scenarios (Figure 2.27). First, pursuing in (McCollum et al., 2018) are the following (average over 2016–2050 1.5°C mitigation efforts requires a major reallocation of the investment timeframe): 0.30–1.3 trillion USD2010 yr−1(ASIA), 0.35–0.85 trillion portfolio, implying a financial system aligned to mitigation challenges. USD2010 yr−1 (OECD), 0.08–0.55 trillion USD2010 yr−1 (MAF), 0.07–0.25 The path laid out by countries’ current NDCs until 2030 will not trillion USD2010 yr−1 (LAM), and 0.05–0.15 trillion USD2010 yr−1 (REF) drive these structural changes; and despite increasing low-carbon (regions are defined consistent with their use in AR5 WGIII, see Table investments in recent years (IEA, 2016b; Frankfurt School-UNEP Centre/ A.II.8 in Krey et al., 2014b). BNEF, 2017), these are not yet aligned with 1.5°C. Second, additional annual average energy-related investments for the period 2016 to 2050 Until now, IAM investment analyses of 1.5°C pathways have focused in pathways limiting warming to 1.5°C compared to the baseline (i.e., on middle-of-the-road socio-economic and technological development pathways without new climate policies beyond those in place today) futures (SSP2) (Fricko et al., 2017). Consideration of a broader range are estimated by the models employed in McCollum et al. (2018) to of development futures would yield different outcomes in terms of be around 830 billion USD2010 (range of 150 billion to 1700 billion the magnitudes of the projected investment levels. Sensitivity analyses USD2010 across six models). This compares to total annual average indicate that the magnitude of supply-side investments as well as the energy supply investments in 1.5°C pathways of 1460 to 3510 billion investment portfolio do not change strongly across the SSPs for a given USD2010 and total annual average energy demand investments of level of climate policy stringency (McCollum et al., 2018). With only one 640 to 910 billion USD2010 for the period 2016 to 2050. Total energy- dedicated multimodel comparison study published, there is limited to related investments increase by about 12% (range of 3% to 24%) in medium evidence available. For some features, there is high agreement 1.5°C pathways relative to 2°C pathways. Average annual investment across modelling frameworks leading, for example, to medium to high in low-carbon energy technologies and energy efficiency are upscaled confidence that limiting global temperature increase to 1.5°C would by roughly a factor of six (range of factor of 4 to 10) by 2050 compared require a major reallocation of the investment portfolio. Given the limited to 2015. Specifically, annual investments in low-carbon energy are amount of sensitivity cases available compared to the default SSP2 154 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 assumptions, medium confidence can be assigned to the specific energy markets and de-risk mitigation investments in the long term (Clarke et and climate mitigation investment estimates reported here. al., 2014; Mundaca et al., 2016; EC, 2017; OECD, 2017). Importantly, the different time horizons that actors have in the competitive finance Assumptions in modelling studies indicate a number of challenges. industry are typically not explicitly captured by modelling assumptions For instance, access to finance and mobilization of funds are critical (Harmes, 2011). See Chapter 4, Section 4.4.5 for details of climate (Fankhauser et al., 2016; OECD, 2017). In turn, policy efforts need to be finance in practice. effective in redirecting financial resources (UNEP, 2015; OECD, 2017) and reducing transaction costs for bankable mitigation projects (i.e. projects In summary and despite inherent uncertainties, the emerging literature that have adequate future cash flow, collateral, etc. so lenders are willing indicates a gap between current investment patterns and those to finance it), particularly on the demand side (Mundaca et al., 2013; compatible with 1.5°C (or 2°C) pathways (limited to medium evidence, Brunner and Enting, 2014; Grubler et al., 2018). Assumptions also imply high agreement). Estimates and assumptions from modelling frameworks that policy certainty, regulatory oversight mechanisms and fiduciary duty suggest a major shift in investment patterns and entail a financial system need to be robust and effective to safeguard credible and stable financial effectively aligned with mitigation challenges (high confidence). 2 Figure 2.27 | Historical and projected global energy investments. (a) Historical investment estimates across six global models from (McCollum et al., 2018) (bars = model means, whiskers full model range) compared to historical estimates from IEA (International Energy Agency (IEA) 2016) (triangles). (b) Average annual investments over the 2016–2050 period in the “baselines” (i.e., pathways without new climate policies beyond those in place today), scenarios which implement the NDCs (‘NDC’, including conditional NDCs), scenarios consistent with the Lower-2°C pathway class (‘2°C’), and scenarios in line with the 1.5°C-low-OS pathway class (‘1.5°C’). Whiskers show the range of models; wide bars show the multimodel means; narrow bars represent analogous values from individual IEA scenarios (OECD/IEA and IRENA, 2017). (c) Average annual mitigation investments and disinvestments for the 2016–2030 periods relative to the baseline. The solid bars show the values for ‘2°C’ pathways, while the hatched areas show the additional investments for the pathways labelled with ‘1.5°C’. Whiskers show the full range around the multimodel means. T&D stands for transmission and distribution, and CCS stands for carbon capture and storage. Global cumulative carbon dioxide emissions, from fossil fuels and industrial processes (FF&I) but excluding land use, over the 2016-2100 timeframe range from 880 to 1074 GtCO2 (multimodel mean: 952 GtCO2) in the ‘2°C’ pathway and from 206 to 525 GtCO2 (mean: 390 GtCO2) in the ‘1.5°C’ pathway. 155 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development 2.5.3 Sustainable Development Features Development Goals (SDGs) (Table 5.1). This section synthesized of 1.5°C Pathways the Chapter 5 insights to assess how these interactions play out in integrated 1.5°C pathways, and the four illustrative pathway Potential synergies and trade-offs between 1.5°C mitigation pathways archetypes of this chapter in particular (see Section 2.1). Information and different sustainable development (SD) dimensions (see Cross- from integrated pathways is combined with the interactions assessed Chapter Box 4 in Chapter 1) are an emerging field of research. Chapter in Chapter 5 and aggregated for each SDG, with a level of confidence 5, Section 5.4 assesses interactions between individual mitigation attributed to each interaction based on the amount and agreement of measures with other societal objectives, as well as the Sustainable the scientific evidence (see Chapter 5). 2 Figure 2.28 | Interactions of individual mitigation measures and alternative mitigations portfolios for 1.5°C with Sustainable Development Goals (SDGs). The assessment of interactions between mitigation measures and individual SDGs is based on the assessment of Chapter 5, Section 5.4. Proxy indicators and synthesis method are described in Supplementary Material 2.SM.1.5. 156 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 Figure 2.28 shows how the scale and combination of individual interactions. Very limited literature suggests that achieving co-benefits mitigation measures (i.e., their mitigation portfolios) influence the is not automatically assured but results from conscious and carefully extent of synergies and trade-offs with other societal objectives. All coordinated policies and implementation strategies (Shukla and pathways generate multiple synergies with sustainable development Chaturvedi, 2012; Clarke et al., 2014; McCollum et al., 2018). dimensions and can advance several other SDGs simultaneously. Some, Understanding these mitigation–SDG interactions is key for selecting however, show higher risks for trade-offs. An example is increased mitigation options that maximize synergies and minimize trade-offs biomass production and its potential to increase pressure on land and towards the 1.5°C and sustainable development objectives (van Vuuren water resources, food production, and biodiversity and to reduce air et al., 2015; Hildingsson and Johansson, 2016; Jakob and Steckel, 2016; quality when combusted inefficiently. At the same time, mitigation von Stechow et al., 2016; Delponte et al., 2017). actions in energy-demand sectors and behavioural response options with appropriate management of rebound effects can advance multiple In summary, the combined evidence indicates that the chosen SDGs simultaneously, more so than energy supply-side mitigation mitigation portfolio can have a distinct impact on the achievement actions (see Chapter 5, Section 5.4, Table 5.1 and Figure 5.3 for more of other societal policy objectives (high confidence); however, there is examples). Of the four pathway archetypes used in this chapter (LED, uncertainty regarding the specific extent of climate–SDG interactions. S1, S2, and S5, referred to as P1, P2, P3, and P4 in the Summary for 2 Policymakers), the S1 and LED pathways show the largest number of synergies and least number of potential trade-offs, while for the S5 pathway more potential trade-offs are identified. In general, pathways 2.6 Knowledge Gaps with emphasis on demand reductions and policies that incentivize behavioural change, sustainable consumption patterns, healthy diets This section summarizes the knowledge gaps articulated in earlier and relatively low use of CDR (or only afforestation) show relatively sections of the chapter. more synergies with individual SDGs than other pathways. 2.6.1 Geophysical Understanding There is robust evidence and high agreement in the pathway literature that multiple strategies can be considered to limit warming to 1.5°C (see Knowledge gaps are associated with the carbon cycle response, the Sections 2.1.3, 2.3 and 2.4). Together with the extensive evidence on role of non-CO2 emissions and the evaluation of an appropriate historic the existence of interactions of mitigation measures with other societal baseline. objectives (Chapter 5, Section 5.4), this results in high confidence that the choice of mitigation portfolio or strategy can markedly affect the Quantifying how the carbon cycle responds to negative emissions is achievement of other societal objectives. For instance, action on SLCFs an important knowledge gap for strong mitigation pathways (Section has been suggested to facilitate the achievement of SDGs (Shindell et 2.2). Earth system feedback uncertainties are important to consider for al., 2017b) and to reduce regional impacts, for example, from black the longer-term response, particularly in how permafrost melting might carbon sources on snow and ice loss in the Arctic and alpine regions affect the carbon budget (Section 2.2). Future research and ongoing (Painter et al., 2013), with particular focus on the warming sub-set of observations over the next years will provide a better indication as to SLCFs. Reductions in both surface aerosols and ozone through methane how the 2006-2015 base period compares with the long-term trends reductions provide health and ecosystem co-benefits (Jacobson, 2002, and might at present bias the carbon budget estimates. 2010; Anenberg et al., 2012; Shindell et al., 2012; Stohl et al., 2015; Collins et al., 2018). Public health benefits of stringent mitigation The future emissions of short-lived climate forcers and their pathways in line with 1.5°C pathways can be sizeable. For instance, temperature response are a large source of uncertainty in 1.5°C a study examining a more rapid reduction of fossil-fuel usage to pathways, having a greater relative uncertainty than in higher CO2 achieve 1.5°C relative to 2°C, similar to that of other recent studies emission pathways. Their global emissions, their sectoral and regional (Grubler et al., 2018; van Vuuren et al., 2018), found that improved disaggregation, and their climate response are generally less well air quality would lead to more than 100 million avoided premature quantified than for CO2 (Sections 2.2 and 2.3). Emissions from the deaths over the 21st century (Shindell et al., 2018). These benefits are agricultural sector, including land-use based mitigation options, in assumed to be in addition to those occurring under 2°C pathways 1.5°C pathways constitute the main source of uncertainty here and (e.g., Silva et al., 2016), and could in monetary terms offset either a are an important gap in understanding the potential achievement of large portion or all of the initial mitigation costs (West et al., 2013; stringent mitigation scenarios (Sections 2.3 and 2.4). This also includes Shindell et al., 2018). However, some sources of SLCFs with important uncertainties surrounding the mitigation potential of the long-lived impacts for public health (e.g., traditional biomass burning) are only GHG nitrous oxide (Sections 2.3 and 2.4). mildly affected by climate policy in the available integrated pathways and are more strongly impacted by baseline assumptions about future There is considerable uncertainty in how future emissions of aerosol societal development and preferences, and technologies instead (Rao precursors will affect the effective radiative forcing from aerosol–cloud et al., 2016, 2017). interaction. The potential future warming from mitigation of these emissions reduces remaining carbon budgets and increases peak At the same time, the literature on climate–SDG interactions is still temperatures (Section 2.2). The potential co-benefits of mitigating air an emergent field of research and hence there is low to medium pollutants and how the reduction in air pollution may affect the carbon confidence in the precise magnitude of the majority of these sink are also important sources of uncertainty (Sections 2.2 and 2.5). 157 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development The pathway classification employed in this chapter employs results industry, buildings, and transport sector in that realized by selected from the MAGICC model with its AR5 parameter sets. The alternative pathways from IAMs, indicating the possibility to strengthen sectoral representation of the relationship between emissions and effective decarbonization strategies compared to the IAM 1.5°C pathways radiative forcing and response in the FAIR model would lead to a different assessed in this chapter (Section 2.1). classification that would make 1.5°C targets more achievable (Section 2.2 and Supplementary Material 2.SM.1.1). Such a revision would Studies indicate that a major shift in investment patterns is required significantly alter the temperature outcomes for the pathways and, if to limit global warming to 1.5°C. This assessment would benefit from the result is found to be robust, future research and assessments would a more explicit representation and understanding of the financial need to adjust their classifications accordingly. Any possible high bias in sector within the modelling approaches. Assumptions in modelling the MAGICC response may be partly or entirely offset by missing Earth studies imply low-to-zero transaction costs for market agents and system feedbacks that are not represented in either climate emulator and that regulatory oversight mechanisms and fiduciary duty need to be that would act to increase the temperature response (Section 2.2). For highly robust to guarantee stable and credible financial markets in this assessment report, any possible bias in the MAGICC setup applied the long term. This area can be subject to high uncertainty, however. in this and earlier reports is not established enough in the literature to The heterogeneity of actors (e.g., banks, insurance companies, asset 2 change the classification approach. However, we only place medium managers, or credit rating agencies) and financial products also needs confidence in the classification adopted by the chapter. to be taken into account, as does the mobilization of capital and financial flows between countries and regions (Section 2.5). 2.6.2 Integrated Assessment Approaches The literature on interactions between 1.5˚C mitigation pathways IAMs attempt to be as broad as possible in order to explore and SDGs is an emergent field of research (Section 2.3.5, 2.5 and Chapter interactions between various societal subsystems, like the economy, 5). Whereas the choice of mitigation strategies can noticeably affect the land, and energy system. They hence include stylized and simplified attainment of various societal objectives, there is uncertainty regarding representations of these subsystems. Climate damages, avoided the extent of the majority of identified interactions. Understanding impacts and societal co-benefits of the modelled transformations climate–SDG interactions helps inform the choice of mitigation options remain largely unaccounted for and are important knowledge gaps. that minimize trade-offs and risks and maximize synergies towards Furthermore, rapid technological changes and uncertainties about sustainable development objectives and the 1.5°C goal (Section 2.5). input data present continuous challenges. 2.6.3 Carbon Dioxide Removal (CDR) The IAMs used in this report do not account for climate impacts (Section 2.1), and similarly, none of the Gross Domestic Product (GDP) Most 1.5°C and 2°C pathways are heavily reliant on CDR at a projections in the mitigation pathway literature assessed in this chapter speculatively large scale before mid-century. There are a number included the feedback of climate damages on economic growth (Section of knowledge gaps associated which such technologies. Chapter 4 2.3). Although some IAMs do allow for climate impact feedbacks in performs a detailed assessment of CDR technologies. their modelling frameworks, particularly in their land components, such feedbacks were by design excluded in pathways developed in the There is uncertainty in the future deployment of CCS given the context of the SSP framework. The SSP framework aims at providing limited pace of current deployment, the evolution of CCS technology an integrative framework for the assessment of climate change that would be associated with deployment, and the current lack of adaptation and mitigation. IAMs are typically developed to inform incentives for large-scale implementation of CCS (Chapter 4, Section the mitigation component of this question, while the assessment of 4.2.7). Technologies other than BECCS and afforestation have yet to impacts is carried out by specialized impact models. However, the use be comprehensively assessed in integrated assessment approaches. No of a consistent set of socio-economic drivers embodied by the SSPs proposed technology is close to deployment at scale, and regulatory allows for an integrated assessment of climate change impacts and frameworks are not established. This limits how they can be realistically mitigation challenges at a later stage. Further integration of these implemented within IAMs. (Section 2.3) two strands of research will allow a better understanding of climate impacts on mitigation studies. Evaluating the potential from BECCS is problematic due to large uncertainties in future land projections due to differences in modelling Many of the IAMs that contributed mitigation pathways to this approaches in current land-use models, and these differences are assessment include a process-based description of the land system in at least as great as the differences attributed to climate scenario addition to the energy system, and several have been extended to cover variations. (Section 2.3) air pollutants and water use. These features make them increasingly fit to explore questions beyond those that touch upon climate mitigation There is substantial uncertainty about the adverse effects of large- only. The models do not, however, fully account for all constraints that scale CDR deployment on the environment and societal sustainable could affect realization of pathways (Section 2.1). development goals. It is not fully understood how land-use and land-management choices for large-scale BECCS will affect various While the representation of renewable energy resource potentials, ecosystem services and sustainable development, and how they further technology costs and system integration in IAMs has been updated translate into indirect impacts on climate, including GHG emissions since AR5, bottom-up studies find higher mitigation potentials in the other than CO2. (Section 2.3, Section 2.5.3) 158 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 Frequently Asked Questions FAQ 2.1 | What Kind of Pathways Limit Warming to 1.5°C and are we on Track? Summary: There is no definitive way to limit global temperature rise to 1.5°C above pre-industrial levels. This Special Report identifies two main conceptual pathways to illustrate different interpretations. One stabilizes global temperature at, or just below, 1.5°C. Another sees global temperature temporarily exceed 1.5°C before coming back down. Countries’ pledges to reduce their emissions are currently not in line with limiting global warming to 1.5°C. Scientists use computer models to simulate the emissions of greenhouse gases that would be consistent with different levels of warming. The different possibilities are often referred to as ‘greenhouse gas emission pathways’. There is no single, definitive pathway to limiting warming to 1.5°C. This IPCC special report identifies two main pathways that explore global warming of 1.5°C. The first involves global temperature stabilizing at or below before 1.5°C above pre-industrial levels. The second pathway sees 2 warming exceed 1.5°C around mid-century, remain above 1.5°C for a maximum duration of a few decades, and return to below 1.5°C before 2100. The latter is often referred to as an ‘overshoot’ pathway. Any alternative situation in which global temperature continues to rise, exceeding 1.5°C permanently until the end of the 21st century, is not considered to be a 1.5°C pathway. The two types of pathway have different implications for greenhouse gas emissions, as well as for climate change impacts and for achieving sustainable development. For example, the larger and longer an ‘overshoot’, the greater the reliance on practices or technologies that remove CO2 from the atmosphere, on top of reducing the sources of emissions (mitigation). Such ideas for CO2 removal have not been proven to work at scale and, therefore, run the risk of being less practical, effective or economical than assumed. There is also the risk that the use of CO2 removal techniques ends up competing for land and water, and if these trade-offs are not appropriately managed, they can adversely affect sustainable development. Additionally, a larger and longer overshoot increases the risk for irreversible climate impacts, such as the onset of the collapse of polar ice shelves and accelerated sea level rise. Countries that formally accept or ‘ratify’ the Paris Agreement submit pledges for how they intend to address climate change. Unique to each country, these pledges are known as Nationally Determined Contributions (NDCs). Different groups of researchers around the world have analysed the combined effect of adding up all the NDCs. Such analyses show that current pledges are not on track to limit global warming to 1.5°C above pre- industrial levels. If current pledges for 2030 are achieved but no more, researchers find very few (if any) ways to reduce emissions after 2030 sufficiently quickly to limit warming to 1.5°C. This, in turn, suggests that with the national pledges as they stand, warming would exceed 1.5°C, at least for a period of time, and practices and technologies that remove CO2 from the atmosphere at a global scale would be required to return warming to 1.5°C at a later date. A world that is consistent with holding warming to 1.5°C would see greenhouse gas emissions rapidly decline in the coming decade, with strong international cooperation and a scaling up of countries’ combined ambition beyond current NDCs. In contrast, delayed action, limited international cooperation, and weak or fragmented policies that lead to stagnating or increasing greenhouse gas emissions would put the possibility of limiting global temperature rise to 1.5°C above pre-industrial levels out of reach. (continued on next page) 159 Chapter 2 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development FAQ 2.1 (continued) 2 FAQ 2.1, Figure 1 | Two main pathways for limiting global temperature rise to 1.5°C above pre-industrial levels are discussed in this Special Report. These are: stabilizing global temperature at, or just below, 1.5°C (left) and global temperature temporarily exceeding 1.5°C before coming back down later in the century (right). Temperatures shown are relative to pre-industrial but pathways are illustrative only, demonstrating conceptual not quantitative characteristics. 160 Mitigation Pathways Compatible with 1.5°C in the Context of Sustainable Development Chapter 2 Frequently Asked Questions FAQ 2.2 | What do Energy Supply and Demand have to do with Limiting Warming to 1.5°C? Summary: Limiting global warming to 1.5°C above pre-industrial levels would require major reductions in green- house gas emissions in all sectors. But different sectors are not independent of each other, and making changes in one can have implications for another. For example, if we as a society use a lot of energy, then this could mean we have less flexibility in the choice of mitigation options available to limit warming to 1.5°C. If we use less energy, the choice of possible actions is greater – for example, we could be less reliant on technologies that remove carbon dioxide (CO2) from the atmosphere. To stabilize global temperature at any level, ‘net’ CO2 emissions would need to be reduced to zero. This means the amount of CO2 entering the atmosphere must equal the amount that is removed. Achieving a balance between CO2 ‘sources’ and ‘sinks’ is often referred to as ‘net zero’ emissions or ‘carbon neutrality’. The implication of net zero emissions is that the concentration of CO2 in the atmosphere would slowly decline over time until a new 2 equilibrium is reached, as CO2 emissions from human activity are redistributed and taken up by the oceans and the land biosphere. This would lead to a near-constant global temperature over many centuries. Warming will not be limited to 1.5°C or 2°C unless transformations in a number of areas achieve the required greenhouse gas emissions reductions. Emissions would need to decline rapidly across all of society’s main sectors, including buildings, industry, transport, energy, and agriculture, forestry and other land use (AFOLU). Actions that can reduce emissions include, for example, phasing out coal in the energy sector, increasing the amount of energy produced from renewable sources, electrifying transport, and reducing the ‘carbon footprint’ of the food we consume. The above are examples of ‘supply-side’ actions. Broadly speaking, these are actions that can reduce greenhouse gas emissions through the use of low-carbon solutions. A different type of action can reduce how much energy human society uses, while still ensuring increasing levels of development and well-being. Known as ‘demand-side’ actions, this category includes improving energy efficiency in buildings and reducing consumption of energy- and greenhouse-gas intensive products through behavioural and lifestyle changes, for example. Demand- and supply-side measures are not an either-or question, they work in parallel with each other. But emphasis can be given to one or the other. Making changes in one sector can have consequences for another, as they are not independent of each other. In other words, the choices that we make now as a society in one sector can either restrict or expand our options later on. For example, a high demand for energy could mean we would need to deploy almost all known options to reduce emissions in order to limit global temperature rise to 1.5°C above pre-industrial levels, with the potential for adverse side-effects. In particular, a pathway with high energy demand would increase our reliance on practices and technologies that remove CO2 from the atmosphere. As of yet, such techniques have not been proven to work on a large scale and, depending on how they are implemented, could compete for land and water. By leading to lower overall energy demand, effective demand-side measures could allow for greater flexibility in how we structure our energy system. However, demand-side measures are not easy to implement and barriers have prevented the most efficient practices being used in the past. 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Ebi (USA), Francois Engelbrecht (South Africa), Joel Guiot (France), Yasuaki Hijioka (Japan), Shagun Mehrotra (USA/India), Antony Payne (UK), Sonia I. Seneviratne (Switzerland), Adelle Thomas (Bahamas), Rachel Warren (UK), Guangsheng Zhou (China) Contributing Authors: Sharina Abdul Halim (Malaysia), Michelle Achlatis (Australia/Greece), Lisa V. Alexander (Australia), Myles R. Allen (UK), Peter Berry (Canada), Christopher Boyer (USA), Lorenzo Brilli (Italy), Marcos Buckeridge (Brazil), Edward Byers (Austria/Brazil), William Cheung (Canada), Marlies Craig (South Africa), Neville Ellis (Australia), Jason Evans (Australia), Hubertus Fischer (Switzerland), Klaus Fraedrich (Germany), Sabine Fuss (Germany), Anjani Ganase (Australia/Trinidad and Tobago), Jean-Pierre Gattuso (France), Peter Greve (Austria/Germany), Tania Guillén Bolaños (Germany/Nicaragua), Naota Hanasaki (Japan), Tomoko Hasegawa (Japan), Katie Hayes (Canada), Annette Hirsch (Switzerland/Australia), Chris Jones (UK), Thomas Jung (Germany), Markku Kanninen (Finland), Gerhard Krinner (France), David Lawrence (USA), Tim Lenton (UK), Debora Ley (Guatemala/Mexico), Diana Liverman (USA), Natalie Mahowald (USA), Kathleen McInnes (Australia), Katrin J. Meissner (Australia), Richard Millar (UK), Katja Mintenbeck (Germany), Dann Mitchell (UK), Alan C. Mix (US), Dirk Notz (Germany), Leonard Nurse (Barbados), Andrew Okem (Nigeria), Lennart Olsson (Sweden), Michael Oppenheimer (USA), Shlomit Paz (Israel), Juliane Petersen (Germany), Jan Petzold (Germany), Swantje Preuschmann (Germany), Mohammad Feisal Rahman (Bangladesh), Joeri Rogelj (Austria/Belgium), Hanna Scheuffele (Germany), Carl-Friedrich Schleussner (Germany), Daniel Scott (Canada), Roland Séférian (France), Jana Sillmann (Germany/Norway), Chandni Singh (India), Raphael Slade (UK), Kimberly Stephenson (Jamaica), Tannecia Stephenson (Jamaica), Mouhamadou B. Sylla (Senegal), Mark Tebboth (UK), Petra Tschakert (Australia/Austria), Robert Vautard (France), Richard Wartenburger (Switzerland/Germany), Michael Wehner (USA), Nora M. Weyer (Germany), Felicia Whyte (Jamaica), Gary Yohe (USA), Xuebin Zhang (Canada), Robert B. Zougmoré (Burkina Faso/Mali) Review Editors: Jose Antonio Marengo (Brazil/Peru), Joy Pereira (Malaysia), Boris Sherstyukov (Russian Federation) Chapter Scientist: Tania Guillén Bolaños (Germany/Nicaragua) This chapter should be cited as: Hoegh-Guldberg, O., D. Jacob, M. Taylor, M. Bindi, S. Brown, I. Camilloni, A. Diedhiou, R. Djalante, K.L. Ebi, F. Engelbrecht, J. Guiot, Y. Hijioka, S. Mehrotra, A. Payne, S.I. Seneviratne, A. Thomas, R. Warren, and G. Zhou, 2018: Impacts of 1.5ºC Global Warming on Natural and Human Systems. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)]. In Press. 175 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Table of Contents Executive Summary ...................................................................177 Cross-Chapter Box 6: Food Security ......................................238 3.4.7 Human Health ............................................................240 3.1 About the Chapter .......................................................182 3.4.8 Urban Areas ...............................................................241 3.2 How are Risks at 1.5°C and Higher Levels 3.4.9 Key Economic Sectors and Services ............................242 of Global Warming Assessed in 3.4.10 Livelihoods and Poverty, and the Changing this Chapter? ..................................................................183 Structure of Communities ...........................................244 3.2.1 How are Changes in Climate and Weather 3.4.11 Interacting and Cascading Risks .................................245 at 1.5°C versus Higher Levels of Warming Assessed? ..................................................................183 3.4.12 Summary of Projected Risks at 1.5°C and 2°C of Global Warming .....................................................245 3.2.2 How are Potential Impacts on Ecosystems Assessed at 1.5°C versus Higher Levels 3.4.13 Synthesis of Key Elements of Risk ..............................251 of Warming? ..............................................................185 3.5 Avoided Impacts and Reduced Risks 3.3 Global and Regional Climate at 1.5°C Compared with 2°C of Changes and Associated Hazards ............................186 Global Warming ............................................................253 3.3.1 Global Changes in Climate .........................................186 3.5.1 Introduction ...............................................................253 3.3.2 Regional Temperatures on Land, Including 3.5.2 Aggregated Avoided Impacts and Reduced Extremes ....................................................................189 Risks at 1.5°C versus 2°C of Global Warming ............253 3 3.3.3 Regional Precipitation, Including Heavy 3.5.3 Regional Economic Benefit Analysis for Precipitation and Monsoons .......................................191 the 1.5°C versus 2°C Global Goals .............................258 3.3.4 Drought and Dryness ..................................................196 3.5.4 Reducing Hotspots of Change for 1.5°C and 2°C of Global Warming .......................................258 Box 3.1: Sub-Saharan Africa: Changes in Temperature and Precipitation Extremes ....................................................197 3.5.5 Avoiding Regional Tipping Points by Achieving More Ambitious Global Temperature Goals ................262 Box 3.2: Droughts in the Mediterranean Basin and the Middle East ........................................................................200 Box 3.6: Economic Damages from Climate Change ............264 3.3.5 Runoff and Fluvial Flooding .......................................201 3.6 Implications of Different 1.5°C and 2°C 3.3.6 Tropical Cyclones and Extratropical Storms ................203 Pathways .........................................................................265 3.3.7 Ocean Circulation and Temperature ...........................204 3.6.1 Gradual versus Overshoot in 1.5°C Scenarios ............265 3.3.8 Sea Ice ........................................................................205 3.6.2 Non-CO2 Implications and Projected Risks of 3.3.9 Sea Level ....................................................................206 Mitigation Pathways ..................................................265 Box 3.3: Lessons from Past Warm Climate Episodes ...........208 Cross-Chapter Box 7: Land-Based Carbon Dioxide Removal in Relation to 1.5°C of Global Warming ...............268 3.3.10 Ocean Chemistry ........................................................209 3.6.3 Implications Beyond the End of the Century ..............270 3.3.11 Global Synthesis .........................................................210 3.7 Knowledge Gaps ...........................................................272 3.4 Observed Impacts and Projected Risks in Natural and Human Systems ................................212 3.7.1 Gaps in Methods and Tools ........................................272 3.4.1 Introduction ...............................................................212 3.7.2 Gaps in Understanding ...............................................272 3.4.2 Freshwater Resources (Quantity and Quality) .............213 Cross-Chapter Box 8: 1.5°C Warmer Worlds .........................274 3.4.3 Terrestrial and Wetland Ecosystems ...........................216 3.4.4 Ocean Ecosystems ......................................................221 Frequently Asked Questions Box 3.4: Warm-Water (Tropical) Coral Reefs in a 1.5°C FAQ 3.1 What are the Impacts of 1.5°C and 2°C Warmer World ..........................................................................229 of Warming? .......................................................................282 3.4.5 Coastal and Low-Lying Areas, and Sea Level Rise .......231 Box 3.5: Small Island Developing States (SIDS)...................234 References ...................................................................................284 3.4.6 Food, Nutrition Security and Food Production Systems (Including Fisheries and Aquaculture) ...........236 176 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Executive Summary There is no single ‘1.5°C warmer world’ (high confidence). In addition to the overall increase in GMST, it is important to consider the size and duration of potential overshoots in temperature. Furthermore, This chapter builds on findings of AR5 and assesses new scientific there are questions on how the stabilization of an increase in GMST of evidence of changes in the climate system and the associated impacts 1.5°C can be achieved, and how policies might be able to influence the on natural and human systems, with a specific focus on the magnitude resilience of human and natural systems, and the nature of regional and pattern of risks linked for global warming of 1.5°C above and subregional risks. Overshooting poses large risks for natural and temperatures in the pre-industrial period. Chapter 3 explores observed human systems, especially if the temperature at peak warming is impacts and projected risks to a range of natural and human systems, high, because some risks may be long-lasting and irreversible, such with a focus on how risk levels change from 1.5°C to 2°C of global as the loss of some ecosystems (high confidence). The rate of change warming. The chapter also revisits major categories of risk (Reasons for for several types of risks may also have relevance, with potentially Concern, RFC) based on the assessment of new knowledge that has large risks in the case of a rapid rise to overshooting temperatures, become available since AR5. even if a decrease to 1.5°C can be achieved at the end of the 21st century or later (medium confidence). If overshoot is to be minimized, 1.5°C and 2°C Warmer Worlds the remaining equivalent CO2 budget available for emissions is very small, which implies that large, immediate and unprecedented global The global climate has changed relative to the pre-industrial efforts to mitigate greenhouse gases are required (high confidence). period, and there are multiple lines of evidence that these {3.2, 3.6.2, Cross-Chapter Box 8 in this chapter} changes have had impacts on organisms and ecosystems, as well as on human systems and well-being (high confidence). The Robust1 global differences in temperature means and extremes increase in global mean surface temperature (GMST), which reached are expected if global warming reaches 1.5°C versus 2°C above 0.87°C in 2006–2015 relative to 1850–1900, has increased the the pre-industrial levels (high confidence). For oceans, regional frequency and magnitude of impacts (high confidence), strengthening surface temperature means and extremes are projected to be higher evidence of how an increase in GMST of 1.5°C or more could impact at 2°C compared to 1.5°C of global warming (high confidence). 3 natural and human systems (1.5°C versus 2°C). {3.3, 3.4, 3.5, 3.6, Temperature means and extremes are also projected to be higher at Cross-Chapter Boxes 6, 7 and 8 in this chapter} 2°C compared to 1.5°C in most land regions, with increases being 2–3 times greater than the increase in GMST projected for some Human-induced global warming has already caused multiple regions (high confidence). Robust increases in temperature means and observed changes in the climate system (high confidence). extremes are also projected at 1.5°C compared to present-day values Changes include increases in both land and ocean temperatures, as well (high confidence) {3.3.1, 3.3.2}. There are decreases in the occurrence as more frequent heatwaves in most land regions (high confidence). of cold extremes, but substantial increases in their temperature, in There is also high confidence that global warming has resulted in an particular in regions with snow or ice cover (high confidence) {3.3.1}. increase in the frequency and duration of marine heatwaves. Further, there is substantial evidence that human-induced global warming has Climate models project robust1 differences in regional climate led to an increase in the frequency, intensity and/or amount of heavy between present-day and global warming up to 1.5°C2, and precipitation events at the global scale (medium confidence), as well between 1.5°C and 2°C2 (high confidence), depending on the as an increased risk of drought in the Mediterranean region (medium variable and region in question (high confidence). Large, robust confidence). {3.3.1, 3.3.2, 3.3.3, 3.3.4, Box 3.4} and widespread differences are expected for temperature extremes (high confidence). Regarding hot extremes, the strongest Trends in intensity and frequency of some climate and weather warming is expected to occur at mid-latitudes in the warm season (with extremes have been detected over time spans during which increases of up to 3°C for 1.5°C of global warming, i.e., a factor of two) about 0.5°C of global warming occurred (medium confidence). and at high latitudes in the cold season (with increases of up to 4.5°C This assessment is based on several lines of evidence, including at 1.5°C of global warming, i.e., a factor of three) (high confidence). attribution studies for changes in extremes since 1950. {3.2, 3.3.1, The strongest warming of hot extremes is projected to occur in 3.3.2, 3.3.3, 3.3.4} central and eastern North America, central and southern Europe, the Mediterranean region (including southern Europe, northern Africa and Several regional changes in climate are assessed to occur with the Near East), western and central Asia, and southern Africa (medium global warming up to 1.5°C as compared to pre-industrial confidence). The number of exceptionally hot days are expected to levels, including warming of extreme temperatures in many increase the most in the tropics, where interannual temperature regions (high confidence), increases in frequency, intensity and/or variability is lowest; extreme heatwaves are thus projected to emerge amount of heavy precipitation in several regions (high confidence), earliest in these regions, and they are expected to already become and an increase in intensity or frequency of droughts in some regions widespread there at 1.5°C global warming (high confidence). Limiting (medium confidence). {3.3.1, 3.3.2, 3.3.3, 3.3.4, Table 3.2} global warming to 1.5°C instead of 2°C could result in around 420 1 Robust is used here to mean that at least two thirds of climate models show the same sign of changes at the grid point scale, and that differences in large regions are statistically significant. 2 Projected changes in impacts between different levels of global warming are determined with respect to changes in global mean near-surface air temperature. 177 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems million fewer people being frequently exposed to extreme heatwaves, Global warming of 2°C would lead to an expansion of areas with and about 65 million fewer people being exposed to exceptional significant increases in runoff, as well as those affected by flood heatwaves, assuming constant vulnerability (medium confidence). hazard, compared to conditions at 1.5°C (medium confidence). {3.3.1, 3.3.2, Cross-Chapter Box 8 in this chapter} Global warming of 1.5°C would also lead to an expansion of the global land area with significant increases in runoff (medium confidence) and Limiting global warming to 1.5°C would limit risks of increases an increase in flood hazard in some regions (medium confidence) in heavy precipitation events on a global scale and in several compared to present-day conditions. {3.3.5} regions compared to conditions at 2°C global warming (medium confidence). The regions with the largest increases in heavy The probability of a sea-ice-free Arctic Ocean3 during summer precipitation events for 1.5°C to 2°C global warming include: several is substantially higher at 2°C compared to 1.5°C of global high-latitude regions (e.g. Alaska/western Canada, eastern Canada/ warming (medium confidence). Model simulations suggest that Greenland/Iceland, northern Europe and northern Asia); mountainous at least one sea-ice-free Arctic summer is expected every 10 years regions (e.g., Tibetan Plateau); eastern Asia (including China and Japan); for global warming of 2°C, with the frequency decreasing to one and eastern North America (medium confidence). Tropical cyclones are sea-ice-free Arctic summer every 100 years under 1.5°C (medium projected to decrease in frequency but with an increase in the number confidence). An intermediate temperature overshoot will have no long- of very intense cyclones (limited evidence, low confidence). Heavy term consequences for Arctic sea ice coverage, and hysteresis is not precipitation associated with tropical cyclones is projected to be higher expected (high confidence). {3.3.8, 3.4.4.7} at 2°C compared to 1.5°C of global warming (medium confidence). Heavy precipitation, when aggregated at a global scale, is projected to Global mean sea level rise (GMSLR) is projected to be around be higher at 2°C than at 1.5°C of global warming (medium confidence) 0.1 m (0.04 – 0.16 m) less by the end of the 21st century in a {3.3.3, 3.3.6} 1.5°C warmer world compared to a 2°C warmer world (medium confidence). Projected GMSLR for 1.5°C of global warming has an Limiting global warming to 1.5°C is expected to substantially indicative range of 0.26 – 0.77m, relative to 1986–2005, (medium 3 reduce the probability of extreme drought, precipitation deficits, confidence). A smaller sea level rise could mean that up to 10.4 million and risks associated with water availability (i.e., water stress) in fewer people (based on the 2010 global population and assuming no some regions (medium confidence). In particular, risks associated adaptation) would be exposed to the impacts of sea level rise globally with increases in drought frequency and magnitude are projected to be in 2100 at 1.5°C compared to at 2°C. A slower rate of sea level rise substantially larger at 2°C than at 1.5°C in the Mediterranean region enables greater opportunities for adaptation (medium confidence). (including southern Europe, northern Africa and the Near East) and There is high confidence that sea level rise will continue beyond 2100. southern Africa (medium confidence). {3.3.3, 3.3.4, Box 3.1, Box 3.2} Instabilities exist for both the Greenland and Antarctic ice sheets, which could result in multi-meter rises in sea level on time scales of century Risks to natural and human systems are expected to be lower to millennia. There is medium confidence that these instabilities could at 1.5°C than at 2°C of global warming (high confidence). This be triggered at around 1.5°C to 2°C of global warming. {3.3.9, 3.4.5, difference is due to the smaller rates and magnitudes of climate 3.6.3} change associated with a 1.5°C temperature increase, including lower frequencies and intensities of temperature-related extremes. Lower The ocean has absorbed about 30% of the anthropogenic rates of change enhance the ability of natural and human systems carbon dioxide, resulting in ocean acidification and changes to to adapt, with substantial benefits for a wide range of terrestrial, carbonate chemistry that are unprecedented for at least the freshwater, wetland, coastal and ocean ecosystems (including coral last 65 million years (high confidence). Risks have been identified reefs) (high confidence), as well as food production systems, human for the survival, calcification, growth, development and abundance of health, and tourism (medium confidence), together with energy a broad range of marine taxonomic groups, ranging from algae to fish, systems and transportation (low confidence). {3.3.1, 3.4} with substantial evidence of predictable trait-based sensitivities (high confidence). There are multiple lines of evidence that ocean warming Exposure to multiple and compound climate-related risks is and acidification corresponding to 1.5°C of global warming would projected to increase between 1.5°C and 2°C of global warming impact a wide range of marine organisms and ecosystems, as well as with greater proportions of people both exposed and susceptible to sectors such as aquaculture and fisheries (high confidence). {3.3.10, poverty in Africa and Asia (high confidence). For global warming from 3.4.4} 1.5°C to 2°C, risks across energy, food, and water sectors could overlap spatially and temporally, creating new – and exacerbating current – Larger risks are expected for many regions and systems for hazards, exposures, and vulnerabilities that could affect increasing global warming at 1.5°C, as compared to today, with adaptation numbers of people and regions (medium confidence). Small island required now and up to 1.5°C. However, risks would be larger at 2°C of states and economically disadvantaged populations are particularly at warming and an even greater effort would be needed for adaptation to risk (high confidence). {3.3.1, 3.4.5.3, 3.4.5.6, 3.4.11, 3.5.4.9, Box 3.5} a temperature increase of that magnitude (high confidence). {3.4, Box 3.4, Box 3.5, Cross-Chapter Box 6 in this chapter} 3 Ice free is defined for the Special Report as when the sea ice extent is less than 106 km2. Ice coverage less than this is considered to be equivalent to an ice-free Arctic Ocean for practical purposes in all recent studies. 178 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Future risks at 1.5°C of global warming will depend on the Ocean Ecosystems mitigation pathway and on the possible occurrence of a transient overshoot (high confidence). The impacts on natural Ocean ecosystems are already experiencing large-scale and human systems would be greater if mitigation pathways changes, and critical thresholds are expected to be reached at temporarily overshoot 1.5°C and return to 1.5°C later in the century, 1.5°C and higher levels of global warming (high confidence). as compared to pathways that stabilize at 1.5°C without an overshoot In the transition to 1.5°C of warming, changes to water temperatures (high confidence). The size and duration of an overshoot would also are expected to drive some species (e.g., plankton, fish) to relocate affect future impacts (e.g., irreversible loss of some ecosystems) (high to higher latitudes and cause novel ecosystems to assemble (high confidence). Changes in land use resulting from mitigation choices confidence). Other ecosystems (e.g., kelp forests, coral reefs) are could have impacts on food production and ecosystem diversity. {3.6.1, relatively less able to move, however, and are projected to experience 3.6.2, Cross-Chapter Boxes 7 and 8 in this chapter} high rates of mortality and loss (very high confidence). For example, multiple lines of evidence indicate that the majority (70–90%) of Climate Change Risks for Natural and Human systems warm water (tropical) coral reefs that exist today will disappear even if global warming is constrained to 1.5°C (very high confidence). Terrestrial and Wetland Ecosystems {3.4.4, Box 3.4} Risks of local species losses and, consequently, risks of Current ecosystem services from the ocean are expected to be extinction are much less in a 1.5°C versus a 2°C warmer world reduced at 1.5°C of global warming, with losses being even (high confidence). The number of species projected to lose over greater at 2°C of global warming (high confidence). The risks half of their climatically determined geographic range at 2°C global of declining ocean productivity, shifts of species to higher latitudes, warming (18% of insects, 16% of plants, 8% of vertebrates) is damage to ecosystems (e.g., coral reefs, and mangroves, seagrass projected to be reduced to 6% of insects, 8% of plants and 4% of and other wetland ecosystems), loss of fisheries productivity (at vertebrates at 1.5°C warming (medium confidence). Risks associated low latitudes), and changes to ocean chemistry (e.g., acidification, with other biodiversity-related factors, such as forest fires, extreme hypoxia and dead zones) are projected to be substantially lower 3 weather events, and the spread of invasive species, pests and when global warming is limited to 1.5°C (high confidence). {3.4.4, diseases, would also be lower at 1.5°C than at 2°C of warming (high Box 3.4} confidence), supporting a greater persistence of ecosystem services. {3.4.3, 3.5.2} Water Resources Constraining global warming to 1.5°C, rather than to 2°C The projected frequency and magnitude of floods and droughts and higher, is projected to have many benefits for terrestrial in some regions are smaller under 1.5°C than under 2°C of and wetland ecosystems and for the preservation of their warming (medium confidence). Human exposure to increased services to humans (high confidence). Risks for natural and flooding is projected to be substantially lower at 1.5°C compared to managed ecosystems are higher on drylands compared to humid 2°C of global warming, although projected changes create regionally lands. The global terrestrial land area projected to be affected by differentiated risks (medium confidence). The differences in the risks ecosystem transformations (13%, interquartile range 8–20%) at 2°C among regions are strongly influenced by local socio-economic is approximately halved at 1.5°C global warming to 4% (interquartile conditions (medium confidence). {3.3.4, 3.3.5, 3.4.2} range 2–7%) (medium confidence). Above 1.5°C, an expansion of desert terrain and vegetation would occur in the Mediterranean Risks of water scarcity are projected to be greater at 2°C than at biome (medium confidence), causing changes unparalleled in the last 1.5°C of global warming in some regions (medium confidence). 10,000 years (medium confidence). {3.3.2.2, 3.4.3.2, 3.4.3.5, 3.4.6.1, Depending on future socio-economic conditions, limiting global 3.5.5.10, Box 4.2} warming to 1.5°C, compared to 2°C, may reduce the proportion of the world population exposed to a climate change-induced increase Many impacts are projected to be larger at higher latitudes, in water stress by up to 50%, although there is considerable variability owing to mean and cold-season warming rates above the between regions (medium confidence). Regions with particularly global average (medium confidence). High-latitude tundra and large benefits could include the Mediterranean and the Caribbean boreal forest are particularly at risk, and woody shrubs are already (medium confidence). Socio-economic drivers, however, are expected encroaching into tundra (high confidence) and will proceed with to have a greater influence on these risks than the changes in climate further warming. Constraining warming to 1.5°C would prevent the (medium confidence). {3.3.5, 3.4.2, Box 3.5} thawing of an estimated permafrost area of 1.5 to 2.5 million km2 over centuries compared to thawing under 2°C (medium confidence). Land Use, Food Security and Food Production Systems {3.3.2, 3.4.3, 3.4.4} Limiting global warming to 1.5°C, compared with 2°C, is projected to result in smaller net reductions in yields of maize, rice, wheat, and potentially other cereal crops, particularly in 179 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems sub-Saharan Africa, Southeast Asia, and Central and South America; The impacts of large-scale CDR deployment could be greatly and in the CO2-dependent nutritional quality of rice and wheat reduced if a wider portfolio of CDR options were deployed, if a (high confidence). A loss of 7–10% of rangeland livestock globally holistic policy for sustainable land management were adopted, is projected for approximately 2°C of warming, with considerable and if increased mitigation efforts were employed to strongly economic consequences for many communities and regions (medium limit the demand for land, energy and material resources, confidence). {3.4.6, 3.6, Box 3.1, Cross-Chapter Box 6 in this chapter} including through lifestyle and dietary changes (medium confidence). In particular, reforestation could be associated with Reductions in projected food availability are larger at 2°C significant co-benefits if implemented in a manner than helps restore than at 1.5°C of global warming in the Sahel, southern Africa, natural ecosystems (high confidence). {Cross-Chapter Box 7 in this the Mediterranean, central Europe and the Amazon (medium chapter} confidence). This suggests a transition from medium to high risk of regionally differentiated impacts on food security between 1.5°C and Human Health, Well-Being, Cities and Poverty 2°C (medium confidence). Future economic and trade environments and their response to changing food availability (medium confidence) Any increase in global temperature (e.g., +0.5°C) is projected are important potential adaptation options for reducing hunger risk to affect human health, with primarily negative consequences in low- and middle-income countries. {Cross-Chapter Box 6 in this (high confidence). Lower risks are projected at 1.5°C than at 2°C chapter} for heat-related morbidity and mortality (very high confidence), and for ozone-related mortality if emissions needed for ozone formation Fisheries and aquaculture are important to global food security remain high (high confidence). Urban heat islands often amplify the but are already facing increasing risks from ocean warming impacts of heatwaves in cities (high confidence). Risks for some and acidification (medium confidence). These risks are vector-borne diseases, such as malaria and dengue fever are projected projected to increase at 1.5°C of global warming and impact to increase with warming from 1.5°C to 2°C, including potential key organisms such as fin fish and bivalves (e.g., oysters), shifts in their geographic range (high confidence). Overall for vector- 3 especially at low latitudes (medium confidence). Small-scale borne diseases, whether projections are positive or negative depends fisheries in tropical regions, which are very dependent on habitat on the disease, region and extent of change (high confidence). Lower provided by coastal ecosystems such as coral reefs, mangroves, risks of undernutrition are projected at 1.5°C than at 2°C (medium seagrass and kelp forests, are expected to face growing risks at 1.5°C confidence). Incorporating estimates of adaptation into projections of warming because of loss of habitat (medium confidence). Risks reduces the magnitude of risks (high confidence). {3.4.7, 3.4.7.1, of impacts and decreasing food security are projected to become 3.4.8, 3.5.5.8} greater as global warming reaches beyond 1.5°C and both ocean warming and acidification increase, with substantial losses likely for Global warming of 2°C is expected to pose greater risks to urban coastal livelihoods and industries (e.g., fisheries and aquaculture) areas than global warming of 1.5°C (medium confidence). The (medium to high confidence). {3.4.4, 3.4.5, 3.4.6, Box 3.1, Box 3.4, extent of risk depends on human vulnerability and the effectiveness Box 3.5, Cross-Chapter Box 6 in this chapter} of adaptation for regions (coastal and non-coastal), informal settlements and infrastructure sectors (such as energy, water and Land use and land-use change emerge as critical features of transport) (high confidence). {3.4.5, 3.4.8} virtually all mitigation pathways that seek to limit global warming to 1.5°C (high confidence). Most least-cost mitigation Poverty and disadvantage have increased with recent warming pathways to limit peak or end-of-century warming to 1.5°C make (about 1°C) and are expected to increase for many populations use of carbon dioxide removal (CDR), predominantly employing as average global temperatures increase from 1°C to 1.5°C significant levels of bioenergy with carbon capture and storage and higher (medium confidence). Outmigration in agricultural- (BECCS) and/or afforestation and reforestation (AR) in their portfolio dependent communities is positively and statistically significantly of mitigation measures (high confidence). {Cross-Chapter Box 7 in associated with global temperature (medium confidence). Our this chapter} understanding of the links of 1.5°C and 2°C of global warming to human migration are limited and represent an important knowledge Large-scale deployment of BECCS and/or AR would have gap. {3.4.10, 3.4.11, 5.2.2, Table 3.5} a far-reaching land and water footprint (high confidence). Whether this footprint would result in adverse impacts, for example Key Economic Sectors and Services on biodiversity or food production, depends on the existence and effectiveness of measures to conserve land carbon stocks, measures Risks to global aggregated economic growth due to climate to limit agricultural expansion in order to protect natural ecosystems, change impacts are projected to be lower at 1.5°C than at 2°C and the potential to increase agricultural productivity (medium by the end of this century (medium confidence). {3.5.2, 3.5.3} agreement). In addition, BECCS and/or AR would have substantial direct effects on regional climate through biophysical feedbacks, The largest reductions in economic growth at 2°C compared which are generally not included in Integrated Assessments Models to 1.5°C of warming are projected for low- and middle-income (high confidence). {3.6.2, Cross-Chapter Boxes 7 and 8 in this chapter} countries and regions (the African continent, Southeast Asia, India, Brazil and Mexico) (low to medium confidence). Countries 180 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 in the tropics and Southern Hemisphere subtropics are projected to Increased Reasons for Concern experience the largest impacts on economic growth due to climate change should global warming increase from 1.5°C to 2°C (medium There are multiple lines of evidence that since AR5 the assessed confidence). {3.5} levels of risk increased for four of the five Reasons for Concern (RFCs) for global warming levels of up to 2°C (high confidence). Global warming has already affected tourism, with increased The risk transitions by degrees of global warming are now: from high risks projected under 1.5°C of warming in specific geographic to very high between 1.5°C and 2°C for RFC1 (Unique and threatened regions and for seasonal tourism including sun, beach and systems) (high confidence); from moderate to high risk between 1°C and snow sports destinations (very high confidence). Risks will be 1.5°C for RFC2 (Extreme weather events) (medium confidence); from lower for tourism markets that are less climate sensitive, such as moderate to high risk between 1.5°C and 2°C for RFC3 (Distribution of gaming and large hotel-based activities (high confidence). Risks for impacts) (high confidence); from moderate to high risk between 1.5°C coastal tourism, particularly in subtropical and tropical regions, will and 2.5°C for RFC4 (Global aggregate impacts) (medium confidence); increase with temperature-related degradation (e.g., heat extremes, and from moderate to high risk between 1°C and 2.5°C for RFC5 storms) or loss of beach and coral reef assets (high confidence). (Large-scale singular events) (medium confidence). {3.5.2} {3.3.6, 3.4.4.12, 3.4.9.1, Box 3.4} 1. The category ‘Unique and threatened systems’ (RFC1) Small Islands, and Coastal and Low-lying areas display a transition from high to very high risk which is now located between 1.5°C and 2°C of global warming as Small islands are projected to experience multiple inter- opposed to at 2.6°C of global warming in AR5, owing to new and related risks at 1.5°C of global warming that will increase with multiple lines of evidence for changing risks for coral reefs, the warming of 2°C and higher levels (high confidence). Climate Arctic and biodiversity in general (high confidence). {3.5.2.1} hazards at 1.5°C are projected to be lower compared to those at 2°C (high confidence). Long-term risks of coastal flooding and impacts on 2. In ‘Extreme weather events’ (RFC2), the transition from populations, infrastructures and assets (high confidence), freshwater moderate to high risk is now located between 1.0°C and 3 stress (medium confidence), and risks across marine ecosystems (high 1.5°C of global warming, which is very similar to the AR5 confidence) and critical sectors (medium confidence) are projected to assessment but is projected with greater confidence (medium increase at 1.5°C compared to present-day levels and increase further confidence). The impact literature contains little information at 2°C, limiting adaptation opportunities and increasing loss and about the potential for human society to adapt to extreme damage (medium confidence). Migration in small islands (internally weather events, and hence it has not been possible to locate and internationally) occurs for multiple reasons and purposes, mostly the transition from ‘high’ to ‘very high’ risk within the context of for better livelihood opportunities (high confidence) and increasingly assessing impacts at 1.5°C versus 2°C of global warming. There owing to sea level rise (medium confidence). {3.3.2.2, 3.3.6–9, is thus low confidence in the level at which global warming could 3.4.3.2, 3.4.4.2, 3.4.4.5, 3.4.4.12, 3.4.5.3, 3.4.7.1, 3.4.9.1, 3.5.4.9, lead to very high risks associated with extreme weather events in Box 3.4, Box 3.5} the context of this report. {3.5} Impacts associated with sea level rise and changes to the 3. With respect to the ‘Distribution of impacts’ (RFC3) a salinity of coastal groundwater, increased flooding and transition from moderate to high risk is now located damage to infrastructure, are projected to be critically between 1.5°C and 2°C of global warming, compared with important in vulnerable environments, such as small islands, between 1.6°C and 2.6°C global warming in AR5, owing to new low-lying coasts and deltas, at global warming of 1.5°C and evidence about regionally differentiated risks to food security, 2°C (high confidence). Localized subsidence and changes to river water resources, drought, heat exposure and coastal submergence discharge can potentially exacerbate these effects. Adaptation is (high confidence). {3.5} already happening (high confidence) and will remain important over multi-centennial time scales. {3.4.5.3, 3.4.5.4, 3.4.5.7, 5.4.5.4, Box 4. In ‘global aggregate impacts’ (RFC4) a transition from 3.5} moderate to high levels of risk is now located between 1.5°C and 2.5°C of global warming, as opposed to at 3.6°C of Existing and restored natural coastal ecosystems may be warming in AR5, owing to new evidence about global aggregate effective in reducing the adverse impacts of rising sea levels economic impacts and risks to Earth’s biodiversity (medium and intensifying storms by protecting coastal and deltaic confidence). {3.5} regions (medium confidence). Natural sedimentation rates are expected to be able to offset the effect of rising sea levels, given 5. Finally, ‘large-scale singular events’ (RFC5), moderate risk the slower rates of sea level rise associated with 1.5°C of warming is now located at 1°C of global warming and high risk is (medium confidence). Other feedbacks, such as landward migration located at 2.5°C of global warming, as opposed to at 1.6°C of wetlands and the adaptation of infrastructure, remain important (moderate risk) and around 4°C (high risk) in AR5, because of new (medium confidence). {3.4.4.12, 3.4.5.4, 3.4.5.7} observations and models of the West Antarctic ice sheet (medium confidence). {3.3.9, 3.5.2, 3.6.3} 181 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems 3.1 About the Chapter This chapter is necessarily transdisciplinary in its coverage of the climate system, natural and managed ecosystems, and human systems and responses, owing to the integrated nature of the natural Chapter 3 uses relevant definitions of a potential 1.5°C warmer world and human experience. While climate change is acknowledged as a from Chapters 1 and 2 and builds directly on their assessment of gradual centrally important driver, it is not the only driver of risks to human and versus overshoot scenarios. It interacts with information presented in natural systems, and in many cases, it is the interaction between these Chapter 2 via the provision of specific details relating to the mitigation two broad categories of risk that is important (Chapter 1). pathways (e.g., land-use changes) and their implications for impacts. Chapter 3 also includes information needed for the assessment and The flow of the chapter, linkages between sections, a list of chapter- implementation of adaptation options (presented in Chapter 4), as and cross-chapter boxes, and a content guide for reading according well as the context for considering the interactions of climate change to focus or interest are given in Figure 3.1. Key definitions used in the with sustainable development and for the assessment of impacts on chapter are collected in the Glossary. Confidence language is used sustainability, poverty and inequalities at the household to subregional throughout this chapter and likelihood statements (e.g., likely, very level (presented in Chapter 5). likely) are provided when there is high confidence in the assessment. Section 3.1 Global and Regional Global and Regional Temperature Introduction Precipitation 3.3.1 | 3.3.2 | 3.3.4 | Box 3.3 | 3.3.11 3.3.1 | 3.3.3 | 3.3.4 | 3.3.11 Drought Floods 3.3.4 | Box 3.2 | 3.4.2 | 3.3.11 3.3.5 | 3.4.2 | 3.4.5 | 3.3.11 Section 3.2 Extreme Weather Snow, Permafrost and Sea Ice Assessing 1.5°C 3.3.2 | 3.3.3 | 3.3.4 | 3.3.6 | 3.3.11 | 3.3.8 | 3.4.4 | 3.5.4 | 3.5.5 | 3.6.3 | 3.4.4 | 3.5.2 3.3.11 3 Sea Level3.3.9 | 3.4.4 | 3.4.5 | 3.4.12 | 3.5.2 | 3.6.3 Section 3.3 Section 3.4 Global and Regional Observed Impacts and Ecosystems Food Security Climate Changes and Projected Risks in Natural 3.4.3 | 3.4.4 | 3.4.5 | 3.4.12 | Box 3.4.6 | 3.4.12 | 3.5.5 | 3.6.2 | X-Box 6 | Associated Hazards and Human Systems 3.4 | 3.5.2 | 3.5.5 X-Box 7 Freshwater Oceans 3.4.2 | 3.4.12 3.3.7 | 3.3.10 | 3.3.11 | 3.4.4 | 3.4.12 Regional Outlooks Coastal and Low Lying Areas 3.3.2 | 3.3.3 | 3.4.3 | Box 3.1 | Box 3.3.5 | 3.4.5 | Box 3.5 | 3.5.4 | 3.4.12 3.2 | 3.4.5 | Box 3.5 | 3.5.4 | 3.5.5 | Section 3.5 Section 3.6 3.3.11 Avoided Impacts and Implications of Different Reduced Risks Cities1.5°C and 2°C Pathways 3.4.5 | 3.4.8 | 3.4.9 Health Key Economic Sectors and Services 3.4.7 | 3.4.12 | 3.5.5 3.4.9 | 3.4.12 Section 3.7 Livelihoods and Poverty RFCs, Hot Spots and Tipping Points Knowledge Gaps 3.4.6 | 3.4.10 3.4.12 | 3.4.13 | 3.5.2 | 3.5.4 | 3.5.5 Box 3.1 Box 3.2 Box 3.3 Box 3.4 Box 3.5 Box 3.6 X-Box 6 X-Box 7 X-Box 8 Sub- Droughts in the Lessons from Warm Water Small Island Economic Food Land-Based Carbon 1.5°C Saharan Mediterranean Past Warm Coral Reefs in Developing Damage from Security Dioxide Removal in Warmer Africa Basin and the Climate a 1.5°C States (SIDS) Climate Change Relation to 1.5°C of Worlds Middle East Episodes Warmer World Global Warming Figure 3.1 | Chapter 3 structure and quick guide. The underlying literature assessed in Chapter 3 is broad and includes a on a broad range of assessment methods. Details about the approaches large number of recent publications specific to assessments for 1.5°C used are presented in Section 3.2. of warming. The chapter also utilizes information covered in prior IPCC special reports, for example the Special Report on Managing the Section 3.3 gives a general overview of recent literature on observed Risks of Extreme Events and Disasters to Advance Climate Change climate change impacts as the context for projected future risks. With Adaptation (SREX; IPCC, 2012), and many chapters from the IPCC a few exceptions, the focus here is the analysis of transient responses WGII Fifth Assessment Report (AR5) that assess impacts on natural at 1.5°C and 2°C of global warming, with simulations of short-term and managed ecosystems and humans, as well as adaptation options stabilization scenarios (Section 3.2) also assessed in some cases. In (IPCC, 2014b). For this reason, the chapter provides information based general, long-term equilibrium stabilization responses could not be 182 Chapter Boxes Chapter Structure Quick Guide Cross Chapter Boxes Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 assessed owing to a lack of data and analysis. A detailed analysis of sections in Chapter 3, highlights knowledge gaps resulting from the detection and attribution is not provided but will be the focus of the next heterogeneous information available across systems, regions and IPCC assessment report (AR6). Furthermore, possible interventions in sectors. Some of these gaps are described in Section 3.7. the climate system through radiation modification measures, which are not tied to reductions of greenhouse gas emissions or concentrations, are not assessed in this chapter. 3.2 How are Risks at 1.5°C and Understanding the observed impacts and projected risks of climate Higher Levels of Global Warming change is crucial to comprehending how the world is likely to change Assessed in this Chapter? under global warming of 1.5°C above temperatures in the pre-industrial period (with reference to 2°C). Section 3.4 explores the new literature The methods that are applied for assessing observed and projected and updates the assessment of impacts and projected risks for a large changes in climate and weather are presented in Section 3.2.1, while number of natural and human systems. By also exploring adaptation those used for assessing the observed impacts on and projected risks to opportunities, where the literature allows, the section prepares the natural and managed systems, and to human settlements, are described reader for discussions in subsequent chapters about opportunities to in Section 3.2.2. Given that changes in climate associated with 1.5°C tackle both mitigation and adaptation. The section is mostly globally of global warming were not the focus of past IPCC reports, dedicated focused because of limited research on regional risks and adaptation approaches based on recent literature that are specific to the present options at 1.5°C and 2°C. For example, the risks of 1.5°C and 2°C of report are also described. Background on specific methodological warming in urban areas, as well as the risks of health outcomes under aspects (climate model simulations available for assessments at 1.5°C these two warming scenarios (e.g. climate-related diseases, air quality global warming, attribution of observed changes in climate and their impacts and mental health problems), were not considered because relevance for assessing projected changes at 1.5°C and 2°C global of a lack of projections of how these risks might change in a 1.5°C or warming, and the propagation of uncertainties from climate forcing 2°C warmer world. In addition, the complexity of many interactions to impacts on ecosystems) are provided in the Supplementary Material of climate change with drivers of poverty, along with a paucity of 3.SM. 3 relevant studies, meant it was not possible to detect and attribute many dimensions of poverty and disadvantage to climate change. Even 3.2.1 How are Changes in Climate and Weather at 1.5°C though there is increasing documentation of climate-related impacts on versus Higher Levels of Warming Assessed? places where indigenous people live and where subsistence-oriented communities are found, relevant projections of the risks associated Evidence for the assessment of changes to climate at 1.5°C versus with warming of 1.5°C and 2°C are necessarily limited. 2°C can be drawn both from observations and model projections. Global mean surface temperature (GMST) anomalies were about To explore avoided impacts and reduced risks at 1.5°C compared with +0.87°C (±0.10°C likely range) above pre-industrial industrial (1850– at 2°C of global warming, the chapter adopts the AR5 ‘Reasons for 1900) values in the 2006-–2015 decade, with a recent warming Concern’ aggregated projected risk framework (Section 3.5). Updates of about 0.2°C (±0.10°C) per decade (Chapter 1). Human-induced in terms of the aggregation of risks are informed by the most recent global warming reached approximately 1°C (±0.2°C likely range) in literature and the assessments offered in Sections 3.3 and 3.4, with 2017 (Chapter 1). While some of the observed trends may be due a focus on the impacts at 2°C of warming that could potentially be to internal climate variability, methods of detection and attribution avoided if warming were constrained to 1.5°C. Economic benefits that can be applied to assess which part of the observed changes may be would be obtained (Section 3.5.3), climate change ‘hotspots’ that could attributed to anthropogenic forcing (Bindoff et al., 2013b). Hence, be avoided or reduced (Section 3.5.4 as guided by the assessments of evidence from attribution studies can be used to assess changes Sections 3.3, 3.4 and 3.5), and tipping points that could be circumvented in the climate system that are already detectable at lower levels of (Section 3.5.5) at 1.5°C compared to higher degrees of global warming global warming and would thus continue to change with a further are all examined. The latter assessments are, however, constrained to 0.5°C or 1°C of global warming (see Supplementary Material 3.SM.1 regional analyses, and hence this particular section does not include an and Sections 3.3.1, 3.3.2, 3.3.3, 3.3.4 and 3.3.11). A recent study assessment of specific losses and damages. identified significant changes in extremes for a 0.5°C difference in global warming based on the historical record (Schleussner et al., Section 3.6 provides an overview on specific aspects of the mitigation 2017). It should also be noted that attributed changes in extremes pathways considered compatible with 1.5°C of global warming, since 1950 that were reported in the IPCC AR5 report (IPCC, 2013) including some scenarios involving temperature overshoot above generally correspond to changes in global warming of about 0.5°C 1.5°C global warming during the 21st century. Non-CO2 implications (see 3.SM.1) and projected risks of mitigation pathways, such as changes to land use and atmospheric compounds, are presented and explored. Finally, Climate model simulations are necessary for the investigation of implications for sea ice, sea level and permafrost beyond the end of the the response of the climate system to various forcings, in particular century are assessed. to forcings associated with higher levels of greenhouse gas concentrations. Model simulations include experiments with global The exhaustive assessment of literature specific to global warming and regional climate models, as well as impact models – driven with of 1.5°C above the pre-industrial period, presented across all the output from climate models – to evaluate the risk related to climate 183 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems change for natural and human systems (Supplementary Material C. Most of the ‘1.5°C scenarios’, and some of the ‘2°C emissions 3.SM.1). Climate model simulations were generally used in the context scenarios’ presented in Chapter 2 include a temperature of particular ‘climate scenarios’ from previous IPCC reports (e.g., overshoot during the course of the 21st century. This means that IPCC, 2007, 2013). This means that emissions scenarios (IPCC, 2000) median temperature projections under these scenarios exceed were used to drive climate models, providing different projections the target warming levels over the course of the century (typically for given emissions pathways. The results were consequently used in 0.5°C–1°C higher than the respective target levels at most), a ‘storyline’ framework, which presents the development of climate before warming returns to below 1.5°C or 2°C by 2100. During in the course of the 21st century and beyond for a given emissions the overshoot phase, impacts would therefore correspond to pathway. Results were assessed for different time slices within the higher transient temperature increases than 1.5°C or 2°C. For this model projections such as 2016–2035 (‘near term’, which is slightly reason, impacts of transient responses at these higher warming below a global warming of 1.5°C according to most scenarios, Kirtman levels are also partly addressed in Cross-Chapter Box 8 in this et al., 2013), 2046–2065 (mid-21st century, Collins et al., 2013), and chapter (on a 1.5°C warmer world), and some analyses for 2081–2100 (end of 21st century, Collins et al., 2013). Given that this changes in extremes are also presented for higher levels of report focuses on climate change for a given mean global temperature warming in Section 3.3 (Figures 3.5, 3.6, 3.9, 3.10, 3.12 and 3.13). response (1.5°C or 2°C), methods of analysis had to be developed and/ Most importantly, different overshoot scenarios may have very or adapted from previous studies in order to provide assessments for distinct impacts depending on (i) the peak temperature of the specific purposes here. the overshoot, (ii) the length of the overshoot period, and (iii) the associated rate of change in global temperature over the A major challenge in assessing climate change under 1.5°C, or 2°C time period of the overshoot. While some of these issues are (and higher levels), of global warming pertains to the definition of briefly addressed in Sections 3.3 and 3.6, and in the Cross-Chapter a ‘1.5°C or 2°C climate projection’ (see also Cross-Chapter Box Box 8, the definition of overshoot and related questions will need 8 in this chapter). Resolving this challenge includes the following to be more comprehensively addressed in the IPCC AR6 report. considerations: 3 D. The levels of global warming that are the focus of this report A. The need to distinguish between (i) transient climate responses (1.5°C and 2°C) are measured relative to the pre-industrial period. (i.e., those that ‘pass through’ 1.5°C or 2°C of global warming), This definition requires an agreement on the exact reference time (ii) short-term stabilization responses (i.e., scenarios for the late period (for 0°C of warming) and the time frame over which the 21st century that result in stabilization at a mean global warming global warming is assessed, typically 20 to 30 years in length. As of 1.5°C or 2°C by 2100), and (iii) long-term equilibrium discussed in Chapter 1, a climate with 1.5°C global warming is stabilization responses (i.e., those occurring after several one in which temperatures averaged over a multi-decade time millennia once climate (temperature) equilibrium at 1.5°C or 2°C scale are 1.5°C above those in the pre-industrial reference period. is reached). These responses can be very different in terms of Greater detail is provided in Cross-Chapter Box 8 in this chapter. climate variables and the inertia associated with a given climate Inherent to this is the observation that the mean temperature of forcing. A striking example is sea level rise (SLR). In this case, a ‘1.5°C warmer world’ can be regionally and temporally much projected increases within the 21st century are minimally higher (e.g., with regional annual temperature extremes involving dependent on the scenario considered, yet they stabilize at very warming of more than 6°C; see Section 3.3 and Cross-Chapter different levels for a long-term warming of 1.5°C versus 2°C Box 8 in this chapter). (Section 3.3.9). E. The interference of factors unrelated to greenhouse gases with B. The ‘1.5°C or 2°C emissions scenarios’ presented in Chapter mitigation pathways can strongly affect regional climate. For 2 are targeted to hold warming below 1.5°C or 2°C with a certain example, biophysical feedbacks from changes in land use and probability (generally two-thirds) over the course, or at the irrigation (e.g., Hirsch et al., 2017; Thiery et al., 2017), or projected end, of the 21st century. These scenarios should be seen as the changes in short-lived pollutants (e.g., Z. Wang et al., 2017), can operationalization of 1.5°C or 2°C warmer worlds. However, have large influences on local temperatures and climate when these emission scenarios are used to drive climate models, conditions. While these effects are not explicitly integrated into the some of the resulting simulations lead to warming above these scenarios developed in Chapter 2, they may affect projected respective thresholds (typically with a probability of one-third, see changes in climate under 1.5°C of global warming. These issues Chapter 2 and Cross-Chapter Box 8 in this chapter). This is due are addressed in more detail in Section 3.6.2.2. both to discrepancies between models and to internal climate variability. For this reason, the climate outcome for any of these The assessment presented in the current chapter largely focuses on scenarios, even those excluding an overshoot (see next point, C.), the analysis of transient responses in climate at 1.5°C versus 2°C include some probability of reaching a global climate warming and higher levels of global warming (see point A. above and Section of more than 1.5°C or 2°C. Hence, a comprehensive assessment 3.3). It generally uses the empirical scaling relationship (ESR) approach of climate risks associated with ‘1.5°C or 2°C climate scenarios’ (Seneviratne et al., 2018c), also termed the ‘time sampling’ approach needs to include consideration of higher levels of warming (e.g., (James et al., 2017), which consists of sampling the response at 1.5°C up to 2.5°C to 3°C, see Chapter 2 and Cross-Chapter Box 8 in this and other levels of global warming from all available global climate chapter). model scenarios for the 21st century (e.g., Schleussner et al., 2016b; 184 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Seneviratne et al., 2016; Wartenburger et al., 2017). The ESR approach and attribution approaches of relevance to assessing changes in focuses more on the derivation of a continuous relationship, while climate at 1.5°C of global warming. the term ‘time sampling’ is more commonly used when comparing a limited number of warming levels (e.g., 1.5°C versus 2°C). A similar 3.2.2 How are Potential Impacts on Ecosystems Assessed approach in the case of regional climate model (RCM) simulations at 1.5°C versus Higher Levels of Warming? consists of sampling the RCM model output corresponding to the time frame at which the driving general circulation model (GCM) Considering that the impacts observed so far are for a global warming reaches the considered temperature level, for example, as done within lower than 1.5°C (generally up to the 2006–2015 decade, i.e., for a IMPACT2C (Jacob and Solman, 2017), see description in Vautard et global warming of 0.87°C or less; see above), direct information on al. (2014). As an alternative to the ESR or time sampling approach, the impacts of a global warming of 1.5°C is not yet available. The pattern scaling may be used. Pattern scaling is a statistical approach global distribution of observed impacts shown in AR5 (Cramer et al., that describes relationships of specific climate responses as a function 2014), however, demonstrates that methodologies now exist which of global temperature change. Some assessments presented in this are capable of detecting impacts on systems strongly influenced by chapter are based on this method. The disadvantage of pattern scaling, factors (e.g., urbanization and human pressure in general) or where however, is that the relationship may not perfectly emulate the models’ climate may play only a secondary role in driving impacts. Attribution responses at each location and for each global temperature level of observed impacts to greenhouse gas forcing is more rarely (James et al., 2017). Expert judgement is a third methodology that can performed, but a recent study (Hansen and Stone, 2016) shows that be used to assess probable changes at 1.5°C or 2°C of global warming most of the detected temperature-related impacts that were reported by combining changes that have been attributed to the observed time in AR5 (Cramer et al., 2014) can be attributed to anthropogenic climate period (corresponding to warming of 1°C or less if assessed over a change, while the signals for precipitation-induced responses are more shorter period) with known projected changes at 3°C or 4°C above ambiguous. pre-industrial temperatures (Supplementary Material 3.SM.1). In order to assess effects induced by a 0.5°C difference in global warming, One simple approach for assessing possible impacts on natural and the historical record can be used at first approximation as a proxy, managed systems at 1.5°C versus 2°C consists of identifying impacts of 3 meaning that conditions are compared for two periods that have a a global 0.5°C of warming in the observational record (e.g., Schleussner 0.5°C difference in GMST warming (such as 1991–2010 and 1960– et al., 2017) assuming that the impacts would scale linearly for higher 1979, e.g., Schleussner et al., 2017). This in particular also applies to levels of warming (although this may not be appropriate). Another attributed changes in extremes since 1950 that were reported in the approach is to use conclusions from analyses of past climates combined IPCC AR5 report (IPCC, 2013; see also 3.SM.1). Using observations, with modelling of the relationships between climate drivers and natural however, it is not possible to account for potential non-linear changes systems (Box 3.3). A more complex approach relies on laboratory or that could occur above 1°C of global warming or as 1.5°C of warming field experiments (Dove et al., 2013; Bonal et al., 2016), which provide is reached. useful information on the causal effect of a few factors, which can be as diverse as climate, greenhouse gases (GHG), management practices, In some cases, assessments of short-term stabilization responses and biological and ecological variables, on specific natural systems that are also presented, derived using a subset of model simulations that may have unusual physical and chemical characteristics (e.g., Fabricius reach a given temperature limit by 2100, or driven by sea surface et al., 2011; Allen et al., 2017). This last approach can be important temperature (SST) values consistent with such scenarios. This includes in helping to develop and calibrate impact mechanisms and models new results from the ‘Half a degree additional warming, prognosis and through empirical experimentation and observation. projected impacts’ (HAPPI) project (Section 1.5.2; Mitchell et al., 2017). Notably, there is evidence that for some variables (e.g., temperature Risks for natural and human systems are often assessed with and precipitation extremes), responses after short-term stabilization impact models where climate inputs are provided by representative (i.e., approximately equivalent to the RCP2.6 scenario) are very similar concentration pathway (RCP)-based climate projections. The number to the transient response of higher-emissions scenarios (Seneviratne et of studies projecting impacts at 1.5°C or 2°C of global warming al., 2016, 2018c; Wartenburger et al., 2017; Tebaldi and Knutti, 2018). has increased in recent times (see Section 3.4), even if the four RCP This is, however, less the case for mean precipitation (e.g., Pendergrass scenarios used in AR5 are not strictly associated with these levels et al., 2015), for which other aspects of the emissions scenarios appear of global warming. Several approaches have been used to extract relevant. the required climate scenarios, as described in Section 3.2.1. As an example, Schleussner et al. (2016b) applied a time sampling (or ESR) For the assessment of long-term equilibrium stabilization responses, approach, described in Section 3.2.1, to estimate the differential effect this chapter uses results from existing simulations where available of 1.5°C and 2°C of global warming on water availability and impacts (e.g., for sea level rise), although the available data for this type of on agriculture using an ensemble of simulations under the RCP8.5 projection is limited for many variables and scenarios and will need to scenario. As a further example using a different approach, Iizumi et al. be addressed in more depth in the IPCC AR6 report. (2017) derived a 1.5°C scenario from simulations with a crop model using an interpolation between the no-change (approximately 2010) Supplementary Material 3.SM.1 of this chapter includes further details conditions and the RCP2.6 scenario (with a global warming of 1.8°C in of the climate models and associated simulations that were used to 2100), and they derived the corresponding 2°C scenario from RCP2.6 support the present assessment, as well as a background on detection and RCP4.5 simulations in 2100. The Inter-Sectoral Impact Model 185 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Integration and Intercomparison Project Phase 2 (ISIMIP2; Frieler et However, impacts can only be partly inferred from these types of al., 2017) extended this approach to investigate a number of sectoral observations, given the strong possibility of non-linear changes, as well impacts on terrestrial and marine ecosystems. In most cases, risks are as lag effects for some climate variables (e.g., sea level rise, snow and assessed by impact models coupled offline to climate models after bias ice melt). For the impact models, three challenges are noted about the correction, which may modify long-term trends (Grillakis et al., 2017). coupling procedure: (i) the bias correction of the climate model, which may modify the simulated response of the ecosystem, (ii) the necessity Assessment of local impacts of climate change necessarily involves to downscale the climate model outputs to reach a pertinent scale for a change in scale, such as from the global scale to that of natural the ecosystem without losing physical consistency of the downscaled or human systems (Frieler et al., 2017; Reyer et al., 2017d; Jacob et climate fields, and (iii) the necessity to develop an integrated study of al., 2018). An appropriate method of downscaling (Supplementary the uncertainties. Material 3.SM.1) is crucial for translating perspectives on 1.5°C and 2°C of global warming to scales and impacts relevant to humans and ecosystems. A major challenge associated with this requirement is the correct reproduction of the variance of local to regional changes, 3.3 Global and Regional Climate as well as the frequency and amplitude of extreme events (Vautard Changes and Associated Hazards et al., 2014). In addition, maintaining physical consistency between downscaled variables is important but challenging (Frost et al., 2011). This section provides the assessment of changes in climate at 1.5°C of global warming relative to changes at higher global mean Another major challenge relates to the propagation of the uncertainties temperatures. Section 3.3.1 provides a brief overview of changes to at each step of the methodology, from the global forcings to the global global climate. Sections 3.3.2–3.3.11 provide assessments for specific climate and from regional climate to impacts at the ecosystem level, aspects of the climate system, including regional assessments for considering local disturbances and local policy effects. The risks for temperature (Section 3.3.2) and precipitation (Section 3.3.3) means natural and human systems are the result of complex combinations of and extremes. Analyses of regional changes are based on the set of 3 global and local drivers, which makes quantitative uncertainty analysis regions displayed in Figure 3.2. A synthesis of the main conclusions difficult. Such analyses are partly done using multimodel approaches, of this section is provided in Section 3.3.11. The section builds upon such as multi-climate and multi-impact models (Warszawski et al., assessments from the IPCC AR5 WGI report (Bindoff et al., 2013a; 2013, 2014; Frieler et al., 2017). In the case of crop projections, for Christensen et al., 2013; Collins et al., 2013; Hartmann et al., 2013; example, the majority of the uncertainty is caused by variation among IPCC, 2013) and Chapter 3 of the IPCC Special Report on Managing crop models rather than by downscaling outputs of the climate models the Risks of Extreme Events and Disasters to Advance Climate Change used (Asseng et al., 2013). Error propagation is an important issue Adaptation (SREX; Seneviratne et al., 2012), as well as a substantial for coupled models. Dealing correctly with uncertainties in a robust body of new literature related to projections of climate at 1.5°C and 2°C probabilistic model is particularly important when considering the of warming above the pre-industrial period (e.g., Vautard et al., 2014; potential for relatively small changes to affect the already small signal Fischer and Knutti, 2015; Schleussner et al., 2016b, 2017; Seneviratne associated with 0.5°C of global warming (Supplementary Material et al., 2016, 2018c; Déqué et al., 2017; Maule et al., 2017; Mitchell et 3.SM.1). The computation of an impact per unit of climatic change, al., 2017, 2018a; Wartenburger et al., 2017; Zaman et al., 2017; Betts et based either on models or on data, is a simple way to present the al., 2018; Jacob et al., 2018; Kharin et al., 2018; Wehner et al., 2018b). probabilistic ecosystem response while taking into account the various The main assessment methods are as already detailed in Section 3.2. sources of uncertainties (Fronzek et al., 2011). 3.3.1 Global Changes in Climate In summary, in order to assess risks at 1.5°C and higher levels of global warming, several things need to be considered. Projected There is high confidence that the increase in global mean surface climates under 1.5°C of global warming differ depending on temporal temperature (GMST) has reached 0.87°C (±0.10°C likely range) aspects and emission pathways. Considerations include whether global above pre-industrial values in the 2006–2015 decade (Chapter 1). temperature is (i) temporarily at this level (i.e., is a transient phase on its AR5 assessed that the globally averaged temperature (combined way to higher levels of warming), (ii) arrives at 1.5°C, with or without over land and ocean) displayed a warming of about 0.85°C [0.65°C overshoot, after stabilization of greenhouse gas concentrations, or (iii) to 1.06°C] during the period 1880–2012, with a large fraction of the is at this level as part of long-term climate equilibrium (complete only detected global warming being attributed to anthropogenic forcing after several millennia). Assessments of impacts of 1.5°C of warming (Bindoff et al., 2013a; Hartmann et al., 2013; Stocker et al., 2013). are generally based on climate simulations for these different possible While new evidence has highlighted that sampling biases and the pathways. Most existing data and analyses focus on transient impacts choice of approaches used to estimate GMST (e.g., using water (i). Fewer data are available for dedicated climate model simulations versus air temperature over oceans and using model simulations that are able to assess pathways consistent with (ii), and very few data versus observations-based estimates) can affect estimates of GMST are available for the assessment of changes at climate equilibrium (iii). increase (Richardson et al., 2016; see also Supplementary Material In some cases, inferences regarding the impacts of further warming of 3.SM.2), the present assessment is consistent with that of AR5 0.5°C above present-day temperatures (i.e., 1.5°C of global warming) regarding a detectable and dominant effect of anthropogenic forcing can also be drawn from observations of similar sized changes (0.5°C) on observed trends in global temperature (also confirmed in Ribes that have occurred in the past, such as during the last 50 years. et al., 2017). As highlighted in Chapter 1, human-induced warming 186 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 ARC* ALA CGI NEU NAS CEU WNA CNA ENA MED CAS TIB WAS EAS CAM CAR* SAH SAS NTP* WAF EAF SEA ETP* AMZ NEB WIO* STP* WSA SAF NAU SSA SAU ANT* Abbreviation Name Abbreviation Name Abbreviation Name Abbreviation Name ALA Alaska/N.W. Canada CNA Central North America NEU North Europe TIB Tibetan Plateau AMZ Amazon EAF East Africa NTP* Pacific Islands region[2] WAF West Africa 3 ANT* Antarctica EAS East Asia SAF Southern Africa WAS West Asia ARC* Arctic ENA East North America SAH Sahara WIO* West Indian Ocean CAM Central America/Mexico ETP* Pacific Islands region[3] SAS South Asia WNA West North America CAR* small islands regions Caribbean MED South Europe/Mediterranean SAU South Australia/New Zealand WSA West Coast South America CAS Central Asia NAS North Asia SEA Southeast Asia CEU Central Europe NAU North Australia SSA Southeastern South America CGI Canada/Greenland/Iceland NEB North−East Brazil STP* Southern Topical Pacific Figure 3.2 | Regions used for regional analyses provided in Section 3.3. The choice of regions is based on the IPCC Fifth Assessment Report (AR5, Chapter 14, Christensen et al., 2013 and Annex 1: Atlas) and the Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX, Chapter 3, Seneviratne et al., 2012), with seven additional regions in the Arctic, Antarctic and islands not included in the IPCC SREX report (indicated with asterisks). Analyses for regions with asterisks are provided in the Supplementary Material 3.SM.2 reached approximately 1°C (±0.2°C likely range) in 2017. More versus pre-industrial conditions, as well as at 2°C global warming background on recent observed trends in global climate is provided versus pre-industrial conditions (high confidence) (Figure 3.3). There in the Supplementary Material 3.SM.2. are consistent but less robust signals when comparing changes in mean precipitation at 2°C versus 1.5°C of global warming. Hence, A global warming of 1.5°C implies higher mean temperatures it is assessed that there is medium confidence in an increase of compared to during pre-industrial times in almost all locations, both mean precipitation in high-latitudes at 2°C versus 1.5°C of global on land and in oceans (high confidence) (Figure 3.3). In addition, warming (Figure 3.3). For droughts, changes in evapotranspiration a global warming of 2°C versus 1.5°C results in robust differences and precipitation timing are also relevant (see Section 3.3.4). Figure in the mean temperatures in almost all locations, both on land and 3.4 displays changes in temperature extremes (the hottest daytime in the ocean (high confidence). The land–sea contrast in warming temperature of the year, TXx, and the coldest night-time temperature is important and implies particularly large changes in temperature of the year, TNn) and heavy precipitation (the annual maximum over land, with mean warming of more than 1.5°C in most land 5-day precipitation, Rx5day). These analyses reveal distinct patterns regions (high confidence; see Section 3.3.2 for more details). The of changes, with the largest changes in TXx occurring on mid-latitude largest increase in mean temperature is found in the high latitudes land and the largest changes in TNn occurring at high latitudes of the Northern Hemisphere (high confidence; Figure 3.3, see Section (both on land and in oceans). Differences in TXx and TNn compared 3.3.2 for more details). Projections for precipitation are more to pre-industrial climate are robust at both global warming levels. uncertain, but they highlight robust increases in mean precipitation Differences in TXx and TNn at 2°C versus 1.5°C of global warming in the Northern Hemisphere high latitudes at 1.5°C global warming are robust across most of the globe. Changes in heavy precipitation 187 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Mean temperature change Mean temperature change Difference in mean temperature at 1.5°C GMST warming at 2.0°C GMST warming change (2.0°C - 1.5°C) Temperature (°C) Temperature (°C) Mean precipitation change Mean precipitation change Difference in mean precipitation at 1.5°C GMST warming at 2.0°C GMST warming change (2.0°C - 1.5°C) Precipitation (%) Precipitation (%) 3 Figure 3.3 | Projected changes in mean temperature (top) and mean precipitation (bottom) at 1.5°C (left) and 2°C (middle) of global warming compared to the pre-industrial period (1861–1880), and the difference between 1.5°C and 2°C of global warming (right). Cross-hatching highlights areas where at least two-thirds of the models agree on the sign of change as a measure of robustness (18 or more out of 26). Values were assessed from the transient response over a 10-year period at a given warming level, based on Representative Concentration Pathway (RCP)8.5 Coupled Model Intercomparison Project Phase 5 (CMIP5) model simulations (adapted from Seneviratne et al., 2016 and Wartenburger et al., 2017, see Supplementary Material 3.SM.2 for more details). Note that the responses at 1.5°C of global warming are similar for RCP2.6 simulations (see Supplementary Material 3.SM.2). Differences compared to 1°C of global warming are provided in the Supplementary Material 3.SM.2. are less robust, but particularly strong increases are apparent at high (very likely) (Bindoff et al., 2013a). In addition, there is medium latitudes as well as in the tropics at both 1.5°C and 2°C of global confidence that anthropogenic forcing has contributed to increases warming compared to pre-industrial conditions. The differences in in mean precipitation at high latitudes in the Northern Hemisphere heavy precipitation at 2°C versus 1.5°C global warming are generally since the mid-20th century and to global-scale increases in heavy not robust at grid-cell scale, but they display consistent increases in precipitation in land regions with sufficient observations over the most locations (Figure 3.4). However, as addressed in Section 3.3.3, same period (Bindoff et al., 2013a). Schleussner et al. (2017) showed, statistically significant differences are found in several large regions and through analyses of recent observed tendencies, that changes in when aggregated over the global land area. We thus assess that there temperature extremes and heavy precipitation indices are detectable is high confidence regarding global-scale differences in temperature in observations for the 1991–2010 period compared with those means and extremes at 2°C versus 1.5°C global warming, and medium for 1960–1979, with a global warming of approximately 0.5°C confidence regarding global-scale differences in precipitation means occurring between these two periods (high confidence). The observed and extremes. Further analyses, including differences at 1.5°C and 2°C tendencies over that time frame are thus consistent with attributed global warming versus 1°C (i.e., present-day) conditions are provided changes since the mid-20th century (high confidence). in the Supplementary Material 3.SM.2. The next sections assess changes in several different types of climate- These projected changes at 1.5°C and 2°C of global warming are related hazards. It should be noted that the different types of hazards consistent with the attribution of observed historical global trends are considered in isolation but some regions are projected to be in temperature and precipitation means and extremes (Bindoff et al., affected by collocated and/or concomitant changes in several types 2013a), as well as with some observed changes under the recent of hazards (high confidence). Two examples are sea level rise and global warming of 0.5°C (Schleussner et al., 2017). These comparisons heavy precipitation in some regions, possibly leading together to more are addressed in more detail in Sections 3.3.2 and 3.3.3. Attribution flooding, and droughts and heatwaves, which can together increase studies have shown that there is high confidence that anthropogenic the risk of fire occurrence. Such events, also called compound events, forcing has had a detectable influence on trends in global warming may substantially increase risks in some regions (e.g., AghaKouchak et (virtually certain since the mid-20th century), in land warming on al., 2014; Van Den Hurk et al., 2015; Martius et al., 2016; Zscheischler all continents except Antarctica (likely since the mid-20th century), et al., 2018). A detailed assessment of physically-defined compound in ocean warming since 1970 (very likely), and in increases in hot events was not possible as part of this report, but aspects related to extremes and decreases in cold extremes since the mid-20th century overlapping multi-sector risks are highlighted in Sections 3.4 and 3.5. 188 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Change in temperature of hottest Change in temperature of hottest Difference in temperature of hottest days (TXx) at 1.5°C GMST warming days (TXx) at 2.0°C GMST warming days (TXx) (2.0°C – 1.5°C) Change in temperature of coldest Change in temperature of coldest Difference in temperature of coldest nights (TNn) at 1.5°C GMST warming nights (TNn) at 2.0°C GMST warming nights (TNn) (2.0°C – 1.5°C) Temperature (°C) Temperature (°C) Change in extreme precipitation Change in extreme precipitation Difference in change in extreme (Rx5day) at 1.5°C GMST warming (Rx5day) at 2.0°C GMST warming precipitation (Rx5day) (2.0°C – 1.5°C) 3 Precipitation (%) Precipitation (%) Figure 3.4 | Projected changes in extremes at 1.5°C (left) and 2°C (middle) of global warming compared to the pre-industrial period (1861–1880), and the difference between 1.5°C and 2°C of global warming (right). Cross-hatching highlights areas where at least two-thirds of the models agree on the sign of change as a measure of robustness (18 or more out of 26): temperature of annual hottest day (maximum temperature), TXx (top), and temperature of annual coldest night (minimum temperature), TNn (middle), and annual maximum 5-day precipitation, Rx5day (bottom). The underlying methodology and data basis are the same as for Figure 3.3 (see Supplementary Material 3.SM.2 for more details). Note that the responses at 1.5°C of global warming are similar for Representative Concentration Pathway (RCP)2.6 simulations (see Supplementary Material 3.SM.2). Differences compared to 1°C of global warming are provided in the Supplementary Material 3.SM.2. 3.3.2 Regional Temperatures on Land, Including Extremes regions, anthropogenic influence has made a substantial contribution to surface temperature increases since the mid-20th century. 3.3.2.1 Observed and attributed changes in regional temperature means and extremes Based on the AR5 and SREX, as well as recent literature (see Supplementary Material 3.SM), there is high confidence (very likely) While the quality of temperature measurements obtained through that there has been an overall decrease in the number of cold days ground observational networks tends to be high compared to that of and nights and an overall increase in the number of warm days and measurements for other climate variables (Seneviratne et al., 2012), nights at the global scale on land. There is also high confidence (likely) it should be noted that some regions are undersampled. Cowtan and that consistent changes are detectable on the continental scale in Way (2014) highlighted issues regarding undersampling, which is North America, Europe and Australia. There is high confidence that most problematic at the poles and over Africa, and which may lead these observed changes in temperature extremes can be attributed to to biases in estimated changes in GMST (see also Supplementary anthropogenic forcing (Bindoff et al., 2013a). As highlighted in Section Material 3.SM.2 and Chapter 1). This undersampling also affects the 3.2, the observational record can be used to assess past changes confidence of assessments regarding regional observed and projected associated with a global warming of 0.5°C. Schleussner et al. (2017) changes in both mean and extreme temperature. Despite this partly used this approach to assess observed changes in extreme indices for limited coverage, the attribution chapter of AR5 (Bindoff et al., 2013a) the 1991–2010 versus the 1960–1979 period, which corresponds to and recent papers (e.g., Sun et al., 2016; Wan et al., 2018) assessed just about a 0.5°C GMST difference in the observed record (based on that, over every continental region and in many sub-continental the Goddard Institute for Space Studies Surface Temperature Analysis 189 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems (GISTEMP) dataset, Hansen et al., 2010). They found that substantial changes are approximately exponential, with higher increases for rare changes due to 0.5°C of warming are apparent for indices related to events (Fischer and Knutti, 2015; Kharin et al., 2018); see also Figure hot and cold extremes, as well as for the Warm Spell Duration Indicator 3.6. This behaviour is consistent with a linear increase in absolute (WSDI). In particular, they identified that one-quarter of the land has temperature for extreme threshold exceedances (Whan et al., 2015). experienced an intensification of hot extremes (maximum temperature on the hottest day of the year, TXx) by more than 1°C and a reduction in As mentioned in Section 3.3.1, there is an important land–sea warming the intensity of cold extremes by at least 2.5°C (minimum temperature contrast, with stronger warming on land (see also Christensen et al., on the coldest night of the year, TNn). In addition, the same study 2013; Collins et al., 2013; Seneviratne et al., 2016), which implies that showed that half of the global land mass has experienced changes regional warming on land is generally more than 1.5°C even when in WSDI of more than six days, as well as an emergence of extremes mean global warming is at 1.5°C. As highlighted in Seneviratne et al. outside the range of natural variability (Schleussner et al., 2017). (2016), this feature is generally stronger for temperature extremes Analyses from Schleussner et al. (2017) for temperature extremes are (Figures 3.4 and 3.5; Supplementary Material 3.SM.2 ). For differences provided in the Supplementary Material 3.SM, Figure 3.SM.6. It should in regional temperature extremes at a mean global warming of 1.5°C be noted that assessments of attributed changes in the IPCC SREX and versus 2°C, that is, a difference of 0.5°C in global warming, this implies AR5 reports were generally provided since 1950, for time frames also differences of as much as 1°C–1.5°C in some locations, which are two approximately corresponding to a 0.5°C global warming (3.SM). to three times larger than the differences in global mean temperature. For hot extremes, the strongest warming is found in central and eastern 3.3.2.2 Projected changes in regional temperature means and North America, central and southern Europe, the Mediterranean, extremes at 1.5°C versus 2°C of global warming western and central Asia, and southern Africa (Figures 3.4 and 3.5) (medium confidence). These regions are all characterized by a strong There are several lines of evidence available for providing a regional soil-moisture–temperature coupling and projected increased dryness assessment of projected changes in temperature means and extremes (Vogel et al., 2017), which leads to a reduction in evaporative cooling at 1.5°C versus 2°C of global warming (see Section 3.2). These include: in the projections. Some of these regions also show a wide range of 3 analyses of changes in extremes as a function of global warming based responses to temperature extremes, in particular central Europe and on existing climate simulations using the empirical scaling relationship central North America, owing to discrepancies in the representation of (ESR) and variations thereof (e.g., Schleussner et al., 2017; Dosio and the underlying processes in current climate models (Vogel et al., 2017). Fischer, 2018; Seneviratne et al., 2018c; see Section 3.2 for details about For mean temperature and cold extremes, the strongest warming is the methodology); dedicated simulations of 1.5°C versus 2°C of global found in the northern high-latitude regions (high confidence). This is warming, for instance based on the Half a degree additional warming, due to substantial ice-snow-albedo-temperature feedbacks (Figure prognosis and projected impacts (HAPPI) experiment (Mitchell et al., 3.3 and Figure 3.4, middle) related to the known ‘polar amplification’ 2017) or other model simulations (e.g., Dosio et al., 2018; Kjellström et mechanism (e.g., IPCC, 2013; Masson-Delmotte et al., 2013). al., 2018); and analyses based on statistical pattern scaling approaches (e.g., Kharin et al., 2018). These different lines of evidence lead to Figure 3.7 displays maps of changes in the number of hot days qualitatively consistent results regarding changes in temperature (NHD) at 1.5°C and 2°C of GMST increase. Maps of changes in the means and extremes at 1.5°C of global warming compared to the pre- number of frost days (FD) can be found in Supplementary Material industrial climate and 2°C of global warming. 3.SM.2. These analyses reveal clear patterns of changes between the two warming levels, which are consistent with analysed changes in There are statistically significant differences in temperature means and heatwave occurrence (e.g., Dosio et al., 2018). For the NHD, the largest extremes at 1.5°C versus 2°C of global warming, both in the global differences are found in the tropics (high confidence), owing to the average (Schleussner et al., 2016b; Dosio et al., 2018; Kharin et al., low interannual temperature variability there (Mahlstein et al., 2011), 2018), as well as in most land regions (high confidence) (Wartenburger although absolute changes in hot temperature extremes tended to et al., 2017; Seneviratne et al., 2018c; Wehner et al., 2018b). Projected be largest at mid-latitudes (high confidence) (Figures 3.4 and 3.5). temperatures over oceans display significant increases in means and Extreme heatwaves are thus projected to emerge earliest in the tropics extremes between 1.5°C and 2°C of global warming (Figures 3.3 and and to become widespread in these regions already at 1.5°C of global 3.4). A general background on the available evidence on regional warming (high confidence). These results are consistent with other changes in temperature means and extremes at 1.5°C versus 2°C of recent assessments. Coumou and Robinson (2013) found that 20% global warming is provided in the Supplementary Material 3.SM.2. As of the global land area, centred in low-latitude regions, is projected an example, Figure 3.5 shows regionally-based analyses for the IPCC to experience highly unusual monthly temperatures during Northern SREX regions (see Figure 3.2) of changes in the temperature of hot Hemisphere summers at 1.5°C of global warming, with this number extremes as a function of global warming (corresponding analyses nearly doubling at 2°C of global warming. for changes in the temperature of cold extremes are provided in the Supplementary Material 3.SM.2). As demonstrated in these analyses, Figure 3.8 features an objective identification of ‘hotspots’ / key the mean response of the intensity of temperature extremes in climate risks in temperature indices subdivided by region, based on the ESR models to changes in the global mean temperature is approximately approach applied to Coupled Model Intercomparison Project Phase linear and independent of the considered emissions scenario 5 (CMIP5) simulations (Wartenburger et al., 2017). Note that results (Seneviratne et al., 2016; Wartenburger et al., 2017). Nonetheless, in based on the HAPPI multimodel experiment (Mitchell et al., 2017) the case of changes in the number of days exceeding a given threshold, are similar (Seneviratne et al., 2018c). The considered regions follow 190 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 the classification used in Figure 3.2 and also include the global land America, central and southern Europe, the Mediterranean, western and areas. Based on these analyses, the following can be stated: significant central Asia, and southern Africa (medium confidence). These regions changes in responses are found in all regions for most temperature have a strong soil-moisture-temperature coupling in common as well indices, with the exception of i) the diurnal temperature range (DTR) in as increased dryness and, consequently, a reduction in evaporative most regions, ii) ice days (ID), frost days (FD) and growing season length cooling. However, there is a substantial range in the representation (GSL) (mostly in regions where differences are zero, because, e.g., there of these processes in models, in particular in central Europe and are no ice or frost days), iii) the minimum yearly value of the maximum central North America (medium confidence). The coldest nights in high daily temperature (TXn) in very few regions. In terms of the sign of latitudes warm by as much as 1.5°C for a 0.5°C increase in GMST, the changes, warm extremes display an increase in intensity, frequency corresponding to a threefold stronger warming (high confidence). NHD and duration (e.g., an increase in the temperature of the hottest day of shows the largest differences between 1.5°C and 2°C in the tropics, the year (TXx) in all regions, an increase in the proportion of days with because of the low interannual temperature variability there (high a maximum temperature above the 90th percentile of Tmax (TX90p) confidence); extreme heatwaves are thus projected to emerge earliest in all regions, and an increase in the length of the WSDI in all regions), in these regions, and they are expected to become widespread already while cold extremes display a decrease in intensity, frequency and at 1.5°C of global warming (high confidence). Limiting global warming duration (e.g., an increase in the temperature of the coldest night of to 1.5°C instead of 2°C could result in around 420 million fewer people the year (TNn) in all regions, a decrease in the proportion of days with being frequently exposed to extreme heatwaves, and about 65 million a minimum temperature below the 10th percentile of Tmin (TN10p), fewer people being exposed to exceptional heatwaves, assuming and a decrease in the cold spell duration index (CSDI) in all regions). constant vulnerability (medium confidence). Hence, while warm extremes are intensified, cold extremes become less intense in affected regions. 3.3.3 Regional Precipitation, Including Heavy Precipitation and Monsoons Overall, large increases in hot extremes occur in many densely inhabited regions (Figure 3.5), for both warming scenarios compared This section addresses regional changes in precipitation on land, with to pre-industrial and present-day climate, as well as for 2°C versus a focus on heavy precipitation and consideration of changes to the key 3 1.5°C GMST warming. For instance, Dosio et al. (2018) concluded, features of monsoons. based on a modelling study, that 13.8% of the world population would be exposed to ‘severe heatwaves’ at least once every 5 years under 3.3.3.1 Observed and attributed changes in regional 1.5°C of global warming, with a threefold increase (36.9%) under 2°C precipitation of GMST warming, corresponding to a difference of about 1.7 billion people between the two global warming levels. They also concluded Observed global changes in the water cycle, including precipitation, that limiting global warming to 1.5°C would result in about 420 are more uncertain than observed changes in temperature (Hartmann million fewer people being frequently exposed to extreme heatwaves, et al., 2013; Stocker et al., 2013). There is high confidence that and about 65 million fewer people being exposed to ‘exceptional mean precipitation over the mid-latitude land areas of the Northern heatwaves’ compared to conditions at 2°C GMST warming. However, Hemisphere has increased since 1951 (Hartmann et al., 2013). For changes in vulnerability were not considered in their study. For this other latitudinal zones, area-averaged long-term positive or negative reason, we assess that there is medium confidence in their conclusions. trends have low confidence because of poor data quality, incomplete data or disagreement amongst available estimates (Hartmann et al., In summary, there is high confidence that there are robust and 2013). There is, in particular, low confidence regarding observed trends statistically significant differences in the projected temperature means in precipitation in monsoon regions, according to the SREX report and extremes at 1.5°C versus 2°C of global warming, both in the global (Seneviratne et al., 2012) and AR5 (Hartmann et al., 2013), as well as average and in nearly all land regions4 (likely). Further, the observational more recent publications (Singh et al., 2014; Taylor et al., 2017; Bichet record reveals that substantial changes due to a 0.5°C GMST warming and Diedhiou, 2018; see Supplementary Material 3.SM.2). are apparent for indices related to hot and cold extremes, as well as for the WSDI (likely). A global warming of 2°C versus 1.5°C would lead to For heavy precipitation, AR5 (Hartmann et al., 2013) assessed that more frequent and more intense hot extremes in all land regions4, as observed trends displayed more areas with increases than decreases in well as longer warm spells, affecting many densely inhabited regions the frequency, intensity and/or amount of heavy precipitation (likely). (very likely). The strongest increases in the frequency of hot extremes In addition, for land regions where observational coverage is sufficient are projected for the rarest events (very likely). On the other hand, cold for evaluation, it was assessed that there is medium confidence that extremes would become less intense and less frequent, and cold spells anthropogenic forcing has contributed to a global-scale intensification would be shorter (very likely). Temperature extremes on land would of heavy precipitation over the second half of the 20th century (Bindoff generally increase more than the global average temperature (very et al., 2013a). likely). Temperature increases of extreme hot days in mid-latitudes are projected to be up to two times the increase in GMST, that is, 3°C at Regarding changes in precipitation associated with global warming 1.5°C GMST warming (high confidence). The highest levels of warming of 0.5°C, the observed record suggests that increases in precipitation for extreme hot days are expected to occur in central and eastern North extremes can be identified for annual maximum 1-day precipitation 4 Using the SREX definition of regions (Figure 3.2) Continued page 194 > 191 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Alaska/N.W. Canada Canada/Greenl./Icel. W. North America C. North America E. North America Central America/Mexico Amazon N.E. Brazil W. Coast South America (ALA) (CGI) (WNA) (CNA) (ENA) (CAM) (AMZ) (NEB) (WSA) 1 2 3 4 5 6 7 8 9 S.E. South America N. Europe C. Europe S. Europe/Mediterranean (SSA) (NEU) (CEU) (MED) 10 11 12 13 1 2 11 18 3 124 5 13 20 2119 22 6 14 23 Sahara W. Africa (SAH) (WAF) 7 15 16 24 E. Africa S. Africa (EAF) (SAF) 14 15 8 16 17 9 17 25 10 26 ∆ TXx (2°C – 1.5°C) (°C) 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1 1.1 N. Asia W. Asia C. Asia Tibetan Plateau E. Asia S. Asia S.E. Asia N. Australia S. Australia/New Zealand (NAS) (WAS) (CAS) (TIB) (EAS) (SAS) (SEA) (NAU) (SAU) 18 19 20 21 22 23 24 25 26 3 Global Land + Ocean# Global Land Global Ocean# Legend CMIP5 (ESR) 5 4 historical 3 RCP 8.5 2 HAPPI 1 1.5°C - pre-industrial 0 -1 2.0°C - pre-industrial0 1 2 3 ∆ T glob(°C) Figure 3.5 | Projected changes in annual maximum daytime temperature (TXx) as a function of global warming for IPCC Special Report on Managing the Risk of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) regions (see Figure 3.2), based on an empirical scaling relationship applied to Coupled Model Intercomparison Project Phase 5 (CMIP5) data (adapted from Seneviratne et al., 2016 and Wartenburger et al., 2017) together with projected changes from the Half a degree additional warming, prognosis and projected impacts (HAPPI) multimodel experiment (Mitchell et al., 2017; based on analyses in Seneviratne et al., 2018c) (bar plots on regional analyses and central plot, respectively). For analyses for other regions from Figure 3.2 (with asterisks), see Supplementary Material 3.SM.2. (The stippling indicates significance of the differences in changes between 1.5°C and 2°C of global warming based on all model simulations, using a two-sided paired Wilcoxon test (P = 0.01, after controlling the false discovery rate according to Benjamini and Hochberg, 1995). See Supplementary Material 3.SM.2 for details. Figure 3.6 | Probability ratio (PR) of exceeding extreme temperature thresholds. (a) PR of exceeding the 99th (blue) and 99.9th (red) percentile of pre-industrial daily temperatures at a given warming level, averaged across land (from Fischer and Knutti, 2015). (b) PR for the hottest daytime temperature of the year (TXx). (c) PR for the coldest night of the year (TNn) for different event probabilities (with RV indicating return values) in the current climate (1°C of global warming). Shading shows the interquartile (25–75%) range (from Kharin et al., 2018). 192 ∆ TXx reg (°C) Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Figure 3.7 | Projected changes in the number of hot days (NHD; 10% warmest days) at 1.5°C (left) and at 2°C (middle) of global warming compared to the pre-industrial period (1861–1880), and the difference between 1.5°C and 2°C of warming (right). Cross-hatching highlights areas where at least two-thirds of the models agree on the sign of change as a measure of robustness (18 or more out of 26). The underlying methodology and the data basis are the same as for Figure 3.2 (see Supplementary Material 3.SM.2 for more details). Differences compared to 1°C global warming are provided in the Supplementary Material 3.SM.2. 3 Figure 3.8 | Significance of differences in regional mean temperature and range of temperature indices between the 1.5°C and 2°C global mean temperature targets (rows). Definitions of indices: T: mean temperature; CSDI: cold spell duration index; DTR: diurnal temperature range; FD: frost days; GSL: growing season length; ID: ice days; SU: summer days; TN10p: proportion of days with a minimum temperature (TN) lower than the 10th percentile of TN; TN90p: proportion of days with TN higher than the 90th percentile of TN; TNn: minimum yearly value of TN; TNx: maximum yearly value of TN; TR: tropical nights; TX10p: proportion of days with a maximum temperature (TX) lower than the 10th percentile of TX; TX90p: proportion of days with TX higher than the 90th percentile of TX; TXn: minimum yearly value of TX; TXx: maximum yearly value of TX; WSDI: warm spell duration index. Columns indicate analysed regions and global land (see Figure 3.2 for definitions). Significant differences are shown in red shading, with increases indicated with + and decreases indicated with –, while non-significant differences are shown in grey shading. White shading indicates when an index is the same at the two global warming levels (i.e., zero changes). Note that decreases in CSDI, FD, ID, TN10p and TX10p are linked to increased temperatures on cold days or nights. Significance was tested using a two-sided paired Wilcoxon test (P=0.01, after controlling the false discovery rate according to Benjamini and Hochberg, 1995) (adapted from Wartenburger et al., 2017). 193 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems 3.3.3.1 (continued) continent, although different indices for heavy precipitation changes (RX1day) and consecutive 5-day precipitation (RX5day) for GMST have been analysed. Based on regional climate simulations, Vautard changes of this magnitude (Supplementary Material 3.SM.2, Figure et al. (2014) found a robust increase in heavy precipitation everywhere 3.SM.7; Schleussner et al., 2017). It should be noted that assessments in Europe and in all seasons, except southern Europe in summer at 2°C of attributed changes in the IPCC SREX and AR5 reports were generally versus 1971–2000. Their findings are consistent with those of Jacob provided since 1950, for time frames also approximately corresponding et al. (2014), who used more recent downscaled climate scenarios to a 0.5°C global warming (3.SM). (EURO-CORDEX) and a higher resolution (12 km), but the change is not so pronounced in Teichmann et al. (2018). There is consistent 3.3.3.2 Projected changes in regional precipitation at 1.5°C agreement in the direction of change in heavy precipitation at 1.5°C versus 2°C of global warming of global warming over much of Europe, compared to 1971–2000 (Jacob et al., 2018). Figure 3.3 in Section 3.3.1 summarizes the projected changes in mean precipitation at 1.5°C and 2°C of global warming. Both warming Differences in heavy precipitation are generally projected to be levels display robust differences in mean precipitation compared to small between 1.5°C and 2°C GMST warming (Figure 3.4 and 3.9 the pre-industrial period. Regarding differences at 2°C vs 1.5°C global and Supplementary Material 3.SM.2, Figure 3.SM.10). Some regions warming, some regions are projected to display changes in mean display substantial increases, for instance southern Asia, but generally precipitation at 2°C compared with that at 1.5°C of global warming in in less than two-thirds of the CMIP5 models (Figure 3.4, Supplementary the CMIP5 multimodel average, such as decreases in the Mediterranean Material 3.SM.2, Figure 3.SM.10). Wartenburger et al. (2017) suggested area, including southern Europe, the Arabian Peninsula and Egypt, or that there are substantial differences in heavy precipitation in eastern increases in high latitudes. The results, however, are less robust across Asia at 1.5°C versus 2°C. Overall, while there is variation among models than for mean temperature. For instance, Déqué et al. (2017) regions, the global tendency is for heavy precipitation to increase at investigated the impact of 2°C of global warming on precipitation over 2°C compared with at 1.5°C (see e.g., Fischer and Knutti, 2015 and tropical Africa and found that average precipitation does not show a Kharin et al., 2018, as illustrated in Figure 3.10 from this chapter; see 3 significant response, owing to two phenomena: (i) the number of days also Betts et al., 2018). with rain decreases whereas the precipitation intensity increases, and (ii) the rainy season occurs later during the year, with less precipitation AR5 assessed that the global monsoon, aggregated over all monsoon in early summer and more precipitation in late summer. The results systems, is likely to strengthen, with increases in its area and intensity, from Déqué et al. (2017) regarding insignificant differences between while the monsoon circulation weakens (Christensen et al., 2013). A 1.5°C and 2°C scenarios for tropical Africa are consistent with the few publications provide more recent evaluations of projections of results presented in Figure 3.3. For Europe, recent studies (Vautard et changes in monsoons for high-emission scenarios (e.g., Jiang and Tian, al., 2014; Jacob et al., 2018; Kjellström et al., 2018) have shown that 2013; Jones and Carvalho, 2013; Sylla et al., 2015, 2016; Supplementary 2°C of global warming was associated with a robust increase in mean Material 3.SM.2 ). However, scenarios at 1.5°C or 2°C global warming precipitation over central and northern Europe in winter but only over would involve a substantially smaller radiative forcing than those northern Europe in summer, and with decreases in mean precipitation assessed in AR5 and these more recent studies, and there appears in central/southern Europe in summer. Precipitation changes reaching to be no specific assessment of changes in monsoon precipitation at 20% have been projected for the 2°C scenario (Vautard et al., 2014) 1.5°C versus 2°C of global warming in the literature. Consequently, the and are overall more pronounced than with 1.5°C of global warming current assessment is that there is low confidence regarding changes (Jacob et al., 2018; Kjellström et al., 2018). in monsoons at these lower global warming levels, as well as regarding differences in monsoon responses at 1.5°C versus 2°C. Regarding changes in heavy precipitation, Figure 3.9 displays projected changes in the 5-day maximum precipitation (Rx5day) as a function Similar to Figure 3.8, Figure 3.11 features an objective identification of of global temperature increase, using a similar approach as in Figure ‘hotspots’ / key risks outlined in heavy precipitation indices subdivided 3.5. Further analyses are available in Supplementary Material 3.SM.2. by region, based on the approach by Wartenburger et al. (2017). The These analyses show that projected changes in heavy precipitation are considered regions follow the classification used in Figure 3.2 and also more uncertain than those for temperature extremes. However, the include global land areas. Hotspots displaying statistically significant mean response of model simulations is generally robust and linear changes in heavy precipitation at 1.5°C versus 2°C global warming (see also Fischer et al., 2014; Seneviratne et al., 2016). As observed for are located in high-latitude (Alaska/western Canada, eastern Canada/ temperature extremes, this response is also mostly independent of the Greenland/Iceland, northern Europe, northern Asia) and high-elevation considered emissions scenario (e.g., RCP2.6 versus RCP8.5; see also (e.g., Tibetan Plateau) regions, as well as in eastern Asia (including Section 3.2). This feature appears to be specific to heavy precipitation, China and Japan) and in eastern North America. Results are less possibly due to a stronger coupling with temperature, as the scaling of consistent for other regions. Note that analyses for meteorological projections of mean precipitation changes with global warming shows drought (lack of precipitation) are provided in Section 3.3.4. some scenario dependency (Pendergrass et al., 2015). In summary, observations and projections for mean and heavy Robust changes in heavy precipitation compared to pre-industrial precipitation are less robust than for temperature means and extremes conditions are found at both 1.5°C and 2°C global warming (Figure (high confidence). Observations show that there are more areas with 3.4). This is also consistent with results for, for example, the European increases than decreases in the frequency, intensity and/or amount of 194 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Alaska/N.W. Canada Canada/Greenl./Icel. W. North America C. North America E. North America Central America/Mexico Amazon N.E. Brazil W. Coast South America (ALA) (CGI) (WNA) (CNA) (ENA) (CAM) (AMZ) (NEB) (WSA) 1 2 3 4 5 6 7 8 9 S.E. South America N. Europe C. Europe S. Europe/Mediterranean (SSA) (NEU) (CEU) (MED) 10 11 12 13 1 2 11 18 3 124 5 13 20 2119 22 6 14 23 Sahara W. Africa 7 15 16 24 E. Africa S. Africa (SAH) (WAF) (EAF) (SAF) 14 15 8 16 17 9 17 25 10 26 ∆ Rx5day (2°C – 1.5°C) (mm) -4 -2 -1 0 1 2 4 6 10 N. Asia W. Asia C. Asia Tibetan Plateau E. Asia S. Asia S.E. Asia N. Australia S. Australia/New Zealand (NAS) (WAS) (CAS) (TIB) (EAS) (SAS) (SEA) (NAU) (SAU) 18 19 20 21 22 23 24 25 26 3 Global Land + Ocean# Global Land Global Ocean# Legend CMIP5 (ESR) 100 historical 80 60 RCP 8.5 40 HAPPI 20 1.5°C - pre-industrial 0 2.0°C - pre-industrial 0 1 2 3 ∆ T glob(°C) Figure 3.9 | Projected changes in annual 5-day maximum precipitation (Rx5day) as a function of global warming for IPCC Special Report on the Risk of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) regions (see Figure 3.2), based on an empirical scaling relationship applied to Coupled Model Intercomparison Project Phase 5 (CMIP5) data together with projected changes from the HAPPI multimodel experiment (bar plots on regional analyses and central plot). The underlying methodology and data basis are the same as for Figure 3.5 (see Supplementary Material 3.SM.2 for more details). Figure 3.10 | Probability ratio (PR) of exceeding (heavy precipitation) thresholds. (a) PR of exceeding the 99th (blue) and 99.9th (red) percentile of pre-industrial daily precipitation at a given warming level, averaged across land (from Fischer and Knutti, 2015). (b) PR for precipitation extremes (RX1day) for different event probabilities (with RV indicating return values) in the current climate (1°C of global warming). Shading shows the interquartile (25–75%) range (from Kharin et al., 2018). 195 ∆ Rx5dayreg (mm) Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems 3.3.3.2 (continued) changes in heavy precipitation between 1.5°C and 2°C of global heavy precipitation (high confidence). Several large regions display warming are located in high latitudes (Alaska/western Canada, eastern statistically significant differences in heavy precipitation at 1.5°C Canada/Greenland/Iceland, northern Europe, northern Asia) and high versus 2°C GMST warming, with stronger increases at 2°C global elevation (e.g., Tibetan Plateau), as well as in eastern Asia (including warming, and there is a global tendency towards increases in heavy China and Japan) and in eastern North America (medium confidence). precipitation on land at 2°C compared with 1.5°C warming (high There is low confidence in projected changes in heavy precipitation in confidence). Overall, regions that display statistically significant other regions. 3 Figure 3.11 | Significance of differences in regional mean precipitation and range of precipitation indices between the 1.5°C and 2°C global mean temperature targets (rows). Definition of indices: PRCPTOT: mean precipitation; CWD: consecutive wet days; R10mm: number of days with precipitation >10 mm; R1mm: number of days with precipitation >1 mm; R20mm: number of days with precipitation >20 mm; R95ptot: proportion of rain falling as 95th percentile or higher; R99ptot: proportion of rain falling as 99th percentile or higher; RX1day: intensity of maximum yearly 1-day precipitation; RX5day: intensity of maximum yearly 5-day precipitation; SDII: Simple Daily Intensity Index. Columns indicate analysed regions and global land (see Figure 3.2 for definitions). Significant differences are shown in light blue (wetting tendency) or brown (drying tendency) shading, with increases indicated with ‘+’ and decreases indicated with ‘–’, while non-significant differences are shown in grey shading. The underlying methodology and the data basis are the same as in Figure 3.8 (see Supplementary Material 3.SM.2 for more details). 3.3.4 Drought and Dryness greenhouse forcing has contributed to increased drying in the Mediterranean region (including southern Europe, northern Africa and 3.3.4.1 Observed and attributed changes the Near East) and that this tendency will continue to increase under higher levels of global warming. The IPCC AR5 assessed that there was low confidence in the sign of drought trends since 1950 at the global scale, but that there was high 3.3.4.2 Projected changes in drought and dryness at 1.5°C confidence in observed trends in some regions of the world, including versus 2°C drought increases in the Mediterranean and West Africa and drought decreases in central North America and northwest Australia (Hartmann There is medium confidence in projections of changes in drought et al., 2013; Stocker et al., 2013). AR5 assessed that there was low and dryness. This is partly consistent with AR5, which assessed these confidence in the attribution of global changes in droughts and did projections as being ‘likely (medium confidence)’ (Collins et al., 2013; not provide assessments for the attribution of regional changes in Stocker et al., 2013). However, given this medium confidence, the droughts (Bindoff et al., 2013a). current assessment does not include a likelihood statement, thereby maintaining consistency with the IPCC uncertainty guidance document The recent literature does not suggest that the SREX and AR5 (Mastrandrea et al., 2010) and the assessment of the IPCC SREX report assessment of drought trends should be revised, except in the (Seneviratne et al., 2012). The technical summary of AR5 (Stocker et Mediterranean region. Recent publications based on observational and al., 2013) assessed that soil moisture drying in the Mediterranean, modelling evidence suggest that human emissions have substantially southwestern USA and southern African regions was consistent with increased the probability of drought years in the Mediterranean region projected changes in the Hadley circulation and increased surface (Gudmundsson and Seneviratne, 2016; Gudmundsson et al., 2017). temperatures, and it concluded that there was high confidence Based on this evidence, there is medium confidence that enhanced in likely surface drying in these regions by the end of this century 196 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Box 3.1 | Sub-Saharan Africa: Changes in Temperature and Precipitation Extremes Sub-Saharan Africa has experienced the dramatic consequences of climate extremes becoming more frequent and more intense over the past decades (Paeth et al., 2010; Taylor et al., 2017). In order to join international efforts to reduce climate change, all African countries signed the Paris Agreement. In particular, through their nationally determined contributions (NDCs), they committed to contribute to the global effort to mitigate greenhouse gas (GHG) emissions with the aim to constrain global temperature increases to ‘well below 2°C’ and to pursue efforts to limit warming to ‘1.5°C above pre-industrial levels’. The target of limiting global warming to 1.5°C above pre- industrial levels is useful for conveying the urgency of the situation. However, it focuses the climate change debate on a temperature threshold (Section 3.3.2), while the potential impacts of these global warming levels on key sectors at local to regional scales, such as agriculture, energy and health, remain uncertain in most regions and countries of Africa (Sections 3.3.3, 3.3.4, 3.3.5 and 3.3.6). Weber et al. (2018) found that at regional scales, temperature increases in sub-Saharan Africa are projected to be higher than the global mean temperature increase (at global warming of 1.5°C and at 2°C; see Section 3.3.2 for further background and analyses of climate model projections). Even if the mean global temperature anomaly is kept below 1.5°C, regions between 15°S and 15°N are projected to experience an increase in hot nights, as well as longer and more frequent heatwaves (e.g., Kharin et al., 2018). Increases would be even larger if the global mean temperature were to reach 2°C of global warming, with significant changes in the occurrence and intensity of temperature extremes in all sub-Saharan regions (Sections 3.3.1 and 3.3.2; Figures 3.4, 3.5 and 3.8). West and Central Africa are projected to display particularly large increases in the number of hot days, both at 1.5°C and 2°C of global warming (Section 3.3.2). This is due to the relatively small interannual present-day variability in this region, which implies that climate- change signals can be detected earlier there (Section 3.3.2; Mahlstein et al., 2011). Projected changes in total precipitation exhibit uncertainties, mainly in the Sahel (Section 3.3.3 and Figure 3.8; Diedhiou et al., 2018). In the Guinea Coast and Central Africa, only a small change in total precipitation is projected, although most models (70%) indicate a decrease in the length of wet periods and a 3 slight increase in heavy rainfall. Western Sahel is projected by most models (80%) to experience the strongest drying, with a significant increase in the maximum length of dry spells (Diedhiou et al., 2018). Above 2°C, this region could become more vulnerable to drought and could face serious food security issues (Cross-Chapter Box 6 and Section 3.4.6 in this chapter; Salem et al., 2017; Parkes et al., 2018). West Africa has thus been identified as a climate-change hotspot with negative impacts from climate change on crop yields and production (Cross-Chapter Box 6 and Section 3.4.6; Sultan and Gaetani, 2016; Palazzo et al., 2017). Despite uncertainty in projections for precipitation in West Africa, which is essential for rain-fed agriculture, robust evidence of yield loss might emerge. This yield loss is expected to be mainly driven by increased mean temperature, while potential wetter or drier conditions – as well as elevated CO2 concentrations – could modulate this effect (Roudier et al., 2011; see also Cross-Chapter Box 6 and Section 3.4.6). Using Representative Concentration Pathway (RCP)8.5 Coordinated Regional Climate Downscaling Experiment (CORDEX) scenarios from 25 regional climate models (RCMs) forced with different general circulation models (GCMs), Klutse et al. (2018) noted a decrease in mean rainfall over West Africa in models with stronger warming for this region at 1.5°C of global warming (Section 3.3.4). Mba et al. (2018) used a similar approach and found a lack of consensus in the changes in precipitation over Central Africa (Figure 3.8 and Section 3.3.4), although there was a tendency towards a decrease in the maximum number of consecutive wet days (CWD) and a significant increase in the maximum number of consecutive dry days (CDD). Over southern Africa, models agree on a positive sign of change for temperature, with temperature rising faster at 2°C (1.5°C–2.5°C) as compared to 1.5°C (0.5°C–1.5°C) of global warming. Areas in the south-western region, especially in South Africa and parts of Namibia and Botswana, are expected to experience the largest increases in temperature (Section 3.3.2; Engelbrecht et al., 2015; Maúre et al., 2018). The western part of southern Africa is projected to become drier with increasing drought frequency and number of heatwaves towards the end of the 21st century (Section 3.3.4; Engelbrecht et al., 2015; Dosio, 2017; Maúre et al., 2018). At 1.5°C, a robust signal of precipitation reduction is found over the Limpopo basin and smaller areas of the Zambezi basin in Zambia, as well as over parts of Western Cape in South Africa, while an increase is projected over central and western South Africa, as well as in southern Namibia (Section 3.3.4). At 2°C, the region is projected to face robust precipitation decreases of about 10–20% and increases in the number of CDD, with longer dry spells projected over Namibia, Botswana, northern Zimbabwe and southern Zambia. Conversely, the number of CWD is projected to decrease, with robust signals over Western Cape (Maúre et al., 2018). Projected reductions in stream flow of 5–10% in the Zambezi River basin have been associated with increased evaporation and transpiration rates resulting from a rise in temperature ( Section 3.3.5; Kling et al., 2014), with issues for hydroelectric power across the region of southern Africa. For Eastern Africa, Osima et al. (2018) found that annual rainfall projections show a robust increase in precipitation over Somalia and a less robust decrease over central and northern Ethiopia (Section 3.3.3). The number of CDD and CWD are projected to increase and decrease, respectively (Section 3.3.4). These projected changes could impact the agricultural and water sectors in the region (Cross- Chapter Box 6 in this chapter and Section 3.4.6). 197 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems under the RCP8.5 scenario. However, more recent assessments have industrial or present-day conditions, as well as between these two highlighted uncertainties in dryness projections due to a range of global warming levels, although there is substantial variability in signals factors, including variations between the drought and dryness indices depending on the considered indices or climate models (Lehner et al., considered, and the effects of enhanced CO2 concentrations on plant 2017; Schleussner et al., 2017; Greve et al., 2018) (medium confidence). water-use efficiency (Orlowsky and Seneviratne, 2013; Roderick et Generally, the clearest signals are found for the Mediterranean region al., 2015). Overall, projections of changes in drought and dryness for (medium confidence). high-emissions scenarios (e.g., RCP8.5, corresponding to about 4°C of global warming) are uncertain in many regions, although a few regions Greve et al. (2018, Figure 3.12) derives the sensitivity of regional display consistent drying in most assessments (e.g., Seneviratne et al., changes in precipitation minus evapotranspiration to global 2012; Orlowsky and Seneviratne, 2013). Uncertainty is expected to be temperature changes. The simulations analysed span the full range of even larger for conditions with a smaller signal-to-noise ratio, such as available emission scenarios, and the sensitivities are derived using for global warming levels of 1.5°C and 2°C. a modified pattern scaling approach. The applied approach assumes linear dependencies on global temperature changes while thoroughly Some published literature is now available on the evaluation of addressing associated uncertainties via resampling methods. Northern differences in drought and dryness occurrence at 1.5°C and 2°C of global high-latitude regions display robust responses tending towards warming for (i) precipitation minus evapotranspiration (P–E, a general increased wetness, while subtropical regions display a tendency measure of water availability; Wartenburger et al., 2017; Greve et al., towards drying but with a large range of responses. While the internal 2018), (ii) soil moisture anomalies (Lehner et al., 2017; Wartenburger variability and the scenario choice play an important role in the overall et al., 2017), (iii) consecutive dry days (CDD) (Schleussner et al., 2016b; spread of the simulations, the uncertainty stemming from the climate Wartenburger et al., 2017), (iv) the 12-month standardized precipitation model choice usually dominates, accounting for about half of the total index (Wartenburger et al., 2017), (v) the Palmer drought severity index uncertainty in most regions (Wartenburger et al., 2017; Greve et al., (Lehner et al., 2017), and (vi) annual mean runoff (Schleussner et al., 2018). The sign of projections, that is, whether there might be increases 2016b, see also next section). These analyses have produced consistent or decreases in water availability under higher global warming levels, 3 findings overall, despite the known sensitivity of drought assessments to is particularly uncertain in tropical and mid-latitude regions. An chosen drought indices (see above paragraph). These analyses suggest assessment of the implications of limiting the global mean temperature that increases in drought, dryness or precipitation deficits are projected increase to values below (i) 1.5°C or (ii) 2°C shows that constraining at 1.5°C or 2°C global warming in some regions compared to the pre- global warming to the 1.5°C target might slightly influence the mean Figure 3.12 | Summary of the likelihood of increases/decreases in precipitation minus evapotranspiration (P–E) in Coupled Model Intercomparison Project Phase 5 (CMIP5) simulations considering all scenarios and a representative subset of 14 climate models (one from each modelling centre). Panel plots show the uncertainty distribution of the sensitivity of P–E to global temperature change, averaged for most IPCC Special Report on Managing the Risk of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) regions (see Figure 3.2) outlined in the map (from Greve et al., 2018). 198 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 response but could substantially reduce the risk of experiencing specific assessment of changes in the tails of the drought and dryness extreme changes in regional water availability (Greve et al., 2018). distribution. The conclusions of Lehner et al. (2017) are that (i) ‘risks of consecutive drought years show little change in the US Southwest and The findings from the analysis for the mean response by Greve et al. Central Plains, but robust increases in Europe and the Mediterranean’, (2018) are qualitatively consistent with results from Wartenburger et and that (ii) ‘limiting warming to 1.5°C may have benefits for future al. (2017), who used an ESR (Section 3.2) rather than a pattern scaling drought risk, but such benefits are regional, and in some cases highly approach for a range of drought and dryness indices. They are also uncertain’. consistent with a study by Lehner et al. (2017), who assessed changes in droughts based on soil moisture changes and the Palmer-Drought Figure 3.13 features projected changes in CDD as a function of global Severity Index. Notably, these two publications do not provide a temperature increase, using a similar approach as for Figures 3.5 (based Alaska/N.W. Canada Canada/Greenl./Icel. W. North America C. North America E. North America Central America/Mexico Amazon N.E. Brazil W. Coast South America (ALA) (CGI) (WNA) (CNA) (ENA) (CAM) (AMZ) (NEB) (WSA) 1 2 3 4 5 6 7 8 9 S.E. South America N. Europe C. Europe S. Europe/Mediterranean (SSA) (NEU) (CEU) (MED) 10 11 12 13 1 2 11 18 3 124 5 13 20 2119 22 6 14 23 Sahara W. Africa (SAH) (WAF) 7 15 16 24 E. Africa S. Africa (EAF) (SAF) 3 14 15 8 16 17 9 17 25 10 26 ∆ CDD (2°C – 1.5°C) (days) -4 -2 -1 -0.5 0 0.5 1 2 4 6 N. Asia W. Asia C. Asia Tibetan Plateau E. Asia S. Asia S.E. Asia N. Australia S. Australia/New Zealand (NAS) (WAS) (CAS) (TIB) (EAS) (SAS) (SEA) (NAU) (SAU) 18 19 20 21 22 23 24 25 26 Global Land + Ocean# Global Land Global Ocean# Legend CMIP5 (ESR) 50 historical 25 RCP 8.5 HAPPI 0 1.5°C - pre-industrial -25 2.0°C - pre-industrial 0 1 2 3 ∆ T glob(°C) Figure 3.13 | Projected changes in consecutive dry days (CDD) as a function of global warming for IPCC Special Report on Managing the Risk of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) regions, based on an empirical scaling relationship applied to Coupled Model Intercomparison Project Phase 5 (CMIP5) data together with projected changes from the HAPPI multimodel experiment (bar plots on regional analyses and central plot, respectively). The underlying methodology and the data basis are the same as for Figure 3.5 (see Supplementary Material 3.SM.2 for more details). Global Land ALA AMZ CAM CAS CEU CGI CNA EAF EAS ENA MED NAS NAU NEB NEU SAF SAH SAS SAU SEA SSA TIB WAF WAS WNA WSA CDD + - + + + + - + + - - + - + + + + + + + - + - + + - + P − E + + + - + + + + + + - - + - - + - - + - + + - + - + - SMA - + - - - - - + + - - - - - - + - - - - - + + - - + - SPI12 + + - + + + + + - + + - + - - + - - - - + - + - - + + Figure 3.14 | Significance of differences in regional drought and dryness indices between the 1.5°C and 2°C global mean temperature targets (rows). Definition of indices: CDD: consecutive dry days; P–E: precipitation minus evapotranspiration; SMA: soil moisture anomalies; SPI12: 12-month Standarized Precipitation Index. Columns indicate analysed regions and global land (see Figure 3.2 for definitions). Significant differences are shown in light blue/brown shading (increases indicated with +, decreases indicated with –; light blue shading indicates decreases in dryness (decreases in CDD, or increases in P–E, SMA or SPI12) and light brown shading indicates increases in dryness (increases in CDD, or decreases in P–E, SMA or SPI12). Non-significant differences are shown in grey shading. The underlying methodology and the data basis are the same as for Figure 3.7 (see Supplementary Material 3.SM.2 for more details). 199 ∆ CDDreg (days) Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems on Wartenburger et al., 2017). The figure also include results from the Brazil, also consistently display drying trends under higher levels of HAPPI experiment (Mitchell et al., 2017). Again, the CMIP5-based ESR forcing in other publications (e.g., Orlowsky and Seneviratne, 2013), estimates and the results of the HAPPI experiment agree well. Note although no published studies could be found reporting observed that the responses vary widely among the considered regions. drying trends in these regions. There are substantial increases in the risk of increased dryness (medium confidence) in both the Similar to Figures 3.8 and 3.11, Figure 3.14 features an objective Mediterranean region and Southern Africa at 2°C versus 1.5°C of identification of ‘hotspots’ / key risks in dryness indices subdivided global warming because these regions display significant changes by region, based on the approach by Wartenburger et al. (2017). This in two dryness indicators (CDD and SMA) between these two global analysis reveals the following hotspots of drying (i.e. increases in CDD warming levels (Figure 3.14); the strongest effects are expected for and/or decreases in P–E, soil moisture anomalies (SMA) and 12-month extreme droughts (medium confidence) (Figure 3.12). There is low Standardized Precipitation Index (SPI12), with at least one of the confidence elsewhere, owing to a lack of consistency in analyses indices displaying statistically significant drying): the Mediterranean with different models or different dryness indicators. However, in region (MED; including southern Europe, northern Africa, and the Near many regions there is medium confidence that most extreme risks of East), northeastern Brazil (NEB) and southern Africa. changes in dryness are avoided if global warming is constrained at 1.5°C instead of 2°C (Figure 3.12). Consistent with this analysis, the available literature particularly supports robust increases in dryness and decreases in water availability In summary, in terms of drought and dryness, limiting global warming in southern Europe and the Mediterranean with a shift from 1.5°C to to 1.5°C is expected to substantially reduce the probability of extreme 2°C of global warming (medium confidence) (Figure 3.13; Schleussner changes in water availability in some regions compared to changes et al., 2016b; Lehner et al., 2017; Wartenburger et al., 2017; Greve et under 2°C of global warming (medium confidence). For shift from 1.5°C al., 2018; Samaniego et al., 2018). This region is already displaying to 2°C of GMST warming, the available studies and analyses suggest substantial drying in the observational record (Seneviratne et al., 2012; strong increases in the probability of dryness and reduced water Sheffield et al., 2012; Greve et al., 2014; Gudmundsson and Seneviratne, availability in the Mediterranean region (including southern Europe, 3 2016; Gudmundsson et al., 2017), which provides additional evidence northern Africa and the Near East) and in southern Africa (medium supporting this tendency and suggests that it will be a hotspot of confidence). Based on observations and modelling experiments, a dryness change at global warming levels beyond 1.5°C (see also Box drying trend is already detectable in the Mediterranean region, that is, 3.2). The other identified hotspots, southern Africa and northeastern at global warming of less than 1°C (medium confidence). Box 3.2 | Droughts in the Mediterranean Basin and the Middle East Human society has developed in tandem with the natural environment of the Mediterranean basin over several millennia, laying the groundwork for diverse and culturally rich communities. Even if advances in technology may offer some protection from climatic hazards, the consequences of climatic change for inhabitants of this region continue to depend on the long-term interplay between an array of societal and environmental factors (Holmgren et al., 2016). As a result, the Mediterranean is an example of a region with high vulnerability where various adaptation responses have emerged. Previous IPCC assessments and recent publications project regional changes in climate under increased temperatures, including consistent climate model projections of increased precipitation deficit amplified by strong regional warming (Section 3.3.3; Seneviratne et al., 2012; Christensen et al., 2013; Collins et al., 2013; Greve and Seneviratne, 2015). The long history of resilience to climatic change is especially apparent in the eastern Mediterranean region, which has experienced a strong negative trend in precipitation since 1960 (Mathbout et al., 2017) and an intense and prolonged drought episode between 2007 and 2010 (Kelley et al., 2015). This drought was the longest and most intense in the last 900 years (Cook et al., 2016). Some authors (e.g., Trigo et al., 2010; Kelley et al., 2015) assert that very low precipitation levels have driven a steep decline in agricultural productivity in the Euphrates and Tigris catchment basins, and displaced hundreds of thousands of people, mainly in Syria. Impacts on the water resources (Yazdanpanah et al., 2016) and crop performance in Iran have also been reported (Saeidi et al., 2017). Many historical periods of turmoil have coincided with severe droughts, for example the drought which occurred at the end of the Bronze Age approximately 3200 years ago (Kaniewski et al., 2015). In this instance, a number of flourishing eastern Mediterranean civilizations collapsed, and rural settlements re-emerged with agro-pastoral activities and limited long-distance trade. This illustrates how some vulnerable regions are forced to pursue drastic adaptive responses, including migration and societal structure changes. The potential evolution of drought conditions under 1.5°C or 2°C of global warming (Section 3.3.4) can be analysed by comparing the 2008 drought (high temperature, low precipitation) with the 1960 drought (low temperature, low precipitation) (Kelley et al., 2015). Though the precipitation deficits were comparable, the 2008 drought was amplified by increased evapotranspiration induced by much higher temperatures (a mean increase of 1°C compared with the 1931–2008 period in Syria) and a large population increase (from 200 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Box 3.2 (continued) 5 million in 1960 to 22 million in 2008). Koutroulis et al. (2016) reported that only 6% out of the total 18% decrease in water availability projected for Crete under 2°C of global warming at the end of the 21st century would be due to decreased precipitation, with the remaining 12% due to an increase in evapotranspiration. This study and others like it confirm an important risk of extreme drought conditions for the Middle East under 1.5°C of global warming (Jacob et al., 2018), with risks being even higher in continental locations than on islands; these projections are consistent with current observed changes (Section 3.3.4; Greve et al., 2014). Risks of drying in the Mediterranean region could be substantially reduced if global warming is limited to 1.5°C compared to 2°C or higher levels of warming (Section 3.4.3; Guiot and Cramer, 2016). Higher warming levels may induce high levels of vulnerability exacerbated by large changes in demography. 3.3.5 Runoff and Fluvial Flooding analysed changes of flood magnitude and frequency in the central United States by considering stream gauge daily records with at least 3.3.5.1 Observed and attributed changes in runoff and river 50 years of data ending no earlier than 2011. They showed that flood flooding frequency has increased, whereas there was limited evidence of a decrease in flood magnitude in this region. Stevens et al. (2016) found There has been progress since AR5 in identifying historical changes a rise in the number of reported floods in the United Kingdom during in streamflow and continental runoff. Using the available streamflow the period 1884–2013, with flood events appearing more frequently data, Dai (2016) showed that long-term (1948–2012) flow trends towards the end of the 20th century. A peak was identified in 2012, are statistically significant only for 27.5% of the world’s 200 major when annual rainfall was the second highest in over 100 years. Do et al. rivers, with negative trends outnumbering the positive ones. Although (2017) computed the trends in annual maximum daily streamflow data streamflow trends are mostly not statistically significant, they are across the globe over the 1966–2005 period. They found decreasing consistent with observed regional precipitation changes. From 1950 to trends for a large number of stations in western North America and 3 2012, precipitation and runoff have increased over southeastern South Australia, and increasing trends in parts of Europe, eastern North America, central and northern Australia, the central and northeastern America, parts of South America, and southern Africa. United States, central and northern Europe, and most of Russia, and they have decreased over most of Africa, East and South Asia, eastern In summary, streamflow trends since 1950 are not statistically coastal Australia, the southeastern and northwestern United States, significant in most of the world’s largest rivers (high confidence), western and eastern Canada, the Mediterranean region and some while flood frequency and extreme streamflow have increased in some regions of Brazil (Dai, 2016). regions (high confidence). A large part of the observed regional trends in streamflow and runoff 3.3.5.2 Projected changes in runoff and river flooding at 1.5°C might have resulted from internal multi-decadal and multi-year climate versus 2°C of global warming variations, especially the Pacific decadal variability (PDV), the Atlantic Multi-Decadal Oscillation (AMO) and the El Niño–Southern Oscillation Global-scale assessments of projected changes in freshwater systems (ENSO), although the effect of anthropogenic greenhouse gases generally suggest that areas with either positive or negative changes and aerosols could also be important (Hidalgo et al., 2009; Gu and in mean annual streamflow are smaller for 1.5°C than for 2°C of Adler, 2013, 2015; Chiew et al., 2014; Luo et al., 2016; Gudmundsson global warming (Betts et al., 2018; Döll et al., 2018). Döll et al. (2018) et al., 2017). Additionally, other human activities can influence the found that only 11% of the global land area (excluding Greenland and hydrological cycle, such as land-use/land-cover change, modifications Antarctica) shows a statistically significantly larger hazard at 2°C than in river morphology and water table depth, construction and at 1.5°C. Significant decreases are found for 13% of the global land operation of hydropower plants, dikes and weirs, wetland drainage, area for both global warming levels, while significant increases are and agricultural practices such as water withdrawal for irrigation. All projected to occur for 21% of the global land area at 1.5°C, and rise of these activities can also have a large impact on runoff at the river to between 26% (Döll et al., 2018) and approximately 50% (Betts et basin scale, although there is less agreement over their influence on al., 2018) at 2°C. global mean runoff (Gerten et al., 2008; Sterling et al., 2012; Hall et al., 2014; Betts et al., 2015; Arheimer et al., 2017). Some studies suggest At the regional scale, projected runoff changes generally follow the that increases in global runoff resulting from changes in land cover spatial extent of projected changes in precipitation (see Section 3.3.3). or land use (predominantly deforestation) are counterbalanced by Emerging literature includes runoff projections for different warming decreases resulting from irrigation (Gerten et al., 2008; Sterling et al., levels. For 2°C of global warming, an increase in runoff is projected 2012). Likewise, forest and grassland fires can modify the hydrological for much of the high northern latitudes, Southeast Asia, East Africa, response at the watershed scale when the burned area is significant northeastern Europe, India, and parts of, Austria, China, Hungary, (Versini et al., 2013; Springer et al., 2015; Wine and Cadol, 2016). Norway, Sweden, the northwest Balkans and Sahel (Schleussner et al., 2016b; Donnelly et al., 2017; Döll et al., 2018; Zhai et al., 2018). Few studies have explored observed changes in extreme streamflow Additionally, decreases are projected in the Mediterranean region, and river flooding since the IPCC AR5. Mallakpour and Villarini (2015) southern Australia, Central America, and central and southern South 201 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems America (Schleussner et al., 2016b; Donnelly et al., 2017; Döll et al., Gosling et al. (2017) analysed the impact of global warming of 1°C, 2°C 2018). Differences between 1.5°C and 2°C would be most prominent and 3°C above pre-industrial levels on river runoff at the catchment in the Mediterranean, where the median reduction in annual runoff scale, focusing on eight major rivers in different continents: Upper is expected to be about 9% (likely range 4.5–15.5%) at 1.5°C, Amazon, Darling, Ganges, Lena, Upper Mississippi, Upper Niger, Rhine while at 2°C of warming runoff could decrease by 17% (likely range and Tagus. Their results show that the sign and magnitude of change 8–25%) (Schleussner et al., 2016b). Consistent with these projections, with global warming for the Upper Amazon, Darling, Ganges, Upper Döll et al. (2018) found that statistically insignificant changes in the Niger and Upper Mississippi is unclear, while the Rhine and Tagus may mean annual streamflow around the Mediterranean region became experience decreases in projected runoff and the Lena may experience significant when the global warming scenario was changed from 1.5°C increases. Donnelly et al. (2017) analysed the mean flow response to to 2°C, with decreases of 10–30% between these two warming levels. different warming levels for six major European rivers: Glomma, Wisla, Donnelly et al. (2017) found an intense decrease in runoff along both Lule, Ebro, Rhine and Danube. Consistent with the increases in mean the Iberian and Balkan coasts with an increase in warming level. runoff projected for large parts of northern Europe, the Glomma, Wisla and Lule rivers could experience increased discharges with global Basin-scale projections of river runoff at different warming levels warming while discharges from the Ebro could decrease, in part due are available for many regions. Betts et al. (2018) assessed runoff to a decrease in runoff in southern Europe. In the case of the Rhine changes in 21 of the world’s major river basins at 1.5°C and 2°C of and Danube rivers, Donnelly et al. (2017) did not find clear results. global warming (Figure 3.15). They found a general tendency towards Mean annual runoff of the Yiluo River catchment in northern China increased runoff, except in the Amazon, Orange, Danube and Guadiana is projected to decrease by 22% at 1.5°C and by 21% at 2°C, while basins where the range of projections indicate decreased mean flows the mean annual runoff for the Beijiang River catchment in southern (Figure 3.13). In the case of the Amazon, mean flows are projected China is projected to increase by less than 1% at 1.5°C and 3% at to decline by up to 25% at 2°C global warming (Betts et al., 2018). 2°C in comparison to the studied baseline period (L. Liu et al., 2017). 3 Figure 3.15 | Runoff changes in twenty-one of the world’s major river basins at 1.5°C (blue) and 2°C (orange) of global warming, simulated by the Joint UK Land Environment Simulator (JULES) ecosystem–hydrology model under the ensemble of six climate projections. Boxes show the 25th and 75th percentile changes, whiskers show the range, circles show the four projections that do not define the ends of the range, and crosses show the ensemble means. Numbers in square brackets show the ensemble-mean flow in the baseline (millimetres of rain equivalent) (Source: Betts et al., 2018). 202 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Chen et al. (2017) assessed the future changes in water resources in in contrast, they are projected to decrease at higher latitudes (e.g., the Upper Yangtze River basin for the same warming levels and found in most of Finland, northwestern Russia and northern Sweden), with a slight decrease in the annual discharge at 1.5°C but a slight increase the exception of southern Sweden and some coastal areas in Norway at 2°C. Montroull et al. (2018) studied the hydrological impacts of the where flood magnitudes may increase (Roudier et al., 2016). At the main rivers (Paraguay, Paraná, Iguazú and Uruguay) in La Plata basin basin scale, Mohammed et al. (2017) found that floods are projected to in South America under 1.5°C and 2°C of global warming and for two be more frequent and flood magnitudes greater at 2°C than at 1.5°C emissions scenarios. The Uruguay basin shows increases in streamflow in the Brahmaputra River in Bangladesh. In coastal regions, increases for all scenarios/warming targets except for the combination of in heavy precipitation associated with tropical cyclones (Section RCP8.5/1.5°C of warming. The increase is approximately 15% above 3.3.6) combined with increased sea levels (Section 3.3.9) may lead to the 1981–2000 reference period for 2°C of global warming and the increased flooding (Section 3.4.5). RCP4.5 scenario. For the other three rivers the sign of the change in mean streamflow depends strongly on the RCP and GCM used. In summary, there is medium confidence that global warming of 2°C above the pre-industrial period would lead to an expansion of the Marx et al. (2018) analysed how hydrological low flows in Europe are area with significant increases in runoff, as well as the area affected affected under different global warming levels (1.5°C, 2°C and 3°C). by flood hazard, compared to conditions at 1.5°C of global warming. The Alpine region showed the strongest low flow increase, from 22% A global warming of 1.5°C would also lead to an expansion of the global at 1.5°C to 30% at 2°C, because of the relatively large snow melt land area with significant increases in runoff (medium confidence) and contribution, while in the Mediterranean low flows are expected to to an increase in flood hazard in some regions (medium confidence) decrease because of the decreases in annual precipitation projected compared to present-day conditions. for that region. Döll et al. (2018) found that extreme low flows in the tropical Amazon, Congo and Indonesian basins could decrease by 10% 3.3.6 Tropical Cyclones and Extratropical Storms at 1.5°C, whereas they could increase by 30% in the southwestern part of Russia under the same warming level. At 2°C, projected increases in Most recent studies on observed trends in the attributes of tropical extreme low flows are exacerbated in the higher northern latitudes and cyclones have focused on the satellite era starting in 1979 (Rienecker 3 in eastern Africa, India and Southeast Asia, while projected decreases et al., 2011), but the study of observed trends is complicated by the intensify in the Amazon basin, western United States, central Canada, heterogeneity of constantly advancing remote sensing techniques and and southern and western Europe, although not in the Congo basin or instrumentation during this period (e.g., Landsea, 2006; Walsh et al., Indonesia, where models show less agreement. 2016). Numerous studies leading up to and after AR5 have reported a decreasing trend in the global number of tropical cyclones and/or Recent analyses of projections in river flooding and extreme runoff and the globally accumulated cyclonic energy (Emanuel, 2005; Elsner et al., flows are available for different global warming levels. At the global 2008; Knutson et al., 2010; Holland and Bruyère, 2014; Klotzbach and scale, Alfieri et al. (2017) assessed the frequency and magnitude of river Landsea, 2015; Walsh et al., 2016). A theoretical physical basis for such floods and their impacts under 1.5°C, 2°C and 4°C global warming a decrease to occur under global warming was recently provided by scenarios. They found that flood events with an occurrence interval Kang and Elsner (2015). However, using a relatively short (20 year) longer than the return period of present-day flood protections are and relatively homogeneous remotely sensed record, Klotzbach (2006) projected to increase in all continents under all considered warming reported no significant trends in global cyclonic activity, consistent levels, leading to a widespread increment in the flood hazard. Döll et al. with more recent findings of Holland and Bruyère (2014). Such (2018) found that high flows are projected to increase significantly on contradictions, in combination with the fact that the almost four- 11% and 21% of the global land area at 1.5°C and 2°C, respectively. decade-long period of remotely sensed observations remains relatively Significantly increased high flows are expected to occur in South and short to distinguish anthropogenically induced trends from decadal Southeast Asia and Central Africa at 1.5°C, with this effect intensifying and multi-decadal variability, implies that there is only low confidence and including parts of South America at 2°C. regarding changes in global tropical cyclone numbers under global warming over the last four decades. Regarding the continental scale, Donnelly et al. (2017) and Thober et al. (2018) explored climate change impacts on European high flows Studies in the detection of trends in the occurrence of very intense and/or floods under 1.5°C, 2°C and 3°C of global warming. Thober et tropical cyclones (category 4 and 5 hurricanes on the Saffir-Simpson al. (2018) identified the Mediterranean region as a hotspot of change, scale) over recent decades have yielded contradicting results. Most with significant decreases in high flows of −11% and –13% at 1.5°C studies have reported increases in these systems (Emanuel, 2005; and 2°C, respectively, mainly resulting from reduced precipitation (Box Webster et al., 2005; Klotzbach, 2006; Elsner et al., 2008; Knutson et al., 3.2). In northern regions, high flows are projected to rise by 1% and 2010; Holland and Bruyère, 2014; Walsh et al., 2016), in particular for the 5% at 1.5°C and 2°C, respectively, owing to increasing precipitation, North Atlantic, North Indian and South Indian Ocean basins (e.g., Singh although floods could decrease by 6% in both scenarios because of et al., 2000; Singh, 2010; Kossin et al., 2013; Holland and Bruyère, 2014; less snowmelt. Donnelly et al. (2017) found that high runoff levels Walsh et al., 2016). In the North Indian Ocean over the Arabian Sea, an could rise in intensity, robustness and spatial extent over large parts increase in the frequency of extremely severe cyclonic storms has been of continental Europe with an increasing warming level. At 2°C, flood reported and attributed to anthropogenic warming (Murakami et al., magnitudes are expected to increase significantly in Europe south of 2017). However, to the east over the Bay of Bengal, tropical cyclones 60°N, except for some regions (Bulgaria, Poland and southern Spain); and severe tropical cyclones have exhibited decreasing trends over 203 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems the period 1961–2010, although the ratio between severe tropical degrees of global warming on tropical cyclones over the southwest cyclones and all tropical cyclones is increasing (Mohapatra et al., Indian Ocean, using transient simulations that downscaled a number of 2017). Moreover, studies that have used more homogeneous records, RCP8.5 GCM projections. Decreases in tropical cyclone frequencies are but were consequently limited to rather short periods of 20 to 25 years, projected under both 1.5°C and 2°C of global warming. The decreases have reported no statistically significant trends or decreases in the in cyclone frequencies under 2°C of global warming are somewhat global number of these systems (Kamahori et al., 2006; Klotzbach and larger than under 1.5°C, but no further decreases are projected under Landsea, 2015). Likewise, CMIP5 model simulations of the historical 3°C. This suggests that 2°C of warming, at least in these downscaling period have not produced anthropogenically induced trends in very simulations, represents a type of stabilization level in terms of tropical intense tropical cyclones (Bender et al., 2010; Knutson et al., 2010, cyclone formation over the southwest Indian Ocean and landfall over 2013; Camargo, 2013; Christensen et al., 2013), consistent with the southern Africa (Muthige et al., 2018). There is thus limited evidence findings of Klotzbach and Landsea (2015). There is consequently low that the global number of tropical cyclones will be lower under 2°C confidence in the conclusion that the number of very intense cyclones compared to 1.5°C of global warming, but with an increase in the is increasing globally. number of very intense cyclones (low confidence). General circulation model (GCM) projections of the changing The global response of the mid-latitude atmospheric circulation to attributes of tropical cyclones under high levels of greenhouse gas 1.5°C and 2°C of warming was investigated using the HAPPI ensemble forcing (3°C to 4°C of global warming) consistently indicate decreases with a focus on the winter season (Li et al., 2018). Under 1.5°C of in the global number of tropical cyclones (Knutson et al., 2010, 2015; global warming a weakening of storm activity over North America, Sugi and Yoshimura, 2012; Christensen et al., 2013; Yoshida et al., an equatorward shift of the North Pacific jet exit and an equatorward 2017). A smaller number of studies based on statistical downscaling intensification of the South Pacific jet are projected. Under an additional methodologies contradict these findings, however, and indicate 0.5°C of warming a poleward shift of the North Atlantic jet exit and increases in the global number of tropical cyclones under climate an intensification on the flanks of the Southern Hemisphere storm change (Emanuel, 2017). Most studies also indicate increases in the track are projected to become more pronounced. The weakening of 3 global number of very intense tropical cyclones under high levels of the Mediterranean storm track that is projected under low mitigation global warming (Knutson et al., 2015; Sugi et al., 2017), consistent emerges in the 2°C warmer world (Li et al., 2018). AR5 assessed that with dynamic theory (Kang and Elsner, 2015), although a few studies under high greenhouse gas forcing (3°C or 4°C of global warming) contradict this finding (e.g., Yoshida et al., 2017). Hence, it is assessed there is low confidence in projections of poleward shifts of the that under 3°C to 4°C of warming that the global number of tropical Northern Hemisphere storm tracks, while there is high confidence that cyclones would decrease whilst the number of very intense cyclones there would be a small poleward shift of the Southern Hemisphere would increase (medium confidence). storm tracks (Stocker et al., 2013). In the context of this report, the assessment is that there is limited evidence and low confidence in To date, only two studies have directly explored the changing tropical whether any projected signal for higher levels of warming would be cyclone attributes under 1.5°C versus 2°C of global warming. Using clearly manifested under 2°C of global warming. a high resolution global atmospheric model, Wehner et al. (2018a) concluded that the differences in tropical cyclone statistics under 1.5°C 3.3.7 Ocean Circulation and Temperature versus 2°C stabilization scenarios, as defined by the HAPPI protocols (Mitchell et al., 2017) are small. Consistent with the majority of studies It is virtually certain that the temperature of the upper layers of the performed for higher degrees of global warming, the total number ocean (0–700 m in depth) has been increasing, and that the global of tropical cyclones is projected to decrease under global warming, mean for sea surface temperature (SST) has been changing at a rate whilst the most intense (categories 4 and 5) cyclones are projected just behind that of GMST. The surfaces of three ocean basins has to occur more frequently. These very intense storms are projected warmed over the period 1950–2016 (by 0.11°C, 0.07°C and 0.05°C to be associated with higher peak wind speeds and lower central per decade for the Indian, Atlantic and Pacific Oceans, respectively; pressures under 2°C versus 1.5°C of global warming. The accumulated Hoegh-Guldberg et al., 2014), with the greatest changes occurring cyclonic energy is projected to decrease globally from 1.5°C to 2°C, in at the highest latitudes. Isotherms (i.e., lines of equal temperature) of association with a decrease in the global number of tropical cyclones sea surface temperature (SST) are shifting to higher latitudes at rates under progressively higher levels of global warming. It is also noted of up to 40 km per year (Burrows et al., 2014; García Molinos et al., that heavy rainfall associated with tropical cyclones was assessed in 2015). Long-term patterns of variability make detecting signals due to the IPCC SREX as likely to increase under increasing global warming climate change complex, although the recent acceleration of changes (Seneviratne et al., 2012). Two recent articles suggest that there is to the temperature of the surface layers of the ocean has made the high confidence that the current level of global warming (i.e., about climate signal more distinct (Hoegh-Guldberg et al., 2014). There is also 1°C, see Section 3.3.1) increased the heavy precipitation associated evidence of significant increases in the frequency of marine heatwaves with the 2017 Hurricane Harvey by about 15% or more (Risser and in the observational record (Oliver et al., 2018), consistent with Wehner, 2017; van Oldenborgh et al., 2017). Hence, it can be inferred, changes in mean ocean temperatures (high confidence). Increasing under the assumption of linear dynamics, that further increases in climate extremes in the ocean are associated with the general rise in heavy precipitation would occur under 1.5°C, 2°C and higher levels of global average surface temperature, as well as more intense patterns global warming (medium confidence). Using a high resolution regional of climate variability (e.g., climate change intensification of ENSO) climate model, Muthige et al. (2018) explored the effects of different (Section 3.5.2.5). Increased heat in the upper layers of the ocean is 204 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 also driving more intense storms and greater rates of inundation in Eisenman, 2017) and anthropogenic CO2 emissions (Notz and Stroeve, some regions, which, together with sea level rise, are already driving 2016). This mismatch between the observed and modelled sensitivity significant impacts to sensitive coastal and low-lying areas (Section of Arctic sea ice implies that the multi-model-mean responses of future 3.3.6). sea ice evolution probably underestimates the sea ice loss for a given amount of global warming. To address this issue, studies estimating Increasing land–sea temperature gradients have the potential to the future evolution of Arctic sea ice tend to bias correct the model strengthen upwelling systems associated with the eastern boundary simulations based on the observed evolution of Arctic sea ice in currents (Benguela, Canary, Humboldt and Californian Currents; response to global warming. Based on such bias correction, pre-AR5 Bakun, 1990). Observed trends support the conclusion that a general and post-AR5 studies generally agree that for 1.5°C of global warming strengthening of longshore winds has occurred (Sydeman et al., 2014), relative to pre-industrial levels, the Arctic Ocean will maintain a sea ice but the implications of trends detected in upwelling currents themselves cover throughout summer in most years (Collins et al., 2013; Notz and are unclear (Lluch-Cota et al., 2014). Projections of the scale of changes Stroeve, 2016; Screen and Williamson, 2017; Jahn, 2018; Niederdrenk between 1°C and 1.5°C of global warming and between 1.5°C and and Notz, 2018; Sigmond et al., 2018). For 2°C of global warming, 2°C are only informed by the changes during the past increase in GMST chances of a sea ice-free Arctic during summer are substantially higher of 0.5°C (low confidence). However, evidence from GCM projections (Screen and Williamson, 2017; Jahn, 2018; Niederdrenk and Notz, of future climate change indicates that a general strengthening of the 2018; Screen et al., 2018; Sigmond et al., 2018). Model simulations Benguela, Canary and Humboldt upwelling systems under enhanced suggest that there will be at least one sea ice-free Arctic5 summer after anthropogenic forcing (D. Wang et al., 2015) is projected to occur approximately 10 years of stabilized warming at 2°C, as compared (medium confidence). This strengthening is projected to be stronger to one sea ice-free summer after 100 years of stabilized warming at at higher latitudes. In fact, evidence from regional climate modelling 1.5°C above pre-industrial temperatures (Jahn, 2018; Screen et al., is supportive of an increase in long-shore winds at higher latitudes, 2018; Sigmond et al., 2018). For a specific given year under stabilized whereas long-shore winds may decrease at lower latitudes as a warming of 2°C, studies based on large ensembles of simulations with consequence of the poleward displacement of the subtropical highs a single model estimate the likelihood of ice-free conditions as 35% under climate change (Christensen et al., 2007; Engelbrecht et al., without a bias correction of the underlying model (Sanderson et al., 3 2009). 2017; Jahn, 2018); as between 10% and >99% depending on the observational record used to correct the sensitivity of sea ice decline It is more likely than not that the Atlantic Meridional Overturning to global warming in the underlying model (Niederdrenk and Notz, Circulation (AMOC) has been weakening in recent decades, given 2018); and as 19% based on a procedure to correct for biases in the the detection of the cooling of surface waters in the North Atlantic climatological sea ice coverage in the underlying model (Sigmond et and evidence that the Gulf Stream has slowed since the late 1950s al., 2018). The uncertainty of the first year of the occurrence of an ice- (Rahmstorf et al., 2015b; Srokosz and Bryden, 2015; Caesar et al., free Arctic Ocean arising from internal variability is estimated to be 2018). There is only limited evidence linking the current anomalously about 20 years (Notz, 2015; Jahn et al., 2016). weak state of AMOC to anthropogenic warming (Caesar et al., 2018). It is very likely that the AMOC will weaken over the 21st century. The best The more recent estimates of the warming necessary to produce an ice- estimates and ranges for the reduction based on CMIP5 simulations free Arctic Ocean during summer are lower than the ones given in AR5 are 11% (1– 24%) in RCP2.6 and 34% (12– 54%) in RCP8.5 (AR5). (about 2.6°C–3.1°C of global warming relative to pre-industrial levels There is no evidence indicating significantly different amplitudes of or 1.6°C–2.1°C relative to present-day conditions), which were similar AMOC weakening for 1.5°C versus 2°C of global warming. to the estimate of 3°C of global warming relative to pre-industrial levels (or 2°C relative to present-day conditions) by Mahlstein and 3.3.8 Sea Ice Knutti (2012) based on bias-corrected CMIP3 models. Rosenblum and Eisenman (2016) explained why the sensitivity estimated by Mahlstein Summer sea ice in the Arctic has been retreating rapidly in recent and Knutti (2012) might be too low, estimating instead that September decades. During the period 1997 to 2014, for example, the monthly sea ice in the Arctic would disappear at 2°C of global warming mean sea ice extent during September (summer) decreased on average relative to pre-industrial levels (or about 1°C relative to present-day by 130,000 km² per year (Serreze and Stroeve, 2015). This is about four conditions), in line with the other recent estimates. Notz and Stroeve times as fast as the September sea ice loss during the period 1979 (2016) used the observed correlation between September sea ice to 1996. Sea ice thickness has also decreased substantially, with an extent and cumulative CO2 emissions to estimate that the Arctic Ocean estimated decrease in ice thickness of more than 50% in the central would become nearly free of sea ice during September with a further Arctic (Lindsay and Schweiger, 2015). Sea ice coverage and thickness 1000 Gt of emissions, which also implies a sea ice loss at about 2°C of also decrease in CMIP5 simulations of the recent past, and are global warming. Some of the uncertainty in these numbers stems from projected to decrease in the future (Collins et al., 2013). However, the possible impact of aerosols (Gagne et al., 2017) and of volcanic the modelled sea ice loss in most CMIP5 models is much smaller forcing (Rosenblum and Eisenman, 2016). During winter, little Arctic than observed losses. Compared to observations, the simulations are sea ice is projected to be lost for either 1.5°C or 2°C of global warming less sensitive to both global mean temperature rise (Rosenblum and (Niederdrenk and Notz, 2018). 5 Ice free is defined for the Special Report as when the sea ice extent is less than 106 km2. Ice coverage less than this is considered to be equivalent to an ice-free Arctic Ocean for practical purposes in all recent studies. 205 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems A substantial number of pre-AR5 studies found that there is no more detailed, process-based modelling Church et al. (2013) assigned indication of hysteresis behaviour of Arctic sea ice under decreasing low confidence to SEMs because these models assume that the temperatures following a possible overshoot of a long-term relation between climate forcing and GMSL is the same in the past temperature target (Holland et al., 2006; Schröder and Connolley, 2007; (calibration) and future (projection). Probable future changes in the Armour et al., 2011; Sedláček et al., 2011; Tietsche et al., 2011; Boucher relative contributions of thermal expansion, glaciers and (in particular) et al., 2012; Ridley et al., 2012). In particular, the relationship between ice sheets invalidate this assumption. However, recent emulation- Arctic sea ice coverage and GMST was found to be indistinguishable based studies overcame this shortcoming by considering individual between a warming scenario and a cooling scenario. These results have GMSL contributors separately, and they are therefore employed in been confirmed by post-AR5 studies (Li et al., 2013; Jahn, 2018), which this assessment. In this subsection, the process-based literature of implies high confidence that an intermediate temperature overshoot individual contributors to GMSL is considered for scenarios close to has no long-term consequences for Arctic sea ice coverage. 1.5°C and 2°C of global warming before emulation-based approaches are assessed. In the Antarctic, sea ice shows regionally contrasting trends, such as a strong decrease in sea ice coverage near the Antarctic peninsula but A limited number of processes-based studies are relevant to GMSL in increased sea ice coverage in the Amundsen Sea (Hobbs et al., 2016). 1.5°C and 2°C worlds. Marzeion et al. (2018) used a global glacier model Averaged over these contrasting regional trends, there has been a slow with temperature-scaled scenarios based on RCP2.6 to investigate long-term increase in overall sea ice coverage in the Southern Ocean, the difference between 1.5°C and 2°C of global warming and found although with comparably low ice coverage from September 2016 little difference between scenarios in the glacier contribution to GMSL onwards. Collins et al. (2013) assessed low confidence in Antarctic for the year 2100 (54–97 mm relative to present-day levels for 1.5°C sea ice projections because of the wide range of model projections and 63–112 mm for 2°C, using a 90% confidence interval). This arises and an inability of almost all models to reproduce observations such because glacier melt during the remainder of the century is dominated as the seasonal cycle, interannual variability and the long-term slow by the response to warming from pre-industrial to present-day levels, increase. No existing studies have robustly assessed the possible future which is in turn a reflection of the slow response times of glaciers. Fürst 3 evolution of Antarctic sea ice under low-warming scenarios. et al. (2015) made projections of the Greenland ice sheet’s contribution to GMSL using an ice-flow model forced by the regional climate In summary, the probability of a sea-ice-free Arctic Ocean during model Modèle Atmosphérique Régional (MAR; considered by Church summer is substantially higher at 2°C compared to 1.5°C of global et al. (2013) to be the ‘most realistic’ such model). They projected an warming relative to pre-industrial levels, and there is medium RCP2.6 range of 24–60 mm (1 standard deviation) by the end of the confidence that there will be at least one sea ice-free Arctic summer century (relative to the year 2000 and consistent with the assessment after about 10 years of stabilized warming at 2°C, while about of Church et al. (2013); however, their projections do not allow the 100 years are required at 1.5°C. There is high confidence that an difference between 1.5°C and 2°C worlds to be evaluated. intermediate temperature overshoot has no long-term consequences for Arctic sea ice coverage with regrowth on decadal time scales. The Antarctic ice sheet can contribute both positively, through increases in outflow (solid ice lost directly to the ocean), and negatively, through 3.3.9 Sea Level increases in snowfall (owing to the increased moisture-bearing capacity of a warmer atmosphere), to future GMSL rise. Frieler et al. (2015) Sea level varies over a wide range of temporal and spatial scales, which suggested a range of 3.5–8.7% °C–1 for this effect, which is consistent can be divided into three broad categories. These are global mean sea with AR5. Observations from the Amundsen Sea sector of Antarctica level (GMSL), regional variation about this mean, and the occurrence of suggest an increase in outflow (Mouginot et al., 2014) over recent sea-level extremes associated with storm surges and tides. GMSL has decades associated with grounding line retreat (Rignot et al., 2014) been rising since the late 19th century from the low rates of change that and the influx of relatively warm Circumpolar Deepwater (Jacobs et al., characterized the previous two millennia (Church et al., 2013). Slowing 2011). Literature on the attribution of these changes to anthropogenic in the reported rate over the last two decades (Cazenave et al., 2014) forcing is still in its infancy (Goddard et al., 2017; Turner et al., 2017a). may be attributable to instrumental drift in the observing satellite RCP2.6-based projections of Antarctic outflow (Levermann et al., system (Watson et al., 2015) and increased volcanic activity (Fasullo 2014; Golledge et al., 2015; DeConto and Pollard, 2016, who include et al., 2016). Accounting for the former results in rates (1993 to mid- snowfall changes) are consistent with the AR5 assessment of Church 2014) between 2.6 and 2.9 mm yr–1 (Watson et al., 2015). The relative et al. (2013) for end-of-century GMSL for RCP2.6, and do not support contributions from thermal expansion, glacier and ice-sheet mass loss, substantial additional GMSL rise by Marine Ice Sheet Instability or and freshwater storage on land are relatively well understood (Church associated instabilities (see Section 3.6). While agreement is relatively et al., 2013; Watson et al., 2015) and their attribution is dominated by good, concerns about the numerical fidelity of these models still exist, anthropogenic forcing since 1970 (15 ± 55% before 1950, 69 ± 31% and this may affect the quality of their projections (Drouet et al., 2013; after 1970) (Slangen et al., 2016). Durand and Pattyn, 2015). An assessment of Antarctic contributions beyond the end of the century, in particular related to the Marine Ice There has been a significant advance in the literature since AR5, which Sheet Instability, can be found in Section 3.6. has included the development of semi-empirical models (SEMs) into a broader emulation-based approach (Kopp et al., 2014; Mengel et al., While some literature on process-based projections of GMSL for the 2016; Nauels et al., 2017) that is partially based on the results from period up to 2100 is available, it is insufficient for distinguishing 206 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 between emissions scenarios associated with 1.5°C and 2°C warmer Recent emulation-based studies show convergence towards this worlds. This literature is, however, consistent with the assessment by AR5 assessment (Table 3.1) and offer the advantage of allowing a Church et al. (2013) of a likely range of 0.28–0.61 m in 2100 (relative comparison between 1.5°C and 2°C warmer worlds. Table 3.1 features to 1986–2005), suggesting that the AR5 assessment is still appropriate. a compilation of recent emulation-based and SEM studies. Table 3.1 | Compilation of recent projections for sea level at 2100 (in cm) for Representative Concentration Pathway (RCP)2.6, and 1.5°C and 2°C scenarios. Upper and lower limits are shown for the 17-84% and 5-95% confidence intervals quoted in the original papers. RCP2.6 1.5°C 2°C Study Baseline 67% 90% 67% 90% 67% 90% AR5 1986–2005 28–61 Kopp et al. (2014) 2000 37–65 29–82 Jevrejeva et al. (2016) 1986–2005 29–58 Kopp et al. (2016) 2000 28–51 24–61 Mengel et al. (2016) 1986–2005 28–56 Nauels et al. (2017) 1986–2005 35–56 Goodwin et al. (2017) 1986–2005 31–59 45–70 45–72 Schaeffer et al. (2012) 2000 52–96 54–99 56–105 Schleussner et al. (2016b) 2000 26–53 36–65 Bittermann et al. (2017) 2000 29–46 39–61 Jackson et al. (2018) 1986–2005 30–58 20–67 35–64 24–74 3 40–77 28–93 47–93 32–117 Sanderson et al. (2017) 50–80 60–90 Nicholls et al. (2018) 1986–2005 24–54 31–65 Rasmussen et al. (2018) 2000 35–64 28–82 39–76 28–96 Goodwin et al. (2018) 1986–2005 26–62 30–69 There is little consensus between the reported ranges of GMSL rise et al. (2018) used this approach to investigate the difference (Table 3.1). Projections vary in the range 0.26–0.77 m and 0.35–0.93 between 1.5°C and 2°C warmer worlds up to 2200. They found that m for 1.5°C and 2°C respectively for the 17–84% confidence interval the reduction in the frequency of 1-in-100-year floods in a 1.5°C (0.20–0.99 m and 0.24–1.17 m for the 5–95% confidence interval). compared to a 2°C warmer world would be greatest in the eastern There is, however, medium agreement that GMSL in 2100 would be USA and Europe, with ESL event frequency amplification being 0.04–0.16 m higher in a 2°C warmer world compared to a 1.5°C reduced by about a half and with smaller reductions for small island warmer world based on the 17–84% confidence interval (0.00–0.24 developing states (SIDS). This last result contrasts with the finding m based on 5–95% confidence interval) with a value of around 0.1 of Vitousek et al. (2017) that regions with low variability in extreme m. There is medium confidence in this assessment because of issues water levels (such as SIDS in the tropics) are particularly sensitive to associated with projections of the Antarctic contribution to GMSL GMSL rise, such that a doubling of frequency may be expected for that are employed in emulation-based studies (see above) and the even small (0.1–0.2 m) rises. Schleussner et al. (2011) emulated the issues previously identified with SEMs (Church et al., 2013). AMOC based on a subset of CMIP-class climate models. When forced using global temperatures appropriate for the CP3-PD scenario (1°C Translating projections of GMSL to the scale of coastlines and of warming in 2100 relative to 2000 or about 2°C of warming relative islands requires two further steps. The first step accounts for regional to pre-industrial) the emulation suggests an 11% median reduction changes associated with changing water and ice loads (such as in AMOC strength at 2100 (relative to 2000) with an associated Earth’s gravitational field and rotation, and vertical land movement), 0.04 m dynamic sea level rise along the New York City coastline. as well as spatial differences in ocean heat uptake and circulation. The second step maps regional sea level to changes in the return In summary, there is medium confidence that GMSL rise will be about periods of particular flood events to account for effects not included 0.1 m (within a 0.00–0.20 m range based on 17–84% confidence- in global climate models, such as tides, storm surges, and wave setup interval projections) less by the end of the 21st century in a 1.5°C and runup. Kopp et al. (2014) presented a framework to do this and compared to a 2°C warmer world. Projections for 1.5°C and 2°C gave an example application for nine sites located in the US, Japan, global warming cover the ranges 0.2–0.8 m and 0.3–1.00 m relative northern Europe and Chile. Of these sites, seven (all except those in to 1986–2005, respectively (medium confidence). Sea level rise northern Europe) were found to experience at least a quadrupling beyond 2100 is discussed in Section 3.6; however, recent literature in the number of years in the 21st century with 1-in-100-year floods strongly supports the assessment by Church et al. (2013) that sea under RCP2.6 compared to under no future sea level rise. Rasmussen level rise will continue well beyond 2100 (high confidence). 207 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Box 3.3 | Lessons from Past Warm Climate Episodes Climate projections and associated risk assessments for a future warmer world are based on climate model simulations. However, Coupled Model Intercomparison Project Phase 5 (CMIP5) climate models do not include all existing Earth system feedbacks and may therefore underestimate both rates and extents of changes (Knutti and Sedláček, 2012). Evidence from natural archives of three moderately warmer (1.5°C–2°C) climate episodes in Earth’s past help to assess such long-term feedbacks (Fischer et al., 2018). While evidence over the last 2000 years and during the Last Glacial Maximum (LGM) was discussed in detail in the IPCC Fifth Assessment Report (Masson-Delmotte et al., 2013), the climate system response during past warm intervals was the focus of a recent review paper (Fischer et al., 2018) summarized in this Box. Examples of past warmer conditions with essentially modern physical geography include the Holocene Thermal Maximum (HTM; broadly defined as about 10–5 kyr before present (BP), where present is defined as 1950), the Last Interglacial (LIG; about 129–116 kyr BP) and the Mid Pliocene Warm Period (MPWP; 3.3–3.0 Myr BP). Changes in insolation forcing during the HTM (Marcott et al., 2013) and the LIG (Hoffman et al., 2017) led to a global temperature up to 1°C higher than that in the pre-industrial period (1850–1900); high-latitude warming was 2°C–4°C (Capron et al., 2017), while temperature in the tropics changed little (Marcott et al., 2013). Both HTM and LIG experienced atmospheric CO2 levels similar to pre-industrial conditions (Masson-Delmotte et al. 2013). During the MPWP, the most recent time period when CO2 concentrations were similar to present-day levels, the global temperature was >1°C and Arctic temperatures about 8°C warmer than pre-industrial (Brigham-Grette et al., 2013). Although imperfect as analogues for the future, these regional changes can inform risk assessments such as the potential for crossing irreversible thresholds or amplifying anthropogenic changes (Box 3.3, Figure 1). For example, HTM and LIG greenhouse gas 3 (GHG) concentrations show no evidence of runaway greenhouse gas releases under limited global warming. Transient releases of CO2 and CH4 may follow permafrost melting, but these occurrences may be compensated by peat growth over longer time scales (Yu et al., 2010). Warming may release CO2 by enhancing soil respiration, counteracting CO2 fertilization of plant growth (Frank et al., 2010). Evidence of a collapse of the Atlantic Meridional Overturning Circulation (AMOC) during these past events of limited global warming could not be found (Galaasen et al., 2014). The distribution of ecosystems and biomes (major ecosystem types) changed significantly during past warming events, both in the ocean and on land. For example, some tropical and temperate forests retreated because of increased aridity, while savannas expanded (Dowsett et al., 2016). Further, poleward shifts of marine and terrestrial ecosystems, upward shifts in alpine regions, and reorganizations of marine productivity during past warming events are recorded in natural archives (Williams et al., 2009; Haywood et al., 2016). Finally, past warming events are associated with partial sea ice loss in the Arctic. The limited amount of data collected so far on Antarctic sea ice precludes firm conclusions about Southern Hemisphere sea ice losses (de Vernal et al., 2013). Reconstructed global sea level rise of 6–9 m during the LIG and possibly >6 m during the MPWP requires a retreat of either the Greenland or Antarctic ice sheets or both (Dutton et al., 2015). While ice sheet and climate models suggest a substantial retreat of the West Antarctic ice sheet (WAIS) and parts of the East Antarctic ice sheet (DeConto and Pollard, 2016) during these periods, direct observational evidence is still lacking. Evidence for ice retreat in Greenland is stronger, although a complete collapse of the Greenland ice sheet during the LIG can be excluded (Dutton et al., 2015). Rates of past sea level rises under modest warming were similar to or up to two times larger than rises observed over the past two decades (Kopp et al., 2013). Given the long time scales required to reach equilibrium in a warmer world, sea level rise will likely continue for millennia even if warming is limited to 2°C. Finally, temperature reconstructions from these past warm intervals suggest that current climate models underestimate regional warming at high latitudes (polar amplification) and long-term (multi-millennial) global warming. None of these past warm climate episodes involved the high rate of change in atmospheric CO2 and temperatures that we are experiencing today (Fischer et al., 2018). 208 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Box 3.3 (continued) Arctic sea ice: HTM: reduced LIG: reduced MPWP: reduced GIS: HTM: deglacial reequilibration LIG: partial retreat MPWP: smaller boreal forests: HTM: northward expansion LIG: expansion MPWP: northward expansion Savanna: HTM: expansion LIG: expansion likely marine ecosystems: MPWP: expansion HTM: rather unchanged LIG: poleward shift MPWP: poleward shift marine ecosystems: HTM: rather unchanged LIG: poleward shift 3 Antarctic sea ice: MPWP: poleward shift HTM: limited evidence LIG: reduced MPWP: reduced WAIS EAIS: HTM: deglacial reequilibration HTM: deglacial reequilibration LIG: partial retreat likely LIG: partial retreat possible MPWP: retreat likely MPWP: partial retreat possible Box 3.3, Figure 1 | Impacts and responses of components of the Earth System. Summary of typical changes found for warmer periods in the paleorecord, as discussed by Fischer et al. (2018). All statements are relative to pre-industrial conditions. Statements in italics indicate that no conclusions can be drawn for the future. Note that significant spatial variability and uncertainty exists in the assessment of each component, and this figure therefore should not be referred to without reading the publication in detail. HTM: Holocene Thermal Maximum, LIG: Last Interglacial, MPWP: Mid Pliocene Warm Period. (Adapted from Fischer et al., 2018). 3.3.10 Ocean Chemistry (high confidence) (Cao et al., 2007; Stocker et al., 2013). Ocean pH has decreased by 0.1 pH units since the pre-industrial period, a shift that Ocean chemistry includes pH, salinity, oxygen, CO2, and a range of other is unprecedented in the last 65 Ma (high confidence) (Ridgwell and ions and gases, which are in turn affected by precipitation, evaporation, Schmidt, 2010) or even 300 Ma of Earth’s history (medium confidence) storms, river runoff, coastal erosion, up-welling, ice formation, and the (Hönisch et al., 2012). activities of organisms and ecosystems (Stocker et al., 2013). Ocean chemistry is changing alongside increasing global temperature, with Ocean acidification is a result of increasing CO2 in the atmosphere impacts projected at 1.5°C and, more so, at 2°C of global warming (very high confidence) and is most pronounced where temperatures (Doney et al., 2014) (medium to high confidence). Projected changes in are lowest (e.g., polar regions) or where CO2-rich water is brought to the upper layers of the ocean include altered pH, oxygen content and the ocean surface by upwelling (Feely et al., 2008). Acidification can sea level. Despite its many component processes, ocean chemistry has also be influenced by effluents from natural or disturbed coastal land been relatively stable for long periods of time prior to the industrial use (Salisbury et al., 2008), plankton blooms (Cai et al., 2011), and period (Hönisch et al., 2012). Ocean chemistry is changing under the the atmospheric deposition of acidic materials (Omstedt et al., 2015). influence of human activities and rising greenhouse gases (virtually These sources may not be directly attributable to climate change, certain; Rhein et al., 2013; Stocker et al., 2013). About 30% of CO2 but they may amplify the impacts of ocean acidification (Bates and emitted by human activities, for example, has been absorbed by Peters, 2007; Duarte et al., 2013). Ocean acidification also influences the upper layers of the ocean, where it has combined with water to the ionic composition of seawater by changing the organic and produce a dilute acid that dissociates and drives ocean acidification inorganic speciation of trace metals (e.g., 20-fold increases in free ion 209 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems concentrations of metals such as aluminium) – with changes expected Ocean salinity is changing in directions that are consistent with to have impacts although they are currently poorly documented and surface temperatures and the global water cycle (i.e., precipitation understood (low confidence) (Stockdale et al., 2016). versus evaporation). Some regions, such as northern oceans and the Arctic, have decreased in salinity, owing to melting glaciers and ice Oxygen varies regionally and with depth; it is highest in polar regions sheets, while others have increased in salinity, owing to higher sea and lowest in the eastern basins of the Atlantic and Pacific Oceans and surface temperatures and evaporation (Durack et al., 2012). These in the northern Indian Ocean (Doney et al., 2014; Karstensen et al., changes in salinity (i.e., density) are also potentially contributing to 2015; Schmidtko et al., 2017). Increasing surface water temperatures large-scale changes in water movement (Section 3.3.8). have reduced oxygen in the ocean by 2% since 1960, with other variables such as ocean acidification, sea level rise, precipitation, wind 3.3.11 Global Synthesis and storm patterns playing roles (Schmidtko et al., 2017). Changes to ocean mixing and metabolic rates, due to increased temperature Table 3.2 features a summary of the assessments of global and and greater supply of organic carbon to deep areas, has increased the regional climate changes and associated hazards described in this frequency of ‘dead zones’, areas where oxygen levels are so low that chapter, based on the existing literature. For more details about they no longer support oxygen dependent life (Diaz and Rosenberg, observation and attribution in ocean and cryosphere systems, 2008). The changes are complex and include both climate change and please refer to the upcoming IPCC Special Report on the Ocean and other variables (Altieri and Gedan, 2015), and are increasing in tropical Cryosphere in a Changing Climate (SROCC) due to be released in as well as temperate regions (Altieri et al., 2017). 2019. Table 3.2 | Summary of assessments of global and regional climate changes and associated hazards. Confidence and likelihood statements are quoted from the relevant chapter text and are omitted where no assessment was made, in which case the IPCC Fifth Assessment Report (AR5) assessment is given where available. GMST: global mean surface temperature, AMOC: Atlantic Meridional Overturning Circulation, GMSL: global mean sea level. 3 Attribution of observed Projected change Projected change Observed change change to human- at 1.5°C of global at 2°C of global Differences between (recent past versus induced forcing warming compared warming compared 2°C and 1.5°C of pre-industrial) (present-day versus to pre-industrial to pre-industrial global warming pre-industrial) (1.5°C versus 0°C) (2°C versus 0°C) GMST anomalies were 0.87°C The observed 0.87°C GMST 1.5°C 2°C 0.5°C (±0.10°C likely range) above increase in the 2006–2015 pre-industrial (1850–1900) decade compared to values in the 2006–2015 pre-industrial (1850–1900) decade, with a recent warming conditions was mostly human- GMST of about 0.2°C (±0.10°C) per induced (high confidence) anomaly decade (high confidence) Human-induced warming [Chapter 1] reached about 1°C (±0.2°C likely range) above pre- industrial levels in 2017 [Chapter 1] Overall decrease in the Anthropogenic forcing has Global-scale increased intensity Global-scale increased intensity Global-scale increased intensity number of cold days and contributed to the observed and frequency of hot days and frequency of hot days and frequency of hot days and nights and overall increase changes in frequency and and nights, and decreased and nights, and decreased nights, and decreased intensity in the number of warm days intensity of daily temperature intensity and frequency of cold intensity and frequency of cold and frequency of cold days and nights at the global extremes on the global days and nights (very likely) days and nights (very likely) and nights (high confidence) scale on land (very likely) scale since the mid-20th century (very likely) Warming of temperature Warming of temperature Global-scale increase in Continental-scale increase in extremes highest over land, extremes highest over land, length of warm spells and intensity and frequency of hot [Section 3.3.2] including many inhabited including many inhabited decrease in length of cold days and nights, and decrease regions (high confidence), with regions (high confidence), with spells (high confidence) Temperature in intensity and frequency increases of up to 3°C in the increases of up to 4°C in the of cold days and nights, in mid-latitude warm season and mid-latitude warm season and Strongest increase in extremes North America, Europe and up to 4.5°C in the high-latitude up to 6°C in the high-latitude frequency for the rarest Australia (very likely) cold season (high confidence) cold season (high confidence) and most extreme events (high confidence) Increases in frequency or Largest increase in Largest increase in duration of warm spell lengths frequency of unusually frequency of unusually Particularly large increases in large parts of Europe, Asia hot extremes in tropical hot extremes in tropical in hot extremes in inhabited and Australia (high confidence regions (high confidence) regions (high confidence) regions (high confidence) (likely)), as well as at the global [Section 3.3.2] scale (medium confidence) [Section 3.3.2] [Section 3.3.2] [Section 3.3.2] 210 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Table 3.2 (continued) Attribution of observed Projected change Projected change Observed change change to human- at 1.5°C of global at 2°C of global Differences between (recent past versus induced forcing warming compared warming compared 2°C and 1.5°C of pre-industrial) (present-day versus to pre-industrial to pre-industrial global warming pre-industrial) (1.5°C versus 0°C) (2°C versus 0°C) More areas with increases than Human influence contrib- Increases in frequency, Increases in frequency, Higher frequency, intensity decreases in the frequency, uted to the global-scale intensity and/or amount intensity and/or amount and/or amount of heavy intensity and/or amount of tendency towards increases in heavy precipitation when heavy precipitation when precipitation when averaged heavy precipitation (likely) the frequency, intensity and/or averaged over global land, averaged over global land, over global land, with positive amount of heavy precipitation with positive trends in several with positive trends in several trends in several regions [Section 3.3.3] events (medium confidence) regions (high confidence) regions (high confidence) (medium confidence) [Section 3.3.3; AR5 Chapter [Section 3.3.3] [Section 3.3.3] Several regions are projected Heavy 10 (Bindoff et al., 2013a)] to experience increases precipitation in heavy precipitation at 2°C versus 1.5°C (medium confidence), in particular in high-latitude and mountainous regions, as well as in eastern Asia and eastern North America (medium confidence) [Section 3.3.3] High confidence in dryness Medium confidence in Medium confidence Medium confidence in drying Medium confidence in trends in some regions, attribution of drying in drying trends in the trends in the Mediterranean stronger drying trends in especially drying in the Medi- trends in southern Europe Mediterranean region region and Southern Africa the Mediterranean region terranean region (including (Mediterranean region) and Southern Africa southern Europe, northern Low confidence elsewhere, in Low confidence elsewhere, in Africa and the Near East) Low confidence elsewhere, in part due to large interannual part due to large interannual Low confidence elsewhere, in 3 part due to large interannual variability and longer duration variability and longer duration part due to large interannual Low confidence in drought variability and longer duration (and thus lower frequency) of (and thus lower frequency) of variability and longer duration and dryness trends at (and thus lower frequency) of drought events, as well as to drought events, as well as to (and thus lower frequency) of the global scale drought events, as well as to dependency on the dryness dependency on the dryness drought events, as well as to Drought and dependency on the dryness index definition applied index definition applied dependency on the dryness [Section 3.3.4] dryness index definition applied index definition appliedIncreases in drought, dryness Increases in drought, dryness [Section 3.3.4] or precipitation deficits or precipitation deficits [Section 3.3.4] projected in some regions projected in some regions compared to the pre-industrial compared to the pre-industrial or present-day conditions, or present-day conditions, but substantial variability but substantial variability in signals depending on in signals depending on considered indices or climate considered indices or climate model (medium confidence) model (medium confidence). [Section 3.3.4] [Section 3.3.4] Streamflow trends mostly Not assessed in this report Expansion of the global land Expansion of the global land Expansion of the global land not statistically significant area with a significant increase area with a significant increase area with significant increase (high confidence) in runoff (medium confidence) in runoff (medium confidence) in runoff (medium confidence) Runoff and Increase in flood frequency and Increase in flood Increase in flood Expansion in the area river flooding extreme streamflow in some hazard in some regions hazard in some regions affected by flood hazard regions (high confidence) (medium confidence) (medium confidence) (medium confidence) [Section 3.3.5] [Section 3.3.5] [Section 3.3.5] [Section 3.3.5] Low confidence in Not meaningful to assess given Increases in heavy precipitation Further increases in heavy Heavy precipitation associated the robustness of low confidence in changes, associated with tropical precipitation associated with tropical cyclones is observed changes due to large interannual cyclones (medium confidence) with tropical cyclones projected to be higher at variability, heterogeneity (medium confidence) 2°C compared to 1.5°C [Section 3.3.6] of the observational record global warming (medium Tropical and and contradictory findings confidence). Limited evidence extra-tropical regarding trends in the that the global number of cyclones observational record tropical cyclones will be lower under 2°C of global warming compared to under 1.5°C of warming, but an increase in the number of very intense cyclones (low confidence) 211 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Table 3.2 (continued) Attribution of observed Projected change Projected change Observed change change to human- at 1.5°C of global at 2°C of global Differences between (recent past versus induced forcing warming compared warming compared 2°C and 1.5°C of pre-industrial) (present-day versus to pre-industrial to pre-industrial global warming pre-industrial) (1.5°C versus 0°C) (2°C versus 0°C) Observed warming of the Limited evidence attributing Further increases in ocean temperatures, including more frequent marine heatwaves (high confidence) upper ocean, with slightly the weakening of AMOC lower rates than global in recent decades to AMOC will weaken over the 21st century and substantially so under high levels (more than 2°C) of warming (virtually certain) anthropogenic forcing global warming (very likely) Ocean Increased occurrence of marine [Section 3.3.7] circulation and heatwaves (high confidence) [Section 3.3.7] temperature AMOC has been weakening over recent decades (more likely than not) [Section 3.3.7] Continuing the trends reported Anthropogenic forcings are At least one sea-ice-free Arctic At least one sea-ice-free Probability of sea-ice-free in AR5, the annual Arctic sea very likely to have contributed summer after about 100 years Arctic summer after about Arctic summer greatly reduced ice extent decreased over to Arctic sea ice loss since 1979 of stabilized warming 10 years of stabilized warming at 1.5°C versus 2°C of global the period 1979–2012. The (medium confidence) (medium confidence) warming (medium confidence) rate of this decrease was [AR5 Chapter 10 Sea ice very likely between 3.5 and (Bindoff et al., 2013a)] [Section 3.3.8] [Section 3.3.8] [Section 3.3.8] 4.1% per decade (0.45 to 0.51 million km2 per decade) Intermediate temperature overshoot has no long-term consequences for Arctic sea ice cover (high confidence) [AR5 Chapter 4 (Vaughan et al., 2013)] [3.3.8] 3 It is likely that the rate of It is very likely that there is Not assessed in this report Not assessed in this report GMSL rise will be about GMSL rise has continued to a substantial contribution 0.1 m (0.00–0.20 m) less increase since the early 20th from anthropogenic forcings at 1.5°C versus 2°C global century, with estimates that to the global mean sea warming (medium confidence) Sea level range from 0.000 [–0.002 level rise since the 1970s to 0.002] mm yr–2 to 0.013 [Section 3.3.9] [0.007 to 0.019] mm yr–2 [AR5 Chapter 10 (Bindoff et al., 2013a)] [AR5 Chapter 13 (Church et al., 2013)] Ocean acidification due to The oceanic uptake of Ocean chemistry is changing with global temperature increases, with impacts increased CO2 has resulted in anthropogenic CO2 has resulted projected at 1.5°C and, more so, at 2°C of warming (high confidence) a 0.1 pH unit decrease since in acidification of surface Ocean the pre-industrial period, which waters (very high confidence). [Section 3.3.10] chemistry is unprecedented in the last 65 Ma (high confidence) [Section 3.3.10] [Section 3.3.10] 3.4 Observed Impacts and Projected Risks regions (IPCC, 2014a, b). The comprehensive assessment undertaken in Natural and Human Systems by AR5 evaluated the evidence of changes to natural systems, and the impact on human communities and industry. While impacts varied 3.4.1 Introduction substantially among systems, sectors and regions, many changes over the past 50 years could be attributed to human driven climate In Section 3.4, new literature is explored and the assessment of impacts change and its impacts. In particular, AR5 attributed observed impacts and projected risks is updated for a large number of natural and in natural ecosystems to anthropogenic climate change, including human systems. This section also includes an exploration of adaptation changes in phenology, geographic and altitudinal range shifts in flora opportunities that could be important steps towards reducing climate and fauna, regime shifts and increased tree mortality, all of which can change, thereby laying the ground for later discussions on opportunities reduce ecosystem functioning and services thereby impacting people. to tackle both mitigation and adaptation while at the same time AR5 also reported increasing evidence of changing patterns of disease recognising the importance of sustainable development and reducing and invasive species, as well as growing risks for communities and the inequities among people and societies facing climate change. industry, which are especially important with respect to sea level rise and human vulnerability. Working Group II (WGII) of the IPCC Fifth Assessment Report (AR5) provided an assessment of the literature on the climate risk for natural One of the important themes that emerged from AR5 is that previous and human systems across a wide range of environments, sectors assessments may have under-estimated the sensitivity of natural and and greenhouse gas scenarios, as well as for particular geographic human systems to climate change. A more recent analysis of attribution 212 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 to greenhouse gas forcing at the global scale (Hansen and Stone, billion people (17% of the global population) who mostly live in South 2016) confirmed that many impacts related to changes in regional and East Asia, North Africa and the Middle East faced serious water atmospheric and ocean temperature can be confidently attributed to shortage and high water stress (Kummu et al., 2016). anthropogenic forcing, while attribution to anthropogenic forcing of changes related to precipitation are by comparison less clear. Moreover, Over the next few decades, and for increases in global mean there is no strong direct relationship between the robustness of climate temperature less than about 2°C, AR5 concluded that changes in attribution and that of impact attribution (Hansen and Stone, 2016). population will generally have a greater effect on water resource The observed changes in human systems are amplified by the loss availability than changes in climate. Climate change, however, will of ecosystem services (e.g., reduced access to safe water) that are regionally exacerbate or offset the effects of population pressure supported by biodiversity (Oppenheimer et al., 2014). Limited research (Jiménez Cisneros et al., 2014). on the risks of warming of 1.5°C and 2°C was conducted following AR5 for most key economic sectors and services, for livelihoods and The differences in projected changes to levels of runoff under 1.5°C poverty, and for rural areas. For these systems, climate is one of many and 2°C of global warming, particularly those that are regional, are drivers that result in adverse outcomes. Other factors include patterns described in Section 3.3.5. Constraining warming to 1.5°C instead of demographic change, socio-economic development, trade and of 2°C might mitigate the risks for water availability, although tourism. Further, consequences of climate change for infrastructure, socio-economic drivers could affect water availability more than the tourism, migration, crop yields and other impacts interact with risks posed by variation in warming levels, while the risks are not underlying vulnerabilities, such as for individuals and communities homogeneous among regions (medium confidence) (Gerten et al., engaged in pastoralism, mountain farming and artisanal fisheries, to 2013; Hanasaki et al., 2013; Arnell and Lloyd-Hughes, 2014; Schewe et affect livelihoods and poverty (Dasgupta et al., 2014). al., 2014; Karnauskas et al., 2018). Assuming a constant population in the models used in his study, Gerten et al. (2013) determined that an Incomplete data and understanding of these lower-end climate additional 8% of the world population in 2000 would be exposed to scenarios have increased the need for more data and an improved new or aggravated water scarcity at 2°C of global warming. This value understanding of the projected risks of warming of 1.5°C and 2°C for was almost halved – with 50% greater reliability – when warming was 3 reference. In this section, the available literature on the projected risks, constrained to 1.5°C. People inhabiting river basins, particularly in the impacts and adaptation options is explored, supported by additional Middle East and Near East, are projected to become newly exposed information and background provided in Supplementary Material to chronic water scarcity even if global warming is constrained to 3.SM.3.1, 3.SM.3.2, 3.SM.3.4, and 3.SM.3.5. A description of the main less than 2°C. Many regions, especially those in Europe, Australia assessment methods of this chapter is given in Section 3.2.2. and southern Africa, appear to be affected at 1.5°C if the reduction in water availability is computed for non-water-scarce basins as well 3.4.2 Freshwater Resources (Quantity and Quality) as for water-scarce regions. Out of a contemporary population of approximately 1.3 billion exposed to water scarcity, about 3% (North 3.4.2.1 Water availability America) to 9% (Europe) are expected to be prone to aggravated scarcity at 2°C of global warming (Gerten et al., 2013). Under the Working Group II of AR5 concluded that about 80% of the world’s Shared Socio-Economic Pathway (SSP)2 population scenario, about 8% population already suffers from serious threats to its water security, as of the global population is projected to experience a severe reduction measured by indicators including water availability, water demand and in water resources under warming of 1.7°C in 2021–2040, increasing pollution (Jiménez Cisneros et al., 2014). UNESCO (2011) concluded to 14% of the population under 2.7°C in 2043–2071, based on the that climate change can alter the availability of water and threaten criteria of discharge reduction of either >20% or >1 standard deviation water security. (Schewe et al., 2014). Depending on the scenarios of SSP1–5, exposure to the increase in water scarcity in 2050 will be globally reduced by Although physical changes in streamflow and continental runoff that 184–270 million people at about 1.5°C of warming compared to the are consistent with climate change have been identified (Section impacts at about 2°C. However, the variation between socio-economic 3.3.5), water scarcity in the past is still less well understood because levels is larger than the variation between warming levels (Arnell and the scarcity assessment needs to take into account various factors, such Lloyd-Hughes, 2014). as the operations of water supply infrastructure and human water use behaviour (Mehran et al., 2017), as well as green water, water quality On many small islands (e.g., those constituting SIDS), freshwater stress and environmental flow requirements (J. Liu et al., 2017). Over the past is expected to occur as a result of projected aridity change. Constraining century, substantial growth in populations, industrial and agricultural warming to 1.5°C, however, could avoid a substantial fraction of activities, and living standards have exacerbated water stress in many water stress compared to 2°C, especially across the Caribbean region, parts of the world, especially in semi-arid and arid regions such as particularly on the island of Hispaniola (Dominican Republic and Haiti) California in the USA (AghaKouchak et al., 2015; Mehran et al., 2015). (Karnauskas et al., 2018). Hanasaki et al. (2013) concluded that the Owing to changes in climate and water consumption behaviour, and projected range of changes in global irrigation water withdrawal particularly effects of the spatial distribution of population growth (relative to the baseline of 1971–2000), using human configuration relative to water resources, the population under water scarcity fixing non-meteorological variables for the period around 2000, are increased from 0.24 billion (14% of the global population) in the 1.1–2.3% and 0.6–2.0% lower at 1.5°C and 2°C, respectively. In the 1900s to 3.8 billion (58%) in the 2000s. In that last period (2000s), 1.1 same study, Hanasaki et al. (2013) highlighted the importance of water 213 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems use scenarios in water scarcity assessments, but neither quantitative capacity to cope with flood risks, all of which depend on socio-economic nor qualitative information regarding water use is available. development conditions, as well as topography and hydro-climatic conditions (Tanoue et al., 2016). AR5 concluded that there was low When the impacts on hydropower production at 1.5°C and 2°C are confidence in the attribution of global changes in droughts (Bindoff et compared, it is found that mean gross potential increases in northern, al., 2013b). However, recent publications based on observational and eastern and western Europe, and decreases in southern Europe (Jacob modelling evidence assessed that human emissions have substantially et al., 2018; Tobin et al., 2018). The Baltic and Scandinavian countries increased the probability of drought years in the Mediterranean region are projected to experience the most positive impacts on hydropower (Section 3.3.4). production. Greece, Spain and Portugal are expected to be the most negatively impacted countries, although the impacts could be reduced WGII AR5 assessed that global flood risk will increase in the future, by limiting warming to 1.5°C (Tobin et al., 2018). In Greece, Spain and partly owing to climate change (low to medium confidence), with Portugal, warming of 2°C is projected to decrease hydropower potential projected changes in the frequency of droughts longer than 12 months below 10%, while limiting global warming to 1.5°C would keep the being more uncertain because of their dependence on accumulated reduction to 5% or less. There is, however, substantial uncertainty precipitation over long periods (Jiménez Cisneros et al., 2014). associated with these results due to a large spread between the climate models (Tobin et al., 2018). Increases in the risks associated with runoff at the global scale (medium confidence), and in flood hazard in some regions (medium Due to a combination of higher water temperatures and reduced confidence), can be expected at global warming of 1.5°C, with an summer river flows, the usable capacity of thermoelectric power plants overall increase in the area affected by flood hazard at 2°C (medium using river water for cooling is expected to reduce in all European confidence) (Section 3.3.5). There are studies, however, that indicate countries (Jacob et al., 2018; Tobin et al., 2018), with the magnitude that socio-economic conditions will exacerbate flood impacts of decreases being about 5% for 1.5°C and 10% for 2°C of global more than global climate change, and that the magnitude of these warming for most European countries (Tobin et al., 2018). Greece, impacts could be larger in some regions (Arnell and Lloyd-Hughes, 3 Spain and Bulgaria are projected to have the largest reduction at 2°C 2014; Winsemius et al., 2016; Alfieri et al., 2017; Arnell et al., 2018; of warming (Tobin et al., 2018). Kinoshita et al., 2018). Assuming constant population sizes, countries representing 73% of the world population will experience increasing Fricko et al. (2016) assessed the direct water use of the global energy flood risk, with an average increase of 580% at 4°C compared to the sector across a broad range of energy system transformation pathways impact simulated over the baseline period 1976–2005. This impact in order to identify the water impacts of a 2°C climate policy. This is projected to be reduced to a 100% increase at 1.5°C and a 170% study revealed that there would be substantial divergence in water increase at 2°C (Alfieri et al., 2017). Alfieri et al. (2017) additionally withdrawal for thermal power plant cooling under conditions in which concluded that the largest increases in flood risks would be found in the distribution of future cooling technology for energy generation is the US, Asia, and Europe in general, while decreases would be found in fixed, whereas adopting alternative cooling technologies and water only a few countries in eastern Europe and Africa. Overall, Alfieri et al. resources would make the divergence considerably smaller. (2017) reported that the projected changes are not homogeneously distributed across the world land surface. Alfieri et al. (2018) studied 3.4.2.2 Extreme hydrological events (floods and droughts) the population affected by flood events using three case studies in European states, specifically central and western Europe, and found Working Group II of AR5 concluded that socio-economic losses from that the population affected could be limited to 86% at 1.5°C of flooding since the mid-20th century have increased mainly because warming compared to 93% at 2°C. Under the SSP2 population of greater exposure and vulnerability (high confidence) (Jiménez scenario, Arnell et al. (2018) found that 39% (range 36–46%) of Cisneros et al., 2014). There was low confidence due to limited impacts on populations exposed to river flooding globally could be evidence, however, that anthropogenic climate change has affected avoided at 1.5°C compared to 2°C of warming. the frequency and magnitude of floods. WGII AR5 also concluded that there is no evidence that surface water and groundwater drought Under scenarios SSP1–5, Arnell and Lloyd-Hughes (2014) found frequency has changed over the last few decades, although impacts that the number of people exposed to increased flooding in 2050 of drought have increased mostly owing to increased water demand under warming of about 1.5°C could be reduced by 26–34 million (Jiménez Cisneros et al., 2014). compared to the number exposed to increased flooding associated with 2°C of warming. Variation between socio-economic levels, Since AR5, the number of studies related to fluvial flooding and however, is projected to be larger than variation between the two meteorological drought based on long-term observed data has been levels of global warming. Kinoshita et al. (2018) found that a serious gradually increasing. There has also been progress since AR5 in increase in potential flood fatality (5.7%) is projected without any identifying historical changes in streamflow and continental runoff adaptation if global warming increases from 1.5°C to 2°C, whereas (Section 3.3.5). As a result of population and economic growth, the projected increase in potential economic loss (0.9%) is relatively increased exposure of people and assets has caused more damage small. Nevertheless, their study indicates that socio-economic changes due to flooding. However, differences in flood risks among regions make a larger contribution to the potentially increased consequences reflect the balance among the magnitude of the flood, the populations, of future floods, and about half of the increase in potential economic their vulnerabilities, the value of assets affected by flooding, and the losses could be mitigated by autonomous adaptation. 214 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 There is limited information about the global and regional 3.4.2.3 Groundwater projected risks posed by droughts at 1.5°C and 2°C of global warming. However, hazards by droughts at 1.5°C could be reduced Working Group II of AR5 concluded that the detection of changes in compared to the hazards at 2°C in some regions, in particular in the groundwater systems, and attribution of those changes to climatic Mediterranean region and southern Africa (Section 3.3.4). Under changes, are rare, owing to a lack of appropriate observation wells constant socio-economic conditions, the population exposed to and an overall small number of studies (Jiménez Cisneros et al., 2014). drought at 2°C of warming is projected to be larger than at 1.5°C (low to medium confidence) (Smirnov et al., 2016; Sun et al., 2017; Since AR5, the number of studies based on long-term observed data Arnell et al., 2018; Liu et al., 2018). Under the same scenario, the continues to be limited. The groundwater-fed lakes in northeastern global mean monthly number of people expected to be exposed to central Europe have been affected by climate and land-use changes, extreme drought at 1.5°C in 2021–2040 is projected to be 114.3 and they showed a predominantly negative lake-level trend in 1999– million, compared to 190.4 million at 2°C in 2041–2060 (Smirnov et 2008 (Kaiser et al., 2014). al., 2016). Under the SSP2 population scenario, Arnell et al. (2018) projected that 39% (range 36–51%) of impacts on populations WGII AR5 concluded that climate change is projected to reduce exposed to drought could be globally avoided at 1.5°C compared groundwater resources significantly in most dry subtropical regions to 2°C warming. (high confidence) (Jiménez Cisneros et al., 2014). Liu et al. (2018) studied the changes in population exposure to severe In some regions, groundwater is often intensively used to supplement droughts in 27 regions around the globe for 1.5°C and 2°C of warming the excess demand, often leading to groundwater depletion. Climate using the SSP1 population scenario compared to the baseline period change adds further pressure on water resources and exaggerates of 1986–2005 based on the Palmer Drought Severity Index (PDSI). human water demands by increasing temperatures over agricultural They concluded that the drought exposure of urban populations in lands (Wada et al., 2017). Very few studies have projected the risks of most regions would be decreased at 1.5°C (350.2 ± 158.8 million groundwater depletion under 1.5°C and 2°C of global warming. Under people) compared to 2°C (410.7 ± 213.5 million people). Liu et al. 2°C of warming, impacts posed on groundwater are projected to be 3 (2018) also suggested that more urban populations would be exposed greater than at 1.5°C (low confidence) (Portmann et al., 2013; Salem to severe droughts at 1.5°C in central Europe, southern Europe, the et al., 2017). Mediterranean, West Africa, East and West Asia, and Southeast Asia, and that number of affected people would increase further in these Portmann et al. (2013) indicated that 2% (range 1.1–2.6%) of the regions at 2°C. However, it should be noted that the PDSI is known global land area is projected to suffer from an extreme decrease in to have limitations (IPCC SREX, Seneviratne et al., 2012), and drought renewable groundwater resources of more than 70% at 2°C, with a projections strongly depend on considered indices (Section 3.3.4); thus clear mitigation at 1.5°C. These authors also projected that 20% of only medium confidence is assigned to these projections. In the Haihe the global land surface would be affected by a groundwater reduction River basin in China, a study has suggested that the proportion of the of more than 10% at 1.5°C of warming, with the percentage of land population exposed to droughts is projected to be reduced by 30.4% impacted increasing at 2°C. In a groundwater-dependent irrigated at 1.5°C but increased by 74.8% at 2°C relative to the baseline value region in northwest Bangladesh, the average groundwater level during of 339.65 million people in the 1986–2005 period, when assessing the major irrigation period (January–April) is projected to decrease in changes in droughts using the Standardized Precipitation-Evaporation accordance with temperature rise (Salem et al., 2017). Index, using a Penman–Monteith estimate of potential evaporation (Sun et al., 2017) . 3.4.2.4 Water quality Alfieri et al. (2018) estimated damage from flooding in Europe for Working Group II of AR5 concluded that most observed changes to the baseline period (1976–2005) at 5 billion euro of losses annually, water quality from climate change are from isolated studies, mostly with projections of relative changes in flood impacts that will rise with of rivers or lakes in high-income countries, using a small number of warming levels, from 116% at 1.5°C to 137% at 2°C. variables (Jiménez Cisneros et al., 2014). AR5 assessed that climate change is projected to reduce raw water quality, posing risks to Kinoshita et al. (2018) studied the increase of potential economic loss drinking water quality with conventional treatment (medium to high under SSP3 and projected that the smaller loss at 1.5°C compared confidence) (Jiménez Cisneros et al., 2014). to 2°C (0.9%) is marginal, regardless of whether the vulnerability is fixed at the current level or not. By analysing the differences in results Since AR5, studies have detected climate change impacts on several with and without flood protection standards, Winsemius et al. (2016) indices of water quality in lakes, watersheds and regions (e.g., Patiño showed that adaptation measures have the potential to greatly reduce et al., 2014; Aguilera et al., 2015; Watts et al., 2015; Marszelewski present-day and future flood damage. They concluded that increases in and Pius, 2016; Capo et al., 2017). The number of studies utilising flood-induced economic impacts (% gross domestic product, GDP) in RCP scenarios at the regional or watershed scale have gradually African countries are mainly driven by climate change and that Africa’s increased since AR5 (e.g., Boehlert et al., 2015; Teshager et al., 2016; growing assets would become increasingly exposed to floods. Hence, Marcinkowski et al., 2017). Few studies, have explored projected there is an increasing need for long-term and sustainable investments impacts on water quality under 1.5°C versus 2°C of warming, in adaptation in Africa. however, the differences are unclear (low confidence) (Bonte and 215 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Zwolsman, 2010; Hosseini et al., 2017). The daily probability of 3.4.3 Terrestrial and Wetland Ecosystems exceeding the chloride standard for drinking water taken from Lake IJsselmeer (Andijk, the Netherlands) is projected to increase by 3.4.3.1 Biome shifts a factor of about five at 2°C relative to the present-day warming level of 1°C since 1990 (Bonte and Zwolsman, 2010). Mean monthly Latitudinal and elevational shifts of biomes (major ecosystem dissolved oxygen concentrations and nutrient concentrations in types) in boreal, temperate and tropical regions have been detected the upper Qu’Appelle River (Canada) in 2050–2055 are projected (Settele et al., 2014) and new studies confirm these changes (e.g., to decrease less at about 1.5°C of warming (RCP2.6) compared to shrub encroachment on tundra; Larsen et al., 2014). Attribution concentrations at about 2°C (RCP4.5) (Hosseini et al., 2017). In three studies indicate that anthropogenic climate change has made a river basins in Southeast Asia (Sekong, Sesan and Srepok), about 2°C greater contribution to these changes than any other factor (medium of warming (corresponding to a 1.05°C increase in the 2030s relative confidence) (Settele et al., 2014). to the baseline period 1981–2008, RCP8.5), impacts posed by land- use change on water quality are projected to be greater than at 1.5°C An ensemble of seven Dynamic Vegetation Models driven by projected (corresponding to a 0.89°C increase in the 2030s relative to the climates from 19 alternative general circulation models (GCMs) baseline period 1981–2008, RCP4.5) (Trang et al., 2017). Under the (Warszawski et al., 2013) shows 13% (range 8–20%) of biomes same warming scenarios, Trang et al. (2017) projected changes in the transforming at 2°C of global warming, but only 4% (range 2–7%) annual nitrogen (N) and phosphorus (P) yields in the 2030s, as well as doing so at 1°C, suggesting that about 6.5% may be transformed at with combinations of two land-use change scenarios: (i) conversion 1.5°C; these estimates indicate a doubling of the areal extent of biome of forest to grassland, and (ii) conversion of forest to agricultural shifts between 1.5°C and 2°C of warming (medium confidence) (Figure land. The projected changes in N (P) yield are +7.3% (+5.1%) under 3.16a). A study using the single ecosystem model LPJmL (Gerten et a 1.5°C scenario and –6.6% (–3.6%) under 2°C, whereas changes al., 2013) illustrated that biome shifts in the Arctic, Tibet, Himalayas, under the combination of land-use scenarios are (i) +5.2% (+12.6%) southern Africa and Australia would be avoided by constraining at 1.5°C and +8.8% (+11.7%) at 2°C, and (ii) +7.5% (+14.9%) at warming to 1.5°C compared with 2°C (Figure 3.16b). Seddon et al. 3 1.5°C and +3.7% (+8.8%) at 2°C (Trang et al., 2017). (2016) quantitatively identified ecologically sensitive regions to climate change in most of the continents from tundra to tropical rainforest. 3.4.2.5 Soil erosion and sediment load Biome transformation may in some cases be associated with novel climates and ecological communities (Prober et al., 2012). Working Group II of AR5 concluded that there is little or no observational evidence that soil erosion and sediment load have been 3.4.3.2 Changes in phenology altered significantly by climate change (low to medium confidence) (Jiménez Cisneros et al., 2014). As the number of studies on climate Advancement in spring phenology of 2.8 ± 0.35 days per decade has change impacts on soil erosion has increased where rainfall is an been observed in plants and animals in recent decades in most Northern important driver (Lu et al., 2013), studies have increasingly considered Hemisphere ecosystems (between 30°N and 72°N), and these shifts other factors, such as rainfall intensity (e.g., Shi and Wang, 2015; have been attributed to changes in climate (high confidence) (Settele Li and Fang, 2016), snow melt, and change in vegetation cover et al., 2014). The rates of change are particularly high in the Arctic resulting from temperature rise (Potemkina and Potemkin, 2015), zone owing to the stronger local warming (Oberbauer et al., 2013), as well as crop management practices (Mullan et al., 2012). WGII whereas phenology in tropical forests appears to be more responsive AR5 concluded that increases in heavy rainfall and temperature are to moisture stress (Zhou et al., 2014). While a full review cannot be projected to change soil erosion and sediment yield, although the included here, trends consistent with this earlier finding continue to extent of these changes is highly uncertain and depends on rainfall be detected, including in the flowering times of plants (Parmesan seasonality, land cover, and soil management practices (Jiménez and Hanley, 2015), in the dates of egg laying and migration in birds Cisneros et al., 2014). (newly reported in China; Wu and Shi, 2016), in the emergence dates of butterflies (Roy et al., 2015), and in the seasonal greening-up of While the number of published studies of climate change impacts on vegetation as detected by satellites (i.e., in the normalized difference soil erosion have increased globally since 2000 (Li and Fang, 2016), vegetation index, NDVI; Piao et al., 2015). few articles have addressed impacts at 1.5°C and 2°C of global warming. The existing studies have found few differences in projected The potential for decoupling species–species interactions owing to risks posed on sediment load under 1.5°C and 2°C (low confidence) differing phenological responses to climate change is well established (Cousino et al., 2015; Shrestha et al., 2016). The differences between (Settele et al., 2014), for example for plants and their insect pollinators average annual sediment load under 1.5°C and 2°C of warming are (Willmer, 2012; Scaven and Rafferty, 2013). Mid-century projections not clear, owing to complex interactions among climate change, land of plant and animal phenophases in the UK clearly indicate that cover/surface and soil management (Cousino et al., 2015; Shrestha the timing of phenological events could change more for primary et al., 2016). Averages of annual sediment loads are projected to consumers (6.2 days earlier on average) than for higher trophic be similar under 1.5°C and 2°C of warming, in particular in the levels (2.5–2.9 days earlier on average) (Thackeray et al., 2016). This Great Lakes region in the USA and in the Lower Mekong region in indicates the potential for phenological mismatch and associated Southeast Asia (Cross-Chapter Box 6 in this chapter, Cousino et al., risks for ecosystem functionality in the future under global warming 2015; Shrestha et al., 2016). of 2.1°C–2.7°C above pre-industrial levels. Further, differing responses 216 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 (a) 3 (b) Figure 3.16 | (a) Fraction of global natural vegetation (including managed forests) at risk of severe ecosystem change as a function of global mean temperature change for all ecosystems, models, global climate change models and Representative Concentration Pathways (RCPs). The colours represent the different ecosystem models, which are also horizontally separated for clarity. Results are collated in unit-degree bins, where the temperature for a given year is the average over a 30-year window centred on that year. The boxes span the 25th and 75th percentiles across the entire ensemble. The short, horizontal stripes represent individual (annual) data points, the curves connect the mean value per ecosystem model in each bin. The solid (dashed) curves are for models with (without) dynamic vegetation composition changes. Source: (Warszawski et al., 2013) (b) Threshold level of global temperature anomaly above pre-industrial levels that leads to significant local changes in terrestrial ecosystems. Regions with severe (coloured) or moderate (greyish) ecosystem transformation; delineation refers to the 90 biogeographic regions. All values denote changes found in >50% of the simulations. Source: (Gerten et al., 2013). Regions coloured in dark red are projected to undergo severe transformation under a global warming of 1.5°C while those coloured in light red do so at 2°C; other colours are used when there is no severe transformation unless global warming exceeds 2°C. 217 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems could alter community structure in temperate forests (Roberts et al., and plant species projected to lose over half of their geographic range 2015). Specifically, temperate forest phenology is projected to advance is halved (Warren et al., 2018a) (medium confidence). These findings are by 14.3 days in the near term (2010–2039) and 24.6 days in the consistent with estimates made from an earlier study suggesting that medium term (2040–2069), so as a first approximation the difference range losses at 1.5°C were significantly lower for plants than those at between 2°C and 1.5°C of global warming is about 10 days (Roberts et 2°C of warming (Smith et al., 2018). It should be noted that at 1.5°C al., 2015). This phenological plasticity is not always adaptive and must of warming, and if species’ ability to disperse naturally to track their be interpreted cautiously (Duputié et al., 2015), and considered in the preferred climate geographically is inhibited by natural or anthropogenic context of accompanying changes in climate variability (e.g., increased obstacles, there would still remain 10% of the amphibians, 8% of the risk of frost damage for plants or earlier emergence of insects resulting in reptiles, 6% of the mammals, 5% of the birds, 10% of the insects and mortality during cold spells). Another adaptive response of some plants is 8% of the plants which are projected to lose over half their range, while range expansion with increased vigour and altered herbivore resistance species on average lose 20–27% of their range (Warren et al., 2018a). in their new range, analogous to invasive plants (Macel et al., 2017). Given that bird and mammal species can disperse more easily than amphibians and reptiles, a small proportion can expand their range In summary, limiting warming to 1.5°C compared with 2°C may avoid as climate changes, but even at 1.5°C of warming the total range loss advance in spring phenology (high confidence) by perhaps a few days integrated over all birds and mammals greatly exceeds the integrated (medium confidence) and hence decrease the risks of loss of ecosystem range gain (Warren et al., 2018a). functionality due to phenological mismatch between trophic levels, and also of maladaptation coming from the sensitivity of many species A number of caveats are noted for studies projecting changes to climatic to increased climate variability. Nevertheless, this difference between range. This approach, for example, does not incorporate the effects of 1.5°C and 2°C of warming might be limited for plants that are able to extreme weather events and the role of interactions between species. expand their range. As well, trophic interactions may locally counteract the range expansion of species towards higher altitudes (Bråthen et al., 2018). There is also 3.4.3.3 Changes in species range, abundance and extinction the potential for highly invasive species to become established in new 3 areas as the climate changes (Murphy and Romanuk, 2014), but there is AR5 (Settele et al., 2014) concluded that the geographical ranges of no literature that quantifies this possibility for 1.5°C of global warming. many terrestrial and freshwater plant and animal species have moved over the last several decades in response to warming: approximately 17 Pecl et al. (2017) summarized at the global level the consequences km poleward and 11 m up in altitude per decade. Recent trends confirm of climate-change-induced species redistribution for economic this finding; for example, the spatial and interspecific variance in bird development, livelihoods, food security, human health and culture. populations in Europe and North America since 1980 were found to be These authors concluded that even if anthropogenic greenhouse gas well predicted by trends in climate suitability (Stephens et al., 2016). emissions stopped today, the effort for human systems to adapt to Further, a recent meta-analysis of 27 studies concerning a total of 976 the most crucial effects of climate-driven species redistribution will species (Wiens, 2016) found that 47% of local extinctions (extirpations) be far-reaching and extensive. For example, key insect crop pollinator reported across the globe during the 20th century could be attributed to families (Apidae, Syrphidae and Calliphoridae; i.e., bees, hoverflies climate change, with significantly more extinctions occurring in tropical and blowflies) are projected to retain significantly greater geographic regions, in freshwater habitats and for animals. IUCN (2018) lists 305 ranges under 1.5°C of global warming compared with 2°C (Warren terrestrial animal and plant species from Pacific Island developing nations et al., 2018a). In some cases, when species (such as pest and disease as being threatened by climate change and severe weather. Owing species) move into areas which have become climatically suitable to lags in the responses of some species to climate change, shifts in they may become invasive or harmful to human or natural systems insect pollinator ranges may result in novel assemblages with unknown (Settele et al., 2014). Some studies are beginning to locate ‘refugial’ implications for biodiversity and ecosystem function (Rafferty, 2017). areas where the climate remains suitable in the future for most of the species currently present. For example, Smith et al. (2018) estimated Warren et al. (2013) simulated climatically determined geographic range that 5.5–14% more of the globe’s terrestrial land area could act as loss under 2°C and 4°C of global warming for 50,000 plant and animal climatic refugia for plants under 1.5°C of warming compared to 2°C. species, accounting for uncertainty in climate projections and for the potential ability of species to disperse naturally in an attempt to track their There is no literature that directly estimates the proportion of species at geographically shifting climate envelope. This earlier study has now been increased risk of global (as opposed to local) commitment to extinction updated and expanded to incorporate 105,501 species, including 19,848 as a result of climate change, as this is inherently difficult to quantify. insects, and new findings indicate that warming of 2°C by 2100 would However, it is possible to compare the proportions of species at risk lead to projected bioclimatic range losses of >50% in 18% (6–35%) of of very high range loss; for example, a discernibly smaller number of the 19,848 insects species, 8% (4–16%) of the 12,429 vertebrate species, terrestrial species are projected to lose over 90% of their range at and 16% (9–28%) of the 73,224 plant species studied (Warren et al., 1.5°C of global warming compared with 2°C (Figure 2 in Warren et 2018a). At 1.5°C of warming, these values fall to 6% (1–18%) of the al., 2018a). A link between very high levels of range loss and greatly insects, 4% (2–9%) of the vertebrates and 8% (4–15%) of the plants increased extinction risk may be inferred (Urban, 2015). Hence, limiting studied. Hence, the number of insect species projected to lose over half global warming to 1.5°C compared with 2°C would be expected to of their geographic range is reduced by two-thirds when warming is reduce both range losses and associated extinction risks in terrestrial limited to 1.5°C compared with 2°C, while the number of vertebrate species (high confidence). 218 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 3.4.3.4 Changes in ecosystem function, biomass There is limited published literature examining modelled land carbon and carbon stocks changes specifically under 1.5°C of warming, but existing CMIP5 models and published data are used in this report to draw some Working Group II of AR5 (Settele et al., 2014) concluded that there is conclusions. For systems with significant inertia, such as vegetation or high confidence that net terrestrial ecosystem productivity at the global soil carbon stores, changes in carbon storage will depend on the rate scale has increased relative to the pre-industrial era and that rising of change of forcing and thus depend on the choice of scenario (Jones CO2 concentrations are contributing to this trend through stimulation et al., 2009; Ciais et al., 2013; Sihi et al., 2017). To avoid legacy effects of photosynthesis. There is, however, no clear and consistent signal of the choice of scenario, this report focuses on the response of gross of a climate change contribution. In northern latitudes, the change in primary productivity (GPP) – the rate of photosynthetic carbon uptake productivity has a lower velocity than the warming, possibly because of – by the models, rather than by changes in their carbon store. a lack of resource and vegetation acclimation mechanisms (M. Huang et al., 2017). Biomass and soil carbon stocks in terrestrial ecosystems Figure 3.17 shows different responses of the terrestrial carbon cycle are currently increasing (high confidence), but they are vulnerable to to climate change in different regions. The models show a consistent loss of carbon to the atmosphere as a result of projected increases in response of increased GPP in temperate latitudes of approximately 2 the intensity of storms, wildfires, land degradation and pest outbreaks GtC yr–1 °C–1. Similarly, Gang et al. (2015) projected a robust increase (Settele et al., 2014; Seidl et al., 2017). These losses are expected to in the net primary productivity (NPP) of temperate forests. However, contribute to a decrease in the terrestrial carbon sink. Anderegg et al. Ahlström et al. (2012) showed that this effect could be offset or reversed (2015) demonstrated that total ecosystem respiration at the global by increases in decomposition. Globally, most models project that GPP scale has increased in response to increases in night-time temperature will increase or remain approximately unchanged (Hashimoto et al., (1 PgC yr–1 °C–1, P=0.02). 2013). This projection is supported by findings by Sakalli et al. (2017) for Europe using Euro-CORDEX regional models under a 2°C global The increase in total ecosystem respiration in spring and autumn, warming for the period 2034–2063, which indicated that storage associated with higher temperatures, may convert boreal forests will increase by 5% in soil and by 20% in vegetation. However, using from carbon sinks to carbon sources (Hadden and Grelle, 2016). In the same models Jacob et al. (2018) showed that limiting warming 3 boreal peatlands, for example, increased temperature may diminish to 1.5°C instead of 2°C avoids an increase in ecosystem vulnerability carbon storage and compromise the stability of the peat (Dieleman (compared to a no-climate change scenario) of 40–50%. et al., 2016). In addition, J. Yang et al. (2015) showed that fires reduce the carbon sink of global terrestrial ecosystems by 0.57 PgC yr–1 in At the global level, linear scaling is acceptable for net primary production, ecosystems with large carbon stores, such as peatlands and tropical biomass burning and surface runoff, and impacts on terrestrial carbon forests. Consequently, for adaptation purposes, it is necessary to storage are projected to be greater at 2°C than at 1.5°C (Tanaka et enhance carbon sinks, especially in forests which are prime regulators al., 2017). If global CO2 concentrations and temperatures stabilize, or within the water, energy and carbon cycles (Ellison et al., 2017). Soil can peak and decline, then both land and ocean carbon sinks – which are also be a key compartment for substantial carbon sequestration (Lal, primarily driven by the continued increase in atmospheric CO2 – will 2014; Minasny et al., 2017), depending on the net biome productivity also decline and may even become carbon sources (Jones et al., 2016). and the soil quality (Bispo et al., 2017). Consequently, if a given amount of anthropogenic CO2 is removed from the atmosphere, an equivalent amount of land and ocean anthropogenic AR5 assessed that large uncertainty remains regarding the land carbon CO2 will be released to the atmosphere (Cao and Caldeira, 2010). cycle behaviour of the future (Ciais et al., 2013), with most, but not all, CMIP5 models simulating continued terrestrial carbon uptake under In conclusion, ecosystem respiration is expected to increase with all four RCP scenarios (Jones et al., 2013). Disagreement between increasing temperature, thus reducing soil carbon storage. Soil carbon models outweighs differences between scenarios even up to the year storage is expected to be larger if global warming is restricted to 2100 (Hewitt et al., 2016; Lovenduski and Bonan, 2017). Increased 1.5°C, although some of the associated changes will be countered by atmospheric CO2 concentrations are expected to drive further increases enhanced gross primary production due to elevated CO2 concentrations in the land carbon sink (Ciais et al., 2013; Schimel et al., 2015), which (i.e., the ‘fertilization effect’) and higher temperatures, especially at could persist for centuries (Pugh et al., 2016). Nitrogen, phosphorus and mid- and high latitudes (medium confidence). other nutrients will limit the terrestrial carbon cycle response to both elevated CO2 and altered climate (Goll et al., 2012; Yang et al., 2014; 3.4.3.5 Regional and ecosystem-specific risks Wieder et al., 2015; Zaehle et al., 2015; Ellsworth et al., 2017). Climate change may accelerate plant uptake of carbon (Gang et al., 2015) A large number of threatened systems, including mountain but also increase the rate of decomposition (Todd-Brown et al., 2014; ecosystems, highly biodiverse tropical wet and dry forests, deserts, Koven et al., 2015; Crowther et al., 2016). Ahlström et al. (2012) found freshwater systems and dune systems, were assessed in AR5. These a net loss of carbon in extra-tropical regions and the largest spread include Mediterranean areas in Europe, Siberian, tropical and desert across model results in the tropics. The projected net effect of climate ecosystems in Asia, Australian rainforests, the Fynbos and succulent change is to reduce the carbon sink expected under CO2 increase alone Karoo areas of South Africa, and wetlands in Ethiopia, Malawi, Zambia (Settele et al., 2014). Friend et al. (2014) found substantial uptake of and Zimbabwe. In all these systems, it has been shown that impacts carbon by vegetation under future scenarios when considering the accrue with greater warming, and thus impacts at 2°C are expected to effects of both climate change and elevated CO2. be greater than those at 1.5°C (medium confidence). 219 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Global 30°S - 30°N 40 20 10 20 0 0 -10 -20 -20 -30 -40 -40 -1 0 1 2 3 4 5 6 -1 0 1 2 3 4 5 6 Change in global T (°C) Change in global T (°C) 30°N - 60°N 60°N - 90°N 20 15 15 10 10 5 5 3 0 0 -5 -10 -5 -1 0 1 2 3 4 5 6 -1 0 1 2 3 4 5 6 Change in global T (°C) Change in global T (°C) Figure 3.17 | The response of terrestrial productivity (gross primary productivity, GPP) to climate change, globally (top left) and for three latitudinal regions: 30°S–30°N; 30–60°N and 60–90°N. Data come from the Coupled Model Intercomparison Project Phase 5 (CMIP5) archive (http://cmip-pcmdi.llnl.gov/cmip5/). Seven Earth System Models were used: Norwegian Earth System Model (NorESM-ME, yellow); Community Earth System Model (CESM, red); Institute Pierre Simon Laplace (IPLS)-CM5-LR (dark blue); Geophysical Fluid Dynamics Laboratory (GFDL, pale blue); Max Plank Institute-Earth System Model (MPI-ESM, pink); Hadley Centre New Global Environmental Model 2-Earth System (HadGEM2-ES, orange); and Canadian Earth System Model 2 (CanESM2, green). Differences in GPP between model simulations with (‘1pctCO2’) and without (‘esmfixclim1’) the effects of climate change are shown. Data are plotted against the global mean temperature increase above pre-industrial levels from simulations with a 1% per year increase in CO2 (‘1pctCO2’). The High Arctic region, with tundra-dominated landscapes, has warmed Projected impacts on forests as climate change occurs include increases more than the global average over the last century (Section 3.3; Settele in the intensity of storms, wildfires and pest outbreaks (Settele et al., et al., 2014). The Arctic tundra biome is experiencing increasing fire 2014), potentially leading to forest dieback (medium confidence). disturbance and permafrost degradation (Bring et al., 2016; DeBeer et Warmer and drier conditions in particular facilitate fire, drought and insect al., 2016; Jiang et al., 2016; Yang et al., 2016). Both of these processes disturbances, while warmer and wetter conditions increase disturbances facilitate the establishment of woody species in tundra areas. Arctic from wind and pathogens (Seidl et al., 2017). Particularly vulnerable terrestrial ecosystems are being disrupted by delays in winter onset regions are Central and South America, Mediterranean Basin, South and mild winters associated with global warming (high confidence) Africa, South Australia where the drought risk will increase (see Figure (Cooper, 2014). Observational constraints suggest that stabilization 3.12). Including disturbances in simulations may influence productivity at 1.5°C of warming would avoid the thawing of approximately 1.5 changes in European forests in response to climate change (Reyer et to 2.5 million km2 of permafrost (medium confidence) compared al., 2017b). There is additional evidence for the attribution of increased with stabilization at 2°C (Chadburn et al., 2017), but the time scale forest fire frequency in North America to anthropogenic climate change for release of thawed carbon as CO2 or CH4 should be many centuries during 1984–2015, via the mechanism of increasing fuel aridity almost (Burke et al., 2017). In northern Eurasia, the growing season length is doubling the western USA forest fire area compared to what would projected to increase by about 3–12 days at 1.5°C and 6–16 days at have been expected in the absence of climate change (Abatzoglou and 2°C of warming (medium confidence) (Zhou et al., 2018). Aalto et al. Williams, 2016). This projection is in line with expected fire risks, which (2017) predicted a 72% reduction in cryogenic land surface processes indicate that fire frequency could increase over 37.8% of the global land in northern Europe for RCP2.6 in 2040–2069 (corresponding to a global area during 2010–2039 (Moritz et al., 2012), corresponding to a global warming of approximately 1.6°C), with only slightly larger losses for warming level of approximately 1.2°C, compared with over 61.9% of RCP4.5 (2°C of global warming). the global land area in 2070–2099, corresponding to a warming of 220 GPP change (GtC yr-1) GPP change (GtC yr-1) GPP change (GtC yr-1) GPP change (GtC yr-1) Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 approximately 3.5°C.6 The values in Table 26-1 in a recent paper by mostly in Europe and Southeast Asia, and are responsible for 5% of Romero-Lankao et al. (2014) also indicate significantly lower wildfire human derived CO2 emissions (Green and Page, 2017). Moreover, in the risks in North America for near-term warming (2030–2040, considered a Congo basin (Dargie et al., 2017) and in the Amazonian basin (Draper et proxy for 1.5°C of warming) than at 2°C (high confidence). al., 2014), the peatlands store the equivalent carbon as that of a tropical forest. However, stored carbon is vulnerable to land-use change and The Amazon tropical forest has been shown to be close to its climatic future risk of drought, for example in northeast Brazil (high confidence) limits (Hutyra et al., 2005), but this threshold may move under elevated (Figure 3.12, Section 3.3.4.2). At the global scale, these peatlands are CO2 (Good et al., 2011). Future changes in rainfall, especially dry season undergoing rapid major transformations through drainage and burning length, will determine responses of the Amazon forest (Good et al., in preparation for oil palm and other crops or through unintentional 2013). The forest may be especially vulnerable to combined pressure burning (Magrin et al., 2014). Wetland salinization, a widespread from multiple stressors, namely changes in climate and continued threat to the structure and ecological functioning of inland and coastal anthropogenic disturbance (Borma et al., 2013; Nobre et al., 2016). wetlands, is occurring at a high rate and large geographic scale (Section Modelling (Huntingford et al., 2013) and observational constraints 3.3.6; Herbert et al., 2015). Settele et al. (2014) found that rising water (Cox et al., 2013) suggest that large-scale forest dieback is less likely temperatures are projected to lead to shifts in freshwater species than suggested under early coupled modelling studies (Cox et al., 2000; distributions and worsen water quality. Some of these ecosystems Jones et al., 2009). Nobre et al. (2016) estimated a climatic threshold of respond non-linearly to changes in temperature. For example, Johnson 4°C of warming and a deforestation threshold of 40%. and Poiani (2016) found that the wetland function of the Prairie Pothole region in North America is projected to decline at temperatures beyond In many places around the world, the savanna boundary is moving a local warming of 2°C–3°C above present-day values (1°C local into former grasslands. Woody encroachment, including increased warming, corresponding to 0.6°C of global warming). If the ratio of local tree cover and biomass, has increased over the past century, owing to global warming remains similar for these small levels of warming, to changes in land management, rising CO2 levels, and climate this would indicate a global temperature threshold of 1.2°C–1.8°C variability and change (often in combination) (Settele et al., 2014). For of warming. Hence, constraining global warming to approximately plant species in the Mediterranean region, shifts in phenology, range 1.5°C would maintain the functioning of prairie pothole ecosystems in 3 contraction and health decline have been observed with precipitation terms of their productivity and biodiversity, although a 20% increase decreases and temperature increases (medium confidence) (Settele of precipitation could offset 2°C of global warming (high confidence) et al., 2014). Recent studies using independent complementary (Johnson and Poiani, 2016). approaches have shown that there is a regional-scale threshold in the Mediterranean region between 1.5°C and 2°C of warming (Guiot and 3.4.3.6 Summary of implications for ecosystem services Cramer, 2016; Schleussner et al., 2016b). Further, Guiot and Cramer (2016) concluded that biome shifts unprecedented in the last 10,000 In summary, constraining global warming to 1.5°C rather than 2°C years can only be avoided if global warming is constrained to 1.5°C has strong benefits for terrestrial and wetland ecosystems and their (medium confidence) – whilst 2°C of warming will result in a decrease services (high confidence). These benefits include avoidance or of 12–15% of the Mediterranean biome area. The Fynbos biome in reduction of changes such as biome transformations, species range southwestern South Africa is vulnerable to the increasing impact of losses, increased extinction risks (all high confidence) and changes fires under increasing temperatures and drier winters. It is projected in phenology (high confidence), together with projected increases to lose about 20%, 45% and 80% of its current suitable climate area in extreme weather events which are not yet factored into these under 1°C, 2°C and 3°C of global warming, respectively, compared to analyses (Section 3.3). All of these changes contribute to disruption of 1961–1990 (high confidence) (Engelbrecht and Engelbrecht, 2016). In ecosystem functioning and loss of cultural, provisioning and regulating Australia, an increase in the density of trees and shrubs at the expense services provided by these ecosystems to humans. Examples of such of grassland species is occurring across all major ecosystems and is services include soil conservation (avoidance of desertification), flood projected to be amplified (NCCARF, 2013). Regarding Central America, control, water and air purification, pollination, nutrient cycling, sources Lyra et al. (2017) showed that the tropical rainforest biomass would be of food, and recreation. reduced by about 40% under global warming of 3°C, with considerable replacement by savanna and grassland. With a global warming of close 3.4.4 Ocean Ecosystems to 1.5°C in 2050, a biomass decrease of 20% is projected for tropical rainforests of Central America (Lyra et al., 2017). If a linear response is The ocean plays a central role in regulating atmospheric gas assumed, this decrease may reach 30% (medium confidence). concentrations, global temperature and climate. It also provides habitat to a large number of organisms and ecosystems that provide Freshwater ecosystems are considered to be among the most threatened goods and services worth trillions of USD per year (e.g., Costanza et on the planet (Settele et al., 2014). Although peatlands cover only about al., 2014; Hoegh-Guldberg et al., 2015). Together with local stresses 3% of the land surface, they hold one-third of the world’s soil carbon (Halpern et al., 2015), climate change poses a major threat to an stock (400 to 600 Pg) (Settele et al., 2014). When drained, this carbon increasing number of ocean ecosystems (e.g., warm water or tropical is released to the atmosphere. At least 15% of peatlands have drained, coral reefs: virtually certain, WGII AR5) and consequently to many 6 The approximate temperatures are derived from Figure 10.5a in Meehl et al. (2007), which indicates an ensemble average projection of 0.7°C or 3°C above 1980–1999 temperatures, which were already 0.5°C above pre-industrial values. 221 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems coastal communities that depend on marine resources for food, more so at 2°C, above the pre-industrial period (Hoegh-Guldberg et livelihoods and a safe place to live. Previous sections of this report al., 2007; Donner, 2009; Frieler et al., 2013; Horta E Costa et al., 2014; have described changes in the ocean, including rapid increases Vergés et al., 2014, 2016; Zarco-Perello et al., 2017) and are likely to in ocean temperature down to a depth of at least 700 m (Section result in decreases in marine biodiversity at the equator but increases 3.3.7). In addition, anthropogenic carbon dioxide has decreased in biodiversity at higher latitudes (Cheung et al., 2009; Burrows et ocean pH and affected the concentration of ions in seawater such al., 2014). as carbonate (Sections 3.3.10 and 3.4.4.5), both over a similar depth range. Increased ocean temperatures have intensified storms in some While the impacts of species shifting their ranges are mostly negative regions (Section 3.3.6), expanded the ocean volume and increased for human communities and industry, there are instances of short- sea levels globally (Section 3.3.9), reduced the extent of polar term gains. Fisheries, for example, may expand temporarily at high summer sea ice (Section 3.3.8), and decreased the overall solubility latitudes in the Northern Hemisphere as the extent of summer sea ice of the ocean for oxygen (Section 3.3.10). Importantly, changes in the recedes and NPP increases (medium confidence) (Cheung et al., 2010; response to climate change rarely operate in isolation. Consequently, Lam et al., 2016; Weatherdon et al., 2016). High-latitude fisheries are the effect of global warming of 1.5°C versus 2°C must be considered not only influenced by the effect of temperature on NPP but are also in the light of multiple factors that may accumulate and interact over strongly influenced by the direct effects of changing temperatures on time to produce complex risks, hazards and impacts on human and fish and fisheries (Section 3.4.4.9; Barange et al., 2014; Pörtner et al., natural systems. 2014; Cheung et al., 2016b; Weatherdon et al., 2016). Temporary gains in the productivity of high-latitude fisheries are offset by a growing 3.4.4.1 Observed impacts number of examples from low and mid-latitudes where increases in sea temperature are driving decreases in NPP, owing to the direct Physical and chemical changes to the ocean resulting from increasing effects of elevated temperatures and/or reduced ocean mixing from atmospheric CO2 and other GHGs are already driving significant changes reduced ocean upwelling, that is, increased stratification (low-medium to ocean systems (very high confidence) and will continue to do so at confidence) (Cheung et al., 2010; Ainsworth et al., 2011; Lam et al., 3 1.5°C, and more so at 2°C, of global warming above pre-industrial 2012, 2014, 2016; Bopp et al., 2013; Boyd et al., 2014; Chust et al., 2014; temperatures (Section 3.3.11). These changes have been accompanied Hoegh-Guldberg et al., 2014; Poloczanska et al., 2014; Pörtner et al., by other changes such as ocean acidification, intensifying storms and 2014; Signorini et al., 2015). Reduced ocean upwelling has implications deoxygenation (Levin and Le Bris, 2015). Risks are already significant for millions of people and industries that depend on fisheries for food at current greenhouse gas concentrations and temperatures, and they and livelihoods (Bakun et al., 2015; FAO, 2016; Kämpf and Chapman, vary significantly among depths, locations and ecosystems, with impacts 2016), although there is low confidence in the projection of the size being singular, interactive and/or cumulative (Boyd et al., 2015). of the consequences at 1.5°C. It is also important to appreciate these changes in the context of large-scale ocean processes such as the 3.4.4.2 Warming and stratification of the surface ocean ocean carbon pump. The export of organic carbon to deeper layers of the ocean increases as NPP changes in the surface ocean, for example, As atmospheric greenhouse gases have increased, the global mean with implications for foodwebs and oxygen levels (Boyd et al., 2014; surface temperature (GMST) has reached about 1°C above the pre- Sydeman et al., 2014; Altieri and Gedan, 2015; Bakun et al., 2015; industrial period, and oceans have rapidly warmed from the ocean Boyd, 2015). surface to the deep sea (high confidence) (Sections 3.3.7; Hughes and Narayanaswamy, 2013; Levin and Le Bris, 2015; Yasuhara and 3.4.4.3 Storms and coastal runoff Danovaro, 2016; Sweetman et al., 2017). Marine organisms are already responding to these changes by shifting their biogeographical Storms, wind, waves and inundation can have highly destructive impacts ranges to higher latitudes at rates that range from approximately 0 on ocean and coastal ecosystems, as well as the human communities to 40 km yr–1 (Burrows et al., 2014; Chust, 2014; Bruge et al., that depend on them (IPCC, 2012; Seneviratne et al., 2012). The intensity 2016; Poloczanska et al., 2016), which has consequently affected of tropical cyclones across the world’s oceans has increased, although the the structure and function of the ocean, along with its biodiversity overall number of tropical cyclones has remained the same or decreased and foodwebs (high confidence). Movements of organisms does (medium confidence) (Section 3.3.6; Elsner et al., 2008; Holland and not necessarily equate to the movement of entire ecosystems. For Bruyère, 2014). The direct force of wind and waves associated with example, species of reef-building corals have been observed to shift larger storms, along with changes in storm direction, increases the risks their geographic ranges, yet this has not resulted in the shift of entire of physical damage to coastal communities and to ecosystems such as coral ecosystems (high confidence) (Woodroffe et al., 2010; Yamano mangroves (low to medium confidence) (Long et al., 2016; Primavera et et al., 2011). In the case of ‘less mobile’ ecosystems (e.g., coral reefs, al., 2016; Villamayor et al., 2016; Cheal et al., 2017) and tropical coral kelp forests and intertidal communities), shifts in biogeographical reefs (De’ath et al., 2012; Bozec et al., 2015; Cheal et al., 2017). These ranges may be limited, with mass mortalities and disease outbreaks changes are associated with increases in maximum wind speed, wave increasing in frequency as the exposure to extreme temperatures height and the inundation, although trends in these variables vary from increases (very high confidence) (Hoegh-Guldberg, 1999; Garrabou region to region (Section 3.3.5). In some cases, this can lead to increased et al., 2009; Rivetti et al., 2014; Maynard et al., 2015; Krumhansl et exposure to related impacts, such as flooding, reduced water quality and al., 2016; Hughes et al., 2017b; see also Box 3.4). These trends are increased sediment runoff (medium-high confidence) (Brodie et al., 2012; projected to become more pronounced at warming of 1.5°C, and Wong et al., 2014; Anthony, 2016; AR5, Table 5.1). 222 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Sea level rise also amplifies the impacts of storms and wave action distribution and abundance of kelp forests has rapidly decreased, with (Section 3.3.9), with robust evidence that storm surges and damage implications for fisheries and other ecosystem services (Ling et al., 2009). are already penetrating farther inland than a few decades ago, These risks to marine ecosystems are projected to become greater at changing conditions for coastal ecosystems and human communities. 1.5°C, and more so at 2°C (medium confidence) (Cheung et al., 2009; This is especially true for small islands (Box 3.5) and low-lying coastal Pereira et al., 2010; Pinsky et al., 2013; Burrows et al., 2014). communities, where issues such as storm surges can transform coastal areas (Section 3.4.5; Brown et al., 2018a). Changes in the frequency of Changes to ocean circulation can have even larger influence in terms of extreme events, such as an increase in the frequency of intense storms, scale and impacts. Weakening of the Atlantic Meridional Overturning have the potential (along with other factors, such as disease, food web Circulation (AMOC), for example, is projected to be highly disruptive to changes, invasive organisms and heat stress-related mortality; Burge natural and human systems as the delivery of heat to higher latitudes et al., 2014; Maynard et al., 2015; Weatherdon et al., 2016; Clements via this current system is reduced (Collins et al., 2013). Evidence of et al., 2017) to overwhelm the capacity for natural and human systems a slowdown of AMOC has increased since AR5 (Smeed et al., 2014; to recover following disturbances. This has recently been seen for key Rahmstorf et al., 2015a, b; Kelly et al., 2016), yet a strong causal ecosystems such as tropical coral reefs (Box 3.4), which have changed connection to climate change is missing (low confidence) (Section from coral-dominated ecosystems to assemblages dominated by other 3.3.7). organisms such as seaweeds, with changes in associated organisms and ecosystem services (high confidence) (De’ath et al., 2012; Bozec et 3.4.4.5 Ocean acidification al., 2015; Cheal et al., 2017; Hoegh-Guldberg et al., 2017; Hughes et al., 2017a, b). The impacts of storms are amplified by sea level rise (Section Ocean chemistry encompasses a wide range of phenomena and chemical 3.4.5), leading to substantial challenges today and in the future for species, many of which are integral to the biology and ecology of the cities, deltas and small island states in particular (Sections 3.4.5.2 to ocean (Section 3.3.10; Gattuso et al., 2014, 2015; Hoegh-Guldberg et 3.4.5.4), as well as for coastlines and their associated ecosystems al., 2014; Pörtner et al., 2014). While changes to ocean chemistry are (Sections 3.4.5.5 to 3.4.5.7). likely to be of central importance, the literature on how climate change might influence ocean chemistry over the short and long term is limited 3 3.4.4.4 Ocean circulation (medium confidence). By contrast, numerous risks from the specific changes associated with ocean acidification have been identified (Dove The movement of water within the ocean is essential to its biology et al., 2013; Kroeker et al., 2013; Pörtner et al., 2014; Gattuso et al., and ecology, as well to the circulation of heat, water and nutrients 2015; Albright et al., 2016), with the consensus that resulting changes around the planet (Section 3.3.7). The movement of these factors to the carbonate chemistry of seawater are having, and are likely to drives local and regional climates, as well as primary productivity and continue to have, fundamental and substantial impacts on a wide variety food production. Firmly attributing recent changes in the strength and of organisms (high confidence). Organisms with shells and skeletons direction of ocean currents to climate change, however, is complicated made out of calcium carbonate are particularly at risk, as are the early by long-term patterns and variability (e.g., Pacific decadal oscillation, life history stages of a large number of organisms and processes such PDO; Signorini et al., 2015) and a lack of records that match the long- as de-calcification, although there are some taxa that have not shown term nature of these changes in many cases (Lluch-Cota et al., 2014). An high-sensitivity to changes in CO2, pH and carbonate concentrations assessment of the literature since AR5 (Sydeman et al., 2014), however, (Dove et al., 2013; Fang et al., 2013; Kroeker et al., 2013; Pörtner et concluded that (overall) upwelling-favourable winds have intensified al., 2014; Gattuso et al., 2015). Risks of these impacts also vary with in the California, Benguela and Humboldt upwelling systems, but latitude and depth, with the greatest changes occurring at high latitudes have weakened in the Iberian system and have remained neutral in as well as deeper regions. The aragonite saturation horizon (i.e., where the Canary upwelling system in over 60 years of records (1946–2012) concentrations of calcium and carbonate fall below the saturation point (medium confidence). These conclusions are consistent with a growing for aragonite, a key crystalline form of calcium carbonate) is decreasing consensus that wind-driven upwelling systems are likely to intensify with depth as anthropogenic CO2 penetrates deeper into the ocean over under climate change in many upwelling systems (Sydeman et al., time. Under many models and scenarios, the aragonite saturation is 2014; Bakun et al., 2015; Di Lorenzo, 2015), with potentially positive projected to reach the surface by 2030 onwards, with a growing list of and negative consequences (Bakun et al., 2015). impacts and consequences for ocean organisms, ecosystems and people (Orr et al., 2005; Hauri et al., 2016). Changes in ocean circulation can have profound impacts on marine ecosystems by connecting regions and facilitating the entry and Further, it is difficult to reliably separate the impacts of ocean warming establishment of species in areas where they were unknown before (e.g., and acidification. As ocean waters have increased in sea surface ‘tropicalization’ of temperate ecosystems; Wernberg et al., 2012; Vergés temperature (SST) by approximately 0.9°C they have also decreased et al., 2014, 2016; Zarco-Perello et al., 2017), as well as the arrival of novel by 0.2 pH units since 1870–1899 (‘pre-industrial’; Table 1 in Gattuso et disease agents (low-medium confidence) (Burge et al., 2014; Maynard al., 2015; Bopp et al., 2013). As CO2 concentrations continue to increase et al., 2015; Weatherdon et al., 2016). For example, the herbivorous sea along with other GHGs, pH will decrease while sea temperature will urchin Centrostephanus rodgersii has been reached Tasmania from the increase, reaching 1.7°C and a decrease of 0.2 pH units (by 2100 Australian mainland, where it was previously unknown, owing to a under RCP4.5) relative to the pre-industrial period. These changes are strengthening of the East Australian Current (EAC) that connects the likely to continue given the negative correlation of temperature and two regions (high confidence) (Ling et al., 2009). As a consequence, the pH. Experimental manipulation of CO2, temperature and consequently 223 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems acidification indicate that these impacts will continue to increase in zones (OMZ) (Turner et al., 2008; Carstensen et al., 2014; Acharya and size and scale as CO2 and SST continue to increase in tandem (Dove et Panigrahi, 2016; Lachkar et al., 2018), physiological impacts (Pörtner al., 2013; Fang et al., 2013; Kroeker et al., 2013). et al., 2014), and mortality and/or displacement of oxygen dependent organisms such as fish (Hamukuaya et al., 1998; Thronson and Quigg, While many risks have been defined through laboratory and mesocosm 2008; Jacinto, 2011) and invertebrates (Hobbs and Mcdonald, 2010; experiments, there is a growing list of impacts from the field (medium Bednaršek et al., 2016; Seibel, 2016; Altieri et al., 2017). In addition, confidence) that include community-scale impacts on bacterial deoxygenation interacts with ocean acidification to present substantial assemblages and processes (Endres et al., 2014), coccolithophores separate and combined challenges for fisheries and aquaculture (K.J.S. Meier et al., 2014), pteropods and polar foodwebs (Bednaršek et (medium confidence) (Hamukuaya et al., 1998; Bakun et al., 2015; al., 2012, 2014), phytoplankton (Moy et al., 2009; Riebesell et al., 2013; Rodrigues et al., 2015; Feely et al., 2016; S. Li et al., 2016; Asiedu et al., Richier et al., 2014), benthic ecosystems (Hall-Spencer et al., 2008; 2017a; Clements and Chopin, 2017; Clements et al., 2017; Breitburg et Linares et al., 2015), seagrass (Garrard et al., 2014), and macroalgae al., 2018). Deoxygenation is expected to have greater impacts as ocean (Webster et al., 2013; Ordonez et al., 2014), as well as excavating warming and acidification increase (high confidence), with impacts sponges, endolithic microalgae and reef-building corals (Dove et al., being larger and more numerous than today (e.g., greater challenges 2013; Reyes-Nivia et al., 2013; Fang et al., 2014), and coral reefs (Box for aquaculture and fisheries from hypoxia), and as the number of 3.4; Fabricius et al., 2011; Allen et al., 2017). Some ecosystems, such as hypoxic areas continues to increase. Risks from deoxygenation are those from bathyal areas (i.e., 200–3000 m below the surface), are likely virtually certain to increase as warming continues, although our to undergo very large reductions in pH by the year 2100 (0.29 to 0.37 understanding of risks at 1.5°C versus 2°C is incomplete (medium pH units), yet evidence of how deep-water ecosystems will respond is confidence). Reducing coastal pollution, and consequently the currently limited despite the potential planetary importance of these penetration of organic carbon into deep benthic habitats, is expected areas (low to medium confidence) (Hughes and Narayanaswamy, to reduce the loss of oxygen in coastal waters and hypoxic areas in 2013; Sweetman et al., 2017). general (high confidence) (Breitburg et al., 2018). 3 3.4.4.6 Deoxygenation 3.4.4.7 Loss of sea ice Oxygen levels in the ocean are maintained by a series of processes Sea ice is a persistent feature of the planet’s polar regions (Polyak et al., including ocean mixing, photosynthesis, respiration and solubility 2010) and is central to marine ecosystems, people (e.g., food, culture (Boyd et al., 2014, 2015; Pörtner et al., 2014; Breitburg et al., 2018). and livelihoods) and industries (e.g., fishing, tourism, oil and gas, and Concentrations of oxygen in the ocean are declining (high confidence) shipping). Summer sea ice in the Arctic, however, has been retreating owing to three main factors related to climate change: (i) heat-related rapidly in recent decades (Section 3.3.8), with an assessment of the stratification of the water column (less ventilation and mixing), (ii) literature revealing that a fundamental transformation is occurring reduced oxygen solubility as ocean temperature increases, and (iii) in polar organisms and ecosystems, driven by climate change (high impacts of warming on biological processes that produce or consume confidence) (Larsen et al., 2014). These changes are strongly affecting oxygen such as photosynthesis and respiration (high confidence) (Bopp people in the Arctic who have close relationships with sea ice and et al., 2013; Pörtner et al., 2014; Altieri and Gedan, 2015; Deutsch et associated ecosystems, and these people are facing major adaptation al., 2015; Schmidtko et al., 2017; Shepherd et al., 2017; Breitburg et challenges as a result of sea level rise, coastal erosion, the accelerated al., 2018). Further, a range of processes (Section 3.4.11) are acting thawing of permafrost, changing ecosystems and resources, and many synergistically, including factors not related to climate change, such other issues (Ford, 2012; Ford et al., 2015). as runoff and coastal eutrophication (e.g., from coastal farming and intensive aquaculture). These changes can lead to increased There is considerable and compelling evidence that a further increase phytoplankton productivity as a result of the increased concentration of 0.5°C beyond the present-day average global surface temperature of dissolved nutrients. Increased supply of organic carbon molecules will lead to multiple levels of impact on a variety of organisms, from from coastal run-off can also increase the metabolic activity of coastal phytoplankton to marine mammals, with some of the most dramatic microbial communities (Altieri and Gedan, 2015; Bakun et al., 2015; changes occurring in the Arctic Ocean and western Antarctic Peninsula Boyd, 2015). Deep sea areas are likely to experience some of the (Turner et al., 2014, 2017b; Steinberg et al., 2015; Piñones and Fedorov, greatest challenges, as abyssal seafloor habitats in areas of deep-water 2016). formation are projected to experience decreased water column oxygen concentrations by as much as 0.03 mL L–1 by 2100 (Levin and Le Bris, The impacts of climate change on sea ice are part of the focus 2015; Sweetman et al., 2017). of the IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC), due to be released in 2019, and hence The number of ‘dead zones’ (areas where oxygenated waters have are not covered comprehensively here. However, there is a range of been replaced by hypoxic conditions) has been growing strongly responses to the loss of sea ice that are occurring and which increase since the 1990s (Diaz and Rosenberg, 2008; Altieri and Gedan, 2015; at 1.5°C and further so with 2°C of global warming. Some of these Schmidtko et al., 2017). While attribution can be difficult because of changes are described briefly here. Photosynthetic communities, the complexity of the processes involved, both related and unrelated such macroalgae, phytoplankton and microalgae dwelling on the to climate change, some impacts associated to deoxygenation (low- underside of floating sea ice are changing, owing to increased medium confidence) include the expansion of oxygen minimum temperatures, light and nutrient levels. As sea ice retreats, mixing of 224 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 the water column increases, and phototrophs have increased access 3.4.4.9 Projected risks and adaptation options for oceans under to seasonally high levels of solar radiation (medium confidence) global warming of 1.5°C or 2°C above pre-industrial levels (Dalpadado et al., 2014; W.N. Meier et al., 2014). These changes are expected to stimulate fisheries productivity in high-latitude regions A comprehensive discussion of risk and adaptation options for all by mid-century (high confidence) (Cheung et al., 2009, 2010, 2016b; natural and human systems is not possible in the context and length Lam et al., 2014), with evidence that this is already happening for of this report, and hence the intention here is to illustrate key risks several high-latitude fisheries in the Northern Hemisphere, such as the and adaptation options for ocean ecosystems and sectors. This Bering Sea, although these ‘positive’ impacts may be relatively short- assessment builds on the recent expert consensus of Gattuso et al. lived (Hollowed and Sundby, 2014; Sundby et al., 2016). In addition to (2015) by assessing new literature from 2015–2017 and adjusting the impact of climate change on fisheries via impacts on net primary the levels of risk from climate change in the light of literature since productivity (NPP), there are also direct effects of temperature on 2014. The original expert group’s assessment (Supplementary Material fish, which may in turn have a range of impacts (Pörtner et al., 2014). 3.SM.3.2) was used as input for this new assessment, which focuses Sea ice in Antarctica is undergoing changes that exceed those seen on the implications of global warming of 1.5°C as compared to 2°C. A in the Arctic (Maksym et al., 2011; Reid et al., 2015), with increases discussion of potential adaptation options is also provided, the details in sea ice coverage in the western Ross Sea being accompanied by of which will be further explored in later chapters of this special report. strong decreases in the Bellingshausen and Amundsen Seas (Hobbs The section draws on the extensive analysis and literature presented in et al., 2016). While Antarctica is not permanently populated, the the Supplementary Material of this report (3.SM.3.2, 3.SM.3.3) and has ramifications of changes to the productivity of vast regions, such a summary in Figures 3.18 and 3.20 which outline the added relative as the Southern Ocean, have substantial implications for ocean risks of climate change. foodwebs and fisheries globally. 3.4.4.10 Framework organisms (tropical corals, mangroves 3.4.4.8 Sea level rise and seagrass) Mean sea level is increasing (Section 3.3.9), with substantial impacts Marine organisms (‘ecosystem engineers’), such as seagrass, kelp, 3 already being felt by coastal ecosystems and communities (Wong et oysters, salt marsh species, mangroves and corals, build physical al., 2014) (high confidence). These changes are interacting with other structures or frameworks (i.e., sea grass meadows, kelp forests, oyster factors, such as strengthening storms, which together are driving larger reefs, salt marshes, mangrove forests and coral reefs) which form the storm surges, infrastructure damage, erosion and habitat loss (Church et habitat for a large number of species (Gutiérrez et al., 2012). These al., 2013; Stocker et al., 2013; Blankespoor et al., 2014). Coastal wetland organisms in turn provide food, livelihoods, cultural significance, and ecosystems such as mangroves, sea grasses and salt marshes are under services such as coastal protection to human communities (Bell et al., pressure from rising sea level (medium confidence) (Section 3.4.5; Di 2011, 2018; Cinner et al., 2012; Arkema et al., 2013; Nurse et al., 2014; Nitto et al., 2014; Ellison, 2014; Lovelock et al., 2015; Mills et al., 2016; Wong et al., 2014; Barbier, 2015; Bell and Taylor, 2015; Hoegh-Guldberg Nicholls et al., 2018), as well as from a wide range of other risks and et al., 2015; Mycoo, 2017; Pecl et al., 2017). impacts unrelated to climate change, with the ongoing loss of wetlands recently estimated at approximately 1% per annum across a large Risks of climate change impacts for seagrass and mangrove ecosystems number of countries (Blankespoor et al., 2014; Alongi, 2015). While some were recently assessed by an expert group led by Short et al. (2016). ecosystems (e.g., mangroves) may be able to shift shoreward as sea levels Impacts of climate change were assessed to be similar across a range increase, coastal development (e.g., buildings, seawalls and agriculture) of submerged and emerged plants. Submerged plants such as sea- often interrupts shoreward shifts, as well as reducing sediment supplies grass were affected mostly by temperature extremes (Arias-Ortiz et al., down some rivers (e.g., dams) due to coastal development (Di Nitto et al., 2018), and indirectly by turbidity, while emergent communities such 2014; Lovelock et al., 2015; Mills et al., 2016). as mangroves and salt marshes were most susceptible to sea level variability and temperature extremes, which is consistent with other Responses to sea level rise challenges for ocean and coastal systems evidence (Di Nitto et al., 2014; Sierra-Correa and Cantera Kintz, 2015; include reducing the impact of other stresses, such as those arising Osorio et al., 2016; Sasmito et al., 2016), especially in the context of from tourism, fishing, coastal development, reduced sediment human activities that reduce sediment supply (Lovelock et al., 2015) supply and unsustainable aquaculture/agriculture, in order to build or interrupt the shoreward movement of mangroves though the ecological resilience (Hossain et al., 2015; Sutton-Grier and Moore, construction of coastal infrastructure. This in turn leads to ‘coastal 2016; Asiedu et al., 2017a). The available literature largely concludes squeeze’ where coastal ecosystems are trapped between changing that these impacts will intensify under a 1.5°C warmer world but will ocean conditions and coastal infrastructure (Mills et al., 2016). be even higher at 2°C, especially when considered in the context of Projections of the future distribution of seagrasses suggest a poleward changes occurring beyond the end of the current century. In some shift, which raises concerns that low-latitude seagrass communities cases, restoration of coastal habitats and ecosystems may be a cost- may contract as a result of increasing stress levels (Valle et al., 2014). effective way of responding to changes arising from increasing levels of exposure to rising sea levels, intensifying storms, coastal inundation Climate change (e.g., sea level rise, heat stress, storms) presents risk and salinization (Section 3.4.5 and Box 3.5; Arkema et al., 2013), for coastal ecosystems such as seagrass (high confidence) and reef- although limitations of these strategies have been identified (e.g., building corals (very high confidence) (Figure 3.18, Supplementary Lovelock et al., 2015; Weatherdon et al., 2016). Material 3.SM.3.2), with evidence of increasing concern since AR5 and 225 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems the conclusion that tropical corals may be even more vulnerable to upwelling, or involve deep-water locations that experience less extreme climate change than indicated in assessments made in 2014 (Hoegh- conditions and impacts. Given the potential value of such locations for Guldberg et al., 2014; Gattuso et al., 2015). The current assessment promoting the survival of coral communities under climate change, also considered the heatwave-related loss of 50% of shallow-water efforts to prevent their loss resulting from other stresses are important corals across hundreds of kilometres of the world’s largest continuous (Bongaerts et al., 2010, 2017; Chollett et al., 2010, 2014; Chollett and coral reef system, the Great Barrier Reef. These large-scale impacts, Mumby, 2013; Fine et al., 2013; van Hooidonk et al., 2013; Cacciapaglia plus the observation of back-to-back bleaching events on the Great and van Woesik, 2015; Beyer et al., 2018). A full understanding of Barrier Reef (predicted two decades ago, Hoegh-Guldberg, 1999) and the role of refugia in reducing the loss of ecosystems has yet to be arriving sooner than predicted (Hughes et al., 2017b, 2018), suggest developed (low to medium confidence). There is also interest in ex that the research community may have underestimated climate risks situ conservation approaches involving the restoration of corals via for coral reefs (Figure 3.18). The general assessment of climate risks for aquaculture (Shafir et al., 2006; Rinkevich, 2014) or the use of ‘assisted mangroves prior to this special report was that they face greater risks evolution’ to help corals adapt to changing sea temperatures (van from deforestation and unsustainable coastal development than from Oppen et al., 2015, 2017), although there are numerous challenges climate change (Alongi, 2008; Hoegh-Guldberg et al., 2014; Gattuso et that must be surpassed if these approaches are to be cost-effective al., 2015). Recent large-scale die-offs (Duke et al., 2017; Lovelock et al., responses to preserving coral reefs under rapid climate change (low 2017), however, suggest that risks from climate change may have been confidence) (Hoegh-Guldberg, 2012, 2014a; Bayraktarov et al., 2016). underestimated for mangroves as well. With the events of the last past three years in mind, risks are now considered to be undetectable to High levels of adaptation are expected to be required to prevent moderate (i.e., moderate risks now start at 1.3°C as opposed to 1.8°C; impacts on food security and livelihoods in coastal populations medium confidence). Consequently, when average global warming (medium confidence). Integrating coastal infrastructure with changing reaches 1.3°C above pre-industrial levels, the risk of climate change to ecosystems such as mangroves, seagrasses and salt marsh, may offer mangroves are projected to be moderate (Figure 3.18) while tropical adaptation strategies as they shift shoreward as sea levels rise (high coral reefs will have reached a high level of risk as examplified by confidence). Maintaining the sediment supply to coastal areas would 3 increasing damage from heat stress since the early 1980s. At global also assist mangroves in keeping pace with sea level rise (Shearman et warming of 1.8°C above pre-industrial levels, seagrasses are projected al., 2013; Lovelock et al., 2015; Sasmito et al., 2016). For this reason, to reach moderate to high levels of risk (e.g., damage resulting from habitat for mangroves can be strongly affected by human actions such sea level rise, erosion, extreme temperatures, and storms), while risks as building dams which reduce the sediment supply and hence the to mangroves from climate change are projected to remain moderate ability of mangroves to escape ‘drowning’ as sea level rises (Lovelock (e.g., not keeping up with sea level rise, and more frequent heat stress et al., 2015). In addition, integrated coastal zone management should mortality) although there is low certainty as to when or if this important recognize the importance and economic expediency of using natural ecosystem is likely to transition to higher levels of additional risk from ecosystems such as mangroves and tropical coral reefs to protect climate change (Figure 3.18). coastal human communities (Arkema et al., 2013; Temmerman et al., 2013; Ferrario et al., 2014; Hinkel et al., 2014; Elliff and Silva, 2017). Warm water (tropical) coral reefs are projected to reach a very high Adaptation options include developing alternative livelihoods and risk of impact at 1.2°C (Figure 3.18), with most available evidence food sources, ecosystem-based management/adaptation such as suggesting that coral-dominated ecosystems will be non-existent at this ecosystem restoration, and constructing coastal infrastructure that temperature or higher (high confidence). At this point, coral abundance reduces the impacts of rising seas and intensifying storms (Rinkevich, will be near zero at many locations and storms will contribute to 2015; Weatherdon et al., 2016; Asiedu et al., 2017a; Feller et al., ‘flattening’ the three-dimensional structure of reefs without recovery, 2017). Clearly, these options need to be carefully assessed in terms as already observed for some coral reefs (Alvarez-Filip et al., 2009). The of feasibility, cost and scalability, as well as in the light of the coastal impacts of warming, coupled with ocean acidification, are expected ecosystems involved (Bayraktarov et al., 2016). to undermine the ability of tropical coral reefs to provide habitat for thousand of species, which together provide a range of ecosystem 3.4.4.11 Ocean foodwebs (pteropods, bivalves, krill and fin fish) services (e.g., food, livelihoods, coastal protection, cultural services) that are important for millions of people (high confidence) (Burke et Ocean foodwebs are vast interconnected systems that transfer solar al., 2011). energy and nutrients from phytoplankton to higher trophic levels, including apex predators and commercially important species such Strategies for reducing the impact of climate change on framework as tuna. Here, we consider four representative groups of marine organisms include reducing stresses not directly related to climate organisms which are important within foodwebs across the ocean, and change (e.g., coastal pollution, overfishing and destructive coastal which illustrate the impacts and ramifications of 1.5°C or higher levels development) in order to increase their ecological resilience in the face of warming. of accelerating climate change impacts (World Bank, 2013; Ellison, 2014; Anthony et al., 2015; Sierra-Correa and Cantera Kintz, 2015; The first group of organisms, pteropods, are small pelagic molluscs Kroon et al., 2016; O’Leary et al., 2017), as well as protecting locations that suspension feed and produce a calcium carbonate shell. They are where organisms may be more robust (Palumbi et al., 2014) or less highly abundant in temperate and polar waters where they are an exposed to climate change (Bongaerts et al., 2010; van Hooidonk et important link in the foodweb between phytoplankton and a range al., 2013; Beyer et al., 2018). This might involve cooler areas due to of other organisms including fish, whales and birds. The second group, 226 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 bivalve molluscs (e.g., clams, oysters and mussels), are filter-feeding such as high rates of ocean acidification coupled with shoaling of the invertebrates. These invertebrate organisms underpin important aragonite saturation horizon, are likely to also play key roles (Kawaguchi fisheries and aquaculture industries, from polar to tropical regions, and et al., 2013; Piñones and Fedorov, 2016). As with many risks associated are important food sources for a range of organisms including humans. with impacts at the ecosystem scale, most adaptation options focus on The third group of organisms considered here is a globally significant the management of stresses unrelated to climate change but resulting group of invertebrates known as euphausiid crustaceans (krill), which from human activities, such as pollution and habitat destruction. are a key food source for many marine organisms and hence a major Reducing these stresses will be important in efforts to maintain important link between primary producers and higher trophic levels (e.g., fish, foodweb components. Fisheries management at local to regional scales mammals and sea birds). Antarctic krill, Euphausia superba, are among will be important in reducing stress on foodweb organisms, such as the most abundant species in terms of mass and are consequently an those discussed here, and in helping communities and industries adapt essential component of polar foodwebs (Atkinson et al., 2009). The last to changing foodweb structures and resources (see further discussion of group, fin fishes, is vitally important components of ocean foodwebs, fisheries per se below; Section 3.4.6.3). One strategy is to maintain larger contribute to the income of coastal communities, industries and nations, population levels of fished species in order to provide more resilient and are important to the foodsecurity and livelihood of hundreds of stocks in the face of challenges that are increasingly driven by climate millions of people globally (FAO, 2016). Further background for this change (Green et al., 2014; Bell and Taylor, 2015). section is provided in Supplementary Material 3.SM.3.2. 3.4.4.12 Key ecosystem services (e.g., carbon uptake, coastal There is a moderate risk to ocean foodwebs under present-day protection, and tropical coral reef recreation) conditions (medium to high confidence) (Figure 3.18). Changing water chemistry and temperature are already affecting the ability of The ocean provides important services, including the regulation of pteropods to produce their shells, swim and survive (Bednaršek et atmospheric composition via gas exchange across the boundary al., 2016). Shell dissolution, for example, has increased by 19–26% between ocean and atmosphere, and the storage of carbon in vegetation in both nearshore and offshore populations since the pre-industrial and soils associated with ecosystems such as mangroves, salt marshes period (Feely et al., 2016). There is considerable concern as to and coastal peatlands. These services involve a series of physicochemical 3 whether these organisms are declining further, especially given processes which are influenced by ocean chemistry, circulation, biology, the central importance in ocean foodwebs (David et al., 2017). temperature and biogeochemical components, as well as by factors other Reviewing the literature reveals that pteropods are projected to than climate (Boyd, 2015). The ocean is also a net sink for CO2 (another face high risks of impact at average global temperatures 1.5°C important service), absorbing approximately 30% of human emissions above pre-industrial levels and increasing risks of impacts at 2°C from the burning of fossil fuels and modification of land use (IPCC, 2013). (medium confidence). Carbon uptake by the ocean is decreasing (Iida et al., 2015), and there is increasing concern from observations and models regarding associated As GMST increases by 1.5°C and more, the risk of impacts from ocean changes to ocean circulation (Sections 3.3.7 and 3.4.4., Rahmstorf et warming and acidification are expected to be moderate to high, except al., 2015b);. Biological components of carbon uptake by the ocean are in the case of bivalves (mid-latitudes) where the risks of impacts are also changing, with observations of changing net primary productivity projected to be high to very high (Figure 3.18). Ocean warming and (NPP) in equatorial and coastal upwelling systems (medium confidence) acidification are already affecting the life history stages of bivalve (Lluch-Cota et al., 2014; Sydeman et al., 2014; Bakun et al., 2015), as molluscs (e.g., Asplund et al., 2014; Mackenzie et al., 2014; Waldbusser well as subtropical gyre systems (low confidence) (Signorini et al., 2015). et al., 2014; Zittier et al., 2015; Shi et al., 2016; Velez et al., 2016; Q. There is general agreement that NPP will decline as ocean warming and Wang et al., 2016; Castillo et al., 2017; Lemasson et al., 2017; Ong et al., acidification increase (medium confidence) (Bopp et al., 2013; Boyd et al., 2017; X. Zhao et al., 2017). Impacts on adult bivalves include decreased 2014; Pörtner et al., 2014; Boyd, 2015). growth, increased respiration and reduced calcification, whereas larval stages tend to show greater developmental abnormalities and Projected risks of impacts from reductions in carbon uptake, coastal increased mortality after exposure to these conditions (medium to high protection and services contributing to coral reef recreation suggest confidence) (Q. Wang et al., 2016; Lemasson et al., 2017; Ong et al., a transition from moderate to high risks at 1.5°C and higher (low 2017; X. Zhao et al., 2017). Risks are expected to accumulate at higher confidence). At 2°C, risks of impacts associated with changes to temperatures for bivalve molluscs, with very high risks expected at carbon uptake are high (high confidence), while the risks associated 1.8°C of warming or more. This general pattern applies to low-latitude with reduced coastal protection and recreation on tropical coral fin fish, which are expected to experience moderate to high risks of reefs are high, especially given the vulnerability of this ecosystem impact at 1.3°C of global warming (medium confidence), and very high type, and others (e.g., seagrass and mangroves), to climate change risks at 1.8°C at low latitudes (medium confidence) (Figure 3.18). (medium confidence) (Figure 3.18). Coastal protection is a service provided by natural barriers such as mangroves, seagrass meadows, Large-scale changes to foodweb structure are occurring in all oceans. For coral reefs, and other coastal ecosystems, and it is important for example, record levels of sea ice loss in the Antarctic (Notz and Stroeve, protecting human communities and infrastructure against the impacts 2016; Turner et al., 2017b) translate into a loss of habitat and hence associated with rising sea levels, larger waves and intensifying reduced abundance of krill (Piñones and Fedorov, 2016), with negative storms (high confidence) (Gutiérrez et al., 2012; Kennedy et al., ramifications for the seabirds and whales which feed on krill (Croxall, 2013; Ferrario et al., 2014; Barbier, 2015; Cooper et al., 2016; Hauer 1992; Trathan and Hill, 2016) (low-medium confidence). Other influences, et al., 2016; Narayan et al., 2016). Both natural and human coastal 227 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems protection have the potential to reduce these impacts (Fu and Song, but they are already under moderate risk of not keeping up with sea 2017). Tropical coral reefs, for example, provide effective protection level rise due to climate change and to contributing factors, such as by dissipating about 97% of wave energy, with 86% of the energy reduced sediment supply or obstacles to shoreward shifts (Saunders being dissipated by reef crests alone (Ferrario et al., 2014; Narayan et al., 2014; Lovelock et al., 2015). This implies that coastal areas et al., 2016). Mangroves similarly play an important role in coastal currently protected by mangroves may experience growing risks over protection, as well as providing resources for coastal communities, time. 3 Figure 3.18 | Summary of additional risks of impacts from ocean warming (and associated climate change factors such ocean acidification) for a range of ocean organisms, ecosystems and sectors at 1.0°C, 1.5°C and 2.0°C of warming of the average sea surface temperature (SST) relative to the pre-industrial period. The grey bar represents the range of GMST for the most recent decade: 2006–2015. The assessment of changing risk levels and associated confidence were primarily derived from the expert judgement of Gattuso et al. (2015) and the lead authors and relevant contributing authors of Chapter 3 (SR1.5), while additional input was received from the many reviewers of the ocean systems section of SR1.5. Notes: (i) The analysis shown here is not intended to be comprehensive. The examples of organisms, ecosystems and sectors included here are intended to illustrate the scale, types and projection of risks for representative natural and human ocean systems. (ii) The evaluation of risks by experts did not consider genetic adaptation, acclimatization or human risk reduction strategies (mitigation and societal adaptation). (iii) As discussed elsewhere (Sections 3.3.10 and 3.4.4.5, Box 3.4; Gattuso et al., 2015), ocean acidification is also having impacts on organisms and ecosystems as carbon dioxide increases in the atmosphere. These changes are part of the responses reported here, although partitioning the effects of the two drivers is difficult at this point in time and hence was not attempted. (iv) Confidence levels for location of transition points between levels of risk (L = low, M = moderate, H = high and VH = very high) are assessed and presented here as in the accompanying study by Gattuso et al. (2015). Three transitions in risk were possible: W–Y (white to yellow), Y–R (yellow to red), and R–P (red to purple), with the colours corresponding to the level of additional risk posed by climate change. The confidence levels for these transitions were assessed, based on level of agreement and extent of evidence, and appear as letters associated with each transition (see key in diagram). 228 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Tourism is one of the largest industries globally (Rosselló-Nadal, 2014; al., 2012; Ferrario et al., 2014; Cooper et al., 2016). Natural ecosystems, Markham et al., 2016; Spalding et al., 2017). A substantial part of the when healthy, also have the ability to repair themselves after being global tourist industry is associated with tropical coastal regions and damaged, which sets them apart from coastal hardening and other islands, where tropical coral reefs and related ecosystems play important human structures that require constant maintenance (Barbier, 2015; Elliff roles (Section 3.4.9.1) (medium confidence). Coastal tourism can be a and Silva, 2017). In general, recognizing and restoring coastal ecosystems dominant money earner in terms of foreign exchange for many countries, may be more cost-effective than installing human structures, in that particularly small island developing states (SIDS) (Section 3.4.9.1, Box creating and maintaining structures is typically expensive (Temmerman 3.5; Weatherdon et al., 2016; Spalding et al., 2017). The direct relationship et al., 2013; Mycoo, 2017). between increasing global temperatures, intensifying storms, elevated thermal stress, and the loss of tropical coral reefs has raised concern Recent studies have increasingly stressed the need for coastal protection about the risks of climate change for local economies and industries to be considered within the context of coastal land management, based on tropical coral reefs. Risks to coral reef recreational services from including protecting and ensuring that coastal ecosystems are able to climate change are considered here, as well as in Box 3.5, Section 3.4.9 undergo shifts in their distribution and abundance as climate change and Supplementary Material 3.SM.3.2. occurs (Clausen and Clausen, 2014; Martínez et al., 2014; Cui et al., 2015; André et al., 2016; Mills et al., 2016). Facilitating these changes Adaptations to the broad global changes in carbon uptake by the ocean will require new tools in terms of legal and financial instruments, as are limited and are discussed later in this report with respect to changes well as integrated planning that involves not only human communities in NPP and implications for fishing industries. These adaptation options and infrastructure, but also associated ecosystem responses and values are broad and indirect, and the only other solution at large scale is (Bell, 2012; Mills et al., 2016). In this regard, the interactions between to reduce the entry of CO2 into the ocean. Strategies for adapting to climate change, sea level rise and coastal disasters are increasingly reduced coastal protection involve (a) avoidance of vulnerable areas being informed by models (Bosello and De Cian, 2014) with a widening and hazards, (b) managed retreat from threatened locations, and/or (c) appreciation of the role of natural ecosystems as an alternative to accommodation of impacts and loss of services (Bell, 2012; André et al., hardened coastal structures (Cooper et al., 2016). Adaptation options 2016; Cooper et al., 2016; Mills et al., 2016; Raabe and Stumpf, 2016; Fu for tropical coral reef recreation include: (i) protecting and improving 3 and Song, 2017). Within these broad options, there are some strategies biodiversity and ecological function by minimizing the impact of that involve direct human intervention, such as coastal hardening and stresses unrelated to climate change (e.g., pollution and overfishing), the construction of seawalls and artificial reefs (Rinkevich, 2014, 2015; (ii) ensuring adequate levels of coastal protection by supporting and André et al., 2016; Cooper et al., 2016; Narayan et al., 2016), while repairing ecosystems that protect coastal regions, (iii) ensuring fair others exploit opportunities for increasing coastal protection by involving and equitable access to the economic opportunities associated with naturally occurring oyster banks, coral reefs, mangroves, seagrass and recreational activities, and (iv) seeking and protecting supplies of water other ecosystems (UNEP-WCMC, 2006; Scyphers et al., 2011; Zhang et for tourism, industry and agriculture alongside community needs. Box 3.4 | Warm-Water (Tropical) Coral Reefs in a 1.5°C Warmer World Warm-water coral reefs face very high risks (Figure 3.18) from climate change. A world in which global warming is restricted to 1.5°C above pre-industrial levels would be a better place for coral reefs than that of a 2°C warmer world, in which coral reefs would mostly disappear (Donner et al., 2005; Hoegh-Guldberg et al., 2014; Schleussner et al., 2016b; van Hooidonk et al., 2016; Frieler et al., 2017; Hughes et al., 2017a). Even with warming up until today (GMST for decade 2006–2015: 0.87°C; Chapter 1), a substantial proportion of coral reefs have experienced large-scale mortalities that have lead to much reduced coral populations (Hoegh-Guldberg et al., 2014). In the last three years alone (2016–2018), large coral reef systems such as the Great Barrier Reef (Australia) have lost as much as 50% of their shallow water corals (Hughes et al., 2017b). Coral-dominated reefs are found along coastlines between latitudes 30°S and 30°N, where they provide habitat for over a million species (Reaka-Kudla, 1997) and food, income, coastal protection, cultural context and many other services for millions of people in tropical coastal areas (Burke et al., 2011; Cinner et al., 2012; Kennedy et al., 2013; Pendleton et al., 2016). Ultimately, coral reefs are underpinned by a mutualistic symbiosis between reef-building corals and dinoflagellates from the genus Symbiodinium (Hoegh- Guldberg et al., 2017). Warm-water coral reefs are found down to depths of 150 m and are dependent on light, making them distinct from the cold deep-water reef systems that extend down to depths of 2000 m or more. The difficulty in accessing deep-water reefs also means that the literature on the impacts of climate change on these systems is very limited by comparison to those on warm- water coral reefs (Hoegh-Guldberg et al., 2017). Consequently, this Box focuses on the impacts of climate change on warm-water (tropical) coral reefs, particularly with respect to their prospects under average global surface temperatures of 1.5°C and 2°C above the pre-industrial period. 229 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Box 3.4 (continued) The distribution and abundance of coral reefs has decreased by approximately 50% over the past 30 years (Gardner et al., 2005; Bruno and Selig, 2007; De’ath et al., 2012) as a result of pollution, storms, overfishing and unsustainable coastal development (Burke et al., 2011; Halpern et al., 2015; Cheal et al., 2017). More recently, climate change (i.e., heat stress; Hoegh-Guldberg, 1999; Baker et al., 2008; Spalding and Brown, 2015; Hughes et al., 2017b) has emerged as the greatest threat to coral reefs, with temperatures of just 1°C above the long-term summer maximum for an area (reference period 1985–1993) over 4–6 weeks being enough to cause mass coral bleaching (loss of the symbionts) and mortality (very high confidence) (WGII AR5, Box 18-2; Cramer et al., 2014). Ocean warming and acidification can also slow growth and calcification, making corals less competitive compared to other benthic organisms such as macroalgae or seaweeds (Dove et al., 2013; Reyes-Nivia et al., 2013, 2014). As corals disappear, so do fish and many other reef-dependent species, which directly impacts industries such as tourism and fisheries, as well as the livelihoods for many, often disadvantaged, coastal people (Wilson et al., 2006; Graham, 2014; Graham et al., 2015; Cinner et al., 2016; Pendleton et al., 2016). These impacts are exacerbated by increasingly intense storms (Section 3.3.6), which physically destroy coral communities and hence reefs (Cheal et al., 2017), and by ocean acidification (Sections 3.3.10 and 3.4.4.5), which can weaken coral skeletons, contribute to disease, and slow the recovery of coral communities after mortality events (low to medium confidence) (Gardner et al., 2005; Dove et al., 2013; Kennedy et al., 2013; Webster et al., 2013; Hoegh-Guldberg, 2014b; Anthony, 2016). Ocean acidification also leads to enhanced activity by decalcifying organisms such as excavating sponges (Kline et al., 2012; Dove et al., 2013; Fang et al., 2013, 2014; Reyes-Nivia et al., 2013, 2014). The predictions of back-to-back bleaching events (Hoegh-Guldberg, 1999) have become the reality in the summers of 2016–2017 (e.g., Hughes et al., 2017b), as have projections of declining coral abundance (high confidence). Models have also become increasingly capable and are currently predicting the large-scale loss of coral reefs by mid-century under even low-emissions scenarios (Hoegh- Guldberg, 1999; Donner et al., 2005; Donner, 2009; van Hooidonk and Huber, 2012; Frieler et al., 2013; Hoegh-Guldberg et al., 3 2014; van Hooidonk et al., 2016). Even achieving emissions reduction targets consistent with the ambitious goal of 1.5°C of global warming under the Paris Agreement will result in the further loss of 70–90% of reef-building corals compared to today, with 99% of corals being lost under warming of 2°C or more above the pre-industrial period (Frieler et al., 2013; Hoegh-Guldberg, 2014b; Hoegh-Guldberg et al., 2014; Schleussner et al., 2016b; Hughes et al., 2017a). The assumptions underpinning these assessments are considered to be highly conservative. In some cases, ‘optimistic’ assumptions in models include rapid thermal adaptation by corals of 0.2°C–1°C per decade (Donner et al., 2005) or 0.4°C per decade (Schleussner et al., 2016b), as well as very rapid recovery rates from impacts (e.g., five years in the case of Schleussner et al., 2016b). Adaptation to climate change at these high rates, has not been documented, and recovery from mass mortality tends to take much longer (>15 years; Baker et al., 2008). Probability analysis also indicates that the underlying increases in sea temperatures that drive coral bleaching and mortality are 25% less likely under 1.5°C when compared to 2°C (King et al., 2017). Spatial differences between the rates of heating suggest the possibility of temporary climate refugia (Caldeira, 2013; van Hooidonk et al., 2013; Cacciapaglia and van Woesik, 2015; Keppel and Kavousi, 2015), which may play an important role in terms of the regeneration of coral reefs, especially if these refuges are protected from risks unrelated to climate change. Locations at higher latitudes are reporting the arrival of reef-building corals, which may be valuable in terms of the role of limited refugia and coral reef structures but will have low biodiversity (high confidence) when compared to present-day tropical reefs (Kersting et al., 2017). Similarly, deep-water (30–150 m) or mesophotic coral reefs (Bongaerts et al., 2010; Holstein et al., 2016) may play an important role because they avoid shallow water extremes (i.e., heat and storms) to some extent, although the ability of these ecosystems to assist in repopulating damaged shallow water areas may be limited (Bongaerts et al., 2017). Given the sensitivity of corals to heat stress, even short periods of overshoot (i.e., decades) are expected to be extremely damaging to coral reefs. Losing 70–90% of today’s coral reefs, however, will remove resources and increase poverty levels across the world’s tropical coastlines, highlighting the key issue of equity for the millions of people that depend on these valuable ecosystems (Cross-Chapter Box 6; Spalding et al., 2014; Halpern et al., 2015). Anticipating these challenges to food and livelihoods for coastal communities will become increasingly important, as will adaptation options, such as the diversification of livelihoods and the development of new sustainable industries, to reduce the dependency of coastal communities on threatened ecosystems such as coral reefs (Cinner et al., 2012, 2016; Pendleton et al., 2016). At the same time, coastal communities will need to pre-empt changes to other services provided by coral reefs such as coastal protection (Kennedy et al., 2013; Hoegh-Guldberg et al., 2014; Pörtner et al., 2014; Gattuso et al., 2015). Other threats and challenges to coastal living, such as sea level rise, will amplify challenges from declining coral reefs, specially for SIDS and low-lying tropical nations. Given the scale and cost of these interventions, implementing them earlier rather than later would be expedient. 230 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 3.4.5 Coastal and Low-Lying Areas, and Sea Level Rise level rise at 2°C compared with 1.5°C in 2100 (medium confidence). With a 1.5°C stabilization scenario in 2100, 62.7 million people per year Sea level rise (SLR) is accelerating in response to climate change are at risk from flooding, with this value increasing to 137.6 million (Section 3.3.9; Church et al., 2013) and will produce significant impacts people per year in 2300 (50th percentile, average across SSP1– 5, no (high confidence). In this section, impacts and projections of SLR are socio-economic change after 2100). These projections assume that no reported at global and city scales (Sections 3.4.5.1 and 3.4.5.2) and for upgrade to current protection levels occurs (Nicholls et al., 2018). The coastal systems (Sections 3.4.5.3 to 3.4.5.6). For some sectors, there number of people at risk increases by approximately 18% in 2030 if is a lack of precise evidence of change at 1.5°C and 2°C of global a 2°C scenario is used and by 266% in 2300 if an RCP8.5 scenario warming. Adaptation to SLR is discussed in Section 3.4.5.7. is considered (Nicholls et al., 2018). Through prescribed IPCC Special Report on Emissions Scenarios (SRES) SLR scenarios, Arnell et al. 3.4.5.1 Global / sub-global scale (2016) also found that the number of people exposed to flooding increased substantially at warming levels higher than 2°C, assuming Sea level rise (SLR) and other oceanic climate changes are already no adaptation beyond current protection levels. Additionally, impacts resulting in salinization, flooding, and erosion and in the future are increased in the second half of the 21st century. projected to affect human and ecological systems, including health, heritage, freshwater availability, biodiversity, agriculture, fisheries and Coastal flooding is projected to cost thousands of billions of USD other services, with different impacts seen worldwide (high confidence). annually, with damage costs under constant protection estimated Owing to the commitment to SLR, there is an overlapping uncertainty at 0.3–5.0% of global gross domestic product (GDP) in 2100 under in projections at 1.5°C and 2°C (Schleussner et al., 2016b; Sanderson an RCP2.6 scenario (Hinkel et al., 2014). Risks are projected to be et al., 2017; Goodwin et al., 2018; Mengel et al., 2018; Nicholls et al., highest in South and Southeast Asia, assuming there is no upgrade 2018; Rasmussen et al., 2018) and about 0.1 m difference in global to current protection levels, for all levels of climate warming (Arnell et mean sea level (GMSL) rise between 1.5°C and 2°C worlds in the year al., 2016; Brown et al., 2016). Countries with at least 50 million people 2100 (Section 3.3.9, Table 3.3). Exposure and impacts at 1.5°C and 2°C exposed to SLR (assuming no adaptation or protection at all) based on differ at different time horizons (Schleussner et al., 2016b; Brown et a 1,280 Pg C emissions scenario (approximately a 1.5°C temperature 3 al., 2018a, b; Nicholls et al., 2018; Rasmussen et al., 2018). However, rise above today’s level) include China, Bangladesh, Egypt, India, these are distinct from impacts associated with higher increases in Indonesia, Japan, Philippines, United States and Vietnam (Clark et al., temperature (e.g., 4°C or more, as discussed in Brown et al., 2018a) 2016). Rasmussen et al. (2018) and Brown et al. (2018a) project that over centennial scales. The benefits of climate change mitigation similar countries would have high exposure to SLR in the 21st century reinforce findings of earlier IPCC reports (e.g., Wong et al., 2014). using 1.5°C and 2°C scenarios. Thus, there is high confidence that SLR will have significant impacts worldwide in this century and beyond. Table 3.3 shows the land and people exposed to SLR (assuming there is no adaptation or protection at all) using the Dynamic Interactive 3.4.5.2 Cities Vulnerability Assessment (DIVA) model (extracted from Brown et al., 2018a and Goodwin et al., 2018; see also Supplementary Material Observations of the impacts of SLR in cities are difficult to record 3.SM, Table 3.SM.4). Thus, exposure increases even with temperature because multiple drivers of change are involved. There are observations stabilization. The exposed land area is projected to at least double by of ongoing and planned adaptation to SLR and extreme water levels 2300 using a RCP8.5 scenario compared with a mitigation scenario in some cities (Araos et al., 2016; Nicholls et al., 2018), whilst other (Brown et al., 2018a). In the 21st century, land area exposed to cities have yet to prepare for these impacts (high confidence) (see sea level rise (assuming there is no adaptation or protection at all) Section 3.4.8 and Cross-Chapter Box 9 in Chapter 4). There are limited is projected to be at least an order of magnitude larger than the observations and analyses of how cities will cope with higher and/or cumulative land loss due to submergence (which takes into account multi-centennial SLR, with the exception of Amsterdam, New York and defences) (Brown et al., 2016, 2018a) regardless of the SLR scenario London (Nicholls et al., 2018). applied. Slower rates of rise due to climate change mitigation may provide a greater opportunity for adaptation (medium confidence), Coastal urban areas are projected to see more extreme water levels which could substantially reduce impacts. due to rising sea levels, which may lead to increased flooding and damage of infrastructure from extreme events (unless adaptation is In agreement with the assessment in WGII AR5 Section 5.4.3.1 (Wong undertaken), plus salinization of groundwater. These impacts may be et al., 2014), climate change mitigation may reduce or delay coastal enhanced through localized subsidence (Wong et al., 2014), which exposure and impacts (very high confidence). Adaptation has the causes greater relative SLR. At least 136 megacities (port cities with potential to substantially reduce risk through a portfolio of available a population greater than 1 million in 2005) are at risk from flooding options (Sections 5.4.3.1 and 5.5 of Wong et al., 2014; Sections 6.4.2.3 due to SLR (with magnitudes of rise possible under 1.5°C or 2°C in the and 6.6 of Nicholls et al., 2007). At 1.5°C in 2100, 31–69 million people 21st century, as indicated in Section 3.3.9) unless further adaptation (2010 population values) worldwide are projected to be exposed to is undertaken (Hanson et al., 2011; Hallegatte et al., 2013). Many of flooding, assuming no adaptation or protection at all, compared these cities are located in South and Southeast Asia (Hallegatte et with 32–79 million people (2010 population values) at 2°C in 2100 al., 2013; Cazenave and Cozannet, 2014; Clark et al., 2016; Jevrejeva (Supplementary Material 3.SM, Table 3.SM.4; Rasmussen et al., 2018). et al., 2016). Jevrejeva et al. (2016) projected that more than 90% of As a result, up to 10.4 million more people would be exposed to sea global coastlines could experience SLR greater than 0.2 m with 2°C 231 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems of warming by 2040 (RCP8.5). However, for scenarios where 2°C is the impacts of SLR and wave-induced flooding (within a temperature stabilized or occurs later in time, this figure is likely to differ because horizon equivalent of 1.5°C), could affect freshwater availability on of the commitment to SLR. Raising existing dikes helps protect against Roi-Namur, Marshall Islands, but is also dependent on other extreme SLR, substantially reducing risks, although other forms of adaptation weather events. Freshwater resources may also be affected by exist. By 2300, dike heights under a non-mitigation scenario (RCP8.5) a 0.40 m rise in sea level (which may be experienced with a 1.5°C could be more than 2 m higher (on average for 136 megacities) than warming) in other Pacific atolls (Terry and Chui, 2012). Whilst SLR is under climate change mitigation scenarios at 1.5°C or 2°C (Nicholls a major hazard for atolls, islands reaching higher elevations are also et al., 2018). Thus, rising sea levels commit coastal cities to long-term threatened given that there is often a lot of infrastructure located near adaptation (high confidence). the coast (high confidence) (Kumar and Taylor, 2015; Nicholls et al., 2018). Tens of thousands of people on small islands are exposed to 3.4.5.3 Small islands SLR (Rasmussen et al., 2018). Giardino et al. (2018) found that hard defence structures on the island of Ebeye in the Marshall Islands were Qualitative physical observations of SLR (and other stresses) include effective in reducing damage due to SLR at 1.5°C and 2°C. Additionally, inundation of parts of low-lying islands, land degradation due to damage was also reduced under mitigation scenarios compared with saltwater intrusion in Kiribati and Tuvalu (Wairiu, 2017), and shoreline non-mitigation scenarios. In Jamaica and St Lucia, SLR and extreme change in French Polynesia (Yates et al., 2013), Tuvalu (Kench et al., sea levels are projected to threaten transport system infrastructure at 2015, 2018) and Hawaii (Romine et al., 2013). Observations, models 1.5°C unless further adaptation is undertaken (Monioudi et al., 2018). and other evidence indicate that unconstrained Pacific atolls have kept Slower rates of SLR will provide a greater opportunity for adaptation pace with SLR, with little reduction in size or net gain in land (Kench to be successful (medium confidence), but this may not be substantial et al., 2015, 2018; McLean and Kench, 2015; Beetham et al., 2017). enough on islands with a very low mean elevation. Migration and/or Whilst islands are highly vulnerable to SLR (high confidence), they are relocation may be an adaptation option (Section 3.4.10). Thomas and also reactive to change. Small islands are impacted by multiple climatic Benjamin (2017) highlight three areas of concern in the context of loss stressors, with SLR being a more important stressor to some islands and damage at 1.5°C: a lack of data, gaps in financial assessments, 3 than others (Sections 3.4.10, 4.3.5.6, 5.2.1, 5.5.3.3, Boxes 3.5, 4.3 and and a lack of targeted policies or mechanisms to address these issues 5.3). (Cross-Chapter Box 12 in Chapter 5). Small islands are projected to remain vulnerable to SLR (high confidence). Observed adaptation to multiple drivers of coastal change, including SLR, includes retreat (migration), accommodation and defence. 3.4.5.4 Deltas and estuaries Migration (internal and international) has always been important on small islands (Farbotko and Lazrus, 2012; Weir et al., 2017), with Observations of SLR and human influence are felt through salinization, changing environmental and weather conditions being just one factor in which leads to mixing in deltas and estuaries, aquifers, leading to the choice to migrate (Sections 3.4.10, 4.3.5.6 and 5.3.2; Campbell and flooding (also enhanced by precipitation and river discharge), land Warrick, 2014). Whilst flooding may result in migration or relocation, degradation and erosion. Salinization is projected to impact freshwater for example in Vunidogoloa, Fiji (McNamara and Des Combes, 2015; sources and pose risks to ecosystems and human systems (Section Gharbaoui and Blocher, 2016) and the Solomon Islands (Albert et al., 5.4; Wong et al., 2014). For instance, in the Delaware River estuary on 2017), in situ adaptation may be tried or preferred, for example stilted the east coast of the USA, upward trends of salinity (measured since housing or raised floors in Tubigon, Bohol, Philippines (Jamero et al., the 1900s), accounting for the effects of streamflow and seasonal 2017), raised roads and floors in Batasan and Ubay, Philippines (Jamero variations, have been detected and SLR is a potential cause (Ross et et al., 2018), and raised platforms for faluw in Leang, Federated States al., 2015). of Micronesia (Nunn et al., 2017). Protective features, such as seawalls or beach nourishment, are observed to locally reduce erosion and flood Z. Yang et al. (2015) found that future climate scenarios for the USA risk but can have other adverse implications (Sovacool, 2012; Mycoo, (A1B 1.6°C and B1 2°C in the 2040s) had a greater effect on salinity 2014, 2017; Nurse et al., 2014; AR5 Section 29.6.22). intrusion than future land-use/land-cover change in the Snohomish River estuary in Washington state (USA). This resulted in a shift in There is a lack of precise, quantitative studies of projected impacts the salinity both upstream and downstream in low flow conditions. of SLR at 1.5°C and 2°C. Small islands are projected to be at risk Projecting impacts in deltas needs an understanding of both fluvial and very sensitive to coastal climate change and other stressors discharge and SLR, making projections complex because the drivers (high confidence) (Nurse et al., 2014; Benjamin and Thomas, 2016; operate on different temporal and spatial scales (Zaman et al., 2017; Ourbak and Magnan, 2017; Brown et al., 2018a; Nicholls et al., 2018; Brown et al., 2018b). The mean annual flood depth when 1.5°C is first Rasmussen et al., 2018; AR5 Sections 29.3 and 29.4), such as oceanic projected to be reached in the Ganges-Brahmaputra delta may be less warming, SLR (resulting in salinization, flooding and erosion), cyclones than the most extreme annual flood depth seen today, taking into and mass coral bleaching and mortality (Section 3.4.4, Boxes 3.4 and account SLR, surges, tides, bathymetry and local river flows (Brown et 3.5). These impacts can have significant socio-economic and ecological al., 2018b). Further, increased river salinity and saline intrusion in the implications, such as on health, agriculture and water resources, which Ganges-Brahmaputra-Meghna is likely with 2°C of warming (Zaman in turn have impacts on livelihoods (Sovacool, 2012; Mycoo, 2014, et al., 2017). Salinization could impact agriculture and food security 2017; Nurse et al., 2014). Combinations of drivers causing adverse (Cross-Chapter Box 6 in this chapter). For 1.5°C or 2°C stabilization impacts are important. For example, Storlazzi et al. (2018) found that conditions in 2200 or 2300 plus surges, a minimum of 44% of the 232 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Bangladeshi Ganges-Brahmaputra, Indian Bengal, Indian Mahanadi change (Section 5.4.2.1 of Wong et al., 2014), which could affect land- and Ghanese Volta delta land area (without defences) would be based ecosystems. Global observations indicate no overall clear effect exposed unless sedimentation occurs (Brown et al., 2018b). Other of SLR on shoreline change (Le Cozannet et al., 2014), as it is highly deltas are similarly vulnerable. SLR is only one factor affecting deltas, site specific (e.g., Romine et al., 2013). Infrastructure and geological and assessment of numerous geophysical and anthropogenic drivers constraints reduce shoreline movement, causing coastal squeeze. In of geomorphic change is important (Tessler et al., 2018). For example, Japan, for example, SLR is projected to cause beach losses under an dike building to reduce flooding and dam building (Gupta et al., 2012) RCP2.6 scenario, which will worsen under RCP8.5 (Udo and Takeda, restricts sediment movement and deposition, leading to enhanced 2017). Further, compound flooding (the combined risk of flooding from subsidence, which can occur at a greater rate than SLR (Auerbach multiple sources) has increased significantly over the past century in et al., 2015; Takagi et al., 2016). Although dikes remain essential for major coastal cities (Wahl et al., 2015) and is likely to increase with reducing flood risk today, promoting sedimentation is an advisable further development and SLR at 1.5°C and 2°C unless adaptation is strategy (Brown et al., 2018b) which may involve nature-based undertaken. Thus, overall SLR will have a wide range of adverse effects solutions. Transformative decisions regarding the extent of sediment on coastal zones (medium confidence). restrictive infrastructure may need to be considered over centennial scales (Brown et al., 2018b). Thus, in a 1.5°C or 2°C warmer world, 3.4.5.7 Adapting to coastal change deltas, which are home to millions of people, are expected to be highly threatened from SLR and localized subsidence (high confidence). Adaptation to coastal change from SLR and other drivers is occurring today (high confidence) (see Cross-Chapter Box 9 in Chapter 3.4.5.5 Wetlands 4), including migration, ecosystem-based adaptation, raising infrastructure and defences, salt-tolerant food production, early Observations indicate that wetlands, such as saltmarshes and mangrove warning systems, insurance and education (Section 5.4.2.1 of Wong et forests, are disrupted by changing conditions (Sections 3.4.4.8; Wong et al., 2014). Climate change mitigation will reduce the rate of SLR this al., 2014; Lovelock et al., 2015), such as total water levels and sediment century, decreasing the need for extensive and, in places, immediate availability. For example, saltmarshes in Connecticut and New York, adaptation. Adaptation will reduce impacts in human settings (high 3 USA, measured from 1900 to 2012, have accreted with SLR but have confidence) (Hinkel et al., 2014; Wong et al., 2014), although there is lost marsh surface relative to tidal datums, leading to increased marsh less certainty for natural ecosystems (Sections 4.3.2 and 4.3.3.3). While flooding and further accretion (Hill and Anisfeld, 2015). This change some ecosystems (e.g., mangroves) may be able to move shoreward stimulated marsh carbon storage and aided climate change mitigation. as sea levels increase, coastal development (e.g., coastal building, seawalls and agriculture) often interrupt these transitions (Saunders et Salinization may lead to shifts in wetland communities and their al., 2014). Options for responding to these challenges include reducing ecosystem functions (Herbert et al., 2015). Some projections of wetland the impact of other stresses such as those arising from tourism, fishing, change, with magnitudes (but not necessarily rates or timing) of SLR coastal development and unsustainable aquaculture/agriculture. In analogous to 1.5°C and 2°C of global warming, indicate a net loss of some cases, restoration of coastal habitats and ecosystems can be a wetlands in the 21st century (e.g., Blankespoor et al., 2014; Cui et al., cost-effective way of responding to changes arising from increasing 2015; Arnell et al., 2016; Crosby et al., 2016), whilst others report a net levels of exposure from rising sea levels, changes in storm conditions, gain with wetland transgression (e.g., Raabe and Stumpf, 2016 in the coastal inundation and salinization (Arkema et al., 2013; Temmerman Gulf of Mexico). However, the feedback between wetlands and sea et al., 2013; Ferrario et al., 2014; Hinkel et al., 2014; Spalding et al., level is complex, with parameters such as a lack of accommodation 2014; Elliff and Silva, 2017). space restricting inland migration, or sediment supply and feedbacks between plant growth and geomorphology (Kirwan and Megonigal, Since AR5, planned and autonomous adaptation and forward planning 2013; Ellison, 2014; Martínez et al., 2014; Spencer et al., 2016) still have become more widespread (Araos et al., 2016; Nicholls et al., being explored. Reducing global warming from 2°C to 1.5°C will 2018), but continued efforts are required as many localities are in the deliver long-term benefits, with natural sedimentation rates more likely early stages of adapting or are not adapting at all (Cross-Chapter Box keep up with SLR. It remains unclear how wetlands will respond and 9 in Chapter 4; Araos et al., 2016). This is region and sub-sector specific, under what conditions (including other climate parameters) to a global and also linked to non-climatic factors (Ford et al., 2015; Araos et al., temperature rise of 1.5°C and 2°C. However, they have great potential 2016; Lesnikowski et al., 2016). Adaptation pathways (e.g., Ranger et to aid and benefit climate change mitigation and adaptation (medium al., 2013; Barnett et al., 2014; Rosenzweig and Solecki, 2014; Buurman confidence) (Sections 4.3.2.2 and 4.3.2.3). and Babovic, 2016) assist long-term planning but are not widespread practices despite knowledge of long-term risks (Section 4.2.2). 3.4.5.6 Other coastal settings Furthermore, human retreat and migration are increasingly being considered as an adaptation response (Hauer et al., 2016; Geisler and Numerous impacts have not been quantified at 1.5°C or 2°C but remain Currens, 2017), with a growing emphasis on green adaptation. There important. This includes systems identified in WGII AR5 (AR5 – Section are few studies on the adaptation limits to SLR where transformation 5.4 of Wong et al., 2014), such as beaches, barriers, sand dunes, rocky change may be required (AR5-Section 5.5 of Wong et al., 2014; Nicholls coasts, aquifers, lagoons and coastal ecosystems (for the last system, et al., 2015). Sea level rise poses a long-term threat (Section 3.3.9), and see Section 3.4.4.12). For example, SLR potentially affects erosion and adaptation will remain essential at the centennial scale under 1.5°C accretion, and therefore sediment movement, instigating shoreline and 2°C of warming (high confidence). 233 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Table 3.3 | Land and people exposed to sea level rise (SLR), assuming no protection at all. Extracted from Brown et al. (2018a) and Goodwin et al. (2018). SSP: Shared Socio- Economic Pathway; wrt: with respect to; *:Population held constant at 2100 level. Impact factor, assuming there is Year Climate scenario no adaptation or protection at all (50th, [5th-95th percentiles]) 2050 2100 2200 2300 1.5°C Temperature rise wrt 1850–1900 (°C) 1.71 (1.44–2.16) 1.60 (1.26–2.33) 1.41 (1.15–2.10) 1.32 (1.12–1.81) SLR (m) wrt 1986–2005 0.20 (0.14–0.29) 0.40 (0.26–0.62) 0.73 (0.47–1.25) 1.00 (0.59–1.55) Land exposed (x103 km2) 574 [558–597] 620 [575–669] 666 [595–772] 702 [666–853] People exposed, SSP1–5 (millions) 127.9–139.0 102.7–153.5 133.8–207.1 [123.4–134.0, [94.8–140.7, -- [112.3–169.6, 134.5–146.4] 102.7–153.5] 165.2–263.4]* 2°C Temperature rise wrt 1850–1900 (° C) 1.76 (1.51–2.16) 2.03 (1.72–2.64) 1.90 (1.66–2.57) 1.80 (1.60–2.20) SLR (m) wrt 1986-2005 0.20 (0.14–0.29) 0.46 (0.30–0.69) 0.90 (0.58–1.50) 1.26 (0.74–1.90) Land exposed (x103 km2) 575 [558–598] 637 [585–686] 705 [618–827] 767 [642–937] People exposed, SSP1–5 (millions) 128.1–139.2 105.5–158.1 148.3–233.0 [123.6–134.2, [97.0–144.1, -- [120.3–183.4, 134.7–146.6] 118.1–179.0] 186.4–301.8]* Box 3.5 | Small Island Developing States (SIDS) 3 Global warming of 1.5°C is expected to prove challenging for small island developing states (SIDS) that are already experiencing impacts associated with climate change (high confidence). At 1.5°C, compounding impacts from interactions between climate drivers may contribute to the loss of, or change in, critical natural and human systems (medium to high confidence). There are a number of reduced risks at 1.5°C versus 2°C, particularly when coupled with adaptation efforts (medium to high confidence). Changing climate hazards for SIDS at 1.5°C Mean surface temperature is projected to increase in SIDS at 1.5°C of global warming (high confidence). The Caribbean region will experience 0.5°C–1.5°C of warming compared to a 1971–2000 baseline, with the strongest warming occurring over larger land masses (Taylor et al., 2018). Under the Representative Concentration Pathway (RCP)2.6 scenario, the western tropical Pacific is projected to experience warming of 0.5°C–1.7°C relative to 1961–1990. Extreme temperatures will also increase, with potential for elevated impacts as a result of comparably small natural variability (Reyer et al., 2017a). Compared to the 1971–2000 baseline, up to 50% of the year is projected to be under warm spell conditions in the Caribbean at 1.5°C, with a further increase of up to 70 days at 2°C (Taylor et al., 2018). Changes in precipitation patterns, freshwater availability and drought sensitivity differ among small island regions (medium to high confidence). Some western Pacific islands and those in the northern Indian Ocean may see increased freshwater availability, while islands in most other regions are projected to see a substantial decline (Holding et al., 2016; Karnauskas et al., 2016). For several SIDS, approximately 25% of the overall freshwater stress projected under 2°C at 2030 could be avoided by limiting global warming to 1.5°C (Karnauskas et al., 2018). In accordance with an overall drying trend, an increasing drought risk is projected for Caribbean SIDS (Lehner et al., 2017), and moderate to extreme drought conditions are projected to be about 9% longer on average at 2°C versus 1.5°C for islands in this region (Taylor et al., 2018). Projected changes in the ocean system at higher warming targets (Section 3.4.4), including potential changes in circulation (Section 3.3.7) and increases in both surface temperatures (Section 3.3.7) and ocean acidification (Section 3.3.10), suggest increasing risks for SIDS associated with warming levels close to and exceeding 1.5°C. Differences in global sea level between 1.5°C and 2°C depend on the time scale considered and are projected to fully materialize only after 2100 (Section 3.3.9). Projected changes in regional sea level are similarly time dependent, but generally found to be above the global average for tropical regions including small islands (Kopp et al., 2014; Jevrejeva et al., 2016). Threats related to sea level rise (SLR) for SIDS, for example from salinization, flooding, permanent inundation, erosion and pressure on ecosystems, will therefore persist well beyond the 21st century even under 1.5°C of warming (Section 3.4.5.3; Nicholls et al., 2018). Prolonged interannual sea level inundations may increase throughout the tropical Pacific with ongoing warming and in the advent of an 234 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Box 3.5 (continued) increased frequency of extreme La Niña events, exacerbating coastal impacts of projected global mean SLR (Widlansky et al., 2015). Changes to the frequency of extreme El Niño and La Niña events may also increase the frequency of droughts and floods in South Pacific islands (Box 4.2, Section 3.5.2; Cai et al., 2012). Extreme precipitation in small island regions is often linked to tropical storms and contributes to the climate hazard (Khouakhi et al., 2017). Similarly, extreme sea levels for small islands, particularly in the Caribbean, are linked to tropical cyclone occurrence (Khouakhi and Villarini, 2017). Under a 1.5°C stabilization scenario, there is a projected decrease in the frequency of weaker tropical storms and an increase in the number of intense cyclones (Section 3.3.6; Wehner et al., 2018a). There are not enough studies to assess differences in tropical cyclone statistics for 1.5°C versus 2°C (Section 3.3.6). There are considerable differences in the adaptation responses to tropical cyclones across SIDS (Cross-Chapter Box 11 in Chapter 4). Impacts on key natural and human systems Projected increases in aridity and decreases in freshwater availability at 1.5°C of warming, along with additional risks from SLR and increased wave-induced run-up, might leave several atoll islands uninhabitable (Storlazzi et al., 2015; Gosling and Arnell, 2016). Changes in the availability and quality of freshwater, linked to a combination of changes to climate drivers, may adversely impact SIDS’ economies (White and Falkland, 2010; Terry and Chui, 2012; Holding and Allen, 2015; Donk et al., 2018). Growth-rate projections based on temperature impacts alone indicate robust negative impacts on gross domestic product (GDP) per capita growth for SIDS (Sections 3.4.7.1, 3.4.9.1 and 3.5.4.9; Pretis et al., 2018). These impacts would be reduced considerably under 1.5°C but may be increased by escalating risks from climate-related extreme weather events and SLR (Sections 3.4.5.3, 3.4.9.4 and 3.5.3) Marine systems and associated livelihoods in SIDS face higher risks at 2°C compared to 1.5°C (medium to high confidence). 3 Mass coral bleaching and mortality are projected to increase because of interactions between rising ocean temperatures, ocean acidification, and destructive waves from intensifying storms (Section 3.4.4 and 5.2.3, Box 3.4). At 1.5°C, approximately 70–90% of global coral reefs are projected to be at risk of long-term degradation due to coral bleaching, with these values increasing to 99% at 2°C (Frieler et al., 2013; Schleussner et al., 2016b). Higher temperatures are also related to an increase in coral disease development, leading to coral degradation (Maynard et al., 2015). For marine fisheries, limiting warming to 1.5°C decreases the risk of species extinction and declines in maximum catch potential, particularly for small islands in tropical oceans (Cheung et al., 2016a). Long-term risks of coastal flooding and impacts on populations, infrastructure and assets are projected to increase with higher levels of warming (high confidence). Tropical regions including small islands are expected to experience the largest increases in coastal flooding frequency, with the frequency of extreme water-level events in small islands projected to double by 2050 (Vitousek et al., 2017). Wave-driven coastal flooding risks for reef-lined islands may increase as a result of coral reef degradation and SLR (Quataert et al., 2015). Exposure to coastal hazards is particularly high for SIDS, with a significant share of population, infrastructure and assets at risk (Sections 3.4.5.3 and 3.4.9; Scott et al., 2012; Kumar and Taylor, 2015; Rhiney, 2015; Byers et al., 2018). Limiting warming to 1.5°C instead of 2°C would spare the inundation of lands currently home to 60,000 individuals in SIDS by 2150 (Rasmussen et al., 2018). However, such estimates do not consider shoreline response (Section 3.4.5) or adaptation. Risks of impacts across sectors are projected to be higher at 1.5°C compared to the present, and will further increase at 2°C (medium to high confidence). Projections indicate that at 1.5°C there will be increased incidents of internal migration and displacement (Sections 3.5.5, 4.3.6 and 5.2.2; Albert et al., 2017), limited capacity to assess loss and damage (Thomas and Benjamin, 2017) and substantial increases in the risk to critical transportation infrastructure from marine inundation (Monioudi et al., 2018). The difference between 1.5°C and 2°C might exceed limits for normal thermoregulation of livestock animals and result in persistent heat stress for livestock animals in SIDS (Lallo et al., 2018). At 1.5°C, limits to adaptation will be reached for several key impacts in SIDS, resulting in residual impacts, as well as loss and damage (Section 1.1.1, Cross-Chapter Box 12 in Chapter 5). Limiting temperature increase to 1.5°C versus 2°C is expected to reduce a number of risks, particularly when coupled with adaptation efforts that take into account sustainable development (Section 3.4.2 and 5.6.3.1, Box 4.3 and 5.3, Mycoo, 2017; Thomas and Benjamin, 2017). Region-specific pathways for SIDS exist to address climate change (Section 5.6.3.1, Boxes 4.6 and 5.3, Cross-Chapter Box 11 in Chapter 4). 235 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems 3.4.6 Food, Nutrition Security and Food Production drought conditions (De Souza et al., 2015). Elevated CO2 concentrations Systems (Including Fisheries and Aquaculture) of 568–590 ppm (a range that corresponds approximately to RCP6 in the 2080s and hence a warming of 2.3°C–3.3°C (van Vuuren et al., 3.4.6.1 Crop production 2011a, AR5 WGI Table 12.2 ) alone reduced the protein, micronutrient and B vitamin content of the 18 rice cultivars grown most widely in Quantifying the observed impacts of climate change on food security Southeast Asia, where it is a staple food source, by an amount sufficient and food production systems requires assumptions about the many to create nutrition-related health risks for 600 million people (Zhu et non-climate variables that interact with climate change variables. al., 2018). Overall, the effects of increased CO2 concentrations alone Implementing specific strategies can partly or greatly alleviate the during the 21st century are therefore expected to have a negative climate change impacts on these systems (Wei et al., 2017), whilst the impact on global food security (medium confidence). degree of compensation is mainly dependent on the geographical area and crop type (Rose et al., 2016). Despite these uncertainties, recent Crop yields in the future will also be affected by projected changes in studies confirm that observed climate change has already affected crop temperature and precipitation. Studies of major cereals showed that suitability in many areas, resulting in changes in the production levels maize and wheat yields begin to decline with 1°C–2°C of local warming of the main agricultural crops. These impacts are evident in many areas and under nitrogen stress conditions at low latitudes (high confidence) of the world, ranging from Asia (C. Chen et al., 2014; Sun et al., 2015; (Porter et al., 2014; Rosenzweig et al., 2014). A few studies since AR5 He and Zhou, 2016) to America (Cho and McCarl, 2017) and Europe have focused on the impacts on cropping systems for scenarios where (Ramirez-Cabral et al., 2016), and they particularly affect the typical the global mean temperature increase is within 1.5°C. Schleussner et local crops cultivated in specific climate conditions (e.g., Mediterranean al. (2016b) projected that constraining warming to 1.5°C rather than crops like olive and grapevine, Moriondo et al., 2013a, b). 2°C would avoid significant risks of declining tropical crop yield in West Africa, Southeast Asia, and Central and South America. Ricke et al. Temperature and precipitation trends have reduced crop production (2016) highlighted that cropland stability declines rapidly between 1°C and yields, with the most negative impacts being on wheat and maize and 3°C of warming, whilst Bassu et al. (2014) found that an increase 3 (Lobell et al., 2011), whilst the effects on rice and soybean yields are in air temperature negatively influences the modelled maize yield less clear and may be positive or negative (Kim et al., 2013; van Oort response by –0.5 t ha−1 °C–1 and Challinor et al. (2014) reported similar and Zwart, 2018). Warming has resulted in positive effects on crop yield effect for tropical regions. Niang et al. (2014) projected significantly in some high-latitude areas (Jaggard et al., 2007; Supit et al., 2010; lower risks to crop productivity in Africa at 1.5°C compared to 2°C of Gregory and Marshall, 2012; C. Chen et al., 2014; Sun et al., 2015; He warming. Lana et al. (2017) indicated that the impact of temperature and Zhou, 2016; Daliakopoulos et al., 2017), and may make it possible increases on crop failure of maize hybrids would be much greater as to have more than one harvest per year (B. Chen et al., 2014; Sun et temperatures increase by 2°C compared to 1.5°C (high confidence). J. al., 2015). Climate variability has been found to explain more than Huang et al. (2017) found that limiting warming to 1.5°C compared 60% of the of maize, rice, wheat and soybean yield variations in the to 2°C would reduce maize yield losses over drylands. Although main global breadbaskets areas (Ray et al., 2015), with the percentage Rosenzweig et al. (2017, 2018) did not find a clear distinction between varying according to crop type and scale (Moore and Lobell, 2015; Kent yield declines or increases in some breadbasket regions between the et al., 2017). Climate trends also explain changes in the length of the two temperature levels, they generally did find projections of decreasing growing season, with greater modifications found in the northern high- yields in breadbasket regions when the effects of CO2 fertilization were latitude areas (Qian et al., 2010; Mueller et al., 2015). excluded. Iizumi et al. (2017) found smaller reductions in maize and soybean yields at 1.5°C than at 2°C of projected warming, higher rice The rise in tropospheric ozone has already reduced yields of wheat, production at 2°C than at 1.5°C, and no clear differences for wheat rice, maize and soybean by 3–16% globally (Van Dingenen et al., on a global mean basis. These results are largely consistent with those 2009). In some studies, increases in atmospheric CO2 concentrations of other studies (Faye et al., 2018; Ruane et al., 2018). In the western were found to increase yields by enhancing radiation and water use Sahel and southern Africa, moving from 1.5°C to 2°C of warming has efficiencies (Elliott et al., 2014; Durand et al., 2018). In open-top been projected to result in a further reduction of the suitability of maize, chamber experiments with a combination of elevated CO2 and 1.5°C of sorghum and cocoa cropping areas and yield losses, especially for C3 warming, maize and potato yields were observed to increase by 45.7% crops, with rainfall change only partially compensating these impacts and 11%, respectively (Singh et al., 2013; Abebe et al., 2016). However, (Läderach et al., 2013; World Bank, 2013; Sultan and Gaetani, 2016). observations of trends in actual crop yields indicate that reductions as a result of climate change remain more common than crop yield A significant reduction has been projected for the global production of increases, despite increased atmospheric CO2 concentrations (Porter wheat (by 6.0 ± 2.9%), rice (by 3.2 ± 3.7%), maize (by 7.4 ± 4.5%), et al., 2014). For instance, McGrath and Lobell (2013) indicated that and soybean, (by 3.1%) for each degree Celsius increase in global production stimulation at increased atmospheric CO2 concentrations mean temperature (Asseng et al., 2015; C. Zhao et al., 2017). Similarly, was mostly driven by differences in climate and crop species, whilst Li et al. (2017) indicated a significant reduction in rice yields for each yield variability due to elevated CO2 was only about 50–70% of the degree Celsius increase, by about 10.3%, in the greater Mekong variability due to climate. Importantly, the faster growth rates induced subregion (medium confidence; Cross-Chapter Box 6: Food Security by elevated CO2 have been found to coincide with lower protein content in this chapter). Large rice and maize yield losses are to be expected in several important C3 cereal grains (Myers et al., 2014), although this in China, owing to climate extremes (medium confidence) (Wei et al., may not always be the case for C4 grains, such as sorghum, under 2017; Zhang et al., 2017). 236 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 While not often considered, crop production is also negatively affected (medium confidence) (Palmer et al., 2008). Elevated temperatures are by the increase in both direct and indirect climate extremes. Direct also expected to increase methane production (Knapp et al., 2014; M.A. extremes include changes in rainfall extremes (Rosenzweig et al., Lee et al., 2017). Globally, a decline in livestock of 7–10% is expected at 2014), increases in hot nights (Welch et al., 2010; Okada et al., 2011), about 2°C of warming, with associated economic losses between $9.7 extremely high daytime temperatures (Schlenker and Roberts, 2009; and $12.6 billion (Boone et al., 2018). Jiao et al., 2016; Lesk et al., 2016), drought (Jiao et al., 2016; Lesk et al., 2016), heat stress (Deryng et al., 2014, Betts et al., 2018), flooding 3.4.6.3 Fisheries and aquaculture production (Betts et al., 2018; Byers et al., 2018), and chilling damage (Jiao et al., 2016), while indirect effects include the spread of pests and diseases Global fisheries and aquaculture contribute a total of 88.6 and 59.8 (Jiao et al., 2014; van Bruggen et al., 2015), which can also have million tonnes of fish and other products annually (FAO, 2016), detrimental effects on cropping systems. and play important roles in the food security of a large number of countries (McClanahan et al., 2015; Pauly and Charles, 2015) as well Taken together, the findings of studies on the effects of changes in as being essential for meeting the protein demand of a growing temperature, precipitation, CO2 concentration and extreme weather global population (Cinner et al., 2012, 2016; FAO, 2016; Pendleton events indicate that a global warming of 2°C is projected to result in a et al., 2016). A steady increase in the risks associated with bivalve greater reduction in global crop yields and global nutrition than global fisheries and aquaculture at mid-latitudes is coincident with increases warming of 1.5°C (high confidence; Section 3.6). in temperature, ocean acidification, introduced species, disease and other drivers ( Lacoue-Labarthe et al., 2016; Clements and Chopin, 3.4.6.2 Livestock production 2017; Clements et al., 2017; Parker et al., 2017). Sea level rise and storm intensification pose a risk to hatcheries and other infrastructure Studies of climate change impacts on livestock production are few in (Callaway et al., 2012; Weatherdon et al., 2016), whilst others risks number. Climate change is expected to directly affect yield quantity and are associated with the invasion of parasites and pathogens (Asplund quality (Notenbaert et al., 2017), as well as indirectly impacting the et al., 2014; Castillo et al., 2017). Specific human strategies have livestock sector through feed quality changes and spread of pests and reduced these risks, which are expected to be moderate under RCP2.6 3 diseases (Kipling et al., 2016) (high confidence). Increased warming and and very high under RCP8.5 (Gattuso et al., 2015). The risks related its extremes are expected to cause changes in physiological processes to climate change for fin fish (Section 3.4.4) are producing a number in livestock (i.e., thermal distress, sweating and high respiratory rates) of challenges for small-scale fisheries (e.g., Kittinger, 2013; Pauly and (Mortola and Frappell, 2000) and to have detrimental effects on animal Charles, 2015; Bell et al., 2018). Recent literature from 2015 to 2017 feeding, growth rates (André et al., 2011; Renaudeau et al., 2011; Collier has described growing threats from rapid shifts in the biogeography and Gebremedhin, 2015) and reproduction (De Rensis et al., 2015). Wall of key species (Poloczanska et al., 2013, 2016; Burrows et al., 2014; et al. (2010) observed reduced milk yields and increased cow mortality García Molinos et al., 2015) and the ongoing rapid degradation of as the result of heat stress on dairy cow production over some UK key ecosystems such as coral reefs, seagrass and mangroves (Section regions. 3.4.4, Box 3.4). The acceleration of these changes, coupled with non- climate stresses (e.g., pollution, overfishing and unsustainable coastal Further, a reduction in water supply might increase cattle water demand development), are driving many small-scale fisheries well below the (Masike and Urich, 2008). Generally, heat stress can be responsible sustainable harvesting levels required to maintain these resources for domestic animal mortality increase and economic losses (Vitali et as a source of food (McClanahan et al., 2009, 2015; Cheung et al., al., 2009), affecting a wide range of reproductive parameters (e.g., 2010; Pendleton et al., 2016). As a result, future scenarios surrounding embryonic development and reproductive efficiency in pigs, Barati et al., climate change and global population growth increasingly project 2008; ovarian follicle development and ovulation in horses, Mortensen shortages of fish protein for many regions, such as the Pacific Ocean et al., 2009). Much attention has also been dedicated to ruminant (Bell et al., 2013, 2018) and Indian Ocean (McClanahan et al., 2015). diseases (e.g., liver fluke, Fox et al., 2011; blue-tongue virus, Guis et al., Mitigation of these risks involves marine spatial planning, fisheries 2012; foot-and-mouth disease (FMD), Brito et al. (2017); and zoonotic repair, sustainable aquaculture, and the development of alternative diseases, Njeru et al., 2016; Simulundu et al., 2017). livelihoods (Kittinger, 2013; McClanahan et al., 2015; Song and Chuenpagdee, 2015; Weatherdon et al., 2016). Other threats concern Climate change impacts on livestock are expected to increase. In the increasing incidence of alien species and diseases (Kittinger et al., temperate climates, warming is expected to lengthen the forage 2013; Weatherdon et al., 2016). growing season but decrease forage quality, with important variations due to rainfall changes (Craine et al., 2010; Hatfield et al., 2011; Risks of impacts related to climate change on low-latitude small-scale Izaurralde et al., 2011). Similarly, a decrease in forage quality is expected fin fisheries are moderate today but are expected to reach very high for both natural grassland in France (Graux et al., 2013) and sown levels by 1.1°C of global warming. Projections for mid- to high-latitude pastures in Australia (Perring et al., 2010). Water resource availability fisheries include increases in fishery productivity in some cases (Cheung for livestock is expected to decrease owing to increased runoff and et al., 2013; Hollowed et al., 2013; Lam et al., 2014; FAO, 2016). These reduced groundwater resources. Increased temperature will likely projections are associated with the biogeographical shift of species induce changes in river discharge and the amount of water in basins, towards higher latitudes (Fossheim et al., 2015), which brings benefits leading human and livestock populations to experience water stress, as well as challenges (e.g., increased production yet a greater risk of especially in the driest areas (i.e., sub-Saharan Africa and South Asia) disease and invasive species; low confidence). Factors underpinning 237 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems the expansion of fisheries production to high-latitude locations include fisheries are undergoing major transformations, and while production warming, increased light levels and mixing due to retreating sea ice is increasing, present-day risk is moderate and is projected to remain (Cheung et al., 2009), which result in substantial increases in primary moderate at 1.5°C and 2°C (Figure 3.18). productivity and fish harvesting in the North Pacific and North Atlantic (Hollowed and Sundby, 2014). Adaptation measures can be applied to shellfish, large pelagic fish resources and biodiversity, and they include options such as protecting Present-day risks for mid-latitude bivalve fisheries and aquaculture reproductive stages and brood stocks from periods of high ocean become undetectible up to 1.1°C of global warming, moderate at acidification (OA), stock selection for high tolerance to OA (high 1.3°C, and moderate to high up to 1.9°C (Figure 3.18). For instance, confidence) (Ekstrom et al., 2015; Rodrigues et al., 2015; Handisyde Cheung et al. (2016a), simulating the loss in fishery productivity et al., 2016; Lee, 2016; Weatherdon et al., 2016; Clements and Chopin, at 1.5°C, 2°C and 3.5°C above the pre-industrial period, found that 2017), redistribution of highly migratory resources (e.g., Pacific tuna) the potential global catch for marine fisheries will likely decrease by (high confidence), governance instruments such as international more than three million metric tonnes for each degree of warming. fisheries agreements (Lehodey et al., 2015; Matear et al., 2015), Low-latitude fin-fish fisheries have higher risks of impacts, with risks protection and regeneration of reef habitats, reduction of coral reef being moderate under present-day conditions and becoming high stresses, and development of alternative livelihoods (e.g., aquaculture; above 0.9°C and very high at 2°C of global warming. High-latitude Bell et al., 2013, 2018). Cross-Chapter Box 6 | Food Security Lead Authors: Ove Hoegh-Guldberg (Australia), Sharina Abdul Halim (Malaysia), Marco Bindi (Italy), Marcos Buckeridge (Brazil), Arona Diedhiou (Ivory 3 Coast/Senegal), Kristie L. Ebi (USA), Deborah Ley (Guatemala/Mexico), Diana Liverman (USA), Chandni Singh (India), Rachel Warren (UK), Guangsheng Zhou (China). Contributing Author: Lorenzo Brilli (Italy) Climate change influences food and nutritional security through its effects on food availability, quality, access and distribution (Paterson and Lima, 2010; Thornton et al., 2014; FAO, 2016). More than 815 million people were undernourished in 2016, and 11% of the world’s population has experienced recent decreases in food security, with higher percentages in Africa (20%), southern Asia (14.4%) and the Caribbean (17.7%) (FAO et al., 2017). Overall, food security is expected to be reduced at 2°C of global warming compared to 1.5°C, owing to projected impacts of climate change and extreme weather on yields, crop nutrient content, livestock, fisheries and aquaculture and land use (cover type and management) (Sections 3.4.3.6, 3.4.4.12 and 3.4.6), (high confidence). The effects of climate change on crop yield, cultivation area, presence of pests, food price and supplies are projected to have major implications for sustainable development, poverty eradication, inequality and the ability of the international community to meet the United Nations sustainable development goals (SDGs; Cross-Chapter Box 4 in Chapter 1). Goal 2 of the SDGs is to end hunger, achieve food security, improve nutrition and promote sustainable agriculture by 2030. This goal builds on the first millennium development goal (MDG-1) which focused on eradicating extreme poverty and hunger, through efforts that reduced the proportion of undernourished people in low- and middle-income countries from 23.3% in 1990 to 12.9% in 2015. Climate change threatens the capacity to achieve SDG 2 and could reverse the progress made already. Food security and agriculture are also critical to other aspects of sustainable development, including poverty eradication (SDG 1), health and well-being (SDG 3), clean water (SDG 6), decent work (SDG 8), and the protection of ecosystems on land (SDG 14) and in water (SDG 15) (UN, 2015, 2017; Pérez-Escamilla, 2017). Increasing global temperature poses large risks to food security globally and regionally, especially in low-latitude areas (medium confidence) (Cheung et al., 2010; Rosenzweig et al., 2013; Porter et al., 2014; Rosenzweig and Hillel, 2015; Lam et al., 2016), with warming of 2°C projected to result in a greater reduction in global crop yields and global nutrition than warming of 1.5°C (high confidence) (Section 3.4.6), owing to the combined effects of changes in temperature, precipitation and extreme weather events, as well as increasing CO2 concentrations. Climate change can exacerbate malnutrition by reducing nutrient availability and the quality of food products (medium confidence) (Cramer et al., 2014; Zhu et al., 2018). Generally, vulnerability to decreases in water and food availability is projected to be reduced at 1.5°C versus 2°C (Cheung et al., 2016a; Betts et al., 2018), especially in regions such as the African Sahel, the Mediterranean, central Europe, the Amazon, and western and southern Africa (medium confidence) (Sultan and Gaetani, 2016; Lehner et al., 2017; Betts et al., 2018; Byers et al., 2018; Rosenzweig et al., 2018). 238 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Cross-Chapter Box 6 (continued) Rosenzweig et al. (2018) and Ruane et al. (2018) reported that the higher CO2 concentrations associated with 2°C as compared to those at 1.5°C of global warming are projected to drive positive effects in some regions. Production can also benefit from warming in higher latitudes, with more fertile soils, favouring crops, and grassland production, in contrast to the situation at low latitudes (Section 3.4.6), and similar benefits could arise for high-latitude fisheries production (high confidence) (Section 3.4.6.3). Studies exploring regional climate change risks on crop production are strongly influenced by the use of different regional climate change projections and by the assumed strength of CO2 fertilization effects (Section 3.6), which are uncertain. For C3 crops, theoretically advantageous CO2 fertilization effects may not be realized in the field; further, they are often accompanied by losses in protein and nutrient content of crops (Section 3.6), and hence these projected benefits may not be realized. In addition, some micronutrients such as iron and zinc will accumulate less and be less available in food (Myers et al., 2014). Together, the impacts on protein availability may bring as many as 150 million people into protein deficiency by 2050 (Medek et al., 2017). However, short-term benefits could arise for high-latitude fisheries production as waters warm, sea ice contracts and primary productivity increases under climate change (high confidence) (Section 3.4.6.3; Cheung et al., 2010; Hollowed and Sundby, 2014; Lam et al., 2016; Sundby et al., 2016; Weatherdon et al., 2016). Factors affecting the projections of food security include variability in regional climate projections, climate change mitigation (where land use is involved; see Section 3.6 and Cross-Chapter Box 7 in this chapter) and biological responses (medium confidence) (Section 3.4.6.1; McGrath and Lobell, 2013; Elliott et al., 2014; Pörtner et al., 2014; Durand et al., 2018), extreme events such as droughts and floods (high confidence) (Sections 3.4.6.1, 3.4.6.2; Rosenzweig et al., 2014; Wei et al., 2017), financial volatility (Kannan et al., 2000; Ghosh, 2010; Naylor and Falcon, 2010; HLPE, 2011), and the distributions of pests and disease (Jiao et al., 2014; van Bruggen et al., 2015). Changes in temperature and precipitation are projected to increase global food prices by 3–84% by 2050 (IPCC, 2013). Differences in price impacts of climate change are accompanied by differences in land-use change (Nelson et al., 2014b), energy policies and food trade (Mueller et al., 2011; Wright, 2011; Roberts and Schlenker, 2013). Fisheries and aquatic production systems (aquaculture) face similar challenges to those of crop and livestock sectors (Section 3.4.6.3; Asiedu et al., 2017a, b; Utete et al., 2018). Human 3 influences on food security include demography, patterns of food waste, diet shifts, incomes and prices, storage, health status, trade patterns, conflict, and access to land and governmental or other assistance (Chapters 4 and 5). Across all these systems, the efficiency of adaptation strategies is uncertain because it is strongly linked with future economic and trade environments and their response to changing food availability (medium confidence) (Lobell et al., 2011; von Lampe et al., 2014; d’Amour et al., 2016; Wei et al., 2017). Climate change impacts on food security can be reduced through adaptation (Hasegawa et al., 2014). While climate change is projected to decrease agricultural yield, the consequences could be reduced substantially at 1.5°C versus 2°C with appropriate investment (high confidence) (Neumann et al., 2010; Muller, 2011; Roudier et al., 2011), awareness-raising to help inform farmers of new technologies for maintaining yield, and strong adaptation strategies and policies that develop sustainable agricultural choices (Sections 4.3.2 and 4.5.3). In this regard, initiatives such as ‘climate-smart’ food production and distribution systems may assist via technologies and adaptation strategies for food systems (Lipper et al., 2014; Martinez-Baron et al., 2018; Whitfield et al., 2018), as well as helping meet mitigation goals (Harvey et al., 2014). K.R. Smith et al. (2014) concluded that climate change will exacerbate current levels of childhood undernutrition and stunting through reduced food availability. As well, climate change can drive undernutrition-related childhood mortality, and increase disability-adjusted life years lost, with the largest risks in Asia and Africa (Supplementary Material 3.SM, Table 3.SM.12; Ishida et al., 2014; Hasegawa et al., 2016; Springmann et al., 2016). Studies comparing the health risks associated with reduced food security at 1.5°C and 2°C concluded that risks would be higher and the globally undernourished population larger at 2°C (Hales et al., 2014; Ishida et al., 2014; Hasegawa et al., 2016). Climate change impacts on dietary and weight-related risk factors are projected to increase mortality, owing to global reductions in food availability and consumption of fruit, vegetables and red meat (Springmann et al., 2016). Further, temperature increases are projected to reduce the protein and micronutrient content of major cereal crops, which is expected to further affect food and nutritional security (Myers et al., 2017; Zhu et al., 2018). Strategies for improving food security often do so in complex settings such as the Mekong River basin in Southeast Asia. The Mekong is a major food bowl (Smajgl et al., 2015) but is also a climate change hotspot (de Sherbinin, 2014; Lebel et al., 2014). This area is also a useful illustration of the complexity of adaptation choices and actions in a 1.5°C warmer world. Climate projections include increased annual average temperatures and precipitation in the Mekong (Zhang et al., 2017), as well as increased flooding and related disaster risks (T.F. Smith et al., 2013; Ling et al., 2015; Zhang et al., 2016). Sea level rise and saline intrusion are ongoing risks to agricultural systems in this area by reducing soil fertility and limiting the crop productivity (Renaud et al., 2015). The main climate impacts in the Mekong are expected to be on ecosystem health, through salinity intrusion, biomass reduction and biodiversity losses (Le Dang et al., 2013; Smajgl et al., 2015); agricultural productivity and food security (Smajgl et al., 2015); livelihoods such as fishing and farming (D. Wu et al., 2013); and disaster risk (D. Wu et al., 2013; Hoang et al., 2016), with implications for human mortality and economic and infrastructure losses. 239 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Cross-Chapter Box 6 (continued) Adaptation imperatives and costs in the Mekong will be higher under higher temperatures and associated impacts on agriculture and aquaculture, hazard exposure, and infrastructure. Adaptation measures to meet food security include greater investment in crop diversification and integrated agriculture–aquaculture practices (Renaud et al., 2015), improvement of water-use technologies (e.g., irrigation, pond capacity improvement and rainwater harvesting), soil management, crop diversification, and strengthening allied sectors such as livestock rearing and aquaculture (ICEM, 2013). Ecosystem-based approaches, such as integrated water resources management, demonstrate successes in mainstreaming adaptation into existing strategies (Sebesvari et al., 2017). However, some of these adaptive strategies can have negative impacts that deepen the divide between land-wealthy and land-poor farmers (Chapman et al., 2016). Construction of high dikes, for example, has enabled triple-cropping, which benefits land-wealthy farmers but leads to increasing debt for land-poor farmers (Chapman and Darby, 2016). Institutional innovation has happened through the Mekong River Commission (MRC), which is an intergovernmental body between Cambodia, Lao PDR, Thailand and Viet Nam that was established in 1995. The MRC has facilitated impact assessment studies, regional capacity building and local project implementation (Schipper et al., 2010), although the mainstreaming of adaptation into development policies has lagged behind needs (Gass et al., 2011). Existing adaptation interventions can be strengthened through greater flexibility of institutions dealing with land-use planning and agricultural production, improved monitoring of saline intrusion, and the installation of early warning systems that can be accessed by the local authorities or farmers (Renaud et al., 2015; Hoang et al., 2016; Tran et al., 2018). It is critical to identify and invest in synergistic strategies from an ensemble of infrastructural options (e.g., building dikes); soft adaptation measures (e.g., land-use change) (Smajgl et al., 2015; Hoang et al., 2018); combinations of top-down government-led (e.g., relocation) and bottom-up household strategies (e.g., increasing house height) (Ling et al., 2015); and community-based adaptation initiatives that merge scientific knowledge with local solutions (Gustafson et al., 2016, 2018; Tran et al., 2018). Special attention needs to be given to strengthening social safety nets and livelihood assets whilst ensuring that adaptation plans are mainstreamed into 3 broader development goals (Sok and Yu, 2015; Kim et al., 2017). The combination of environmental, social and economic pressures on people in the Mekong River basin highlights the complexity of climate change impacts and adaptation in this region, as well as the fact that costs are projected to be much lower at 1.5°C than 2°C of global warming. 3.4.7 Human Health and 3.SM.10 (based on Ebi et al., 2018). Other climate-sensitive health outcomes, such as diarrheal diseases, mental health issues Climate change adversely affects human health by increasing exposure and the full range of sources of poor air quality, were not considered and vulnerability to climate-related stresses, and decreasing the because of the lack of projections of how risks could change at 1.5°C capacity of health systems to manage changes in the magnitude and and 2°C. Few projections were available for specific temperatures pattern of climate-sensitive health outcomes (Cramer et al., 2014; Hales above pre-industrial levels; Supplementary Material 3.SM, Table et al., 2014). Changing weather patterns are associated with shifts in 3.SM.7 provides the conversions used to translate risks projected for the geographic range, seasonality and transmission intensity of selected particular time slices to those for specific temperature changes (Ebi climate-sensitive infectious diseases (e.g., Semenza and Menne, 2009), et al., 2018). and increasing morbidity and mortality are associated with extreme weather and climate events (e.g., K.R. Smith et al., 2014). Health Temperature-related morbidity and mortality: The magnitude of detection and attribution studies conducted since AR5 have provided projected heat-related morbidity and mortality is greater at 2°C than evidence, using multistep attribution, that climate change is negatively at 1.5°C of global warming (very high confidence)(Doyon et al., 2008; affecting adverse health outcomes associated with heatwaves, Jackson et al., 2010; Hanna et al., 2011; Huang et al., 2012; Petkova Lyme disease in Canada, and Vibrio emergence in northern Europe et al., 2013; Hajat et al., 2014; Hales et al., 2014; Honda et al., 2014; (Mitchell, 2016; Mitchell et al., 2016; Ebi et al., 2017). The IPCC AR5 Vardoulakis et al., 2014; Garland et al., 2015; Huynen and Martens, concluded there is high to very high confidence that climate change 2015; Li et al., 2015; Schwartz et al., 2015; L. Wang et al., 2015; will lead to greater risks of injuries, disease and death, owing to more Guo et al., 2016; T. Li et al., 2016; Chung et al., 2017; Kendrovski intense heatwaves and fires, increased risks of undernutrition, and et al., 2017; Mishra et al., 2017; Arnell et al., 2018; Mitchell et al., consequences of reduced labour productivity in vulnerable populations 2018b). The number of people exposed to heat events is projected (K.R. Smith et al., 2014). to be greater at 2°C than at 1.5°C (Russo et al., 2016; Mora et al., 2017; Byers et al., 2018; Harrington and Otto, 2018; King et al., 3.4.7.1 Projected risk at 1.5°C and 2°C of global warming 2018). The extent to which morbidity and mortality are projected to increase varies by region, presumably because of differences in The projected risks to human health of warming of 1.5°C and 2°C, acclimatization, population vulnerability, the built environment, based on studies of temperature-related morbidity and mortality, access to air conditioning and other factors (Russo et al., 2016; Mora air quality and vector borne diseases assessed in and since AR5, are et al., 2017; Byers et al., 2018; Harrington and Otto, 2018; King et summarized in Supplementary Material 3.SM, Tables 3.SM.8, 3.SM.9 al., 2018). Populations at highest risk include older adults, children, 240 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 women, those with chronic diseases, and people taking certain change, with expansions and reductions depending on the degree of medications (very high confidence). Assuming adaptation takes place local warming, the ecology of the mosquito vector, and other factors reduces the projected magnitude of risks (Hales et al., 2014; Huynen (Ren et al., 2016). and Martens, 2015; T. Li et al., 2016). Aedes (mosquito vector for dengue fever, chikungunya, yellow In some regions, cold-related mortality is projected to decrease with fever and Zika virus): Projections of the geographic distribution of increasing temperatures, although increases in heat-related mortality Aedes aegypti and Ae. albopictus (principal vectors) or of the prevalence generally are projected to outweigh any reductions in cold-related of dengue fever generally conclude that there will be an increase in the mortality with warmer winters, with the heat-related risks increasing number of mosquitos and a larger geographic range at 2°C than at with greater degrees of warming (Huang et al., 2012; Hajat et al., 2014; 1.5°C, and they suggest that more individuals will be at risk of dengue Vardoulakis et al., 2014; Gasparrini et al., 2015; Huynen and Martens, fever, with regional differences (high confidence) (Fischer et al., 2011, 2015; Schwartz et al., 2015). 2013; Colón-González et al., 2013, 2018; Bouzid et al., 2014; Ogden et al., 2014a; Mweya et al., 2016). The risks increase with greater Occupational health: Higher ambient temperatures and humidity levels warming. Projections suggest that climate change is projected to place additional stress on individuals engaging in physical activity. Safe expand the geographic range of chikungunya, with greater expansions work activity and worker productivity during the hottest months of the occurring at higher degrees of warming (Tjaden et al., 2017). year would be increasingly compromised with additional climate change (medium confidence) (Dunne et al., 2013; Kjellstrom et al., 2013, 2018; Other vector-borne diseases: Increased warming in North Sheffield et al., 2013; Habibi Mohraz et al., 2016). Patterns of change may America and Europe could result in geographic expansions of be complex; for example, at 1.5°C, there could be about a 20% reduction regions (latitudinally and altitudinally) climatically suitable for West in areas experiencing severe heat stress in East Asia, compared to Nile virus transmission, particularly along the current edges of its significant increases in low latitudes at 2°C (Lee and Min, 2018). The costs transmission areas, and extension of the transmission season, with of preventing workplace heat-related illnesses through worker breaks the magnitude and pattern of changes varying by location and level suggest that the difference in economic loss between 1.5°C and 2°C could of warming (Semenza et al., 2016). Most projections conclude that 3 be approximately 0.3% of global gross domestic product (GDP) in 2100 climate change could expand the geographic range and seasonality (Takakura et al., 2017). In China, taking into account population growth of Lyme and other tick-borne diseases in parts of North America and and employment structure, high temperature subsidies for employees Europe (Ogden et al., 2014b; Levi et al., 2015). The projected changes working on extremely hot days are projected to increase from 38.6 billion are larger with greater warming and under higher greenhouse gas yuan yr–1 in 1979–2005 to 250 billion yuan yr–1 in the 2030s (about 1.5°C) emissions pathways. Projections of the impacts of climate change on (Zhao et al., 2016). leishmaniosis and Chagas disease indicate that climate change could increase or decrease future health burdens, with greater impacts Air quality: Because ozone formation is temperature dependent, occurring at higher degrees of warming (González et al., 2014; projections focusing only on temperature increase generally conclude Ceccarelli and Rabinovich, 2015). that ozone-related mortality will increase with additional warming, with the risks higher at 2°C than at 1.5°C (high confidence) (Supplementary In summary, warming of 2°C poses greater risks to human health than Material 3.SM, Table 3.SM.9; Heal et al., 2013; Tainio et al., 2013; warming of 1.5°C, often with the risks varying regionally, with a few Likhvar et al., 2015; Silva et al., 2016; Dionisio et al., 2017; J.Y. Lee exceptions (high confidence). There is very high confidence that each et al., 2017). Reductions in precursor emissions would reduce future additional unit of warming could increase heat-related morbidity and ozone concentrations and associated mortality. Mortality associated mortality, and that adaptation would reduce the magnitude of impacts. with exposure to particulate matter could increase or decrease in the There is high confidence that ozone-related mortality could increase if future, depending on climate projections and emissions assumptions precursor emissions remain the same, and that higher temperatures (Supplementary Material 3.SM, Table 3.SM.8; Tainio et al., 2013; could affect the transmission of some infectious diseases, with Likhvar et al., 2015; Silva et al., 2016). increases and decreases projected depending on the disease (e.g., malaria, dengue fever, West Nile virus and Lyme disease), region and Malaria: Recent projections of the potential impacts of climate degree of temperature change. change on malaria globally and for Asia, Africa, and South America (Supplementary Material 3.SM, Table 3.SM.10) confirm that weather 3.4.8 Urban Areas and climate are among the drivers of the geographic range, intensity of transmission, and seasonality of malaria, and that the relationships are There is new literature on urban climate change and its differential not necessarily linear, resulting in complex patterns of changes in risk impacts on and risks for infrastructure sectors – energy, water, transport with additional warming (very high confidence) (Ren et al., 2016; Song and buildings – and vulnerable populations, including those living in et al., 2016; Semakula et al., 2017). Projections suggest that the burden informal settlements (UCCRN, 2018). However, there is limited literature of malaria could increase with climate change because of a greater on the risks of warming of 1.5°C and 2°C in urban areas. Heat-related geographic range of the Anopheles vector, longer season, and/or extreme events (Matthews et al., 2017), variability in precipitation (Yu increase in the number of people at risk, with larger burdens at higher et al., 2018) and sea level rise can directly affect urban areas (Section levels of warming, but with regionally variable patterns (medium to 3.4.5, Bader et al., 2018; Dawson et al., 2018). Indirect risks may arise high confidence). Vector populations are projected to shift with climate from interactions between urban and natural systems. 241 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Future warming and urban expansion could lead to more extreme depending on the vulnerability of the location (coastal or non-coastal) heat stress (Argüeso et al., 2015; Suzuki-Parker et al., 2015). At 1.5°C (high confidence), businesses, infrastructure sectors (energy, water of warming, twice as many megacities (such as Lagos, Nigeria and and transport), levels of poverty, and the mix of formal and informal Shanghai, China) could become heat stressed, exposing more than settlements. 350 million more people to deadly heat by 2050 under midrange population growth. Without considering adaptation options, such 3.4.9 Key Economic Sectors and Services as cooling from more reflective roofs, and overall characteristics of urban agglomerations in terms of land use, zoning and building codes Climate change could affect tourism, energy systems and transportation (UCCRN, 2018), Karachi (Pakistan) and Kolkata (India) could experience through direct impacts on operations (e.g., sea level rise) and through conditions equivalent to the deadly 2015 heatwaves on an annual impacts on supply and demand, with the risks varying significantly with basis under 2°C of warming (Akbari et al., 2009; Oleson et al., 2010; geographic region, season and time. Projected risks also depend on Matthews et al., 2017). Warming of 2°C is expected to increase the assumptions with respect to population growth, the rate and pattern risks of heatwaves in China’s urban agglomerations (Yu et al., 2018). of urbanization, and investments in infrastructure. Table 3.SM.11 in Stabilizing at 1.5°C of warming instead of 2°C could decrease mortality Supplementary Material 3.SM summarizes the cited publications. related to extreme temperatures in key European cities, assuming no adaptation and constant vulnerability (Jacob et al., 2018; Mitchell et 3.4.9.1 Tourism al., 2018a). Holding temperature change to below 2°C but taking urban heat islands (UHI) into consideration, projections indicate that there The implications of climate change for the global tourism sector are could be a substantial increase in the occurrence of deadly heatwaves in far-reaching and are impacting sector investments, destination assets cities. The urban impacts of these heatwaves are expected to be similar (environment and cultural), operational and transportation costs, and at 1.5°C and 2°C and substantially larger than under the present climate tourist demand patterns (Scott et al., 2016a; Scott and Gössling, 2018). (Matthews et al., 2017; Yu et al., 2018). Increases in the intensity of Since AR5, observed impacts on tourism markets and destination UHI could exacerbate warming of urban areas, with projections ranging communities continue to be not well analysed, despite the many 3 from a 6% decrease to a 30% increase for a doubling of CO2 (McCarthy analogue conditions (e.g., heatwaves, major hurricanes, wild fires, et al., 2010). Increases in population and city size, in the context of a reduced snow pack, coastal erosion and coral reef bleaching) that warmer climate, are projected to increase UHI (Georgescu et al., 2012; are anticipated to occur more frequently with climate change. There Argüeso et al., 2014; Conlon et al., 2016; Kusaka et al., 2016; Grossman- is some evidence that observed impacts on tourism assets, such as Clarke et al., 2017). environmental and cultural heritage, are leading to the development of ‘last chance to see’ tourism markets, where travellers visit destinations For extreme heat events, an additional 0.5°C of warming implies before they are substantially degraded by climate change impacts or a shift from the upper bounds of observed natural variability to a to view the impacts of climate change on landscapes (Lemelin et al., new global climate regime (Schleussner et al., 2016b), with distinct 2012; Stewart et al., 2016; Piggott-McKellar and McNamara, 2017). implications for the urban poor (Revi et al., 2014; Jean-Baptiste et al., 2018; UCCRN, 2018). Adverse impacts of extreme events could arise There is limited research on the differential risks of a 1.5° versus in tropical coastal areas of Africa, South America and Southeast Asia 2°C temperature increase and resultant environmental and socio- (Schleussner et al., 2016b). These urban coastal areas in the tropics economic impacts in the tourism sector. The translation of these are particularly at risk given their large informal settlements and other changes in climate resources for tourism into projections of tourism vulnerable urban populations, as well as vulnerable assets, including demand remains geographically limited to Europe. Based on analyses businesses and critical urban infrastructure (energy, water, transport of tourist comfort, summer and spring/autumn tourism in much and buildings) (McGranahan et al., 2007; Hallegatte et al., 2013; Revi of western Europe may be favoured by 1.5°C of warming, but with et al., 2014; UCCRN, 2018). Mediterranean water stress is projected negative effects projected for Spain and Cyprus (decreases of 8% and to increase from 9% at 1.5°C to 17% at 2°C compared to values in 2%, respectively, in overnight stays) and most coastal regions of the 1986–2005 period. Regional dry spells are projected to expand from Mediterranean (Jacob et al., 2018). Similar geographic patterns of 7% at 1.5°C to 11% at 2°C for the same reference period. Sea level rise potential tourism gains (central and northern Europe) and reduced is expected to be lower at 1.5°C than 2°C, lowering risks for coastal summer favourability (Mediterranean countries) are projected under metropolitan agglomerations (Schleussner et al., 2016b). 2°C (Grillakis et al., 2016). Considering potential changes in natural snow only, winter overnight stays at 1.5°C are projected to decline Climate models are better at projecting implications of greenhouse by 1–2% in Austria, Italy and Slovakia, with an additional 1.9 million gas forcing on physical systems than at assessing differential risks overnight stays lost under 2°C of warming (Jacob et al., 2018). Using associated with achieving a specific temperature target (James et an econometric analysis of the relationship between regional tourism al., 2017). These challenges in managing risks are amplified when demand and climate conditions, Ciscar et al. (2014) projected that a combined with the scale of urban areas and assumptions about socio- 2°C warmer world would reduce European tourism by 5% (€15 billion economic pathways (Krey et al., 2012; Kamei et al., 2016; Yu et al., yr–1), with losses of up to 11% (€6 billion yr–1) for southern Europe and 2016; Jiang and Neill, 2017). a potential gain of €0.5 billion yr–1 in the UK. In summary, in the absence of adaptation, in most cases, warming There is growing evidence that the magnitude of projected impacts is of 2°C poses greater risks to urban areas than warming of 1.5°C, temperature dependent and that sector risks could be much greater 242 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 with higher temperature increases and resultant environmental In summary, climate is an important factor influencing the geography and socio-economic impacts (Markham et al., 2016; Scott et al., and seasonality of tourism demand and spending globally (very high 2016a; Jones, 2017; Steiger et al., 2017). Studies from 27 countries confidence). Increasing temperatures are projected to directly impact consistently project substantially decreased reliability of ski areas that climate-dependent tourism markets, including sun, beach and snow are dependent on natural snow, increased snowmaking requirements sports tourism, with lesser risks for other tourism markets that are less and investment in snowmaking systems, shortened and more variable climate sensitive (high confidence). The degradation or loss of beach ski seasons, a contraction in the number of operating ski areas, and coral reef assets is expected to increase risks for coastal tourism, altered competitiveness among and within regional ski markets, particularly in subtropical and tropical regions (high confidence). and subsequent impacts on employment and the value of vacation properties (Steiger et al., 2017). Studies that omit snowmaking do 3.4.9.2 Energy systems not reflect the operating realities of most ski areas and overestimate impacts at 1.5°C–2°C. In all regional markets, the extent and timing Climate change is projected to lead to an increased demand for air of these impacts depend on the magnitude of climate change and the conditioning in most tropical and subtropical regions (Arent et al., types of adaptive responses by the ski industry, skiers and destination 2014; Hong and Kim, 2015) (high confidence). Increasing temperatures communities. The decline in the number of former Olympic Winter will decrease the thermal efficiency of fossil, nuclear, biomass and Games host locations that could remain climatically reliable for future solar power generation technologies, as well as buildings and other Olympic and Paralympic Winter Games has been projected to be much infrastructure (Arent et al., 2014). For example, in Ethiopia, capital greater under scenarios warmer than 2°C (Scott et al., 2015; Jacob et expenditures through 2050 might either decrease by approximately al., 2018). 3% under extreme wet scenarios or increase by up to 4% under a severe dry scenario (Block and Strzepek, 2012). The tourism sector is also affected by climate-induced changes in environmental assets critical for tourism, including biodiversity, Impacts on energy systems can affect gross domestic product (GDP). beaches, glaciers and other features important for environmental and The economic damage in the United States from climate change is cultural heritage. Limited analyses of projected risks associated with estimated to be, on average, roughly 1.2% cost of GDP per year per 3 1.5°C versus 2°C are available (Section 3.4.4.12). A global analysis of 1°C increase under RCP8.5 (Hsiang et al., 2017). Projections of GDP sea level rise (SLR) risk to 720 UNESCO Cultural World Heritage sites indicate that negative impacts of energy demand associated with projected that about 47 sites might be affected under 1°C of warming, space heating and cooling in 2100 will be greatest (median: –0.94% with this number increasing to 110 and 136 sites under 2°C and 3°C, change in GDP) under 4°C (RCP8.5) compared with under 1.5°C respectively (Marzeion and Levermann, 2014). Similar risks to vast (median: –0.05%), depending on the socio-economic conditions (Park worldwide coastal tourism infrastructure and beach assets remain et al., 2018). Additionally, projected total energy demands for heating unquantified for most major tourism destinations and small island and cooling at the global scale do not change much with increases in developing states (SIDS) that economically depend on coastal tourism. global mean surface temperature (GMST) of up to 2°C. A high degree One exception is the projection that an eventual 1 m SLR could of variability is projected between regions (Arnell et al., 2018). partially or fully inundate 29% of 900 coastal resorts in 19 Caribbean countries, with a substantially higher proportion (49–60%) vulnerable Evidence for the impact of climate change on energy systems since AR5 to associated coastal erosion (Scott and Verkoeyen, 2017). is limited. Globally, gross hydropower potential is projected to increase (by 2.4% under RCP2.6 and by 6.3% under RCP8.5 for the 2080s), with A major barrier to understanding the risks of climate change for tourism, the most growth expected in Central Africa, Asia, India and northern from the destination community scale to the global scale, has been high latitudes (van Vliet et al., 2016). Byers et al. (2018) found that the lack of integrated sectoral assessments that analyse the full range energy impacts at 2°C increase, including more cooling degree days, of potential compounding impacts and their interactions with other especially in tropical regions, as well as increased hydro-climatic risk major drivers of tourism (Rosselló-Nadal, 2014; Scott et al., 2016b). to thermal and hydropower plants predominantly in Europe, North When applied to 181 countries, a global vulnerability index including America, South and Southeast Asia and southeast Brazil. Donk et al. 27 indicators found that countries with the lowest risk are located in (2018) assessed future climate impacts on hydropower in Suriname western and northern Europe, central Asia, Canada and New Zealand, and projected a decrease of approximately 40% in power capacity while the highest sector risks are projected for Africa, the Middle for a global temperature increase in the range of 1.5°C. At minimum East, South Asia and SIDS in the Caribbean, Indian and Pacific Oceans and maximum increases in global mean temperature of 1.35°C and (Scott and Gössling, 2018). Countries with the highest risks and where 2°C, the overall stream flow in Florida, USA is projected to increase tourism represents a significant proportion of the national economy by an average of 21%, with pronounced seasonal variations, resulting (i.e., more than 15% of GDP) include many SIDS and least developed in increases in power generation in winter (+72%) and autumn countries. Sectoral climate change risk also aligns strongly with regions (+15%) and decreases in summer (–14%; Chilkoti et al., 2017). Greater where tourism growth is projected to be the strongest over the coming changes are projected at higher temperature increases. In a reference decades, including sub-Saharan Africa and South Asia, pointing to an scenario with global mean temperatures rising by 1.7°C from 2005 important potential barrier to tourism development. The transnational to 2050, U.S. electricity demand in 2050 was 1.6–6.5% higher than implications of these impacts on the highly interconnected global in a control scenario with constant temperatures (McFarland et al., tourism sector and the contribution of tourism to achieving the 2030 2015). Decreased electricity generation of –15% is projected for Brazil sustainable development goals (SDGs) remain important uncertainties. starting in 2040, with values expected to decline to –28% later in the 243 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems century (de Queiroz et al., 2016). In large parts of Europe, electricity signal was limited, with more evidence of impacts of climate change on demand is projected to decrease, mainly owing to reduced heating the places where indigenous people live and use traditional ecological demand (Jacob et al., 2018). knowledge (Olsson et al., 2014). In Europe, no major differences in large-scale wind energy resources 3.4.10.1 Livelihoods and poverty or in inter- or intra-annual variability are projected for 2016–2035 under RCP8.5 and RCP4.5 (Carvalho et al., 2017). However, in 2046– At approximately 1.5°C of global warming (2030), climate change is 2100, wind energy density is projected to decrease in eastern Europe expected to be a poverty multiplier that makes poor people poorer and (–30%) and increase in Baltic regions (+30%). Intra-annual variability increases the poverty head count (Hallegatte et al., 2016; Hallegatte is expected to increase in northern Europe and decrease in southern and Rozenberg, 2017). Poor people might be heavily affected by climate Europe. Under RCP4.5 and RCP8.5, the annual energy yield of European change even when impacts on the rest of population are limited. wind farms as a whole, as projected to be installed by 2050, will remain Climate change alone could force more than 3 million to 16 million stable (±5 yield for all climate models). However, wind farm yields are people into extreme poverty, mostly through impacts on agriculture projected to undergo changes of up to 15% in magnitude at country and food prices (Hallegatte et al., 2016; Hallegatte and Rozenberg, and local scales and of 5% at the regional scale (Tobin et al., 2015, 2017). Unmitigated warming could reshape the global economy later 2016). Hosking et al. (2018) assessed wind power generation over in the century by reducing average global incomes and widening Europe for 1.5°C of warming and found the potential for wind energy global income inequality (Burke et al., 2015b). The most severe impacts to be greater than previously assumed in northern Europe. Additionally, are projected for urban areas and some rural regions in sub-Saharan Tobin et al. (2018) assessed impacts under 1.5°C and 2°C of warming Africa and Southeast Asia. on wind, solar photovoltaic and thermoelectric power generation across Europe. These authors found that photovoltaic and wind power 3.4.10.2 The changing structure of communities: might be reduced by up to 10%, and hydropower and thermoelectric migration, displacement and conflict generation might decrease by up to 20%, with impacts being limited 3 at 1.5°C of warming but increasing as temperature increases (Tobin et Migration: In AR5, the potential impacts of climate change on migration al., 2018). and displacement were identified as an emerging risk (Oppenheimer et al., 2014). The social, economic and environmental factors underlying 3.4.9.3 Transportation migration are complex and varied; therefore, detecting the effect of observed climate change or assessing its possible magnitude with any Road, air, rail, shipping and pipeline transportation can be impacted degree of confidence is challenging (Cramer et al., 2014). directly or indirectly by weather and climate, including increases in precipitation and temperature; extreme weather events (flooding and No studies have specifically explored the difference in risks between storms); SLR; and incidence of freeze–thaw cycles (Arent et al., 2014). 1.5°C and 2°C of warming on human migration. The literature Much of the published research on the risks of climate change for the consistently highlights the complexity of migration decisions and the transportation sector has been qualitative. difficulties in attributing causation (e.g., Nicholson, 2014; Baldwin and Fornalé, 2017; Bettini, 2017; Constable, 2017; Islam and Shamsuddoha, The limited new research since AR5 supports the notion that increases 2017; Suckall et al., 2017). The studies on migration that have in global temperatures will impact the transportation sector. Warming most closely explored the probable impacts of 1.5°C and 2°C have is projected to result in increased numbers of days of ice-free navigation mainly focused on the direct effects of temperature and precipitation and a longer shipping season in cold regions, thus affecting shipping anomalies on migration or the indirect effects of these climatic changes and reducing transportation costs (Arent et al., 2014). In the North Sea through changing agriculture yield and livelihood sources (Mueller et Route, large-scale commercial shipping might not be possible until al., 2014; Piguet and Laczko, 2014; Mastrorillo et al., 2016; Sudmeier- 2030 for bulk shipping and until 2050 for container shipping under Rieux et al., 2017). RCP8.5. A 0.05% increase in mean temperature is projected from an increase in short-lived pollutants, as well as elevated CO2 and non-CO2 Temperature has had a positive and statistically significant effect emissions, associated with additional economic growth enabled by the on outmigration over recent decades in 163 countries, but only for North Sea Route. (Yumashev et al., 2017). Open water vessel transit agriculture-dependent countries (R. Cai et al., 2016). A 1°C increase has the potential to double by mid-century, with a two to four month in average temperature in the International Migration Database of the longer season (Melia et al., 2016). Organisation for Economic Co-operation and Development (OECD) was associated with a 1.9% increase in bilateral migration flows from 3.4.10 Livelihoods and Poverty, and the Changing 142 sending countries and 19 receiving countries, and an additional Structure of Communities millimetre of average annual precipitation was associated with an increase in migration by 0.5% (Backhaus et al., 2015). In another Multiple drivers and embedded social processes influence the study, an increase in precipitation anomalies from the long-term mean, magnitude and pattern of livelihoods and poverty, as well as the was strongly associated with an increase in outmigration, whereas no changing structure of communities related to migration, displacement significant effects of temperature anomalies were reported (Coniglio and conflict (Adger et al., 2014). In AR5, evidence of a climate change and Pesce, 2015). 244 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Internal and international migration have always been important for poorer and increases poverty head count, and the association between small islands (Farbotko and Lazrus, 2012; Weir et al., 2017). There is temperature and economic productivity is not linear (high confidence). rarely a single cause for migration (Constable, 2017). Numerous factors Temperature has a positive and statistically significant effect on are important, including work, education, quality of life, family ties, outmigration for agriculture-dependent communities (medium access to resources, and development (Bedarff and Jakobeit, 2017; confidence). Speelman et al., 2017; Nicholls et al., 2018). Depending on the situation, changing weather, climate or environmental conditions might each be 3.4.11 Interacting and Cascading Risks a factor in the choice to migrate (Campbell and Warrick, 2014). The literature on compound as well as interacting and cascading risks Displacement: At 2°C of warming, there is a potential for significant at warming of 1.5°C and 2°C is limited. Spatially compound risks, population displacement concentrated in the tropics (Hsiang and Sobel, often referred to as hotspots, involve multiple hazards from different 2016). Tropical populations may have to move distances greater than sectors overlapping in location (Piontek et al., 2014). Global exposures 1000 km if global mean temperature rises by 2°C from 2011–2030 to were assessed for 14 impact indicators, covering water, energy and the end of the century. A disproportionately rapid evacuation from the land sectors, from changes including drought intensity and water tropics could lead to a concentration of population in tropical margins stress index, cooling demand change and heatwave exposure, habitat and the subtropics, where population densities could increase by 300% degradation, and crop yields using an ensemble of climate and impact or more (Hsiang and Sobel, 2016). models (Byers et al., 2018). Exposures are projected to approximately double between 1.5°C and 2°C, and the land area affected by climate Conflict: A recent study has called for caution in relating conflict risks is expected to increase as warming progresses. For populations to climate change, owing to sampling bias (Adams et al., 2018). vulnerable to poverty, the exposure to climate risks in multiple sectors Insufficient consideration of the multiple drivers of conflict often leads could be an order of magnitude greater (8–32 fold) in the high poverty to inconsistent associations being reported between climate change and inequality scenarios (SSP3; 765–1,220 million) compared to under and conflict (e.g., Hsiang et al., 2013; Hsiang and Burke, 2014; Buhaug, sustainable socio-economic development (SSP1; 23–85 million). Asian 2015, 2016; Carleton and Hsiang, 2016; Carleton et al., 2016). There and African regions are projected to experience 85–95% of global 3 also are inconsistent relationships between climate change, migration exposure, with 91–98% of the exposed and vulnerable population and conflict (e.g., Theisen et al., 2013; Buhaug et al., 2014; Selby, 2014; (depending on SSP/GMT combination), approximately half of which Christiansen, 2016; Brzoska and Fröhlich, 2016; Burrows and Kinney, are in South Asia. Figure 3.19 shows that moderate and large multi- 2016; Reyer et al., 2017c; Waha et al., 2017). Across world regions and sector impacts are prevalent at 1.5°C where vulnerable people live, from the international to micro level, the relationship between drought predominantly in South Asia (mostly Pakistan, India and China), but that and conflict is weak under most circumstances (Buhaug, 2016; von impacts spread to sub-Saharan Africa, the Middle East and East Asia at Uexkull et al., 2016). However, drought significantly increases the higher levels of warming. Beyond 2°C and at higher risk thresholds, likelihood of sustained conflict for particularly vulnerable nations or the world’s poorest populations are expected to be disproportionately groups, owing to the dependence of their livelihood on agriculture. impacted, particularly in cases (SSP3) of great inequality in Africa and This is particularly relevant for groups in the least developed countries southern Asia. Table 3.4 shows the number of exposed and vulnerable (von Uexkull et al., 2016), in sub-Saharan Africa (Serdeczny et al., 2016; people at 1.5°C and 2°C of warming, with 3°C shown for context, for Almer et al., 2017) and in the Middle East (Waha et al., 2017). Hsiang selected multi-sector risks. et al. (2013) reported causal evidence and convergence across studies that climate change is linked to human conflicts across all major 3.4.12 Summary of Projected Risks at 1.5°C and 2°C regions of the world, and across a range of spatial and temporal scales. of Global Warming A 1°C increase in temperature or more extreme rainfall increases the frequency of intergroup conflicts by 14% (Hsiang et al., 2013). If The information presented in Section 3.4 is summarized below in Table the world warms by 2°C–4°C by 2050, rates of human conflict could 3.5, which illustrates the growing evidence of increasing risks across a increase. Some causal associations between violent conflict and broad range of natural and human systems at 1.5°C and 2°C of global socio-political instability were reported from local to global scales warming. and from hour to millennium time frames (Hsiang and Burke, 2014). A temperature increase of one standard deviation increased the risk of interpersonal conflict by 2.4% and intergroup conflict by 11.3% (Burke et al., 2015a). Armed-conflict risks and climate-related disasters are both relatively common in ethnically fractionalized countries, indicating that there is no clear signal that environmental disasters directly trigger armed conflicts (Schleussner et al., 2016a). In summary, average global temperatures that extend beyond 1.5°C are projected to increase poverty and disadvantage in many populations globally (medium confidence). By the mid- to late 21st century, climate change is projected to be a poverty multiplier that makes poor people 245 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems 3 Figure 3.19 | Multi-sector risk maps for 1.5°C (top), 2°C (middle), and locations where 2°C brings impacts not experienced at 1.5°C (2°C–1.5°C; bottom). The maps in the left column show the full range of the multi-sector risk (MSR) score (0–9), with scores ≤5.0 shown with a transparency gradient and scores >5.0 shown with a colour gradient. Score must be >4.0 to be considered ‘multi-sector’. The maps in the right column overlay the 2050 vulnerable populations (low income) under Shared Socio-Economic Pathway (SSP)2 (greyscale) with the multi-sector risk score >5.0 (colour gradient), thus indicating the concentrations of exposed and vulnerable populations to risks in multiple sectors. Source: Byers et al. (2018). Table 3.4 | Number of exposed and vulnerable people at 1.5°C, 2°C, and 3°C for selected multi-sector risks under shared socioeconomic pathways (SSPs). Source: Byers et al., 2018 SSP2 1.5°C 2°C 3°C (SSP1 to SSP3 range), millions Exposed Exposed Exposed Indicator Exposed Exposed Exposed and vulnerable and vulnerable and vulnerable Water stress index 3340 (3032–3584) 496 (103–1159) 3658 (3080–3969) 586 (115–1347) 3920 (3202–4271) 662 (146–1480) Heatwave event exposure 3960 (3546–4508) 1187 (410–2372) 5986 (5417–6710) 1581 (506–3218) 7909 (7286–8640) 1707 (537–3575) Hydroclimate risk to power production 334 (326–337) 30 (6–76) 385 (374–389) 38 (9–94) 742 (725–739) 72 (16–177) Crop yield change 35 (32–36) 8 (2–20) 362 (330–396) 81 (24–178) 1817 (1666–1992) 406 (118–854) Habitat degradation 91 (92–112) 10 (4–31) 680 (314–706) 102 (23–234) 1357 (809–1501) 248 (75–572) Multi-sector exposure Two indicators 1129 (1019–1250) 203 (42–487) 2726 (2132–2945) 562 (117–1220) 3500 (3212–3864) 707 (212–1545) Three indicators 66 (66–68) 7 (0.9–19) 422 (297–447) 54 (8–138) 1472 (1177–1574) 237 (48–538) Four indicators 5 (0.3–5.7) 0.3 (0–1.2) 11 (5–14) 0.5 (0–2) 258 (104–280) 33 (4–86) 246 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 3 247 Table 3.5 | Summary of projected risks to natural and human systems at 1.5°C and 2°C of global warming, and of the potential to adapt to these risks. Table summarizes the chapter text and with references supporting table entries found in the main chapter text. Risk magnitude is provided either as assessed levels of risk (very high: vh, high: h, medium: m, or low: l) or as quantitative examples of risk levels taken from the literature. Further compilations of quantified levels of risk taken from the literature may be found Tables 3.SM1-5 in the Supplementary Material. Similarly, potential to adapt is assessed from the literature by expert judgement as either high (h), medium (m), or low (l). Confidence in each assessed level/quantification of risk, or in each assessed adaptation potential, is indicated as very high (VH), high (H), medium (M), or low (L). Note that the use of l, m, h and vh here is distinct from the use of L, M, H and VH in Figures 3.18, 3.20 and 3.21. Regions Global risks Global Regions where the Physical at 1.5°C risks at 2°C Change in where risk when Confidence risks are change in risk Regions when moving with little Adaptation Adaptation Confidence climate Nature of global of global RFC* potential potential in assigning Sector particularly change of risk warming warming moving from in risk or no adaptation drivers above pre- above pre- 1.5°C to 2°C statements high with from 1.5°C at 1.5°C at 2°C potential industrial industrial of warming 2°C of global to 2°C are information warming particularly high Additional 8% of the world Around half population in Up to 100% Europe, Australia, Water Stress compared to the 2000 exposed M 3 l l M 1 increase southern Africarisks at 2°C to new or aggravated water scarcity1 100% increase 170% increase in the population in the population affected affected compared to the compared to the USA, Asia, Africa, Fluvial flood 70% increase M 2 l/m l/m M impact simulated impact simulated Europe Oceania over the over the baseline period baseline period 1976–20052 1976–20052 350.2 ± 158.8 410.7 ± 213.5 Central Europe, 60.5 ± 84.1 million, changes million, changes southern Europe, million in urban in urban Mediterranean, (±84.1 based population population West Africa, East Drought on the SSP1 M 2 l/m l/m L exposure to exposure to and West Asia, scenario) severe drought at severe drought at Southeast Asia (based on PDSI the globe scale3 the globe scale3 (based on PDSI estimate) estimate#) 6% insects, 4% 18% insects, Species vertebrates, 8% vertebrates, Amazon, Europe, Double or triple M 1,4 m l H range loss 8% plants, lose 16% plants lose southern Africa >50% range4 >50% range4 Loss of ecosystem m h M 4 functioning and services Shifts of biomes 13% (range Arctic, Tibet, About 7% (major ecosystem 5 8–20%) About double M Himalayas, South 4transformed types) transformed5 Africa, Australia Central and South America, Canada, USA and 1, 2, Wildfire h h Increased risk M Mediterranean Australia, l l M Mediterranean 4, 5 Russia, China, Africa T e r r e s t r i a l e c o s y s t e m s F r e s h w a t e r H e a t a n d c o l d s t r e s s , w a r m i n g , T e m p e r a t u r e , p r e c i p i t a t i o n P r e c i p i t a t i o n , t e m p e r a t u r e , s n o w m e l t p r e c i p i t a t i o n d r o u g h t Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems 3 248 Table 3.5 (continued) Regions Global risks Global Regions where the change in Physical at 1.5°C risks at 2°C Change in where Regions Confidence climate Nature of global of global risk when Confidence risks are risk when Adaptation Adaptation Sector particularly moving with little RFC* potential potential in assigning change of risk warming warming moving from in risk high with from 1.5°C or no adaptation drivers above pre- above pre- 1.5°C to 2°C statements to2°C are information at 1.5°C at 2°C potential industrial industrial of warming 2°C of global warming particularly high Greater rate Southern Red Loss of of loss: from Tropical/ Tropical/ Sea, Somalia, framework vh vh 70–90% loss at H/very H subtropical subtropical Yemen, 1,2 h l H species (coral 1.5°C to 99% loss countries countries deep water reefs) at 2°C and above coral reefs Loss of Southern Red Tropical/ Tropical/ framework Sea, Somalia, m h Increase in risk M subtropical subtropical 1,2 m l M/H species Yemen, countries countries (seagrass) Myanmar Loss of Southern Red Uncertain and Tropical/ Tropical/ framework Sea, Somalia, m m depends on other M/H subtropical subtropical 1,3 m l L/M species Yemen, human activities countries countries (mangroves) Myanmar Disruption of Large increase h vh M Global Global Deep sea 4 m l M/H marine foodwebs in risk Range migration Large increase of marine species m h H Global Global Deep sea 1 m l H in risk and ecosystems Loss of fin fish Large increase Deep sea, up- h h/vh H Global Global 4 m m/l M/H and fisheries in risk welling systems Low-latitude Loss of coastal Low-latitude Most regions tropical/ ecosystems and m h Increase in risk M tropical/subtropi- – risks not 1 m m/l M subtropical protection cal countries well defined countries Loss of bivalves Temperate Temperate Most regions Large increase and bivalve m/h h/vh H countries with countries with – risks not 4 m/h l/m M/H in risk fisheries upwelling upwelling well defined Changes to Most regions physiology l/m m Increase in risk H Global Global – risks not 4 l l M/H and ecology of well defined marine species Increased Temperate Temperate Large increase hypoxic dead l l/m L/M countries with countries with Deep sea 4 m l M in risk zones upwelling upwelling Changes to Some Most upwelling Most upwelling upwelling l m Increase in risk L/M upwelling 4 l l M regions regions productivity systems O c e a n R e d u c e d b u l k o c e a n O c e a n a c i d i fi c a t i o n a n d c i r c u l a t i o n a n d W a r m i n g a n d s t r a t i fi c a t i o n o f t h e s u r f a c e o c e a n e l e v a t e d s e a t e m p e r a t u r e s d e - o x y g e n a t i o n Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 3 249 Table 3.5 (continued) Regions where the Global risks Global Regions change in Physical at 1.5°C risks at 2°C Change in where Regions Confidence climate Nature of global of global risk when Confidence risks are risk when particularly moving with little Adaptation Adaptation Sector moving from in risk or no RFC* potential potential in assigning change of risk warming warming from 1.5°C at 1.5°C at 2°C adaptation drivers above pre- above pre- 1.5°C to 2°C statements high with potential industrial industrial of warming 2°C of global to2°C are information warming particularly high Tropical/ Tropical/ Loss of coastal Large increase h h/vh H subtropical subtropical 1, 4 m l M ecosystems in risk countries countries Inundation and destruction of Large increase human/coastal h h/vh H Global Global 1, 5 m/h m M/L in risk infrastructure and livelihoods Large increase Loss of habitat h vh H Polar regions Polar regions 1 l very l H in risk Increased productivity Large increase l/m m/h very H Polar regions Polar regions 1, 4 l m/l H but changing in risk fisheries Increasing; 25–38th km2 when M/H Area exposed 562–575th km2 590–613th km2 temperatures (dependent Asia, small Asia, small (assuming no when 1.5°C first when 2°C first are first reached, Small islands 2, 3 m m M defences) reached6,7,8 reached6,7,8 10–17th km2 in on population islands islands 2100 increasing datasets) to 16–230th km2 in 23006,7,8 Increasing; 13–8 million when Population temperatures are M/H 128–143 million 141–151 million exposed first reached, 0–6 (dependent Asia, small Asia, small when 1.5°C when 2°C first Small islands 2, 3 m m M (assuming no million people in on population islands islandsfirst reached reached defences) 2100, increasing datasets) to 35–95 million people in 23006 2–28 million 15–53 million People at risk people yr–1 if people yr–1 if Increasing with M/H Asia, small accounting defences are not defences are not time, but highly islands, Asia, small for defences Small islands 2, 3, 4 m m M upgraded from upgraded from dependent on (dependent on potentially islands (modelled the modelled the modelled adaptation9 adaptation) African nations in 1995) 1995 baseline9 1995 baseline9 C o a s t a l O c e a n I n t e n s i fi e d s t o r m s , S e a l e v e l r i s e , i n c r e a s e d s t o r m i n e s s L o s s o f s e a i c e p r e c i p i t a t i o n p l u s s e a l e v e l r i s e Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems 3 250 Table 3.5 (continued) Regions Global risks Global Regions where the Physical at 1.5°C risks at 2°C Change in where change in Regions Confidence climate Nature of global of global risk when Confidence risks are risk when Adaptation Adaptation Sector particularly moving with little RFC* potential potential in assigning change of risk warming warming moving from in risk or no adaptation drivers above pre- above pre- 1.5°C to 2°C statements high with from 1.5°C at 1.5°C at 2°C potential industrial industrial of warming 2°C of global to2°C are information warming particularly high North America, Central and Changes in South America, ecosystem m/h h Large increase M/H Global Mediterranean 2, 4, 5 h m/h M/H production basin, South Africa, Australia, Asia Shift and composition Global, Moderate 1, 2, change of m/h h L/M Global tropical areas, Africa, Asia l/m l L/M increase 3, 4 biomes (major Mediterranean ecosystem types) Heat-related morbidity and m m/h Risk increased VH All regions at risk All regions Africa 2, 3, 4 h h H mortality Occupational m m/h Risk increased M Tropical regions Tropical regions Africa 2, 3, 4 h m M heat stress m (if precursor m/h (if precursor High income High income Ozone-related Africa, parts emissions remain emissions remain Risk increased H and emerging and emerging 2, 3, 4 l l M mortality of Asia the same) the same) economies economies Low-income Low-income Undernutrition m m/h Risk increased H countries in countries in Small islands 2, 3, 4 m l M Africa and Asia Africa and Asia Coastal tourism, Coastal tourism, Tourism particularly in particularly in (sun, beach, and m/h h Risk increased VH Africa 1, 2, 3 m l H subtropical and subtropical and snow sports) tropical regions tropical regions *RFC: 1 = unique and threatened systems, 2 = extreme events, 3 = unequal distribution of impacts, 4 = global aggregate impacts (economic + biodiversity), 5 = large-scale singular events. # PDSI-based drought estimates tend to overestimate drought impacts (see Section 3.3.4); hence projections with other drought indices may differ. Further quantifications may be found in Table 3.SM.1 1 Gerten et al., 2013; 2 Alfieri et al., 2017; 3 Liu et al., 2018; 4 Warren et al., 2018a; 5 Warzawski et al., 2013; 6 Brown et al., 2018a; 7 Rasmussen et al., 2018; 8 Yokoki et al., 2018; 9 Nicholls et al., 2018. K e y F o o d s e c u r i t y a n d e c o n o m i c H u m a n h e a l t h f o o d p r o d u c t i o n s y s t e m s s e c t o r s H e a t a n d c o l d H e a t a n d T e m p e r a t u r e , A i r s t r e s s , w a r m i n g , T e m p e r a t u r e T e m p e r a t u r e c o l d s t r e s s , w a r m i n g , p r e c i p i t a t i o n p r e c i p i t a t i o n q u a l i t y p r e c i p i t a t i o n , d r o u g h t d r o u g h t Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 3.4.13 Synthesis of Key Elements of Risk in Figure 3.20) is located below 2°C (high confidence). With 3°C of warming, however, biome shifts and species range losses are expected Some elements of the assessment in Section 3.4 were synthesized into to escalate to very high levels, and the systems are projected to have Figure 3.18 and 3.20, indicating the overall risk for a representative set very little capacity to adapt (Figure 3.20) (high confidence) (Section of natural and human systems from increases in global mean surface 3.4.3). temperature (GMST) and anthropogenic climate change. The elements included are supported by a substantive enough body of literature In the Arctic (related to RFC1), the increased rate of summer sea ice providing at least medium confidence in the assessment. The format for melt was detected and attributed to climate change by the year 2000 Figures 3.18 and 3.20 match that of Figure 19.4 of WGII AR5 Chapter (corresponding to warming of 0.7°C), indicating moderate risk. At 19 (Oppenheimer et al., 2014) indicating the levels of additional risk 1.5°C of warming an ice-free Arctic Ocean is considered unlikely, whilst as colours: undetectable (white) to moderate (detected and attributed; by 2°C of warming it is considered likely and this unique ecosystem is yellow), from moderate to high (severe and widespread; red), and projected to be unable to adapt. Hence, a transition from high to very from high to very high (purple), the last of which indicates significant high risk is expected between 1.5°C and 2°C of warming. irreversibility or persistence of climate-related hazards combined with a much reduced capacity to adapt. Regarding the transition For warm-water coral reefs, there is high confidence in the transitions from undetectable to moderate, the impact literature assessed in AR5 between risk levels, especially in the growing impacts in the focused on describing and quantifying linkages between weather and transition of warming from non-detectable (0.2°C to 0.4°C), and then climate patterns and impact outcomes, with limited detection and successively higher levels risk until high and very high levels of risks attribution to anthropogenic climate change (Cramer et al., 2014). A by 1.2°C (Section 3.4.4 and Box 3.4). This assessment considered the more recent analysis of attribution to greenhouse gas forcing at the heatwave-related loss of 50% of shallow water corals across hundreds global scale (Hansen and Stone, 2016) confirmed that the impacts of kilometres of the world’s largest continuous coral reef system, related to changes in regional atmospheric and ocean temperature can the Great Barrier Reef, as well as losses at other sites globally. The be confidently attributed to anthropogenic forcing, while attribution major increase in the size and loss of coral reefs over the past three to anthropogenic forcing of those impacts related to precipitation is years, plus sequential mass coral bleaching and mortality events on 3 only weakly evident or absent. Moreover, there is no strong direct the Great Barrier Reef, (Hoegh-Guldberg, 1999; Hughes et al., 2017b, relationship between the robustness of climate attribution and that of 2018), have reinforced the scale of climate-change related risks to impact attribution (Hansen and Stone, 2016). coral reefs. General assessments of climate-related risks for mangroves prior to this special report concluded that they face greater risks from The current synthesis is complementary to the synthesis in Section 3.5.2 deforestation and unsustainable coastal development than from that categorizes risks into ‘Reasons for Concern’ (RFCs), as described in climate change (Alongi, 2008; Hoegh-Guldberg et al., 2014; Gattuso et Oppenheimer et al. (2014). Each element, or burning ember, presented al., 2015). Recent climate-related die-offs (Duke et al., 2017; Lovelock here (Figures 3.18, 3.20) maps to one or more RFCs (Figure 3.21). It et al., 2017), however, suggest that climate change risks may have should be emphasized that risks to the elements assessed here are been underestimated for mangroves as well, and risks have thus been only a subset of the full range of risks that contribute to the RFCs. assessed as undetectable to moderate, with the transition now starting Figures 3.18 and 3.20 are not intended to replace the RFCs but rather at 1.3°C as opposed to 1.8°C as assessed in 2015 (Gattuso et al., 2015). to indicate how risks to particular elements of the Earth system accrue Risks of impacts related to climate change on small-scale fisheries at with global warming, through the visual burning embers format, low latitudes, many of which are dependent on ecosystems such as with a focus on levels of warming of 1.5°C and 2°C. Key evidence coral reefs and mangroves, are moderate today but are expected to assessed in earlier parts of this chapter is summarized to indicate the reach high levels of risk around 0.9°C–1.1°C (high confidence) (Section transition points between the levels of risk. In this regard, the assessed 3.4.4.10). confidence in assigning the transitions between risk levels are as follows: L=Low, M=Medium, H=High, and VH=Very high levels of The transition from undetectable to moderate risk (related to RFCs 3 confidence. A detailed account of the procedures involved is provided and 4), shown as white to yellow in Figure 3.20, is based on AR5 WGII in the Supplementary Material (3.SM.3.2 and 3.SM.3.3). Chapter 7, which indicated with high confidence that climate change impacts on crop yields have been detected and attributed to climate In terrestrial ecosystems (feeding into RFC1 and RFC4), detection and change, and the current assessment has provided further evidence attribution studies show that impacts of climate change on terrestrial to confirm this (Section 3.4.6). Impacts have been detected in the ecosystems began to take place over the past few decades, indicating tropics (AR5 WGII Chapters 7 and 18), and regional risks are projected a transition from no risk (white areas in Figure 3.20) to moderate risk to become high in some regions by 1.5°C of warming, and in many below recent temperatures (high confidence) (Section 3.4.3). Risks to regions by 2.5°C, indicating a transition from moderate to high risk unique and threatened terrestrial ecosystems are generally projected to between 1.5°C and 2.5°C of warming (medium confidence). be higher under warming of 2°C compared to 1.5°C (Section 3.5.2.1), while at the global scale severe and widespread risks are projected Impacts from fluvial flooding (related to RFCs 2, 3 and 4) depend on to occur by 2°C of warming. These risks are associated with biome the frequency and intensity of the events, as well as the extent of shifts and species range losses (Sections 3.4.3 and 3.5.2.4); however, exposure and vulnerability of society (i.e., socio-economic conditions because many systems and species are projected to be unable to adapt and the effect of non-climate stressors). Moderate risks posed by to levels of warming below 2°C, the transition to high risk (red areas 1.5°C of warming are expected to continue to increase with higher 251 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems levels of warming (Sections 3.3.5 and 3.4.2), with projected risks being risk (Section 3.4.5). With 2.5°C of warming, adaptation limits are threefold the current risk in economic damages due to flooding in 19 expected to be exceeded in sensitive areas, and hence a transition to countries for warming of 2°C, indicating a transition to high risk at very high risk is projected. Additionally, at this temperature, sea level this level (medium confidence). Because few studies have assessed the rise could have adverse effects for centuries, posing significant risk to potential to adapt to these risks, there was insufficient evidence to low-lying areas (high confidence) (Sections 3.4.5.7 and 3.5.2.5). locate a transition to very high risk (purple). For heat-related morbidity and mortality (related to RFCs 2, 3 and 4), Climate-change induced sea level rise (SLR) and associated coastal detection and attribution studies show heat-related mortality in some flooding (related to RFCs 2, 3 and 4) have been detectable and locations increasing with climate change (high confidence) (Section attributable since approximately 1970 (Slangen et al., 2016), during 3.4.7; Ebi et al., 2017). The projected risks of heat-related morbidity and which time temperatures have risen by 0.3°C (medium confidence) mortality are generally higher under warming of 2°C than 1.5°C (high (Section 3.3.9). Analysis suggests that impacts could be more confidence), with projections of greater exposure to high ambient widespread in sensitive systems such as small islands (high confidence) temperatures and increased morbidity and mortality (Section 3.4.7). (Section 3.4.5.3) and increasingly widespread by the 2070s (Brown Risk levels will depend on the rate of warming and the (related) level of et al., 2018a) as temperatures rise from 1.5°C to 2°C, even when adaptation, so a transition in risk from moderate (yellow) to high (red) adaptation measures are considered, suggesting a transition to high is located between 1°C and 3°C (medium confidence). Risks and/or impacts for specific natural, managed and human systems The key elements are presented here as a function of the risk level assessed between 1.5°C and 2°C. Purple indicates very high risks of severe impacts and 3 H the presence of significant Very high irreversibility or the H 2.0 persistence of climate-related H H hazards, combined with 1.5 High limited ability to adapt due to H H the nature of the hazard or 1.0 VH H M 2006-2015 Moderate impacts/risks. H Red indicates severe and VH H H widespread impacts/risks. H M Undetectable Yellow indicates that 0 Warm-water Artic Coastal Small scale Terrestrial Index: Level of additional impacts/risks are detectable corals, (including flooding fisheries Ecosystems risk due to climate change and attributable to climate Coral reefs ocean area (low latitude) change with at least medium and sea ice) confidence. White indicates that no impacts are detectable and attributable to climate M M change. 2.0 MM M 1.5 M M 1.0 H 2006-2015 M H H 0 Fluvial Crop Heat-related Tourism Ability to achieve Mangroves Flooding Yields morbidity Sustainable and mortality Development Goals (SDGs) Confidence level for transition: L=Low, M=Medium, H=High and VH=Very high Figure 3.20 | The dependence of risks and/or impacts associated with selected elements of human and natural systems on the level of climate change, adapted from Figure 3.21 and from AR5 WGII Chapter 19, Figure 19.4, and highlighting the nature of this dependence between 0°C and 2°C warming above pre-industrial levels. The selection of impacts and risks to natural, managed and human systems is illustrative and is not intended to be fully comprehensive. Following the approach used in AR5, literature was used to make expert judgements to assess the levels of global warming at which levels of impact and/or risk are undetectable (white), moderate (yellow), high (red) or very high (purple). The colour scheme thus indicates the additional risks due to climate change. The transition from red to purple, introduced for the first time in AR4, is defined by a very high risk of severe impacts and the presence of significant irreversibility or persistence of climate-related hazards combined with limited ability to adapt due to the nature of the hazard or impact. Comparison of the increase of risk across RFCs indicates the relative sensitivity of RFCs to increases in GMST. As was done previously, this assessment takes autonomous adaptation into account, as well as limits to adaptation independently of development pathway. The levels of risk illustrated reflect the judgements of the authors of Chapter 3 and Gattuso et al. (2015; for three marine elements). The grey bar represents the range of GMST for the most recent decade: 2006–2015. 252 Global mean surface temperature change Global mean surface temperature change relative to pre-industrial levels (0C) relative to pre-industrial levels (0C) Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 For tourism (related to RFCs 3 and 4), changing weather patterns, of Oppenheimer et al. (2014) was adopted, with updates to the extreme weather and climate events, and sea level rise are affecting aggregation of risk informed by the most recent literature, for the many – but not all – global tourism investments, as well as analysis of avoided impacts at 1.5°C compared to 2°C of global environmental and cultural destination assets (Section 3.4.4.12), with warming presented in this section. ‘last chance to see’ tourism markets developing based on observed impacts on environmental and cultural heritage (Section 3.4.9.1), The regional economic benefits that could be obtained by limiting the indicating a transition from undetectable to moderate risk between global temperature increase to 1.5°C of warming, rather than 2°C 0°C and 1.5°C of warming (high confidence). Based on limited or higher levels, are discussed in Section 3.5.3 in the light of the five analyses, risks to the tourism sector are projected to be larger at 2°C RFCs explored in Section 3.5.2. Climate change hotspots that could than at 1.5°C, with impacts on climate-sensitive sun, beach and snow be avoided or reduced by achieving the 1.5°C target are summarized sports tourism markets being greatest. The degradation or loss of in Section 3.5.4. The section concludes with a discussion of regional coral reef systems is expected to increase the risks to coastal tourism tipping points that could be avoided at 1.5°C compared to higher in subtropical and tropical regions. A transition in risk from moderate degrees of global warming (Section 3.5.5). to high levels of added risk from climate change is projcted to occur between 1.5°C and 3°C (medium confidence). 3.5.2 Aggregated Avoided Impacts and Reduced Risks at 1.5°C versus 2°C of Global Warming Climate change is already having large scale impacts on ecosystems, human health and agriculture, which is making it much more difficult A brief summary of the accrual of RFCs with global warming, as to reach goals to eradicate poverty and hunger, and to protect health assessed in WGII AR5, is provided in the following sections, which and life on land (Sections 5.1 and 5.2.1 in Chapter 5), suggesting a leads into an update of relevant literature published since AR5. The transition from undetectable to moderate risk for recent temperatures new literature is used to confirm the levels of global warming at which at 0.5°C of warming (medium confidence). Based on the limited risks are considered to increase from undetectable to moderate, from analyses available, there is evidence and agreement that the risks moderate to high, and from high to very high. Figure 3.21 modifies to sustainable development are considerably less at 1.5°C than 2°C Figure 19.4 from AR5 WGII, and the following text in this subsection 3 (Section 5.2.2), including impacts on poverty and food security. It is provides justification for the modifications. O’Neill et al. (2017) easier to achieve many of the sustainable development goals (SDGs) at presented a very similar assessment to that of WGII AR5, but with 1.5°C, suggesting that a transition to higher risk will not begin yet at further discussion of the potential to create ‘embers’ specific to socio- this level. At 2°C and higher levels of warming (e.g., RCP8.5), however, economic scenarios in the future. There is insufficient literature to there are high risks of failure to meet SDGs such as eradicating do this at present, so the original, simple approach has been used poverty and hunger, providing safe water, reducing inequality and here. As the focus of the present assessment is on the consequences protecting ecosystems, and these risks are projected to become severe of global warming of 1.5°C–2°C above the pre-industrial period, no and widespread if warming increases further to about 3°C (medium assessment for global warming of 3°C or more is included in the confidence) (Section 5.2.3). figure (i.e., analysis is discontinued at 2.5°C). Disclosure statement: The selection of elements depicted in Figures 3.5.2.1 RFC 1 – Unique and threatened systems 3.18 and 3.20 is not intended to be fully comprehensive and does not necessarily include all elements for which there is a substantive body WGII AR5 Chapter 19 found that some unique and threatened of literature, nor does it necessarily include all elements which are of systems are at risk from climate change at current temperatures, particular interest to decision-makers. with increasing numbers of systems at potential risk of severe consequences at global warming of 1.6°C above pre-industrial levels. It was also observed that many species and ecosystems have a limited ability to adapt to the very large risks associated with warming of 3.5 Avoided Impacts and Reduced Risks 2.6°C or more, particularly Arctic sea ice and coral reef systems (high at 1.5°C Compared with 2°C confidence). In the AR5 analysis, a transition from white to yellow of Global Warming indicated that the onset of moderate risk was located below present- day global temperatures (medium confidence); a transition from 3.5.1 Introduction yellow to red indicated that the onset of high risk was located at 1.6°C, and a transition from red to purple indicated that the onset Oppenheimer et al. (2014, AR5 WGII Chapter 19) provided a framework of very high risk was located at about 2.6°C. This WGII AR5 analysis that aggregates projected risks from global mean temperature already implied that there would be a significant reduction in risks change into five categories identified as ‘Reasons for Concern’. Risks to unique and threatened systems if warming were limited to 1.5°C are classified as moderate, high or very high and coloured yellow, compared with 2°C. Since AR5, evidence of present-day impacts in red or purple, respectively, in Figure 19.4 of that chapter (AR5 WGII these systems has continued to grow (Sections 3.4.2, 3.4.4 and 3.4. Chapter 19 for details and findings). The framework’s conceptual 5), whilst new evidence has also accumulated for reduced risks at basis and the risk judgements made by Oppenheimer et al. (2014) 1.5°C compared to 2°C of warming in Arctic ecosystems (Section were recently reviewed, and most judgements were confirmed in the 3.3.9), coral reefs (Section 3.4.4) and some other unique ecosystems light of more recent literature (O’Neill et al., 2017). The approach (Section 3.4.3), as well as for biodiversity. 253 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Figure 3.21 | The dependence of risks and/or impacts associated with the Reasons for Concern (RFCs) on the level of climate change, updated and adapted from WGII AR5 Ch 19, Figure 19.4 and highlighting the nature of this dependence between 0°C and 2°C warming above pre-industrial levels. As in the AR5, literature was used to make expert judgements to assess the levels of global warming at which levels of impact and/or risk are undetectable (white), moderate (yellow), high (red) or very high (purple). The colour scheme thus indicates the additional risks due to climate change. The transition from red to purple, introduced for the first time in AR4, is defined by very high risk 3 of severe impacts and the presence of significant irreversibility, or persistence of climate-related hazards combined with a limited ability to adapt due to the nature of the hazard or impact. Comparison of the increase of risk across RFCs indicates the relative sensitivity of RFCs to increases in GMST. As was done previously, this assessment takes autonomous adaptation into account, as well as limits to adaptation (RFC 1, 3, 5) independently of development pathway. The rate and timing of impacts were taken into account in assessing RFC 1 and 5. The levels of risk illustrated reflect the judgements of the Ch 3 authors. RFC1 Unique and threatened systems: ecological and human systems that have restricted geographic ranges constrained by climate related conditions and have high endemism or other distinctive properties. Examples include coral reefs, the Arctic and its indigenous people, mountain glaciers and biodiversity hotspots. RFC2 Extreme weather events: risks/impacts to human health, livelihoods, assets and ecosystems from extreme weather events such as heatwaves, heavy rain, drought and associated wildfires, and coastal flooding. RFC3 Distribution of impacts: risks/impacts that disproportionately affect particular groups due to uneven distribution of physical climate change hazards, exposure or vulnerability. RFC4 Global aggregate impacts: global monetary damage, global scale degradation and loss of ecosystems and biodiversity. RFC5 Large-scale singular events: are relatively large, abrupt and sometimes irreversible changes in systems that are caused by global warming. Examples include disintegration of the Greenland and Antarctic ice sheets. The grey bar represents the range of GMST for the most recent decade: 2006–2015. New literature since AR5 has provided a closer focus on the comparative yet chances of an ice-free Arctic during summer being high at 2°C of levels of risk to coral reefs at 1.5°C versus 2°C of global warming. As warming (Section 3.3.8). Less of the permafrost in the Arctic is projected assessed in Section 3.4.4 and Box 3.4, reaching 2°C will increase the to thaw under 1.5°C of warming (17–44%) compared with under 2°C frequency of mass coral bleaching and mortality to a point at which it (28–53%) (Section 3.3.5.2; Chadburn et al., 2017), which is expected will result in the total loss of coral reefs from the world’s tropical and to reduce risks to both social and ecological systems in the Arctic. This subtropical regions. Restricting overall warming to 1.5°C will still see indicates a transition in the risk in this system from high to very high a downward trend in average coral cover (70–90% decline by mid- between 1.5°C and 2°C of warming and contributes to a lowering of century) but will prevent the total loss of coral reefs projected with the transition from high to very high in this RFC1 compared to in AR5. warming of 2°C (Frieler et al., 2013). The remaining reefs at 1.5°C will also benefit from increasingly stable ocean conditions by the mid-to- AR5 identified a large number of threatened systems, including mountain late 21st century. Limiting global warming to 1.5°C during the course ecosystems, highly biodiverse tropical wet and dry forests, deserts, of the century may, therefore, open the window for many ecosystems freshwater systems and dune systems. These include Mediterranean to adapt or reassort geographically. This indicates a transition in risk areas in Europe, Siberian, tropical and desert ecosystems in Asia, in this system from high to very high (high confidence) at 1.5°C of Australian rainforests, the Fynbos and succulent Karoo areas of South warming and contributes to a lowering of the transition from high to Africa, and wetlands in Ethiopia, Malawi, Zambia and Zimbabwe. In all very high (Figure 3.21) in this RFC1 compared to in AR5. Further details these systems, impacts accrue with greater warming and impacts at 2°C of risk transitions for ocean systems are described in Figure 3.18. are expected to be greater than those at 1.5°C (medium confidence). One study since AR5 has shown that constraining global warming to Substantial losses of Arctic Ocean summer ice were projected in 1.5°C would maintain the functioning of prairie pothole ecosystems WGI AR5 for global warming of 1.6°C, with a nearly ice-free Arctic in North America in terms of their productivity and biodiversity, whilst Ocean being projected for global warming of more than 2.6°C. warming of 2°C would not do so (Johnson et al., 2016). The large Since AR5, the importance of a threshold between 1°C and 2°C has proportion of insects projected to lose over half their range at 2°C of been further emphasized in the literature, with sea ice projected to warming (25%) compared to at 1.5°C (9%) also suggests a significant persist throughout the year for a global warming of less than 1.5°C, loss of functionality in these threatened systems at 2°C of warming, 254 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 owing to the critical role of insects in nutrient cycling, pollination, assessment. It concluded with medium confidence that anthropogenic detritivory and other important ecosystem processes (Section 3.4.3). forcing has contributed to a global-scale intensification of heavy precipitation over the second half of the 20th century, for a global Unique and threatened systems in small island states and in systems warming of approximately 0.5°C (Section 3.3.3). A recent observation- fed by glacier meltwater were also considered to contribute to this based study likewise showed that a 0.5°C increase in global mean RFC in AR5, but there is little new information about these systems temperature has had a detectable effect on changes in precipitation that pertains to 1.5°C or 2°C of global warming. Taken together, the extremes at the global scale (Schleussner et al., 2017), thus suggesting evidence suggests that the transition from high to very high risk in that there would be detectable differences in heavy precipitation at unique and threatened systems occurs at a lower level of warming, 1.5°C and 2°C of global warming. These results are consistent with between 1.5°C and 2°C (high confidence), than in AR5, where this analyses of climate projections, although they also highlight a large transition was located at 2.6°C. The transition from moderate to high amount of regional variation in the sensitivity of changes in heavy risk relocates very slightly from 1.6°C to 1.5°C (high confidence). There precipitation (Section 3.3.3). is also high confidence in the location of the transition from low to moderate risk below present-day global temperatures. Droughts: When considering the difference between precipitation and evaporation (P–E) as a function of global temperature changes, the 3.5.2.2 RFC 2 – Extreme weather events subtropics generally display an overall trend towards drying, whilst the northern high latitudes display a robust response towards increased Reduced risks in terms of the likelihood of occurrence of extreme wetting (Section 3.3.4, Figure 3.12). Limiting global mean temperature weather events are discussed in this sub-subsection for 1.5°C as increase to 1.5°C as opposed to 2°C could substantially reduce the risk compared to 2°C of global warming, for those extreme events where of reduced regional water availability in some regions (Section 3.3.4). evidence is currently available based on the assessments of Section 3.3. Regions that are projected to benefit most robustly from restricted AR5 assigned a moderate level of risk from extreme weather events at warming include the Mediterranean and southern Africa (Section recent temperatures (1986–2005) owing to the attribution of heat and 3.3.4). precipitation extremes to climate change, and a transition to high risk 3 beginning below 1.6°C of global warming based on the magnitude, Fire: Increasing evidence that anthropogenic climate change has likelihood and timing of projected changes in risk associated with already caused significant increases in fire area globally (Section extreme events, indicating more severe and widespread impacts. 3.4.3) is in line with projected fire risks. These risks are projected to The AR5 analysis already suggested a significant benefit of limiting increase further under 1.5°C of global warming relative to the present warming to 1.5°C, as doing so might keep risks closer to the moderate day (Section 3.4.3). Under 1.2°C of global warming, fire frequency level. New literature since AR5 has provided greater confidence in a has been estimated to increase by over 37.8% of global land areas, reduced level of risks due to extreme weather events at 1.5°C versus compared to 61.9% of global land areas under 3.5°C of warming. For 2°C of warming for some types of extremes (Section 3.3 and below; in-depth discussion and uncertainty estimates, see Meehl et al. (2007), Figure 3.21). Moritz et al. (2012) and Romero-Lankao et al. (2014). Temperature: It is expected that further increases in the number of Regarding extreme weather events (RFC2), the transition from warm days/nights and decreases in the number of cold days/nights, moderate to high risk is located between 1°C and 1.5°C of global and an increase in the overall temperature of hot and cold extremes warming (Figure 3.21), which is very similar to the AR5 assessment but would occur under 1.5°C of global warming relative to pre-industrial is assessed with greater confidence (medium confidence). The impact levels (high confidence) compared to under the present-day climate literature contains little information about the potential for human (1°C of warming), with further changes occurring towards 2°C of society to adapt to extreme weather events, and hence it has not been global warming (Section 3.3). As assessed in Sections 3.3.1 and 3.3.2, possible to locate the transition from high to very high risk within the impacts of 0.5°C of global warming can be identified for temperature context of assessing impacts at 1.5°C and 2°C of global warming. extremes at global scales, based on observations and the analysis of There is thus low confidence in the level at which global warming could climate models. At 2°C of global warming, it is likely that temperature lead to very high risks associated with extreme weather events in the increases of more than 2°C would occur over most land regions in context of this report. terms of extreme temperatures (up to 4°C–6°C depending on region and considered extreme index) (Section 3.3.2, Table 3.2). Regional 3.5.2.3 RFC 3 – Distribution of impacts increases in temperature extremes can be robustly limited if global warming is constrained to 1.5°C, with regional warmings of up to Risks due to climatic change are unevenly distributed and are 3°C–4.5°C (Section 3.3.2, Table 3.2). Benefits obtained from this generally greater at lower latitudes and for disadvantaged people and general reduction in extremes depend to a large extent on whether the communities in countries at all levels of development. AR5 located lower range of increases in extremes at 1.5°C is sufficient for critical the transition from undetectable to moderate risk below recent thresholds to be exceeded, within the context of wide-ranging aspects temperatures, owing to the detection and attribution of regionally such as crop yields, human health and the sustainability of ecosystems. differentiated changes in crop yields (medium to high confidence; Figure 3.20), and new literature has continued to confirm this finding. Heavy precipitation: AR5 assessed trends in heavy precipitation Based on the assessment of risks to regional crop production and for land regions where observational coverage was sufficient for water resources, AR5 located the transition from moderate to high risk 255 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems between 1.6°C and 2.6°C above pre-industrial levels. Cross-Chapter and 87% (74–91%) from 2°C rather than 3.66°C. In the second Box 6 in this chapter highlights that at 2°C of warming, new literature study, Pretis et al. (2018) identified several regions where economic shows that risks of food shortage are projected to emerge in the African damages are projected to be greater at 2°C compared to 1.5°C of Sahel, the Mediterranean, central Europe, the Amazon, and western and warming, further estimating that projected damages at 1.5°C remain southern Africa, and that these are much larger than the corresponding similar to today’s levels of economic damage. The third study, by M. risks at 1.5°C. This suggests a transition from moderate to high risk of Burke et al. (2018) used an empirical, statistical approach and found regionally differentiated impacts between 1.5°C and 2°C above pre- that limiting warming to 1.5°C instead of 2°C would save 1.5–2.0% industrial levels for food security (medium confidence) (Figure 3.20). of the gross world product (GWP) by mid-century and 3.5% of the Reduction in the availability of water resources at 2°C is projected to GWP by end-of-century (see Figure 2A in M. Burke et al., 2018). be greater than 1.5°C of global warming, although changes in socio- Based on a 3% discount rate, this corresponds to 8.1–11.6 trillion economics could have a greater influence (Section 3.4.2), with larger USD and 38.5 trillion USD in avoided damages by mid- and end-of- risks in the Mediterranean (Box 3.2); estimates of the magnitude of the century, respectively, agreeing closely with the estimate by Warren et risks remain similar to those cited in AR5. Globally, millions of people al. (2018c) of 15 trillion USD. Under the no-policy baseline scenario, may be at risk from sea level rise (SLR) during the 21st century (Hinkel temperature rises by 3.66°C by 2100, resulting in a global gross et al., 2014; Hauer et al., 2016), particularly if adaptation is limited. At domestic product (GDP) loss of 2.6% (5–95% percentile range 0.5– 2°C of warming, more than 90% of global coastlines are projected to 8.2%), compared with 0.3% (0.1–0.5%) by 2100 under the 1.5°C experience SLR greater than 0.2 m, suggesting regional differences in scenario and 0.5% (0.1–1.0%) in the 2°C scenario. Limiting warming the risks of coastal flooding. Regionally differentiated multi-sector risks to 1.5°C rather than 2°C by 2060 has also been estimated to result are already apparent at 1.5°C of warming, being more prevalent where in co-benefits of 0.5–0.6% of the world GDP, owing to reductions in vulnerable people live, predominantly in South Asia (mostly Pakistan, air pollution (Shindell et al., 2018), which is similar to the avoided India and China), but these risks are projected to spread to sub-Saharan damages identified for the USA (Box 3.6). Africa, the Middle East and East Asia as temperature rises, with the world’s poorest people disproportionately impacted at 2°C of warming Two studies focusing only on the USA found that economic damages 3 (Byers et al., 2018). The hydrological impacts of climate change in are projected to be higher by 2100 if warming reaches 2°C than if it Europe are projected to increase in spatial extent and intensity across is constrained to 1.5°C. Hsiang et al. (2017) found a mean difference increasing global warming levels of 1.5°C, 2°C and 3°C (Donnelly et of 0.35% GDP (range 0.2–0.65%), while Yohe (2017) identified a GDP al., 2017). Taken together, a transition from moderate to high risk is loss of 1.2% per degree of warming, hence approximately 0.6% for half now located between 1.5°C and 2°C above pre-industrial levels, based a degree. Further, the avoided risks compared to a no-policy baseline on the assessment of risks to food security, water resources, drought, are greater in the 1.5°C case (4%, range 2–7%) compared to the 2°C heat exposure and coastal submergence (high confidence; Figure 3.21). case (3.5%, range 1.8–6.5%). These analyses suggest that the point at which global aggregates of economic impacts become negative is 3.5.2.4 RFC 4 – Global aggregate impacts below 2°C (medium confidence), and that there is a possibility that it is below 1.5°C of warming. Oppenheimer et al. (2014) explained the inclusion of non-economic metrics related to impacts on ecosystems and species at the global Oppenheimer et al. (2014) noted that the global aggregated damages level, in addition to economic metrics in global aggregate impacts. associated with large-scale singular events has not been explored, and The degradation of ecosystem services by climate change and ocean reviews of integrated modelling exercises have indicated a potential acidification have generally been excluded from previous global underestimation of global aggregate damages due to the lack of aggregate economic analyses. consideration of the potential for these events in many studies. Since AR5, further analyses of the potential economic consequences of Global economic impacts: WGII AR5 found that overall global triggering these large-scale singular events have indicated a two to aggregate impacts become moderate at 1°C–2°C of warming, and the eight fold larger economic impact associated with warming of 3°C transition to moderate risk levels was therefore located at 1.6°C above than estimated in most previous analyses, with the extent of increase pre-industrial levels. This was based on the assessment of literature depending on the number of events incorporated. Lemoine and Traeger using model simulations which indicated that the global aggregate (2016) included only three known singular events whereas Y. Cai et al. economic impact will become significantly negative between 1°C and (2016) included five. 2°C of warming (medium confidence), whilst there will be a further increase in the magnitude and likelihood of aggregate economic risks Biome shifts, species range loss, increased risks of species at 3°C of warming (low confidence). extinction and risks of loss of ecosystem functioning and services: 13% (range 8–20%) of Earth’s land area is projected to Since AR5, three studies have emerged using two entirely different undergo biome shifts at 2°C of warming compared to approximately approaches which indicate that economic damages are projected to 7% at 1.5°C (medium confidence) (Section 3.4.3; Warszawski et al., be higher by 2100 if warming reaches 2°C than if it is constrained 2013), implying a halving of biome transformations. Overall levels of to 1.5°C. The study by Warren et al. (2018c) used the integrated species loss at 2°C of warming are similar to values found in previous assessment model PAGE09 to estimate that avoided global economic studies for plants and vertebrates (Warren et al., 2013, 2018a), but damages of 22% (10–26%) accrue from constraining warming to insects have been found to be more sensitive to climate change, with 1.5°C rather than 2°C, 90% (77–93%) from 1.5°C rather than 3.66°C, 18% (6–35%) projected to lose over half their range at 2°C of warming 256 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 compared to 6% (1–18%) under 1.5°C of warming, corresponding temperature increase that may initiate irreversible loss of the West to a difference of 66% (Section 3.4.3). The critical role of insects in Antarctic ice sheet and marine ice sheet instability (MISI) is estimated ecosystem functioning therefore suggests that there will be impacts to lie be between 1.5°C and 2°C. The time scale for eventual loss of the on global ecosystem functioning already at 2°C of warming, whilst ice sheets varies between millennia and tens of millennia and assumes species that lose large proportions of their range are considered to constant surface temperature forcing during this period. If temperature be at increased risk of extinction (Section 3.4.3.3). Since AR5, new were to decline subsequently the ice sheets might regrow, although literature has indicated that impacts on marine fish stocks and fisheries the amount of cooling required is likely to be highly dependent on the are lower under 1.5°C–2°C of global warming relative to pre-industrial duration and rate of the previous retreat. The magnitude of global sea levels compared to under higher warming scenarios (Section 3.4.6), level rise that could occur over the next two centuries under 1.5°C–2°C especially in tropical and polar systems. of global warming is estimated to be in the order of several tenths of a metre according to most studies (low confidence) (Schewe et al., 2011; In AR5, the transition from undetectable to moderate impacts was Church et al., 2013; Levermann et al., 2014; Marzeion and Levermann, considered to occur between 1.6°C and 2.6°C of global warming 2014; Fürst et al., 2015; Golledge et al., 2015), although a smaller reflecting impacts on the economy and on biodiversity globally, whereas number of investigations (Joughin et al., 2014; Golledge et al., 2015; high risks were associated with 3.6°C of warming to reflect the high DeConto and Pollard, 2016) project increases of 1–2 m. This body of risks to biodiversity and accelerated effects on the global economy. evidence suggests that the temperature range of 1.5°C–2°C may be New evidence suggests moderate impacts on the global aggregate regarded as representing moderate risk, in that it may trigger MISI in economy and global biodiversity by 1.5°C of warming, suggesting a Antarctica or irreversible loss of the Greenland ice sheet and it may be lowering of the temperature level for the transition to moderate risk associated with sea level rise by as much as 1–2 m over a period of to 1.5°C (Figure 3.21). Further, recent literature points to higher risks two centuries. than previously assessed for the global aggregate economy and global biodiversity by 2°C of global warming, suggesting that the transition Thermohaline circulation (slowdown of AMOC): It is more likely to a high risk level is located between 1.5°C and 2.5°C of warming than not that the AMOC has been weakening in recent decades, (Figure 3.21), as opposed to at 3.6°C as previously assessed (medium given the detection of cooling of surface waters in the North Atlantic 3 confidence). and evidence that the Gulf Stream has slowed since the late 1950s (Rahmstorf et al., 2015b; Srokosz and Bryden, 2015; Caesar et al., 3.5.2.5 RFC 5 – Large-scale singular events 2018). There is limited evidence linking the recent weakening of the AMOC to anthropogenic warming (Caesar et al., 2018). It is very likely Large-scale singular events are components of the global Earth system that the AMOC will weaken over the 21st century. Best estimates and that are thought to hold the risk of reaching critical tipping points ranges for the reduction based on CMIP5 simulations are 11% (1–24%) under climate change, and that can result in or be associated with in RCP2.6 and 34% (12–54%) in RCP8.5 (AR5). There is no evidence major shifts in the climate system. These components include: indicating significantly different amplitudes of AMOC weakening for 1.5°C versus 2°C of global warming, or of a shutdown of the AMOC at • the cryosphere: West Antarctic ice sheet, Greenland ice sheet these global temperature thresholds. Associated risks are classified as • the thermohaline circulation: slowdown of the Atlantic Meridional low to moderate. Overturning Circulation (AMOC) • the El Niño–Southern Oscillation (ENSO) as a global mode of El Niño–Southern Oscillation (ENSO): Extreme El Niño events are climate variability associated with significant warming of the usually cold eastern Pacific • role of the Southern Ocean in the global carbon cycle Ocean, and they occur about once every 20 years (Cai et al., 2015). Such events reorganize the distribution of regions of organized convection AR5 assessed that the risks associated with these events become and affect weather patterns across the globe. Recent research indicates moderate between 0.6°C and 1.6°C above pre-industrial levels, based that the frequency of extreme El Niño events increases linearly with the on early warning signs, and that risk was expected to become high global mean temperature, and that the number of such events might between 1.6°C and 4.6°C based on the potential for commitment to double (one event every ten years) under 1.5°C of global warming (G. large irreversible sea level rise from the melting of land-based ice sheets Wang et al., 2017). This pattern is projected to persist for a century after (low to medium confidence). The increase in risk between 1.6°C and stabilization at 1.5°C, thereby challenging the limits to adaptation, and 2.6°C above pre-industrial levels was assessed to be disproportionately thus indicates high risk even at the 1.5°C threshold. La Niña event large. New findings since AR5 are described in detail below. (the opposite or balancing event to El Niño) frequency is projected to remain similar to that of the present day under 1.5°C–2°C of global Greenland and West Antarctic ice sheets and marine ice sheet warming. instability (MISI): Various feedbacks between the Greenland ice sheet and the wider climate system, most notably those related to Role of the Southern Ocean in the global carbon cycle: The critical the dependence of ice melt on albedo and surface elevation, make role of the Southern Ocean as a net sink of carbon might decline under irreversible loss of the ice sheet a possibility. Church et al. (2013) global warming, and assessing this effect under 1.5°C compared to assessed this threshold to be at 2°C of warming or higher levels relative 2°C of global warming is a priority. Changes in ocean chemistry (e.g., to pre-industrial temperature. Robinson et al. (2012) found a range for oxygen content and ocean acidification), especially those associated this threshold of 0.8°C–3.2°C (95% confidence). The threshold of global with the deep sea, are associated concerns (Section 3.3.10). 257 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems For large-scale singular events (RFC5), moderate risk is now located The world’s largest economies are also projected to benefit from at 1°C of warming and high risk is located at 2.5°C (Figure 3.21), as restricting warming to 1.5°C as opposed to 2°C (medium confidence), opposed to at 1.6°C (moderate risk) and around 4°C (high risk) in with the likelihood of such benefits being realized estimated at AR5, because of new observations and models of the West Antarctic 76%, 85% and 81% for the USA, China and Japan, respectively (M. ice sheet (medium confidence), which suggests that the ice sheet Burke et al., 2018). Two studies focusing only on the USA found that may be in the early stages of marine ice sheet instability (MISI). economic damages are projected to be higher by 2100 if warming Very high risk is assessed as lying above 5°C because the growing reaches 2°C than if it is constrained to 1.5°C. Yohe (2017) found a literature on process-based projections of the West Antarctic ice sheet mean difference of 0.35% GDP (range 0.2–0.65%), while Hsiang predominantly supports the AR5 assessment of an MISI contribution of et al. (2017) identified a GDP loss of 1.2% per degree of warming, several additional tenths of a metre by 2100. hence approximately 0.6% for half a degree. Overall, no statistically significant changes in GDP are projected to occur over most of the 3.5.3 Regional Economic Benefit Analysis for the 1.5°C developed world under 1.5°C of global warming in comparison to versus 2°C Global Goals present-day conditions, but under 2°C of global warming impacts on GDP are projected to be generally negative (low confidence) (Pretis This section reviews recent literature that has estimated the economic et al., 2018). benefits of constraining global warming to 1.5°C compared to 2°C. The focus here is on evidence pertaining to specific regions, rather A caveat to the analyses of Pretis et al. (2018) and M. Burke et al. than on global aggregated benefits (Section 3.5.2.4). At 2°C of global (2018) is that the effects of sea level rise were not included in the warming, lower economic growth is projected for many countries than estimations of damages or future economic growth, implying a potential at 1.5°C of global warming, with low-income countries projected to underestimation of the benefits of limiting warming to 1.5°C for the experience the greatest losses (low to medium confidence) (M. Burke case where significant sea level rise is avoided at 1.5°C but not at 2°C. et al., 2018; Pretis et al., 2018). A critical issue for developing countries in particular is that advantages in some sectors are projected to be 3.5.4 Reducing Hotspots of Change for 1.5°C and 2°C 3 offset by increasing mitigation costs (Rogelj et al., 2013; M. Burke et of Global Warming al., 2018), with food production being a key factor. That is, although restraining the global temperature increase to 2°C is projected to This subsection integrates Sections 3.3 and 3.4 in terms of climate- reduce crop losses under climate change relative to higher levels of change-induced hotspots that occur through interactions across the warming, the associated mitigation costs may increase the risk of physical climate system, ecosystems and socio-economic human hunger in low-income countries (low confidence) (Hasegawa et al., systems, with a focus on the extent to which risks can be avoided or 2016). It is likely that the even more stringent mitigation measures reduced by achieving the 1.5°C global warming goal (as opposed to required to restrict global warming to 1.5°C (Rogelj et al., 2013) will the 2°C goal). Findings are summarized in Table 3.6. further increase these mitigation costs and impacts. International trade in food might be a key response measure for alleviating hunger 3.5.4.1 Arctic sea ice in developing countries under 1.5°C and 2°C stabilization scenarios (IFPRI, 2018). Ice-free Arctic Ocean summers are very likely at levels of global warming higher than 2°C (Notz and Stroeve, 2016; Rosenblum and Although warming is projected to be the highest in the Northern Eisenman, 2016; Screen and Williamson, 2017; Niederdrenk and Hemisphere under 1.5°C or 2°C of global warming, regions in Notz, 2018). Some studies even indicate that the entire Arctic Ocean the tropics and Southern Hemisphere subtropics are projected to summer period will become ice free under 2°C of global warming, experience the largest impacts on economic growth (low to medium whilst others more conservatively estimate this probability to be in the confidence) (Gallup et al., 1999; M. Burke et al., 2018; Pretis et al., order of 50% (Section 3.3.8; Sanderson et al., 2017). The probability 2018). Despite the uncertainties associated with climate change of an ice-free Arctic in September at 1.5°C of global warming is low projections and econometrics (e.g., M. Burke et al., 2018), it is more and substantially lower than for the case of 2°C of global warming likely than not that there will be large differences in economic (high confidence) (Section 3.3.8; Screen and Williamson, 2017; Jahn, growth under 1.5°C and 2°C of global warming for developing 2018; Niederdrenk and Notz, 2018). There is, however, a single versus developed countries (M. Burke et al., 2018; Pretis et al., study that questions the validity of the 1.5°C threshold in terms of 2018). Statistically significant reductions in gross domestic product maintaining summer Arctic Ocean sea ice (Niederdrenk and Notz, (GDP) per capita growth are projected across much of the African 2018). In contrast to summer, little ice is projected to be lost during continent, Southeast Asia, India, Brazil and Mexico (low to medium winter for either 1.5°C or 2°C of global warming (medium confidence) confidence). Countries in the western parts of tropical Africa are (Niederdrenk and Notz, 2018). The losses in sea ice at 1.5°C and projected to benefit most from restricting global warming to 1.5°C, 2°C of warming will result in habitat losses for organisms such as as opposed to 2°C, in terms of future economic growth (Pretis et al., seals, polar bears, whales and sea birds (e.g., Larsen et al., 2014). 2018). An important reason why developed countries in the tropics There is high agreement and robust evidence that photosynthetic and subtropics are projected to benefit substantially from restricting species will change because of sea ice retreat and related changes global warming to 1.5°C is that present-day temperatures in these in temperature and radiation (Section 3.4.4.7), and this is very likely regions are above the threshold thought to be optimal for economic to benefit fisheries productivity in the Northern Hemisphere spring production (M. Burke et al., 2015b, 2018). bloom system (Section 3.4.4.7). 258 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 3.5.4.2 Arctic land regions 3.5.4.5 Southern Europe and the Mediterranean In some Arctic land regions, the warming of cold extremes and the The Mediterranean is regarded as a climate change hotspot, both in increase in annual minimum temperature at 1.5°C are stronger than terms of projected stronger warming of the regional land-based hot the global mean temperature increase by a factor of two to three, extremes compared to the mean global temperature increase (e.g., meaning 3°C–4.5°C of regional warming at 1.5°C of global warming Seneviratne et al., 2016) and in terms of of robust increases in the (e.g., northern Europe in Supplementary Material 3.SM, Figure 3.SM.5 probability of occurrence of extreme droughts at 2°C vs 1.5°C global see also Section 3.3.2.2 and Seneviratne et al., 2016). Moreover, over warming (Section 3.3.4). Low river flows are projected to decrease in much of the Arctic, a further increase of 0.5°C in the global surface the Mediterranean under 1.5°C of global warming (Marx et al., 2018), temperature, from 1.5°C to 2°C, may lead to further temperature with associated significant decreases in high flows and floods (Thober increases of 2°C–2.5°C (Figure 3.3). As a consequence, biome (major et al., 2018), largely in response to reduced precipitation. The median ecosystem type) shifts are likely in the Arctic, with increases in fire reduction in annual runoff is projected to almost double from about frequency, degradation of permafrost, and tree cover likely to occur at 9% (likely range 4.5–15.5%) at 1.5°C to 17% (likely range 8–25%) 1.5°C of warming and further amplification of these changes expected at 2°C (Schleussner et al., 2016b). Similar results were found by Döll under 2°C of global warming (e.g., Gerten et al., 2013; Bring et al., et al. (2018). Overall, there is high confidence that strong increases in 2016). Rising temperatures, thawing permafrost and changing weather dryness and decreases in water availability in the Mediterranean and patterns are projected to increasingly impact people, infrastructure and southern Europe would occur from 1.5°C to 2°C of global warming. Sea industries in the Arctic (W.N. Meier et al., 2014) with these impacts level rise is expected to be lower for 1.5°C versus 2°C, lowering risks larger at 2°C than at 1.5°C of warming (medium confidence). for coastal metropolitan agglomerations. The risks (assuming current adaptation) related to water deficit in the Mediterranean are high for 3.5.4.3 Alpine regions global warming of 2°C but could be substantially reduced if global warming were limited to 1.5°C (Section 3.3.4; Guiot and Cramer, 2016; Alpine regions are generally regarded as climate change hotspots Schleussner et al., 2016b; Donnelly et al., 2017). given that rich biodiversity has evolved in their cold and harsh climate, 3 but with many species consequently being vulnerable to increases in 3.5.4.6 West Africa and the Sahel temperature. Under regional warming, alpine species have been found to migrate upwards on mountain slopes (Reasoner and Tinner, 2009), West Africa and the Sahel are likely to experience increases in the an adaptation response that is obviously limited by mountain height number of hot nights and longer and more frequent heatwaves and habitability. Moreover, many of the world’s alpine regions are even if the global temperature increase is constrained to 1.5°C, with important from a water security perspective through associated glacier further increases expected at 2°C of global warming and beyond melt, snow melt and river flow (see Section 3.3.5.2 for a discussion of (e.g., Weber et al., 2018). Moreover, daily rainfall intensity and runoff these aspects). Projected biome shifts are likely to be severe in alpine is expected to increase (low confidence) towards 2°C and higher regions already at 1.5°C of warming and to increase further at 2°C levels of global warming (Schleussner et al., 2016b; Weber et al., (Gerten et al., 2013, Figure 1b; B. Chen et al., 2014). 2018), with these changes also being relatively large compared to the projected changes at 1.5°C of warming. Moreover, increased risks 3.5.4.4 Southeast Asia are projected in terms of drought, particularly for the pre-monsoon season (Sylla et al., 2015), with both rural and urban populations Southeast Asia is a region highly vulnerable to increased flooding in affected, and more so at 2°C of global warming as opposed to 1.5°C the context of sea level rise (Arnell et al., 2016; Brown et al., 2016, (Liu et al., 2018). Based on a World Bank (2013) study for sub-Saharan 2018a). Risks from increased flooding are projected to rise from 1.5°C Africa, a 1.5°C warming by 2030 might reduce the present maize to 2°C of warming (medium confidence), with substantial increases cropping areas by 40%, rendering these areas no longer suitable projected beyond 2°C (Arnell et al., 2016). Southeast Asia displays for current cultivars. Substantial negative impacts are also projected statistically significant differences in projected changes in heavy for sorghum suitability in the western Sahel (Läderach et al., 2013; precipitation, runoff and high flows at 1.5°C versus 2°C of warming, Sultan and Gaetani, 2016). An increase in warming to 2°C by 2040 with stronger increases occurring at 2°C (Section 3.3.3; Wartenburger would result in further yield losses and damages to crops (i.e., maize, et al., 2017; Döll et al., 2018; Seneviratne et al., 2018c); thus, this region sorghum, wheat, millet, groundnut and cassava). Schleussner et al. is considered a hotspot in terms of increases in heavy precipitation (2016b) found consistently reduced impacts on crop yield for West between these two global temperature levels (medium confidence) Africa under 2°C compared to 1.5°C of global warming. There is (Schleussner et al., 2016b; Seneviratne et al., 2016). For Southeast Asia, medium confidence that vulnerabilities to water and food security in 2°C of warming by 2040 could lead to a decline by one-third in per the African Sahel will be higher at 2°C compared to 1.5°C of global capita crop production associated with general decreases in crop yields warming (Cheung et al., 2016a; Betts et al., 2018), and at 2°C these (Nelson et al., 2010). However, under 1.5°C of warming, significant vulnerabilities are expected to be worse (high evidence) (Sultan and risks for crop yield reduction in the region are avoided (Schleussner et Gaetani, 2016; Lehner et al., 2017; Betts et al., 2018; Byers et al., al., 2016b). These changes pose significant risks for poor people in both 2018; Rosenzweig et al., 2018). Under global warming of more than rural regions and urban areas of Southeast Asia (Section 3.4.10.1), with 2°C, the western Sahel might experience the strongest drying and these risks being larger at 2°C of global warming compared to 1.5°C experience serious food security issues (Ahmed et al., 2015; Parkes (medium confidence). et al., 2018). 259 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems 3.5.4.7 Southern Africa 3.5.4.9 Small islands The southern African region is projected to be a climate change hotspot It is widely recognized that small islands are very sensitive to climate in terms of both hot extremes (Figures 3.5 and 3.6) and drying (Figure change impacts such as sea level rise, oceanic warming, heavy 3.12). Indeed, temperatures have been rising in the subtropical regions precipitation, cyclones and coral bleaching (high confidence) (Nurse et of southern Africa at approximately twice the global rate over the last al., 2014; Ourbak and Magnan, 2017). Even at 1.5°C of global warming, five decades (Engelbrecht et al., 2015). Associated elevated warming the compounding impacts of changes in rainfall, temperature, tropical of the regional land-based hot extremes has occurred (Section 3.3; cyclones and sea level are likely to be significant across multiple Seneviratne et al., 2016). Increases in the number of hot nights, as natural and human systems. There are potential benefits to small well as longer and more frequent heatwaves, are projected even if the island developing states (SIDS) from avoided risks at 1.5°C versus global temperature increase is constrained to 1.5°C (high confidence), 2°C, especially when coupled with adaptation efforts. In terms of sea with further increases expected at 2°C of global warming and beyond level rise, by 2150, roughly 60,000 fewer people living in SIDS will be (high confidence) (Weber et al., 2018). exposed in a 1.5°C world than in a 2°C world (Rasmussen et al., 2018). Constraining global warming to 1.5°C may significantly reduce water Moreover, southern Africa is likely to generally become drier with stress (by about 25%) compared to the projected water stress at 2°C, reduced water availability under low mitigation (Niang et al., 2014; for example in the Caribbean region (Karnauskas et al., 2018), and may Engelbrecht et al., 2015; Karl et al., 2015; James et al., 2017), with enhance the ability of SIDS to adapt (Benjamin and Thomas, 2016). Up this particular risk being prominent under 2°C of global warming and to 50% of the year is projected to be very warm in the Caribbean at even under 1.5°C (Gerten et al., 2013). Risks are significantly reduced, 1.5°C, with a further increase by up to 70 days at 2°C versus 1.5°C however, under 1.5°C of global warming compared to under higher (Taylor et al., 2018). By limiting warming to 1.5°C instead of 2°C in levels (Schleussner et al., 2016b). There are consistent and statistically 2050, risks of coastal flooding (measured as the flood amplification significant increases in projected risks of increased meteorological factors for 100-year flood events) are reduced by 20–80% for SIDS drought in southern Africa at 2°C versus 1.5°C of warming (medium (Rasmussen et al., 2018). A case study of Jamaica with lessons for 3 confidence). Despite the general rainfall reductions projected for other Caribbean SIDS demonstrated that the difference between 1.5°C southern Africa, daily rainfall intensities are expected to increase over and 2°C is likely to challenge livestock thermoregulation, resulting in much of the region (medium confidence), and increasingly so with persistent heat stress for livestock (Lallo et al., 2018). higher levels of global warming. There is medium confidence that livestock in southern Africa will experience increased water stress 3.5.4.10 Fynbos and shrub biomes under both 1.5°C and 2°C of global warming, with negative economic consequences (e.g., Boone et al., 2018). The region is also projected The Fynbos and succulent Karoo biomes of South Africa are to experience reduced maize, sorghum and cocoa cropping area threatened systems that were assessed in AR5. Similar shrublands suitability, as well as yield losses under 1.5°C of warming, with further exist in the semi-arid regions of other continents, with the Sonora- decreases occurring towards 2°C of warming (World Bank, 2013). Mojave creosotebush-white bursage desert scrub ecosystem in the Generally, there is high confidence that vulnerability to decreases in USA being a prime example. Impacts accrue across these systems water and food availability is reduced at 1.5°C versus 2°C for southern with greater warming, with impacts at 2°C likely to be greater than Africa (Betts et al., 2018), whilst at 2°C these are expected to be higher those at 1.5°C (medium confidence). Under 2°C of global warming, (high confidence) (Lehner et al., 2017; Betts et al., 2018; Byers et al., regional warming in drylands is projected to be 3.2°C–4°C, and under 2018; Rosenzweig et al., 2018). 1.5°C of global warming, mean warming in drylands is projected to still be about 3°C. The Fynbos biome in southwestern South Africa 3.5.4.8 Tropics is vulnerable to the increasing impact of fires under increasing temperatures and drier winters (high confidence). The Fynbos biome Worldwide, the largest increases in the number of hot days are is projected to lose about 20%, 45% and 80% of its current suitable projected to occur in the tropics (Figure 3.7). Moreover, the largest climate area relative to its present-day area under 1°C, 2°C and differences in the number of hot days for 1.5°C versus 2°C of global 3°C of warming, respectively (Engelbrecht and Engelbrecht, 2016), warming are projected to occur in the tropics (Mahlstein et al., 2011). demonstrating the value of climate change mitigation in protecting In tropical Africa, increases in the number of hot nights, as well as this rich centre of biodiversity. longer and more frequent heatwaves, are projected under 1.5°C of global warming, with further increases expected under 2°C of global warming (Weber et al., 2018). Impact studies for major tropical cereals reveal that yields of maize and wheat begin to decline with 1°C to 2°C of local warming in the tropics. Schleussner et al. (2016b) project that constraining warming to 1.5°C rather than 2°C would avoid significant risks of tropical crop yield declines in West Africa, Southeast Asia, and Central and South America. There is limited evidence and thus low confidence that these changes may result in significant population displacement from the tropics to the subtropics (e.g., Hsiang and Sobel, 2016). 260 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Table 3.6 | Emergence and intensity of climate change hotspots under different degrees of global warming. Region and/or Warming of 1.5°C or less Warming of 1.5°C–2°C Warming of 2°C–3°C Phenomenon Arctic summer sea ice is likely to be maintained The risk of an ice-free Arctic in summer is about 50% The Arctic is very likely to be ice free in summer or higher Habitat losses for organisms such as polar bears, Habitat losses for organisms such as polar bears, Critical habitat losses for organisms such as Arctic sea ice whales, seals and sea birds whales,seals and sea birds may be critical if polar bears, whales, seals and sea birds summers are ice free Benefits for Arctic fisheries Benefits for Arctic fisheries Benefits for Arctic fisheries Cold extremes warm by a factor of 2–3, reaching Cold extremes warm by as much as 8°C Drastic regional warming is very likely up to 4.5°C (high confidence) (high confidence) Arctic land regions Biome shifts in the tundra and permafrost Larger intrusions of trees and shrubs in the tundra A collapse in permafrost may occur (low deterioration are likely than under 1.5°C of warming are likely; larger confidence); a drastic biome shift from tundra but constrained losses in permafrost are likely to boreal forest is possible (low confidence) Alpine regions Severe shifts in biomes are likely Even more severe shifts are likely Critical losses in alpine habitats are likely Risks for increased flooding related to sea level rise Higher risks of increased flooding related Substantial increases in risks related to flooding to sea level rise (medium confidence) from sea level rise Increases in heavy precipitation events Stronger increases in heavy precipitation events Substantial increase in heavy precipitation Southeast Asia (medium confidence) and high-flow events Significant risks of crop yield reductions are avoided One-third decline in per capita crop production Substantial reductions in crop yield (medium confidence) Increase in probability of extreme Robust increase in probability of extreme Robust and large increases in extreme drought (medium confidence) drought (medium confidence) drought. Substantial reductions in precipitation Mediterranean Medium confidence in reduction in runoff Medium confidence in further reductions and in runoff (medium confidence) of about 9% (likely range 4.5–15.5%) (about 17%) in runoff (likely range 8–28%) Risk of water deficit (medium confidence) Higher risks of water deficit (medium confidence) Very high risks of water deficit (medium confidence) 3 Increases in the number of hot nights and longer Further increases in number of hot nights and Substantial increases in the number of hot nights and more frequent heatwaves are likely longer and more frequent heatwaves are likely and heatwave duration and frequency (very likely) Reduced maize and sorghum production is likely, Negative impacts on maize and sorghum production Negative impacts on crop yield may result in major West Africa and with area suitable for maize production reduced likely larger than at 1.5°C; medium confidence regional food insecurities (medium confidence) the Sahel by as much as 40% that vulnerabilities to food security in the African Sahel will be higher at 2°C compared to 1.5°C Increased risks of undernutrition Higher risks of undernutrition High risks of undernutrition Reductions in water availability (medium confidence) Larger reductions in rainfall and water Large reductions in rainfall and water availability (medium confidence) availability (medium confidence) Increases in number of hot nights and longer and Further increases in number of hot nights and Drastic increases in the number of hot nights, hot more frequent heatwaves (high confidence) longer and more frequent heatwaves (high days and heatwave duration and frequency to Southern Africa confidence), associated increases in risks of impact substantially on agriculture, livestock and High risks of increased mortality from heatwaves increased mortality from heatwaves compared human health and mortality (high confidence) to 1.5°C warming (high confidence) High risk of undernutrition in communities Higher risks of undernutrition in communities Very high risks of undernutrition in communities dependent on dryland agriculture and livestock dependent on dryland agriculture and livestock dependent on dryland agriculture and livestock Increases in the number of hot days and hot nights The largest increase in hot days under 2°C compared Oppressive temperatures and accumulated as well as longer and more frequent heatwaves to 1.5°C is projected for the tropics. heatwave duration very likely to directly impact (high confidence) human health, mortality and productivity Tropics Risks to tropical crop yields in West Africa, Risks to tropical crop yields in West Africa, Substantial reductions in crop yield very likely Southeast Asia and Central and South America Southeast Asia and Central and South America are significantly less than under 2°C of warming could be extensive Land of 60,000 less people exposed by 2150 on SIDS Tens of thousands of people displaced owing to Substantial and widespread impacts compared to impacts under 2°C of global warming inundation of SIDS through inundation of SIDS, coastal flooding, Risks for coastal flooding reduced by 20–80% High risks for coastal flooding freshwater stress, persistent heat stress and for SIDS compared to 2°C of global warming loss of most coral reefs (very likely) Freshwater stress reduced by 25% Freshwater stress reduced by 25% compared to 2°C of global warming Small islands Freshwater stress from projected aridity Increase in the number of warm days for SIDS Further increase of about 70 warm days per year in the tropics Persistent heat stress in cattle avoided Persistent heat stress in cattle in SIDS Loss of 70–90% of coral reefs Loss of most coral reefs and weaker remaining structures owing to ocean acidification About 30% of suitable climate area lost Increased losses (about 45%) of suitable climate Up to 80% of suitable climate area lost Fynbos biome (medium confidence) area (medium confidence) (medium confidence) 261 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems 3.5.5 Avoiding Regional Tipping Points by Achieving 3.5.5.3 Permafrost More Ambitious Global Temperature Goals Widespread thawing of permafrost potentially makes a large carbon Tipping points refer to critical thresholds in a system that, when exceeded, store (estimated to be twice the size of the atmospheric store; Dolman can lead to a significant change in the state of the system, often with an et al., 2010) vulnerable to decomposition, which could lead to further understanding that the change is irreversible. An understanding of the increases in atmospheric carbon dioxide and methane and hence to sensitivities of tipping points in the physical climate system, as well as in further global warming. This feedback loop between warming and the ecosystems and human systems, is essential for understanding the risks release of greenhouse gas from thawing tundra represents a potential associated with different degrees of global warming. This subsection tipping point. However, the carbon released to the atmosphere from reviews tipping points across these three areas within the context thawing permafrost is projected to be restricted to 0.09–0.19 Gt C yr–1 of the different sensitivities to 1.5°C versus 2°C of global warming. at 2°C of global warming and to 0.08–0.16 Gt C yr–1 at 1.5°C (E.J. Sensitivities to less ambitious global temperature goals are also briefly Burke et al., 2018), which does not indicate a tipping point (medium reviewed. Moreover, an analysis is provided of how integrated risks confidence). At higher degrees of global warming, in the order of across physical, natural and human systems may accumulate to lead 3°C, a different type of tipping point in permafrost may be reached. to the exceedance of thresholds for particular systems. The emphasis in A single model projection (Drijfhout et al., 2015) suggested that this section is on the identification of regional tipping points and their higher temperatures may induce a smaller ice fraction in soils in the sensitivity to 1.5°C and 2°C of global warming, whereas tipping points tundra, leading to more rapidly warming soils and a positive feedback in the global climate system, referred to as large-scale singular events, mechanism that results in permafrost collapse (low confidence). The were already discussed in Section 3.5.2. A summary of regional tipping disparity between the multi-millennial time scales of soil carbon points is provided in Table 3.7. accumulation and potentially rapid decomposition in a warming climate implies that the loss of this carbon to the atmosphere would 3.5.5.1 Arctic sea ice be essentially irreversible (Collins et al., 2013). 3 Collins et al. (2013) discussed the loss of Artic sea ice in the context 3.5.5.4 Asian monsoon of potential tipping points. Climate models have been used to assess whether a bifurcation exists that would lead to the irreversible loss At a fundamental level, the pressure gradient between the Indian Ocean of Arctic sea ice (Armour et al., 2011; Boucher et al., 2012; Ridley et and Asian continent determines the strength of the Asian monsoon. As al., 2012) and to test whether the summer sea ice extent can recover land masses warm faster than the oceans, a general strengthening of after it has been lost (Schröder and Connolley, 2007; Sedláček et al., this gradient, and hence of monsoons, may be expected under global 2011; Tietsche et al., 2011). These studies did not find evidence of warming (e.g., Lenton et al., 2008). Additional factors such as changes bifurcation or indicate that sea ice returns within a few years of its loss, in albedo induced by aerosols and snow-cover change may also affect leading Collins et al. (2013) to conclude that there is little evidence temperature gradients and consequently pressure gradients and the for a tipping point in the transition from perennial to seasonal ice strength of the monsoon. In fact, it has been estimated that an increase cover. No evidence has been found for irreversibility or tipping points, of the regional land mass albedo to 0.5 over India would represent a suggesting that year-round sea ice will return given a suitable climate tipping point resulting in the collapse of the monsoon system (Lenton (medium confidence) (Schröder and Connolley, 2007; Sedláček et al., et al., 2008). The overall impacts of the various types of radiative 2011; Tietsche et al., 2011). forcing under different emissions scenarios are more subtle, with a weakening of the monsoon north of about 25°N in East Asia but a 3.5.5.2 Tundra strengthening south of this latitude projected by Jiang and Tian (2013) under high and modest emissions scenarios. Increases in the intensity Tree growth in tundra-dominated landscapes is strongly constrained by of monsoon precipitation are likely under low mitigation (AR5). Given the number of days with mean air temperature above 0°C. A potential that scenarios of 1.5°C or 2°C of global warming would include a tipping point exists where the number of days below 0°C decreases substantially smaller radiative forcing than those assessed in the study to the extent that the tree fraction increases significantly. Tundra- by Jiang and Tian (2013), there is low confidence regarding changes in dominated landscapes have warmed more than the global average monsoons at these low global warming levels, as well as regarding the over the last century (Settele et al., 2014), with associated increases differences between responses at 1.5°C versus 2°C of warming. in fires and permafrost degradation (Bring et al., 2016; DeBeer et al., 2016; Jiang et al., 2016; Yang et al., 2016). These processes facilitate 3.5.5.5 West African monsoon and the Sahel conditions for woody species establishment in tundra areas, and for the eventual transition of the tundra to boreal forest. The number of Earlier work has identified 3°C of global warming as the tipping point investigations into how the tree fraction may respond in the Arctic to leading to a significant strengthening of the West African monsoon and different degrees of global warming is limited, and studies generally subsequent wettening (and greening) of the Sahel and Sahara (Lenton indicate that substantial increases will likely occur gradually (e.g., et al., 2008). AR5 (Niang et al., 2014), as well as more recent research Lenton et al., 2008). Abrupt changes are only plausible at levels of through the Coordinated Regional Downscaling Experiment for Africa warming significantly higher than 2°C (low confidence) and would (CORDEX–AFRICA), provides a more uncertain view, however, in terms occur in conjunction with a collapse in permafrost (Drijfhout et al., of the rainfall futures of the Sahel under low mitigation futures. Even 2015). if a wetter Sahel should materialize under 3°C of global warming (low 262 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 confidence), it should be noted that there would be significant offsets in the occurrence of deadly heatwaves in cities if urban heat island in the form of strong regional warming and related adverse impacts effects are considered, with impacts being similar at 1.5°C and 2°C but on crop yield, livestock mortality and human health under such low substantially larger than under the present climate (Matthews et al., mitigation futures (Engelbrecht et al., 2015; Sylla et al., 2016; Weber 2017). At 1.5°C of warming, twice as many megacities (such as Lagos, et al., 2018). Nigeria, and Shanghai, China) than at present are likely to become heat stressed, potentially exposing more than 350 million more people to 3.5.5.6 Rainforests deadly heat stress by 2050. At 2°C of warming, Karachi (Pakistan) and Kolkata (India) could experience conditions equivalent to their deadly A large portion of rainfall over the world’s largest rainforests is 2015 heatwaves on an annual basis (medium confidence). These recirculated (e.g., Lenton et al., 2008), which raises the concern that statistics imply a tipping point in the extent and scale of heatwave deforestation may trigger a threshold in reduced forest cover, leading impacts. However, these projections do not integrate adaptation to to pronounced forest dieback. For the Amazon, this deforestation projected warming, for instance cooling that could be achieved with threshold has been estimated to be 40% (Nobre et al., 2016). Global more reflective roofs and urban surfaces in general (Akbari et al., 2009; warming of 3°C–4°C may also, independent of deforestation, represent Oleson et al., 2010). a tipping point that results in a significant dieback of the Amazon forest, with a key forcing mechanism being stronger El Niño events 3.5.5.9 Agricultural systems: key staple crops bringing more frequent droughts to the region (Nobre et al., 2016). Increased fire frequencies under global warming may interact with and A large number of studies have consistently indicated that maize crop accelerate deforestation, particularly during periods of El Niño-induced yield will be negatively affected under increased global warming, with droughts (Lenton et al., 2008; Nobre et al., 2016). Global warming of negative impacts being higher at 2°C of warming than at 1.5°C (e.g., 3°C is projected to reduce the extent of tropical rainforest in Central Niang et al., 2014; Schleussner et al., 2016b; J. Huang et al., 2017; America, with biomass being reduced by about 40%, which can lead Iizumi et al., 2017). Under 2°C of global warming, losses of 8–14% to a large replacement of rainforest by savanna and grassland (Lyra et are projected in global maize production (Bassu et al., 2014). Under al., 2017). Overall, modelling studies (Huntingford et al., 2013; Nobre global warming of more than 2°C, regional losses are projected to 3 et al., 2016) and observational constraints (Cox et al., 2013) suggest be about 20% if they co-occur with reductions in rainfall (Lana et al., that pronounced rainforest dieback may only be triggered at 3°C–4°C 2017). These changes may be classified as incremental rather than (medium confidence), although pronounced biomass losses may occur representing a tipping point. Large-scale reductions in maize crop yield, at 1.5°C– 2°C of global warming. including the potential collapse of this crop in some regions, may exist under 3°C or more of global warming (low confidence) (e.g., Thornton 3.5.5.7 Boreal forests et al., 2011). Boreal forests are likely to experience stronger local warming than the 3.5.5.10 Agricultural systems: livestock in the tropics and global average (WGII AR5; Collins et al., 2013). Increased disturbance subtropics from fire, pests and heat-related mortality may affect, in particular, the southern boundary of boreal forests (medium confidence) (Gauthier The potential impacts of climate change on livestock (Section 3.4.6), et al., 2015), with these impacts accruing with greater warming and in particular the direct impacts through increased heat stress, have thus impacts at 2°C would be expected to be greater than those at been less well studied than impacts on crop yield, especially from 1.5°C (medium confidence). A tipping point for significant dieback of the perspective of critical thresholds being exceeded. A case study the boreal forests is thought to exist, where increased tree mortality from Jamaica revealed that the difference in heat stress for livestock would result in the creation of large regions of open woodlands between 1.5°C and 2°C of warming is likely to exceed the limits for and grasslands, which would favour further regional warming and normal thermoregulation and result in persistent heat stress for these increased fire frequencies, thus inducing a powerful positive feedback animals (Lallo et al., 2018). It is plausible that this finding holds for mechanism (Lenton et al., 2008; Lenton, 2012). This tipping point has livestock production in both tropical and subtropical regions more been estimated to exist between 3°C and 4°C of global warming generally (medium confidence) (Section 3.4.6). Under 3°C of global (low confidence) (Lucht et al., 2006; Kriegler et al., 2009), but given warming, significant reductions in the areas suitable for livestock the complexities of the various forcing mechanisms and feedback production could occur (low confidence), owing to strong increases in processes involved, this is thought to be an uncertain estimate. regional temperatures in the tropics and subtropics (high confidence). Thus, regional tipping points in the viability of livestock production may 3.5.5.8 Heatwaves, unprecedented heat and human health well exist, but little evidence quantifying such changes exists. Increases in ambient temperature are linearly related to hospitalizations and deaths once specific thresholds are exceeded (so there is not a tipping point per se). It is plausible that coping strategies will not be in place for many regions, with potentially significant impacts on communities with low adaptive capacity, effectively representing the occurrence of a local/regional tipping point. In fact, even if global warming is restricted to below 2°C, there could be a substantial increase 263 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Table 3.7 | Summary of enhanced risks in the exceedance of regional tipping points under different global temperature goals. Tipping point Warming of 1.5°C or less Warming of 1.5°C–2°C Warming of up to 3°C Arctic summer sea ice is likely to be maintained The risk of an ice-free Arctic in summer is about Arctic is very likely to be ice free in summer 50% or higher Arctic sea ice Sea ice changes reversible under suitable climate Sea ice changes reversible under suitable climate Sea ice changes reversible under suitable climate restoration restoration restoration Decrease in number of growing degree days Further decreases in number of growing degree below 0°C days below 0°C Tundra Abrupt increases in tree cover are unlikely Abrupt increased in tree cover are unlikely Potential for an abrupt increase in tree fraction (low confidence) 17–44% reduction in permafrost 28–53% reduction in permafrost Potential for permafrost collapse (low confidence) Approximately 2 million km2 more Irreversible loss of stored carbon Permafrost permafrost maintained than under 2°C of global warming (medium confidence) Irreversible loss of stored carbon Low confidence in projected changes Low confidence in projected changes Increases in the intensity of Asian monsoon monsoon precipitation likely Uncertain changes; unlikely that a tipping point is Uncertain changes; unlikely that tipping point is Strengthening of monsoon with reached reached wettening and greening of the Sahel West African monsoon and Sahara (low confidence) and the Sahel Negative associated impacts through increases in extreme temperature events Reduced biomass, deforestation and fire Larger biomass reductions than under 1.5°C of Reduced extent of tropical rainforest in Central increases pose uncertain risks to forest dieback warming; deforestation and fire increases pose America and large replacement of rainforest 3 Rainforests uncertain risk to forest dieback by savanna and grassland Potential tipping point leading to pronounced forest dieback (medium confidence) Increased tree mortality at southern boundary of Further increases in tree mortality at southern Potential tipping point at 3°C–4°C for significant Boreal forests boreal forest (medium confidence) boundary of boreal forest (medium confidence) dieback of boreal forest (low confidence) Substantial increase in occurrence of potentially Substantial increase in potentially deadly Substantial increase in potentially deadly deadly heatwaves (likely) heatwaves (likely) heatwaves very likely Heatwaves, unprecedented heat and human health More than 350 million more people exposed to Annual occurrence of heatwaves similar to the deadly heat by 2050 under a midrange deadly 2015 heatwaves in India and Pakistan population growth scenario (likely) (medium confidence) Global maize crop reductions of about 10% Larger reductions in maize crop production than Drastic reductions in maize crop globally Agricultural systems: under 1.5°C of about 15% and in Africa (high confidence) key staple crops Potential tipping point for collapse of maize crop in some regions (low confidence) Livestock in the tropics Increased heat stress Onset of persistent heat stress Persistent heat stress likely and subtropics (medium confidence) Box 3.6 | Economic Damages from Climate Change Balancing the costs and benefits of mitigation is challenging because estimating the value of climate change damages depends on multiple parameters whose appropriate values have been debated for decades (for example, the appropriate value of the discount rate) or that are very difficult to quantify (for example, the value of non-market impacts; the economic effects of losses in ecosystem services; and the potential for adaptation, which is dependent on the rate and timing of climate change and on the socio-economic content). See Cross-Chapter Box 5 in Chapter 2 for the definition of the social cost of carbon and for a discussion of the economics of 1.5°C-consistent pathways and the social cost of carbon, including the impacts of inequality on the social cost of carbon. Global economic damages of climate change are projected to be smaller under warming of 1.5°C than 2°C in 2100 (Warren et al., 2018c). The mean net present value of the costs of damages from warming in 2100 for 1.5°C and. 2°C (including costs associated with climate change-induced market and non-market impacts, impacts due to sea level rise, and impacts associated with large-scale discontinuities) are $54 and $69 trillion, respectively, relative to 1961–1990. 264 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Box 3.6 (continued) Values of the social cost of carbon vary when tipping points are included. The social cost of carbon in the default setting of the Dynamic Integrated Climate-Economy (DICE) model increases from $15 tCO –12 to $116 (range 50–166) tCO –1 2 when large-scale singularities or ‘tipping elements’ are incorporated (Y. Cai et al., 2016; Lemoine and Traeger, 2016). Lemoine and Traeger (2016) included optimization calculations that minimize welfare impacts resulting from the combination of climate change risks and climate change mitigation costs, showing that welfare is minimized if warming is limited to 1.5°C. These calculations excluded the large health co-benefits that accrue when greenhouse gas emissions are reduced (Section 3.4.7.1; Shindell et al., 2018). The economic damages of climate change in the USA are projected to be large (Hsiang et al., 2017; Yohe, 2017). Hsiang et al. (2017) shows that the USA stand to lose -0.1 to 1.7% of the Gross Domestic Product (GDP) at 1.5°C warming. Yohe (2017) calculated transient temperature trajectories from a linear relationship with contemporaneous cumulative emissions under a median no-policy baseline trajectory that brings global emissions to roughly 93 GtCO –12 yr by the end of the century (Fawcett et al., 2015), with 1.75°C per 1000 GtCO2 as the median estimate. Associated aggregate economic damages in decadal increments through the year 2100 are estimated in terms of the percentage loss of GDP at the median, 5th percentile and 95th percentile transient temperature (Hsiang et al., 2017). The results for the baseline no-policy case indicate that economic damages along median temperature change and median damages (median-median) reach 4.5% of GDP by 2100, with an uncertainty range of 2.5% and 8.5% resulting from different combinations of temperature change and damages. Avoided damages from achieving a 1.5°C temperature limit along the median-median case are nearly 4% (range 2–7%) by 2100. Avoided damages from achieving a 2°C temperature limit are only 3.5% (range 1.8–6.5%). Avoided damages from achieving 1.5°C versus 2°C are modest at about 0.35% (range 0.20–0.65%) by 2100. The values of achieving the two temperature limits do not diverge significantly until 2040, when their difference tracks between 0.05 and 0.13%; the differences between the two temperature targets begin to diverge substantially in the second half of the century. 3 3.6 Implications of Different 1.5°C and 2°C such as less consumption of resource-intensive commodities (animal Pathways products) or reductions in food waste, reduce pressure on land (Popp et al., 2017; Rogelj et al., 2018). Finally, carbon dioxide removal This section provides an overview on specific aspects of the mitigation (CDR) is a key component of most, but not all, mitigation pathways pathways considered compatible with 1.5°C of global warming. Some presented in the literature to date which constrain warming to 1.5°C of these aspects are also addressed in more detail in Cross-Chapter or 2°C. Carbon dioxide removal measures that require land include Boxes 7 and 8 in this chapter. bioenergy with carbon capture and storage (BECCS), afforestation and reforestation (AR), soil carbon sequestration, direct air capture, biochar 3.6.1 Gradual versus Overshoot in 1.5°C Scenarios and enhanced weathering (see Cross-Chapter Box 7 in this chapter). These potential methods are assessed in Section 4.3.7. All 1.5°C scenarios from Chapter 2 include some overshoot above 1.5°C of global warming during the 21st century (Chapter 2 and Cross- In cost-effective integrated assessment modelling (IAM) pathways Chapter Box 8 in this chapter). The level of overshoot may also depend recently developed to be consistent with limiting warming to 1.5°C, on natural climate variability. An overview of possible outcomes of use of CDR in the form of BECCS and AR are fundamental elements 1.5°C-consistent mitigation scenarios for changes in the physical (Chapter 2; Popp et al., 2017; Hirsch et al., 2018; Rogelj et al., 2018; climate at the time of overshoot and by 2100 is provided in Cross- Seneviratne et al., 2018c). The land-use footprint of CDR deployment Chapter Box 8 on ‘1.5°C warmer worlds’. Cross-Chapter Box 8 also in 1.5°C-consistent pathways can be substantial (Section 2.3.4, Figure highlights the implications of overshoots. 2.11), even though IAMs predominantly rely on second-generation biomass and assume future productivity increases in agriculture. 3.6.2 Non-CO2 Implications and Projected Risks of Mitigation Pathways A body of literature has explored potential consequences of large-scale use of CDR. In this case, the corresponding land footprint by the end 3.6.2.1 Risks arising from land-use changes of the century could be extremely large, with estimates including: up in mitigation pathways to 18% of the land surface being used (Wiltshire and Davies-Barnard, 2015); vast acceleration of the loss of primary forest and natural In mitigation pathways, land-use change is affected by many different grassland (Williamson, 2016) leading to increased greenhouse gas mitigation options. First, mitigation of non-CO2 emissions from emissions (P. Smith et al., 2013, 2015); and potential loss of up to 10% agricultural production can shift agricultural production between of the current forested lands to biofuels (Yamagata et al., 2018). Other regions via trade of agricultural commodities. Second, protection of estimates reach 380–700 Mha or 21–64% of current arable cropland carbon-rich ecosystems such as tropical forests constrains the area (Section 4.3.7). Boysen et al. (2017) found that in a scenario in which for agricultural expansion. Third, demand-side mitigation measures, emissions reductions were sufficient only to limit warming to 2.5°C, 265 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems use of CDR to further limit warming to 1.7°C would result in the management used. However, not all of the land footprint of CDR is conversion of 1.1–1.5 Gha of land – implying enormous losses of both necessarily to be in competition with biodiversity protection. Where cropland and natural ecosystems. Newbold et al. (2015) found that reforestation is the restoration of natural ecosystems, it benefits both biodiversity loss in the Representative Concentration Pathway (RCP)2.6 carbon sequestration and conservation of biodiversity and ecosystem scenario could be greater than that in RCP4.5 and RCP6, in which there services (Section 4.3.7) and can contribute to the achievement of is more climate change but less land-use change. Risks to biodiversity the Aichi targets under the Convention on Biological Diversity (CBD) conservation and agricultural production are therefore projected to (Leadley et al., 2016). However, reforestation is often not defined in result from large-scale bioenergy deployment pathways (P. Smith et this way (Section 4.3.8; Stanturf et al., 2014) and the ability to deliver al., 2013; Tavoni and Socolow, 2013). One study explored an extreme biodiversity benefits is strongly dependent on the precise nature mitigation strategy encouraging biofuel expansion sufficient to limit of the reforestation, which has different interpretations in different warming to 1.5°C and found that this would be more disruptive to land contexts and can often include agroforestry rather than restoration use and crop prices than the impacts of a 2°C warmer world which of pristine ecosystems (Pistorious and Kiff, 2017). However, ‘natural has a larger climate signal and lower mitigation requirement (Ruane climate solutions’, defined as conservation, restoration, and improved et al., 2018). However, it should again be emphasized that many of the land management actions that increase carbon storage and/or avoid pathways explored in Chapter 2 of this report follow strategies that greenhouse gas emissions across global forests, wetlands, grasslands explore how to reduce these issues. Chapter 4 provides an assessment and agricultural lands, are estimated to have the potential to provide of the land footprint of various CDR technologies (Section 4.3.7). 37% of the cost-effective CO2 mitigation needed by southern Europe and the Mediterranean by 2030 – in order to have a >66% chance of The degree to which BECCS has these large land-use footprints holding warming to below 2°C (Griscom et al., 2017). depends on the source of the bioenergy used and the scale at which BECCS is deployed. Whether there is competition with food production Any reductions in agricultural production driven by climate change and biodiversity depends on the governance of land use, agricultural and/or land management decisions related to CDR may (e.g., Nelson intensification, trade, demand for food (in particular meat), feed and et al., 2014a; Dalin and Rodríguez-Iturbe, 2016) or may not (Muratori 3 timber, and the context of the whole supply chain (Section 4.3.7, et al., 2016) affect food prices. However, these studies did not consider Fajardy and Mac Dowell, 2017; Booth, 2018; Sterman et al., 2018). the deployment of second-generation (instead of first-generation) bioenergy crops, for which the land footprint can be much smaller. The more recent literature reviewed in Chapter 2 explores pathways which limit warming to 2°C or below and achieve a balance between Irrespective of any mitigation-related issues, in order for ecosystems sources and sinks of CO2 by using BECCS that relies on second- to adapt to climate change, land use would also need to be carefully generation (or even third-generation) biofuels, changes in diet or more managed to allow biodiversity to disperse to areas that become generally, management of food demand, or CDR options such as forest newly climatically suitable for it (Section 3.4.1) and to protect the restoration (Chapter 2; Bajželj et al., 2014). Overall, this literature areas where the future climate will still remain suitable. This implies explores how to reduce the issues of competition for land with food a need for considerable expansion of the protected area network production and with natural ecosystems (in particular forests) (Cross- (Warren et al., 2018b), either to protect existing natural habitat or Chapter Box 1 in Chapter 1; van Vuuren et al., 2009; Haberl et al., to restore it (perhaps through reforestation, see above). At the same 2010, 2013; Bajželj et al., 2014; Daioglou et al., 2016; Fajardy and Mac time, adaptation to climate change in the agricultural sector (Rippke Dowell, 2017). et al., 2016) can require transformational as well as new approaches to land-use management; in order to meet the rising food demand Some IAMs manage this transition by effectively protecting carbon of a growing human population, it is projected that additional stored on land and focusing on the conversion of pasture area land will need to be brought into production unless there are large into both forest area and bioenergy cropland. Some IAMs explore increases in agricultural productivity (Tilman et al., 2011). However, 1.5°C-consistent pathways with demand-side measures such as dietary future rates of deforestation may be underestimated in the existing changes and efficiency gains such as agricultural changes (Sections literature (Mahowald et al., 2017a), and reforestation may therefore 2.3.4 and 2.4.4), which lead to a greatly reduced CDR deployment and be associated with significant co-benefits if implemented to restore consequently land-use impacts (van Vuuren et al., 2018). In reality, natural ecosystems (high confidence). however, whether this CDR (and bioenergy in general) has large adverse impacts on environmental and societal goals depends in large 3.6.2.2 Biophysical feedbacks on regional climate part on the governance of land use (Section 2.3.4; Obersteiner et al., associated with land-use changes 2016; Bertram et al., 2018; Humpenöder et al., 2018). Changes in the biophysical characteristics of the land surface are known Rates of sequestration of 3.3 GtC ha–1 require 970 Mha of afforestation to have an impact on local and regional climates through changes in and reforestation (Smith et al., 2015). Humpenöder et al. (2014) albedo, roughness, evapotranspiration and phenology, which can lead estimated that in least-cost pathways afforestation would cover 2800 to a change in temperature and precipitation. This includes changes in Mha by the end of the century to constrain warming to 2°C. Hence, land use through agricultural expansion/intensification (e.g., Mueller the amount of land considered if least-cost mitigation is implemented et al., 2016), reforestation/revegetation endeavours (e.g., Feng et al., by afforestation and reforestation could be up to three to five 2016; Sonntag et al., 2016; Bright et al., 2017) and changes in land times greater than that required by BECCS, depending on the forest management (e.g., Luyssaert et al., 2014; Hirsch et al., 2017) that can 266 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Figure 3.22 | Regional temperature scaling with carbon dioxide (CO2) concentration (ppm) from 1850 to 2099 for two different regions defined in the Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate Change Adaptation (SREX) for central Europe (CEU) (a) and central North America (CNA) (b). Solid lines correspond to the regional average annual maximum daytime temperature (TXx) anomaly, and dashed lines correspond to the global mean temperature anomaly, where all temperature anomalies are relative to 1850–1870 and units are degrees Celsius. The black line in all panels denotes the three-member control ensemble mean, with the grey shaded regions corresponding to the ensemble range. The coloured lines represent the three-member ensemble means of the experiments corresponding to albedo +0.02 (cyan), 3 albedo +0.04 (purple), albedo + 0.08 (orange), albedo +0.10 (red), irrigation (blue), and irrigation with albedo +0.10 (green). Adapted from Hirsch et al. (2017). involve double cropping (e.g., Jeong et al., 2014; Mueller et al., 2015; ecosystem services. This includes climate change-induced changes in Seifert and Lobell, 2015), irrigation (e.g., Lobell et al., 2009; Sacks et crop yield (e.g., Schlenker and Roberts, 2009; van der Velde et al., 2012; al., 2009; Cook et al., 2011; Qian et al., 2013; de Vrese et al., 2016; Asseng et al., 2013, 2015; Butler and Huybers, 2013; Lobell et al., 2014) Pryor et al., 2016; Thiery et al., 2017), no-till farming and conservation which may be further exacerbated by competing demands for arable agriculture (e.g., Lobell et al., 2006; Davin et al., 2014), and wood land between reforestation mitigation activities, crop growth for BECCS harvesting (e.g., Lawrence et al., 2012). Hence, the biophysical impacts (Chapter 2), increasing food production to support larger populations, of land-use changes are an important topic to assess in the context of and urban expansion (see review by Smith et al., 2010). In particular, low-emissions scenarios (e.g., van Vuuren et al., 2011b), in particular some land management practices may have further implications for for 1.5°C warming levels (see also Cross-Chapter Box 7 in this chapter). food security, for instance throughincreases or decreases in yield when tillage is ceased in some regions (Pittelkow et al., 2014). The magnitude of the biophysical impacts is potentially large for temperature extremes. Indeed, changes induced both by modifications We note that the biophysical impacts of land use in the context of in moisture availability and irrigation and by changes in surface albedo mitigation pathways constitute an emerging research topic. This tend to be larger (i.e., stronger cooling) for hot extremes than for mean topic, as well as the overall role of land-use change in climate change temperatures (e.g., Seneviratne et al., 2013; Davin et al., 2014; Wilhelm projections and socio-economic pathways, will be addressed in depth et al., 2015; Hirsch et al., 2017; Thiery et al., 2017). The reasons for in the upcoming IPCC Special Report on Climate Change and Land Use reduced moisture availability are related to a strong contribution of due in 2019. moisture deficits to the occurrence of hot extremes in mid-latitude regions (Mueller and Seneviratne, 2012; Seneviratne et al., 2013). In 3.6.2.3 Atmospheric compounds (aerosols and methane) the case of surface albedo, cooling associated with higher albedo (e.g., in the case of no-till farming) is more effective at cooling hot days There are multiple pathways that could be used to limit anthropogenic because of the higher incoming solar radiation for these days (Davin climate change, and the details of the pathways will influence the et al., 2014). The overall effect of either irrigation or albedo has been impacts of climate change on humans and ecosystems. Anthropogenic- found to be at the most in the order of about 1°C–2°C regionally for driven changes in aerosols cause important modifications to the temperature extremes. This can be particularly important in the context global climate (Bindoff et al., 2013a; Boucher et al., 2013b; P. Wu et of low-emissions scenarios because the overall effect is in this case al., 2013; Sarojini et al., 2016; H. Wang et al., 2016). Enforcement of of similar magnitude to the response to the greenhouse gas forcing strict air quality policies may lead to a large decrease in cooling aerosol (Figure 3.22; Hirsch et al., 2017; Seneviratne et al., 2018a,c). emissions in the next few decades. These aerosol emission reductions may cause a warming comparable to that resulting from the increase In addition to the biophysical feedbacks from land-use change and land in greenhouse gases by mid-21st century under low CO2 pathways management on climate, there are potential consequences for particular (Kloster et al., 2009; Acosta Navarro et al., 2017). Further background 267 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems is provided in Sections 2.2.2 and 2.3.1; Cross Chapter Box 1 in Chapter change can provide multiple co-benefits (Shindell et al., 2017). These 1). Because aerosol effects on the energy budget are regional, strong pathways are discussed in detail in Sections 4.3.7 and 5.4.1 and in regional changes in precipitation from aerosols may occur if aerosol Cross-Chapter Box 12 in Chapter 5. emissions are reduced for air quality reasons or as a co-benefit from switches to sustainable energy sources (H. Wang et al., 2016). Thus, Atmospheric aerosols and gases can also modify the land and ocean regional impacts, especially on precipitation, are very sensitive to uptake of anthropogenic CO2; some compounds enhance uptake while 1.5°C-consistent pathways (Z. Wang et al., 2017). others reduce it (Section 2.6.2; Ciais et al., 2013). While CO2 emissions tend to encourage greater uptake of carbon by the land and the Pathways which rely heavily on reductions in methane (CH4) instead ocean (Ciais et al., 2013), CH4 emissions can enhance ozone pollution, of CO2 will reduce warming in the short term because CH4 is such a depending on nitrogen oxides, volatile organic compounds and other stronger and shorter-lived greenhouse gas than CO2, but will lead organic species concentrations, and ozone pollution tends to reduce to stronger warming in the long term because of the much longer land productivity (Myhre et al., 2013; B. Wang et al., 2017). Aside from residence time of CO2 (Myhre et al., 2013; Pierrehumbert, 2014). In inhibiting land vegetation productivity, ozone may also alter the CO2, addition, the dominant loss mechanism for CH4 is atmospheric photo- CH4 and nitrogen (N2O) exchange at the land–atmosphere interface oxidation. This conversion modifies ozone formation and destruction in and transform the global soil system from a sink to a source of the troposphere and stratosphere, therefore modifying the contribution carbon (B. Wang et al., 2017). Aerosols and associated nitrogen-based of ozone to radiative forcing, as well as feedbacks on the oxidation compounds tend to enhance the uptake of CO2 in land and ocean rate of methane itself (Myhre et al., 2013). Focusing on pathways and systems through deposition of nutrients and modification of climate policies which both improve air quality and reduce impacts of climate (Ciais et al., 2013; Mahowald et al., 2017b). 3 Cross-Chapter Box 7 | Land-Based Carbon Dioxide Removal in Relation to 1.5°C of Global Warming Lead Authors: Rachel Warren (United Kingdom), Marcos Buckeridge (Brazil), Sabine Fuss (Germany), Markku Kanninen (Finland), Joeri Rogelj (Austria/Belgium), Sonia I. Seneviratne (Switzerland), Raphael Slade (United Kingdom) Climate and land form a complex system characterized by multiple feedback processes and the potential for non-linear responses to perturbation. Climate determines land cover and the distribution of vegetation, affecting above- and below-ground carbon stocks. At the same time, land cover influences global climate through altered biogeochemical processes (e.g., atmospheric composition and nutrient flow into oceans), and regional climate through changing biogeophysical processes including albedo, hydrology, transpiration and vegetation structure (Forseth, 2010). Greenhouse gas (GHG) fluxes related to land use are reported in the ‘agriculture, forestry and other land use’ sector (AFOLU) and comprise about 25% (about 10–12 GtCO2eq yr –1) of anthropogenic GHG emissions (P. Smith et al., 2014). Reducing emissions from land use, as well as land-use change, are thus an important component of low-emissions mitigation pathways (Clarke et al., 2014), particularly as land-use emissions can be influenced by human actions such as deforestation, afforestation, fertilization, irrigation, harvesting, and other aspects of cropland, grazing land and livestock management (Paustian et al., 2006; Griscom et al., 2017; Houghton and Nassikas, 2018). In the IPCC Fifth Assessment Report, the vast majority of scenarios assessed with a 66% or better chance of limiting global warming to 2°C by 2100 included carbon dioxide removal (CDR) – typically about 10 GtCO2 yr –1 in 2100 or about 200–400 GtCO2 over the course of the century (Smith et al., 2015; van Vuuren et al., 2016). These integrated assessment model (IAM) results were predominately achieved by using bioenergy with carbon capture and storage (BECCS) and/or afforestation and reforestation (AR). Virtually all scenarios that limit either peak or end-of-century warming to 1.5°C also use land-intensive CDR technologies (Rogelj et al., 2015; Holz et al., 2017; Kriegler et al., 2017; Fuss et al., 2018; van Vuuren et al., 2018). Again, AR (Sections 2.3 and 4.3.7) and BECCS (Sections 4.3.2. and 4.3.7) predominate. Other CDR options, such as the application of biochar to soil, soil carbon sequestration, and enhanced weathering (Section 4.3.7) are not yet widely incorporated into IAMs, but their deployment would also necessitate the use of land and/or changes in land management. Integrated assessment models provide a simplified representation of land use and, with only a few exceptions, do not include biophysical feedback processes (e.g., albedo and evapotranspiration effects) (Kreidenweis et al., 2016) despite the importance of these processes for regional climate, in particular hot extremes (Section 3.6.2.2; Seneviratne et al., 2018c). The extent, location and impacts of large-scale land-use change described by existing IAMs can also be widely divergent, depending on model structure, scenario parameters, modelling objectives and assumptions (including regarding land availability and productivity) (Prestele et 268 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Cross-Chapter Box 7 (continued) al., 2016; Alexander et al., 2017; Popp et al., 2017; Seneviratne et al., 2018c). Despite these limitations, IAM scenarios effectively highlight the extent and nature of potential land-use transitions implicit in limiting warming to 1.5°C. Cross-Chapter Box 7 Table 1 presents a comparison of the five CDR options assessed in this report. This illustrates that if BECCS and AR were to be deployed at a scale of 12 GtCO yr–12 in 2100, for example, they would have a substantial land and water footprint. Whether this footprint would result in adverse impacts, for example on biodiversity or food production, depends on the existence and effectiveness of measures to conserve land carbon stocks, limit the expansion of agriculture at the expense of natural ecosystems, and increase agriculture productivity (Bonsch et al., 2016; Obersteiner et al., 2016; Bertram et al., 2018; Humpenöder et al., 2018). In comparison, the land and water footprints of enhanced weathering, soil carbon sequestration and biochar application are expected to be far less per GtCO2 sequestered. These options may offer potential co-benefits by providing an additional source of nutrients or by reducing N2O emissions, but they are also associated with potential side effects. Enhanced weathering would require massive mining activity, and providing feedstock for biochar would require additional land, even though a proportion of the required biomass is expected to come from residues (Woolf et al., 2010; Smith, 2016). For the terrestrial CDR options, permanence and saturation are important considerations, making their viability and long-term contributions to carbon reduction targets uncertain. The technical, political and social feasibility of scaling up and implementing land-intensive CDR technologies (Cross-Chapter Box 3 in Chapter 1) is recognized to present considerable potential barriers to future deployment (Boucher et al., 2013a; Fuss et al., 2014, 2018; Anderson and Peters, 2016; Vaughan and Gough, 2016; Williamson, 2016; Minx et al., 2017, 2018; Nemet et al., 2018; Strefler et al., 2018; Vaughan et al., 2018). To investigate the implications of restricting CDR options should these barriers prove difficult to overcome, IAM studies (Section 2.3.4) have developed scenarios that limit – either implicitly or explicitly – the use of BECCS and bioenergy (Krey et al., 2014; Bauer et al., 2018; Rogelj et al., 2018) or the use of BECCS and afforestation (Strefler et al., 2018). Alternative strategies to limit future reliance on CDR have also been examined, including increased electrification, agricultural 3 intensification, behavioural change, and dramatic improvements in energy and material efficiency (Bauer et al., 2018; Grubler et al., 2018; van Vuuren et al., 2018). Somewhat counterintuitively, scenarios that seek to limit the deployment of BECCs may result in increased land use, through greater deployment of bioenergy, and afforestation (Chapter 2, Box 2.1; Krey et al., 2014; Krause et al., 2017; Bauer et al., 2018; Rogelj et al., 2018). Scenarios aiming to minimize the total human land footprint (including land for food, energy and climate mitigation) also result in land-use change, for example by increasing agricultural efficiency and dietary change (Grubler et al., 2018). The impacts of changing land use are highly context, location and scale dependent (Robledo-Abad et al., 2017). The supply of biomass for CDR (e.g., energy crops) has received particular attention. The literature identifies regional examples of where the use of land to produce biofuels might be sustainably increased (Jaiswal et al., 2017), where biomass markets could contribute to the provision of ecosystem services (Dale et al., 2017), and where bioenergy could increase the resilience of production systems and contribute to rural development (Kline et al., 2017). However, studies of global biomass potential provide only limited insight into the local feasibility of supplying large quantities of biomass on a global scale (Slade et al., 2014). Concerns about large-scale use of biomass for CDR include a range of potential consequences including greatly increased demand for freshwater use, increased competition for land, loss of biodiversity and/or impacts on food security (Section 3.6.2.1; Heck et al., 2018). The short- versus long- term carbon impacts of substituting biomass for fossil fuels, which are largely determined by feedstock choice, also remain a source of contention (Schulze et al., 2012; Jonker et al., 2014; Booth, 2018; Sterman et al., 2018). Afforestation and reforestation can also present trade-offs between biodiversity, carbon sequestration and water use, and these strategies have a higher land footprint per tonne of CO2 removed (Cunningham, 2015; Naudts et al., 2016; Smith et al., 2018). For example, changing forest management to strategies favouring faster growing species, greater residue extraction and shorter rotations may have a negative impact on biodiversity (de Jong et al., 2014). In contrast, reforestation of degraded land with native trees can have substantial benefits for biodiversity (Section 3.6). Despite these constraints, the potential for increased carbon sequestration through improved land stewardship measures is considered to be substantial (Griscom et al., 2017). Evaluating the synergies and trade-offs between mitigation and adaptation actions, resulting land and climate impacts, and the myriad issues related to land-use governance will be essential to better understand the future role of CDR technologies. This topic will be addressed further in the IPCC Special Report on Climate Change and Land (SRCCL) due to be published in 2019. Cross-Chapter Box 7 (continued next page) 269 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Cross-Chapter Box 7 (continued) Key messages: Cost-effective strategies to limit peak or end-of-century warming to 1.5°C all include enhanced GHG removals in the AFOLU sector as part of their portfolio of measures (high confidence). Large-scale deployment of land-based CDR would have far-reaching implications for land and water availability (high confidence). This may impact food production, biodiversity and the provision of other ecosystem services (high confidence). The impacts of deploying land-based CDR at large scales can be reduced if a wider portfolio of CDR options is deployed, and if increased mitigation effort focuses on strongly limiting demand for land, energy and material resources, including through lifestyle and dietary changes (medium confidence). Afforestation and reforestation may be associated with significant co-benefits if implemented appropriately, but they feature large land and water footprints if deployed at large scales (medium confidence). Cross-Chapter Box 7, Table 1 | Comparison of land-based carbon removal options. Sources: a assessed ranges by Fuss et al. (2018), see Figures in Section 4.3.7 for full literature range; b based on the 2100 estimate for mean potentials by Smith et al. (2015). Note that biophysical impacts of land-based CDR options besides albedo changes (e.g., through changes in evapotranspiration related to irrigation or land cover/use type) are not displayed. 3 Option Potentials a Cost a Required Required Impact on Impact on Saturation land b water b nutrients b albedo b and permanence a GtCO y−12 $ tCO −1 2 Mha GtCO −1 km32 GtCO −1 2 Mt N, P, K y −1 No units No units Variable; depends on source Long-term governance of of biofuel (higher albedo for storage; limits on rates of BECCS 0.5–5 100–200 31–58 60 Variable crops than for forests) and bioenergy production and on land management (e.g., carbon sequestration no-till farming for crops) Saturation of forests; Afforestation Negative, or reduced GHG vulnerable to disturbance; 0.5–3.6 5–50 80 92 0.5 & reforestation benefit where not negative post-AR forest management essential Saturation of soil; residence Enhanced 2–4 50–200 3 0.4 0 0 time from months to weathering geological timescale N: 8.2, Mean residence times P: 2.7, between decades to Biochar 0.3–2 30–120 16–100 0 K: 19.1 0.08–0.12 centuries, depending on soil type, management and environmental conditions N: 21.8, Soil sinks saturate and can Soil carbon 2.3–5 0–100 0 0 P: 5.5, 0 reverse if poor management sequestration K: 4.1 practices resume 3.6.3 Implications Beyond the End of the Century for climates in the late 20th and early 21st centuries. Further studies (Armour et al., 2011; Boucher et al., 2012; Ridley et al., 2012) modelled 3.6.3.1 Sea ice the removal of sea ice by raising CO2 concentrations and studied subsequent regrowth by lowering CO2. These studies suggest that Sea ice is often cited as a tipping point in the climate system (Lenton, changes in Arctic sea ice are neither irreversible nor exhibit bifurcation 2012). Detailed modelling of sea ice (Schröder and Connolley, 2007; behaviour. It is therefore plausible that the extent of Arctic sea ice may Sedláček et al., 2011; Tietsche et al., 2011), however, suggests that quickly re-equilibrate to the end-of-century climate under an overshoot summer sea ice can return within a few years after its artificial removal scenario. 270 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 3.6.3.2 Sea level yet further retreat (Schoof, 2007). More recently, a variant on this mechanism was postulated in which an ice cliff forms at the grounding Policy decisions related to anthropogenic climate change will have a line and retreats rapidly though fracture and iceberg calving (DeConto profound impact on sea level, not only for the remainder of this century and Pollard, 2016). There is a growing body of evidence (Golledge et but for many millennia to come (Clark et al., 2016). On these long time al., 2015; DeConto and Pollard, 2016) that large-scale retreat may be scales, 50 m of sea level rise (SLR) is possible (Clark et al., 2016). While it avoided in emissions scenarios such as Representative Concentration is virtually certain that sea level will continue to rise well beyond 2100, Pathway (RCP)2.6 but that higher-emissions RCP scenarios could lead the amount of rise depends on future cumulative emissions (Church et to the loss of the West Antarctic ice sheet and sectors in East Antarctica, al., 2013) as well as their profile over time (Bouttes et al., 2013; Mengel although the duration (centuries or millennia) and amount of mass loss et al., 2018). Marzeion et al. (2018) found that 28–44% of present-day during such a collapse is highly dependent on model details and no glacier volume is unsustainable in the present-day climate and that it consensus exists yet. Schoof (2007) suggested that retreat may be would eventually melt over the course of a few centuries, even if there irreversible, although a rigorous test has yet to be made. In this context, were no further climate change. Some components of SLR, such as overshoot scenarios, especially of higher magnitude or longer duration, thermal expansion, are only considered reversible on centennial time could increase the risk of such irreversible retreat. scales (Bouttes et al., 2013; Zickfeld et al., 2013), while the contribution from ice sheets may not be reversible under any plausible future Church et al. (2013) noted that the collapse of marine sectors of the scenario (see below). Antarctic ice sheet could lead to a global mean sea level (GMSL) rise above the likely range, and that there was medium confidence that this Based on the sensitivities summarized by Levermann et al. (2013), the additional contribution ‘would not exceed several tenths of a metre contributions of thermal expansion (0.20–0.63 m °C–1) and glaciers during the 21st century’. (0.21 m °C–1 but falling at higher degrees of warming mostly because of the depletion of glacier mass, with a possible total loss of about The multi-centennial evolution of the Antarctic ice sheet has been 0.6 m) amount to 0.5–1.2 m and 0.6–1.7 m in 1.5°C and 2°C warmer considered in papers by DeConto and Pollard (2016) and Golledge et worlds, respectively. The bulk of SLR on greater than centennial time al. (2015). Both suggest that RCP2.6 is the only RCP scenario leading 3 scales will therefore be caused by contributions from the continental to long-term contributions to GMSL of less than 1.0 m. The long-term ice sheets of Greenland and Antarctica, whose existence is threatened committed future of Antarctica and the GMSL contribution at 2100 on multi-millennial time scales. are complex and require further detailed process-based modelling; however, a threshold in this contribution may be located close to 1.5°C For Greenland, where melting from the ice sheet’s surface is important, to 2°C of global warming. a well-documented instability exists where the surface of a thinning ice sheet encounters progressively warmer air temperatures that In summary, there is medium confidence that a threshold in the long- further promote melting and thinning. A useful indicator associated term GMSL contribution of both the Greenland and Antarctic ice sheets with this instability is the threshold at which annual mass loss from lies around 1.5°C to 2°C of global warming relative to pre-industrial; the ice sheet by surface melt exceeds mass gain by snowfall. Previous however, the GMSL associated with these two levels of global warming estimates put this threshold at about 1.9°C to 5.1°C above pre- cannot be differentiated on the basis of the existing literature. industrial temperatures (Gregory and Huybrechts, 2006). More recent analyses, however, suggest that this threshold sits between 0.8°C 3.6.3.3 Permafrost and 3.2°C, with a best estimate at 1.6°C (Robinson et al., 2012). The continued decline of the ice sheet after this threshold has been passed The slow rate of permafrost thaw introduces a lag between the is highly dependent on the future climate and varies between about transient degradation of near-surface permafrost and contemporary 80% loss after 10,000 years to complete loss after as little as 2000 climate, so that the equilibrium response is expected to be 25–38% years (contributing about 6 m to SLR). Church et al. (2013) were unable greater than the transient response simulated in climate models (Slater to quantify a likely range for this threshold. They assigned medium and Lawrence, 2013). The long-term, equilibrium Arctic permafrost loss confidence to a range greater than 2°C but less than 4°C, and had to global warming was analysed by Chadburn et al. (2017). They used low confidence in a threshold of about 1°C. There is insufficient new an empirical relation between recent mean annual air temperatures literature to change this assessment. and the area underlain by permafrost coupled to Coupled Model Intercomparison Project Phase 5 (CMIP5) stabilization projections The Antarctic ice sheet, in contrast, loses the mass gained by snowfall to 2300 for RCP2.6 and RCP4.5. Their estimate of the sensitivity of as outflow and subsequent melt to the ocean, either directly from the permafrost to warming is 2.9–5.0 million km2 °C–1 (1 standard deviation underside of floating ice shelves or indirectly by the melting of calved confidence interval), which suggests that stabilizing climate at 1.5°C as icebergs. The long-term existence of this ice sheet will also be affected opposed to 2°C would reduce the area of eventual permafrost loss by by a potential instability (the marine ice sheet instability, MISI), which 1.5 to 2.5 million km2 (stabilizing at 56–83% as opposed to 43–72% of links outflow (or mass loss) from the ice sheet to water depth at the 1960–1990 levels). This work, combined with the assessment of Collins grounding line (i.e., the point at which grounded ice starts to float and et al. (2013) on the link between global warming and permafrost loss, becomes an ice shelf) so that retreat into deeper water (the bedrock leads to the assessment that permafrost extent would be appreciably underlying much of Antarctica slopes downwards towards the centre greater in a 1.5°C warmer world compared to in a 2°C warmer world of the ice sheet) leads to further increases in outflow and promotes (low to medium confidence). 271 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems 3.7 Knowledge Gaps • The distinct impacts of different overshoot scenarios, depending on (i) the peak temperature of the overshoot, (ii) the length of the overshoot period, and (iii) the associated rate of change in global Most scientific literature specific to global warming of 1.5°C is only temperature over the time period of the overshoot. just emerging. This has led to differences in the amount of information available and gaps across the various sections of this chapter. In 3.7.2.2 Physical and chemical characteristics of a 1.5°C general, the number of impact studies that specifically focused on warmer world 1.5°C lags behind climate-change projections in general, due in part to the dependence of the former on the latter. There are also insufficient • Critical thresholds for extreme events (e.g., drought and inundation) studies focusing on regional changes, impacts and consequences at between 1.5°C and 2°C of warming for different climate models 1.5°C and 2°C of global warming. and projections. All aspects of storm intensity and frequency as a function of climate change, especially for 1.5°C and 2°C warmer The following gaps have been identified with respect to tools, worlds, and the impact of changing storminess on storm surges, methodologies and understanding in the current scientific literature damage, and coastal flooding at regional and local scales. specific to Chapter 3. The gaps identified here are not comprehensive but highlight general areas for improved understanding, especially • The timing and implications of the release of stored carbon in regarding global warming at 1.5°C compared to 2°C and higher levels. Arctic permafrost in a 1.5°C warmer world and for climate stabilization by the end of the century. 3.7.1 Gaps in Methods and Tools • Antarctic ice sheet dynamics, global sea level, and links between • Regional and global climate model simulations for low-emissions seasonal and year-long sea ice in both polar regions. scenarios such as a 1.5°C warmer world. 3.7.2.3 Terrestrial and freshwater systems 3 • Robust probabilistic models which separate the relatively small signal between 1.5°C versus 2°C from background noise, and • The dynamics between climate change, freshwater resources and which handle the many uncertainties associated with non- socio-economic impacts for lower levels of warming. linearities, innovations, overshoot, local scales, and latent or lagging responses in climate. • How the health of vegetation is likely to change, carbon storage in plant communities and landscapes, and phenomena such as the • Projections of risks under a range of climate and development fertilization effect. pathways required to understand how development choices affect the magnitude and pattern of risks, and to provide better • The risks associated with species’ maladaptation in response to estimates of the range of uncertainties. climatic changes (e.g., effects of late frosts). Questions associated with issues such as the consequences of species advancing their • More complex and integrated socio-ecological models for predicting spring phenology in response to warming, as well as the interaction the response of terrestrial as well as coastal and oceanic ecosystems between climate change, range shifts and local adaptation in a to climate and models which are more capable of separating climate 1.5°C warmer world. effects from those associated with human activities. • The biophysical impacts of land use in the context of mitigation • Tools for informing local and regional decision-making, especially pathways. when the signal is ambiguous at 1.5°C and/or reverses sign at higher levels of global warming. 3.7.2.4 Ocean Systems 3.7.2 Gaps in Understanding • Deep sea processes and risks to deep sea habitats and ecosystems. 3.7.2.1 Earth systems and 1.5°C of global warming • How changes in ocean chemistry in a 1.5°C warmer world, including decreasing ocean oxygen content, ocean acidification • The cumulative effects of multiple stresses and risks (e.g., and changes in the activity of multiple ion species, will affect increased storm intensity interacting with sea level rise and the natural and human systems. effect on coastal people; feedbacks on wetlands due to climate change and human activities). • How ocean circulation is changing towards 1.5°C and 2°C warmer worlds, including vertical mixing, deep ocean processes, currents, • Feedbacks associated with changes in land use/cover for low- and their impacts on weather patterns at regional to local scales. emissions scenarios, for example feedback from changes in forest cover, food production, biofuel production, bio-energy with • The impacts of changing ocean conditions at 1.5°C and 2°C of carbon capture and storage (BECCS), and associated unquantified warming on foodwebs, disease, invading species, coastal protection, biophysical impacts. fisheries and human well-being, especially as organisms modify 272 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 their biogeographical ranges within a changing ocean. for natural and human systems, within cities and in interaction with surrounding areas. For example, current projections do not • Specific linkages between food security and changing coastal and integrate adaptation to projected warming by considering cooling ocean resources. that could be achieved through a combination of revised building codes, zoning and land use to build more reflective roofs and 3.7.2.5 Human systems urban surfaces that reduce urban heat island effects. • The impacts of global and regional climate change at 1.5°C on • Implications of climate change at 1.5°C on livelihoods and food distribution, nutrition, poverty, tourism, coastal infrastructure poverty, as well as on rural communities, indigenous groups and and public health, particularly for developing nations. marginalized people. • Health and well-being risks in the context of socio-economic • The changing levels of risk in terms of extreme events, including and climate change at 1.5°C, especially in key areas such as storms and heatwaves, especially with respect to people being occupational health, air quality and infectious disease. displaced or having to migrate away from sensitive and exposed systems such as small islands, low-lying coasts and deltas. • Micro-climates at urban/city scales and their associated risks 3 273 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Cross-Chapter Box 8 | 1.5°C Warmer Worlds Lead Authors: Sonia I. Seneviratne (Switzerland), Joeri Rogelj (Austria/Belgium), Roland Séférian (France), Myles R. Allen (United Kingdom), Marcos Buckeridge (Brazil), Kristie L. Ebi (United States of America), Ove Hoegh-Guldberg (Australia), Richard J. Millar (United Kingdom), Antony J. Payne (United Kingdom), Petra Tschakert (Australia), Rachel Warren (United Kingdom) Contributing Authors: Neville Ellis (Australia), Richard Wartenburger (Germany/Switzerland) Introduction The Paris Agreement includes goals of stabilizing global mean surface temperature (GMST) well below 2°C and 1.5°C above pre- industrial levels in the longer term. There are several aspects, however, that remain open regarding what a ‘1.5°C warmer world’ could be like, in terms of mitigation (Chapter 2) and adaptation (Chapter 4), as well as in terms of projected warming and associated regional climate change (Chapter 3), which are overlaid on anticipated and differential vulnerabilities (Chapter 5). Alternative ‘1.5°C warmer worlds’ resulting from mitigation and adaptation choices, as well as from climate variability (climate ‘noise’), can be vastly different, as highlighted in this Cross-Chapter Box. In addition, the range of models underlying 1.5°C projections can be substantial and needs to be considered. Key questions7: 3 • What is a 1.5°C global mean warming, how is it measured, and what temperature increase does it imply for single locations and at specific times? Global mean surface temperature (GMST) corresponds to the globally averaged temperature of Earth derived from point-scale ground observations or computed in climate models (Chapters 1 and 3). Global mean surface temperature is additionally defined over a given time frame, for example averaged over a month, a year, or multiple decades. Because of climate variability, a climate-based GMST typically needs to be defined over several decades (typically 20 or 30 years; Chapter 3, Section 3.2). Hence, whether or when global warming reaches 1.5°C depends to some extent on the choice of pre-industrial reference period, whether 1.5°C refers to total or human-induced warming, and which variables and coverage are used to define GMST change (Chapter 1). By definition, because GMST is an average in time and space, there will be locations and time periods in which 1.5°C of warming is exceeded, even if the global mean warming is at 1.5°C. In some locations, these differences can be particularly large (Cross-Chapter Box 8, Figure 1). • What is the impact of different climate models for projected changes in climate at 1.5°C of global warming? The range between single model simulations of projected regional changes at 1.5°C GMST increase can be substantial for regional responses (Chapter 3, Section 3.3). For instance, for the warming of cold extremes in a 1.5°C warmer world, some model simulations project a 3°C warming while others project more than 6°C of warming in the Arctic land areas (Cross- Chapter Box 8, Figure 2). For hot temperature extremes in the contiguous United States, the range of model simulations includes temperatures lower than pre-industrial values (–0.3°C) and a warming of 3.5°C (Cross-Chapter Box 8, Figure 2). Some regions display an even larger range (e.g., 1°C–6°C regional warming in hot extremes in central Europe at 1.5°C of warming; Chapter 3, Sections 3.3.1 and 3.3.2). This large spread is due to both modelling uncertainty and internal climate variability. While the range is large, it also highlights risks that can be avoided with near certainty in a 1.5°C warmer world compared to worlds at higher levels of warming (e.g., an 8°C warming of cold extremes in the Arctic is not reached at 1.5°C of global warming in the multimodel ensemble but could happen at 2°C of global warming; Cross-Chapter Box 8, Figure 2). Inferred projected ranges of regional responses (mean value, minimum and maximum) for different mitigation scenarios from Chapter 2 are displayed in Cross-Chapter Box 8, Table 1. • What is the impact of emissions pathways with, versus without, an overshoot? All mitigation pathways projecting less than 1.5°C of global warming over or at the end of the 21st century include some probability of overshooting 1.5°C. These pathways include some periods with warming stronger than 1.5°C in the course of the coming decades and/or some probability of not reaching 1.5°C (Chapter 2, Section 2.2). This is inherent to the difficulty of limiting global warming to 1.5°C, given that we are already very close to this warming level. The implications of overshooting are large for risks to natural and human 7 Pa rt of this discussion is based on Seneviratne et al. (2018b). 274 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Cross-Chapter Box 8 (continued) 3 Cross-Chapter Box 8, Figure 1 | Range of projected realized temperatures at 1.5°C of global warming (due to stochastic noise and model-based spread). Temperatures with a 25% chance of occurrence at any location within a 10-year time frame are shown, corresponding to GMST anomalies of 1.5°C (Coupled Model Intercomparison Project Phase 5 (CMIP5) multimodel ensemble). The plots display the 25th percentile (Q25, left) and 75th percentile (Q75, right) values of mean temperature (Tmean), yearly maximum daytime temperature (TXx) and yearly minimum night-time temperature (TNn), sampled from all time frames with GMST anomalies of 1.5°C in Representative Concentration Pathway (RCP)8.5 model simulations of the CMIP5 ensemble. From Seneviratne et al. (2018b). Cross-Chapter Box 8 (continued next page) 275 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Cross -Chapter Box 8 (continued) Global mean temperature anomaly relative to pre-industrial conditions (°C) Cross-Chapter Box 8, Figure 2 | Spread of projected multimodel changes in minimum annual night-time temperature (TNn) in Arctic land (left) and in maximum annual daytime temperature (TXx) in the contiguous United States as a function of mean global warming in climate simulations. The multimodel range (due to model spread and internal climate variability) is indicated in red shading (minimum and maximum value based on climate model simulations). The multimodel mean value is displayed with solid red and blue lines for two emissions pathways (blue: Representative Concentration Pathway (RCP)4.5; red: RCP8.5). The dashed red line indicates projections for a 1.5°C warmer world. The dashed black line displays the 1:1 line. The figure is based on Figure 3 of Seneviratne et al. (2016). 3 systems, especially if the temperature at peak warming is high, because some risks may be long lasting and irreversible, such as the loss of some ecosystems (Chapter 3, Box 3.4). The chronology of emissions pathways and their implied warming is also important for the more slowly evolving parts of the Earth system, such as those associated with sea level rise. In addition, for several types of risks the rate of change may be most relevant (Loarie et al., 2009; LoPresti et al., 2015), with potentially large risks occurring in the case of a rapid rise to overshooting temperatures, even if a decrease to 1.5°C may be achieved at the end of the 21st century or later. On the other hand, if overshoot is to be minimized, the remaining equivalent CO2 budget available for emissions has to be very small, which implies that large, immediate and unprecedented global efforts to mitigate GHGs are required (Cross-Chapter Box 8, Table 1; Chapter 4). • What is the probability of reaching 1.5°C of global warming if emissions compatible with 1.5°C pathways are followed? Emissions pathways in a ‘prospective scenario’ (see Chapter 1, Section 1.2.3, and Cross-Chapter Box 1 in Chapter 1 on ‘Scenarios and pathways’) compatible with 1.5°C of global warming are determined based on their probability of reaching 1.5°C by 2100 (Chapter 2, Section 2.1), given current knowledge of the climate system response. These probabilities cannot be quantified precisely but are typically 50–66% in 1.5°C-consistent pathways (Section 1.2.3). This implies a one-in-two to one-in-three probability that global warming would exceed 1.5°C even under a 1.5°C-consistent pathway, including some possibility that global warming would be substantially over this value (generally about 5–10% probability; see Cross-Chapter Box 8, Table 1 and Seneviratne et al., 2018b). These alternative outcomes need to be factored into the decision-making process. To address this issue, ‘adaptive’ mitigation scenarios have been proposed in which emissions are continually adjusted to achieve a temperature goal (Millar et al., 2017). The set of dimensions involved in mitigation options (Chapter 4) is complex and need system-wide approaches to be successful. Adaptive scenarios could be facilitated by the global stocktake mechanism established in the Paris Agreement, and thereby transfer the risk of higher-than-expected warming to a risk of faster-than- expected mitigation efforts. However, there are some limits to the feasibility of such approaches because some investments, for example in infrastructure, are long term and also because the actual departure from an aimed pathway will need to be detected against the backdrop of internal climate variability, typically over several decades (Haustein et al., 2017; Seneviratne et al., 2018b). Avoiding impacts that depend on atmospheric composition as well as GMST (Baker et al., 2018) would also require limits on atmospheric CO2 concentrations in the event of a lower-than-expected GMST response. • How can the transformation towards a 1.5°C warmer world be implemented? This can be achieved in a variety of ways, such as decarbonizing the economy with an emphasis on demand reductions and sustainable lifestyles, or, alternatively, with an emphasis on large-scale technological solutions, amongst many other options (Chapter 2, Sections 2.3 and 2.4; Chapter 4, Sections 4.1 and 4.4.4). Different portfolios of mitigation measures come with distinct synergies and trade-offs with respect to other societal objectives. Integrated solutions and approaches are required to achieve multiple societal objectives simultaneously (see Chapter 4, Section 4.5.4 for a set of synergies and trade-offs). 276 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Cross-Chapter Box 8 (continued) • What determines risks and opportunities in a 1.5°C warmer world? The risks to natural, managed and human systems in a 1.5°C warmer world will depend not only on uncertainties in the regional climate that results from this level of warming, but also very strongly on the methods that humanity uses to limit global warming to 1.5°C. This is particularly the case for natural ecosystems and agriculture (see Cross-Chapter Box 7 in this chapter and Chapter 4, Section 4.3.2). The risks to human systems will also depend on the magnitude and effectiveness of policies and measures implemented to increase resilience to the risks of climate change and on development choices over coming decades, which will influence the underlying vulnerabilities and capacities of communities and institutions for responding and adapting. • Which aspects are not considered, or only partly considered, in the mitigation scenarios from Chapter 2? These include biophysical impacts of land use, water constraints on energy infrastructure, and regional implications of choices of specific scenarios for tropospheric aerosol concentrations or the modulation of concentrations of short-lived climate forcers, that is, greenhouse gases (Chapter 3, Section 3.6.3). Such aspects of development pathways need to be factored into comprehensive assessments of the regional implications of mitigation and adaptation measures. On the other hand, some of these aspects are assessed in Chapter 4 as possible options for mitigation and adaptation to a 1.5°C warmer world. • Are there commonalities to all alternative 1.5°C warmer worlds? Human-driven warming linked to CO2 emissions is nearly irreversible over time frames of 1000 years or more (Matthews and Caldeira, 2008; Solomon et al., 2009). The GSMT of the Earth responds to the cumulative amount of CO2 emissions. Hence, all 1.5°C stabilization scenarios require both net CO2 emissions and multi-gas CO2-forcing-equivalent emissions to be zero at some point (Chapter 2, Section 2.2). This is also the case for stabilization scenarios at higher levels of warming (e.g., at 2°C); the only difference is the projected time at which the net CO2 budget is zero. Hence, a transition to decarbonization of energy use is necessary in all scenarios. It should be noted that all scenarios 3 of Chapter 2 include approaches for carbon dioxide removal (CDR) in order to achieve the net zero CO2 emissions budget. Most of these use carbon capture and storage (CCS) in addition to reforestation, although to varying degrees (Chapter 4, Section 4.3.7). Some potential pathways to 1.5°C of warming in 2100 would minimize the need for CDR (Obersteiner et al., 2018; van Vuuren et al., 2018). Taking into account the implementation of CDR, the CO2-induced warming by 2100 is determined by the difference between the total amount of CO2 generated (that can be reduced by early decarbonization) and the total amount permanently stored out of the atmosphere, for example by geological sequestration (Chapter 4, Section 4.3.7). • What are possible storylines of ‘warmer worlds’ at 1.5°C versus higher levels of global warming? Cross-Chapter Box 8, Table 2 features possible storylines based on the scenarios of Chapter 2, the impacts of Chapters 3 and 5, and the options of Chapter 4. These storylines are not intended to be comprehensive of all possible future outcomes. Rather, they are intended as plausible scenarios of alternative warmer worlds, with two storylines that include stabilization at 1.5°C (Scenario 1) or close to 1.5°C (Scenario 2), and one storyline missing this goal and consequently only including reductions of CO2 emissions and efforts towards stabilization at higher temperatures (Scenario 3). Summary: There is no single ‘1.5°C warmer world’. Impacts can vary strongly for different worlds characterized by a 1.5°C global warming. Important aspects to consider (besides the changes in global temperature) are the possible occurrence of an overshoot and its associated peak warming and duration, how stabilization of the increase in global surface temperature at 1.5°C could be achieved, how policies might be able to influence the resilience of human and natural systems, and the nature of regional and subregional risks. The implications of overshooting are large for risks to natural and human systems, especially if the temperature at peak warming is high, because some risks may be long lasting and irreversible, such as the loss of some ecosystems. In addition, for several types of risks, the rate of change may be most relevant, with potentially large risks occurring in the case of a rapid rise to overshooting temperatures, even if a decrease to 1.5°C may be achieved at the end of the 21st century or later. If overshoot is to be minimized, the remaining equivalent CO2 budget available for emissions has to be very small, which implies that large, immediate and unprecedented global efforts to mitigate GHGs are required. The time frame for initiating major mitigation measures is essential in order to reach a 1.5°C (or even a 2°C) global stabilization of climate warming (see consistent cumulative CO2 emissions up to peak warming in Cross-Chapter Box 8, Table 1). If mitigation pathways are not rapidly activated, much more expensive and complex adaptation measures will have to be taken to avoid the impacts of higher levels of global warming on the Earth system. Cross-Chapter Box 8 (continued next page) 277 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Cross-Chapter Box 8 (continued) Cross-Chapter Box 8, Table 1 | Different worlds resulting from 1.5°C and 2°C mitigation (prospective) pathways, including 66% (probable) best-case outcome, and 5% worst-case outcome, based on Chapter 2 scenarios and Chapter 3 assessments of changes in regional climate. Note that the pathway characteristics estimates are based on computations with the MAGICC model (Meinshausen et al., 2011) consistent with the set-up used in AR5 WGIII (Clarke et al., 2014), but are uncertain and will be subject to updates and adjust-ments (see Chapter 2 for details). Updated from Seneviratne et al. (2018b). B1.5_LOS (below 1.5°C B1.5_LOS (below 1.5°C L20 (lower than 2°C) L20 (lower than 2°C) with low overshoot) with low overshoot) with 2/3 ´probable with 1/20 ´worst-case with 2/3 ´probable with 1/20 ´worst-case best-case outcome´a outcome´b best-case outcome´a outcome´b Overshoot > 1.5°C in 21st centuryc Yes (51/51) Yes (51/51) Yes (72/72) Yes (72/72) Overshoot > 2°C in 21st century No (0/51) Yes (37/51) No (72/72) Yes (72/72) Cumulative CO2 emissions up to peak 610–760 590–750 1150–1460 1130–1470 warming (relative to 2016)d [GtCO2] Cumulative CO2 emissions up to 170–560 1030–1440 2100 (relative to 2016)d [GtCO2] Global GHG emissions in 2030d [GtCO2 y-1] 19–23 31–38 Years of global net zero CO2 emissions d 2055–2066 2082–2090 Global mean temperature 1.7°C (1.66°C–1.72°C) 2.05°C (2.00°C–2.09°C) 2.11°C (2.05°C–2.17°C) 2.67°C (2.59°C–2.76°C) anomaly at peak warming Warming in the Arctice (TNnf) 4.93°C (4.36, 5.52) 6.02°C (5.12, 6.89) 6.24°C (5.39, 7.21) 7.69°C (6.69, 8.93) Warming in Central North Americae (TXxg) 2.65°C (1.92, 3.15) 3.11°C (2.37, 3.63) 3.18°C (2.50, 3.71) 4.06°C (3.35, 4.63) 3 Warming in Amazon regione (TXx) 2.55°C (2.23, 2.83) 3.07°C (2.74, 3.46) 3.16°C (2.84, 3.57) 4.05°C (3.62, 4.46) Drying in the Mediterranean regione,h –1.11 (–2.24, –0.41) –1.28 (–2.44, –0.51) –1.38 (–2.58, –0.53) –1.56 (–3.19, –0.67) Increase in heavy precipita- 9.94% (6.76, 14.00) 11.94% (7.52, 18.86) 12.68% (7.71, 22.39) 19.67% (11.56, 27.24) tion eventse in Southern Asiai Global mean temperature 1.46°C (1.41°C–1.51°C) 1.87°C (1.81°C–1.94°C) 2.06°C (1.99°C–2.15°C) 2.66°C (2.56°C–2.76°C) warming in 2100 Warming in the Arcticj (TNn) 4.28°C (3.71, 4.77) 5.50°C (4.74, 6.21) 6.08°C (5.20, 6.94) 7.63°C (6.66, 8.90) Warming in Central North Americaj (TXx) 2.31°C (1.56, 2.66) 2.83°C (2.03, 3.49) 3.12°C (2.38, 3.67) 4.06°C (3.33, 4.59) Warming in Amazon regionj (TXx) 2.22°C (2.00, 2.45) 2.76°C (2.50, 3.07) 3.10°C (2.75, 3.49) 4.03°C (3.62, 4.45) Drying in the Mediterranean regionj –0.95 (–1.98, –0.30) –1.10 (–2.17, –0.51) –1.26 (–2.43, –0.52) –1.55 (–3.17, –0.67) Increase in heavy precipitation events 8.38% (4.63, 12.68) 10.34% (6.64, 16.07) 12.02% (7.41, 19.62) 19.72% (11.34, 26.95) in Southern Asiaj Notes: a) 66th percentile for global temperature (that is, 66% likelihood of being at or below values) b) 95th percentile for global temperature (that is, 5% likelihood of being at or above values) c) All 1.5°C scenarios include a substantial probability of overshooting above 1.5°C global warming before returning to 1.5°C. d) Interquartile range (25th percentile, q25, and 75th percentile, q75) e) The regional projections in these rows provide the median and the range [q25, q75] associated with the median global temperature outcomes of the considered mitigation scenarios at peak warming. f) TNn: Annual minimum night-time temperature g) TXx: Annual maximum day-time temperature h) Indicates drying of soil moisture expressed in units of standard deviations of pre-industrial climate (1861–1880) variability (where −1 is dry; −2 is severely dry; and −3 is very severely dry); i) Rx5day: the annual maximum consecutive 5-day precipitation. j) As for footnote e, but for the regional responses associated with the median global temperature outcomes of the considered mitigation scenarios in 2100 278 Possible climate range Possible climate range at peak General characteristics in 2100 (regional+global) warming (regional+global) of pathway Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Cross-Chapter Box 8 (continued) Cross-Chapter Box 8, Table 2 | Storylines of possible worlds resulting from different mitigation options. The storylines build upon Cross-Chapter Box 8, Table 1 and the assessments of Chapters 1–5. Only a few of the many possible storylines were chosen and they are presented for illustrative purposes. Scenario 1 [one possible storyline In 2020, strong participation and support for the Paris Agreement and its ambitious goals for reducing CO2 emissions among best-case scenarios]: by an almost unanimous international community led to a time frame for net zero emissions that is compatible with halting global warming at 1.5°C by 2100. Mitigation: early move to decarbonization, There is strong participation in all major world regions at the national, state and/or city levels. Transport is strongly decarbonized decarbonization designed to minimize through a shift to electric vehicles, with more cars with electric than combustion engines being sold by 2025 (Chapter 2, Section land footprint, coordination and 2.4.3; Chapter 4, Section 4.3.3). Several industry-sized plants for carbon capture and storage are installed and tested in the 2020s rapid action of the world’s nations (Chapter 2, Section 2.4.2; Chapter 4, Sections 4.3.4 and 4.3.7). Competition for land between bioenergy cropping, food production, towards 1.5°C goal by 2100 and biodiversity conservation is minimized by sourcing bioenergy for carbon capture and storage from agricultural wastes, algae and kelp farms (Cross-Chapter Box 7 in Chapter 3; Chapter 4, Section 4.3.2). Agriculture is intensified in countries with coordinated Internal climate variability: planning associated with a drastic decrease in food waste (Chapter 2, Section 2.4.4; Chapter 4, Section 4.3.2). This leaves many probable (66%) best-case outcome for natural ecosystems relatively intact, supporting continued provision of most ecosystem services, although relocation of species global and regional climate responses towards higher latitudes and elevations still results in changes in local biodiversity in many regions, particularly in mountain, tropical, coastal and Arctic ecosystems (Chapter 3, Section 3.4.3). Adaptive measures such as the establishment of corridors for the movement of species and parts of ecosystems become a central practice within conservation management (Chapter 3, Section 3.4.3; Chapter 4, Section 4.3.2). The movement of species presents new challenges for resource management as novel ecosystems, as well as pests and disease, increase (Cross-Chapter Box 6 in Chapter 3). Crops are grown on marginal land, no-till agriculture is deployed, and large areas are reforested with native trees (Chapter 2, Section 2.4.4; Chapter 3, Section 3.6.2; Cross-Chapter Box 7 in Chapter 3; Chapter 4, Section 4.3.2). Societal preference for healthy diets reduces meat consumption and associated GHG emissions (Chapter 2, Section 2.4.4; Chapter 4, Section 4.3.2; Cross-Chapter Box 6 in Chapter 3). By 2100, global mean temperature is on average 0.5°C warmer than it was in 2018 (Chapter 1, Section 1.2.1). Only a minor temperature overshoot occurs during the century (Chapter 2, Section 2.2). In mid-latitudes, frequent hot summers and precipitation 3 events tend to be more intense (Chapter 3, Section 3.3). Coastal communities struggle with increased inundation associated with rising sea levels and more frequent and intense heavy rainfall (Chapter 3, Sections 3.3.2 and 3.3.9; Chapter 4, Section 4.3.2; Chapter 5, Box 5.3 and Section 5.3.2; Cross-Chapter Box 12 in Chapter 5), and some respond by moving, in many cases with consequences for urban areas. In the tropics, in particular in megacities, there are frequent deadly heatwaves whose risks are reduced by proactive adaptation (Chapter 3, Sections 3.3.1 and 3.4.8; Chapter 4, Section 4.3.8), overlaid on a suite of development challenges and limits in disaster risk management (Chapter 4, Section 4.3.3; Chapter 5, Sections 5.2.1 and 5.2.2; Cross-Chapter Box 12 in Chapter 5). Glaciers extent decreases in most mountainous areas (Chapter 3, Sections 3.3.5 and 3.5.4). Reduced Arctic sea ice opens up new shipping lanes and commercial corridors (Chapter 3, Section 3.3.8; Chapter 4, Box 4.3). Small island developing states (SIDS), as well as coastal and low-lying areas, have faced significant changes but have largely persisted in most regions (Chapter 3, Sections 3.3.9 and 3.5.4, Box 3.5). The Mediterranean area becomes drier (Chapter 3, Section 3.3.4 and Box 3.2) and irrigation of crops expands, drawing the water table down in many areas (Chapter 3, Section 3.4.6). The Amazon is reasonably well preserved, through avoided risk of droughts (Chapter 3, Sections 3.3.4 and 3.4.3; Chapter 4, Box 4.3) and reduced deforestation (Chapter 2, Section 2.4.4; Cross-Chapter Box 7 in Chapter 3; Chapter 4, Section 4.3.2), and the forest services are working with the pattern observed at the beginning of the 21st century (Chapter 4, Box 4.3). While some climate hazards become more frequent (Chapter 3, Section 3.3), timely adaptation measures help reduce the associated risks for most, although poor and disadvantaged groups continue to experience high climate risks to their livelihoods and well-being (Chapter 5, Section 5.3.1; Cross-Chapter Box 12 in Chapter 5; Chapter 3, Boxes 3.4 and 3.5; Cross-Chapter Box 6 in Chapter 3). Summer sea ice has not completely disappeared from the Arctic (Chapter 3, Section 3.4.4.7) and coral reefs, having been driven to a low level (10–30% of levels in 2018), have partially recovered by 2100 after extensive dieback (Chapter 3, Section 3.4.4.10 and Box 3.4). The Earth system, while warmer, is still recognizable compared to the 2000s, and no major tipping points are reached (Chapter 3, Section 3.5.2.5). Crop yields remain relatively stable (Chapter 3, Section 3.4). Aggregate economic damage of climate change impacts is relatively small, although there are some local losses associated with extreme weather events (Chapter 3, Section 3.5; Chapter 4). Human well-being remains overall similar to that in 2020 (Chapter 5, Section 5.2.2). Scenario 2 [one possible storyline The international community continues to largely support the Paris Agreement and agrees in 2020 on reduction among mid-case scenarios]: targets for CO2 emissions and time frames for net zero emissions. However, these targets are not ambitious enough to reach stabilization at 2°C of warming, let alone 1.5°C. Mitigation: delayed action (ambitious targets In the 2020s, internal climate variability leads to higher warming than projected, in a reverse development to what reached only after warmer decade happened in the so-called ‘hiatus’ period of the 2000s. Temperatures are regularly above 1.5°C of warming, although in the 2020s due to internal climate radiative forcing is consistent with a warming of 1.2°C or 1.3°C. Deadly heatwaves in major cities (Chicago, Kolkata, Beijing, variability), overshoot at 2°C, decrease Karachi, São Paulo), droughts in southern Europe, southern Africa and the Amazon region, and major flooding in Asia, all towards 1.5°C afterward, no efforts to intensified by the global and regional warming (Chapter 3, Sections 3.3.1, 3.3.2, 3.3.3, 3.3.4 and 3.4.8; Cross-Chapter minimize the land and water footprints Box 11 in Chapter 4), lead to increasing levels of public unrest and political destabilization (Chapter 5, Section 5.2.1). An of bioenergy emergency global summit in 2025 moves to much more ambitious climate targets. Costs for rapidly phasing out fossil fuel use and infrastructure, while rapidly expanding renewables to reduce emissions, are much higher than in Scenario 1, owing to a failure to Internal climate variability: support economic measures to drive the transition (Chapter 4). Disruptive technologies become crucial to face up to the adaptation 10% worst-case outcome (2020s) measures needed (Chapter 4, Section 4.4.4). followed by normal internal climate variability 279 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Cross-Chapter Box 8 (continued) Cross-Chapter Box 8, Table 2 (continued) Scenario 2 [one possible storyline Temperature peaks at 2°C of warming by the middle of the century before decreasing again owing to intensive implementation among mid-case scenarios]: of bioenergy plants with carbon capture and storage (Chapter 2), without efforts to minimize the land and water footprint of bioenergy production (Cross-Chapter Box 7 in Chapter 3). Reaching 2°C of warming for several decades eliminates or severely Mitigation: damages key ecosystems such as coral reefs and tropical forests (Chapter 3, Section 3.4). The elimination of coral reef ecosystems delayed action (ambitious targets and the deterioration of their calcified frameworks, as well as serious losses of coastal ecosystems such as mangrove forests and reached only after warmer decade seagrass beds (Chapter 3, Boxes 3.4 and 3.5, Sections 3.4.4.10 and 3.4.5), leads to much reduced levels of coastal defence from in the 2020s due to internal climate storms, winds and waves. These changes increase the vulnerability and risks facing communities in tropical and subtropical regions, variability), overshoot at 2°C, decrease with consequences for many coastal communities (Cross-Chapter Box 12 in Chapter 5). These impacts are being amplified by towards 1.5°C afterward, no efforts to steadily rising sea levels (Chapter 3, Section 3.3.9) and intensifying storms (Chapter 3, Section 3.4.4.3). The intensive area required minimize the land and water footprints for the production of bioenergy, combined with increasing water stress, puts pressure on food prices (Cross-Chapter Box 6 in of bioenergy Chapter 3), driving elevated rates of food insecurity, hunger and poverty (Chapter 4, Section 4.3.2; Cross-Chapter Box 6 in Chapter 3; Cross-Chapter Box 11 in Chapter 4). Crop yields decline significantly in the tropics, leading to prolonged famines in some African Internal climate variability: countries (Chapter 3, Section 3.4; Chapter 4, Section 4.3.2). Food trumps environment in terms of importance in most countries, with 10% worst-case outcome (2020s) the result that natural ecosystems decrease in abundance, owing to climate change and land-use change (Cross-Chapter Box 7 in followed by normal internal Chapter 3). The ability to implement adaptive action to prevent the loss of ecosystems is hindered under the circumstances and climate variability is consequently minimal (Chapter 3, Sections 3.3.6 and 3.4.4.10). Many natural ecosystems, in particular in the Mediterranean, are lost because of the combined effects of climate change and land-use change, and extinction rates increase greatly (Chapter 3, Section 3.4 and Box 3.2). By 2100, warming has decreased but is still stronger than 1.5°C, and the yields of some tropical crops are recovering (Chapter 3, Section 3.4.3). Several of the remaining natural ecosystems experience irreversible climate change-related damages whilst others have been lost to land-use change, with very rapid increases in the rate of species extinctions (Chapter 3, Section 3.4; 3 Cross-Chapter Box 7 in Chapter 3; Cross-Chapter Box 11 in Chapter 4). Migration, forced displacement, and loss of identity are extensive in some countries, reversing some achievements in sustainable development and human security (Chapter 5, Section 5.3.2). Aggregate economic impacts of climate change damage are small, but the loss in ecosystem services creates large economic losses (Chapter 4, Sections 4.3.2 and 4.3.3). The health and well-being of people generally decrease from 2020, while the levels of poverty and disadvantage increase considerably (Chapter 5, Section 5.2.1). Scenario 3 [one possible storyline In 2020, despite past pledges, the international support for the Paris Agreement starts to wane. In the years that among worst-case scenarios]: follow, CO2 emissions are reduced at the local and national level but efforts are limited and not always successful. Mitigation: Radiative forcing increases and, due to chance, the most extreme events tend to happen in less populated regions and thus do not uncoordinated action, major increase global concerns. Nonetheless, there are more frequent heatwaves in several cities and less snow in mountain resorts in actions late in the 21st century, the Alps, Rockies and Andes (Chapter 3, Section 3.3). Global warming of 1.5°C is reached by 2030 but no major changes in policies 3°C of warming in 2100 occur. Starting with an intense El Niño–La Niña phase in the 2030s, several catastrophic years occur while global warming starts to approach 2°C. There are major heatwaves on all continents, with deadly consequences in tropical regions and Asian megacities, Internal climate variability: especially for those ill-equipped for protecting themselves and their communities from the effects of extreme temperatures unusual (ca. 10%) best-case scenario (Chapter 3, Sections 3.3.1, 3.3.2 and 3.4.8). Droughts occur in regions bordering the Mediterranean Sea, central North America, for one decade, followed by normal the Amazon region and southern Australia, some of which are due to natural variability and others to enhanced greenhouse gas internal climate variability forcing (Chapter 3, Section 3.3.4; Chapter 4, Section 4.3.2; Cross-Chapter Box 11 in Chapter 4). Intense flooding occurs in high- latitude and tropical regions, in particular in Asia, following increases in heavy precipitation events (Chapter 3, Section 3.3.3). Major ecosystems (coral reefs, wetlands, forests) are destroyed over that period (Chapter 3, Section 3.4), with massive disruption to local livelihoods (Chapter 5, Section 5.2.2 and Box 5.3; Cross-Chapter Box 12 in Chapter 5). An unprecedented drought leads to large impacts on the Amazon rainforest (Chapter 3, Sections 3.3.4 and 3.4), which is also affected by deforestation (Chapter 2). A hurricane with intense rainfall and associated with high storm surges (Chapter 3, Section 3.3.6) destroys a large part of Miami. A two-year drought in the Great Plains in the USA and a concomitant drought in eastern Europe and Russia decrease global crop production (Chapter 3, Section 3.3.4), resulting in major increases in food prices and eroding food security. Poverty levels increase to a very large scale, and the risk and incidence of starvation increase considerably as food stores dwindle in most countries; human health suffers (Chapter 3, Section 3.4.6.1; Chapter 4, Sections 4.3.2 and 4.4.3; Chapter 5, Section 5.2.1). There are high levels of public unrest and political destabilization due to the increasing climatic pressures, resulting in some countries becoming dysfunctional (Chapter 4, Sections 4.4.1 and 4.4.2). The main countries responsible for the CO2 emissions design rapidly conceived mitigation plans and try to install plants for carbon capture and storage, in some cases without sufficient prior testing (Chapter 4, Section 4.3.6). Massive investments in renewable energy often happen too late and are uncoordinated; energy prices soar as a result of the high demand and lack of infrastructure. In some cases, demand cannot be met, leading to further delays. Some countries propose to consider sulphate-aerosol based Solar Radiation Modification (SRM) (Chapter 4, Section 4.3.8); however, intensive international negotiations on the topic take substantial time and are inconclusive because of overwhelming concerns about potential impacts on monsoon rainfall and risks in case of termination (Cross-Chapter Box 10 in Chapter 5). Global and regional temperatures continue to increase strongly while mitigation solutions are being developed and implemented. 280 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Cross-Chapter Box 8 (continued) Cross-Chapter Box 8, Table 2 (continued) Scenario 3 [one possible storyline Global mean warming reaches 3°C by 2100 but is not yet stabilized despite major decreases in yearly CO2 emissions, as a net zero among worst-case scenarios]: CO2 emissions budget could not yet be achieved and because of the long lifetime of CO2 concentrations (Chapters 1, 2 and 3). The world as it was in 2020 is no longer recognizable, with decreasing life expectancy, reduced outdoor labour productivity, and Mitigation: lower quality of life in many regions because of too frequent heatwaves and other climate extremes (Chapter 4, Section 4.3.3). uncoordinated action, major Droughts and stress on water resources renders agriculture economically unviable in some regions (Chapter 3, Section 3.4; Chapter actions late in the 21st century, 4, Section 4.3.2) and contributes to increases in poverty (Chapter 5, Section 5.2.1; Cross-Chapter Box 12 in Chapter 5). Progress on 3°C of warming in 2100 the sustainable development goals is largely undone and poverty rates reach new highs (Chapter 5, Section 5.2.3). Major conflicts take place (Chapter 3, Section 3.4.9.6; Chapter 5, Section 5.2.1). Almost all ecosystems experience irreversible impacts, species Internal climate variability: extinction rates are high in all regions, forest fires escalate, and biodiversity strongly decreases, resulting in extensive losses to unusual (ca. 10%) best-case scenario ecosystem services. These losses exacerbate poverty and reduce quality of life (Chapter 3, Section 3.4; Chapter 4, Section 4.3.2). for one decade, followed by normal Life for many indigenous and rural groups becomes untenable in their ancestral lands (Chapter 4, Box 4.3; Cross-Chapter Box 12 internal climate variability in Chapter 5). The retreat of the West Antarctic ice sheet accelerates (Chapter 3, Sections 3.3 and 3.6), leading to more rapid sea level rise (Chapter 3, Section 3.3.9; Chapter 4, Section 4.3.2). Several small island states give up hope of survival in their locations and look to an increasingly fragmented global community for refuge (Chapter 3, Box 3.5; Cross-Chapter Box 12 in Chapter 5). Aggregate economic damages are substantial, owing to the combined effects of climate changes, political instability, and losses of ecosystem services (Chapter 4, Sections 4.4.1 and 4.4.2; Chapter 3, Box 3.6 and Section 3.5.2.4). The general health and well- being of people is substantially reduced compared to the conditions in 2020 and continues to worsen over the following decades (Chapter 5, Section 5.2.3). 3 281 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems Frequently Asked Questions FAQ 3.1 | What are the Impacts of 1.5°C and 2°C of Warming? Summary: The impacts of climate change are being felt in every inhabited continent and in the oceans. However, they are not spread uniformly across the globe, and different parts of the world experience impacts differently. An average warming of 1.5°C across the whole globe raises the risk of heatwaves and heavy rainfall events, amongst many other potential impacts. Limiting warming to 1.5°C rather than 2°C can help reduce these risks, but the impacts the world experiences will depend on the specific greenhouse gas emissions ‘pathway’ taken. The consequences of temporarily overshooting 1.5°C of warming and returning to this level later in the century, for example, could be larger than if temperature stabilizes below 1.5°C. The size and duration of an overshoot will also affect future impacts. Human activity has warmed the world by about 1°C since pre-industrial times, and the impacts of this warming have already been felt in many parts of the world. This estimate of the increase in global temperature is the average of many thousands of temperature measurements taken over the world’s land and oceans. Temperatures are not changing at the same speed everywhere, however: warming is strongest on continents and is particularly strong in the Arctic in the cold season and in mid-latitude regions in the warm season. This is due to self- amplifying mechanisms, for instance due to snow and ice melt reducing the reflectivity of solar radiation at the surface, or soil drying leading to less evaporative cooling in the interior of continents. This means that some parts of the world have already experienced temperatures greater than 1.5°C above pre-industrial levels. Extra warming on top of the approximately 1°C we have seen so far would amplify the risks and associated 3 impacts, with implications for the world and its inhabitants. This would be the case even if the global warming is held at 1.5°C, just half a degree above where we are now, and would be further amplified at 2°C of global warming. Reaching 2°C instead of 1.5°C of global warming would lead to substantial warming of extreme hot days in all land regions. It would also lead to an increase in heavy rainfall events in some regions, particularly in the high latitudes of the Northern Hemisphere, potentially raising the risk of flooding. In addition, some regions, such as the Mediterranean, are projected to become drier at 2°C versus 1.5°C of global warming. The impacts of any additional warming would also include stronger melting of ice sheets and glaciers, as well as increased sea level rise, which would continue long after the stabilization of atmospheric CO2 concentrations. Change in climate means and extremes have knock-on effects for the societies and ecosystems living on the planet. Climate change is projected to be a poverty multiplier, which means that its impacts are expected to make the poor poorer and the total number of people living in poverty greater. The 0.5°C rise in global temperatures that we have experienced in the past 50 years has contributed to shifts in the distribution of plant and animal species, decreases in crop yields and more frequent wildfires. Similar changes can be expected with further rises in global temperature. Essentially, the lower the rise in global temperature above pre-industrial levels, the lower the risks to human societies and natural ecosystems. Put another way, limiting warming to 1.5°C can be understood in terms of ‘avoided impacts’ compared to higher levels of warming. Many of the impacts of climate change assessed in this report have lower associated risks at 1.5°C compared to 2°C. Thermal expansion of the ocean means sea level will continue to rise even if the increase in global temperature is limited to 1.5°C, but this rise would be lower than in a 2°C warmer world. Ocean acidification, the process by which excess CO2 is dissolving into the ocean and increasing its acidity, is expected to be less damaging in a world where CO2 emissions are reduced and warming is stabilized at 1.5°C compared to 2°C. The persistence of coral reefs is greater in a 1.5°C world than that of a 2°C world, too. The impacts of climate change that we experience in future will be affected by factors other than the change in temperature. The consequences of 1.5°C of warming will additionally depend on the specific greenhouse gas emissions ‘pathway’ that is followed and the extent to which adaptation can reduce vulnerability. This IPCC Special Report uses a number of ‘pathways’ to explore different possibilities for limiting global warming to 1.5°C above pre-industrial levels. One type of pathway sees global temperature stabilize at, or just below, 1.5°C. Another sees global temperature temporarily exceed 1.5°C before declining later in the century (known as an ‘overshoot’ pathway). (continued on next page) 282 Impacts of 1.5°C of Global Warming on Natural and Human Systems Chapter 3 Such pathways would have different associated impacts, so it is important to distinguish between them for planning adaptation and mitigation strategies. For example, impacts from an overshoot pathway could be larger than impacts from a stabilization pathway. The size and duration of an overshoot would also have consequences for the impacts the world experiences. For instance, pathways that overshoot 1.5°C run a greater risk of passing through ‘tipping points’, thresholds beyond which certain impacts can no longer be avoided even if temperatures are brought back down later on. The collapse of the Greenland and Antarctic ice sheets on the time scale of centuries and millennia is one example of a tipping point. FAQ3.1:Impact of 1.5°C and 2.0°C global warming Temperature rise is not uniform across the world. Some regions will experience greater increases in the temperature of hot days and cold nights than others. + 1.5°C: Change in average temperature of hottest days + 2.0°C: Change in average temperature of hottest days 3 + 1.5°C: Change in average temperature of coldest nights + 2.0°C: Change in average temperature of coldest nights °C 0.0 0.5 1.0 1.5 2.0 3.0 4.0 6.0 8.0 10.0 FAQ 3.1, Figure 1 | Temperature change is not uniform across the globe. Projected changes are shown for the average temperature of the annual hottest day (top) and the annual coldest night (bottom) with 1.5°C of global warming (left) and 2°C of global warming (right) compared to pre-industrial levels. 283 Chapter 3 Impacts of 1.5°C of Global Warming on Natural and Human Systems References Aalto, J., S. Harrison, and M. Luoto, 2017: Statistical modelling predicts almost Almer, C., J. Laurent-Lucchetti, and M. 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Marine Environmental Research, 125, 82–89, doi:10.1016/j.marenvres.2017.01.007. 311 Strengthening and Implementing the Global Response 4 Coordinating Lead Authors: Heleen de Coninck (Netherlands/EU), Aromar Revi (India) Lead Authors: Mustafa Babiker (Sudan), Paolo Bertoldi (Italy), Marcos Buckeridge (Brazil), Anton Cartwright (South Africa), Wenjie Dong (China), James Ford (UK/Canada), Sabine Fuss (Germany), Jean-Charles Hourcade (France), Debora Ley (Guatemala/Mexico), Reinhard Mechler (Germany), Peter Newman (Australia), Anastasia Revokatova (Russian Federation), Seth Schultz (USA), Linda Steg (Netherlands), Taishi Sugiyama (Japan) Contributing Authors: Malcolm Araos (Canada), Stefan Bakker (Netherlands), Amir Bazaz (India), Ella Belfer (Canada), Tim Benton (UK), Sarah Connors (France/UK), Joana Correia de Oliveira de Portugal Pereira (UK/Portugal), Dipak Dasgupta (India), Kiane de Kleijne (Netherlands/EU), Maria del Mar Zamora Dominguez (Mexico), Michel den Elzen (Netherlands), Kristie L. Ebi (USA), Dominique Finon (France), Piers Forster (UK), Jan Fuglestvedt (Norway), Frédéric Ghersi (France), Adriana Grandis (Brazil), Eamon Haughey (Ireland), Bronwyn Hayward (New Zealand), Ove Hoegh-Guldberg (Australia), Daniel Huppmann (Austria), Kejun Jiang (China), Richard Klein (Netherlands/Germany), Shagun Mehrotra (USA/India), Luis Mundaca (Sweden/Chile), Carolyn Opio (Uganda), Maxime Plazzotta (France), Andy Reisinger (New Zealand), Kevon Rhiney (Jamaica), Timmons Roberts (USA), Joeri Rogelj (Austria/Belgium), Arjan van Rooij (Netherlands), Roland Séférian (France), Drew Shindell (USA), Jana Sillmann (Germany/Norway), Chandni Singh (India), Raphael Slade (UK), Gerd Sparovek (Brazil), Pablo Suarez (Argentina), Adelle Thomas (Bahamas), Evelina Trutnevyte (Switzerland/ Lithuania), Anne van Valkengoed (Netherlands), Maria Virginia Vilariño (Argentina), Eva Wollenberg (USA) Review Editors: Amjad Abdulla (Maldives), Rizaldi Boer (Indonesia), Mark Howden (Australia), Diana Ürge-Vorsatz (Hungary) Chapter Scientists: Kiane de Kleijne (Netherlands/EU), Chandni Singh (India) This chapter should be cited as: de Coninck, H., A. Revi, M. Babiker, P. Bertoldi, M. Buckeridge, A. Cartwright, W. Dong, J. Ford, S. Fuss, J.-C. Hourcade, D. Ley, R. Mechler, P. Newman, A. Revokatova, S. Schultz, L. Steg, and T. Sugiyama, 2018: Strengthening and Implementing the Global Response. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson- Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)]. In Press. 313 Chapter 4 Strengthening and Implementing the Global Response Table of Contents Executive Summary ...................................................................315 4.4.3 Enabling Lifestyle and Behavioural Change ...............362 Box 4.5 | How Pricing Policy has Reduced Car Use 4.1 Accelerating the Global Response in Singapore, Stockholm and London ...................................366 to Climate Change ........................................................319 Box 4.6 | Bottom-up Initiatives: Adaptation Responses Initiated by Individuals and Communities ........368 4.2 Pathways Compatible with 1.5°C: Starting Points for Strengthening Implementation ............320 4.4.4 Enabling Technological Innovation .............................369 4.2.1 Implications for Implementation of Box 4.7 | Bioethanol in Brazil: Innovation and 1.5°C-Consistent Pathways ........................................320 Lessons for Technology Transfers...........................................371 4.2.2 System Transitions and Rates of Change ....................322 4.4.5 Strengthening Policy Instruments and Enabling Climate Finance ..........................................................372 4.3 Systemic Changes Box 4.8 | Investment Needs and the Financial for 1.5°C-Consistent Pathways ................................323 Challenge of Limiting Warming to 1.5°C ..............................373 4.3.1 Energy System Transitions ..........................................324 Box 4.9 | Emerging Cities and ‘Peak Car Use’: Evidence of Decoupling in Beijing.........................................376 4.3.2 Land and Ecosystem Transitions .................................327 4.3.3 Urban and Infrastructure System Transitions ..............330 4.5 Integration and Enabling Transformation .............380 4.3.4 Industrial Systems Transitions .....................................324 4.5.1 Assessing Feasibility of Options for Accelerated Transitions ..................................................................380 4.3.5 Overarching Adaptation Options Supporting Adaptation Transitions ...............................................336 4.5.2 Implementing Mitigation............................................381 Cross-Chapter Box 9 | Risks, Adaptation Interventions, 4.5.3 Implementing Adaptation...........................................383 and Implications for Sustainable Development and Equity Across Four Social-Ecological Systems: 4.5.4 Synergies and Trade-Offs between Arctic, Caribbean, Amazon, and Urban .................................338 Adaptation and Mitigation .........................................386 4.3.6 Short-Lived Climate Forcers ........................................341 Box 4.10 | Bhutan: Synergies and Trade-Offs in Economic Growth, Carbon Neutrality and Happiness ..........................387 4.3.7 Carbon Dioxide Removal (CDR) ..................................342 4 4.3.8 Solar Radiation Modification (SRM) ...........................347 4.6 Knowledge Gaps and Key Uncertainties ...............387 Cross-Chapter Box 10 | Solar Radiation Modification in the Context of 1.5°C Mitigation Pathways ......................349 Frequently Asked Questions 4.4 Implementing Far-Reaching and Rapid Change ..352 FAQ 4.1: What Transitions Could Enable Limiting Global Warming to 1.5°C? ..................................................392 4.4.1 Enhancing Multilevel Governance ..............................352 FAQ 4.2: What are Carbon Dioxide Removal and Box 4.1 | Multilevel Governance in the EU Covenant Negative Emissions? ..........................................................394 of Mayors: Example of the Provincia di Foggia ...................355 FAQ 4.3: Why is Adaptation Important in a Box 4.2 | Watershed Management in a 1.5˚C World ............356 1.5°C-Warmer World? .........................................................396 Cross-Chapter Box 11 | Consistency Between Nationally Determined Contributions and 1.5°C Scenarios ........................................................................357 References ...................................................................................398 4.4.2 Enhancing Institutional Capacities .............................359 Box 4.3 | Indigenous Knowledge and Community Adaptation ...............................................................................360 Box 4.4 | Manizales, Colombia: Supportive National Government and Localized Planning and Integration as an Enabling Condition for Managing Climate and Development Risks ..........................................................361 314 Strengthening and Implementing the Global Response Chapter 4 Executive Summary System Transitions The energy system transition that would be required to limit Limiting warming to 1.5°C above pre-industrial levels would global warming to 1.5°C above pre-industrial conditions is require transformative systemic change, integrated with underway in many sectors and regions around the world sustainable development. Such change would require the (medium evidence, high agreement). The political, economic, social upscaling and acceleration of the implementation of far- and technical feasibility of solar energy, wind energy and electricity reaching, multilevel and cross-sectoral climate mitigation storage technologies has improved dramatically over the past few and addressing barriers. Such systemic change would need years, while that of nuclear energy and carbon dioxide capture to be linked to complementary adaptation actions, including and storage (CCS) in the electricity sector have not shown similar transformational adaptation, especially for pathways that improvements. {4.3.1} temporarily overshoot 1.5°C (medium evidence, high agreement) {Chapter 2, Chapter 3, 4.2.1, 4.4.5, 4.5}. Current national pledges Electrification, hydrogen, bio-based feedstocks and substitution, on mitigation and adaptation are not enough to stay below the Paris and, in several cases, carbon dioxide capture, utilization and Agreement temperature limits and achieve its adaptation goals. While storage (CCUS) would lead to the deep emissions reductions transitions in energy efficiency, carbon intensity of fuels, electrification required in energy-intensive industries to limit warming to and land-use change are underway in various countries, limiting 1.5°C. However, those options are limited by institutional, economic and warming to 1.5°C will require a greater scale and pace of change to technical constraints, which increase financial risks to many incumbent transform energy, land, urban and industrial systems globally. {4.3, 4.4, firms (medium evidence, high agreement). Energy efficiency in industry Cross-Chapter Box 9 in this Chapter} is more economically feasible and helps enable industrial system transitions but would have to be complemented with greenhouse gas Although multiple communities around the world are (GHG)-neutral processes or carbon dioxide removal (CDR) to make demonstrating the possibility of implementation consistent with energy-intensive industries consistent with 1.5°C (high confidence). 1.5°C pathways {Boxes 4.1-4.10}, very few countries, regions, {4.3.1, 4.3.4} cities, communities or businesses can currently make such a claim (high confidence). To strengthen the global response, Global and regional land-use and ecosystems transitions and almost all countries would need to significantly raise their level associated changes in behaviour that would be required to of ambition. Implementation of this raised ambition would limit warming to 1.5°C can enhance future adaptation and require enhanced institutional capabilities in all countries, land-based agricultural and forestry mitigation potential. Such including building the capability to utilize indigenous and local transitions could, however, carry consequences for livelihoods knowledge (medium evidence, high agreement). In developing that depend on agriculture and natural resources {4.3.2, Cross- countries and for poor and vulnerable people, implementing the Chapter Box 6 in Chapter 3}. Alterations of agriculture and forest 4 response would require financial, technological and other forms of systems to achieve mitigation goals could affect current ecosystems support to build capacity, for which additional local, national and and their services and potentially threaten food, water and livelihood international resources would need to be mobilized (high confidence). security. While this could limit the social and environmental feasibility However, public, financial, institutional and innovation capabilities of land-based mitigation options, careful design and implementation currently fall short of implementing far-reaching measures at scale in could enhance their acceptability and support sustainable development all countries (high confidence). Transnational networks that support objectives (medium evidence, medium agreement). {4.3.2, 4.5.3} multilevel climate action are growing, but challenges in their scale-up remain. {4.4.1, 4.4.2, 4.4.4, 4.4.5, Box 4.1, Box 4.2, Box 4.7} Changing agricultural practices can be an effective climate adaptation strategy. A diversity of adaptation options exists, Adaptation needs will be lower in a 1.5°C world compared to including mixed crop-livestock production systems which can be a a 2°C world (high confidence) {Chapter 3; Cross-Chapter Box 11 cost-effective adaptation strategy in many global agriculture systems in this chapter}. Learning from current adaptation practices and (robust evidence, medium agreement). Improving irrigation efficiency strengthening them through adaptive governance {4.4.1}, lifestyle could effectively deal with changing global water endowments, and behavioural change {4.4.3} and innovative financing mechanisms especially if achieved via farmers adopting new behaviours and water- {4.4.5} can help their mainstreaming within sustainable development efficient practices rather than through large-scale infrastructural practices. Preventing maladaptation, drawing on bottom-up approaches interventions (medium evidence, medium agreement). Well-designed {Box 4.6} and using indigenous knowledge {Box 4.3} would effectively adaptation processes such as community-based adaptation can be engage and protect vulnerable people and communities. While effective depending upon context and levels of vulnerability. {4.3.2, adaptation finance has increased quantitatively, significant further 4.5.3} expansion would be needed to adapt to 1.5°C. Qualitative gaps in the distribution of adaptation finance, readiness to absorb resources, and Improving the efficiency of food production and closing yield monitoring mechanisms undermine the potential of adaptation finance gaps have the potential to reduce emissions from agriculture, to reduce impacts. {Chapter 3, 4.4.2, 4.4.5, 4.6} reduce pressure on land, and enhance food security and future 315 Chapter 4 Strengthening and Implementing the Global Response mitigation potential (high confidence). Improving productivity of Converging adaptation and mitigation options can lead to existing agricultural systems generally reduces the emissions intensity synergies and potentially increase cost-effectiveness, but of food production and offers strong synergies with rural development, multiple trade-offs can limit the speed of and potential for poverty reduction and food security objectives, but options to reduce scaling up. Many examples of synergies and trade-offs exist in absolute emissions are limited unless paired with demand-side all sectors and system transitions. For instance, sustainable water measures. Technological innovation including biotechnology, with management (high evidence, medium agreement) and investment in adequate safeguards, could contribute to resolving current feasibility green infrastructure (medium evidence, high agreement) to deliver constraints and expand the future mitigation potential of agriculture. sustainable water and environmental services and to support urban {4.3.2, 4.4.4} agriculture are less cost-effective than other adaptation options but can help build climate resilience. Achieving the governance, finance Shifts in dietary choices towards foods with lower emissions and social support required to enable these synergies and to avoid and requirements for land, along with reduced food loss and trade-offs is often challenging, especially when addressing multiple waste, could reduce emissions and increase adaptation options objectives, and attempting appropriate sequencing and timing of (high confidence). Decreasing food loss and waste and changing interventions. {4.3.2, 4.3.4, 4.4.1, 4.5.2, 4.5.3, 4.5.4} dietary behaviour could result in mitigation and adaptation (high confidence) by reducing both emissions and pressure on land, with Though CO2 dominates long-term warming, the reduction of significant co-benefits for food security, human health and sustainable warming short-lived climate forcers (SLCFs), such as methane development {4.3.2, 4.4.5, 4.5.2, 4.5.3, 5.4.2}, but evidence of and black carbon, can in the short term contribute significantly to successful policies to modify dietary choices remains limited. limiting warming to 1.5°C above pre-industrial levels. Reductions of black carbon and methane would have substantial co-benefits Mitigation and Adaptation Options and Other Measures (high confidence), including improved health due to reduced air pollution. This, in turn, enhances the institutional and socio- A mix of mitigation and adaptation options implemented in a cultural feasibility of such actions. Reductions of several warming participatory and integrated manner can enable rapid, systemic SLCFs are constrained by economic and social feasibility (low evidence, transitions – in urban and rural areas – that are necessary high agreement). As they are often co-emitted with CO2, achieving the elements of an accelerated transition consistent with limiting energy, land and urban transitions necessary to limit warming to 1.5°C warming to 1.5°C. Such options and changes are most effective would see emissions of warming SLCFs greatly reduced. {2.3.3.2, 4.3.6} when aligned with economic and sustainable development, and when local and regional governments are supported by Most CDR options face multiple feasibility constraints, which national governments {4.3.3, 4.4.1, 4.4.3}. Various mitigation differ between options, limiting the potential for any single options are expanding rapidly across many geographies. Although option to sustainably achieve the large-scale deployment 4 many have development synergies, not all income groups have so required in the 1.5°C-consistent pathways described in far benefited from them. Electrification, end-use energy efficiency Chapter 2 (high confidence). Those 1.5°C pathways typically rely and increased share of renewables, amongst other options, are on bioenergy with carbon capture and storage (BECCS), afforestation lowering energy use and decarbonizing energy supply in the built and reforestation (AR), or both, to neutralize emissions that are environment, especially in buildings. Other rapid changes needed in expensive to avoid, or to draw down CO2 emissions in excess of the urban environments include demotorization and decarbonization of carbon budget {Chapter 2}. Though BECCS and AR may be technically transport, including the expansion of electric vehicles, and greater use and geophysically feasible, they face partially overlapping yet different of energy-efficient appliances (medium evidence, high agreement). constraints related to land use. The land footprint per tonne of CO2 Technological and social innovations can contribute to limiting removed is higher for AR than for BECCS, but given the low levels of warming to 1.5°C, for example, by enabling the use of smart grids, current deployment, the speed and scales required for limiting warming energy storage technologies and general-purpose technologies, such to 1.5°C pose a considerable implementation challenge, even if the as information and communication technology (ICT) that can be issues of public acceptance and absence of economic incentives were deployed to help reduce emissions. Feasible adaptation options include to be resolved (high agreement, medium evidence). The large potential green infrastructure, resilient water and urban ecosystem services, of afforestation and the co-benefits if implemented appropriately (e.g., urban and peri-urban agriculture, and adapting buildings and land use on biodiversity and soil quality) will diminish over time, as forests through regulation and planning (medium evidence, medium to high saturate (high confidence). The energy requirements and economic agreement). {4.3.3, 4.4.3, 4.4.4} costs of direct air carbon capture and storage (DACCS) and enhanced weathering remain high (medium evidence, medium agreement). At the Synergies can be achieved across systemic transitions through local scale, soil carbon sequestration has co-benefits with agriculture several overarching adaptation options in rural and urban areas. and is cost-effective even without climate policy (high confidence). Its Investments in health, social security and risk sharing and spreading potential feasibility and cost-effectiveness at the global scale appears are cost-effective adaptation measures with high potential for scaling to be more limited. {4.3.7} up (medium evidence, medium to high agreement). Disaster risk management and education-based adaptation have lower prospects of Uncertainties surrounding solar radiation modification scalability and cost-effectiveness (medium evidence, high agreement) (SRM) measures constrain their potential deployment. These but are critical for building adaptive capacity. {4.3.5, 4.5.3} uncertainties include: technological immaturity; limited physical 316 Strengthening and Implementing the Global Response Chapter 4 understanding about their effectiveness to limit global warming; and up initiatives can result in greater participation in the governance of a weak capacity to govern, legitimize, and scale such measures. Some systems transitions and increase support for technologies, practices recent model-based analysis suggests SRM would be effective but that and policies that are part of the global response to limit warming to it is too early to evaluate its feasibility. Even in the uncertain case that 1.5°C . {Chapter 2, 4.4.1, 4.4.3, Figure 4.3} the most adverse side-effects of SRM can be avoided, public resistance, ethical concerns and potential impacts on sustainable development This rapid and far-reaching response required to keep warming could render SRM economically, socially and institutionally undesirable below 1.5°C and enhance the capacity to adapt to climate risks (low agreement, medium evidence). {4.3.8, Cross-Chapter Box 10 in would require large increases of investments in low-emission this chapter} infrastructure and buildings, along with a redirection of financial flows towards low-emission investments (robust evidence, high Enabling Rapid and Far-Reaching Change agreement). An estimated mean annual incremental investment of around 1.5% of global gross fixed capital formation (GFCF) for the The speed of transitions and of technological change required energy sector is indicated between 2016 and 2035, as well as about to limit warming to 1.5°C above pre-industrial levels has been 2.5% of global GFCF for other development infrastructure that could observed in the past within specific sectors and technologies also address SDG implementation. Though quality policy design and {4.2.2.1}. But the geographical and economic scales at which effective implementation may enhance efficiency, they cannot fully the required rates of change in the energy, land, urban, substitute for these investments. {2.5.2, 4.2.1, 4.4.5} infrastructure and industrial systems would need to take place are larger and have no documented historic precedent (limited Enabling this investment requires the mobilization and better evidence, medium agreement). To reduce inequality and alleviate integration of a range of policy instruments that include the poverty, such transformations would require more planning and reduction of socially inefficient fossil fuel subsidy regimes and innovative stronger institutions (including inclusive markets) than observed in the price and non-price national and international policy instruments. These past, as well as stronger coordination and disruptive innovation across would need to be complemented by de-risking financial instruments actors and scales of governance. {4.3, 4.4} and the emergence of long-term low-emission assets. These instruments would aim to reduce the demand for carbon-intensive services and shift Governance consistent with limiting warming to 1.5°C and the market preferences away from fossil fuel-based technology. Evidence political economy of adaptation and mitigation can enable and and theory suggest that carbon pricing alone, in the absence of accelerate systems transitions, behavioural change, innovation and sufficient transfers to compensate their unintended distributional cross- technology deployment (medium evidence, medium agreement). sector, cross-nation effects, cannot reach the incentive levels needed For 1.5°C-consistent actions, an effective governance framework to trigger system transitions (robust evidence, medium agreement). would include: accountable multilevel governance that includes non- But, embedded in consistent policy packages, they can help mobilize state actors, such as industry, civil society and scientific institutions; incremental resources and provide flexible mechanisms that help reduce 4 coordinated sectoral and cross-sectoral policies that enable collaborative the social and economic costs of the triggering phase of the transition multi-stakeholder partnerships; strengthened global-to-local financial (robust evidence, medium agreement). {4.4.3, 4.4.4, 4.4.5} architecture that enables greater access to finance and technology; addressing climate-related trade barriers; improved climate education Increasing evidence suggests that a climate-sensitive and greater public awareness; arrangements to enable accelerated realignment of savings and expenditure towards low-emission, behaviour change; strengthened climate monitoring and evaluation climate-resilient infrastructure and services requires an systems; and reciprocal international agreements that are sensitive evolution of global and national financial systems. Estimates to equity and the Sustainable Development Goals (SDGs). System suggest that, in addition to climate-friendly allocation of public transitions can be enabled by enhancing the capacities of public, private investments, a potential redirection of 5% to 10% of the annual and financial institutions to accelerate climate change policy planning capital revenues1 is necessary for limiting warming to 1.5°C {4.4.5, and implementation, along with accelerated technological innovation, Table 1 in Box 4.8}. This could be facilitated by a change of incentives deployment and upkeep. {4.4.1, 4.4.2, 4.4.3, 4.4.4} for private day-to-day expenditure and the redirection of savings from speculative and precautionary investments towards long- Behaviour change and demand-side management can term productive low-emission assets and services. This implies the significantly reduce emissions, substantially limiting the mobilization of institutional investors and mainstreaming of climate reliance on CDR to limit warming to 1.5°C {Chapter 2, 4.4.3}. finance within financial and banking system regulation. Access by Political and financial stakeholders may find climate actions more cost- developing countries to low-risk and low-interest finance through effective and socially acceptable if multiple factors affecting behaviour multilateral and national development banks would have to be are considered, including aligning these actions with people’s core facilitated (medium evidence, high agreement). New forms of public– values (medium evidence, high agreement). Behaviour- and lifestyle- private partnerships may be needed with multilateral, sovereign and related measures and demand-side management have already led sub-sovereign guarantees to de-risk climate-friendly investments, to emission reductions around the world and can enable significant support new business models for small-scale enterprises and help future reductions (high confidence). Social innovation through bottom- households with limited access to capital. Ultimately, the aim is to 1 Annual capital revenues are paid interests plus an increase of asset value. 317 Chapter 4 Strengthening and Implementing the Global Response promote a portfolio shift towards long-term low-emission assets that would help redirect capital away from potentially stranded assets (medium evidence, medium agreement). {4.4.5} Knowledge Gaps Knowledge gaps around implementing and strengthening the global response to climate change would need to be urgently resolved if the transition to a 1.5°C world is to become reality. Remaining questions include: how much can be realistically expected from innovation and behavioural and systemic political and economic changes in improving resilience, enhancing adaptation and reducing GHG emissions? How can rates of changes be accelerated and scaled up? What is the outcome of realistic assessments of mitigation and adaptation land transitions that are compliant with sustainable development, poverty eradication and addressing inequality? What are life-cycle emissions and prospects of early-stage CDR options? How can climate and sustainable development policies converge, and how can they be organised within a global governance framework and financial system, based on principles of justice and ethics (including ‘common but differentiated responsibilities and respective capabilities’ (CBDR-RC)), reciprocity and partnership? To what extent would limiting warming to 1.5°C require a harmonization of macro-financial and fiscal policies, which could include financial regulators such as central banks? How can different actors and processes in climate governance reinforce each other, and hedge against the fragmentation of initiatives? {4.1, 4.3.7, 4.4.1, 4.4.5, 4.6} 4 318 Strengthening and Implementing the Global Response Chapter 4 4.1 Accelerating the Global Response (e.g., institutions, market structures and political processes) (Hallegatte to Climate Change et al., 2016; Pelling et al., 2018) could enhance the adaptive capacity of key systems at risk (e.g., water, energy, food, biodiversity, urban, regional and coastal systems) to 1.5°C climate impacts (Chapter This chapter discusses how the global economy and socio-technical 3). The issue is whether aligning 1.5°C-consistent pathways with and socio-ecological systems can transition to 1.5°C-consistent the Sustainable Development Goals (SDGs) will secure support for pathways and adapt to warming of 1.5°C above pre-industrial levels. accelerated change and a new growth cycle (Stern, 2013, 2015). It is In the context of systemic transitions, the chapter assesses adaptation difficult to imagine how a 1.5°C world would be attained unless the and mitigation options, including carbon dioxide removal (CDR), and SDG on cities and sustainable urbanization is achieved in developing potential solar radiation modification (SRM) remediative measures countries (Revi, 2016), or without reforms in the global financial (Section 4.3), as well as the enabling conditions that would be required intermediation system. for implementing the rapid and far-reaching global response of limiting warming to 1.5°C (Section 4.4), and render the options more or less Unless affordable and environmentally and socially acceptable feasible (Section 4.5). CDR becomes feasible and available at scale well before 2050, 1.5°C-consistent pathways will be difficult to realize, especially in The impacts of a 1.5°C-warmer world, while less than in a 2°C-warmer overshoot scenarios. The social costs and benefits of 1.5°C-consistent world, would require complementary adaptation and development pathways depend on the depth and timing of policy responses and action, typically at local and national scale. From a mitigation their alignment with short term and long-term development objectives, perspective, 1.5°C-consistent pathways require immediate action on through policy packages that bring together a diversity of policy a greater and global scale so as to achieve net zero emissions by mid- instruments, including public investment (Grubb et al., 2014; Winkler century, or earlier (Chapter 2). This chapter and Chapter 5 highlight and Dubash, 2015; Campiglio, 2016). the potential that combined mitigation, development and poverty reduction offer for accelerated decarbonization. Whatever its potential long-term benefits, a transition to a 1.5°C world may suffer from a lack of broad political and public support, The global context is an increasingly interconnected world, with the if it exacerbates existing short-term economic and social tensions, human population growing from the current 7.6 billion to over 9 billion including unemployment, poverty, inequality, financial tensions, by mid-century (UN DESA, 2017). There has been a consistent growth of competitiveness issues and the loss of economic value of carbon- global economic output, wealth and trade with a significant reduction intensive assets (Mercure et al., 2018). The challenge is therefore how in extreme poverty. These trends could continue for the next few to strengthen climate policies without inducing economic collapse or decades (Burt et al., 2014), potentially supported by new and disruptive hardship, and to make them contribute to reducing some of the ‘fault information and communication, and nano- and bio-technologies. lines’ of the world economy (Rajan, 2011). However, these trends co-exist with rising inequality (Piketty, 2014), 4 exclusion and social stratification, and regions locked in poverty traps This chapter reviews literature addressing the alignment of climate (Deaton, 2013) that could fuel social and political tensions. with other public policies (e.g., fiscal, trade, industrial, monetary, urban planning, infrastructure, and innovation) and with a greater access to The aftermath of the 2008 financial crisis generated a challenging basic needs and services, defined by the SDGs. It also reviews how environment in which leading economists have issued repeated alerts de-risking low-emission investments and the evolution of the financial about the ‘discontents of globalisation’ (Stiglitz, 2002), ‘depression intermediation system can help reduce the ‘savings glut’ (Arezki et economics’ (Krugman, 2009), an excessive reliance of export-led al., 2016) and the gap between cash balances and long-term assets development strategies (Rajan, 2011), and risks of ‘secular stagnation’ (Aglietta et al., 2015b) to support more sustainable and inclusive due to the ‘saving glut’ that slows down the flow of global savings growth. towards productive 1.5°C-consistent investments (Summers, 2016). Each of these affects the implementation of both 1.5°C-consistent As the transitions associated with 1.5°C-consistent pathways require pathways and sustainable development (Chapter 5). accelerated and coordinated action, in multiple systems across all world regions, they are inherently exposed to risks of freeriding and The range of mitigation and adaptation actions that can be deployed in moral hazards. A key governance challenge is how the convergence the short run are well-known: for example, low-emission technologies, of voluntary domestic policies can be organized via aligned global, new infrastructure, and energy efficiency measures in buildings, national and sub-national governance, based on reciprocity (Ostrom industry and transport; transformation of fiscal structures; reallocation and Walker, 2005) and partnership (UN, 2016), and how different of investments and human resources towards low-emission assets; actors and processes in climate governance can reinforce each other sustainable land and water management; ecosystem restoration; to enable this (Gupta, 2014; Andonova et al., 2017). The emergence of enhancement of adaptive capacities to climate risks and impacts; polycentric sources of climate action and transnational and subnational disaster risk management; research and development; and mobilization networks that link these efforts (Abbott, 2012) offer the opportunity to of new, traditional and indigenous knowledge. experiment and learn from different approaches, thereby accelerating approaches led by national governments (Cole, 2015; Jordan et al., The convergence of short-term development co-benefits from 2015). mitigation and adaptation to address ‘everyday development failures’ 319 Chapter 4 Strengthening and Implementing the Global Response Section 4.2 of this chapter outlines existing rates of change and could trigger the transition to 1.5°C-consistent pathways. Section 4.5 attributes of accelerated change. Section 4.3 identifies global systems, assesses mitigation and adaptation options for feasibility, strategies for and their components, that offer options for this change. Section 4.4 implementation and synergies and trade-offs between mitigation and documents the enabling conditions that influence the feasibility of adaptation. those options, including economic, financial and policy instruments that 4.2 Pathways Compatible with 1.5°C: Starting land-use change. Both the detailed integrated modelling pathway Points for Strengthening Implementation literature and a number of broader sectoral and bottom-up studies provide examples of how these sectoral technological and policy 4.2.1 Implications for Implementation of characteristics can be broken down sectorally for 1.5°C-consistent 1.5°C-Consistent Pathways pathways (see Table 4.1). The 1.5°C-consistent pathways assessed in Chapter 2 form the Both the integrated pathway literature and the sectoral studies agree basis for the feasibility assessment in section 4.5. A wide range of on the need for rapid transitions in the production and use of energy 1.5°C-consistent pathways from integrated assessment modelling across various sectors, to be consistent with limiting global warming (IAM), supplemented by other literature, are assessed in Chapter 2 to 1.5°C. The pace of these transitions is particularly significant for (Sections 2.1, 2.3, 2.4, and 2.5). The most common feature shared the supply mix and electrification (Table 4.1). Individual, sectoral by these pathways is their requirement for faster and more radical studies may show higher rates of change compared to IAMs (Figueres changes compared to 2°C and higher warming pathways. et al., 2017; Rockström et al., 2017; WBCSD, 2017; Kuramochi et al., 2018). These trends and transformation patterns create opportunities A variety of 1.5°C-consistent technological options and policy targets and challenges for both mitigation and adaptation (Sections 4.2.1.1 is identified in the assessed modelling literature (Sections 2.3, 2.4, 2.5). and 4.2.1.2) and have significant implications for the assessment of These technology and policy options include energy demand reduction, feasibility and enablers, including governance, institutions, and policy greater penetration of low-emission and carbon-free technologies instruments addressed in Sections 4.3 and 4.4. as well as electrification of transport and industry, and reduction of Table 4.1 | Sectoral indicators of the pace of transformation in 1.5°C-consistent pathways, based on selected integrated pathways assessed in Chapter 2 (from the scenario database) and several other studies reviewed in Chapter 2 that assess mitigation transitions consistent with limiting warming to 1.5°C. Values for ‘1.5°C-no or -low-OS’ and ‘1.5C-high- OS’ indicate the median and the interquartile ranges for 1.5°C scenarios. If a number in square brackets is indicated, this is the number of scenarios for this indicator. S1, S2, S5 and LED represent the four illustrative pathway archetypes selected for this assessment (see Chapter 2, Section 2.1 and Supplementary Material 4.SM.1 for detailed description). 4 Energy Buildings Transport Industry Share of low- Number Change Industrial Share of carbon fuels Pathways of Share of in energy Share of emissions renewables (electricity, scenarios renewables in demand for electricity in reductions in primary hydrogen and electricity [%] buildings (2010 transport [%] (2010 baseline) energy [%] biofuel) in baseline) [%] [%] transport [%] 1.5°C-no or low-OS 50 29 (37; 26) 54 (65; 47) 0 (7; −7) [42] 12 (18; 9) [29] 5 (7; 3) [49] 42 (55; 34) [42] 1.5°C-high-OS 35 24 (27; 20) 43 (54; 37) −17 (−12; −20) [29] 7 (8; 6) [23] 3 (5; 3) 18 (28; −13) [29] IAM S1 29 58 −8 4 49 Pathways 2030 S2 29 48 −14 5 4 19 S5 14 25 3 1 LED 37 60 30 21 42 Other Löffler et al. (2017) 46 79 Studies IEA (2017c) (ETP) 31 47 2 14 5 22 2030 IEA (2017g) (WEM) 27 50 –6 17 6 15 1.5°C-no or low-OS 50 60 (67; 52) 77 (86; 69) −17 (3; −36) [42] 55 (66; 35) [29] 23 (29; 17) [49] 79 (91; 67) [42] 1.5°C-high-OS 35 62 (68; 47) 82 (88; 64) −37 (−13; −51) [29] 38 (44; 27) [23] 18 (23; 14) 68 (81; 54) [29] IAM S1 58 81 −21 34 74 Pathways 2050 S2 53 63 −25 26 23 73 S5 67 70 53 10 LED 73 77 45 59 91 Löffler et al. (2017) 100 100 Other Studies IEA (2017c) (ETP) 58 74 5 55 30 57 2050 IEA (2017g) (WEM) 47 69 −5 58 32 55 320 Strengthening and Implementing the Global Response Chapter 4 4.2.1.1 Challenges and Opportunities for Mitigation Along currently assessed literature are scant, yet suggestive. For example, IAM the Reviewed Pathways simulations assessed in Chapter 2 project (with a probability greater than 50%) that marginal abatement costs, typically represented in Greater scale, speed and change in investment patterns. There IAMs through a carbon price, would increase by about 3–4 times by is agreement in the literature reviewed by Chapter 2 that staying 2050 under a 1.5°C-consistent pathway compared to a 2°C-consistent below 1.5°C would entail significantly greater transformation in terms pathway (Chapter 2, Section 2.5.2, Figure 2.26). Managing these of energy systems, lifestyles and investments patterns compared costs and distributional effects would require an approach that takes to 2°C-consistent pathways. Yet there is limited evidence and low account of unintended cross-sector, cross-nation, and cross-policy agreement regarding the magnitudes and costs of the investments trade-offs during the transition (Droste et al., 2016; Stiglitz et al., 2017; (Sections 2.5.1, 2.5.2 and 4.4.5). Based on the IAM literature reviewed Pollitt, 2018; Sands, 2018; Siegmeier et al., 2018). in Chapter 2, climate policies in line with limiting warming to 1.5°C would require a marked upscaling of supply-side energy system Greater sustainable development implications. Few studies investments between now and mid-century, reaching levels of between address the relations between the Shared Socio-Economic Pathways 1.6–3.8 trillion USD yr−1 globally with an average of about 3.5 trillion (SSPs) and the Sustainable Developments Goals (SDGs) (O’Neill et al., USD yr−1 over 2016–2050 (see Figure 2.27). This can be compared to 2015; Riahi et al., 2017). Nonetheless, literature on potential synergies an average of about 3.0 trillion USD yr−1 over the same period for and trade-offs between 1.5°C-consistent mitigation pathways and 2°C-consistent pathways (also in Figure 2.27). sustainable development dimensions is emerging (Chapter 2, Section 2.5.3, Chapter 5, Section 5.4). Areas of potential trade-offs include Not only the level of investment but also the type and speed of reduction in final energy demand in relation to SDG 7 (the universal sectoral transformation would be impacted by the transitions clean energy access goal) and increase of biomass production in associated with 1.5°C-consistent pathways. IAM literature projects relation to land use, water resources, food production, biodiversity that investments in low-emission energy would overtake fossil and air quality (Chapter 2, Sections 2.4.3, 2.5.3). Strengthening the fuel investments globally by 2025 in 1.5°C-consistent pathways institutional and policy responses to deal with these challenges is (Chapter 2, Section 2.5.2). The projected low-emission investments discussed in Section 4.4 together with the linkage between disruptive in electricity generation allocations over the period 2016–2050 are: changes in the energy sector and structural changes in other solar (0.09–1.0 trillion USD yr−1), wind (0.1–0.35 trillion USD yr−1), infrastructure (transport, building, water and telecommunication) nuclear (0.1–0.25 trillion USD yr−1), and transmission, distribution, sectors. A more in-depth assessment of the complexity and interfaces and storage (0.3–1.3 trillion USD yr−1). In contrast, investments in between 1.5°C-consistent pathways and sustainable development is fossil fuel extraction and unabated fossil electricity generation along presented in Chapter 5. a 1.5°C-consistent pathway are projected to drop by 0.3–0.85 trillion USD yr−1 over the period 2016–2050, with investments in unabated 4.2.1.2 Implications for Adaptation Along the Reviewed coal generation projected to halt by 2030 in most 1.5°C-consistent Pathways 4 pathways (Chapter 2, Section 2.5.2). Estimates of investments in other infrastructure are currently unavailable, but they could be Climate variability and uncertainties in the underlying assumptions considerably larger in volume than solely those in the energy sector in Chapter 2’s IAMs as well as in model comparisons complicate (Section 4.4.5). discerning the implications for climate impacts, adaptation options and avoided adaptation investments at the global level of 2°C compared to Greater policy design and decision-making implications. The 1.5°C warming (James et al., 2017; Mitchell et al., 2017). 1.5°C-consistent pathways raise multiple challenges for effective policy design and responses to address the scale, speed, and pace Incremental warming from 1.5°C to 2°C would lead to significant of mitigation technology, finance and capacity building needs. These increases in temperature and precipitation extremes in many regions policies and responses would also need to deal with their distributional (Chapter 3, Section 3.3.2, 3.3.3). Those projected changes in climate implications while addressing adaptation to residual climate impacts extremes under both warming levels, however, depend on the (see Chapter 5). The available literature indicates that 1.5°C-consistent emissions pathways, as they have different greenhouse gas (GHG)/ pathways would require robust, stringent and urgent transformative aerosol forcing ratios. Impacts are sector-, system- and region-specific, policy interventions targeting the decarbonization of energy supply, as described in Chapter 3. For example, precipitation-related impacts electrification, fuel switching, energy efficiency, land-use change, and reveal distinct regional differences (Chapter 3, Sections 3.3.3, 3.3.4, lifestyles (Chapter 2, Section 2.5, 4.4.2, 4.4.3). Examples of effective 3.3.5, 3.4.2). Similarly, regional reduction in water availability and approaches to integrate mitigation with adaptation in the context of the lengthening of regional dry spells have negative implications for sustainable development and to deal with distributional implications agricultural yields depending on crop types and world regions (see for proposed in the literature include the utilization of dynamic adaptive example Chapter 3, Sections 3.3.4, 3.4.2, 3.4.6). policy pathways (Haasnoot et al., 2013; Mathy et al., 2016) and transdisciplinary knowledge systems (Bendito and Barrios, 2016). Adaptation helps reduce impacts and risks. However, adaptation has Yet, even with good policy design and effective implementation, limits. Not all systems can adapt, and not all impacts can be reversed 1.5°C-consistent pathways would incur higher costs. Projections of the (Cross-Chapter Box 12 in Chapter 5). For example, tropical coral reefs magnitudes of global economic costs associated with 1.5°C-consistent are projected to be at risk of severe degradation due to temperature- pathways and their sectoral and regional distributions from the induced bleaching (Chapter 3, Box 3.4). 321 Chapter 4 Strengthening and Implementing the Global Response 4.2.2 System Transitions and Rates of Change One barrier to a greater rate of change in energy systems is that economic growth in the past has been coupled to the use of fossil Society-wide transformation involves socio-technical transitions fuels. Disruptive innovation and socio-technical changes could enable and social-ecological resilience (Gillard et al., 2016). Transitional the decoupling of economic growth from a range of environmental adaptation pathways would need to respond to low-emission drivers, including the consumption of fossil fuels, as represented by energy and economic systems, and the socio-technical transitions 1.5°C-consistent pathways (UNEP, 2014; Newman, 2017). This may for mitigation involve removing barriers in social and institutional be relative decoupling due to rebound effects that see financial processes that could also benefit adaptation (Pant et al., 2015; Geels savings generated by renewable energy used in the consumption of et al., 2017; Ickowitz et al., 2017). In this chapter, transformative new products and services (Jackson and Senker, 2011; Gillingham et change is framed in mitigation around socio-technical transitions, and al., 2013), but in 2015 and 2016 total global GHG emissions have in adaptation around socio-ecological transitions. In both instances, decoupled absolutely from economic growth (IEA, 2017g; Peters emphasis is placed on the enabling role of institutions (including et al., 2017). A longer data trend would be needed before stable markets, and formal and informal regulation). 1.5°C-consistent decoupling can be established. The observed decoupling in 2015 pathways and adaptation needs associated with warming of 1.5°C and 2016 was driven by absolute declines in both coal and oil use imply both incremental and rapid, disruptive and transformative since the early 2000s in Europe, in the past seven years in the United changes. States and Australia, and more recently in China (Newman, 2017). In 2017, decoupling in China reversed by 2% due to a drought 4.2.2.1 Mitigation: historical rates of change and state and subsequent replacement of hydropower with coal-fired power of decoupling (Tollefson, 2017), but this reversal is expected to be temporary (IEA, 2017c). Oil consumption in China is still rising slowly, but absolute Realizing 1.5°C-consistent pathways would require rapid and decoupling is ongoing in megacities like Beijing (Gao and Newman, systemic changes on unprecedented scales (see Chapter 2 and 2018) (see Box 4.9). Section 4.2.1). This section examines whether the needed rates of change have historical precedents and are underway. 4.2.2.2 Transformational adaptation Some studies conduct a de-facto validation of IAM projections. For CO2 In some regions and places, incremental adaptation would not emission intensity over 1990–2010, this resulted in the IAMs projecting be sufficient to mitigate the impacts of climate change on social- declining emission intensities while actual observations showed an ecological systems (see Chapter 3). Transformational adaptation increase. For individual technologies (in particular solar energy), IAM would then be required (Bahadur and Tanner, 2014; Pant et al., projections have been conservative regarding deployment rates and 2015; Gillard, 2016; Gillard et al., 2016; Colloff et al., 2017; Termeer cost reductions (Creutzig et al., 2017), suggesting that IAMs do not et al., 2017). Transformational adaptation refers to actions aiming 4 always impute actual rates of technological change resulting from at adapting to climate change resulting in significant changes in influence of shocks, broader changes and mutually reinforcing factors structure or function that go beyond adjusting existing practices in society and politics (Geels and Schot, 2007; Daron et al., 2015; (Dowd et al., 2014; IPCC, 2014a; Few et al., 2017), including Sovacool, 2016; Battiston et al., 2017). approaches that enable new ways of decision-making on adaptation (Colloff et al., 2017). Few studies have assessed the potentially Other studies extrapolate historical trends into the future (Höök et al., transformative character of adaptation options (Pelling et al., 2015; 2011; Fouquet, 2016), or contrast the rates of change associated with Rippke et al., 2016; Solecki et al., 2017), especially in the context of specific temperature limits in IAMs (such as those in Chapter 2) with warming of 1.5°C. historical trends to investigate plausibility of emission pathways and associated temperature limits (Wilson et al., 2013; Gambhir et al., 2017; Transformational adaptation can be adopted at a large scale, can lead Napp et al., 2017). When metrics are normalized to gross domestic to new strategies in a region or resource system, transform places product (GDP; as opposed to other normalization metrics such as and potentially shift locations (Kates et al., 2012). Some systems primary energy), low-emission technology deployment rates used by might require transformational adaptation at 1.5°C. Implementing IAMs over the course of the coming century are shown to be broadly adaptation policies in anticipation of 1.5°C would require consistent with past trends, but rates of change in emission intensity transformation and flexible planning of adaptation (sometimes are typically overestimated (Wilson et al., 2013; Loftus et al., 2014; van called adaptation pathways) (Rothman et al., 2014; Smucker et Sluisveld et al., 2015). This bias is consistent with the findings from al., 2015; Holland, 2017; Gajjar et al., 2018), an understanding of the ‘validation’ studies cited above, suggesting that IAMs may under- the varied stakeholders involved and their motives, and knowledge report the potential for supply-side technological change assumed of less visible aspects of vulnerability based on social, cultural, in 1.5°-consistent pathways, but may be more optimistic about the political, and economic factors (Holland, 2017). Transformational systemic ability to realize incremental changes in reduction of emission adaptation would seek deep and long-term societal changes that intensity as a consequence of favourable energy efficiency payback influence sustainable development (Chung Tiam Fook, 2017; Few times (Wilson et al., 2013). This finding suggests that barriers and et al., 2017). enablers other than costs and climate limits play a role in technological change, as also found in the innovation literature (Hekkert et al., 2007; Adaptation requires multidisciplinary approaches integrating Bergek et al., 2008; Geels et al., 2016b). scientific, technological and social dimensions. For example, a 322 Strengthening and Implementing the Global Response Chapter 4 framework for transformational adaptation and the integration Innovations that disrupt entire systems may leave firms and utilities of mitigation and adaptation pathways can transform rural with stranded assets, as the transition can happen very quickly (IPCC, indigenous communities to address risks of climate change and 2014b; Kossoy et al., 2015). This may have consequences for fossil other stressors (Thornton and Comberti, 2017). In villages in rural fuels that are rendered ‘unburnable’ (McGlade and Ekins, 2015) and Nepal, transformational adaptation has taken place, with villagers fossil fuel-fired power and industry assets that would become obsolete changing their agricultural and pastoralist livelihood strategies after (Caldecott, 2017; Farfan and Breyer, 2017). The presence of multiple years of lost crops due to changing rain patterns and degradation barriers and enablers operating in a system implies that rapid change, of natural resources (Thornton and Comberti, 2017). Instead, they whether the product of many small changes (Termeer et al., 2017) are now opening stores, hotels, and tea shops. In another case, the or large-scale disruptions, is seldom an insular or discrete process arrival of an oil pipeline altered traditional Alaskan communities’ (Sterling et al., 2017). This finding informs the multidimensional nature livelihoods. With growth of oil production, investments were made of feasibility in Cross-Chapter Box 3 in Chapter 1 which is applied in for rural development. A later drop in oil production decreased these Section 4.5. Climate responses that are aligned with multiple feasibility investments. Alaskan indigenous populations are also dealing with dimensions and combine adaptation and mitigation interventions with impacts of climate change, such as sea level rise, which is altering non-climate benefits can accelerate change and reduce risks and costs their livelihood sources. Transformational adaptation is taking (Fazey et al., 2018). Also political, social and technological influences on place by changing the energy matrix to renewable energy, in which energy transitions, for example, can accelerate them faster than narrow indigenous people apply their knowledge to achieve environmental, techno-economic analysis suggests is possible (Kern and Rogge, 2016), economic, and social benefits (Thornton and Comberti, 2017). but could also introduce new constraints and risks (Geels et al., 2016b; Sovacool, 2016; Eyre et al., 2018). 4.2.2.3 Disruptive innovation Disruptive innovation and technological change may play a role in Demand-driven disruptive innovations that emerge as the product mitigation and in adaptation. The next section assesses mitigation of political and social changes across multiple scales can be and adaptation options in energy, land and ecosystem, urban and transformative (Seba, 2014; Christensen et al., 2015; Green and infrastructure and industrial systems. Newman, 2017a). Such innovations would lead to simultaneous, profound changes in behaviour, economies and societies (Seba, 2014; Christensen et al. 2015), but are difficult to predict in supply-focused economic models (Geels et al., 2016a; Pindyck, 2017). Rapid socio- 4.3 Systemic Changes for 1.5°C-Consistent technical change has been observed in the solar industry (Creutzig et Pathways al. (2017). Similar changes to socio-ecological systems can stimulate adaptation and mitigation options that lead to more climate-resilient Section 4.2 emphasizes the importance of systemic change for systems (Adger et al., 2005; Ostrom, 2009; Gillard et al., 2016) (see 1.5°C-consistent pathways. This section translates this into four 4 the Alaska and Nepal examples in Section 4.2.2.2). The increase in main system transitions: energy, land and ecosystem, urban and roof-top solar and energy storage technology as well as the increase in infrastructure, and industrial system transitions. This section assesses passive housing and net zero-emissions buildings are further examples the mitigation, adaptation and carbon dioxide removal options that of such disruptions (Green and Newman, 2017b). Both roof-top solar offer the potential for such change within those systems, based on and energy storage have benefitted from countries’ economic growth options identified by Chapter 2 and risks and impacts in Chapter 3. strategies and associated price declines in photovoltaic technologies, particularly in China (Shrivastava and Persson, 2018), as well as from The section puts more emphasis on those adaptation options (Sections new information and communication technologies (Koomey et al., 4.3.1–4.3.5) and mitigation options (Sections 4.3.1–4.3.4, 4.3.6 2013), rising demand for electricity in urban areas, and global concern and 4.3.7) that are 1.5°C-relevant and have developed considerably regarding greenhouse gas emissions (Azeiteiro and Leal Filho, 2017; since AR5. They also form the basis for the mitigation and adaptation Lutz and Muttarak, 2017; Wamsler, 2017). feasibility assessments in Section 4.5. Section 4.3.8 discusses solar radiation modification methods. System co-benefits can create the potential for mutually enforcing and demand-driven climate responses (Jordan et al., 2015; This section emphasizes that no single solution or option can enable a Hallegatte and Mach, 2016; Pelling et al., 2018), and for rapid and global transition to 1.5°C-consistent pathways or adapting to projected transformational change (Cole, 2015; Geels et al., 2016b; Hallegatte impacts. Rather, accelerating change, much of which is already starting and Mach, 2016). Examples of co-benefits include gender equality, or underway, in multiple global systems, simultaneously and at different agricultural productivity (Nyantakyi-Frimpong and Bezner-Kerr, 2015), scales, could provide the impetus for these system transitions. The reduced indoor air pollution (Satterthwaite and Bartlett, 2017), flood feasibility of individual options as well as the potential for synergies buffering (Colenbrander et al., 2017), livelihood support (Shaw et and reducing trade-offs will vary according to context and the local al., 2014; Ürge-Vorsatz et al., 2014), economic growth (GCEC, 2014; enabling conditions. These are explored at a high level in Section 4.5. Stiglitz et al., 2017), social progress (Steg et al., 2015; Hallegatte and Policy packages that bring together multiple enabling conditions can Mach, 2016) and social justice (Ziervogel et al., 2017; Patterson et provide building blocks for a strategy to scale up implementation and al., 2018). intervention impacts. 323 Chapter 4 Strengthening and Implementing the Global Response 4.3.1 Energy System Transitions (Yenneti and Day, 2016; Rand and Hoen, 2017; Gorayeb et al., 2018) that raise landscape management (Nadaï and Labussière, 2017) and This section discusses the feasibility of mitigation and adaptation distributional justice (Yenneti and Day, 2016) challenges. Research options related to the energy system transition. Only options relevant indicates that financial participation and community engagement can to 1.5°C and with significant changes since AR5 are discussed, which be effective in mitigating resistance (Brunes and Ohlhorst, 2011; Rand means that for options like hydropower and geothermal energy, and Hoen, 2017) (see Section 4.4.3). the chapter refers to AR5 and does not provide a discussion. Socio- technical inertia of energy options for 1.5°C-consistent pathways are Bottom-up studies estimating the use of renewable energy in the future, increasingly being surmounted as fossil fuels start to be phased out. either at the global or at the national level, are plentiful, especially in Supply-side mitigation and adaptation options and energy demand- the grey literature. It is hotly debated whether a fully renewable energy side options, including energy efficiency in buildings and transportation, or electricity system, with or without biomass, is possible (Jacobson et are discussed in Section 4.3.3; options around energy use in industry al., 2015, 2017) or not (Clack et al., 2017; Heard et al., 2017), and by are discussed in Section 4.3.4. what year. Scale-up estimates vary with assumptions about costs and technological maturity, as well as local geographical circumstances Section 4.5 assesses the feasibility in a systematic manner based on and the extent of storage used (Ghorbani et al., 2017; REN21, 2017). the approach outlined in Cross-Chapter Box 3 in Chapter 1. Several countries have adopted targets of 100% renewable electricity (IEA, 2017c) as this meets multiple social, economic and environmental 4.3.1.1 Renewable electricity: solar and wind goals and contributes to mitigation of climate change (REN21, 2017). All renewable energy options have seen considerable advances over 4.3.1.2 Bioenergy and biofuels the years since AR5, but solar energy and both onshore and offshore wind energy have had dramatic growth trajectories. They appear well Bioenergy is renewable energy from biomass. Biofuel is biomass-based underway to contribute to 1.5°C-consistent pathways (IEA, 2017c; energy used in transport. Chapter 2 suggests that pathways limiting IRENA, 2017b; REN21, 2017). warming to 1.5°C would enable supply of 67–310 (median 150) EJ yr−1 (see Table 2.8) from biomass. Most scenarios find that bioenergy The largest growth driver for renewable energy since AR5 has been is combined with carbon dioxide capture and storage (CCS, BECCS) if it the dramatic reduction in the cost of solar photovoltaics (PV) (REN21, is available but also find robust deployment of bioenergy independent 2017). This has made rooftop solar competitive in sunny areas between of the availability of CCS (see Chapter 2, Section 2.3.4.2 and Section 45° north and south latitude (Green and Newman, 2017b), though 4.3.7 for a discussion of BECCS). Detailed assessments indicate that IRENA (2018) suggests it is cost effective in many other places too. Solar deployment is similar for pathways limiting global warming to below PV with batteries has been cost effective in many rural and developing 2°C (Chum et al., 2011; P. Smith et al., 2014; Creutzig et al., 2015b). 4 areas (Pueyo and Hanna, 2015; Szabó et al., 2016; Jimenez, 2017), There is however high agreement that the sustainable bioenergy for example 19 million people in Bangladesh now have solar-battery potential in 2050 would be restricted to around 100 EJ yr−1 (Slade electricity in remote villages and are reporting positive experiences on et al., 2014; Creutzig et al., 2015b). Sustainable deployment at such safety and ease of use (Kabir et al., 2017). Small-scale distributed energy or higher levels envisioned by 1.5°C-consistent pathways may put projects are being implemented in developed and developing cities significant pressure on available land, food production and prices where residential and commercial rooftops offer potential for consumers (Popp et al., 2014b; Persson, 2015; Kline et al., 2017; Searchinger et becoming producers (called prosumers) (ACOLA, 2017; Kotilainen and al., 2017), preservation of ecosystems and biodiversity (Creutzig et Saari, 2018). Such prosumers could contribute significantly to electricity al., 2015b; Holland et al., 2015; Santangeli et al., 2016), and potential generation in sun-rich areas like California (Kurdgelashvili et al., 2016) water and nutrient constraints (Gerbens-Leenes et al., 2009; Gheewala or sub-Saharan Africa in combination with micro-grids and mini-grids et al., 2011; Bows and Smith, 2012; Smith and Torn, 2013; Bonsch et (Bertheau et al., 2017). It could also contribute to universal energy al., 2016; Lampert et al., 2016; Mouratiadou et al., 2016; Smith et al., access (SDG 7) as shown by (IEA, 2017c). 2016b; Wei et al., 2016; Mathioudakis et al., 2017); but there is still low agreement on these interactions (Robledo-Abad et al., 2017). Some The feasibility of renewable energy options depends to a large of the disagreement on the sustainable capacity for bioenergy stems extent on geophysical characteristics of the area where the option is from global versus local assessments. Global assessments may mask implemented. However, technological advances and policy instruments local dynamics that exacerbate negative impacts and shortages while make renewable energy options increasingly attractive in other areas. at the same time niche contexts for deployment may avoid trade-offs For example, solar PV is deployed commercially in areas with low solar and exploit co-benefits more effectively. In some regions of the world insolation, like northwest Europe (Nyholm et al., 2017). Feasibility also (e.g., the case of Brazilian ethanol, see Box 4.7, where land may be less depends on grid adaptations (e.g., storage, see below) as renewables of a constraint, the use of bioenergy is mature and the industry is well grow (IEA, 2017c). For regions with high energy needs, such as developed), land transitions could be balanced with food production industrial areas (see Section 4.3.4), high-voltage DC transmission and biodiversity to enable a global impact on CO2 emissions (Jaiswal across long distances would be needed (MacDonald et al., 2016). et al., 2017). Another important factor affecting feasibility is public acceptance, in The carbon intensity of bioenergy, key for both bioenergy as an particular for wind energy and other large-scale renewable facilities emission-neutral energy option and BECCS as a CDR measure, is 324 Strengthening and Implementing the Global Response Chapter 4 still a matter of debate (Buchholz et al., 2016; Liu et al., 2018) and investment risks of high-capital expenditure technologies have depends on management (Pyörälä et al., 2014; Torssonen et al., 2016; become significant. ‘Learning by doing’ processes often failed to Baul et al., 2017; Kilpeläinen et al., 2017); direct and indirect land-use compensate for this trend because they were slowed down by the change emissions (Plevin et al., 2010; Schulze et al., 2012; Harris et absence of standardization and series effects (Grubler, 2010). What al., 2015; Repo et al., 2015; DeCicco et al., 2016; Qin et al., 2016)2; the the costs of nuclear power are and have been is debated in the feedstock considered; and time frame (Zanchi et al., 2012; Daioglou et literature (Lovering et al., 2016; Koomey et al., 2017). Countries with al., 2017; Booth, 2018; Sterman et al., 2018), as well as the availability liberalized markets that continue to develop nuclear employ de-risking of coordinated policies and management to minimize negative instruments through long-term contracts with guaranteed sale prices side effects and trade-offs, particularly those around food security (Finon and Roques, 2013). For instance, the United Kingdom works (Stevanović et al., 2017) and livelihood and equity considerations with public guarantees covering part of the upfront investment costs (Creutzig et al., 2013; Calvin et al., 2014) . of newly planned nuclear capacity. This dynamic differs in countries such as China and South Korea, where monopolistic conditions in Biofuels are a part of the transport sector in some cities and countries, the electric system allow for reducing investment risks, deploying and may be deployed as a mitigation option for aviation, shipping series effects and enhancing the engineering capacities of users and freight transport (see Section 4.3.3.5) as well as industrial due to stable relations between the security authorities and builders decarbonization (IEA, 2017g) (Section 4.3.4), though only Brazil has (Schneider et al., 2017). mainstreamed ethanol as a substantial, commercial option. Lower emissions and reduced urban air pollution have been achieved there The safety of nuclear plants depends upon the public authorities of by use of ethanol and biodiesel as fuels (Hill et al., 2006; Salvo et al., each country. However, because accidents affect worldwide public 2017) (see Box 4.7). acceptance of this industry, questions have been raised about the risk of economic and political pressures weakening the safety of the plants 4.3.1.3 Nuclear energy (Finon, 2013; Budnitz, 2016). This raises the issue of international governance of civil nuclear risks and reinforced international Many scenarios in Chapter 2 and in AR5 (Bruckner et al., 2014) cooperation involving governments, companies and engineering project an increase in the use of nuclear power, while others project (Walker and Lönnroth, 1983; Thomas, 1988; Finon, 2013), based on the a decrease. The increase can be realized through existing mature experience of the International Atomic Energy Agency. nuclear technologies or new options (generation III/IV reactors, breeder reactors, new uranium and thorium fuel cycles, small reactors 4.3.1.4 Energy storage or nuclear cogeneration). The growth in electricity storage for renewables has been around grid Even though scalability and speed of scaling of nuclear plants have flexibility resources (GFR) that would enable several places to source historically been high in many nations, such rates are currently not more than half their power from non-hydro renewables (Komarnicki, 4 achieved anymore. In the 1960s and 1970s, France implemented a 2016). Ten types of GFRs within smart grids have been developed programme to rapidly get 80% of its power from nuclear in about (largely since AR5)(Blaabjerg et al., 2004; IRENA, 2013; IEA, 2017d; 25 years (IAEA, 2018), but the current time lag between the decision Majzoobi and Khodaei, 2017), though how variable renewables date and the commissioning of plants is observed to be 10-19 years can be balanced without hydro or natural gas-based power back- (Lovins et al., 2018). The current deployment pace of nuclear energy is up at a larger scale would still need demonstration. Pumped hydro constrained by social acceptability in many countries due to concerns comprised 150 GW of storage capacity in 2016, and grid-connected over risks of accidents and radioactive waste management (Bruckner battery storage just 1.7 GW, but the latter grew between 2015 to et al., 2014). Though comparative risk assessment shows health risks 2016 by 50% (REN21, 2017). Battery storage has been the main are low per unit of electricity production (Hirschberg et al., 2016), and growth feature in energy storage since AR5 (Breyer et al., 2017). land requirement is lower than that of other power sources (Cheng and This appears to the result of significant cost reductions due to mass Hammond, 2017), the political processes triggered by societal concerns production for electric vehicles (EVs) (Nykvist and Nilsson, 2015; Dhar depend on the country-specific means of managing the political et al., 2017). Although costs and technical maturity look increasingly debates around technological choices and their environmental impacts positive, the feasibility of battery storage is challenged by concerns (Gregory et al., 1993). Such differences in perception explain why the over the availability of resources and the environmental impacts of 2011 Fukushima incident resulted in a confirmation or acceleration of its production (Peters et al., 2017). Lithium, a common element in phasing out nuclear energy in five countries (Roh, 2017) while 30 other the earth’s crust, does not appear to be restricted and large increases countries have continued using nuclear energy, amongst which 13 are in production have happened in recent years with eight new mines building new nuclear capacity, including China, India and the United in Western Australia where most lithium is produced (GWA, 2016). Kingdom (IAEA, 2017; Yuan et al., 2017). Emerging battery technologies may provide greater efficiency and recharge rates (Belmonte et al., 2016) but remain significantly more Costs of nuclear power have increased over time in some developed expensive due to speed and scale issues compared to lithium ion nations, principally due to market conditions where increased batteries (Dhar et al., 2017; IRENA, 2017a). 2 While there is high agreement that indirect land use change (iLUC) could occur, there is low agreement about the actual extent of iLUC (P. Smith et al., 2014; Verstegen et al., 2015; Zilberman, 2017) 325 Chapter 4 Strengthening and Implementing the Global Response Research and demonstration of energy storage in the form of thermal plants can reduce emissions and water needs (Eisenack and Stecker, and chemical systems continues, but large-scale commercial systems 2012; van Vliet et al., 2016), but applying CCS would increase water are rare (Pardo et al., 2014). Renewably derived synthetic liquid (like consumption (Koornneef et al., 2012). The technological, economic, methanol and ammonia) and gas (like methane and hydrogen) are social and institutional feasibility of efficiency improvements is high, increasingly being seen as a feasible storage options for renewable but insufficient to limit temperature rise to 1.5°C (van Vliet et al., 2016). energy (producing fuel for use in industry during times when solar and wind are abundant) (Bruce et al., 2010; Jiang et al., 2010; Ezeji, In addition, a number of options for water cooling management 2017) but, in the case of carbonaceous storage media, would need a systems have been proposed, such as hydraulic measures (Eisenack renewable source of carbon to make a positive contribution to GHG and Stecker, 2012) and alternative cooling technologies (Chandel et al., reduction (von der Assen et al., 2013; Abanades et al., 2017) (see also 2011; Eisenack and Stecker, 2012; Bartos and Chester, 2015; Murrant Section 4.3.4.5). The use of electric vehicles as a form of storage has et al., 2015; Bustamante et al., 2016; van Vliet et al., 2016; Huang et al., been modelled and evaluated as an opportunity, and demonstrations 2017b). There is high agreement on the technological and economic are emerging (Dhar et al., 2017; Green and Newman, 2017a), but feasibility of these technologies, as their absence can severely impact challenges to upscaling remain. the functioning of the power plant as well as safety and security standards. 4.3.1.5 Options for adapting electricity systems to 1.5°C 4.3.1.6 Carbon dioxide capture and storage in the power sector Climate change has started to disrupt electricity generation and, if climate change adaptation options are not considered, it is predicted The AR5 (IPCC, 2014b) as well as Chapter 2, Section 2.4.2, assign that these disruptions will be lengthier and more frequent (Jahandideh- significant emission reductions over the course of this century to CO2 Tehrani et al., 2014; Bartos and Chester, 2015; Kraucunas et al., 2015; capture and storage (CCS) in the power sector. This section focuses van Vliet et al., 2016). Adaptation would both secure vulnerable on CCS in the fossil-fuelled power sector; Section 4.3.4 discusses infrastructure and ensure the necessary generation capacity (Minville CCS in non-power industry, and Section 4.3.7 discusses bioenergy et al., 2009; Eisenack and Stecker, 2012; Schaeffer et al., 2012; Cortekar with CCS (BECCS). Section 2.4.2 puts the cumulative CO2 stored and Groth, 2015; Murrant et al., 2015; Panteli and Mancarella, 2015; from fossil-fuelled power at 410 (199–470 interquartile range) GtCO2 Goytia et al., 2016). The literature shows high agreement that climate over this century. Such modelling suggests that CCS in the power change impacts need to be planned for in the design of any kind of sector can contribute to cost-effective achievement of emission infrastructure, especially in the energy sector (Nierop, 2014), including reduction requirements for limiting warming to 1.5°C. CCS may also interdependencies with other sectors that require electricity to function, offer employment and political advantages for fossil fuel-dependent including water, data, telecommunications and transport (Fryer, 2017). economies (Kern et al., 2016), but may entail more limited co-benefits than other mitigation options (that, e.g., generate power) and therefore 4 Recent research has developed new frameworks and models that relies on climate policy incentives for its business case and economic aim to assess and identify vulnerabilities in energy infrastructure feasibility. Since 2017, two CCS projects in the power sector capture and create more proactive responses (Francis and Bekera, 2014; 2.4 MtCO2 annually, while 30 MtCO2 is captured annually in all CCS Ouyang and Dueñas-Osorio, 2014; Arab et al., 2015; Bekera and projects (Global CCS Institute, 2017). Francis, 2015; Knight et al., 2015; Jeong and An, 2016; Panteli et al., 2016; Perrier, 2016; Erker et al., 2017; Fu et al., 2017). Assessments of The technological maturity of CO2 capture options in the power sectors energy infrastructure adaptation, while limited, emphasize the need has improved considerably (Abanades et al., 2015; Bui et al., 2018), for redundancy (Liu et al., 2017). The implementation of controllable but costs have not come down between 2005 and 2015 due to limited and islandable microgrids, including the use of residential batteries, learning in commercial settings and increased energy and resources can increase resiliency, especially after extreme weather events (Qazi costs (Rubin et al., 2015). Storage capacity estimates vary greatly, but and Young Jr., 2014; Liu et al., 2017). Hybrid renewables-based power Section 2.4.2 as well as literature (V. Scott et al., 2015) indicate that systems with non-hydro capacity, such as with high-penetration wind perhaps 10,000 GtCO2 could be stored in underground reservoirs. generation, could provide the required system flexibility (Canales et Regional availability of this may not be sufficient, and it requires al., 2015). Overall, there is high agreement that hybrid systems, taking efforts to have this storage and the corresponding infrastructure advantage of an array of sources and time of use strategies, can help available at the necessary rates and times (de Coninck and Benson, make electricity generation more resilient (Parkinson and Djilali, 2015), 2014). CO2 retention in the storage reservoir was recently assessed given that energy security standards are in place (Almeida Prado et as 98% over 10,000 years for well-managed reservoirs, and 78% al., 2016). for poorly regulated ones (Alcalde et al., 2018). A paper reviewing 42 studies on public perception of CCS (Seigo et al., 2014) found that Interactions between water and energy are complex (IEA, 2017g). social acceptance of CCS is predicted by trust, perceived risks and Water scarcity patterns and electricity disruptions will differ across benefits. The technology itself mattered less than the social context of regions. There is high agreement that mitigation and adaptation the project. Though insights on communication of CCS projects to the options for thermal electricity generation (if that remains fitted with general public and inhabitants of the area around the CO2 storage sites CCS) need to consider increasing water shortages, taking into account have been documented over the years, project stakeholders are not other factors such as ambient water resources and demand changes in consistently implementing these lessons, although some projects have irrigation water (Hayashi et al., 2018). Increasing the efficiency of power observed good practices (Ashworth et al., 2015). 326 Strengthening and Implementing the Global Response Chapter 4 CCS in the power sector is hardly being realized at scale, mainly work well in water-limited agroecosystems when implemented jointly because the incremental costs of capture, and the development of with residue retention and crop rotation, but when used independently, transport and storage infrastructures are not sufficiently compensated may decrease yields in other situations (Pittelkow et al., 2014). by market or government incentives (IEA, 2017c). In the two full-scale Additional climate adaptations include adjusting planting times and projects in the power sector mentioned above, part of the capture costs crop varietal selection and improving irrigation efficiency. Adaptations are compensated for by revenues from enhanced oil recovery (EOR) such as these may increase wheat and maize yields by 7–12% under (Global CCS Institute, 2017), demonstrating that EOR helps developing climate change (Challinor et al., 2014). CA can also help build adaptive CCS further. EOR is a technique that uses CO2 to mobilize more oil capacity (medium evidence, medium agreement) (H. Smith et al., 2017; out of depleting oil fields, leading to additional CO2 emissions by Pradhan et al., 2018) and have mitigation co-benefits through improved combusting the additionally recovered oil (Cooney et al., 2015). fertiliser use or efficient use of machinery and fossil fuels (Harvey et al., 2014; Cui et al., 2018; Pradhan et al., 2018). CA practices can also raise 4.3.2 Land and Ecosystem Transitions soil carbon and therefore remove CO2 from the atmosphere (Aguilera et al., 2013; Poeplau and Don, 2015; Vicente-Vicente et al., 2016). This section assesses the feasibility of mitigation and adaptation options However, CA adoption can be constrained by inadequate institutional related to land use and ecosystems. Land transitions are grouped around arrangements and funding mechanisms (Harvey et al., 2014; Baudron agriculture and food, ecosystems and forests, and coastal systems. et al., 2015; Li et al., 2016; Dougill et al., 2017; H. Smith et al., 2017). 4.3.2.1 Agriculture and food Sustainable intensification of agriculture consists of agricultural systems with increased production per unit area but with management In a 1.5°C world, local yields are projected to decrease in tropical of the range of potentially adverse impacts on the environment (Pretty regions that are major food producing areas of the world (West Africa, and Bharucha, 2014). Sustainable intensification can increase the Southeast Asia, South Asia, and Central and northern South America) efficiency of inputs and enhance health and food security (Ramankutty (Schleussner et al., 2016). Some high-latitude regions may benefit from et al., 2018). the combined effects of elevated CO2 and temperature because their average temperatures are below optimal temperature for crops. In both Livestock management. Livestock are responsible for more GHG cases there are consequences for food production and quality (Cross- emissions than all other food sources. Emissions are caused by feed Chapter Box 6 in Chapter 3 on Food Security), conservation agriculture, production, enteric fermentation, animal waste, land-use change irrigation, food wastage, bioenergy and the use of novel technologies. and livestock transport and processing. Some estimates indicate that livestock supply chains could account for 7.1 GtCO2 per year, equivalent Food production and quality. Increased temperatures, including to 14.5% of global anthropogenic greenhouse gas emissions (Gerber 1.5°C warming, would affect the production of cereals such as wheat et al., 2013). Cattle (beef, milk) are responsible for about two-thirds and rice, impacting food security (Schleussner et al., 2016). There is of that total, largely due to methane emissions resulting from rumen 4 medium agreement that elevated CO2 concentrations can change food fermentation (Gerber et al., 2013; Opio et al., 2013). composition, with implications for nutritional security (Taub et al., 2008; Högy et al., 2009; DaMatta et al., 2010; Loladze, 2014; De Souza Despite ongoing gains in livestock productivity and volumes, the et al., 2015), with the effects being different depending on the region increase of animal products in global diets is restricting overall (Medek et al., 2017). agricultural efficiency gains because of inefficiencies in the conversion of agricultural primary production (e.g., crops) in the feed-animal Meta-analyses of the effects of drought, elevated CO2, and temperature products pathway (Alexander et al., 2017), offsetting the benefits of conclude that at 2°C local warming and above, aggregate production of improvements in livestock production systems (Clark and Tilman, 2017). wheat, maize, and rice are expected to decrease in both temperate and tropical areas (Challinor et al., 2014). These production losses could be There is increasing agreement that overall emissions from food systems lowered if adaptation measures are taken (Challinor et al., 2014), such could be reduced by targeting the demand for meat and other livestock as developing varieties better adapted to changing climate conditions. products, particularly where consumption is higher than suggested by human health guidelines. Adjusting diets to meet nutritional Adaptation options can help ensure access to sufficient, quality food. targets could bring large co-benefits, through GHG mitigation and Such options include conservation agriculture, improved livestock improvements in the overall efficiency of food systems (Erb et al., 2009; management, increasing irrigation efficiency, agroforestry and Tukker et al., 2011; Tilman and Clark, 2014; van Dooren et al., 2014; management of food loss and waste. Complementary adaptation and Ranganathan et al., 2016). Dietary shifts could contribute one-fifth of mitigation options, for example, the use of climate services (Section the mitigation needed to hold warming below 2°C, with one-quarter of 4.3.5), bioenergy (Section 4.3.1) and biotechnology (Section 4.4.4) can low-cost options (Griscom et al., 2017). There, however, remains limited also serve to reduce emissions intensity and the carbon footprint of food evidence of effective policy interventions to achieve such large-scale production. shifts in dietary choices, and prevailing trends are for increasing rather than decreasing demand for livestock products at the global scale Conservation agriculture (CA) is a soil management approach (Alexandratos and Bruinsma, 2012; OECD/FAO, 2017). How the role that reduces the disruption of soil structure and biotic processes by of dietary shift could change in 1.5°C-consistent pathways is also not minimising tillage. A recent meta-analysis showed that no-till practices clear (see Chapter 2). 327 Chapter 4 Strengthening and Implementing the Global Response Adaptation of livestock systems can include a suite of strategies such Each strategy has differing costs and benefits relating to unique as using different breeds and their wild relatives to develop a genetic biophysical, social, and economic contexts. Also, increasing irrigation pool resilient to climatic shocks and longer-term temperature shifts efficiency may foster higher dependency on irrigation, resulting in a (Thornton and Herrero, 2014), improving fodder and feed management heightened sensitivity to climate that may be maladaptive in the long (Bell et al., 2014; Havet et al., 2014) and disease prevention and control term (Lindoso et al., 2014). (Skuce et al., 2013; Nguyen et al., 2016). Most interventions that improve the productivity of livestock systems and enhance adaptation Improvements in irrigation efficiency would need to be supplemented to climate changes would also reduce the emissions intensity of food with ancillary activities, such as shifting to crops that require less water production, with significant co-benefits for rural livelihoods and the and improving soil and moisture conservation (Fader et al., 2016; security of food supplies (Gerber et al., 2013; FAO and NZAGRC, 2017a, Hong and Yabe, 2017; Sikka et al., 2018). Currently, the feasibility of b, c). Whether such reductions in emission intensity result in lower improving irrigation efficiency is constrained by issues of replicability or higher absolute GHG emissions depends on overall demand for across scale and sustainability over time (Burney and Naylor, 2012), livestock products, indicating the relevance of integrating supply-side institutional barriers and inadequate market linkages (Pittock et al., with demand-side measures within food security objectives (Gerber 2017). et al., 2013; Bajželj et al., 2014). Transitions in livestock production systems (e.g., from extensive to intensive) can also result in significant Growing evidence suggests that investing in behavioural shifts emission reductions as part of broader land-based mitigation strategies towards using irrigation technology such as micro-sprinklers or drip (Havlik et al., 2014). irrigation, is an effective and quick adaptation strategy (Varela-Ortega et al., 2016; Herwehe and Scott, 2018; Sikka et al., 2018) as opposed Overall, there is high agreement that farm strategies that integrate to large dams which have high financial, ecological and social costs mixed crop–livestock systems can improve farm productivity and (Varela-Ortega et al., 2016). While improving irrigation efficiency is have positive sustainability outcomes (Havet et al., 2014; Thornton technically feasible (R. Fishman et al., 2015) and has clear benefits for and Herrero, 2014; Herrero et al., 2015; Weindl et al., 2015). Shifting environmental values (Pfeiffer and Lin, 2014; R. Fishman et al., 2015), towards mixed crop–livestock systems is estimated to reduce feasibility is regionally differentiated as shown by examples as diverse agricultural adaptation costs to 0.3% of total production costs while as Kansas (Jägermeyr et al., 2015), India (R. Fishman et al., 2015) and abating deforestation by 76 Mha globally, making it a highly cost- Africa (Pittock et al., 2017). effective adaptation option with mitigation co-benefits (Weindl et al., 2015). Evidence from various regions supports this (Thornton and Agroforestry. The integration of trees and shrubs into crop and Herrero, 2015), although the feasible scale varies between regions and livestock systems, when properly managed, can potentially restrict soil systems, as well as being moderated by overall demand in specific erosion, facilitate water infiltration, improve soil physical properties food products. In Australia, some farmers have successfully shifted and buffer against extreme events (Lasco et al., 2014; Mbow et al., 4 to crop–livestock systems where, each year, they allocate land and 2014; Quandt et al., 2017; Sida et al., 2018). There is medium evidence forage resources in response to climate and price trends (Bell et al., and high agreement on the feasibility of agroforestry practices that 2014) . However, there can be some unintended negative impacts enhance productivity, livelihoods and carbon storage (Lusiana et al., of such integration, including increased burdens on women, higher 2012; Murthy, 2013; Coulibaly et al., 2017; Sida et al., 2018), including requirements of capital, competing uses of crop residues (e.g., feed from indigenous production systems (Coq-Huelva et al., 2017), with vs. mulching vs. carbon sequestration) and higher requirements variation by region, agroforestry type, and climatic conditions (Place of management skills, which can be a challenge across several low et al., 2012; Coe et al., 2014; Mbow et al., 2014; Iiyama et al., 2017; income countries (Thornton and Herrero, 2015; Thornton et al., 2018). Abdulai et al., 2018). Long-term studies examining the success of Finally, the feasibility of improving livestock efficiency is dependent agroforestry, however, are rare (Coe et al., 2014; Meijer et al., 2015; on socio-cultural context and acceptability: there remain significant Brockington et al., 2016; Zomer et al., 2016). issues around widespread adoption of crossbred animals, especially by smallholders (Thornton et al., 2018). The extent to which agroforestry practices employed at the farm level could be scaled up globally while satisfying growing food demand Irrigation efficiency. Irrigation efficiency is especially critical since is relatively unknown. Agroforestry adoption has been relatively low water endowments are expected to change, with 20–60 Mha of and uneven (Jacobi et al., 2017; Hernández-Morcillo et al., 2018), with global cropland being projected to revert from irrigated to rain-fed constraints including the expense of establishment and lack of reliable land, while other areas will receive higher precipitation in shorter time financial support, insecure land tenure, landowner’s lack of experience spans, thus affecting irrigation demand (Elliott et al., 2014). While with trees, complexity of management practices, fluctuating market increasing irrigation system efficiency is necessary, there is mixed demand and prices for different food and fibre products, the time and evidence on how to enact efficiency improvements (Fader et al., 2016; knowledge required for management, low intermediate benefits to Herwehe and Scott, 2018). Physical and technical strategies include offset revenue lags, and inadequate market access (Pattanayak et al., building large-scale reservoirs or dams, renovating or deepening 2003; Mercer, 2004; Sendzimir et al., 2011; Valdivia et al., 2012; Coe et irrigation channels, building on-farm rainwater harvesting structures, al., 2014; Meijer et al., 2015; Coulibaly et al., 2017; Jacobi et al., 2017). lining ponds, channels and tanks to reduce losses through percolation and evaporation, and investing in small infrastructure such as sprinkler Managing food loss and waste. The way food is produced, or drip irrigation sets (Varela-Ortega et al., 2016; Sikka et al., 2018). processed and transported strongly influences GHG emissions. Around 328 Strengthening and Implementing the Global Response Chapter 4 one-third of the food produced on the planet is not consumed (FAO, fibre resources, and could reduce impacts on land and conventional 2013), affecting food security and livelihoods (See Cross-Chapter Box agriculture (Greene et al., 2017). 6 on Food Security in Chapter 3). Food wastage is a combination of food loss – the decrease in mass and nutritional value of food Technological innovation could assist in increased agricultural efficiency due to poor infrastructure, logistics, and lack of storage technologies (e.g., via precision agriculture), decrease food wastage and genetics and management – and food waste that derives from inappropriate that enhance plant adaptation traits (Section 4.4.4). Technological and human consumption that leads to food spoilage associated with associated management improvements may be ways to increase the inferior quality or overproduction. Food wastage could lead to an efficiency of contemporary agriculture to help produce enough food increase in emissions estimated to 1.9–2.5 GtCO2-eq yr −1 (Hiç et al., to cope with population increases in a 1.5°C warmer world, and help 2016). reduce the pressure on natural ecosystems and biodiversity. Decreasing food wastage has high mitigation and adaptation potential 4.3.2.2 Forests and other ecosystems and could play an important role in land transitions towards 1.5°C, provided that reduced food waste results in lower production-side Ecosystem restoration. Biomass stocks in tropical, subtropical, emissions rather than increased consumption (Foley et al., 2011). There temperate and boreal biomes currently hold 1085, 194, 176, 190 Gt CO2, is medium agreement that a combination of individual–institutional respectively. Conservation and restoration can enhance these natural behaviour (Refsgaard and Magnussen, 2009; Thornton and Herrero, carbon sinks (Erb et al., 2017). 2014), and improved technologies and management (Lin et al., 2013; Papargyropoulou et al., 2014) can transform food waste into products Recent studies explore options for conservation, restoration and with marketable value. Institutional behaviour depends on investment improved land management estimating up to 23 GtCO2 (Griscom et and policies, which if adequately addressed could enable mitigation al., 2017). Mitigation potentials are dominated by reduced rates of and adaptation co-benefits in a relatively short time. deforestation, reforestation and forest management, and concentrated in tropical regions (Houghton, 2013; Canadell and Schulze, 2014; Grace Novel technologies. New molecular biology tools have been et al., 2014; Houghton et al., 2015; Griscom et al., 2017). Much of the developed that can lead to fast and precise genome modification (De literature focuses on REDD+ (reducing emissions from deforestation and Souza et al., 2016; Scheben et al., 2016) (e.g., CRISPR Cas9; Ran et forest degradation) as an institutional mechanism. However, restoration al., 2013; Schaeffer and Nakata, 2015). Such genome editing tools and management activities need not be limited to REDD+, and locally may moderately assist in mitigation and adaptation of agriculture adapted implementation may keep costs low, capitalize on co-benefits in relation to climate changes, elevated CO2, drought and flooding and ensure consideration of competing for socio-economic goals (Jantke (DaMatta et al., 2010; De Souza et al., 2015, 2016). These tools could et al., 2016; Ellison et al., 2017; Perugini et al., 2017; Spencer et al., 2017). contribute to developing new plant varieties that can adapt to warming of 1.5°C and overshoot, potentially avoiding some of the costs of crop Half of the estimated potential can be achieved at <100 USD/tCO2; and 4 shifting (Schlenker and Roberts, 2009; De Souza et al., 2016). However, a third of the cost-effective potential at <10 USD/tCO2 (Griscom et al., biosafety concerns and government regulatory systems can be a major 2017). Variation of costs in projects aiming to reduce emissions from barrier to the use of these tools as this increases the time and cost deforestation is high when considering opportunity and transaction of turning scientific discoveries into ready applicable technologies costs (Dang Phan et al., 2014; Overmars et al., 2014; Ickowitz et al., (Andow and Zwahlen, 2006; Maghari and Ardekani, 2011). 2017; Rakatama et al., 2017). The strategy of reducing enteric methane emissions by ruminants However, the focus on forests raises concerns of cross-biome leakage through the development of inhibitors or vaccines has already been (medium evidence, low agreement) (Popp et al., 2014a; Strassburg attempted with some successes, although the potential for application et al., 2014; Jayachandran et al., 2017) and encroachment on other at scale and in different situations remains uncertain. A methane ecosystems (Veldman et al., 2015). Reducing rates of deforestation inhibitor has been demonstrated to reduce methane from feedlot constrains the land available for agriculture and grazing, with trade- systems by 30% over a 12-week period (Hristov et al., 2015) with offs between diets, higher yields and food prices (Erb et al., 2016a; some productivity benefits, but the ability to apply it in grazing systems Kreidenweis et al., 2016). Forest restoration and conservation are will depend on further technological developments as well as costs compatible with biodiversity (Rey Benayas et al., 2009; Jantke et al., and incentives. A vaccine could potentially modify the microbiota of 2016) and available water resources; in the tropics, reducing rates of the rumen and be applicable even in extensive grazing systems by deforestation maintains cooler surface temperatures (Perugini et al., reducing the presence of methanogenic micro-organisms (Wedlock et 2017) and rainfall (Ellison et al., 2017). al., 2013) but has not yet been successfully demonstrated to reduce emissions in live animals. Selective breeding for lower-emitting Its multiple potential co-benefits have made REDD+ important for local ruminants is becoming rapidly feasible, offering small but cumulative communities, biodiversity and sustainable landscapes (Ngendakumana emissions reductions without requiring substantial changes in farm et al., 2017; Turnhout et al., 2017). There is low agreement on whether systems (Pickering et al., 2015). climate impacts will reverse mitigation benefits of restoration (Le Page et al., 2013) by increasing the likelihood of disturbance (Anderegg et Technological innovation in culturing marine and freshwater micro al., 2015), or reinforce them through carbon fertilization (P. Smith et and macro flora has significant potential to expand food, fuel and al., 2014). 329 Chapter 4 Strengthening and Implementing the Global Response Emerging regional assessments offer new perspectives for upscaling. hardening through the building of seawalls and the re-establishment Strengthening coordination, additional funding sources, and access of coastal ecosystems such as mangroves (André et al., 2016; Cooper and disbursement points increase the potential of REDD+ in working et al., 2016). While the feasibility of the solutions is high, they are towards 2°C and 1.5°C limits (Well and Carrapatoso, 2017). While expensive to scale (robust evidence, medium agreement). there are indications that land tenure has a positive impact (Sunderlin et al., 2014), a meta-analysis by Wehkamp et al. (2018a) shows that There is low evidence and high agreement that reducing the impact there is medium evidence and low agreement on which aspects of of local stresses (Halpern et al., 2015) will improve the resilience of governance improvements are supportive of conservation. Local marine ecosystems as they transition to a 1.5°C world (O’Leary et benefits, especially for indigenous communities, will only be accrued if al., 2017). Approaches to reducing local stresses are considered land tenure is respected and legally protected, which is not often the feasible, cost-effective and highly scalable. Ecosystem resilience case (Sunderlin et al., 2014; Brugnach et al., 2017). Although payments may be increased through alternative livelihoods (e.g., sustainable for reduced rates of deforestation may benefit the poor, the most aquaculture), which are among a suite of options for building resilience vulnerable populations could have limited, uneven access (Atela et al., in coastal ecosystems. These options enjoy high levels of feasibility yet 2014) and face lower opportunity costs from deforestation (Ickowitz are expensive, which stands in the way of scalability (robust evidence, et al., 2017). medium agreement) (Hiwasaki et al., 2015; Brugnach et al., 2017). Community-based adaptation (CbA). There is medium evidence Working with coastal communities has the potential for improving and high agreement for the use of CbA. The specific actions to take the resilience of coastal ecosystems. Combined with the advantages will depend upon the location, context, and vulnerability of the specific of using indigenous knowledge to guide transitions, solutions can be community. CbA is defined as ‘a community-led process, based on more effective when undertaken in partnership with local communities, communities’ priorities, needs, knowledge, and capacities, which aim cultures, and knowledge (See Box 4.3). to empower people to plan for and cope with the impacts of climate change’ (Reid et al., 2009). The integration of CbA with ecosystems- Restoration of coastal ecosystems and fisheries. Marine based adaptation (EbA) has been increasingly promoted, especially in restoration is expensive compared to terrestrial restoration, and the efforts to alleviate poverty (Mannke, 2011; Reid, 2016). survival of projects is currently low, with success depending on the ecosystem and site, rather than the size of the financial investment Despite the potential and advantages of both CbA and EbA, including (Bayraktarov et al., 2016). Mangrove replanting shows evidence knowledge exchange, information access and increased social capital of success globally, with numerous examples of projects that have and equity; institutional and governance barriers still constitute a established forests (Kimball et al., 2015; Bayraktarov et al., 2016). challenge for local adaptation efforts (Wright et al., 2014; Fernández- Giménez et al., 2015). Efforts with reef-building corals have been attempted with a low level 4 of success (Bayraktarov et al., 2016). Technologies to help re-establish Wetland management. In wetland ecosystems, temperature rise has coral communities are limited (Rinkevich, 2014), as are largely direct and irreversible impacts on species functioning and distribution, untested disruptive technologies (e.g., genetic manipulation, assisted ecosystem equilibrium and services, and second-order impacts on local evolution) (van Oppen et al., 2015). Current technologies also have livelihoods (see Chapter 3, Section 3.4.3). The structure and function trouble scaling given the substantial costs and investment required of wetland systems are changing due to climate change. Wetland (Bayraktarov et al., 2016). management strategies, including adjustments in infrastructural, behavioural, and institutional practices have clear implications for Johannessen and Macdonald (2016) report the ‘blue carbon’ sink to adaptation (Colloff et al., 2016b; Finlayson et al., 2017; Wigand et al., be 0.4–0.8% of global anthropogenic emissions. However, this does 2017) not adequately account for post-depositional processes and could overestimate removal potentials, subject to a risk of reversal. Seagrass Despite international initiatives on wetland restoration and beds will thus not contribute significantly to enabling 1.5°C-consistent management through the Ramsar Convention on Wetlands, policies pathways. have not been effective (Finlayson, 2012; Finlayson et al., 2017). Institutional reform, such as flexible, locally relevant governance, 4.3.3 Urban and Infrastructure System Transitions drawing on principles of adaptive co-management, and multi- stakeholder participation becomes increasingly necessary for effective There will be approximately 70 million additional urban residents every wetland management (Capon et al., 2013; Finlayson et al., 2017). year through to the middle part of this century (UN DESA, 2014). The majority of these new urban citizens will reside in small and medium- 4.3.2.3 Coastal systems sized cities in low- and middle-income countries (Cross-Chapter Box 13 in Chapter 5). The combination of urbanization and economic Managing coastal stress. Particularly to allow for the landward and infrastructure development could account for an additional relocation of coastal ecosystems under a transition to a 1.5°C warmer 226 GtCO2 by 2050 (Bai et al. 2018). However, urban systems can world, planning for climate change would need to be integrated with harness the mega-trends of urbanization, digitalization, financialization the use of coastlines by humans (Saunders et al., 2014; Kelleway et al., and growing sub-national commitment to smart cities, green cities, 2017). Adaptation options for managing coastal stress include coastal resilient cities, sustainable cities and adaptive cities, for the type of 330 Strengthening and Implementing the Global Response Chapter 4 transformative change required by 1.5°C-consistent pathways (SDSN, price changes in renewable energy technologies to enable clean 2013; Parag and Sovacool, 2016; Roberts, 2016; Wachsmuth et al., 2016; energy access to citizens (SDG 7) (Cartwright, 2015; Watkins, 2015; Revi, 2017; Solecki et al., 2018). There is a growing number of urban Lwasa, 2017; Kennedy et al., 2018; Teferi and Newman, 2018). This will climate responses driven by cost-effectiveness, development, work require strengthened energy governance in these countries (Eberhard creation and inclusivity considerations (Solecki et al., 2013; Ahern et et al., 2017). Where renewable energy displaces paraffin, wood fuel al., 2014; Floater et al., 2014; Revi et al., 2014a; Villarroel Walker et or charcoal feedstocks in informal urban settlements, it provides al., 2014; Kennedy et al., 2015; Rodríguez, 2015; McGranahan et al., the co-benefits of improved indoor air quality, reduced fire risk and 2016; Dodman et al., 2017a; Newman et al., 2017; UN-Habitat, 2017; reduced deforestation, all of which can enhance adaptive capacity Westphal et al., 2017). and strengthen demand for this energy (Newham and Conradie, 2013; Winkler, 2017; Kennedy et al., 2018; Teferi and Newman, 2018). In addition, low-carbon cities could reduce the need to deploy carbon dioxide removal (CDR) and solar radiation modification (SRM) (Fink, 4.3.3.2 Urban infrastructure, buildings and appliances 2013; Thomson and Newman, 2016). Buildings are responsible for 32% of global energy consumption (IEA, Cities are also places in which the risks associated with warming of 2016c) and have a large energy saving potential with available and 1.5°C, such as heat stress, terrestrial and coastal flooding, new disease demonstrated technologies such as energy efficiency improvements vectors, air pollution and water scarcity, will coalesce (see Chapter 3, in technical installations and in thermal insulation (Toleikyte et al., Section 3.3) (Dodman et al., 2017a; Satterthwaite and Bartlett, 2017). 2018) and energy sufficiency (Thomas et al., 2017). Kuramochi et Unless adaptation and mitigation efforts are designed around the need al. (2018) show that 1.5°C-consistent pathways require building to decarbonize urban societies in the developed world and provide emissions to be reduced by 80–90% by 2050, new construction to low-carbon solutions to the needs of growing urban populations in be fossil-free and near-zero energy by 2020, and an increased rate of developing countries, they will struggle to deliver the pace or scale energy refurbishment of existing buildings to 5% per annum in OECD of change required by 1.5°C-consistent pathways (Hallegatte et al., (Organisation for Economic Co-operation and Development) countries 2013; Villarroel Walker et al., 2014; Roberts, 2016; Solecki et al., 2018). (see also Section 4.2.1). The pace and scale of urban climate responses can be enhanced by attention to social equity (including gender equity), urban ecology Based on the IEA-ETP (IEA, 2017g), Chapter 2 identifies large saving (Brown and McGranahan, 2016; Wachsmuth et al., 2016; Ziervogel potential in heating and cooling through improved building design, et al., 2016a) and participation in sub-national networks for climate efficient equipment, lighting and appliances. Several examples of action (Cole, 2015; Jordan et al., 2015). net zero energy in buildings are now available (Wells et al., 2018). In existing buildings, refurbishment enables energy saving (Semprini The long-lived urban transport, water and energy systems that will be et al., 2017; Brambilla et al., 2018; D’Agostino and Parker, 2018; Sun constructed in the next three decades to support urban populations in et al., 2018) and cost savings (Toleikyte et al., 2018; Zangheri et al., 4 developing countries and to retrofit cities in developed countries will 2018). have to be different to those built in Europe and North America in the 20th century, if they are to support the required transitions (Freire et al., Reducing the energy embodied in building materials provides further 2014; Cartwright, 2015; McPhearson et al., 2016; Roberts, 2016; Lwasa, energy and GHG savings (Cabeza et al., 2013; Oliver and Morecroft, 2017). Recent literature identifies energy, infrastructure, appliances, 2014; Koezjakov et al., 2018), in particular through increased use of bio- urban planning, transport and adaptation options as capable of based materials (Lupíšek et al., 2015) and wood construction (Ramage facilitating systemic change. It is these aspects of the urban system that et al., 2017). The United Nations Environment Programme (UNEP3) are discussed below and from which options in Section 4.5 are selected. estimates that improving embodied energy, thermal performance, and direct energy use of buildings can reduce emissions by 1.9 GtCO2e yr −1 4.3.3.1 Urban energy systems (UNEP, 2017b), with an additional reduction of 3 GtCO2e yr −1 through energy efficient appliances and lighting (UNEP, 2017b). Further Urban economies tend to be more energy intensive than national increasing the energy efficiency of appliances and lighting, heating economies due to higher levels of per capita income, mobility and and cooling offers the potential for further savings (Parikh and Parikh, consumption (Kennedy et al., 2015; Broto, 2017; Gota et al., 2018). 2016; Garg et al., 2017). However, some urban systems have begun decoupling development from the consumption of fossil fuel-powered energy through energy Smart technology, drawing on the internet of things (IoT) and building efficiency, renewable energy and locally managed smart grids information modelling, offers opportunities to accelerate energy (Dodman, 2009; Freire et al., 2014; Eyre et al., 2018; Glazebrook and efficiency in buildings and cities (Moreno-Cruz and Keith, 2013; Hoy, Newman, 2018). 2016) (see also Section 4.4.4). Some cities in developing countries are drawing on these technologies to adopt ‘leapfrog’ infrastructure, The rapidly expanding cities of Africa and Asia, where energy poverty buildings and appliances to pursue low-carbon development (Newman currently undermines adaptive capacity (Westphal et al., 2017; et al., 2017; Teferi and Newman, 2017) (Cross-Chapter Box 13 in Satterthwaite et al., 2018), have the opportunity to benefit from recent Chapter 5). 3 Currently called UN Environment. 331 Chapter 4 Strengthening and Implementing the Global Response 4.3.3.3 Urban transport and urban planning and social cohesion (Goodwin and Van Dender, 2013; Newman and Kenworthy, 2015; Wee, 2015). Urban form impacts demand for energy (Sims et al., 2014) and other welfare related factors: a meta-analysis of 300 papers reported Technology and electrification trends since AR5 make carbon-efficient energy savings of 26 USD per person per year attributable to a 10% urban transport easier (Newman et al., 2016), but realizing urban increase in urban population density (Ahlfeldt and Pietrostefani, transport’s contribution to a 1.5°C-consistent pathways will require 2017). Significant reductions in car use are associated with dense, the type of governance that can overcome the financial, institutional, pedestrianized cities and towns and medium-density transit corridors behavioural and legal barriers to change (Geels, 2014; Bakker et al., (Newman and Kenworthy, 2015; Newman et al., 2017) relative to low- 2017). density cities in which car dependency is high (Schiller and Kenworthy, 2018). Combined dense urban forms and new mass transit systems Adaptation to a 1.5°C world is enabled by urban design and spatial in Shanghai and Beijing have yielded less car use (Gao and Newman, planning policies that consider extreme weather conditions and reduce 2018) (see Box 4.9). Compact cities also create the passenger density displacement by climate related disasters (UNISDR, 2009; UN-Habitat, required to make public transport more financially viable (Rode et al., 2011; Mitlin and Satterthwaite, 2013). 2017; Ahlfeldt and Pietrostefani, 2017) and enable combinations of cleaner fuel feedstocks and urban smart grids, in which vehicles form Building codes and technology standards for public lighting, part of the storage capacity (Oldenbroek et al., 2017). Similarly, the including traffic lights (Beccali et al., 2015), play a critical role in spatial organization of urban energy influenced the trajectories of reducing carbon emissions, enhancing urban climate resilience and urban development in cities as diverse as Hong Kong, Bengaluru and managing climate risk (Steenhof and Sparling, 2011; Parnell, 2015; Maputo (Broto, 2017). Shapiro, 2016; Evans et al., 2017). Building codes can support the convergence to zero emissions from buildings (Wells et al., 2018) and The informal settlements of middle- and low-income cities, where urban can be used retrofit the existing building stock for energy efficiency density is more typically associated with a range of water- and vector- (Ruparathna et al., 2016). borne health risks, may provide a notable exception to the adaptive advantages of urban density (Mitlin and Satterthwaite, 2013; Lilford et The application of building codes and standards for 1.5°C-consistent al., 2017) unless new approaches and technologies are harnessed to pathways will require improved enforcement, which can be a challenge accelerate slum upgrading (Teferi and Newman, 2017). in developing countries where inspection resources are often limited and codes are poorly tailored to local conditions (Ford et al., 2015c; Scenarios consistent with 1.5°C depend on a roughly 15% reduction Chandel et al., 2016; Eisenberg, 2016; Shapiro, 2016; Hess and Kelman, in final energy use by the transport sector by 2050 relative to 2015 2017; Mavhura et al., 2017). In all countries, building codes can be (Chapter 2, Figure 2.12). In one analysis the phasing out of fossil fuel undermined by industry interests and can be maladaptive if they 4 passenger vehicle sales by 2035–2050 was identified as a benchmark prevent buildings or land use from evolving to reduce climate impacts for aligning with 1.5°C-consistent pathways (Kuramochi et al., 2018). (Eisenberg, 2016; Shapiro, 2016). Reducing emissions from transport has lagged the power sector (Sims et al., 2014; Creutzig et al., 2015a), but evidence since AR5 suggests The deficit in building codes and standards in middle-income that cities are urbanizing and re-urbanizing in ways that coordinate and developing-country cities need not be a constraint to more transport sector adaptation and mitigation (Colenbrander et al., 2017; energy-efficient and resilient buildings (Tait and Euston-Brown, Newman et al., 2017; Salvo et al., 2017; Gota et al., 2018). The global 2017). For example, the relatively high price that poor households transport sector could reduce 4.7 GtCO −12e yr (4.1–5.3) by 2030. pay for unreliable and at times dangerous household energy This is significantly more than is predicted by integrated assessment in African cities has driven the uptake of renewable energy and models (UNEP, 2017b). Such a transition depends on cities that energy efficiency technologies in the absence of regulations or enable modal shifts and avoided journeys and that provide incentives fiscal incentives (Eberhard et al., 2011, 2016; Cartwright, 2015; for uptake of improved fuel efficiency and changes in urban design Watkins, 2015). The Kuyasa Housing Project in Khayelitsha, one of that encourage walkable cities, non-motorized transport and shorter Cape Town’s poorest suburbs, created significant mitigation and commuter distances (IEA, 2016a; Mittal et al., 2016; Zhang et al., adaptation benefits by installing ceilings, solar water heaters and 2016; Li and Loo, 2017). In at least 4 African cities, 43 Asian cities energy-efficient lightbulbs in houses independent of the formal and 54 Latin American cities, transit-oriented development (TOD), housing or electrification programme (Winkler, 2017). has emerged as an organizing principle for urban growth and spatial planning (Colenbrander et al., 2017; Lwasa, 2017; BRTData, 2018). 4.3.3.4 Electrification of cities and transport This trend is important to counter the rising demand for private cars in developing-country cities (AfDB/OECD/UNDP, 2016). In India, TOD has The electrification of urban systems, including transport, has shown been combined with localized solar PV installations and new ways of global progress since AR5 (IEA, 2016a; Kennedy et al., 2018; Schiller financing rail expansion (Sharma, 2018). and Kenworthy, 2018). High growth rates are now appearing in electric vehicles (Figure 4.1), electric bikes and electric transit (IEA, Cities pursuing sustainable transport benefit from reduced air pollution, 2018), which would need to displace fossil fuel-powered passenger congestion and road fatalities and are able to harness the relationship vehicles by 2035–2050 to remain in line with 1.5°C-consistent between transport systems, urban form, urban energy intensity pathways. China’s 2017 Road Map calls for 20% of new vehicle 332 Strengthening and Implementing the Global Response Chapter 4 in IAMs (Bows-Larkin, 2015), but could be reduced by between a third and two-thirds through energy efficiency measures and operational changes (Dahlmann et al., 2016). On shorter intercity trips, aviation could be replaced by high-speed electric trains drawing on renewable energy (Åkerman, 2011). Some progress has been made on the use of electricity in planes and shipping (Grewe et al., 2017) though no commercial applications have arisen. Studies indicate that biofuels are the most viable means of decarbonizing intercontinental travel, given their technical characteristics, energy content and affordability (Wise et al., 2017). The lifecycle emissions of bio-based jet fuels and marine fuels can be considerable (Cox et al., 2014; IEA, 2017g) depending on their location (Elshout et al., 2014), but can be reduced by feedstock and conversion technology choices (de Jong et al., 2017). Figure 4.1 | Increase of the global electric car stock by country (2013– In recent years the potential for transport to use synfuels, such as 2017). The grey line is battery electric vehicles (BEV) only while the black line includes ethanol, methanol, methane, ammonia and hydrogen, created from both BEV and plug-in hybrid vehicles (PHEV). Source: (IEA, 2018). Based on IEA data from Global EV Outlook 2018 © OECD/IEA 2018, IEA Publishing. renewable electricity and CO2, has gained momentum but has not yet demonstrated benefits on a scale consistent with 1.5°C pathways (Ezeji, 2017; Fasihi et al., 2017). Decarbonizing the fuel used by the world’s sales to be electric. India is aiming for exclusively electric vehicles 60,000 large ocean vessels faces governance barriers and the need for (EVs) by 2032 (NITI Aayog and RMI, 2017). Globally, EV sales were a global policy (Bows and Smith, 2012; IRENA, 2015; Rehmatulla and up 42% in 2016 relative to 2015, and in the United States EV sales Smith, 2015). Low-emission marine fuels could simultaneously address were up 36% over the same period (Johnson and Walker, 2016). sulphur and black carbon issues in ports and around waterways and accelerate the electrification of all large ports (Bouman et al., 2017; The extent of electric railways in and between cities has expanded IEA, 2017g). since AR5 (IEA, 2016a; Mittal et al., 2016; Zhang et al., 2016; Li and Loo, 2017). In high-income cities there is medium evidence for the 4.3.3.6 Climate-resilient land use decoupling of car use and wealth since AR5 (Newman, 2017). In cities where private vehicle ownership is expected to increase, less carbon- Urban land use influences energy intensity, risk exposure and adaptive intensive fuel sources and reduced car journeys will be necessary as capacity (Carter et al., 2015; Araos et al., 2016a; Ewing et al., 2016; well as electrification of all modes of transport (Mittal et al., 2016; Newman et al., 2016; Broto, 2017). Accordingly, urban land-use van Vuuren et al., 2017). Some recent urban data show a decoupling planning can contribute to climate mitigation and adaptation (Parnell, 4 of urban growth and GHG emissions (Newman and Kenworthy, 2015) 2015; Francesch-Huidobro et al., 2017) and the growing number of and that ‘peak car’ has been reached in Shanghai and Beijing (Gao and urban climate adaptation plans provide instruments to do this (Carter Kenworthy, 2017) and beyond (Manville et al., 2017) (also see Box 4.9). et al., 2015; Dhar and Khirfan, 2017; Siders, 2017; Stults and Woodruff, 2017). Adaptation plans can reduce exposure to urban flood risk An estimated 800 cities globally have operational bike-share schemes (E. (which, in a 1.5°C world, could double relative to 1976–2005; Alfieri Fishman et al., 2015), and China had 250 million electric bicycles in 2017 et al., 2017), heat stress (Chapter 3, Section 3.5.5.8), fire risk (Chapter (Newman et al., 2017). Advances in information and communication 3, Section 3.4.3.4) and sea level rise (Chapter 3, Section 3.4.5.1) technologies (ICT) offer cities the chance to reduce urban transport (Schleussner et al., 2016). congestion and fuel consumption by making better use of the urban vehicle fleet through car sharing, driverless cars and coordinated public Cities can reduce their risk exposure by considering investment in transport, especially when electrified (Wee, 2015; Glazebrook and infrastructure and buildings that are more resilient to warming of Newman, 2018). Advances in ‘big-data’ can assist in creating a better 1.5°C or beyond. Where adaptation planning and urban planning understanding of the connections between cities, green infrastructure, generate the type of local participation that enhances capacity to cope environmental services and health (Jennings et al., 2016) and improve with risks, they can be mutually supportive processes (Archer et al., decision-making in urban development (Lin et al., 2017). 2014; Kettle et al., 2014; Campos et al., 2016; Chu et al., 2017; Siders, 2017; Underwood et al., 2017). Not all adaptation plans are reported 4.3.3.5 Shipping, freight and aviation as effective (Measham et al., 2011; Hetz, 2016; Woodruff and Stults, 2016; Mahlkow and Donner, 2017), especially in developing-country International transport hubs, including airports and ports, and the cities (Kiunsi, 2013). In cases where adaptation planning may further associated mobility of people are major economic contributors to most marginalize poor citizens, either through limited local control over large cities even while under the governance of national authorities adaptation priorities or by displacing impacts onto poorer communities, and international legislation. Shipping, freight and aviation systems successful urban risk management would need to consider factors have grown rapidly, and little progress has been made since AR5 on such as justice, equity, and inclusive participation, as well as recognize replacing fossil fuels, though some trials are continuing (Zhang, 2016; the political economy of adaptation (Archer, 2016; Shi et al., 2016; Bouman et al., 2017; EEA, 2017). Aviation emissions do not yet feature Ziervogel et al., 2016a, 2017; Chu et al., 2017). 333 Chapter 4 Strengthening and Implementing the Global Response 4.3.3.7 Green urban infrastructure and ecosystem services Urban surface-sealing with impervious materials affects the volume and velocity of runoff and flooding during intense rainfall (Skougaard Integrating and promoting green urban infrastructure (including Kaspersen et al., 2015), but urban design in many cities now seeks street trees, parks, green roofs and facades, and water features) into to mediate runoff, encourage groundwater recharge and enhance city planning can be difficult (Leck et al., 2015) but increases urban water quality (Liu et al., 2014; Lamond et al., 2015; Voskamp and resilience to impacts of 1.5°C warming (Table 4.2) in ways that can be Van de Ven, 2015; Costa et al., 2016; Mguni et al., 2016; Xie et al., more cost-effective than conventional infrastructure (Cartwright et al., 2017). Challenges remain for managing intense rainfall events that are 2013; Culwick and Bobbins, 2016). reported to be increasing in frequency and intensity in some locations (Ziervogel et al., 2016b), and urban flooding is expected to increase at Realizing climate benefits from urban green infrastructure sometimes 1.5°C of warming (Alfieri et al., 2017). This risk falls disproportionately requires a city-region perspective (Wachsmuth et al., 2016). Where on women and poor people in cities (Mitlin, 2005; Chu et al., 2016; the urban impact on ecological systems in and beyond the city is Ziervogel et al., 2016b; Chant et al., 2017; Dodman et al., 2017a, b). appreciated, the potential for transformative change exists (Soderlund and Newman, 2015; Ziervogel et al., 2016a), and a locally appropriate Nexus approaches that highlight urban areas as socio-ecological combination of green space, ecosystem goods and services and the systems can support policy coherence (Rasul and Sharma, 2016) and built environment can increase the set of urban adaptation options sustainable urban livelihoods (Biggs et al., 2015). The water–energy– (Puppim de Oliveira et al., 2013). food (WEF) nexus is especially important to growing urban populations (Tacoli et al., 2013; Lwasa et al., 2014; Villarroel Walker et al., 2014). Milan, Italy, a city with deliberate urban greening policies, planted 10,000 hectares of new forest and green areas over the last two decades (Sanesi et al., 2017). The accelerated growth of urban trees, 4.3.4 Industrial Systems Transitions relative to rural trees, in several regions of the world is expected to decrease tree longevity (Pretzsch et al., 2017), requiring monitoring Industry consumes about one-third of global final energy and contributes, and additional management of urban trees if their contribution to directly and indirectly, about one-third of global GHG emissions (IPCC, urban ecosystem-based adaptation and mitigation is to be maintained 2014b). If the increase in global mean temperature is to remain under in a 1.5°C world (Buckeridge, 2015; Pretzsch et al., 2017). 1.5°C, modelling indicates that industry cannot emit more than 2 GtCO2 in 2050, corresponding to a reduction of between 67 and 91% 4.3.3.8 Sustainable urban water and environmental services (interquartile range) in GHG emissions compared to 2010 (see Chapter 2, Figures 2.20 and 2.21, and Table 4.1). Moreover, the consequences Urban water supply and wastewater treatment is energy intensive and of warming of 1.5°C or more pose substantial challenges for industrial currently accounts for significant GHG emissions (Nair et al., 2014). diversity. This section will first briefly discuss the limited literature on 4 Cities can integrate sustainable water resource management and the adaptation options for industry. Subsequently, new literature since AR5 supply of water services in ways that support mitigation, adaptation on the feasibility of industrial mitigation options will be discussed. and development through waste water recycling and storm water diversion (Xue et al., 2015; Poff et al., 2016). Governance and finance Research assessing adaptation actions by industry indicates that only challenges complicate balancing sustainable water supply and rising a small fraction of corporations has developed adaptation measures. urban demand, particularly in low-income cities (Bettini et al., 2015; Studies of adaptation in the private sector remain limited (Agrawala et Deng and Zhao, 2015; Hill Clarvis and Engle, 2015; Lemos, 2015; al., 2011; Linnenluecke et al., 2015; Averchenkova et al., 2016; Bremer Margerum and Robinson, 2015). and Linnenluecke, 2016; Pauw et al., 2016a) and for 1.5°C are largely Table 4.2 | Green urban infrastructure and benefits Green Adaptation Mitigation References Infrastructure Benefits Benefits Reduced heat island Less cement, reduced Urban tree planting, Demuzere et al., 2014; Mullaney et al., 2015; Soderlund and Newman, 2015; effect, psychological air-conditioning use urban parks Beaudoin and Gosselin, 2016; Green et al., 2016; Lin et al., 2017 benefits Less cement in city, Liu et al., 2014; Lamond et al., 2015; Skougaard Kaspersen et al., 2015; Voskamp Permeable surfaces Water recharge some bio-sequestration, and Van de Ven, 2015; Costa et al., 2016; Mguni et al., 2016; Xie et al., 2017 less water pumping Forest retention, urban Flood mediation, Nowak et al., 2006; Tallis et al., 2011; Elmqvist et al., 2013; Buckeridge, 2015; Culwick and Reduced air pollution agricultural land healthy lifestyles Bobbins, 2016; Panagopoulos et al., 2016; Stevenson et al., 2016; R. White et al., 2017 Reduced urban flood- Some bio-sequestration, Cartwright et al., 2013; Elmqvist et al., 2015; Brown and McGranahan, 2016; Wetland restoration, ing, low-skilled local less energy spent on Camps-Calvet et al., 2016; Culwick and Bobbins, 2016; McPhearson et al., riparian buffer zones work, sense of place water treatment 2016; Ziervogel et al., 2016b; Collas et al., 2017; F. Li et al., 2017 Psychological benefits, Beatley, 2011; Elmqvist et al., 2015; Brown and McGranahan, 2016; Camps-Calvet et al., 2016; Biodiverse urban habitat Carbon sequestration inner-city recreation McPhearson et al., 2016; Collas et al., 2017; F. Li et al., 2017 334 Strengthening and Implementing the Global Response Chapter 4 absent. This knowledge gap is particularly evident for medium-sized are available. In general, their feasibility depends on lowering capital enterprises and in low- and middle-income nations (Surminski, 2013). costs and raising awareness and expertise (Wesseling et al., 2017). General-purpose technologies, such as ICT, and energy management Depending on the industrial sector, mitigation consistent with 1.5°C tools can improve the prospects of energy efficiency in industry (see would mean, across industries, a reduction of final energy demand Section 4.4.4). by one-third, an increase of the rate of recycling of materials and the development of a circular economy in industry (Lewandowski, 2016; Cross-sector technologies and practices, which play a role in all Linder and Williander, 2017), the substitution of materials in high- industrial sectors including small- and medium-sized enterprises (SMEs) carbon products with those made up of renewable materials (e.g., wood and non-energy intensive industry, also offer potential for considerable instead of steel or cement in the construction sector, natural textile energy efficiency improvements. They include: (i) motor systems (for fibres instead of plastics), and a range of deep emission reduction example electric motors, variable speed drives, pumps, compressors options, including use of bio-based feedstocks, low-emission heat and fans), responsible for about 10% of worldwide industrial energy sources, electrification of production processes, and/or capture and consumption, with a global energy efficiency improvement potential of storage of all CO2 emissions by 2050 (Åhman et al., 2016). Some of the around 20–25% (Napp et al., 2014); and (ii) steam systems, responsible choices for mitigation options and routes for GHG-intensive industry for about 30% of industrial energy consumption and energy saving are discrete and potentially subject to path dependency: if an industry potentials of about 10% (Hasanbeigi et al., 2014; Napp et al., 2014). goes one way (e.g., in keeping existing processes), it will be harder to Waste heat recovery from industry has substantial potential for energy transition to process change (e.g., electrification) (Bataille et al., 2018). efficiency and emission reduction (Forman et al., 2016). Low awareness In the context of rising demand for construction, an increasing share and competition from other investments limit the feasibility of such of industrial production may be based in developing countries (N. Li et options (Napp et al., 2014). al., 2017), where current efficiencies may be lower than in developed countries, and technical and institutional feasibility may differ (Ma et 4.3.4.2 Substitution and circularity al., 2015). Recycling materials and developing a circular economy can be Except for energy efficiency, costs of disruptive change associated institutionally challenging, as it requires advanced capabilities (Henry et with hydrogen- or electricity-based production, bio-based feedstocks al., 2006) and organizational changes (Cooper-Searle et al., 2018), but and carbon dioxide capture, (utilization) and storage (CC(U)S) for has advantages in terms of cost, health, governance and environment trade-sensitive industrial sectors (in particular the iron and steel, (Ali et al., 2017). An assessment of the impacts on energy use and petrochemical and refining industries) make policy action by individual environmental issues is not available, but substitution could play a large countries challenging because of competitiveness concerns (Åhman et role in reducing emissions (Åhman et al., 2016) although its potential al., 2016; Nabernegg et al., 2017). depends on the demand for material and the turnover rate of, for example, buildings (Haas et al., 2015). Material substitution and CO 42 Table 4.3 provides an overview of applicable mitigation options for key storage options are under development, for example, the use of algae industrial sectors. and renewable energy for carbon fibre production, which could become a net sink of CO2 (Arnold et al., 2018). 4.3.4.1 Energy efficiency 4.3.4.3 Bio-based feedstocks Isolated efficiency implementation in energy-intensive industries is a necessary but insufficient condition for deep emission reductions (Napp Bio-based feedstock processes could be seen as part of the circular et al., 2014; Aden, 2018). Various options specific to different industries materials economy (see section above). In several sectors, bio-based Table 4.3 | Overview of different mitigation options potentially consistent with limiting warming to 1.5°C and applicable to main industrial sectors, including examples of application (Napp et al., 2014; Boulamanti and Moya, 2017; Wesseling et al., 2017). Refineries and Industrial mitigation option Iron/Steel Cement Chemicals Petrochemicals Process and Energy Can make a difference of between 10% and 50%, depending on the plant. Relevant but not enough for 1.5°C Efficiency Coke can be made from biomass Partial (only energy-related Bio-based Biomass can replace fossil feedstocks instead of coal emissions) More recycling and replacement by low-emission materials, Circularity & Substitution Limited potential including alternative chemistries for cement Direct reduction with hydrogen Partial (only electrified heat Electrification & Hydrogen Electrified heat and hydrogen generation Heat generation through electricity generation) Possible for process emissions and energy. Reduces Carbon dioxide capture, Can be applied to energy emissions and different stacks but not on emissions by 80–95%, and net emissions can become utilization and storage emissions of products in the use phase (e.g., gasoline) negative when combined with biofuel 335 Chapter 4 Strengthening and Implementing the Global Response feedstocks would leave the production process of materials relatively current pilot plants (Idem et al., 2015), increasing both technical and untouched, and a switch would not affect the product quality, economic potential for this option. The heterogeneity of industrial making the option more attractive. However, energy requirements production processes might point to the need for specific institutional for processing bio-based feedstocks are often high, costs are also arrangements to incentivize industrial CCS (Mikunda et al., 2014), and still higher, and the emissions over the full life cycle, both upstream may decrease institutional feasibility. and downstream, could be significant (Wesseling et al., 2017). Bio- based feedstocks may put pressure on natural resources by increasing Whether carbon dioxide utilization (CCU) can contribute to limiting land demand by biodiversity impacts beyond bioenergy demand for warming to 1.5°C depends on the origin of the CO2 (fossil, biogenic electricity, transport and buildings (Slade et al., 2014), and, partly as a or atmospheric), the source of electricity for converting the CO2 result, face barriers in public acceptance (Sleenhoff et al., 2015). or regenerating catalysts, and the lifetime of the product. Review studies indicate that CO2 utilization in industry has a small role to 4.3.4.4 Electrification and hydrogen play in limiting warming to 1.5°C because of the limited potential of reusing CO2 with currently available technologies and the re-emission Electrification of manufacturing processes would constitute a of CO2 when used as a fuel (IPCC, 2005b; Mac Dowell et al., 2017). significant technological challenge and would entail a more disruptive However, new developments could make CCU more feasible, in innovation in industry than bio-based or CCS options to get to very low particular in CO2 use as a feedstock for carbon-based materials that or zero emissions, except potentially in steel-making (Philibert, 2017). would isolate CO2 from the atmosphere for a long time, and in low- The disruptive characteristics could potentially lead to stranded assets, cost, low-emission electricity that would make the energy use of CO2 and could reduce political feasibility and industry support (Åhman capture more sustainable. The conversion of CO2 to fuels using zero- et al., 2016). Electrification of manufacturing would require further emission electricity has a lower technical, economic and environmental technological development in industry, as well as an ample supply of feasibility than direct CO2 capture and storage from industry (Abanades cost-effective low-emission electricity (Philibert, 2017). et al., 2017), although the economic prospects have improved recently (Philibert, 2017). Low-emission hydrogen can be produced by natural gas with CCS, by electrolysis of water powered by zero-emission electricity, or 4.3.5 Overarching Adaptation Options Supporting potentially in the future by generation IV nuclear reactors. Feasibility of Adaptation Transitions electrification and use of hydrogen in production processes or fuel cells is affected by technical development (in terms of efficient hydrogen This section assesses overarching adaptation options –specific solutions production and electrification of processes), by geophysical factors from which actors can choose and make decisions to reduce climate related to the availability of low-emission electricity (MacKay, 2013), vulnerability and build resilience. We examine their feasibility in by associated public perception and by economic feasibility, except the context of transitions of energy, land and ecosystem, urban and 4 in areas with ample solar and/or wind resources (Philibert, 2017; infrastructure, and industrial systems here, and further in Section 4.5. Wesseling et al., 2017). These options can contribute to creating an enabling environment for adaptation (see Table 4.4 and Section 4.4). 4.3.4.5 CO2 capture, utilization and storage in industry 4.3.5.1 Disaster risk management (DRM) CO2 capture in industry is generally considered more feasible than CCS in the power sector (Section 4.3.1) or from bioenergy sources (Section DRM is a process for designing, implementing and evaluating strategies, 4.3.7), although CCS in industry faces similar barriers. Almost all of policies and measures to improve the understanding of disaster risk, the current full-scale (>1MtCO2 yr −1) CCS projects capture CO2 from and promoting improvement in disaster preparedness, response and industrial sources, including the Sleipner project in Norway, which has recovery (IPCC, 2012). There is increased demand to integrate DRM and been injecting CO2 from a gas facility in an offshore saline formation adaptation (Howes et al., 2015; Kelman et al., 2015; Serrao-Neumann since 1996 (Global CCS Institute, 2017). Compared to the power et al., 2015; Archer, 2016; Rose, 2016; van der Keur et al., 2016; Kelman, sector, retrofitting CCS on existing industrial plants would leave the 2017; Wallace, 2017) to reduce vulnerability, but institutional, technical production process of materials relatively untouched (Åhman et al., and financial capacity challenges in frontline agencies constitute 2016), though significant investments and modifications still have to constraints (medium evidence, high agreement) (Eakin et al., 2015; Kita, be made. Some industries, in particular cement, emit CO2 as inherent 2017; Wallace, 2017). process emissions and can therefore not reduce emissions to zero without CC(U)S. CO2 stacks in some industries have a high economic 4.3.5.2 Risk sharing and spreading and technical feasibility for CO2 capture as the CO2 concentration in the exhaust gases is relatively high (IPCC, 2005b; Leeson et al., 2017), Risks associated with 1.5°C warming (Chapter 3, Section 3.4) may but others require strong modifications in the production process, increase the demand for options that share and spread financial limiting technical and economic feasibility, though costs remain burdens. Formal, market-based (re)insurance spreads risk and lower than other deep GHG reduction options (Rubin et al., 2015). provides a financial buffer against the impacts of climate hazards There are indications that the energy use in CO2 capture through (Linnerooth-Bayer and Hochrainer-Stigler, 2015; Wolfrom and Yokoi- amine solvents (for solvent regeneration) can decrease by around Arai, 2015; O’Hare et al., 2016; Glaas et al., 2017; Patel et al., 2017). 60%, from 5 GJ tCO −12 in 2005 to 2 GJ tCO −1 2 in the best-performing As an alternative to traditional indemnity-based insurance, index- 336 Strengthening and Implementing the Global Response Chapter 4 based micro-crop and livestock insurance programmes have been 4.3.5.6 Human migration rolled out in regions with less developed insurance markets (Akter et al., 2016, 2017; Jensen and Barrett, 2017). There is medium evidence Human migration, whether planned, forced or voluntary, is increasingly and medium agreement on the feasibility of insurance for adaptation, gaining attention as a response, particularly where climatic risks are with financial, social, and institutional barriers to implementation and becoming severe (Chapter 3, Section 3.4.10.2). There is medium uptake, especially in low-income nations (García Romero and Molina, evidence and low agreement as to whether migration is adaptive, 2015; Joyette et al., 2015; Lashley and Warner, 2015; Jin et al., 2016). in relation to cost effectiveness concerns (Grecequet et al., 2017) Social protection programmes include cash and in-kind transfers to and scalability (Brzoska and Fröhlich, 2016; Gemenne and Blocher, protect poor and vulnerable households from the impact of economic 2017; Grecequet et al., 2017). Migrating can have mixed outcomes shocks, natural disasters and other crises (World Bank, 2017b), and on reducing socio-economic vulnerability (Birk and Rasmussen, can build generic adaptive capacity and reduce vulnerability when 2014; Kothari, 2014; Adger et al., 2015; Betzold, 2015; Kelman, 2015; combined with a comprehensive climate risk management approach Grecequet et al., 2017; Melde et al., 2017; World Bank, 2017a; Kumari (medium evidence, medium agreement) (Devereux, 2016; Lemos et al., Rigaud et al., 2018) and its feasibility is constrained by low political 2016). and legal acceptability and inadequate institutional capacity (Betzold, 2015; Methmann and Oels, 2015; Brzoska and Fröhlich, 2016; Gemenne 4.3.5.3 Education and learning and Blocher, 2017; Grecequet et al., 2017; Yamamoto et al., 2017). Educational adaptation options motivate adaptation through building 4.3.5.7 Climate services awareness (Butler et al., 2016; Myers et al., 2017), leveraging multiple knowledge systems (Pearce et al., 2015; Janif et al., 2016), developing There is medium evidence and high agreement that climate services participatory action research and social learning processes (Butler and can play a critical role in aiding adaptation decision-making (Vaughan Adamowski, 2015; Ensor and Harvey, 2015; Butler et al., 2016; Thi and Dessai, 2014; Wood et al., 2014; Lourenço et al., 2016; Trenberth et Hong Phuong et al., 2017; Ford et al., 2018), strengthening extension al., 2016; Singh et al., 2017; Vaughan et al., 2018). The higher uptake services, and building mechanisms for learning and knowledge sharing of short-term climate information such as weather advisories and through community-based platforms, international conferences and daily forecasts contrast with lesser use of longer-term information knowledge networks (Vinke-de Kruijf and Pahl-Wostl, 2016) (medium such as seasonal forecasts and multi-decadal projections (Singh et al., evidence, high agreement). 2017; Vaughan et al., 2018). Climate service interventions have met challenges with scaling up due to low capacity, inadequate institutions, 4.3.5.4 Population health and health system adaptation options and difficulties in maintaining systems beyond pilot project stage (Sivakumar et al., 2014; Tall et al., 2014; Gebru et al., 2015; Singh et Climate change will exacerbate existing health challenges (Chapter 3, al., 2016b), and technical, institutional, design, financial and capacity Section 3.4.7). Options for enhancing current health services include barriers to the application of climate information for better decision- 4 providing access to safe water and improved sanitation, enhancing making remain (Briley et al., 2015; WMO, 2015; L. Jones et al., 2016; access to essential services such as vaccination, and developing or Lourenço et al., 2016; Snow et al., 2016; Harjanne, 2017; Singh et al., strengthening integrated surveillance systems (WHO, 2015). Combining 2017; C.J. White et al., 2017). these with iterative management can facilitate effective adaptation (medium evidence, high agreement). 4.3.5.5 Indigenous knowledge There is medium evidence and high agreement that indigenous knowledge is critical for adaptation, underpinning adaptive capacity through the diversity of indigenous agro-ecological and forest management systems, collective social memory, repository of accumulated experience and social networks (Hiwasaki et al., 2015; Pearce et al., 2015; Mapfumo et al., 2016; Sherman et al., 2016; Ingty, 2017) (Box 4.3). Indigenous knowledge is threatened by acculturation, dispossession of land rights and land grabbing, rapid environmental changes, colonization and social change, resulting in increasing vulnerability to climate change – which climate policy can exacerbate if based on limited understanding of indigenous worldviews (Thornton and Manasfi, 2010; Ford, 2012; Nakashima et al., 2012; McNamara and Prasad, 2014). Many scholars argue that recognition of indigenous rights, governance systems and laws is central to adaptation, mitigation and sustainable development (Magni, 2017; Thornton and Comberti, 2017; Pearce, 2018). 337 Chapter 4 Strengthening and Implementing the Global Response Table 4.4 | Assessment of overarching adaptation options in relation to enabling conditions. For more details, see Supplementary Material 4.SM.2. Option Enabling Conditions Examples Disaster risk Early warning systems (Anacona et al., 2015), and monitoring of dangerous lakes and Governance and institutional capacity: supports post-disaster management surrounding slopes (including using remote sensing) offer DRM opportunities recovery and reconstruction (Kelman et al., 2015; Kull et al., 2016). (DRM) (Emmer et al., 2016; Milner et al., 2017). Risk sharing Institutional capacity and finance: buffers climate risk In 2007, the Caribbean Catastrophe Risk Insurance Facility was formed to pool risk from and spreading: (Wolfrom and Yokoi-Arai, 2015; O’Hare et al., 2016; Glaas tropical cyclones, earthquakes, and excess rainfalls (Murphy et al., 2012; CCRIF, 2017). insurance et al., 2017; Jenkins et al., 2017; Patel et al., 2017). In sub-Saharan Africa, cash transfer programmes targeting poor communities have proven Institutional capacity and finance: builds generic adaptive capacity successful in smoothing household welfare and food security during droughts, strengthening Social safety nets and reduces social vulnerability (Weldegebriel and Prowse, 2013; community ties, and reducing debt levels (del Ninno et al., 2016; Asfaw et al., 2017; Eakin et al., 2014; Lemos et al., 2016; Schwan and Yu, 2017). Asfaw and Davis, 2018). Behavioural change and institutional capacity: social learning Participatory scenario planning is a process by which multiple stakeholders work together Education and strengthens adaptation and affects longer-term change (Clemens to envision future scenarios under a range of climatic conditions (Oteros-Rozas et al., learning et al., 2015; Ensor and Harvey, 2015; Henly-Shepard et al., 2015). 2015; Butler et al., 2016; Flynn et al., 2018). Heatwave early warning and response systems coordinate the implementation of multiple Institutional capacity: 1.5°C warming will primarily exacerbate Population health measures in response to predicted extreme temperatures (e.g., public announcements, existing health challenges (K.R. Smith et al., 2014), which can and health system opening public cooling shelters, distributing information on heat stress symptoms) be targeted by enhancing health services. (Knowlton et al., 2014; Takahashi et al., 2015; Nitschke et al., 2016, 2017). Institutional capacity and behavioural change: knowledge of Options such as integration of indigenous knowledge into resource management systems Indigenous environmental conditions helps communities detect and monitor and school curricula, are identified as potential adaptations (Cunsolo Willox et al., 2013; knowledge change (Johnson et al., 2015; Mistry and Berardi, 2016; McNamara and Prasad, 2014; MacDonald et al., 2015; Pearce et al., 2015; Chambers Williams et al., 2017). et al., 2017; Inamara and Thomas, 2017). Governance: revising and adopting migration issues in national In dryland India, populations in rural regions already experiencing 1.5°C warming are Human migration disaster risk management policies, National Adaptation Plans migrating to cities (Gajjar et al., 2018) but are inadequately covered by existing and NDCs (Kuruppu and Willie, 2015; Yamamoto et al., 2017). policies (Bhagat, 2017). Technological innovation: rapid technical development (due to increased financial inputs and growing demand) is improving Climate services are seeing wide application in sectors such as agriculture, health, Climate services quality of climate information provided (Rogers and Tsirkunov, disaster management and insurance (Lourenço et al., 2016; Vaughan et al., 2018), 2010; Clements et al., 2013; Perrels et al., 2013; Gasc et al., 2014; with implications for adaptation decision-making (Singh et al., 2017). WMO, 2015; Roudier et al., 2016). 4 Cross-Chapter Box 9 | Risks, Adaptation Interventions, and Implications for Sustainable Development and Equity Across Four Social-Ecological Systems: Arctic, Caribbean, Amazon, and Urban Authors: Debora Ley (Guatemala/Mexico), Malcolm E. Araos (Canada), Amir Bazaz (India), Marcos Buckeridge (Brazil), Ines Camilloni (Argentina), James Ford (UK/Canada), Bronwyn Hayward (New Zealand), Shagun Mehrotra (USA/India), Antony Payne (UK), Patricia Pinho (Brazil), Aromar Revi (India), Kevon Rhiney (Jamaica), Chandni Singh (India), William Solecki (USA), Avelino Suarez (Cuba), Michael Taylor (Jamaica), Adelle Thomas (Bahamas). This box presents four case studies from different social-ecological systems as examples of risks of 1.5°C warming and higher (Chapter 3); adaptation options that respond to these risks (Chapter 4); and their implications for poverty, livelihoods and sustainability (Chapter 5). It is not yet possible to generalize adaptation effectiveness across regions due to a lack of empirical studies and monitoring and evaluation of current efforts. Arctic The Arctic is undergoing the most rapid climate change globally (Larsen et al., 2014), warming by 1.9°C over the last 30 years (Walsh, 2014; Grosse et al., 2016). For 2°C of global warming relative to pre-industrial levels, chances of an ice-free Arctic during summer are substantially higher than at 1.5°C (see Chapter 3, Sections 3.3.5 and 3.3.8), with permafrost melt, increased instances of storm surge, and extreme weather events anticipated along with later ice freeze up, earlier break up, and a longer ice-free open water season (Bring et al., 2016; DeBeer et al., 2016; Jiang et al., 2016; Chadburn et al., 2017; Melvin et al., 2017). Negative impacts on health, infrastructure, and economic sectors (AMAP, 2017a, b, 2018) are projected, although the extension of the summer ocean- shipping season has potential economic opportunities (Ford et al., 2015b; Dawson et al., 2016; Ng et al., 2018). 338 Strengthening and Implementing the Global Response Chapter 4 Cross Chapter Box 9 (continued) Communities, many with indigenous roots, have adapted to environmental change, developing or shifting harvesting activities and patterns of travel and transitioning economic systems (Forbes et al., 2009; Wenzel, 2009; Ford et al., 2015b; Pearce et al., 2015), although emotional and psychological effects have been documented (Cunsolo Willox et al., 2012; Cunsolo and Ellis, 2018). Besides climate change (Keskitalo et al., 2011; Loring et al., 2016), economic and social conditions can constrain the capacity to adapt unless resources and cooperation are available from public and private sector actors (AMAP, 2017a, 2018) (see Chapter 5, Box 5.3). In Alaska, the cumulative economic impacts of climate change on public infrastructure are projected at 4.2 billion USD to 5.5 billion USD from 2015 to 2099, with adaptation efforts halving these estimates (Melvin et al., 2017). Marginalization, colonization, and land dispossession provide broader underlying challenges facing many communities across the circumpolar north in adapting to change (Ford et al., 2015a; Sejersen, 2015) (see Section 4.3.5). Adaptation opportunities include alterations to building codes and infrastructure design, disaster risk management, and surveillance (Ford et al., 2014a; AMAP, 2017a, b; Labbé et al., 2017). Most adaptation initiatives are currently occurring at local levels in response to both observed and projected environmental changes as well as social and economic stresses (Ford et al., 2015a). In a recent study of Canada, most adaptations were found to be in the planning stages (Labbé et al., 2017). Studies have suggested that a number of the adaptation actions are not sustainable, lack evaluation frameworks, and hold potential for maladaptation (Loboda, 2014; Ford et al., 2015a; Larsson et al., 2016). Utilizing indigenous and local knowledge and stakeholder engagement can aid the development of adaptation policies and broader sustainable development, along with more proactive and regionally coherent adaptation plans and actions, and regional cooperation (e.g., through the Arctic Council) (Larsson et al., 2016; AMAP, 2017a; Melvin et al., 2017; Forbis Jr and Hayhoe, 2018) (see Section 4.3.5). Caribbean Small Island Developing States (SIDS) and Territories Extreme weather, linked to tropical storms and hurricanes, represent one of the largest risks facing Caribbean island nations (Chapter 3, Section 3.4.5.3). Non-economic damages include detrimental health impacts, forced displacement and destruction of cultural heritages. Projections of increased frequency of the most intense storms at 1.5°C and higher warming levels (Wehner et al., 2018; Chapter 3, Section 3.3.6; Box 3.5) are a significant cause for concern, making adaptation a matter of survival (Mycoo and Donovan, 2017). Despite a shared vulnerability arising from commonalities in location, circumstance and size (Bishop and Payne, 2012; Nurse et al., 2014), adaptation approaches are nuanced by differences in climate governance, affecting vulnerability and adaptive capacity (see Section 4.4.1). Three cases exemplify differences in disaster risk management. 4 Cuba: Together with a robust physical infrastructure and human-resource base (Kirk, 2017), Cuba has implemented an effective civil defence system for emergency preparedness and disaster response, centred around community mobilization and preparedness (Kirk, 2017). Legislation to manage disasters, an efficient and robust early warning system, emergency stockpiles, adequate shelter system and continuous training and education of the population help create a ‘culture of risk’ (Isayama and Ono, 2015; Lizarralde et al., 2015) which reduces vulnerability to extreme events (Pichler and Striessnig, 2013). Cuba’s infrastructure is still susceptible to devastation, as seen in the aftermath of the 2017 hurricane season. United Kingdom Overseas Territories (UKOT): All UKOT have developed National Disaster Preparedness Plans (PAHO/WHO, 2016) and are part of the Caribbean Disaster Risk Management Program which aims to improve disaster risk management within the health sector. Different vulnerability levels across the UKOT (Lam et al., 2015) indicate the benefits of greater regional cooperation and capacity-building, not only within UKOT, but throughout the Caribbean (Forster et al., 2011). While sovereign states in the region can directly access climate funds and international support, Dependent Territories are reliant on their controlling states (Bishop and Payne, 2012). There tends to be low-scale management for environmental issues in UKOT, which increases UKOT’s vulnerability. Institutional limitations, lack of human and financial resources, and limited long-term planning are identified as barriers to adaptation (Forster et al., 2011). Jamaica: Disaster management is coordinated through a hierarchy of national, parish and community disaster committees under the leadership of the Office of Disaster Preparedness and Emergency Management (ODPEM). ODPEM coordinates disaster preparedness and risk-reduction efforts among key state and non-state agencies (Grove, 2013). A National Disaster Committee provides technical and policy oversight to the ODPEM and is composed of representatives from multiple stakeholders (Osei, 2007). Most initiatives are primarily funded through a mix of multilateral and bilateral loan and grant funding focusing on strengthening technical and institutional capacities of state- and research-based institutions and supporting integration of climate change considerations into national and sectoral development plans (Robinson, 2017). 339 Chapter 4 Strengthening and Implementing the Global Response Cross Chapter Box 9 (continued) To improve climate change governance in the region, Pittman et al. (2015) suggest incorporating holistic and integrated management systems, improving flexibility in collaborative processes, implementing monitoring programs, and increasing the capacity of local authorities. Implementation of the 2030 Sustainable Development Agenda and the Sustainable Development Goals (SDGs) can contribute to addressing the risks related with extreme events (Chapter 5, Box 5.3). The Amazon Terrestrial forests, such as the Amazon, are sensitive to changes in the climate, particularly drought (Laurance and Williamson, 2001) which might intensify through the 21st century (Marengo and Espinoza, 2016) (Chapter 3, Section 3.5.5.6). The poorest communities in the region face substantial risks with climate change, and barriers and limits to adaptive capacity (Maru et al., 2014; Pinho et al., 2014, 2015; Brondízio et al., 2016). The Amazon is considered a hotspot, with interconnections between increasing temperature, decreased precipitation and hydrological flow (Betts et al., 2018) (Sections 3.3.2.2, 3.3.3.2 and 3.3.5); low levels of socio-economic development (Pinho et al., 2014); and high levels of climate vulnerability (Darela et al., 2016). Limiting global warming to 1.5°C could increase food and water security in the region compared to 2°C (Betts et al., 2018), reduce the impact on poor people and sustainable development, and make adaptation easier (O’Neill et al., 2017), particularly in the Amazon (Bathiany et al., 2018) (Chapter 5, Section 5.2.2). Climate policy in many Amazonian nations has focused on forests as carbon sinks (Soares-Filho et al., 2010). In 2009, the Brazilian National Policy on Climate Change acknowledged adaptation as a concern, and the government sought to mainstream adaptation into public administration. Brazil’s National Adaptation Plan sets guidelines for sectoral adaptation measures, primarily by developing capacity building, plans, assessments and tools to support adaptive decision-making. Adaptation is increasingly being presented as having mitigation co-benefits in the Brazilian Amazon (Gregorio et al., 2016), especially within ecosystem-based adaptation (Locatelli et al., 2011). In Peru’s Framework Law for Climate Change, every governmental sector will consider climatic conditions as potential risks and/or opportunities to promote economic development and to plan adaptation. Drought and flood policies have had limited effectiveness in reducing vulnerability (Marengo et al., 2013). In the absence of effective adaptation, achieving the SDGs will be challenging, mainly in poverty, health, water and sanitation, inequality and gender equality (Chapter 5, Section 5.2.3). 4 Urban systems Around 360 million people reside in urban coastal areas where precipitation variability is exposing inadequacies of urban infrastructure and governance, with the poor being especially vulnerable (Reckien et al., 2017) (Cross-Chapter Box 13 in Chapter 5). Urban systems have seen growing adaptation action (Revi et al., 2014b; Araos et al., 2016b; Amundsen et al., 2018). Developing cities spend more on health and agriculture-related adaptation options while developed cities spend more on energy and water (Georgeson et al., 2016). Current adaptation activities are lagging in emerging economies, which are major centres of population growth facing complex interrelated pressures on investment in health, housing and education (Georgeson et al., 2016; Reckien et al., 2017). New York, United States: Adaptation plans are undertaken across government levels, sectors and departments (NYC Parks, 2010; Vision 2020 Project Team, 2011; PlaNYC, 2013), and have been advanced by an expert science panel that is obligated by local city law to provide regular updates on policy-relevant climate science (NPCC, 2015). Federal initiatives include 2013’s Rebuild By Design competition to promote resilience through infrastructural projects (HSRTF, 2013). In 2013 the Mayor’s office, in response to Hurricane Sandy, published the city’s adaptation strategy (PlaNYC, 2013). In 2015, the OneNYC Plan for a Strong and Just City (OneNYC Team, 2015) laid out a strategy for urban planning through a justice and equity lens. In 2017, new climate resiliency guidelines proposed that new construction must include sea level rise projections into planning and development (ORR, 2018). Although this attention to climate-resilient development may help reduce income inequality, its full effect could be constrained if a policy focus on resilience obscures analysis of income redistribution for the poor (Fainstein, 2018). Kampala, Uganda: Kampala Capital City Authority (KCCA) has the statutory responsibility for managing the city. The Kampala Climate Change Action Strategy (KCCAS) is responding to climatic impacts of elevated temperature and more intense, erratic rain. KCCAS has considered multi-scale and temporal aspects of response (Chelleri et al., 2015; Douglas, 2017; Fraser et al., 2017), strengthened community adaptation (Lwasa, 2010; Dobson, 2017), responded to differential adaptive capacities (Waters and Adger, 2017) and believes in participatory processes and bridging of citywide linkages (KCCA, 2016). Analysis of the implications of uniquely adapted local solutions (e.g., motorcycle taxis) suggests sustainability can be enhanced when planning recognizes the need to adapt to uniquely local solutions (Evans et al., 2018). 340 Strengthening and Implementing the Global Response Chapter 4 Cross Chapter Box 9 (continued) Rotterdam, The Netherlands: The Rotterdam Climate Initiative (RCI) was launched to reduce greenhouse gas emissions and climate-proof Rotterdam (RCI, 2017). Rotterdam has an integrated adaptation strategy, built on flood management, accessibility, adaptive building, urban water systems and urban climate, defined through the Rotterdam Climate Proof programme and the Rotterdam Climate Change Adaptation Strategy (RCI, 2008, 2013). Governance mechanisms that enabled integration of flood risk management plans with other policies, citizen participation, institutional eco-innovation, and focusing on green infrastructure (Albers et al., 2015; Dircke and Molenaar, 2015; de Boer et al., 2016a; Huang-Lachmann and Lovett, 2016) have contributed to effective adaptation (Ward et al., 2013). Entrenched institutional characteristics constrain the response framework (Francesch- Huidobro et al., 2017), but emerging evidence suggests that new governance arrangements and structures can potentially overcome these barriers in Rotterdam (Hölscher et al., 2018). 4.3.6 Short-Lived Climate Forcers poorest populations who still rely on biomass fuels, as this affects the reference level of BC emissions (Rogelj et al., 2014). The main short-lived climate forcer (SLCF) emissions that cause warming are methane (CH4), other precursors of tropospheric ozone Some studies have evaluated the focus on SLCFs in mitigation strategies (i.e., carbon monoxide (CO), non-methane volatile organic compounds and point towards trade-offs between short-term SLCF benefits (NMVOC), black carbon (BC) and hydrofluorocarbons (HFCs); Myhre et and lock-in of long-term CO2 warming (Smith and Mizrahi, 2013; al., 2013). SLCFs also include emissions that lead to cooling, such as Pierrehumbert, 2014). Reducing fossil fuel combustion will reduce sulphur dioxide (SO2) and organic carbon (OC). Nitrogen oxides (NOx) aerosols levels, and thereby cause warming from removal of aerosol can have both warming and cooling effects, by affecting ozone (O3) cooling effects (Myhre et al., 2013; Xu and Ramanathan, 2017; Samset and CH4, depending on time scale and location (Myhre et al., 2013). et al., 2018). While some studies have found a lower temperature effect from BC mitigation, thus questioning the effectiveness of targeted BC Cross-Chapter Box 2 in Chapter 1 provides a discussion of role of mitigation for climate change mitigation (Myhre et al., 2013; Baker et SLCFs in comparison to long-lived GHGs. Chapter 2 shows that al., 2015; Stjern et al., 2017; Samset et al., 2018), other models and 1.5°C-consistent pathways require stringent reductions in CO2 and observationally constrained estimates suggest that these widely-used CH4, and that non-CO2 climate forcers reduce carbon budgets by models do not fully capture observed effects of BC and co-emissions about 2200 GtCO2 per degree of warming attributed to them (see the on climate (e.g., Bond et al., 2013; Cui et al., 2016; Peng et al., 2016). Supplementary Material to Chapter 2). Table 4.5 provides an overview of three warming SLCFs and their 4 Reducing non-CO2 emissions is part of most mitigation pathways emission sources, with examples of options for emission reductions (IPCC, 2014c). All current GHG emissions and other forcing agents and associated co-benefits. affect the rate and magnitude of climate change over the next few decades, while long-term warming is mainly driven by CO2 emissions. A wide range of options to reduce SLCF emissions was extensively CO2 emissions result in a virtually permanent warming, while discussed in AR5 (IPCC, 2014b). Fossil fuel and waste sector methane temperature change from SLCFs disappears within decades after mitigation options have high cost-effectiveness, producing a net profit emissions of SLCFs are ceased. Any scenario that fails to reduce CO2 over a few years, considering market costs only. Moreover, reducing emissions to net zero would not limit global warming, even if SLCFs are roughly one-third to one-half of all human-caused emissions has reduced, due to accumulating CO2-induced warming that overwhelms societal benefits greater than mitigation costs when considering SLCFs’ mitigation benefits in a couple of decades (Shindell et al., 2012; environmental impacts only (UNEP, 2011; Höglund-Isaksson, 2012; IEA, Schmale et al., 2014) (and see Chapter 2, Section 2.3.3.2). 2017b; Shindell et al., 2017a). Since AR5, new options for methane, such as those related to shale gas, have been included in mitigation Mitigation options for warming SLCFs often overlap with other portfolios (e.g., Shindell et al., 2017a). mitigation options, especially since many warming SLCFs are co-emitted with CO2. SLCFs are generally mitigated in 1.5°C- or Reducing BC emissions and co-emissions has sustainable development 2°C-consistent pathways as an integral part of an overall mitigation co-benefits, especially around human health (Stohl et al., 2015; strategy (Chapter 2). For example, Section 2.3 indicates that most very- Haines et al., 2017; Aakre et al., 2018), avoiding premature deaths low-emissions pathways include a transition away from the use of coal and increasing crop yields (Scovronick et al., 2015; Peng et al., 2016). and natural gas in the energy sector and oil in transportation, which Additional benefits include lower likelihood of non-linear climate coincides with emission-reduction strategies related to methane from changes and feedbacks (Shindell et al., 2017b) and temporarily slowing the fossil fuel sector and BC from the transportation sector. Much SLCF down the rate of sea level rise (Hu et al., 2013). Interventions to reduce emission reduction aims at BC-rich sectors and considers the impacts BC offer tangible local air quality benefits, increasing the likelihood of of several co-emitted SLCFs (Bond et al., 2013; Sand et al., 2015; Stohl local public support (Eliasson, 2014; Venkataraman et al., 2016) (see et al., 2015). The benefits of such strategies depend greatly upon the Chapter 5, Section 5.4.2.1). Limited interagency co-ordination, poor assumed level of progression of access to modern energy for the science-policy interactions (Zusman et al., 2015), and weak policy and 341 Chapter 4 Strengthening and Implementing the Global Response Table 4.5 | Overview of main characteristics of three warming short-lived climate forcers (SLCFs) (core information based on Pierrehumbert, 2014 and Schmale et al., 2014; rest of the details as referenced). Examples of Options Examples of Co-Benefits SLCF Atmospheric Annual Global Main Anthropogenic to Reduce Emissions Based on Haines et al. (2017) Compound Lifetime Emission Emission Sources Consistent with 1.5°C Unless Specified Otherwise Managing manure from livestock; Fossil fuel extraction and Reduction of tropospheric ozone Intermittent irrigation of rice; transportation; (Shindell et al., 2017a); On the order 0.3 GtCH4 (2010) Capture and usage of fugitive Methane Land-use change; Health benefits of dietary changes; of 10 years (Pierrehumbert, 2014) methane; Livestock and rice cultivation; Increased crop yields; Dietary change; Waste and wastewater Improved access to drinking water For more: see Section 4.3.2 Alternatives to HFCs in Months to decades, 0.35 GtCO2-eq (2010) Air conditioning; Refrigeration; Greater energy efficiency HFCs air-conditioning and refrigeration depending on the gas (Velders et al., 2015) Construction material (Mota-Babiloni et al., 2017) applications Fewer and cleaner vehicles; Reducing Incomplete combustion of fossil agricultural biomass burning; Health benefits of better air quality; fuels or biomass in vehicles (esp. Cleaner cook stoves, gas-based Increased education opportunities; ~7 Mt (2010) Black Carbon Days diesel), cook stoves or kerosene or electric cooking; Reduced coal consumption for modern (Klimont et al., 2017) lamps; Replacing brick and coke ovens; brick kilns; Field and biomass burning Solar lamps; Reduced deforestation For more see Section 4.3.3 absence of inspections and enforcement (Kholod and Evans, 2016) are the absence of international frameworks for integrating SLCFs into among barriers that reduce the institutional feasibility of options to emissions accounting and reporting mechanisms being a barrier to reduce vehicle-induced BC emissions. A case study for India shows that developing policies for addressing SLCF emissions (Venkataraman et switching from biomass cook stoves to cleaner gas stoves (based on al., 2016). The incentives for reducing SLCFs are particularly strong for liquefied petroleum gas or natural gas) or to electric cooking stoves is small groups of countries, and such collaborations could increase the technically and economically feasible in most areas, but faces barriers feasibility and effectiveness of SLCF mitigation options (Aakre et al., in user preferences, costs and the organization of supply chains 2018). (Jeuland et al., 2015). Similar feasibility considerations emerge in switching from kerosene wick lamps for lighting to solar lanterns, from 4.3.7 Carbon Dioxide Removal (CDR) current low-efficiency brick kilns and coke ovens to cleaner production 4 technologies; and from field burning of crop residues to agricultural CDR methods refer to a set of techniques for removing CO2 from the practices using deep-sowing and mulching technologies (Williams et atmosphere. In the context of 1.5°C-consistent pathways (Chapter 2), al., 2011; Wong, 2012). they serve to offset residual emissions and, in most cases, achieve net negative emissions to return to 1.5°C from an overshoot. See Cross- The radiative forcing from HFCs are currently small but have been Chapter Box 7 in Chapter 3 for a synthesis of land-based CDR options. growing rapidly (Myhre et al., 2013). The Kigali Amendment (from Cross-cutting issues and uncertainties are summarized in Table 4.6. 2016) to the Montreal Protocol set out a global accord for phasing out these compounds (Höglund-Isaksson et al., 2017). HFC mitigation 4.3.7.1 Bioenergy with carbon capture and storage (BECCS) options include alternatives with reduced warming effects, ideally combined with improved energy efficiency so as to simultaneously BECCS has been assessed in previous IPCC reports (IPCC, 2005b, reduce CO2 and co-emissions (Shah et al., 2015). Costs for most 2014b; P. Smith et al., 2014; Minx et al., 2017) and has been of HFC’s mitigation potential are estimated to be below USD2010 incorporated into integrated assessment models (Clarke et al., 2014), 60 tCO2-eq −1, and the remainder below roughly double that number but also 1.5°C-consistent pathways without BECCS have emerged (Höglund-Isaksson et al., 2017). (Bauer et al., 2018; Grubler et al., 2018; Mousavi and Blesl, 2018; van Vuuren et al., 2018). Still, the overall set of pathways limiting global Reductions in SLCFs can provide large benefits towards sustainable warming to 1.5°C with limited or no overshoot indicates that 0–1, 0–8, development, beneficial for social, institutional and economic and 0–16 GtCO −12 yr would be removed by BECCS by 2030, 2050 and feasibility. Strategies that reduce SLCFs can provide benefits that 2100, respectively (Chapter 2, Section 2.3.4). BECCS is constrained by include improved air quality (e.g., Anenberg et al., 2012) and crop yields sustainable bioenergy potentials (Section 4.3.1.2, Chapter 5, Section (e.g., Shindell et al., 2012), energy access, gender equality and poverty 5.4.1.3 and Cross-Chapter Box 6 in Chapter 3), and availability of eradication (e.g.,Shindell et al., 2012; Haines et al., 2017). Institutional safe storage for CO2 (Section 4.3.1.6). Literature estimates for BECCS feasibility can be negatively affected by an information deficit, with mitigation potentials in 2050 range from 1–85 GtCO 42 . Fuss et al. 4 As more bottom-up literature exists on bioenergy potentials, this exercise explored the bioenergy literature and converted those estimates to BECCS potential with 1EJ of bioenergy yielding 0.02–0.05 GtCO2 emission reduction. For the bottom-up literature references for the potentials range, please refer to Supplementary Material 4.SM.3 Table 1. 342 Strengthening and Implementing the Global Response Chapter 4 (2018) narrow this range to 0.5–5 GtCO2 yr −1 (medium agreement, both bioenergy and CCS (Section 4.3.1). Current pathways are believed high evidence) (Figure 4.3), meaning that BECCS mitigation potentials to have inadequate assumptions on the development of societal are not necessarily sufficient for 1.5°C-consistent pathways. This is, support and governance structures (Vaughan and Gough, 2016). among other things, related to sustainability concerns (Boysen et al., However, removing BECCS and CCS from the portfolio of available 2017; Heck et al., 2018; Henry et al., 2018). options significantly raises modelled mitigation costs (Kriegler et al., 2013; Bauer et al., 2018). Assessing BECCS deployment in 2°C pathways (of about 12 GtCO2-eq yr −1 by 2100, considered as a conservative deployment 4.3.7.2 Afforestation and reforestation (AR) estimate for BECCS-accepting pathways consistent with 1.5°C), Smith et al. (2016b) estimate a land-use intensity of 0.3–0.5 ha tCO2-eq −1 yr−1 Afforestation implies planting trees on land not forested for a long using forest residues, 0.16 ha CO -eq−1 −12 yr for agricultural residues, time (e.g., over the last 50 years in the context of the Kyoto Protocol), and 0.03–0.1 ha tCO −1 −12-eq yr for purpose-grown energy crops. The while reforestation implies re-establishment of forest formations after average amount of BECCS in these pathways requires 25–46% of a temporary condition with less than 10% canopy cover due to human- arable and permanent crop area in 2100. Land area estimates differ induced or natural perturbations. Houghton et al. (2015) estimate in scale and are not necessarily a good indicator of competition with, about 500 Mha could be available for the re-establishment of forests for example, food production, because requiring a smaller land area for on lands previously forested, but not currently used productively. This the same potential could indicate that high-productivity agricultural could sequester at least 3.7 GtCO −12 yr for decades. The full literature land is used. In general, the literature shows low agreement on the range gives 2050 potentials of 1–7 GtCO2 yr −1 (low evidence, medium availability of land (Fritz et al., 2011; see Erb et al., 2016b for recent agreement), narrowed down to 0.5–3.6 GtCO yr−12 based on a number advances). Productivity, food production and competition with other of constraints (Fuss et al., 2018). Abatement costs are estimated to ecosystem services and land use by local communities are important be low compared to other CDR options, 5–50 USD tCO2-eq −1 (robust factors for designing regulation. These potentials and trade-offs are not evidence, high agreement). Yet, realizing such large potentials comes homogenously distributed across regions. However, Robledo-Abad et at higher land and water footprints than BECCS, although there would al. (2017) find that regions with higher potentials are understudied, be a positive impact on nutrients and the energy requirement would given their potential contribution. Researchers have expressed the be negligible (Smith et al., 2016b; Cross-Chapter Box 7 in Chapter 3). need to complement global assessments with regional, geographically The 2030 estimate by Griscom et al. (2017) is up to 17.9 GtCO yr−12 explicit bottom-up studies of biomass potentials and socio-economic for reforestation with significant co-benefits (Cross-Chapter Box 7 in impacts (e.g., de Wit and Faaij, 2010; Kraxner et al., 2014; Baik et al., Chapter 3). 2018). Biogenic storage is not as permanent as emission reductions by Energy production and land and water footprints show wide ranges geological storage. In addition, forest sinks saturate, a process which in bottom-up assessments due to differences in technology, feedstock typically occurs in decades to centuries compared to the thousands 4 and other parameters (−1–150 EJ yr−1 of energy, 109–990 Mha, 6–79 of years of residence time of CO2 stored geologically (Smith et al., MtN, 218–4758 km3 yr−1 of water per GtCO yr−12 ; Smith and Torn, 2016a) and is subject to disturbances that can be exacerbated by 2013; Smith et al., 2016b; Fajardy and Mac Dowell, 2017) and are not climate change (e.g., drought, forest fires and pests) (Seidl et al., 2017). comparable to IAM pathways which consider system effects (Bauer Handling these challenges requires careful forest management. There et al., 2018). Global impacts on nutrients and albedo are difficult to is much practical experience with AR, facilitating upscaling but with quantify (Smith et al., 2016b). BECCS competes with other land-based two caveats: AR potentials are heterogeneously distributed (Bala et al., CDR and mitigation measures for resources (Chapter 2). 2007), partly because the planting of less reflective forests results in higher net absorbed radiation and localised surface warming in higher There is uncertainty about the feasibility of timely upscaling (Nemet et latitudes (Bright et al., 2015; Jones et al., 2015), and forest governance al., 2018). CCS (see Section 4.3.1) is largely absent from the Nationally structures and monitoring capacities can be bottlenecks and are Determined Contributions (Spencer et al., 2015) and lowly ranked in usually not considered in models (Wang et al., 2016; Wehkamp et al., investment priorities (Fridahl, 2017). Although there are dozens of small- 2018b). There is medium agreement on the positive impacts of AR on scale BECCS demonstrations (Kemper, 2015) and a full-scale project ecosystems and biodiversity due to different forms of afforestation capturing 1 MtCO2 exists (Finley, 2014), this is well below the numbers discussed in the literature: afforestation of grassland ecosystems or associated with 1.5°C or 2°C-compatible pathways (IEA, 2016a; diversified agricultural landscapes with monocultures or invasive alien Peters et al., 2017). Although the majority of BECCS cost estimates are species can have significant negative impacts on biodiversity, water below 200 USD tCO −12 (Figure 4.2), estimates vary widely. Economic resources, etc. (P. Smith et al., 2014), while forest ecosystem restoration incentives for ramping up large CCS or BECCS infrastructure are weak (forestry and agroforestry) with native species can have positive social (Bhave et al., 2017). The 2050 average investment costs for such a and environmental impacts (Cunningham et al., 2015; Locatelli et al., BECCS infrastructure for bio-electricity and biofuels are estimated at 2015; Paul et al., 2016; See Section 4.3.2). 138 and 123 billion USD yr−1, respectively (Smith et al., 2016b). Synergies with other policy goals are possible (see also Section 4.5.4); BECCS deployment is further constrained by bioenergy’s carbon for example, land spared by diet shifts could be afforested (Röös et al., accounting, land, water and nutrient requirements (Section 4.3.1), its 2017) or used for energy crops (Grubler et al., 2018). Such land-sparing compatibility with other policy goals and limited public acceptance of strategies could also benefit other land-based CDR options. 343 Chapter 4 Strengthening and Implementing the Global Response 4 Figure 4.2 | Evidence on carbon dioxide removal (CDR) abatement costs, 2050 deployment potentials, and key side effects. Panel A presents estimates based on a systematic review of the bottom up literature (Fuss et al., 2018), corresponding to dashed blue boxes in Panel B. Dashed lines represent saturation limits for the corresponding technology. Panel B shows the percentage of papers at a given cost or potential estimate. Reference year for all potential estimates is 2050, while all cost estimates preceding 2050 have been included (as early as 2030, older estimates are excluded if they lack a base year and thus cannot be made comparable). Ranges have been trimmed to show detail (see Fuss et al., 2018 for the full range). Costs refer only to abatement costs. Icons for side-effects are allocated only if a critical mass of papers corroborates their occurrence Notes: For references please see Supplementary Material Table 4.SM.3. Direct air carbon dioxide capture and storage (DACCS) is theoretically only constrained by geological storage capacity, estimates presented are considering upscaling and cost challenges (Nemet et al., 2018). BECCS potential estimates are based on bioenergy estimates in the literature (EJ yr−1), converted to GtCO2 following footnote 4. Potentials cannot be added up, as CDR options would compete for resources (e.g., land). SCS - soil carbon sequestration; OA - ocean alkalinization; EW- enhanced weathering; DACCS - direct air carbon dioxide capture and storage; BECCS - bioenergy with carbon capture and storage; AR - afforestation. 344 Strengthening and Implementing the Global Response Chapter 4 4.3.7.3 Soil carbon sequestration and biochar 4.3.7.4 Enhanced weathering (EW) and ocean alkalinization At local scales there is robust evidence that soil carbon sequestration Weathering is the natural process of rock decomposition via chemical (SCS, e.g., agroforestry, De Stefano and Jacobson, 2018), restoration and physical processes in which CO2 is spontaneously consumed and of degraded land (Griscom et al., 2017), or conservation agriculture converted to solid or dissolved alkaline bicarbonates and/or carbonates management practices (Aguilera et al., 2013; Poeplau and Don, 2015; (IPCC, 2005a). The process is controlled by temperature, reactive Vicente-Vicente et al., 2016) have co-benefits in agriculture and that surface area, interactions with biota and, in particular, water solution many measures are cost-effective even without supportive climate composition. CDR can be achieved by accelerating mineral weathering policy. Evidence at global scale for potentials and especially costs is through the distribution of ground-up rock material over land much lower. The literature spans cost ranges of −45–100 USD tCO −12 (Hartmann and Kempe, 2008; Wilson et al., 2009; Köhler et al., 2010; (negative costs relating to the multiple co-benefits of SCS, such as Renforth, 2012; ten Berge et al., 2012; Manning and Renforth, 2013; increased productivity and resilience of soils; P. Smith et al., 2014), Taylor et al., 2016), shorelines (Hangx and Spiers, 2009; Montserrat et and 2050 potentials are estimated at between 0.5 and 11 GtCO −12 yr , al., 2017) or the open ocean (House et al., 2007; Harvey, 2008; Köhler narrowed down to 2.3–5.3 GtCO −12 yr considering that studies above et al., 2013; Hauck et al., 2016). Ocean alkalinization adds alkalinity to 5 GtCO yr−12 often do not apply constraints, while estimates lower than marine areas to locally increase the CO2 buffering capacity of the ocean 2 GtCO −12 yr mostly focus on single practices (Fuss et al., 2018). (González and Ilyina, 2016; Renforth and Henderson, 2017). SCS has negligible water and energy requirements (Smith, 2016), In the case of land application of ground minerals, the estimated CDR affects nutrients and food security favourably (high agreement, robust potential range is 0.72–95 GtCO yr−12 (low evidence, low agreement) evidence) and can be applied without changing current land use, thus (Hartmann and Kempe, 2008; Köhler et al., 2010; Hartmann et al., making it socially more acceptable than CDR options with a high land 2013; Taylor et al., 2016; Strefler et al., 2018a). Marine application footprint. However, soil sinks saturate after 10–100 years, depending of ground minerals is limited by feasible rates of mineral extraction, on the SCS option, soil type and climate zone (Smith, 2016). grinding and delivery, with estimates of 1–6 GtCO −12 yr (low evidence, low agreement) (Köhler et al., 2013; Hauck et al., 2016; Renforth and Biochar is formed by recalcitrant (i.e., very stable) organic carbon Henderson, 2017). Agreement is low due to a variety of assumptions obtained from pyrolysis, which, applied to soil, can increase soil carbon and unknown parameter ranges in the applied modelling procedures sequestration leading to improved soil fertility properties.5 Looking at that would need to be verified by field experiments (Fuss et al., 2018). the full literature range, the global potential in 2050 lies between 1 As with other CDR options, scaling and maturity are challenges, with and 35 Gt CO2 yr −1 (low agreement, low evidence), but considering deployment at scale potentially requiring decades (NRC, 2015a), limitations in biomass availability and uncertainties due to a lack of considerable costs in transport and disposal (Hangx and Spiers, 2009; large-scale trials of biochar application to agricultural soils under field Strefler et al., 2018a) and mining (NRC, 2015a; Strefler et al., 2018a)6. conditions, Fuss et al. (2018) lower the 2050 range to 0.3–2 GtCO yr−1. 42 This potential is below previous estimates (e.g., Woolf et al., 2010), Site-specific cost estimates vary depending on the chosen technology which additionally consider the displacement of fossil fuels through for rock grinding (an energy-intensive process; Köhler et al., 2013; biochar. Permanence depends on soil type and biochar production Hauck et al., 2016), material transport, and rock source (Renforth, temperatures, varying between a few decades and several centuries 2012; Hartmann et al., 2013), and range from 15–40 USD tCO −12 to (Fang et al., 2014). Costs are 30– 120 USD tCO −12 (medium agreement, 3,460 USD tCO −1 2 (limited evidence, low agreement; Figure 4.2) medium evidence) (McCarl et al., 2009; McGlashan et al., 2012; (Schuiling and Krijgsman, 2006; Köhler et al., 2010; Taylor et al., McLaren, 2012; Smith, 2016). 2016). The evidence base for costs of ocean alkalinization and marine enhanced weathering is sparser than the land applications. The ocean Water requirements are low and at full theoretical deployment, up alkalinization potential is assessed to be 0.1–10 GtCO −12 yr with costs to 65 EJ yr−1 of energy could be generated as a side product (Smith, of 14– >500 USD tCO −12 (Renforth and Henderson, 2017). 2016). Positive side effects include a favourable effect on nutrients and reduced N2O emissions (Cayuela et al., 2014; Kammann et al., 2017). The main side effects of terrestrial EW are an increase in water pH However, 40–260 Mha are needed to grow the biomass for biochar (Taylor et al., 2016), the release of heavy metals like Ni and Cr and plant for implementation at 0.3 GtCO −12-eq yr (Smith, 2016), even though nutrients like K, Ca, Mg, P and Si (Hartmann et al., 2013), and changes in it is also possible to use residues (e.g., Windeatt et al., 2014). Biochar hydrological soil properties. Respirable particle sizes, though resulting in is further constrained by the maximum safe holding capacity of soils higher potentials, can have impacts on health (Schuiling and Krijgsman, (Lenton, 2010) and the labile nature of carbon sequestrated in plants 2006; Taylor et al., 2016); utilization of wave-assisted decomposition and soil at higher temperatures (Wang et al., 2013). through deployment on coasts could avert the need for fine grinding (Hangx and Spiers, 2009; Schuiling and de Boer, 2010). Side effects 5 Other pyrolysis products that can achieve net CO2 removals are bio-oil (pumped into geological storages) and permanent-pyrogas (capture and storage of CO2 from gas combustion) (Werner et al., 2018) 6 It has also been suggested that ocean alkalinity can be increased through accelerated weathering of limestone (Rau and Caldeira, 1999; Rau, 2011; Chou et al., 2015) or electrochemical processes (House et al., 2007; Rau, 2008; Rau et al., 2013; Lu et al., 2015). However, these techniques have not been proven at large scale either (Renforth and Henderson, 2017). 345 Chapter 4 Strengthening and Implementing the Global Response of marine EW and ocean alkalinization are the potential release of et al., 2016), deploying the technology at scale is still a considerable heavy metals like Ni and Cr (Montserrat et al., 2017). Increasing ocean challenge, though both optimistic (Lackner et al., 2012) and pessimistic alkalinity helps counter ocean acidification (Albright et al., 2016; Feng outlooks exist (Pritchard et al., 2015). et al., 2016). Ocean alkalinization could affect ocean biogeochemical functioning (González and Ilyina, 2016). A further caveat of relates to 4.3.7.6 Ocean fertilization saturation state and the potential to trigger spontaneous carbonate precipitation.7 While the geochemical potential to remove and store Nutrients can be added to the ocean resulting in increased biologic CO2 is quite large, limited evidence on the preceding topics makes it production, leading to carbon fixation in the sunlit ocean and difficult to assess the true capacity, net benefits and desirability of EW subsequent sequestration in the deep ocean or sea floor sediments. and ocean alkalinity addition in the context of CDR. The added nutrients can be either micronutrients (such as iron) or macronutrients (such as nitrogen and/or phosphorous) (Harrison, 4.3.7.5 Direct air carbon dioxide capture and storage (DACCS) 2017). There is limited evidence and low agreement on the readiness of this technology to contribute to rapid decarbonization (Williamson et Capturing CO2 from ambient air through chemical processes with al., 2012). Only small-scale field experiments and theoretical modelling subsequent storage of the CO2 in geological formations is independent have been conducted (e.g., McLaren, 2012). The full range of CDR of source and timing of emissions and can avoid competition for land. potential estimates is from 15.2 ktCO yr−12 (Bakker et al., 2001) for a Yet, this is also the main challenge: while the theoretical potential spatially constrained field experiment up to 44 GtCO2 yr −1 (Sarmiento for DACCS is mainly limited by the availability of safe and accessible and Orr, 1991) following a modelling approach, but Fuss et al. (2018) geological storage, the CO2 concentration in ambient air is 100–300 consider the potential to be extremely limited given the evidence and times lower than at gas- or coal-fired power plants (Sanz-Pérez et al., existing barriers. Due to scavenging of iron, the iron addition only leads 2016) thus requiring more energy than flue gas CO2 capture (Pritchard to inefficient use of the nitrogen in exporting carbon (Zeebe, 2005; et al., 2015). This appears to be the main challenge to DACCS (Sanz- Aumont and Bopp, 2006; Zahariev et al., 2008). Pérez et al., 2016; Barkakaty et al., 2017). Cost estimates range from 2 USD tCO −12 (for iron fertilization) (Boyd Studies explore alternative techniques to reduce the energy penalty and Denman, 2008) to 457 USD tCO −12 (Harrison, 2013). Jones (2014) of DACCS (van der Giesen et al., 2017). Energy consumption could be proposed values greater than 20 USD tCO −12 for nitrogen fertilization. up to 12.9 GJ tCO2-eq −1; translating into an average of 156 EJ yr−1 by Fertilization is expected to impact food webs by stimulating its base 2100 (current annual global primary energy supply is 600 EJ); water organisms (Matear, 2004), and extensive algal blooms may cause requirements are estimated to average 0.8–24.8 km3 GtCO -eq−1 yr−12 anoxia (Sarmiento and Orr, 1991; Matear, 2004; Russell et al., 2012) (Smith et al., 2016b, based on Socolow et al., 2011). and deep water oxygen decline (Matear, 2004), with negative impacts on biodiversity. Nutrient inputs can shift ecosystem production from 4 However, the literature shows low agreement and is fragmented an iron-limited system to a P, N-, or Si-limited system depending on (Broehm et al., 2015). This fragmentation is reflected in a large range the location (Matear, 2004; Bertram, 2010) and non-CO2 GHGs may of cost estimates: from 20–1,000 USD tCO −12 (Keith et al., 2006; Pielke, increase (Sarmiento and Orr, 1991; Matear, 2004; Bertram, 2010). The 2009; House et al., 2011; Ranjan and Herzog, 2011; Simon et al., 2011; greatest theoretical potential for this practice is the Southern Ocean, Goeppert et al., 2012; Holmes and Keith, 2012; Zeman, 2014; Sanz- posing challenges for monitoring and governance (Robinson et al., Pérez et al., 2016; Sinha et al., 2017). There is lower agreement and a 2014). The London Protocol of the International Maritime Organization smaller evidence base at the lower end of the cost range. Fuss et al. has asserted authority for regulation of ocean fertilization (Strong et al., (2018) narrow this range to 100–300 USD tCO -12 . 2009), which is widely viewed as a de facto moratorium on commercial ocean fertilization activities. Research and efforts by small-scale commercialization projects focus on utilization of captured CO2 (Wilcox et al., 2017). Given that only There is low agreement in the technical literature on the permanence a few IAM scenarios incorporate DACCS (e.g., Chen and Tavoni, of CO2 in the ocean, with estimated residence times of 1,600 years 2013; Strefler et al., 2018b) its possible role in cost-optimized 1.5°C to millennia, especially if injected or buried in or below the sea floor scenarios is not yet fully explored. Given the technology’s early stage (Williams and Druffel, 1987; Jones, 2014). Storage at the surface would of development (McLaren, 2012; NRC, 2015a; Nemet et al., 2018) mean that the carbon would be rapidly released after cessation (Zeebe, and few demonstrations (Holmes et al., 2013; Rau et al., 2013; Agee 2005; Aumont and Bopp, 2006). 7 This analysis relies on the assessment in Fuss et al. (2018), which provides more detail on saturation and permanence. 346 Strengthening and Implementing the Global Response Chapter 4 Table 4.6 | Cross-cutting issues and uncertainties across carbon dioxide removal (CDR) options, aspects and uncertainties Area of Uncertainty Cross-Cutting Issues and Uncertainties • CDR options are at different stages of technological readiness (McLaren, 2012) and differ with respect to scalability. • Nemet et al. (2018) find >50% of the CDR innovation literature concerned with the earliest stages of the innovation process (R&D), identifying a Technology upscaling dissonance between the large CO2 removals needed in 1.5°C pathways and the long -time periods involved in scaling up novel technologies. • Lack of post-R&D literature, including incentives for early deployment, niche markets, scale up, demand, and public acceptance. • For BECCS, there are niche opportunities with high efficiencies and fewer trade-offs, for example, sugar and paper processing facilities (Möllersten et al., 2003), district heating (Kärki et al., 2013; Ericsson and Werner, 2016), and industrial and municipal waste (Sanna et al., 2012). Turner et al. (2018) constrain potential using sustainability considerations and overlap with storage basins to avoid the CO2 transportation challenge, providing a possible, though limited entry point for BECCS. • The impacts on land use, water, nutrients and albedo of BECCS could be alleviated using marine sources of biomass that could include aquacultured micro and macro flora (Hughes et al., 2012; Lenton, 2014). Emerging and niche • Regarding captured CO2 as a resource is discussed as an entry point for CDR. However, this does not necessarily lead to carbon removals, particularly if technologies the CO2 is sourced from fossil fuels and/or if the products do not store the CO2 for climate-relevant horizons (von der Assen et al., 2013) (see also Section 4.3.4.5). • Methane8 is a much more potent GHG than CO2 (Montzka et al., 2011), associated with difficult-to-abate emissions in industry and agriculture and with outgassing from lakes, wetlands, and oceans (Lockley, 2012; Stolaroff et al., 2012). Enhancing processes that naturally remove methane, either by chemical or biological decomposition (Sundqvist et al., 2012), has been proposed to remove CH4. There is low confidence that existing technologies for CH4 removal are economically or energetically suitable for large-scale air capture (Boucher and Folberth, 2010). Methane removal potentials are limited due to its low atmospheric concentration and its low chemical reactivity at ambient conditions. • Preston (2013) identifies distributive and procedural justice, permissibility, moral hazard (Shue, 2018), and hubris as ethical aspects that could apply to Ethical aspects large-scale CDR deployment. • There is a lack of reflection on the climate futures produced by recent modelling and implying very different ethical costs/risks and benefits (Minx et al., 2018). • Existing governance mechanisms are scarce and either targeted at particular CDR options (e.g., ocean-based) or aspects (e.g., concerning indirect land-use change (iLUC)) associated with bioenergy upscaling, and often the mechanisms are at national or regional scale (e.g., EU). Regulation accounting for iLUC Governance by formulating sustainability criteria (e.g., the EU Renewable Energy Directive) has been assessed as insufficient in avoiding leakage (e.g., Frank et al., 2013). • An international governance mechanism is only in place for R&D of ocean fertilization within the Convention on Biological Diversity (IMO, 1972, 1996; CBD, 2008, 2010). • Burns and Nicholson (2017) propose a human rights-based approach to protect those potentially adversely impacted by CDR options. • The CDR potentials that can be realized are constrained by the lack of policy portfolios incentivising large-scale CDR (Peters and Geden, 2017). • Near-term opportunities could be supported through modifying existing policy mechanisms (Lomax et al., 2015). • Scott and Geden (2018) sketch three possible routes for limited progress, (i) at EU-level, (ii) at EU Member State level, and (iii) at private sector level, noting Policy the implied paradigm shift this would entail. • EU may struggle to adopt policies for CDR deployment on the scale or time-frame envisioned by IAMs (Geden et al., 2018). • Social impacts of large-scale CDR deployment (Buck, 2016) require policies taking these into account. • On long time scales, natural sinks could reverse (C.D. Jones et al., 2016) Carbon cycle • No robust assessments yet of the effectiveness of CDR in reverting climate change (Tokarska and Zickfeld, 2015; Wu et al., 2015; Keller et al., 2018), see also Chapter 2, Section 2.2.2.2. 4 4.3.8 Solar Radiation Modification (SRM) SRM could reduce some of the global risks of climate change related to temperature rise (Izrael et al., 2014; MacMartin et al., 2014), rate of This report refrains from using the term ‘geoengineering’ and separates sea level rise (Moore et al., 2010), sea-ice loss (Berdahl et al., 2014) and SRM from CDR and other mitigation options (see Chapter 1, Section frequency of extreme storms in the North Atlantic and heatwaves in 1.4.1 and Glossary). Europe (Jones et al., 2018). SRM also holds risks of changing precipitation and ozone concentrations and potentially reductions in biodiversity Table 4.7 gives an overview of SRM methods and characteristics. For a (Pitari et al., 2014; Visioni et al., 2017a; Trisos et al., 2018). Literature more comprehensive discussion of currently proposed SRM methods, only supports SRM as a supplement to deep mitigation, for example in and their implications for geophysical quantities and sustainable overshoot scenarios (Smith and Rasch, 2013; MacMartin et al., 2018). development, see also Cross-Chapter Box 10 in this Chapter. This section assesses the feasibility, from an institutional, technological, 4.3.8.1 Governance and institutional feasibility economic and social-cultural viewpoint, focusing on stratospheric aerosol injection (SAI) unless otherwise indicated, as most available There is robust evidence but medium agreement for unilateral action literature is about SAI. potentially becoming a serious SRM governance issue (Weitzman, 2015; Rabitz, 2016), as some argue that enhanced collaboration Some of the literature on SRM appears in the forms of commentaries, might emerge around SRM (Horton, 2011). An equitable institutional policy briefs, viewpoints and opinions (e.g., (Horton et al., 2016; Keith et or governance arrangement around SRM would have to reflect al., 2017; Parson, 2017). This assessment covers original research rather views of different countries (Heyen et al., 2015) and be multilateral than viewpoints, even if the latter appear in peer-reviewed journals. because of the risk of termination, and risks that implementation or unilateral action by one country or organization will produce negative precipitation or extreme weather effects across borders (Lempert and 8 Current work (e.g., de Richter et al., 2017) examines other technologies considering non-CO2 GHGs like N2O. 347 Chapter 4 Strengthening and Implementing the Global Response Table 4.7 | Overview of the main characteristics of the most-studied SRM methods. Stratospheric Aerosol Marine Cloud Cirrus Cloud Ground-Based Albedo SRM indicator injection (SAI) Brightening (MCB) Thinning (CCT) Modification (GBAM) Whitening roofs, changes in land use Injection of a gas in the Seeding to promote nucleation, reducing Spraying sea salt or other management (e.g., no-till farming), Description of stratosphere, which then converts optical thickness and cloud lifetime, particles into marine clouds, change of albedo at a larger scale SRM method to aerosols. Injection of other to allow more outgoing longwave making them more reflective. (covering glaciers or deserts with reflective particles also considered. radiation to escape into space. sheeting and changes in ocean albedo). Radiative forcing 100–295 Tg dry sea Small on global scale, up to 1°C–3°C 1–4 TgS W−1 m2 yr−1 Not known efficiencies salt W−1 m2 yr−1 on regional scale Amount needed 0.04–0.1 albedo change in agricultural 2–8 TgS yr−1 70 Tg dry sea salt yr−1 Not known for 1°C overshoot and urban areas Changes in precipitation patterns and circulation regimes; in case of SO2 injection, disruption to stratospheric chemistry (for SRM specific Low-level cloud changes; instance NOx depletion and Regional rainfall responses; Impacts on precipitation in monsoon areas; impacts on climate tropospheric drying; intensification changes in methane lifetime); reduction in hurricane intensity could target hot extremes variables of the hydrological cycle increase in stratospheric water vapour and tropospheric- stratospheric ice formation affecting cloud microphysics In case of SO2 injection, stratospheric ozone loss (which SRM specific could also have a positive Reduction in the number impacts on human/ effect – a net reduction in global Not known Not known of mild crop failures natural systems mortality due to competing health impact pathways) and significant increase of surface UV Volcanic analogues; high Observed in ships tracks; Natural and land-use analogues; agreement amongst simulations; No clear physical mechanism; several simulations confirm several simulations confirm mechanism; Maturity of science robust evidence on ethical, limited evidence and low agreement; mechanism; high agreement to influence on regional governance and sustainable several simulations regionally limited temperature; land use costly development limitations 4 Robock et al., 2008; Salter et al., 2008; Heckendorn et al., 2009; Alterskjær et al., 2012; Irvine et al., 2011; Tilmes et al., 2012, 2016; Storelvmo et al., 2014; Jones and Haywood, 2012; Akbari et al., 2012; Pitari et al., 2014; Kristjánsson et al., 2015; Latham et al., 2012, 2013; Jacobson and Ten Hoeve, 2012; Key references Crook et al., 2015; Jackson et al., 2016; Kravitz et al., 2013; Davin et al., 2014; C.J. Smith et al., 2017; Kärcher, 2017; Crook et al., 2015; Crook et al., 2015, 2016; Visioni et al., 2017a, b; Lohmann and Gasparini, 2017 Parkes et al., 2015; Seneviratne et al., 2018 Eastham et al., 2018; Ahlm et al., 2017 Plazzotta et al., 2018 Prosnitz, 2011; Dilling and Hauser, 2013; NRC, 2015b). Some have Alongside SBSTA, the WMO, UNESCO and UN Environment could play suggested that the governance of research and field experimentation a role in governance of SRM (Nicholson et al., 2018). Each of these can help clarify uncertainties surrounding deployment of SRM (Long organizations has relevance with respect to the regulatory framework and Shepherd, 2014; Parker, 2014; NRC, 2015c; Caldeira and Bala, (Bodle et al., 2012; Williamson and Bodle, 2016). The UNCBD gives 2017; Lawrence and Crutzen, 2017), and that SRM is compatible with guidance that ‘that no climate-related geo-engineering activities that democratic processes (Horton et al., 2018) or not (Szerszynski et al., may affect biodiversity take place’ (CBD, 2010). 2013; Owen, 2014). 4.3.8.2 Economic and technological feasibility Several possible institutional arrangements have been considered for SRM governance: under the UNFCCC (in particular under the The literature on the engineering costs of SRM is limited and may Subsidiary Body on Scientific and Technological Advice (SBSTA)) or the be unreliable in the absence of testing or deployment. There is high United Nations Convention on Biological Diversity (UNCBD) (Honegger agreement that costs of SAI (not taking into account indirect and social et al., 2013; Nicholson et al., 2018), or through a consortium of costs, research and development costs and monitoring expenses) may states (Bodansky, 2013; Sandler, 2017). Reasons for states to join an be in the range of 1–10 billion USD yr−1 for injection of 1–5 MtS to international governance framework for SRM include having a voice in achieve cooling of 1–2 W m−2 (Robock et al., 2009; McClellan et al., SRM diplomacy, prevention of unilateral action by others and benefits 2012; Ryaboshapko and Revokatova, 2015; Moriyama et al., 2016), from research collaboration (Lloyd and Oppenheimer, 2014). suggesting that cost-effectiveness may be high if side-effects are low 348 Strengthening and Implementing the Global Response Chapter 4 or neglected (McClellan et al., 2012). The overall economic feasibility shows low agreement on whether SRM research and deployment may of SRM also depends on externalities and social costs (Moreno-Cruz lead policy-makers to reduce mitigation efforts and thus imply a moral and Keith, 2013; Mackerron, 2014), climate sensitivity (Kosugi, 2013), hazard (Linnér and Wibeck, 2015). SRM might motivate individuals option value (Arino et al., 2016), presence of climate tipping points (as opposed to policymakers) to reduce their GHG emissions, but even (Eric Bickel, 2013) and damage costs as a function of the level of SRM a subtle difference in the articulation of information about SRM can (Bahn et al., 2015; Heutel et al., 2018). Modelling of game-theoretic, influence subsequent judgements of favourability (Merk et al., 2016). strategic interactions of states under heterogeneous climatic impacts The argument that SRM research increases the likelihood of deployment shows low agreement on the outcome and viability of a cost-benefit (the ‘slippery slope’ argument), is also made (Quaas et al., 2017), but analysis for SRM (Ricke et al., 2015; Weitzman, 2015). some also found an opposite effect (Bellamy and Healey, 2018). For SAI, there is high agreement that aircrafts could, after some Unequal representation and deliberate exclusion are plausible in modifications, inject millions of tons of SO2 in the lower stratosphere decision-making on SRM, given diverging regional interests and the (at approximately 20 km; (Davidson et al., 2012; McClellan et al., 2012; anticipated low resource requirements to deploy SRM (Ricke et al., Irvine et al., 2016). 2013). Whyte (2012) argues that the concerns, sovereignties, and experiences of indigenous peoples may particularly be at risk. 4.3.8.3 Social acceptability and ethics The general public can be characterized as oblivious to and worried Ethical questions around SRM include those of international about SRM (Carr et al., 2013; Parkhill et al., 2013; Wibeck et al., 2017). responsibilities for implementation, financing, compensation for An emerging literature discusses public perception of SRM, showing a negative effects, the procedural justice questions of who is involved lack of knowledge and unstable opinions (Scheer and Renn, 2014). The in decisions, privatization and patenting, welfare, informed consent perception of controllability affects legitimacy and public acceptability by affected publics, intergenerational ethics (because SRM requires of SRM experiments (Bellamy et al., 2017). In Germany, laboratory sustained action in order to avoid termination hazards), and the work on SRM is generally approved of, field research much less so, so-called ‘moral hazard’ (Burns, 2011; Whyte, 2012; Gardiner, 2013; and immediate deployment is largely rejected (Merk et al., 2015; Braun Lin, 2013; Buck et al., 2014; Klepper and Rickels, 2014; Morrow, 2014; et al., 2017). Various factors could explain variations in the degree of Wong, 2014; Reynolds, 2015; Lockley and Coffman, 2016; McLaren, rejection of SRM between Canada, China, Germany, Switzerland, the 2016; Suarez and van Aalst, 2017; Reynolds et al., 2018). The literature United Kingdom, and the United States (Visschers et al., 2017). Cross-Chapter Box 10 | Solar Radiation Modification in the Context of 1.5°C Mitigation Pathways 4 Contributing Authors: Anastasia Revokatova (Russian Federation), Heleen de Coninck (Netherlands/EU), Piers Forster (UK), Veronika Ginzburg (Russian Federation), Jatin Kala (Australia), Diana Liverman (USA), Maxime Plazzotta (France), Roland Séférian (France), Sonia I. Seneviratne (Switzerland), Jana Sillmann (Norway). Solar radiation modification (SRM) refers to a range of radiation modification measures not related to greenhouse gas (GHG) mitigation that seek to limit global warming (see Chapter 1, Section 1.4.1). Most methods involve reducing the amount of incoming solar radiation reaching the surface, but others also act on the longwave radiation budget by reducing optical thickness and cloud lifetime (see Table 4.7). In the context of this report, SRM is assessed in terms of its potential to limit warming below 1.5°C in temporary overshoot scenarios as a way to reduce elevated temperatures and associated impacts (Irvine et al., 2016; Keith and Irvine, 2016; Chen and Xin, 2017; Sugiyama et al., 2017a; Visioni et al., 2017a; MacMartin et al., 2018). The inherent variability of the climate system would make it difficult to detect the efficacy or side-effects of SRM intervention when deployed in such a temporary scenario (Jackson et al., 2015). A. Potential SRM timing and magnitude Published SRM approaches are summarized in Table 4.7. The timing and magnitude of potential SRM deployment depends on the temperature overshoot associated with mitigation pathways. All overshooting pathways make use of carbon dioxide removal. Therefore, if considered, SRM would only be deployed as a supplemental measure to large-scale carbon dioxide removal (Chapter 2, Section 2.3). Cross-Chapter Box 10, Figure 1 below illustrates an example of how a hypothetical SRM deployment based on stratospheric aerosols injection (SAI) could be used to limit warming below 1.5°C using an ‘adaptive SRM’ approach (e.g., Kravitz et al., 2011; Tilmes et al., 2016), where global mean temperature rise exceeds 1.5°C compared to pre-industrial level by mid-century and returns below 1.5°C before 2100 with a 66% likelihood (see Chapter 2). In all such limited adaptive deployment scenarios, deployment of SRM only 349 Chapter 4 Strengthening and Implementing the Global Response Cross Chapter Box 10 (continued) commences under conditions in which CO2 emissions have already fallen substantially below their peak level and are continuing to fall. In order to hold warming to 1.5°C, a hypothetical SRM deployment could span from one to several decades, with the earliest possible threshold exceedance occurring before mid-century. Over this duration, SRM has to compensate for warming that exceeds 1.5°C (displayed with hatching on panel a) with a decrease in radiative forcing (panel b) which could be achieved with a rate of SAI varying between 0–5.9 MtSO2 yr −1 (panel c) (Robock et al., 2008; Heckendorn et al., 2009). 4 Cross-Chapter Box 10, Figure 1 | Evolution of hypothetical SRM deployment (based on stratospheric aerosols injection, or SAI) in the context of 1.5°C-consistent pathways. (a) Range of median temperature outcomes as simulated by MAGICC (see in Chapter 2, Section 2.2) given the range of CO2 emissions and (b) other climate forcers for mitigation pathways exceeding 1.5°C at mid-century and returning below by 2100 with a 66% likelihood. Geophysical characteristics are represented by (c) the magnitude of radiative forcing and (d) the amount of stratospheric SO2 injection that are required to keep the global median temperature below 1.5°C during the temperature overshoot (given by the blue hatching on panel a). SRM surface radiative forcing has been diagnosed using a mean cooling efficiency of 0.3°C (W− m2) of Plazzotta et al. (2018). Magnitude and timing of SO2 injection have been derived from published estimates of Heckendorn et al. (2009) and Robock et al. (2008). SAI is the most-researched SRM method, with high agreement that it could limit warming to below 1.5°C (Tilmes et al., 2016; Jones et al., 2018). The response of global temperature to SO2 injection, however, is uncertain and varies depending on the model parametrization and emission scenarios (Jones et al., 2011; Kravitz et al., 2011; Izrael et al., 2014; Crook et al., 2015; Niemeier and Timmreck, 2015; Tilmes et al., 2016; Kashimura et al., 2017). Uncertainty also arises due to the nature and the optical properties of injected aerosols. 350 Strengthening and Implementing the Global Response Chapter 4 Cross Chapter Box 10 (continued) Other approaches are less well researched, but the literature suggests that ground-based albedo modification (GBAM), marine cloud brightening (MCB) or cirrus cloud thinning (CCT) are not assessed to be able to substantially reduce overall global temperature (Irvine et al., 2011; Seneviratne et al., 2018). However, these SRM approaches are known to create spatially heterogeneous forcing and potentially more spatially heterogeneous climate effects, which may be used to mitigate regional climate impacts. This may be of most relevance in the case of GBAM when applied to crop and urban areas (Seneviratne et al., 2018). Most of the literature on regional mitigation has focused on GBAM in relationship with land-use and land-cover change scenarios. Both models and observations suggest that there is a high agreement that GBAM would result in cooling over the region of changed albedo, and in particular would reduce hot extremes (Irvine et al., 2011; Akbari et al., 2012; Jacobson and Ten Hoeve, 2012; Davin et al., 2014; Crook et al., 2015, 2016; Alkama and Cescatti, 2016; Seneviratne et al., 2018). In comparison, there is a limited evidence on the ability of MCB or CCT to mitigate regional climate impacts of 1.5°C warming because the magnitude of the climate response to MCB or CCT remains uncertain and the processes are not fully understood (Lohmann and Gasparini, 2017). B. General consequences and impacts of solar radiation modification It has been proposed that deploying SRM as a supplement to mitigation may reduce increases in global temperature-related extremes and rainfall intensity, and lessen the loss of coral reefs from increasing sea-surface temperatures (Keith and Irvine, 2016), but it would not address, or could even worsen (Tjiputra et al., 2016), negative effects from continued ocean acidification. Another concern with SRM is the risk of a ‘termination shock’ or ‘termination effect’ when suddenly stopping SRM, which might cause rapid temperature rise and associated impacts (Jones et al., 2013; Izrael et al., 2014; McCusker et al., 2014), most noticeably biodiversity loss (Trisos et al., 2018). The severity of the termination effect has recently been debated (Parker and Irvine, 2018) and depends on the degree of SRM cooling. This report only considers limited SRM in the context of mitigation pathways to 1.5°C. Other risks of SRM deployment could be associated with the lack of testing of the proposed deployment schemes (e.g., Schäfer et al., 2013). Ethical aspects and issues related to the governance and economics are discussed in Section 4.3.8. C. Consequences and impacts of SRM on the carbon budget Because of its effects on surface temperature, precipitation and surface shortwave radiation, SRM would also alter the carbon budget pathways to 1.5°C or 2°C (Eliseev, 2012; Keller et al., 2014; Keith et al., 2017; Lauvset et al., 2017). Despite the large uncertainties in the simulated climate response to SRM, current model simulations suggest that SRM would lead to altered carbon budgets compatible with 1.5°C or 2°C. The 6 CMIP5 models investigated simulated an increase of natural 4 carbon uptake by land biosphere and, to a smaller extent, by the oceans (high agreement). The multimodel mean of this response suggests an increase of the RCP4.5 carbon budget of about 150 GtCO2 after 50 years of SO2 injection with a rate of 4 TgS yr −1, which represents about 4 years of CO2 emissions at the current rate (36 GtCO2 yr −1). However, there is uncertainty around quantitative determination of the effects that SRM or its cessation has on the carbon budget due to a lack of understanding of the radiative processes driving the global carbon cycle response to SRM (Ramachandran et al., 2000; Mercado et al., 2009; Eliseev, 2012; Xia et al., 2016), uncertainties about how the carbon cycle will respond to termination effects of SRM, and uncertainties in climate–carbon cycle feedbacks (Friedlingstein et al., 2014). D. Sustainable development and SRM There are few studies investigating potential implications of SRM for sustainable development. These are based on a limited number of scenarios and hypothetical considerations, mainly referring to benefits from lower temperatures (Irvine et al., 2011; Nicholson, 2013; Anshelm and Hansson, 2014; Harding and Moreno-Cruz, 2016). Other studies suggest negative impacts from SRM implementation concerning issues related to regional disparities (Heyen et al., 2015), equity (Buck, 2012), fisheries, ecosystems, agriculture, and termination effects (Robock, 2012; Morrow, 2014; Wong, 2014). If SRM is initiated by the richer nations, there might be issues with local agency, and possibly worsening conditions for those suffering most under climate change (Buck et al., 2014). In addition, ethical issues related to testing SRM have been raised (e.g., Lenferna et al., 2017). Overall, there is high agreement that SRM would affect many development issues but limited evidence on the degree of influence, and how it manifests itself across regions and different levels of society. E. Overall feasibility of SRM If mitigation efforts do not keep global mean temperature below 1.5°C, SRM can potentially reduce the climate impacts of a temporary temperature overshoot, in particular extreme temperatures, rate of sea level rise and intensity of tropical cyclones, alongside intense mitigation and adaptation efforts. While theoretical developments show that SRM is technically feasible (see Section 4.3.8.2), global field experiments have not been conducted and most of the knowledge about SRM is based on imperfect 351 Chapter 4 Strengthening and Implementing the Global Response Cross Chapter Box 10 (continued) model simulations and some natural analogues. There are also considerable challenges to the implementation of SRM associated with disagreements over the governance, ethics, public perception, and distributional development impacts (see Section 4.3.8) (Boyd, 2016; Preston, 2016; Asayama et al., 2017; Sugiyama et al., 2017b; Svoboda, 2017; McKinnon, 2018; Talberg et al., 2018). Overall, the combined uncertainties surrounding the various SRM approaches, including technological maturity, physical understanding, potential impacts, and challenges of governance, constrain the ability to implement SRM in the near future. 4.4 Implementing Far-Reaching 4.4.1.1 Institutions and their capacity to invoke far-reaching and Rapid Change and rapid change The feasibility of 1.5°C-compatible pathways is contingent upon Institutions – the rules and norms that guide human interactions enabling conditions for systemic change (see Cross Chapter Box 3 in (Section 4.4.2) – enable or impede the structures, mechanisms Chapter 1). Section 4.3 identifies the major systems, and options within and measures that guide mitigation and adaptation. Institutions, those systems, that offer the potential for change to align with 1.5°C understood as the ‘rules of the game’ (North, 1990), exert direct and pathways. indirect influence over the viability of 1.5°C-consistent pathways (Munck et al., 2014; Willis, 2017). Governance would be needed to AR5 identifies enabling conditions as influencing the feasibility support wide-scale and effective adoption of mitigation and adaptation of climate responses (Kolstad et al., 2014). This section draws on options. Institutions and governance structures are strengthened 1.5°C-specific and related literature on rapid and scaled up change when the principle of the ‘commons’ is explored as a way of sharing to identify the enabling conditions that influence the feasibility of management and responsibilities (Ostrom et al., 1999; Chaffin et adaptation and mitigation options assessed in Section 4.5. Examples al., 2014; Young, 2016). Institutions would need to be strengthened from diverse regions and sectors are provided in Boxes 4.1 to 4.10 to interact amongst themselves, and to share responsibilities for the to illustrate how these conditions could enable or constrain the development and implementation of rules, regulations and policies implementation of incremental, rapid, disruptive and transformative (Ostrom et al., 1999; Wejs et al., 2014; Craig et al., 2017), with the goal mitigation and adaptation consistent with 1.5°C pathways. of ensuring that these embrace equity, justice, poverty alleviation and sustainable development, enabling a 1.5°C world (Reckien et al., 2017; Coherence between the enabling conditions holds potential to enhance Wood et al., 2017). the feasibility of 1.5°C-consistent pathways and adapting to the 4 consequences. This includes better alignment across governance scales Several authors have identified different modes of cross-stakeholder (OECD, 2015a; Geels et al., 2017), enabling multilevel governance interaction in climate policy, including the role played by large (Cheshmehzangi, 2016; Revi, 2017; Tait and Euston-Brown, 2017) and multinational corporations, small enterprises, civil society and non- nested institutions (Abbott, 2012). It also includes interdisciplinary state actors. Ciplet et al. (2015) argue that civil society is to a great actions, combined adaptation and mitigation action (Göpfert et al., extent the only reliable motor for driving institutions to change at 2018), and science–policy partnerships (Vogel et al., 2007; Hering et al., the pace required. Kern and Alber (2009) recognize different forms of 2014; Roberts, 2016; Figueres et al., 2017; Leal Filho et al., 2018). These collaboration relevant to successful climate policies beyond the local partnerships are difficult to establish and sustain, but can generate level. Horizontal collaboration (e.g., transnational city networks) and trust (Cole, 2015; Jordan et al., 2015) and inclusivity that ultimately can vertical collaboration within nation-states can play an enabling role provide durability and the realization of co-benefits for sustained rapid (Ringel, 2017). Vertical and horizontal collaboration requires synergistic change (Blanchet, 2015; Ziervogel et al., 2016a). relationships between stakeholders (Ingold and Fischer, 2014; Hsu et al., 2017). The importance of community participation is emphasized 4.4.1 Enhancing Multilevel Governance in literature, and in particular the need to take into account equity and gender considerations (Chapter 5) (Graham et al., 2015; Bryan Addressing climate change and implementing responses to et al., 2017; Wangui and Smucker, 2017). Participation often faces 1.5°C-consistent pathways would require engagement between implementation challenges and may not always result in better policy various levels and types of governance (Betsill and Bulkeley, 2006; outcomes. Stakeholders, for example, may not view climate change as Kern and Alber, 2009; Christoforidis et al., 2013; Romero-Lankao et al., a priority and may not share the same preferences, potentially creating 2018). AR5 highlighted the significance of governance as a means of a policy deadlock (Preston et al., 2013, 2015; Ford et al., 2016). strengthening adaptation and mitigation and advancing sustainable development (Fleurbaey et al., 2014). Governance is defined in the 4.4.1.2 International governance broadest sense as the ‘processes of interaction and decision-making among actors involved in a common problem’ (Kooiman, 2003; Hufty, International treaties help strengthen policy implementation, providing 2011; Fleurbaey et al., 2014). This definition goes beyond notions of a medium- and long-term vision (Obergassel et al., 2016). International formal government or political authority and integrates other actors, climate governance is organized via many mechanisms, including networks, informal institutions and communities. international organizations, treaties and conventions, for example, 352 Strengthening and Implementing the Global Response Chapter 4 UNFCCC, the Paris Agreement and the Montreal Protocol. Other is thought be more effective in securing trust (Dagnet et al., 2016) multilateral and bilateral agreements, such as trade agreements, also and enables effective monitoring and timely reporting on national have a bearing on climate change. actions (including adaptation), allowing for international scrutiny and persistent efforts of civil society and non-state actors to encourage There are significant differences between global mitigation and action in both national and international contexts (Allan and Hadden, adaptation governance frames. Mitigation tends to be global by its 2017; Bäckstrand and Kuyper, 2017; Höhne et al., 2017; Lesnikowski et nature and based on the principle of the climate system as a global al., 2017; Maor et al., 2017; UNEP, 2017a), with some limitations (Nieto commons (Ostrom et al., 1999). Adaptation has traditionally been et al., 2018). viewed as a local process, involving local authorities, communities, and stakeholders (Khan, 2013; Preston et al., 2015), although it is now The paradigm shift enabled at Cancun succeeded by focusing on the recognized to be a multi-scaled, multi-actor process that transcends objective of ‘equitable access to sustainable development’ (Hourcade scales from local and sub-national to national and international et al., 2015). The use of ‘pledge and review’ now underpins the Paris (Mimura et al., 2014; UNEP, 2017a). National governments provide a Agreement. This consolidates multiple attempts to define a governance central pivot for coordination, planning, determining policy priorities approach that relies on Nationally Determined Contributions (NDCs) and distributing resources. National governments are accountable and on means for a ‘facilitative model’ (Bodansky and Diringer, 2014) to the international community through international agreements. to reinforce them. This enables a regular, iterative, review of NDCs Yet, many of the impacts of climate change are transboundary, so allowing countries to set their own ambitions after a global stocktake that bilateral and multilateral cooperation are needed (Nalau et al., and more flexible, experimental forms of climate governance, which may 2015; Donner et al., 2016; Magnan and Ribera, 2016; Tilleard and Ford, provide room for higher ambition and be consistent with the needs of 2016; Lesnikowski et al., 2017). The Kigali Amendment to the Montreal governing for a rapid transition to close the emission gap (Clémençon, Protocol demonstrates that a global environmental agreement 2016; Falkner, 2016) (Cross-Chapter Box 11 in this chapter). Beyond facilitating common but differentiated responsibilities is possible a general consensus on the necessity of measurement, reporting and (Sharadin, 2018). This was operationalized by developed countries verification (MRV) mechanisms as a key element of a climate regime acting first, with developing countries following and benefiting from (Ford et al., 2015b; van Asselt et al., 2015), some authors emphasize leap-frogging the trial-and-error stages of innovative technology different governance approaches to implement the Paris Agreement. development. Through the new proposed sustainable development mechanism in Article 6, the Paris Agreement allows the space to harness the lowest Work on international climate governance has focused on the nature cost mitigation options worldwide. This may incentivize policymakers of ‘climate regimes’ and coordinating the action of nation-states to enhance mitigation ambition by speeding up climate action as part (Aykut, 2016) organized around a diverse set of instruments: (i) binding of a ‘climate regime complex’ (Keohane and Victor, 2011) of loosely limits allocated by principles of historical responsibility and equity, (ii) interrelated global governance institutions. In the Paris Agreement, the carbon prices, emissions quotas, (iii) pledges and review of policies and ‘common but differentiated responsibilities and respective capabilities’ 4 measures or (iv) a combination of these options (Stavins, 1988; Grubb, (CBDR-RC) principle could be expanded and revisited under a ‘sharing 1990; Pizer, 2002; Newell and Pizer, 2003). the pie’ paradigm (Ji and Sha, 2015) as a tool to open innovation processes towards alternative development pathways (Chapter 5). Literature on the Kyoto Protocol provides two important insights for the 1.5°C transition: the challenge of agreeing on rules to allocate COP 16 in Cancun was also the first time in the UNFCCC that emissions quotas (Shukla, 2005; Caney, 2012; Winkler et al., 2013; adaptation was recognized to have similar priority as mitigation. The Gupta, 2014; Méjean et al., 2015) and a climate-centric vision (Shukla, Paris Agreement recognizes the importance of adaptation action and 2005; BASIC experts, 2011), separated from development issues which cooperation to enhance such action. Chung Tiam Fook (2017) and drove resistance from many developing nations (Roberts and Parks, Lesnikowski et al. (2017) suggest that the Paris Agreement is explicit 2006). For the former, a burden-sharing approach led to an adversarial about multilevel adaptation governance, outlines stronger transparency process among nations to decide who should be allocated ‘how much’ mechanisms, links adaptation to development and climate justice, and of the remainder of the emissions budget (Caney, 2014; Ohndorf et al., is therefore suggestive of greater inclusiveness of non-state voices and 2015; Roser et al., 2015; Giménez-Gómez et al., 2016). Industry group the broader contexts of social change. lobbying further contributed to reducing space for manoeuvre of some major emitting nations (Newell and Paterson, 1998; Levy and Egan, 1.5°C-consistent pathways require further exploration of conditions of 2003; Dunlap and McCright, 2011; Michaelowa, 2013; Geels, 2014). trust and reciprocity amongst nation states (Schelling, 1991; Ostrom and Walker, 2005). Some authors (Colman et al., 2011; Courtois et al., Given the political unwillingness to continue with the Kyoto Protocol 2015) suggest a departure from the vision of actors acting individually approach a new approach was introduced in the Copenhagen Accord, in the pursuit of self-interest to that of iterated games with actors the Cancun Agreements, and finally in the Paris Agreement. The interacting over time showing that reciprocity, with occasional transition to 1.5°C requires carbon neutrality and thus going beyond forgiveness and initial good faith, can lead to win-win outcomes and the traditional framing of climate as a ‘tragedy of the commons’ to be to cooperation as a stable strategy (Axelrod and Hamilton, 1981). addressed via cost-optimal allocation rules, which demonstrated a low probability of enabling a transition to 1.5°C-consistent pathways (Patt, Regional cooperation plays an important role in the context of 2017). The Paris Agreement, built on a ‘pledge and review’ system, global governance. Literature on climate regimes has only started 353 Chapter 4 Strengthening and Implementing the Global Response exploring innovative governance arrangements, including coalitions (Bulkeley, 2005). However, Michaelowa and Michaelowa (2017) find of transnational actors including state, market and non-state actors low effectiveness for over 100 of such mitigation initiatives. (Bulkeley et al., 2012; Hovi et al., 2016; Hagen et al., 2017; Hermwille et al., 2017; Roelfsema et al., 2018) and groupings of countries, as 4.4.1.4 Interactions and processes for multilevel governance a complement to the UNFCCC (Abbott and Snidal, 2009; Biermann, 2010; Zelli, 2011; Nordhaus, 2015). Climate action requires multilevel Literature has proposed multilevel governance in climate change as governance from the local and community level to national, regional an enabler for systemic transformation and effective governance, and international levels. Box 4.1 shows the role of sub-national as the concept is thought to allow for combining decisions across authorities (e.g., regions and provinces) in facilitating urban climate levels and sectors and across institutional types at the same level action, while Box 4.2 shows that climate governance can be organized (Romero-Lankao et al., 2018), with multilevel reinforcement and the across hydrological as well as political units. mobilization of economic interests at different levels of governance (Jänicke and Quitzow, 2017). These governance mechanisms are 4.4.1.3 Sub-national governance based on accountability and transparency rules and participation and coordination across and within these levels. Local governments can play a key role (Melica et al., 2018; Romero- Lankao et al., 2018) in influencing mitigation and adaptation A study of 29 European countries showed that the rapid adoption strategies. It is important to understand how rural and urban and diffusion of adaptation policymaking is largely driven by internal areas, small islands, informal settlements and communities might factors, at the national and sub-national levels (Massey et al., 2014). intervene to reduce climate impacts (Bulkeley et al., 2011), either by An assessment of national-level adaptation in 117 countries (Berrang- implementing climate objectives defined at higher government levels Ford et al., 2014) found good governance to be the one of the strongest or by taking initiative autonomously or collectively (Aall et al., 2007; predictors of national adaptation policy. An analysis of the climate Reckien et al., 2014; Araos et al., 2016a; Heidrich et al., 2016). Local responses of 200 large and medium-sized cities across eleven European governance faces the challenge of reconciling local concerns with countries found that factors such as membership of climate networks, global objectives. Local governments could coordinate and develop population size, gross domestic product (GDP) per capita and adaptive effective local responses, and could pursue procedural justice in capacity act as drivers of mitigation and adaptation plans (Reckien et ensuring community engagement and more effective policies around al., 2015). energy and vulnerability reduction (Moss et al., 2013; Fudge et al., 2016). They can enable more participative decision-making (Barrett, Adaptation policy has seen growth in some areas (Massey et al., 2015; Hesse, 2016). Fudge et al. (2016) argue that local authorities 2014; Lesnikowski et al., 2016), although efforts to track adaptation are well-positioned to involve the wider community in: designing progress are constrained by an absence of data sources on adaptation and implementing climate policies, engaging with sustainable energy (Berrang-Ford et al., 2011; Ford and Berrang-Ford, 2016; Magnan, 4 generation (e.g., by supporting energy communities) (Slee, 2015), and 2016; Magnan and Ribera, 2016). Many developing countries have the delivery of demand-side measures and adaptation implementation. made progress in formulating national policies, plans and strategies on responding to climate change. The NDCs have been identified as one By 2050, it is estimated three billion people will be living in slums and such institutional mechanism (Cross-Chapter Box 11 in this Chapter) informal settlements: neighbourhoods without formal governance, on (Magnan et al., 2015; Kato and Ellis, 2016; Peters et al., 2017). un-zoned land developments and in places that are exposed to climate- related hazards (Bai et al., 2018). Emerging research is examining how To overcome barriers to policy implementation, local conflicts of citizens can contribute informally to governance with rapid urbanization interest or vested interests, strong leadership and agency is needed by and weaker government regulation (Sarmiento and Tilly, 2018). It political leaders. As shown by the Covenant of Mayors initiative (Box remains to be seen how the possibilities and consequences of alternative 4.1), political leaders with a vision for the future of the local community urban governance models will be managed for large, complex problems can succeed in reducing GHG emissions, when they are supported by and for addressing inequality and urban adaptation (Amin and Cirolia, civil society (Rivas et al., 2015; Croci et al., 2017; Kona et al., 2018). 2018; Bai et al., 2018; Sarmiento and Tilly, 2018). Any political vision would need to be translated into an action plan, which could include elements describing policies and measures needed Expanding networks of cities are sharing experiences on coping with to achieve transition, the human and financial resources needed, climate change and drawing economic and development benefits from milestones, and appropriate measurement and verification processes climate change responses – a recent institutional innovation. This could (Azevedo and Leal, 2017). Discussing the plan with stakeholders be complemented by efforts of national governments to enhance local and civil society, including citizens and allowing for participation for climate action through national urban policies (Broekhoff et al., 2018). minorities, and having them provide input and endorse it, has been Over the years, non-state actors have set up several transnational found to increase the likelihood of success (Rivas et al., 2015; Wamsler, climate governance initiatives to accelerate the climate response, for 2017). However, as described by Nightingale (2017) and Green (2016), example, ICLEI (1990), C–40 (2005), the Global Island Partnership struggles over natural resources and adaptation governance both at (2006) and the Covenant of Mayors (2008) (Gordon and Johnson, the national and community levels would also need to be addressed 2017; Hsu et al., 2017; Ringel, 2017; Kona et al., 2018; Melica et al., ‘in politically unstable contexts, where power and politics shape 2018) and to exert influence on national governments and the UNFCCC adaptation outcomes’. 354 Strengthening and Implementing the Global Response Chapter 4 Multilevel governance includes adaptation across local, regional, and A multilevel approach considers that adaptation planning is affected national scales (Adger et al., 2005). The whole-of-government approach by scale mismatches between the local manifestation of climate to understanding and influencing climate change policy design and impacts and the diverse scales at which the problem is driven (Shi implementation puts analytical emphasis on how different levels of et al., 2016). Multilevel approaches may be relevant in low-income government and different types of actors (e.g., public and private) countries where limited financial resources and human capabilities can constrain or support local adaptive capacity (Corfee-Morlot et al., within local governments often lead to greater dependency on 2011), including the role of the civil society. National governments, national governments and other (donor) organizations, to strengthen for example, have been associated with enhancing adaptive capacity adaptation responses (Donner et al., 2016; Adenle et al., 2017). through building awareness of climate impacts, encouraging economic National governments or international organizations may motivate growth, providing incentives, establishing legislative frameworks urban adaptation externally through broad policy directives or projects conducive to adaptation, and communicating climate change by international donors. Municipal governments on the other hand information (Berrang-Ford et al., 2014; Massey et al., 2014; Austin et al., work within the city to spur progress on adaptation. Individual political 2015; Henstra, 2016; Massey and Huitema, 2016). Local governments, leadership in municipal government, for example, has been cited as on the other hand, are responsible for delivering basic services and a factor driving the adaptation policies of early adapters in Quito, utilities to the urban population, and protecting their integrity from Ecuador, and Durban, and South Africa (Anguelovski et al., 2014), the impacts of extreme weather (Austin et al., 2015; Cloutier et al., and for adaptation more generally (Smith et al., 2009). Adaptation 2015; Nalau et al., 2015; Araos et al., 2016b). National policies and pathways can help identify maladaptive actions (Juhola et al., 2016; transnational governance could be seen as complementary, rather Magnan et al., 2016; Gajjar et al., 2018) and encourage social learning than competitors, and strong national policies favour transnational approaches across multiple levels of stakeholders in sectors such as engagement of sub- and non-state actors (Andonova et al., 2017). marine biodiversity and water supply (Bosomworth et al., 2015; Butler Local initiatives are complementary with higher level policies and can et al., 2015; van der Brugge and Roosjen, 2015). be integrated in the multilevel governance system (Fuhr et al., 2018). Box 4.1 | Multilevel Governance in the EU Covenant of Mayors: Example of the Provincia di Foggia Since 2005, cities have emerged as a locus of institutional and governance climate innovation (Melica et al., 2018) and are driving responses to climate change (Roberts, 2016). Many cities have adopted more ambitious greenhouse gas (GHG) emission reduction targets than countries (Kona et al., 2018), with an overall commitment of GHG emission reduction targets by 2020 of 27%, almost 7 percentage points higher than the minimum target for 2020 (Kona et al., 2018). The Covenant of Mayors (CoM) is an initiative in which municipalities voluntarily commit to CO2 emission reduction. The participation of small municipalities has been facilitated 4 by the development and testing of a new multilevel governance model involving Covenant Territorial Coordinators (CTCs), i.e., provinces and regions, which commit to providing strategic guidance and financial and technical support to municipalities in their territories. Results from the 315 monitoring inventories submitted show an achievement of 23% reduction in emissions (compared to an average year 2005) for more than half of the cities under a CTC schema (Kona et al., 2018). The Province of Foggia, acting as a CTC, gave support to 36 municipalities to participate in the CoM and to prepare Sustainable Energy Action Plans (SEAPs). The Province developed a common approach to prepare SEAPs, provided data to compile municipal emission inventories (Bertoldi et al., 2018) and guided the signatory to identify an appropriate combination of measures to curb GHG emissions. The local Chamber of Commerce also had a key role in the implementation of these projects by the municipalities (Lombardi et al., 2016). The joint action by the province and the municipalities in collaboration with the local business community could be seen as an example of multilevel governance (Lombardi et al., 2016). Researchers have investigated local forms of collaboration within local government, with the active involvement of citizens and stakeholders, and acknowledge that public acceptance is key to the successful implementation of policies (Larsen and Gunnarsson- Östling, 2009; Musall and Kuik, 2011; Pollak et al., 2011; Christoforidis et al., 2013; Pasimeni et al., 2014; Lee and Painter, 2015). Achieving ambitious targets would need leadership, enhanced multilevel governance, vision and widespread participation in transformative change (Castán Broto and Bulkeley, 2013; Rosenzweig et al., 2015; Castán Broto, 2017; Fazey et al., 2017; Wamsler, 2017; Romero-Lankao et al., 2018). The Chapter 5, Section 5.6.4 case studies of climate-resilient development pathways, at state and community scales, show that participation, social learning and iterative decision-making are governance features of strategies that deliver mitigation, adaptation, and sustainable development in a fair and equitable manner. Another insight is the finding that incremental voluntary changes are amplified through community networking, polycentric governance (Dorsch and Flachsland, 2017), partnerships, and long-term change to governance systems at multiple levels (Stevenson and Dryzek, 2014; Lövbrand et al., 2017; Pichler et al., 2017; Termeer et al., 2017). 355 Chapter 4 Strengthening and Implementing the Global Response Box 4.2 | Watershed Management in a 1.5˚C World Water management is necessary in order for the global community to adapt to 1.5°C-consistent pathways. Cohesive planning that includes numerous stakeholders would be required to improve access, utilization and efficiency of water use and to ensure hydrologic viability. Response to drought and El Niño–Southern Oscillation (ENSO) in southern Guatemala Hydro-meteorological events, including ENSO, have impacted Central America (Steinhoff et al., 2014; Chang et al., 2015; Maggioni et al., 2016) and are projected to increase in frequency during a 1.5°C transition (Wang et al., 2017). The 2014–2016 ENSO damaged agriculture, seriously impacting rural communities. In 2016, the Climate Change Institute, in conjunction with local governments, the private sector, communities and human rights organizations, established dialogue tables for different watersheds to discuss water usage amongst stakeholders and plans to mitigate the effects of drought, alleviate social tension, and map water use of watersheds at risk. The goal was to encourage better water resource management and to enhance ecological flow through improved communication, transparency, and coordination amongst users. These goals were achieved in 2017 when each previously affected river reached the Pacific Ocean with at least its minimum ecological flow (Guerra, 2017). Drought management through the Limpopo Watercourse Commission The governments sharing the Limpopo river basin (Botswana, Mozambique, South Africa and Zimbabwe) formed the Limpopo Watercourse Commission in 2003 (Nyagwambo et al., 2008; Mitchell, 2013). It has an advisory body composed of working groups that assess water use and sustainability, decide national level distribution of water access, and support disaster and emergency planning. The Limpopo basin delta is highly vulnerable (Tessler et al., 2015), and is associated with a lack of infrastructure and investment capacity, requiring increased economic development together with plans for vulnerability reduction (Tessler et al., 2015) and water rights (Swatuk, 2015). The high vulnerability is influenced by gender inequality, limited stakeholder participation and limited institutional capacity to address unequal water access (Mehta et al., 2014). The implementation of integrated water resources management (IWRM) would need to consider pre-existing social, economic, historical and cultural contexts (Merrey, 2009; Mehta et al., 2014). The Commission therefore could play a role in improving participation and in providing an adaptable and equitable strategy for cross-border water sharing (Ekblom et al., 2017). 4 Flood management in the Danube The Danube River Protection Convention is the official instrument for cooperation on transboundary water governance between the countries that share the Danube Basin. The International Commission for the Protection of the Danube River (ICPDR) provides a strong science–policy link through expert working groups dealing with issues including governance, monitoring and assessment, and flood protection (Schmeier, 2014). The Trans-National Monitoring Network (TNMN) was developed to undertake comprehensive monitoring of water quality (Schmeier, 2014). Monitoring of water quality constitutes almost 50% of ICPDR’s scientific publications, although ICPDR also works on governance, basin planning, monitoring, and IWRM, indicating its importance. The ICPDR is an example of IWRM ‘coordinating groundwater, surface water abstractions, flood management, energy production, navigation, and water quality’ (Hering et al., 2014). Box 4.2 exemplifies how multilevel governance has been used for watershed management in different basins, given the impacts on water sources (Chapter 3, Section 3.4.2). 356 Strengthening and Implementing the Global Response Chapter 4 Cross-Chapter Box 11 | Consistency Between Nationally Determined Contributions and 1.5°C Scenarios Contributing Authors: Paolo Bertoldi (Italy), Michel den Elzen (Netherlands), James Ford (Canada/UK), Richard Klein (Netherlands/Germany), Debora Ley (Guatemala/Mexico), Timmons Roberts (USA), Joeri Rogelj (Austria/Belgium). Mitigation 1. Introduction There is high agreement that Nationally Determined Contributions (NDCs) are important for the global response to climate change and represent an innovative bottom-up instrument in climate change governance (Section 4.4.1), with contributions from all signatory countries (den Elzen et al., 2016; Rogelj et al., 2016; Vandyck et al., 2016; Luderer et al., 2018; Vrontisi et al., 2018). The global emission projections resulting from full implementation of the NDCs represent an improvement compared to business as usual (Rogelj et al., 2016) and current policies scenarios to 2030 (den Elzen et al., 2016; Vrontisi et al., 2018). Most G20 economies would require new policies and actions to achieve their NDC targets (den Elzen et al., 2016; Vandyck et al., 2016; UNEP, 2017b; Kuramochi et al., 2018). 2. The effect of NDCs on global greenhouse gas (GHG) emissions Several studies estimate global emission levels that would be achieved under the NDCs (e.g., den Elzen et al., 2016; Luderer et al., 2016; Rogelj et al., 2016, 2017; Vandyck et al., 2016; Rose et al., 2017; Vrontisi et al., 2018). Rogelj et al. (2016) and UNEP (2017b) concluded that the full implementation of the unconditional and conditional NDCs are expected to result in global GHG emissions of about 55 (52–58) and 53 (50–54) GtCO2-eq yr −1, respectively (Cross-Chapter Box 11, Figure 1 below). 65 – 25th percentile 60 – Median 61 – 75th percentile 60 NDC emission projections: 56 56 57 58 56 Unconditional NDCs 55 54 55 54 53 52 53 52 52 53 52 50 52 53 50 51 Conditional NDCs 50 48 49 50 48 4 47 47 48 45 44 44 42 40 Range of emissions (25th 38 39 percentile, median, 75th 37 35 percentile) in scenarios that 35 hold global mean temperature increase below 30 1.5oC and 2˚C 30 30 27 25 25 22 20 21 2010 2020 2020 2020 2020 2020 2020 2030 2030 2030 2030 2030 2030 Current Higher-2°C Lower-2°C 1.5°C-high-OS 1.5°C-low-OS Below-1.5°C Current Higher-2°C Lower-2°C 1.5°C-high-OS 1.5°C-low-OS Below-1.5°C policies policies Cross-Chapter Box 11, Figure 1 | GHG emissions are all expressed in units of CO2-equivalence computed with 100-year global warming potentials (GWPs) reported in IPCC SAR, while the emissions for the 1.5°C and 2°C scenarios in Table 2.4 are reported using the 100-year GWPs reported in IPCC AR4, and are hence about 3% higher. Using IPCC AR4 instead of SAR GWP values is estimated to result in a 2–3% increase in estimated 1.5°C and 2°C emissions levels in 2030. Source: based on Rogelj et al. (2016) and UNEP (2017b). 3. The effect of NDCs on temperature increase and carbon budget Estimates of global average temperature increase are 2.9°C–3.4°C above preindustrial levels with a greater than 66% probability by 2100 (Rogelj et al., 2016; UNEP, 2017b), under a full implementation of unconditional NDCs and a continuation of climate action similar to that of the NDCs. Full implementation of the conditional NDCs would lower the estimates by about 0.2°C by 2100. As an indication of the carbon budget implications of NDC scenarios, Rogelj et al. (2016) estimated cumulative emissions in the range 357 Global greenhouse gas emissions, including LULUCF- emissions (GtCO2-eq yr-1) Chapter 4 Strengthening and Implementing the Global Response Cross Chapter Box 11 (continued) of 690 to 850 GtCO2 for the period 2011–2030 if the NDCs are successfully implemented. The carbon budget for post-2010 till 2100 compatible with staying below 1.5°C with a 50–66% probability was estimated at 550–600 GtCO2 (Clarke et al., 2014; Rogelj et al., 2016), which will be well exceeded by 2030 at full implementation of the NDCs (Chapter 2, Section 2.2 and Section 2.3.1). 4. The 2030 emissions gap with 1.5°C and urgency of action As the 1.5°C pathways require reaching carbon neutrality by mid-century, the NDCs alone are not sufficient, as they have a time horizon until 2030. Rogelj et al. (2016) and Hof et al. (2017) have used results or compared NDC pathways with emissions pathways produced by integrated assessment models (IAMs) assessing the contribution of NDCs to achieve the 1.5°C targets. There is high agreement that current NDC emissions levels are not in line with pathways that limit warming to 1.5°C by the end of the century (Rogelj et al., 2016, 2017; Hof et al., 2017; UNEP, 2017b; Vrontisi et al., 2018). The median 1.5°C emissions gap (>66% chance) for the full implementation of both the conditional and unconditional NDCs for 2030 is 26 (19–29) to 28 (22–33) GtCO2-eq (Cross- Chapter Box 11, Figure 1 above). Studies indicate important trade-offs of delaying global emissions reductions (Chapter 2, Sections 2.3.5 and 2.5.1). AR5 identified flexibility in 2030 emission levels when pursuing a 2°C objective (Clarke et al., 2014) indicating that strongest trade-offs for 2°C pathways could be avoided if emissions are limited to below 50 GtCO2-eq yr −1 in 2030 (here computed with the GWP–100 metric of the IPCC SAR). New scenario studies show that full implementation of the NDCs by 2030 would imply the need for deeper and faster emission reductions beyond 2030 in order to meet 2°C, and also higher costs and efforts of negative emissions (Fujimori et al., 2016; Sanderson et al., 2016; Rose et al., 2017; van Soest et al., 2017; Luderer et al., 2018). However, no flexibility has been found for 1.5°C-consistent pathways (Luderer et al., 2016; Rogelj et al., 2017), indicating that if emissions through 2030 are at NDC levels, the resulting post-2030 reductions required to remain within a 1.5°C-consistent carbon budget during the 21st century (Chapter 2, Section 2.2) are not within the feasible operating space of IAMs. This indicates that the chances of failing to reach a 1.5°C pathway are significantly increased (Riahi et al., 2015), if near-term ambition is not strengthened beyond the level implied by current NDCs. Accelerated and stronger short-term action and enhanced longer-term national ambition going beyond the NDCs would be needed for 1.5°C-consistent pathways. Implementing deeper emissions reductions than current NDCs would imply action towards levels identified in Chapter 2, Section 2.3.3, either as part of or over-delivering on NDCs. 5. The impact of uncertainties on NDC emission levels 4 The measures proposed in NDCs are not legally binding (Nemet et al., 2017), further impacting estimates of anticipated 2030 emission levels. The aggregation of targets results in high uncertainty (Rogelj et al., 2017), which could be reduced with clearer guidelines for compiling future NDCs focused more on energy accounting (Rogelj et al., 2017) and increased transparency and comparability (Pauw et al., 2018). Many factors would influence NDCs global aggregated effects, including: (1) variations in socio-economic conditions (GDP and population growth), (2) uncertainties in historical emission inventories, (3) conditionality of certain NDCs, (4) definition of NDC targets as ranges instead of single values, (5) the way in which renewable energy targets are expressed, and (6) the way in which traditional biomass use is accounted for. Additionally, there are land-use mitigation uncertainties (Forsell et al., 2016; Grassi et al., 2017). Land-use options play a key role in many country NDCs; however, many analyses on NDCs do not use country estimates on land-use emissions, but use model estimates, mainly because of the large difference in estimating the ‘anthropogenic’ forest sink between countries and models (Grassi et al., 2017). 6. Comparing countries’ NDC ambition (equity, cost optimal allocation and other indicators) Various assessment frameworks have been proposed to analyse, benchmark and compare NDCs, and indicate possible strengthening, based on equity and other indicators (Aldy et al., 2016; den Elzen et al., 2016; Höhne et al., 2017; Jiang et al., 2017; Holz et al., 2018).There is large variation in conformity/fulfilment with equity principles across NDCs and countries. Studies use assessment frameworks based on six effort sharing categories in the AR5 (Clarke et al., 2014) with the principles of ‘responsibility’, ‘capability’ and ‘equity’ (Höhne et al., 2017; Pan et al., 2017; Robiou du Pont et al., 2017). There is an important methodological gap in the assessment of the NDCs’ fairness and equity implications, partly due to lack of information on countries’ own assessments (Winkler et al., 2017). Implementation of Article 2.2 of the Paris Agreement could reflect equity and the principle of ‘common but differentiated responsibilities and respective capabilities’, due to different national circumstances and different interpretations of equity principles (Lahn and Sundqvist, 2017; Lahn, 2018). 358 Strengthening and Implementing the Global Response Chapter 4 Cross Chapter Box 11 (continued) Adaptation The Paris Agreement recognizes adaptation by establishing a global goal for adaptation (Kato and Ellis, 2016; Rajamani, 2016; Kinley, 2017; Lesnikowski et al., 2017; UNEP, 2017a). This is assessed qualitatively, as achieving a temperature goal would determine the level of adaptation ambition required to deal with the consequent risks and impacts (Rajamani, 2016). Countries can include domestic adaptation goals in their NDCs, which together with national adaptation plans (NAPs) give countries flexibility to design and adjust their adaptation trajectories as their needs evolve and as progress is evaluated over time. A challenge for assessing progress on adaptation globally is the aggregation of many national adaptation actions and approaches. Knowledge gaps still remain about how to design measurement frameworks that generate and integrate national adaptation data without placing undue burdens on countries (UNEP, 2017a). The Paris Agreement stipulates that adaptation communications shall be submitted as a component of or in conjunction with other communications, such as an NDC, a NAP, or a national communication. Of the 197 Parties to the UNFCCC, 140 NDCs have an adaptation component, almost exclusively from developing countries. NDC adaptation components could be an opportunity for enhancing adaptation planning and implementation by highlighting priorities and goals (Kato and Ellis, 2016). At the national level they provide momentum for the development of NAPs and raise the profile of adaptation (Pauw et al., 2016b, 2018). The Paris Agreement’s transparency framework includes adaptation, through which ‘adaptation communication’ and accelerated adaptation actions are submitted and reviewed every five years (Hermwille, 2016; Kato and Ellis, 2016). This framework, unlike others used in the past, is applicable to all countries taking into account differing capacities amongst Parties (Rajamani, 2016). Adaptation measures presented in qualitative terms include sectors, risks and vulnerabilities that are seen as priorities by the Parties. Sectoral coverage of adaptation actions identified in NDCs is uneven, with adaptation primarily reported to focus on the water sector (71% of NDCs with adaptation component), agriculture (63%), health (54%), and biodiversity/ecosystems (50%) (Pauw et al., 2016b, 2018). 4.4.2 Enhancing Institutional Capacities 1.5°C-consistent pathways (mitigation) and enables the building of adaptive capacity that together, will enable sustainable development The implementation of sound responses and strategies to enable a and poverty reduction. 4 transition to 1.5°C world would require strengthening governance and scaling up institutional capacities, particularly in developing Rising to the challenge of a transition to a 1.5°C world would require countries (Adenle et al., 2017; Rosenbloom, 2017). Building on the enhancing institutional climate change capacities along multiple characterization of governance in Section 4.4.1, this section examines dimensions presented below. the necessary institutional capacity to implement actions to limit warming to 1.5°C and adapt to the consequences. This takes into 4.4.2.1 Capacity for policy design and implementation account a plurality of regional and local responses, as institutional capacity is highly context-dependent (North, 1990; Lustick et al., The enhancement of institutional capacity for integrated policy design 2011). and implementation has long been among the top items on the UN agenda of addressing global environmental problems and sustainable Institutions would need to interact with one another and align across development (see Chapter 5, Section 5.5) (UNEP, 2005). scales to ensure that rules and regulations are followed (Chaffin and Gunderson, 2016; Young, 2016). The institutional architecture Political stability, an effective regulatory and enforcement framework required for a 1.5°C world would include the growing proportion of (e.g., institutions to impose sanctions, collect taxes and to verify the world’s population that live in peri-urban and informal settlements building codes), access to a knowledge base and the availability of and engage in informal economic activity (Simone and Pieterse, 2017). resources, would be needed at various governance levels to address This population, amongst the most exposed to perturbed climates in a wide range of stakeholders and their concerns. The strengthening the world (Hallegatte et al., 2017), is also beyond the direct reach of the global response would need to support these with different of some policy instruments (Jaglin, 2014; Thieme, 2018). Strategies interventions, in the context of sustainable development (Chapter 5, that accommodate the informal rules of the game adopted by these Section 5.5.1) (Pasquini et al., 2015). populations have large chances of success (McGranahan et al., 2016; Kaika, 2017). Given the scale of change needed to limit warming to 1.5°C, strengthening the response capacity of relevant institutions is best The goal for strengthening implementation is to ensure that these rules addressed in ways that take advantage of existing decision-making and regulations embrace equity, equality and poverty alleviation along processes in local and regional governments and within cities and 359 Chapter 4 Strengthening and Implementing the Global Response communities (Romero-Lankao et al., 2013), and draws upon diverse settlements which are vulnerable to climate impacts. It is common knowledge sources including indigenous and local knowledge for 30–50% of urban populations in low-income nations to live in (Nakashima et al., 2012; Smith and Sharp, 2012; Mistry and Berardi, informal settlements with no regulatory infrastructure (Revi et al., 2016; Tschakert et al., 2017). Examples of successful local institutional 2014b). For example, in Huambo (Angola), a classified ‘urban’ area processes and the integration of local knowledge in climate-related extends 20 km west of the city and is predominantly made up of decision-making are provided in Box 4.3 and Box 4.4. ‘unplanned’ urban settlements (Smith and Jenkins, 2015). Implementing 1.5°C-consistent strategies would require well- Internationally, the Paris Agreement process has aimed at enhancing functioning legal frameworks to be in place, in conjunction with the capacity of decision-making institutions in developing countries clearly defined mandates, rights and responsibilities to enable the to support effective implementation. These efforts are particularly institutional capacity to deliver (Romero-Lankao et al., 2013). As reflected in Article 11 of the Paris Agreement on capacity building an example, current rates of urbanization occurring in cities with a (the creation of the Paris Committee on Capacity Building), Article 13 lack of institutional capacity for effective land-use planning, zoning (the creation of the Capacity Building Initiative on Transparency), and and infrastructure development result in unplanned, informal urban Article 15 on compliance (UNFCCC, 2016). Box 4.3 | Indigenous Knowledge and Community Adaptation Indigenous knowledge refers to the understandings, skills and philosophies developed by societies with long histories of interaction with their natural surroundings (UNESCO, 2017). This knowledge can underpin the development of adaptation and mitigation strategies (Ford et al., 2014b; Green and Minchin, 2014; Pearce et al., 2015; Savo et al., 2016). Climate change is an important concern for the Maya, who depend on climate knowledge for their livelihood. In Guatemala, the collaboration between the Mayan K’iché population of the Nahualate river basin and the Climate Change Institute has resulted in a catalogue of indigenous knowledge, used to identify indicators for watershed meteorological forecasts (López and Álvarez, 2016). These indicators are relevant but would need continuous assessment if their continued reliability is to be confirmed (Nyong et al., 2007; Alexander et al., 2011; Mistry and Berardi, 2016). For more than ten years, Guatemala has maintained an ‘Indigenous Table for Climate Change’, to enable the consideration of indigenous knowledge in disaster management and adaptation development. 4 In Tanzania, increased variability of rainfall is challenging indigenous and local communities (Mahoo et al., 2015; Sewando et al., 2016). The majority of agro-pastoralists use indigenous knowledge to forecast seasonal rainfall, relying on observations of plant phenology, bird, animal, and insect behaviour, the sun and moon, and wind (Chang’a et al., 2010; Elia et al., 2014; Shaffer, 2014). Increased climate variability has raised concerns about the reliability of these indicators (Shaffer, 2014); therefore, initiatives have focused on the co-production of knowledge by involving local communities in monitoring and discussing the implications of indigenous knowledge and meteorological forecasts (Shaffer, 2014), and creating local forecasts by utilizing the two sources of knowledge (Mahoo et al., 2013). This has resulted in increased documentation of indigenous knowledge, understanding of relevant climate information amongst stakeholders, and adaptive capacity at the community level (Mahoo et al., 2013, 2015; Shaffer, 2014). The Pacific Islands and small island developing states (SIDS) are vulnerable to the effects of climate change, but the cultural resilience of Pacific Island inhabitants is also recognized (Nunn et al., 2017). In Fiji and Vanuatu, strategies used to prepare for cyclones include building reserve emergency supplies and utilizing farming techniques to ensure adequate crop yield to combat potential losses from a cyclone or drought (McNamara and Prasad, 2014; Granderson, 2017; Pearce et al., 2017). Social cohesion and kinship are important in responding and preparing for climate-related hazards, including the role of resource sharing, communal labour, and remittances (McMillen et al., 2014; Gawith et al., 2016; Granderson, 2017). There is a concern that indigenous knowledge will weaken, a process driven by westernization and disruptions in established bioclimatic indicators and traditional planning calendars (Granderson, 2017). In some urban settlements, it has been noted that cultural practices (e.g., prioritizing the quantity of food over the quality of food) can lower food security through dispersing limited resources and by encouraging the consumption of cheap but nutrient-poor foods (Mccubbin et al., 2017) (See Cross-Chapter Box 6 on Food Security in Chapter 3). Indigenous practices also encounter limitations, particularly in relation to sea level rise (Nunn et al., 2017). 360 Strengthening and Implementing the Global Response Chapter 4 Box 4.4 | Manizales, Colombia: Supportive National Government and Localized Planning and Integration as an Enabling Condition for Managing Climate and Development Risks Institutional reform in the city of Manizales, Colombia, helps identify three important features of an enabling environment: integrating climate change adaptation, mitigation and disaster risk management at the city-scale; the importance of decentralized planning and policy formulation within a supportive national policy environment; and the role of a multi-sectoral framework in mainstreaming climate action in development activities. Manizales is exposed to risks caused by rapid development and expansion in a mountainous terrain exposed to seismic activity and periodic wet and dry spells. Local assessments expect climate change to amplify the risk of disasters (Carreño et al., 2017). The city is widely recognized for its longstanding urban environmental policy (Biomanizales) and local environmental action plan (Bioplan), and has been integrating environmental planning in its development agenda for nearly two decades (Velásquez Barrero, 1998; Hardoy and Velásquez Barrero, 2014). When the city’s environmental agenda was updated in 2014 to reflect climate change risks, assessments were conducted in a participatory manner at the street and neighbourhood level (Hardoy and Velásquez Barrero, 2016). The creation of a new Environmental Secretariat assisted in coordination and integration of environmental policies, disaster risk management, development and climate change (Leck and Roberts, 2015). Planning in Manizales remains mindful of steep gradients through its longstanding Slope Guardian programme that trains women and keeps records of vulnerable households. Planning also looks to include mitigation opportunities and enhance local capacity through participatory engagement (Hardoy and Velásquez Barrero, 2016). Manizales’ mayors were identified as important champions for much of these early integration and innovation efforts. Their role may have been enabled by Colombia’s history of decentralized approaches to planning and policy formulation, including establishing environmental observatories (for continuous environmental assessment) and participatory tracking of environmental indicators. Multi-stakeholder involvement has both enabled and driven progress, and has enabled the integration of climate risks in development planning (Hardoy and Velásquez Barrero, 2016). 4.4.2.2 Monitoring, reporting, and review institutions 4.4.2.3 Financial institutions 4 One of the novel features of the new climate governance architecture IPCC AR5 assessed that in order to enable a transition to a 2°C pathway, emerging from the 2015 Paris Agreement is the transparency the volume of climate investments would need to be transformed along framework in Article 13 committing countries, based on capacity, with changes in the pattern of general investment behaviour towards to provide regular progress reports on national pledges to address low emissions. The report argued that, compared to 2012, annually up climate change (UNFCCC, 2016). Many countries will rely on public to a trillion dollars in additional investment in low-emission energy and policies and existing national reporting channels to deliver on their energy efficiency measures may be required until 2050 (Blanco et al., NDCs under the Paris Agreement. Scaling up the mitigation and 2014; IEA, 2014a). Financing of 1.5°C would present an even greater adaptation efforts in these countries to be consistent with 1.5°C challenge, addressing financing of both existing and new assets, which would put significant pressure on the need to develop, enhance and would require significant transitions to the type and structure of financial streamline local, national and international climate change reporting institutions as well as to the method of financing (Cochrani et al., 2014; and monitoring methodologies and institutional capacity in relation Ma, 2014). Both public and private financial institutions would be needed to mitigation, adaptation, finance, and GHG inventories (Ford et al., to contribute to the large resource mobilization needed for 1.5°C, yet, in 2015b; Lesnikowski et al., 2015; Schoenefeld et al., 2016). Consistent the ordinary course of business, these transitions may not be expected. with this direction, the provision of the information to the stocktake On the one hand, private financial institutions could face scale-up risk, under Article 14 of the Paris Agreement would contribute to enhancing for example, the risks associated with commercialization and scaling reporting and transparency (UNFCCC, 2016). Nonetheless, approaches, up of renewable technologies to accelerate mitigation (Wilson, 2012; reporting procedures, reference points, and data sources to assess Hartley and Medlock, 2013) and/or price risk, such as carbon price progress on implementation across and within nations are still largely volatility that carbon markets could face. In contrast, traditional public underdeveloped (Ford et al., 2015b; Araos et al., 2016b; Magnan and financial institutions are limited by both structure and instruments, while Ribera, 2016; Lesnikowski et al., 2017). The availability of independent concessional financing would require taxpayer support for subsidization. private and public reporting and statistical institutions are integral to Special efforts and innovative approaches would be needed to address oversight, effective monitoring, reporting and review. The creation and these challenges, for example the creation of special institutions that enhancement of these institutions would be an important contribution underwrite the value of emission reductions using auctioned price floors to an effective transition to a low-emission world. (Bodnar et al., 2018) to deal with price volatility. 361 Chapter 4 Strengthening and Implementing the Global Response Financial institutions are equally important for adaptation. to self-interest of stakeholders to a more ‘rational’ conception of risk Linnerooth-Bayer and Hochrainer-Stigler (2015) discussed the assessment, measured across a risk-tolerance spectrum (Moffatt, 2014). benefits of financial instruments in adaptation, including the provision of post-disaster finances for recovery and pre-disaster Self-governing and self-organ¬ised institutional settings, where security necessary for climate adaptation and poverty reduction. equipment and resource systems are commonly owned and managed, Pre-disaster financial instruments and options include insurance, can poten¬tially generate a much higher diversity of administration such as index-based weather insurance schemes, catastrophe bonds, solutions, than other institutional arrangements, where energy and laws to encourage insurance purchasing. The development and technology and resource systems are either owned and administered enhancement of microfinance institutions to ensure social resilience individually in market settings or via a central authority (e.g., the and smooth transitions in the adaptation to climate change impacts state). They can also increase the adaptability of technological systems could be an important local institutional innovation (Hammill et al., while reducing their burden on the environment (Labanca, 2017). 2008). Educational, learning and awareness-building institutions can help strengthen the societal response to climate change (Butler et al., 2016; 4.4.2.4 Co-operative institutions and social safety nets Thi Hong Phuong et al., 2017). Effective cooperative institutions and social safety nets may help 4.4.3 Enabling Lifestyle and Behavioural Change address energy access and adaptation, as well as distributional impacts during the transition to 1.5°C-consistent pathways and enabling Humans are at the centre of global climate change: their actions cause sustainable development. Not all countries have the institutional anthropogenic climate change, and social change is key to effectively capabilities to design and manage these. Social capital for adaptation responding to climate change (Vlek and Steg, 2007; Dietz et al., 2013; in the form of bonding, bridging, and linking social institutions has ISSC and UNESCO, 2013; Hackmann et al., 2014). Chapter 2 shows proved to be effective in dealing with climate crises at the local, that 1.5°C-consistent pathways assume substantial changes in regional and national levels (Aldrich et al., 2016). behaviour. This section assesses the potential of behaviour change, as the integrated assessment models (IAMs) applied in Chapter 2 do not The shift towards sustainable energy systems in transitioning comprehensively asses this potential. economies could impact the livelihoods of large populations in traditional and legacy employment sectors. The transition of selected Table 4.8 shows examples of mitigation and adaption actions relevant EU Member States to biofuels, for example, caused anxiety among for 1.5°C-consistent pathways. Reductions in population growth can farmers, who lacked confidence in the biofuel crop market. Enabling reduce overall carbon demand and mitigate climate change (Bridgeman, contracts between farmers and energy companies, involving local 2017), particularly when population growth is accompanied by increases governments, helped create an atmosphere of confidence during the in affluence and carbon-intensive consumption (Rosa and Dietz, 2012; 4 transition (McCormick and Kåberger, 2007). Clayton et al., 2017). Mitigation actions with a substantial carbon emission reduction potential (see Figure 4.3) that individuals may How do broader socio-economic processes influence urban readily adopt would have the most climate impact (Dietz et al., 2009). vulnerabilities and thereby underpin climate change adaptation? This is a systemic challenge originating from a lack of collective Various policy approaches and strategies can encourage and enable societal ownership of the responsibility for climate risk management. climate actions by individuals and organizations. Policy approaches Explanations for this situation include competing time-horizons due would be more effective when they address key contextual and psycho- Table 4.8 | Examples of mitigation and adaptation behaviours relevant for 1.5°C (Dietz et al., 2009; Jabeen, 2014; Taylor et al., 2014; Araos et al., 2016b; Steg, 2016; Stern et al., 2016b; Creutzig et al., 2018) Climate action Type of action Examples Insulation Implementing resource efficiency in buildings Low-carbon building materials Electric vehicles Adopting low-emission innovations Heat pumps, district heating and cooling Energy-efficient heating or cooling Adopting energy efficient appliances Energy-efficient appliances Walking or cycling rather than drive short distances Mitigation Using mass transit rather than flying Energy-saving behaviour Lower temperature for space heating Line drying of laundry Reducing food waste Reducing meat and dairy consumption Buying products and materials with low GHG Buying local, seasonal food emissions during production and transport Replacing aluminium products by low-GHG alternatives Designing low-emission products and procedures Organisational behaviour Replacing business travel by videoconferencing 362 Strengthening and Implementing the Global Response Chapter 4 Table 4.8 (continued) Climate action Type of action Examples Growing different crops and raising different animal varieties Using crops with higher tolerance for higher temperatures or CO2 elevation Elevating barriers between rooms Flood protective behaviour Building elevated storage spaces Building drainage channels outside the home Adaptation Staying hydrated Heat protective behaviour Moving to cooler places Installing green roofs Rationing water Efficient water use during water shortage crisis Constructing wells or rainwater tanks Solar PV Adoption of renewable energy sources Mitigation & Solar water heaters adaptation Engage through civic channels to encourage or support planning for low-carbon Citizenship behaviour climate-resilient development 4 Figure 4.3 | Examples of mitigation behaviour and their GHG emission reduction potential. Mitigation potential assessments are printed in different units. Based on [1] Carlsson-Kanyama and González (2009); [2] Tuomisto and Teixeira de Mattos (2011); [3] Springmann et al. (2016); [4] Nijland and Meerkerk (2017); [5] Woodcock et al. (2009); [6] Salon et al. (2012); [7] Dietz et al. (2009); [8] Mulville et al. (2017); [9] Huebner and Shipworth (2017); [10] Jaboyedoff et al. (2004); [11] Pellegrino et al. (2016); [12] Nägele et al. (2017). social factors influencing climate actions, which differ across contexts In the United States and Europe, GHG emissions are lower when and individuals (Steg and Vlek, 2009; Stern, 2011). This suggests legislators have strong environmental records (Jensen and Spoon, 2011; that diverse policy approaches would be needed in 1.5°C-consistent Dietz et al., 2015). Political elites affect public concern about climate pathways in different contexts and regions. Combinations of policies change: pro-climate action statements increased concern, while anti- that target multiple barriers and enabling factors simultaneously can climate action statements and anti-environment voting reduced public be more effective (Nissinen et al., 2015). concern about climate change (Brulle et al., 2012). In the European 363 Chapter 4 Strengthening and Implementing the Global Response Union (EU), individuals worry more about climate change and engage climate concerns and actions (Blennow et al., 2012; Taylor et al., 2014), more in climate actions in countries where political party elites are more so than second-hand information (Spence et al., 2011; Myers et united rather than divided in their support for environmental issues al., 2012; Demski et al., 2017); high impact events with low frequency (Sohlberg, 2017). are remembered more than low impact regular events (Meze-Hausken, 2004; Singh et al., 2016b; Sullivan-Wiley and Short Gianotti, 2017). This section discusses how to enable and encourage behaviour and Personal experience with climate hazards strengthens motivation to lifestyle changes that strengthen implementation of 1.5°C-consistent protect oneself (Jabeen, 2014) and enhances adaptation actions (Bryan pathways by assessing psycho-social factors related to climate action, et al., 2009; Berrang-Ford et al., 2011; Demski et al., 2017), although as well as the effects and acceptability of policy approaches targeting this does not always translate into proactive adaptation (Taylor et climate actions that are consistent with 1.5°C. Box 4.5 and Box 4.6 al., 2014). Collectively constructed notions of risk and expectations illustrate how these have worked in practice. of future climate variability shape risk perception and adaptation behaviour (Singh et al., 2016b). People with particular political views 4.4.3.1 Factors related to climate actions and those who emphasize individual autonomy may reject climate science knowledge and believe that there is widespread scientific Mitigation and adaptation behaviour is affected by many factors that disagreement about climate change (Kahan, 2010; O’Neill et al., 2013), shape which options are feasible and considered by individuals. Besides inhibiting support for climate policy (Ding et al., 2011; McCright et al., contextual factors (see other sub-sections in Section 4.4), these include 2013). This may explain why extreme weather experiences enhances abilities and different types of motivation to engage in behaviour. preparedness to reduce energy use among left- but not right-leaning voters (Ogunbode et al., 2017). Ability to engage in climate action. Individuals more often engage in adaptation (Gebrehiwot and van der Veen, 2015; Koerth et al., Motivation to engage in climate action. Climate actions are 2017) and mitigation behaviour (Pisano and Lubell, 2017) when they more strongly related to motivational factors than to knowledge, are or feel more capable to do so. Hence, it is important to enhance reflecting individuals’ reasons for actions, such as values, ideology ability to act on climate change, which depends on income and and worldviews (Hornsey et al., 2016). People consider various types knowledge, among other things. A higher income is related to higher of costs and benefits of actions (Gölz and Hahnel, 2016) and focus CO2 emissions; higher income groups can afford more carbon-intensive on consequences that have implications for the values they find most lifestyles (Lamb et al., 2014; Dietz et al., 2015; Wang et al., 2015). Yet important (Dietz et al., 2013; Hahnel et al., 2015; Steg, 2016). This low-income groups may lack resources to invest in energy-efficient implies that different individuals consider different consequences when technology and refurbishments (Andrews-Speed and Ma, 2016) and making choices. People who strongly value protecting the environment adaptation options (Wamsler, 2007; Fleming et al., 2015b; Takahashi et and other people generally more strongly consider climate impacts and al., 2016). Adaptive capacity further depends on gender roles (Jabeen, act more on climate change than those who strongly endorse hedonic 4 2014; Bunce and Ford, 2015), technical capacities and knowledge and egoistic values (Taylor et al., 2014; Steg, 2016). People are more (Feola et al., 2015; Eakin et al., 2016; Singh et al., 2016b). prone to adopt sustainable innovations when they are more open to new ideas (Jansson, 2011; Wolske et al., 2017). Further, a free-market Knowledge of the causes and consequences of climate change and ideology is associated with weaker climate change beliefs (McCright of ways to reduce GHG emissions is not always accurate (Bord et al., and Dunlap, 2011; Hornsey et al., 2016), and a capital-oriented culture 2000; Whitmarsh et al., 2011; Tobler et al., 2012), which can inhibit tends to promote activity associated with GHG emissions (Kasser et climate actions, even when people would be motivated to act. For al., 2007). example, people overestimate savings from low-energy activities, and underestimate savings from high-energy activities (Attari et al., Some indigenous populations believe it is arrogant to predict the 2010). They know little about ‘embodied’ energy (i.e., energy needed future, and some cultures have belief systems that interpret natural to produce products; Tobler et al., 2011), including meat (de Boer et phenomena as sentient, where thoughts and words are believed to al., 2016b). Some people mistake weather for climate (Reynolds et al., influence the future, with people reluctant to talk about negative future 2010), or conflate climate risks with other hazards, which can inhibit possibilities (Natcher et al., 2007; Flynn et al., 2018). Integrating these adequate adaptation (Taylor et al., 2014). considerations into the design of adaptation and mitigation policy is important (Cochran et al., 2013; Chapin et al., 2016; Brugnach et al., More knowledge on adaptation is related to higher engagement in 2017; Flynn et al., 2018). adaptation actions in some circumstances (Bates et al., 2009; van Kasteren, 2014; Hagen et al., 2016). How adaptation is framed in People are more prone to act on climate change when individual benefits the media can influence the types of options viewed as important in of actions exceed costs (Steg and Vlek, 2009; Kardooni et al., 2016; different contexts (Boykoff et al., 2013; Moser, 2014; Ford and King, Wolske et al., 2017). For this reason, people generally prefer adoption of 2015). energy-efficient appliances above energy-consumption reductions; the latter is perceived as more costly (Poortinga et al., 2003; Steg et al., Knowledge is important, but is often not sufficient to motivate action 2006), although transaction costs can inhibit the uptake of mitigation (Trenberth et al., 2016). Climate change knowledge and perceptions technology (Mundaca, 2007). Decentralized renewable energy systems are not strongly related to mitigation actions (Hornsey et al., 2016). are evaluated most favourably when they guarantee independence, Direct experience of events related to climate change influences autonomy, control and supply security (Ecker et al., 2017). 364 Strengthening and Implementing the Global Response Chapter 4 Besides, social costs and benefits affect climate action (Farrow et al., Habits, heuristics and biases. Decisions are often not based on 2017). People engage more in climate actions when they think others weighing costs and benefits, but on habit or automaticity, both of expect them to do so and when others act as well (Nolan et al., 2008; individuals (Aarts and Dijksterhuis, 2000; Kloeckner et al., 2003) Le Dang et al., 2014; Truelove et al., 2015; Rai et al., 2016), and when and within organizations (Dooley, 2017) and institutions (Munck they experience social support (Singh et al., 2016a; Burnham and Ma, et al., 2014). When habits are strong, individuals are less perceptive 2017; Wolske et al., 2017). Discussing effective actions with peers also of information (Verplanken et al., 1997; Aarts et al., 1998) and may encourages climate action (Esham and Garforth, 2013), particularly not consider alternatives as long as outcomes are good enough when individuals strongly identify with their peers (Biddau et al., (Maréchal, 2010). Habits are mostly only reconsidered when the 2012; Fielding and Hornsey, 2016). Further, individuals may engage situation changed significantly (Fujii and Kitamura, 2003; Maréchal, in mitigation actions when they think doing so would enhance their 2010; Verplanken and Roy, 2016). Hence, strategies that create the reputation (Milinski et al., 2006; Noppers et al., 2014; Kastner and opportunity for reflection and encourage active decisions can break Stern, 2015). Such social costs and benefits can be addressed in climate habits (Steg et al., 2018). policy (see Section 4.4.3.2). Individuals can follow heuristics, or ‘rules of thumb’, in making Feelings affect climate action (Brosch et al., 2014). Negative feelings inferences, which demand less cognitive resources, knowledge related to climate change can encourage adaptation action (Kerstholt and time than thinking through all implications of actions (Preston et al., 2017; Zhang et al., 2017), while positive feelings associated with et al., 2013; Frederiks et al., 2015; Gillingham and Palmer, 2017). climate risks may inhibit protective behaviour (Lefevre et al., 2015). For example, people tend to think that larger and more visible Individuals are more prone to engage in mitigation actions when they appliances use more energy, which is not always accurate (Cowen worry about climate change (Verplanken and Roy, 2013) and when and Gatersleben, 2017). They underestimate energy used for water they expect to derive positive feelings from such actions (Pelletier et heating and overestimate energy used for lighting (Stern, 2014). al., 1998; Taufik et al., 2016). When facing choice overload, people may choose the easiest or first available option, which can inhibit energy-saving behaviour (Stern Furthermore, collective consequences affect climate actions and Gardner, 1981; Frederiks et al., 2015). As a result, individuals (Balcombe et al., 2013; Dóci and Vasileiadou, 2015; Kastner and and firms often strive for satisficing (‘good enough’) outcomes with Stern, 2015). People are motivated to see themselves as morally regard to energy decisions (Wilson and Dowlatabadi, 2007; Klotz, right, which encourages mitigation actions (Steg et al., 2015), 2011), which can inhibit investments in energy efficiency (Decanio, particularly when long-term goals are salient (Zaval et al., 2015) and 1993; Frederiks et al., 2015). behavioural costs are not too high (Diekmann and Preisendörfer, 2003). Individuals are more prone to engage in climate actions when Biases also play a role. In Mozambique, farmers displayed omission they believe climate change is occurring, when they are aware of biases (unwillingness to take adaptation actions with potentially threats caused by climate change and by their inaction, and when negative consequences to avoid personal responsibility for losses), 4 they think they can engage in actions that will reduce these threats while policymakers displayed action biases (wanting to demonstrate (Esham and Garforth, 2013; Arunrat et al., 2017; Chatrchyan et al., positive action despite potential negative consequences; Patt and 2017). The more individuals are concerned about climate change and Schröter, 2008). People tend to place greater value on relative losses aware of the negative climate impact of their behaviour, the more than gains (Kahneman, 2003). Perceived gains and losses depend on they feel responsible for their actions and think that their actions can the reference point or status-quo (Kahneman, 2003). Loss aversion help reduce such negative impacts, which can strengthen their moral and the status-quo bias prevent consumers from switching electricity norms to act accordingly (Steg and de Groot, 2010; Jakovcevic and suppliers (Ek and Söderholm, 2008), to time-of-use electricity tariffs Steg, 2013; Chen, 2015; Ray et al., 2017; Wolske et al., 2017; Woods (Nicolson et al., 2017), and to accept new energy systems (Leijten et et al., 2017). Individuals may engage in mitigation actions when al., 2014). they see themselves as supportive of the environment (i.e., strong environmental self-identity) (Fielding et al., 2008; van der Werff et Owned inefficient appliances and fossil fuel-based electricity can act as al., 2013b; Kashima et al., 2014; Barbarossa et al., 2017); a strong endowments, increasing their value compared to alternatives (Pichert environmental identity strengthens intrinsic motivation to engage and Katsikopoulos, 2008; Dinner et al., 2011). Uncertainty and loss in mitigation actions both at home (van der Werff et al., 2013a) aversion lead consumers to undervalue future energy savings (Greene, and at work (Ruepert et al., 2016). Environmental self-identity is 2011) and savings from energy efficient technologies (Kolstad et al., strengthened when people realize they have engaged in mitigation 2014). Uncertainties about the performance of products and illiquidity actions, which can in turn promote further mitigation actions (van der of investments can drive consumers to postpone (profitable) energy- Werff et al., 2014b). efficient investments (Sutherland, 1991; van Soest and Bulte, 2001). People with a higher tendency to delay decisions may engage less Individuals are less prone to engage in adaptation behaviour in energy saving actions (Lillemo, 2014). Training energy auditors in themselves when they rely on external measures such as government loss-aversion increased their clients’ investments in energy efficiency interventions (Grothmann and Reusswig, 2006; Wamsler and Brink, improvements (Gonzales et al., 1988). Engagement in energy saving 2014a; Armah et al., 2015; Burnham and Ma, 2017) or perceive and renewable energy programmes can be enhanced if participation is themselves as protected by god (Gandure et al., 2013; Dang et al., set as a default option (Pichert and Katsikopoulos, 2008; Ölander and 2014; Cannon, 2015). Thøgersen, 2014; Ebeling and Lotz, 2015). 365 Chapter 4 Strengthening and Implementing the Global Response 4.4.3.2 Strategies and policies to promote actions overlooked (Stern et al., 2016a). For example, promising energy- on climate change saving or low-carbon technology may not be adopted or not be used as intended (Pritoni et al., 2015) when people lack resources and Policy can enable and strengthen motivation to act on climate change trustworthy information (Stern, 2011; Balcombe et al., 2013). via top-down or bottom-up approaches, through informational campaigns, regulatory measures, financial (dis)incentives, and Financial incentives or feedback on financial savings can encourage infrastructural and technological changes (Adger et al., 2003; Steg and climate action (Santos, 2008; Bolderdijk et al., 2011; Maki et al., Vlek, 2009; Henstra, 2016). 2016) (see Box 4.5), but are not always effective (Delmas et al., 2013) and can be less effective than social rewards (Handgraaf et Adaptation efforts tend to focus on infrastructural and technological al., 2013) or emphasising benefits for people and the environment solutions (Ford and King, 2015) with lower emphasis on socio-cognitive (Bolderdijk et al., 2013b; Asensio and Delmas, 2015; Schwartz et and finance aspects of adaptation. For example, flooding policies in al., 2015). The latter can happen when financial incentives reduce cities focus on infrastructure projects and regulation such as building a focus on environmental considerations and weaken intrinsic codes, and hardly target individual or household behaviour (Araos et motivation to engage in climate action (Evans et al., 2012; Agrawal al., 2016b; Georgeson et al., 2016). et al., 2015; Schwartz et al., 2015). In addition, pursuing small financial gains is perceived to be less worth the effort than pursuing Current mitigation policies emphasize infrastructural and technology equivalent CO2 emission reductions (Bolderdijk et al., 2013b; Dogan development, regulation, financial incentives and information et al., 2014). Also, people may not respond to financial incentives provision (Mundaca and Markandya, 2016) that can create conditions (e.g., to improve energy efficiency) because they do not trust the enabling climate action, but target only some of the many factors organization sponsoring incentive programmes (Mundaca, 2007) or influencing climate actions (see Section 4.4.5.1). They fall short of when it takes too much effort to receive the incentive (Stern et al., their true potential if their social and psychological implications are 2016a). Box 4.5 | How Pricing Policy has Reduced Car Use in Singapore, Stockholm and London In Singapore, Stockholm and London, car ownership, car use, and GHG emissions have reduced because of pricing and regulatory policies and policies facilitating behaviour change. Notably, acceptability of these policies has increased as people experienced their positive effects. 4 Singapore implemented electronic road pricing in the central business district and at major expressways, a vehicle quota and registration fee system, and investments in mass transit. In the vehicle quota system introduced in 1990, registration of new vehicles is conditional upon a successful bid (via auctioning) (Chu, 2015), costing about 50,000 USD in 2014 (LTA, 2015). The registration tax incentivizes purchases of low-emission vehicles via a feebate system. As a result, per capita transport emissions (approximately 1.25 tCO2yr −1) and car ownership (107 vehicles per 1000 capita) (LTA, 2017) are substantially lower than in cities with comparable income levels. Modal share of public transport was 63% during peak hours in 2013 (LTA, 2013). The Stockholm congestion charge implemented in 2007 (after a trial in 2006) reduced kilometres driven in the inner city by 16%, and outside the city by 5%; traffic volumes reduced by 20% and remained constant over time despite economic and population growth (Eliasson, 2014). CO2 emissions from traffic reduced by 2–3% in Stockholm county. Vehicles entering or leaving the city centre were charged during weekdays (except for holidays). Charges were 1–2€ (maximum 6€ per day), being higher during peak hours; taxis, emergency vehicles and buses were exempted. Before introducing the charge, public transport and parking places near mass transit stations were extended. The aim and effects of the charge were extensively communicated to the public. Acceptability of the congestion charge was initially low, but the scheme gained support of about two-thirds of the population and all political parties after it was implemented (Eliasson, 2014), which may be related to the fact that the revenues were earmarked for constructing a motorway tunnel. After the trial, people believed that the charge had more positive effects on environmental, congestion and parking problems while costs increased less than they anticipated beforehand (Schuitema et al., 2010a). The initially hostile media eventually declared the scheme to be a success. In 2003, a congestion charge was implemented in the Greater London area, with an enforcement and compliance scheme and an information campaign on the functioning of the scheme. Vehicles entering, leaving, driving or parking on a public road in the zone at weekdays at daytime pay a congestion charge of 8£ (until 2005, 5£), with some exemptions. Revenues were invested in London’s bus network (80%), cycling facilities, and road safety measures (Leape, 2006). The number of cars entering the zone decreased by 18% in 2003 and 2004. In the charging zone, vehicle kilometres driven decreased by 15% in the first year and a further 6% a year later, while CO2 emissions from road traffic reduced by 20% (Santos, 2008). 366 Strengthening and Implementing the Global Response Chapter 4 While providing information on the causes and consequences of climate when they involve face-to-face interaction (Abrahamse and Steg, 2013). change or on effective climate actions generally increases knowledge, For example, community approaches, where change is initiated from it often does not encourage engagement in climate actions by the bottom-up, can promote adaptation (see Box 4.6) and mitigation individuals (Abrahamse et al., 2005; Ünal et al., 2017) or organizations actions (Middlemiss, 2011; Seyfang and Haxeltine, 2012; Abrahamse (Anderson and Newell, 2004). Similarly, media coverage on the UN and Steg, 2013), especially when community ties are strong (Weenig Climate Summit slightly increased knowledge about the conference and Midden, 1991). Furthermore, providing social models of desired but did not enhance motivation to engage personally in climate actions can encourage mitigation action (Osbaldiston and Schott, protection (Brüggemann et al., 2017). Fear-inducing representations of 2012; Abrahamse and Steg, 2013). Social influence approaches that do climate change may inhibit action when they make people feel helpless not involve social interaction, such as social norm, social comparison and overwhelmed (O’Neill and Nicholson-Cole, 2009). Energy-related and group feedback, are less effective, but can be easily administered recommendations and feedback (e.g., via performance contracts, on a large scale at low costs (Allcott, 2011; Abrahamse and Steg, 2013). energy audits, smart metering) are more effective for promoting energy conservation, load shifting in electricity use and sustainable travel Goal setting can promote mitigation action when goals are not set choices when framed in terms of losses rather than gains (Gonzales et too low or too high (Loock et al., 2013). Commitment strategies where al., 1988; Wolak, 2011; Bradley et al., 2016; Bager and Mundaca, 2017). people make a pledge to engage in climate actions can encourage mitigation behaviour (Abrahamse and Steg, 2013; Lokhorst et al., 2013), Credible and targeted information at the point of decision can promote particularly when individuals also indicate how and when they will climate action (Stern et al., 2016a). For example, communicating the perform the relevant action and anticipate how to cope with possible impacts of climate change is more effective when provided right barriers (i.e., implementation intentions) (Bamberg, 2000, 2002). Such before adaptation decisions are taken (e.g., before the agricultural strategies take advantage of individuals’ desire to be consistent (Steg, season) and when bundled with information on potential actions to 2016). Similarly, hypocrisy-related strategies that make people aware of ameliorate impacts, rather than just providing information on climate inconsistencies between their attitudes and behaviour can encourage projections with little meaning to end users (e.g., weather forecasts, mitigation actions (Osbaldiston and Schott, 2012). seasonal forecasts, decadal climate trends) (Dorward et al., 2015; Singh et al., 2017). Similarly, heat action plans that provide early alerts Actions that reduce climate risks can be rewarded and facilitated, while and advisories combined with emergency public health measures can actions that increase climate risks can be punished and inhibited, and reduce heat-related morbidity and mortality (Benmarhnia et al., 2016). behaviour change can be voluntary (e.g., information provision) or imposed (e.g., by law); voluntary changes that involve rewards are Information provision is more effective when tailored to the personal more acceptable than imposed changes that restrict choices (Eriksson situation of individuals, demonstrating clear impacts, and resonating et al., 2006, 2008; Steg et al., 2006; Dietz et al., 2007). Policies punishing with individuals’ core values (Daamen et al., 2001; Abrahamse et al., maladaptive behaviour can increase vulnerability when they reinforce 2007; Bolderdijk et al., 2013a; Dorward et al., 2015; Singh et al., 2017). socio-economic inequalities that typically produce the maladaptive 4 Tailored information prevents information overload, and people are behaviour in the first place (Adger et al., 2003). Change can be initiated more motivated to consider and act upon information that aligns with by governments at various levels, but also by individuals, communities, their core values and beliefs (Campbell and Kay, 2014; Hornsey et al., profit-making organizations, trade organizations, and other non- 2016). Also, tailored information can remove barriers to receive and governmental actors (Lindenberg and Steg, 2013; Robertson and interpret information faced by vulnerable groups, such as the elderly Barling, 2015; Stern et al., 2016b). during heatwaves (Vandentorren et al., 2006; Keim, 2008). Further, prompts can be effective when they serve as reminders to perform a Strategies can target intrinsic versus extrinsic motivation. It may be planned action (Osbaldiston and Schott, 2012). particularly important to enhance intrinsic motivation so that people voluntarily engage in climate action over and again (Steg, 2016). Feedback provision is generally effective in promoting mitigation Endorsement of mitigation and adaptation actions are positively behaviour within households (Abrahamse et al., 2005; Delmas et al., related (Brügger et al., 2015; Carrico et al., 2015); both are positively 2013; Karlin et al., 2015) and at work (Young et al., 2015), particularly related to concern about climate change (Brügger et al., 2015). when provided in real-time or immediately after the action (Abrahamse Strategies that target general antecedents that affect a wide range et al., 2005), which makes the implications of one’s behaviour more of actions, such as values, identities, worldviews, climate change salient (Tiefenbeck et al., 2016). Simple information is more effective beliefs, awareness of the climate impacts of one’s actions, and feelings than detailed and technical data (Wilson and Dowlatabadi, 2007; Ek of responsibility to act on climate change, can encourage consistent and Söderholm, 2010; Frederiks et al., 2015). Energy labels (Banerjee actions on climate change (van Der Werff and Steg, 2015; Hornsey and Solomon, 2003; Stadelmann, 2017), visualization techniques (Pahl et al., 2016; Steg, 2016). Initial climate actions can lead to further et al., 2016), and ambient persuasive technology (Midden and Ham, commitment to climate action (Juhl et al., 2017), when people learn 2012) can encourage mitigation actions by providing information that such actions are easy and effective (Lauren et al., 2016), when they and feedback in a format that immediately makes sense and hardly engaged in the initial behaviour for environmental reasons (Peters et requires users’ conscious attention. al., 2018), hold strong pro-environmental values and norms (Thøgersen and Ölander, 2003), and when initial actions make them realise they Social influence approaches that emphasize what other people do or are an environmentally sensitive person, motivating them to act on think can encourage climate action (Clayton et al., 2015), particularly climate change in subsequent situations so as to be consistent (van der 367 Chapter 4 Strengthening and Implementing the Global Response Box 4.6 | Bottom-up Initiatives: Adaptation Responses Initiated by Individuals and Communities To effectively adapt to climate change, bottom-up initiatives by individuals and communities are essential, in addition to efforts of governments, organizations, and institutions (Wamsler and Brink, 2014a). This box presents examples of bottom-up adaptation responses and behavioural change. Fiji increasingly faces a lack of freshwater due to decreasing rainfall and rising temperatures (Deo, 2011; IPCC, 2014a). While some villages have access to boreholes, these are not sufficient to supply the population with freshwater. Villagers are adapting by rationing water, changing diets, and setting up inter-village sharing networks (Pearce et al., 2017). Some villagers take up wage employment to buy food instead of growing it themselves (Pearce et al., 2017). In Kiribati, residents adapt to drought by purchasing rainwater tanks and constructing additional wells (Kuruppu and Liverman, 2011). An important factor that motivated residents of Kiribati to adapt to drought was the perception that they could effectively adapt to the negative consequences of climate change (Kuruppu and Liverman, 2011). In the Philippines, seismic activity has caused some islands to flood during high tide. While the municipal government offered affected island communities the possibility to relocate to the mainland, residents preferred to stay and implement measures themselves in their local community to reduce flood damage (Laurice Jamero et al., 2017). Migration is perceived as undesirable because island communities have strong place-based identities (Mortreux and Barnett, 2009). Instead, these island communities have adapted to flooding by constructing stilted houses and raising floors, furniture, and roads to prevent water damage (Laurice Jamero et al., 2017). While inundation was in this case caused by seismic activity, this example indicates how island-based communities may respond to rising sea levels caused by climate change. Adaptation initiatives by individuals may temporarily reduce the impacts of climate change and enable residents to cope with changing environmental circumstances. However, they may not be sufficient to sustain communities’ way of life in the long term. For instance, in Fiji and Kiribati, freshwater and food are projected to become even scarcer in the future, rendering individual adaptations ineffective. Moreover, individuals can sometimes engage in behaviour that may be maladaptive over larger spatio-temporal scales. For example, in the Philippines, many islanders adapt to flooding by elevating their floors using coral stone (Laurice Jamero et al., 2017). Over time, this can harm the survivability of their community, as coral reefs are critical for reducing flood vulnerability (Ferrario et al., 2014). In Maharashtra, India, on-farm ponds are promoted as rainwater harvesting structures to adapt to dry spells during the monsoon season. However, some individuals fill these ponds with groundwater, leading to depletion of water tables and 4 potentially maladaptive outcomes in the long run (Kale, 2015). Integration of individuals’ adaptation initiatives with top-down adaptation policy is critical (Butler et al., 2015), as failing to do so may lead individual actors to mistrust authority and can discourage them from undertaking adequate adaptive actions (Wamsler and Brink, 2014a). Werff et al., 2014a; Lacasse, 2015, 2016). Yet some studies suggest that 2011) or redistributed towards those affected (Schuitema and Steg, people may feel licensed not to engage in further mitigation actions 2008). Acceptability can increase when people experience positive when they believe they have already done their part (Truelove et al., effects after a policy has been implemented (Schuitema et al., 2010a; 2014). Eliasson, 2014; Weber, 2015); effective policy trials can thus build public support for climate policy (see Box 4.8). 4.4.3.3 Acceptability of policy and system changes Climate policy and renewable energy systems are more acceptable Public acceptability can shape, enable or prevent policy and system when people strongly value other people and the environment, or changes. Acceptability reflects the extent to which policy or system support egalitarian worldviews, left-wing or green political ideologies changes are evaluated (un)favourably. Acceptability is higher when (Drews and Van den Bergh, 2016), and less acceptable when people people expect more positive and less negative effects of policy strongly endorse self-enhancement values, or support individualistic and system changes (Perlaviciute and Steg, 2014; Demski et al., and hierarchical worldviews (Dietz et al., 2007; Perlaviciute and Steg, 2015; Drews and Van den Bergh, 2016), including climate impacts 2014; Drews and Van den Bergh, 2016). Solar radiation modification (Schuitema et al., 2010b). Because of this, policy ‘rewarding’ is more acceptable when people strongly endorse self-enhancement climate actions is more acceptable than policy ‘punishing’ actions values, and less acceptable when they strongly value other people that increase climate risks (Steg et al., 2006; Eriksson et al., 2008). and the environment (Visschers et al., 2017). Climate policy is more Pricing policy is more acceptable when revenues are earmarked for acceptable when people believe climate change is real, when they environmental purposes (Steg et al., 2006; Sælen and Kallbekken, are concerned about climate change (Hornsey et al., 2016), when 368 Strengthening and Implementing the Global Response Chapter 4 they think their actions may reduce climate risks, and when they feel (Kauffman, 2002; Arthur, 2009). To illustrate such a process of responsible to act on climate change (Steg et al., 2005; Eriksson et co-evolution: the progress of computer simulation enables us to better al., 2006; Jakovcevic and Steg, 2013; Drews and Van den Bergh, 2016; understand climate, agriculture, and material sciences, contributing Kim and Shin, 2017). Stronger environmental awareness is associated to upgrading food production and quality, microscale manufacturing with a preference for governmental regulation and behaviour change techniques, and leading to much faster computing technologies, rather than free-market and technological solutions (Poortinga et al., resulting, for instance, in better performing photovoltaic (PV) cells. 2002). A variety of technological developments have and will contribute to Climate policy is more acceptable when costs and benefits are 1.5°C-consistent climate action or the lack of it. They can do this, for distributed equally, when nature and future generations are example, in the form of applications such as smart lighting systems, protected (Sjöberg and Drottz-Sjöberg, 2001; Schuitema et al., 2011; more efficient drilling techniques that make fossil fuels cheaper, or Drews and Van den Bergh, 2016), and when fair procedures have precision agriculture. As discussed in Section 4.3.1, costs of PV (IEA, been followed, including participation by the public (Dietz, 2013; 2017f) and batteries (Nykvist and Nilsson, 2015) have sharply dropped. Bernauer et al., 2016a; Bidwell, 2016) or public society organizations In addition, costs of fuel cells (Iguma and Kidoshi, 2015; Wei et al., 2017) (Bernauer and Gampfer, 2013). Providing benefits to compensate and shale gas and oil (Wang et al., 2014; Mills, 2015) have come down affected communities for losses due to policy or systems changes as a consequence of innovation. enhanced public acceptability in some cases (Perlaviciute and Steg, 2014), although people may disagree on what would be a worthwhile 4.4.4.2 Technologies as enablers of climate action compensation (Aitken, 2010; Cass et al., 2010), or feel they are being bribed (Cass et al., 2010; Perlaviciute and Steg, 2014). Since AR5, literature has emerged as to how much future GHG emission reductions can be enabled by the rapid progress of general purpose Public support is higher when individuals trust responsible parties technologies (GPTs), consisting of information and communication (Perlaviciute and Steg, 2014; Drews and Van den Bergh, 2016). Yet, technologies (ICT), including artificial intelligence (AI) and the internet public support for multilateral climate policy is not higher than for of things (IoT), nanotechnologies, biotechnologies, robotics, and so forth unilateral policy (Bernauer and Gampfer, 2015); public support for (WEF, 2015; OECD, 2017c). Although these may contribute to limiting unilateral, non-reciprocal climate policy is rather strong and robust warming to 1.5°C, the potential environmental, social and economic (Bernauer et al., 2016b). Public opposition may result from a culturally impacts of new technologies are uncertain. valued landscape being affected by adaptation or mitigation options, such as renewable energy development (Warren et al., 2005; Devine- Rapid improvement of performance and cost reduction is observed wright and Howes, 2010) or coastal protection measures (Kimura, for many GPTs. They include AI, sensors, internet, memory storage 2016), particularly when people have formed strong emotional bonds and microelectromechanical systems. The latter GPTs are not usually with the place (Devine-Wright, 2009, 2013). categorized as climate technologies, but they can impact GHG emissions. 4 Climate actions may reduce human well-being when such actions Progress of GPT could help reduce GHG emissions more cost- involve more costs, effort or discomfort. Yet some climate actions effectively. Examples are shown in Table 4.9. It may however, result in enhance well-being, such as technology that improves daily comfort more emissions by increasing the volume of economic activities, with and nature-based solutions for climate adaptation (Wamsler and Brink, unintended negative consequence on sustainable development. While 2014b). Further, climate action may enhance well-being (Kasser and ICT increases electricity consumption (Aebischer and Hilty, 2015), the Sheldon, 2002; Xiao et al., 2011; Schmitt et al., 2018) because pursuing energy consumption of ICT is usually dwarfed by the energy saving by meaning by acting on climate change can make people feel good ICT (Koomey et al., 2013; Malmodin et al., 2014), but rebound effects (Venhoeven et al., 2013, 2016; Taufik et al., 2015), more so than merely and other sustainable development impacts may be significant. An pursuing pleasure. appropriate policy framework that accommodates such impacts and their uncertainties could address the potential negative impacts by GPT 4.4.4 Enabling Technological Innovation (Jasanoff, 2007). This section focuses on the role of technological innovation in limiting GHG emission reduction potentials in relation to GPTs were estimated warming to 1.5°C, and how innovation can contribute to strengthening for passenger cars using a combination of three emerging technologies: implementation to move towards or to adapt to 1.5°C worlds. This electric vehicles, car sharing, and self-driving. GHG emission reduction assessment builds on information of technological innovation and potential is reported, assuming generation of electricity with low GHG related policy debates in and after AR5 (Somanathan et al., 2014). emissions (Greenblatt and Saxena, 2015; ITF, 2015; Viegas et al., 2016; Fulton et al., 2017). It is also possible that GHG emissions increase due 4.4.4.1 The nature of technological innovations to an incentive to car use. Appropriate policies such as urban planning and efficiency regulations could contain such rebound effects (Wadud Technological systems have their own dynamics. New technologies et al., 2016). have been described as emerging as part of a ‘socio-technical system’ that is integrated with social structures and that itself evolves over time Estimating emission reductions by GPT is difficult due to substantial (Geels and Schot, 2007). This progress is cumulative and accelerating uncertainties, including projections of future technological performance, 369 Chapter 4 Strengthening and Implementing the Global Response Table 4.9 | Examples of technological innovations relevant to 1.5°C enabled by general purpose technologies (GPT). Note: lists of enabling GPT or adaptation/mitigation options are not exhaustive, and the GPTs by themselves do not reduce emissions or increase climate change resilience. Sector Examples of Mitigation/Adaptation Technological Innovation Enabling GPT Energy and CO2 efficiency of logistics, warehouse and shops (GeSI, 2015; IEA, 2017a) IoT, AI Buildings Smart lighting and air conditioning (IEA, 2016b, 2017a) IoT, AI Energy efficiency improvement by industrial process optimization (IEA, 2017a) Robots, IoT Industry Bio-based plastic production by biorefinery (OECD, 2017c) Biotechnology New materials from biorefineries (Fornell et al., 2013; McKay et al., 2016) ICT, biotechnology Electric vehicles, car sharing, automation (Greenblatt and Saxena, 2015; Fulton et al., 2017) Biotechnology Bio-based diesel fuel by biorefinery (OECD, 2017c) ICT, biotechnology Second generation bioethanol potentially coupled to carbon capture systems (De Souza et al., 2014; Rochedo et al., 2016) Biotechnology Transport Logistical optimization, and electrification of trucks by overhead line (IEA, 2017e) ICT, biotechnology Reduction of transport needs by remote education, health and other services (GeSI, 2015; IEA, 2017a) Biotechnology Additive manufacturing Energy saving by lightweight aircraft components (Beyer, 2014; Faludi et al., 2015; Verhoef et al., 2018) (3D printing) Solar PV manufacturing (Nemet, 2014) Nanotechnology Electricity Smart grids and grid flexibility to accommodate intermittent renewables (Heard et al., 2017) IoT, AI Plasma confinement for nuclear fusion (Baltz et al., 2017) AI Precision agriculture (improvement of energy and resource efficiency including reduction of fertilizer use and N2O emissions) Biotechnology ICT, AI (Pierpaoli et al., 2013; Brown et al., 2016; Schimmelpfennig and Ebel, 2016) Methane inhibitors (and methane-suppressing vaccines) that reduce livestock emissions from enteric fermentation (Wedlock et al. Agriculture Biotechnology2013; Hristov et al. 2015; Wollenberg et al. 2016) Engineering C3 into C4 photosynthesis to improve agricultural production and productivity (Schuler et al., 2016) Biotechnology Genome editing using CRISPR to improve/adapt crops to a changing climate (Gao, 2018) Biotechnology Weather forecasting and early warning systems, in combination with user knowledge (Hewitt et al., 2012; Lourenço et al., 2016) ICT Disaster Reduction Climate risk reduction (Upadhyay and Bijalwan, 2015) ICT and Adaptation Rapid assessment of disaster damage (Kryvasheyeu et al., 2016) ICT 4 costs, penetration rates, and induced human activity. Even if a 4.4.4.3 The role of government in 1.5°C-consistent technology is available, the establishment of business models might climate technology policy not be feasible (Linder and Williander, 2017). Indeed, studies show a wide range of estimates, ranging from deep emission reductions to While literature on 1.5°C-specific innovation policy is absent, a growing possible increases in emissions due to the rebound effect (Larson and body of literature indicates that governments aim to achieve social, Zhao, 2017). economic and environmental goals by promoting science and a broad range of technologies through ‘mission-driven’ innovation policies, GPT could also enable climate adaptation, in particular through more based on differentiated national priorities (Edler and Fagerberg, effective climate disaster risk management and improved weather 2017). Governments can play a role in advancing climate technology forecasting. via a ‘technology push’ policy on the technology supply side (e.g., R&D subsidies), and by ‘demand pull’ policy on the demand side (e.g., Government policy usually plays a role in promoting or limiting energy-efficiency regulation), and these policies can be complemented GPTs, or science and technology in general. It has impacts on climate by enabling environments (Somanathan et al., 2014). Governments may action, because the performance of further climate technologies also play a role in removing existent support for incumbents (Kivimaa will partly depend on the progress of GPTs. Governments have and Kern, 2016). A growing literature indicates that policy mixes, rather established institutions for achieving many social, and sometimes than single policy instruments, are more effective in addressing climate conflicting goals, including economic growth and addressing climate innovation challenges ranging from technologies in the R&D phase to change (OECD, 2017c), which include investment in basic research those ready for diffusion (Veugelers, 2012; Quitzow, 2015; Rogge et al., and development (R&D) that can help develop game-changing 2017; Rosenow et al., 2017). Such innovation policies can help address technologies (Shayegh et al., 2017). Governments are also needed two kinds of externalities: environmental externalities and proprietary to create an enabling environment for the growth of scientific and problems (GEA, 2012; IPCC, 2014b; Mazzucato and Semieniuk, 2017). To technological ecosystems necessary for GPT development (Tassey, avoid ‘picking winners’, governments often maintain a broad portfolio 2014). of technological options (Kverndokk and Rosendahl, 2007) and work in 370 Strengthening and Implementing the Global Response Chapter 4 close collaboration with the industrial sector and society in general. Some However, the complexity of these transfer processes is high, and governments have achieved relative success in supporting innovation they have to be conducted carefully by governments and institutions policies (Grubler et al., 2012; Mazzucato, 2013) that addressed climate- (Favretto et al., 2017). It is noticeable that the impact of the EU emission related R&D (see Box 4.7 on bioethanol in Brazil). trading scheme (EU ETS) on innovation is contested; recent work (based on lower carbon prices than anticipated for 1.5°C-consistent Funding for R&D could come from various sources, including the general pathways) indicates that it is limited (Calel and Dechezleprêtre, 2016), budget, energy or resource taxation, or emission trading schemes (see but earlier assessments (Blanco et al., 2014) indicate otherwise. Section 4.4.5). Investing in climate-related R&D has as an additional benefit of building capabilities to implement climate mitigation and 4.4.4.4 Technology transfer in the Paris Agreement adaptation technologies (Ockwell et al., 2015). Countries regard innovation in general and climate technology specifically as a national Technology development and transfer is recognized as an enabler of both interests issue and addressing climate change primarily as being in mitigation and adaptation in Article 10 in the Paris Agreement (UNFCCC, the global interest. Reframing part of climate policy as technology or 2016) as well as in Article 4.5 of the original text of the UNFCCC (UNFCCC, industrial policy might therefore contribute to resolving the difficulties 1992). As previous sections have focused on technology development that continue to plague emission target negotiations (Faehn and and diffusion, this section focuses on technology transfer. Technology Isaksen, 2016; Fischer et al., 2017; Lachapelle et al., 2017). transfer can adapt technologies to local circumstances, reduce financing costs, develop indigenous technology, and build capabilities to operate, Climate technology transfer to emerging economies has happened maintain, adapt and innovate on technology globally (Ockwell et al., regardless of international treaties, as these countries have been keen 2015; de Coninck and Sagar, 2017). Technology cooperation could to acquire them, and companies have an incentive to access emerging decrease global mitigation cost, and enhance developing countries’ markets to remain competitive (Glachant and Dechezleprêtre, 2016). mitigation contributions (Huang et al., 2017a). Box 4.7 | Bioethanol in Brazil: Innovation and Lessons for Technology Transfer The use of sugarcane as a bioenergy source started in Brazil in the 1970s. Government and multinational car factories modified car engines nationwide so that vehicles running only on ethanol could be produced. As demand grew, production and distribution systems matured and costs came down (Soccol et al., 2010). After a transition period in which both ethanol-only and gasoline-only cars were used, the flex-fuel era started in 2003, when all gasoline was blended with 25% ethanol (de Freitas and Kaneko, 2011). By 2010, around 80% of the car fleet in Brazil had been converted to use flex-fuel (Goldemberg, 2011; Su et al., 2015). 4 More than forty years of combining technology push and market pull measures led to the deployment of ethanol production, transportation and distribution systems across Brazil, leading to a significant decrease in CO2 emissions (Macedo et al., 2008). Examples of innovations include: (i) the development of environmentally well-adapted varieties of sugarcane; (ii) the development and scaling up of sugar fermentation in a non-sterile environment, and (iii) the development of adaptations of car engines to use ethanol as a fuel in isolation or in combination with gasoline (Amorim et al., 2011; de Freitas and Kaneko, 2011; De Souza et al., 2014). Public procurement, public investment in R&D and mandated fuel blends accompanying these innovations were also crucial (Hogarth, 2017). In the future, innovation could lead to viable partial CO2 removal through deployment of BECCS associated with the bioethanol refineries (Fuss et al., 2014; Rochedo et al., 2016) (see Section 4.3.7). Ethanol appears to reduce urban car emission of health-affecting ultrafine particles by 30% compared to gasoline-based cars, but increases ozone (Salvo et al., 2017). During the 1990s, when sugarcane burning was still prevalent, particulate pollution had negative consequences for human health and the environment (Ribeiro, 2008; Paraiso and Gouveia, 2015). While Jaiswal et al. (2017) report bioethanol’s limited impact on food production and forests in Brazil, despite the large scale, and attribute this to specific agro-ecological zoning legislation, various studies report adverse effects of bioenergy production through forest substitution by croplands (Searchinger et al., 2008), as well as impacts on biodiversity, water resources and food security (Rathore et al., 2016). For new generation biofuels, feasibility and life cycle assessment studies can provide information on their impacts on environmental, economic and social factors (Rathore et al., 2016). Brazil and the European Union have tried to replicate Brazil’s bioethanol experience in climatically suitable African countries. Although such technology transfer achieved relative success in Angola and Sudan, the attempts to set up bioethanol value chains did not pass the phase of political deliberations and feasibility studies elsewhere in Africa. Lessons learned include the need for political and economic stability of the donor country (Brazil) and the necessity for market creation to attract investments in first- generation biofuels alongside a safe legal and policy environment for improved technologies (Afionis et al., 2014; Favretto et al., 2017). 371 Chapter 4 Strengthening and Implementing the Global Response The international institutional landscape around technology 4.4.5 Strengthening Policy Instruments and Enabling development and transfer includes the UNFCCC (via its technology Climate Finance framework and Technology Mechanism including the Climate Technology Centre and Network (CTCN)), the United Nations (a Triggering rapid and far-reaching change in technical choices and technology facilitation mechanism for the SDGs) and a variety of institutional arrangements, consumption and lifestyles, infrastructure, non-UN multilateral and bilateral cooperation initiatives such as the land use, and spatial patterns implies the ability to scale up policy signals Consultative Group on International Agricultural Research (CGIAR, to enable the decoupling of GHGs emission, and economic growth and founded in the 1970s), and numerous initiatives of companies, development (Section 4.2.2.3). Such a scale-up would also imply that foundations, governments and non-governmental and academic potential short-term negative responses by populations and interest organizations. Moreover, in 2015, twenty countries launched an groups, which could block these changes from the outset, would need initiative called ‘Mission Innovation’, seeking to double their energy to be prevented or overcome. This section describes the size and nature R&D funding. At this point it is difficult to evaluate whether Mission of investment needs and the financial challenge over the coming two Innovation achieved its objective (Sanchez and Sivaram, 2017). At decades in the context of 1.5°C warmer worlds, assesses the potential the same time, the private sector started an innovation initiative and constraints of three categories of policy instruments that respond to called the ‘Breakthrough Energy Coalition’. the challenge, and explains the conditions for using them synergistically. The policy and finance instruments discussed in this section relate to Most technology transfer is driven by through markets by the Section 4.4.1 (on governance) and other Sections in 4.4. interests of technology seekers and technology holders, particularly in regions with well-developed institutional and technological 4.4.5.1 The core challenge: cost-efficiency, coordination capabilities such as developed and emerging nations (Glachant and of expectations and distributive effects Dechezleprêtre, 2016). However, the current international technology transfer landscape has gaps, in particular in reaching out to least- Box 4.8 shows that the average estimate by seven models of annual developed countries, where institutional and technology capabilities investment needs in the energy system is around 2.38 trillion USD2010 are limited (de Coninck and Puig, 2015; Ockwell and Byrne, 2016). (1.38 to 3.25) between 2016 and 2035. This represents between 2.53% On the one hand, literature suggests that the management or even (1.6–4%) of the world GDP in market exchange rates (MER) and 1.7% monitoring of all these UN, bilateral, private and public initiatives of the world GDP in purchasing power parity (PPP). OECD investment may fail to lead to better results. On the other hand, it is probably assessments for a 2°C-consistent transition suggest that including more cost-effective to adopt a strategy of ‘letting a thousand flowers investments in transportation and in other infrastructure would increase bloom’, by challenging and enticing researchers in the public and the investment needs by a factor of three. Other studies not included in the private sector to direct innovation towards low-emission and Box 4.8, in particular by the World Economic Forum (WEF, 2013) and the adaptation options (Haselip et al., 2015). This can be done at the Global Commission on the Economy and Climate (GCEC, 2014) confirm 4 same time as mission-oriented research is adopted in parallel by the these orders of magnitude of investment. scientific community (Mazzucato, 2018). The average increase of investment in the energy sector resulting from At COP 21, the UNFCCC requested the Subsidiary Body for Scientific Box 4.8 represents a mean value of 1.5% of the total world investment and Technological Advice (SBSTA) to initiate the elaboration of compared with the baselines scenario in MER and a little over 1% in the technology framework established under the Paris Agreement PPP. Including infrastructure investments would raise this to 2.5% and (UNFCCC, 2016). Among other things, the technology framework 1.7% respectively.9 would ‘provide overarching guidance for the work of the Technology Mechanism in promoting and facilitating enhanced action on These incremental investments could be funded through a drain on technology development and transfer in order to support the consumption (Bowen et al., 2017), which would necessitate between implementation of this Agreement’ (this Agreement being the 0.68% and 0.45% lower global consumption than in the baseline. But, Paris Agreement). An enhanced guidance issued by the Technology consumption at a constant savings/consumption ratio can alternatively Executive Committee (TEC) for preparing a technology action plan be funded by shifting savings towards productive adaptation and (TAP) supports the new technology framework as well as the Parties’ mitigation investments, instead of real-estate sector and liquid financial long-term vision on technology development and transfer, reflected products. This response depends upon whether it is possible to close the in the Paris Agreement (TEC, 2016). global investment funding gap for infrastructure that potentially inhibits growth, through structural changes in the global economy. In this case, investing more in infrastructure would not be an incremental cost in terms of development and welfare (IMF, 2014; Gurara et al., 2017) 9 A calculation in MER tends indeed to underestimate the world GDP and its growth by giving a lower weight to fast-growing developing countries, whereas a calculation in PPP tends to overestimate it. The difference between the value of two currencies in PPP and MER should vanish as the gap of the income levels of the two concerned countries decreases. Accounting for this trend in modelling is challenging. 372 Strengthening and Implementing the Global Response Chapter 4 Box 4.8 | Investment Needs and the Financial Challenge of Limiting Warming to 1.5°C Peer-reviewed literature that estimates the investment needs over the next two decades to scale up the response to limit warming to 1.5°C is very limited (see Section 4.6). This box attempts to bring together available estimates of the order of magnitude of these investments, after consultation with the makers of those estimates, to provide the context for global and national financial mobilization policy and related institutional arrangements. Table 1 in this box presents mean annual investments up to 2035, based on three studies (after clarifying their scope and harmonizing their metrics): an ensemble of four integrated assessment models (here denoted IAM, see Chapter 2), an Organization for Economic Co-operation and Development (OECD) scenario for a 2°C limit (OECD, 2017a) and scenarios from the International Energy Agency (IEA, 2016c). All three sources provide estimates for the energy sector for various mitigation scenarios. They give a mean value of 2.38 trillion USD of yearly investments in the energy sector over the period, with minimum and maximum values of 1.38 and 3.25 respectively. We also report the OECD estimate for 2°C because it also covers transportation and other infrastructure (water, sanitation, and telecommunication), which are essential to deliver the Sustainable Development Goals (SDGs), including SDG 7 on clean energy access, and enhance the adaptive capacity to climate change. Box 4.8, Table 1 | Estimated annualized world mitigation investment needed to limit global warming to 2°C or 1.5°C (2015–2035 in trillions of USD at market exchange rates) from different sources. The top four lines indicate the results of Integrated Assessment Models (IAMs) as reported in Chapter 2 for their Baseline, Nationally Determined Contributions (NDC), 2°C- and 1.5°C-consistent pathways. These numbers only cover the energy sector and the second row includes energy efficiency in all sectors. The final two rows indicate the mitigation investment needs for the energy, transport and other infrastructure according to the Organization for Economic Co-operation and Development (OECD) for a Baseline pathway and a 2°C-consistent pathway. Sources: IEA, 2016c; OECD, 2017a. Energy Of which Transport Other Infra- Total Ratio to Investments Demand Side structures MER GDP IAM Baseline (mean) 1.96 0.24 1.96 1.8% IAM NDC (mean) 2.04 0.28 2.04 1.9% IAM 2°C (mean) 2.19 0.38 2.19 2.1% IAM 1.5°C (mean) 2.32 0.45 2.32 2.2% IEA NDC 2.40 0.72 2.40 2.3% IEA 1.5°C 2.76 1.13 2.76 2.7% 4 Mean IAM-IEA, 1.5°C 2.38 0.54 2.38 2.53% Min IAM-IEA, 1.5°C 1.38 0.38 1.38 1.6% Max IAM-IEA, 1.5°C 3.25 1.13 3.25 4.0% OECD Baseline 5.74 5.4% OECD 2°C 2.13 0.40 2.73 1.52 6.38 6.0% The mean incremental share of annual energy investments to stay well below 2°C is 0.36% (between 0.2–1%) of global GDP between 2016 and 2035. Since total world investment (also called gross fixed capital formation (GFCF)) is about 24% of global GDP, the estimated incremental energy investments between a baseline and a 1.5°C transition would be approximately 1.5% (between 0.8–4.2%) of projected total world investments. As the higher ends of these ranges reflect pessimistic assumptions in 1.5°C-consistent pathways on technological change, the implementation of policies to accelerate technical change (see the remainder of Section 4.4.5) could lower the probability of higher incremental investment. If we assume the amounts of investments given by the OECD for transportation and other infrastructure for warming of 2°C to be a lower limit for an 1.5°C pathway, then total incremental investments for all sectors for a 1.5°C-consistent pathway would be estimated at 2.4% of total world investments. This total incremental investment reaches 2.53% if the investments in transportation are scaled up proportionally with the investments in the energy sector and if all other investments are kept constant. Comparing this 2.4% or 2.53% number for all sectors to the 1.5% number for energy only (see previous paragraph) suggests that the investments in sectors other than energy contribute significantly to incremental world investments, even though a comprehensive study or estimate of these investments for a 1.5°C limit is not available. The issue, from a macroeconomic perspective, is whether these investments would be funded by higher savings at the costs of lower consumption. This would mean a 0.5% reduction in consumption for the energy sector for 1.5°C. Note that for a 2°C scenario, this 373 Chapter 4 Strengthening and Implementing the Global Response Box 4.8 (continued) reduction would be 0.8% if we account for the investment needs of all infrastructure sectors. Assuming conversely a constant savings ratio, this would necessitate reallocating existing capital flows towards infrastructure. In addition to these incremental investments, the amount of redirected investments is relevant from a financial perspective. In the reported IAM energy sector scenarios, about three times the incremental investments is redirected. There is no such assessment for the other sectors. The OECD report suggests that these ratios might be higher. These orders of magnitude of investment can be compared to the available statistics of the global stock of 386 trillion USD of financial capital, which consists of 100 trillion USD in bonds (SIFMA, 2017), around 60 trillion USD in equity (World Bank, 2018b), and 226 trillion USD of loans managed by the banking system (IIF, 2017; World Bank, 2018a). The long-term rate of return (interest plus increase of shareholder value) is about 3% on bonds, 5% on bank lending and 7% on equity, leading to a weighted mean return on capital of 3.4% in real terms (5.4% in nominal terms). Using 3.4% as a lower bound and 5% as a higher bound (following Piketty, 2014) and taking a conservative assumption that global financial capital grows at the same rate as global GDP, the estimated yearly financial capital revenues would be between 16.8 and 25.4 trillion USD. Assuming that a quarter of these investments comes from public funds (as estimated by the World Bank; World Bank, 2018a), the amount of private resources needed to enable an energy sector transition is between 3.3% and 5.3% of annual capital income and between 5.6% and 8.3% of these revenues for all infrastructure to meet the 2°C limit and the SDGs. Since the financial system has limited fungibility across budget lines, changing the partitioning of investments is not a zero-sum game. An effective policy regime could encourage investment managers to change their asset allocation. Part of the challenge may lie in increasing the pace of financing of low-emission assets to compensate for a possible 38% decrease, by 2035, in the value of fossil fuel assets (energy sector and indirect holdings in downstream uses like automobiles) (Mercure et al., 2018). Investments in other (non-energy system) infrastructure to meet opportunities (GCEC, 2014; NCE, 2016). By offsetting the crowding-out development and poverty-reduction goals can strengthen the adaptive of other private and public investments (Pollitt and Mercure, 2017), the capacity to address climate change, and are difficult to separate from ensuing ripple effect could reinforce growth and the sustainability of overall sustainable development and poverty-alleviation investments development (King, 2011; Teulings and Baldwin, 2014) and potentially 4 (Hallegatte and Rozenberg, 2017). The magnitude of potential climate trigger a new growth cycle (Stern, 2013, 2015). In this case, a massive change damages is related to pre-existing fragility of impacted mobilization of low-emission investments would require a significant societies (Hallegatte et al., 2007). Enhancing infrastructure and service effort but may be complementary to sustainable development provision would lower this fragility, for example, through the provision investments. of universal (water, sanitation, telecommunication) service access (Arezki et al., 2016). This uncertain but potentially positive outcome might be constrained by the higher energy costs of low-emission options in the energy and The main challenge is thus not just a lack of mobilization of aggregate transportation sectors. The envelope of worldwide marginal abatement resources but of redirection of savings towards infrastructure, and costs for 1.5°C-consistent pathways reported in Chapter 2 is 135–5500 the further redirection of these infrastructure investments towards USD2010 tCO −12 in 2030 and 245–13000 USD2010 tCO −1 2 in 2050, low-emission options. If emission-free assets emerge fast enough to which is between three to four times higher than for a 2°C limit. compensate for the devaluation of high-emission assets, the sum of the required incremental and redirected investments in the energy These figures are consistent with the dramatic reduction in the unit sector would (up to 2035) be equivalent to between 3.3% and 5.3% costs of some low-emission technical options (for example solar of the average annual revenues of the private capital stock (see Box PV, LED lighting) over the past decade (see Section 4.3.1) (OECD, 4.8) and to between 5.6% and 8.3%, including all infrastructure 2017c). Yet there are multiple constraints to a system-wide energy investments. transition. Lower costs of some supply- and demand-side options do not always result in a proportional decrease in energy system costs. The interplay between mechanisms of financial intermediation The adoption of alternative options can be slowed down by increasing and the private risk-return calculus is a major barrier to realizing costs of decommissioning existing infrastructure, the inertia of market these investments (Sirkis et al., 2015). This obstacle is not specific to structures, cultural habits and risk-adverse user behaviour (see Sections climate mitigation investments but also affects infrastructure and 4.4.1 to 4.4.3). Learning-by-doing processes and R&D can accelerate has been characterised as the gap between the ‘propensity to save’ the cost-efficiency of low-emission technology but often imply higher and the ‘propensity to invest’ (Summers, 2016). The issue is whether early-phase costs. The German energy transition resulted in high new financial instruments could close this gap and inject liquidity consumer prices for electricity in Germany (Kreuz and Müsgens, 2017) into the low-emission transition, thereby unlocking new economic and needed strong accompanying measures to succeed. 374 Strengthening and Implementing the Global Response Chapter 4 One key issue is that energy costs can propagate across sectors and These distributional issues, if addressed carefully and expeditiously, could amplify overall production costs. During the early stage of a low- affect popular sensitivity towards climate policies. Addressing them emission transition, an increase in the prices of non-energy goods could could mitigate adverse macroeconomic effects on economic growth and reduce consumer purchasing power and final demand. A rise in energy employment that could undermine the potential benefits of a redirection prices has a proportionally greater impact in developing countries of savings and investments towards 1.5°C-consistent pathways. that are in a catch-up phase, as they have a stronger dependence on energy-intensive sectors (Crassous et al., 2006; Luderer et al., 2012) Strengthening policy instruments for a low-emission transition would and a higher ratio of energy to labour cost (Waisman et al., 2012). This thus need to reconcile three objectives: (i) handling the short-term explains why with lower carbon prices, similar emission reductions are frictions inherent to this transition in an equitable way, (ii) minimizing reached in South Africa (Altieri et al., 2016) and Brazil (La Rovere et al., these frictions by lowering the cost of avoided GHGs emissions, and (iii) 2017a) compared to developed countries. However, three distributional coordinating expectations of multiple stakeholders at various decision- issues emerge. making levels to accelerate the decline in costs of emission reduction, efficiency and decoupling options and maximizing their co-benefits First, in the absence of countervailing policies, higher energy costs (see the practical example of lowering car use in cities in Box 4.9). have an adverse effect on the distribution of welfare (see also Chapter 5). The negative impact is inversely correlated with the Three categories of policy tools would be available to meet the level of income (Harberger, 1984; Fleurbaey and Hammond, 2004) distributional challenges: carbon pricing, regulatory instruments and and positively correlated with the share of energy in the households information and financial tools. Each of them has its own strengths budget, which is high for low- and middle-income households and weaknesses, from a 1.5°C perspective, policy tools would have to (Proost and Van Regemorter, 1995; Barker and Kohler, 1998; West be both scaled up and better coordinated in packages in a synergistic and Williams, 2004; Chiroleu-Assouline and Fodha, 2011). Moreover, manner. climatic conditions and the geographical conditions of human settlements matter for heating and mobility needs (see Chapter 5). 4.4.5.2 Carbon pricing: necessity and constraints Medium-income populations in the suburbs, in remote areas, and in low-density regions can be as vulnerable as residents of low-income Economic literature has long argued that climate and energy policy urban areas. Poor households with low levels of energy consumption grounded only in regulation, standards and public funding of R&D is are also impacted by price increases of non-energy goods caused by at risk of being influenced by political and administrative arbitrariness, the propagation of energy costs (Combet et al., 2010; Dubois, 2012). which could raise the costs of implementation. This literature has argued These impacts are generally not offset by non-market co-benefits of that it may be more efficient to make these costs explicit through carbon climate policies for the poor (Baumgärtner et al., 2017). taxes and carbon trading, securing the abatement of emissions in places and sectors where it is cheapest (IPCC, 1995, 2001; Gupta et al., 2007; A second matter of concern is the distortion of international competition Somanathan et al., 2014). 4 and employment implications in the case of uneven carbon constraints, especially for energy-intensive industries (Demailly and Quirion, 2008). In a frictionless world, a uniform world carbon price could minimize the Some of these industries are not highly exposed to international social costs of the low-carbon transition by equating the marginal costs competition because of their very high transportation costs per unit of abatement across all sources of emissions. This implies that investors value added (Sartor, 2013; Branger et al., 2016), but other industries will be able to make the right choices under perfect foresight and that could suffer severe shocks, generate ‘carbon leakage’ through cheaper domestic and international compensatory transfers offset the adverse imports from countries with lower carbon constraints (Branger and distributional impacts of higher energy prices and their consequences on Quirion, 2014), and weaken the surrounding regional industrial fabric economic activity. In the absence of such transfers, carbon prices would with economy-wide and employment implications. have to be differentiated by jurisdiction (Chichilnisky and Heal, 2000; Sheeran, 2006; Böhringer et al., 2009; Böhringer and Alexeeva-Talebi, A third challenge is the depreciation of assets whose value is based on 2013). This differentiation could in turn raise concerns of distortions in the valuation of fossil energy resources, of which future revenues may international competition (Hourcade et al., 2001; Stavins et al., 2014). decline precipitously with higher carbon prices (Waisman et al., 2013; Jakob and Hilaire, 2015; McGlade and Ekins, 2015), and on emission- Obstacles to enforcing a uniform world carbon price in the short run intensive capital stocks (Guivarch and Hallegatte, 2011; OECD, 2015a; would not necessarily crowd out explicit national carbon pricing, for Pfeiffer et al., 2016). This raises issues of changes in industrial structure, three reasons. First, a uniform carbon price would limit an emissions adaptation of worker skills, and of stability of financial, insurance and rebound resulting from a higher consumption of energy services social security systems. These systems are in part based on current enabled by efficiency gains, if energy prices do not change (Greening et holdings of carbon-based assets whose value might decrease by about al., 2000; Fleurbaey and Hammond, 2004; Sorrell et al., 2009; Guivarch 38% by the mid-2030s (Mercure et al., 2018). This stranded asset and Hallegatte, 2011; Chitnis and Sorrell, 2015; Freire-González, 2017). challenge may be exacerbated by a decline of export revenues of fossil Second, it could hedge against the arbitrariness of regulatory policies. fuel producing countries and regions (Waisman et al., 2013; Jakob and Third, ‘revenue neutral’ recycling, at a constant share of taxes on GDP, Hilaire, 2015; McGlade and Ekins, 2015). into lowering some existing taxes would compensate for at least part of the propagation effect of higher energy costs (Stiglitz et al., 2017). The substitution by carbon taxes of taxes that cause distortions on the 375 Chapter 4 Strengthening and Implementing the Global Response Box 4.9 | Emerging Cities and ‘Peak Car Use’: Evidence of Decoupling in Beijing The phenomenon of ‘peak car use’, or reductions in per capita car use, provides hope for continuing reductions in greenhouse gases from oil consumption (Millard-Ball and Schipper, 2011; Newman and Kenworthy, 2011; Goodwin and Van Dender, 2013). The phenomenon has been mostly associated with developed cities apart from some early signs in Eastern Europe, Latin America and China (Newman and Kenworthy, 2015). New research indicates that peak car is now also underway in China (Gao and Newman, 2018). China’s rapid urban motorization was a result of strong economic growth, fast urban development and the prosperity of the Chinese automobile industry (Gao et al., 2015). However, recent data (Gao and Newman, 2018) (expressed as a percentage of daily trips) suggest the first signs of a break in the growth of car use along with the growth in mass transit, primarily the expansion of Metro systems (see Box 4.9, Figure 1). 70 Transit Private Vehicles Bicycle 60 50 40 30 20 10 0 1985 1990 1995 2000 2005 2010 2015 Year Box 4.9, Figure 1 | The modal split data in Beijing between 1986 and 2014. Source: (Gao and Newman, 2018). Chinese urban fabrics, featuring traditional dense linear forms and mixed land use, favour mass transit systems over automobiles (Gao and Newman, 2018). The data show that the decline in car use did not impede economic development, but the growth in vehicle kilometres of travel (VKT) has decoupled absolutely from GDP as shown in Box 4.9, Figure 2 below. 4 20000 5000 15000 4000 3000 10000 2000 5000 per capita GDP (USD) 1000 per capita VKT (km) 0 0 2002 2004 2006 2008 2010 2012 2014 2016 Year Box 4.9, Figure 2 | Peak car in Beijing: relationships between economic performance and private automobile use in Beijing from 1986 to 2014. VKT is vehicle kilometres of travel. Source: (Gao and Newman, 2018). economy can counteract the regressive effect of higher energy prices. For (Goulder, 1995; Bovenberg, 1999; Mooij, 2000). In the context of OECD example, offsetting increased carbon prices with lower labour taxes can countries, the literature examines how carbon taxation could substitute potentially decrease labour costs (without affecting salaries), enhance for other taxes to fund the social security system (Combet, 2013). The employment and reduce the attractiveness of informal economic activity same general principles apply for countries that are building their social (Goulder, 2013). welfare system, such as China (Li and Wang, 2012) or Brazil (La Rovere et al., 2017a), but an optimal recycling scheme could differ based on the The conditions under which an economic gain along with climate structure of the economy (Lefèvre et al., 2018). benefit (a ‘double dividend’) can be expected are well documented 376 per capita GDP (USD ) Modal split of daily trips (% ) per capita VKT (km ) Strengthening and Implementing the Global Response Chapter 4 In every country the design of carbon pricing policy implies a balance 4.4.5.3 Regulatory measures and information flows between incentivizing low-carbon behaviour and mitigating the adverse distributional consequences of higher energy prices (Combet Regulatory instruments are a common tool for improving energy et al., 2010). Carbon taxes can offset these effects if their revenues efficiency and enhancing renewable energy in OECD countries (e.g., the are redistributed through rebates to poor households. Other options USA, Japan, Korea, Australia, the EU) and, more recently, in developing include the reduction of value-added taxes for basic products or direct countries (M.J. Scott et al., 2015; Brown et al., 2017). Such instruments benefit transfers to enable poverty reduction (see Winkler et al. (2017) include constraints on the import of products banned in other countries for South Africa and Grottera et al. (2016) for Brazil). This is possible (Knoop and Lechtenböhmer, 2017). because higher-income households pay more in absolute terms, even though their carbon tax burden is a relatively smaller share of their For energy efficiency, these instruments include end-use standards and income (Arze del Granado et al., 2012). labelling for domestic appliances, lighting, electric motors, water heaters and air-conditioners. They are often complemented by mandatory Ultimately, the pace of increase of carbon prices would depend on the efficiency labels to attract consumers’ attention and stimulate the pace at which they can be embedded in a consistent set of fiscal and manufacture of more efficient products (Girod et al., 2017). Experience social policies. This is specifically critical in the context of the 1.5°C shows that these policy instruments are effective only if they are limit (Michaelowa et al., 2018). This is why, after a quarter century of regularly reviewed to follow technological developments, as in the ‘Top academic debate and experimentation (see IPCC WGIII reports since Runner’ programme for domestic appliances in Japan (Sunikka-Blank the SAR), a gap persists with respect to ‘switching carbon prices’ and Iwafune, 2011). needed to trigger rapid changes. In 2016, only 15% of global emissions are covered by carbon pricing, three-quarters of which with prices In four countries, efficiency standards (e.g. miles per gallon or level of below 10 USD tCO −12 (World Bank, 2016). This is too low to outweigh CO2 emission per kilometre) have been used in the transport sector, the ‘noise’ from the volatility of oil markets (in the range of 100 USD for light- and heavy-duty vehicles, which have spillovers for the global tCO −12 over the past decade), of other price dynamics (interest rates, car industry. In the EU (Ajanovic and Haas, 2017) and the USA (Sen currency exchange rates and real estate prices) and of regulatory et al., 2017), vehicle manufacturers need to meet an annual CO2 policies in energy, transportation and industry. For example, the emission target for their entire new vehicle fleet. This allows them to dynamics of mobility depend upon a trade-off between housing prices compensate through the introduction of low-emission vehicles for the and transportation costs in which the price of real estate and the inert high-emission ones in the fleet. This leads to increasingly efficient fleets endowments in public transport play as important a role as liquid fuel of vehicles over time but does not necessarily limit the driven distance. prices (Lampin et al., 2013). Building codes that prescribe efficiency requirements for new and These considerations apply to attempts to secure a minimum price in existing buildings have been adopted in many OECD countries (Evans carbon trading systems (Wood and Jotzo, 2011; Fell et al., 2012; Fuss et al., 2017) and are regularly revised to increase their efficiency per 4 et al., 2018) and to the reduction of fossil fuel subsidies. Estimated at unit of floor space. Building codes can avoid locking rapidly urbanizing 650 billion USD in 2015 (Coady et al., 2017), these subsidies represent countries into poorly performing buildings that remain in use for the 25–30% of government expenditures in forty (mostly developing) next 50–100 years (Ürge-Vorsatz et al., 2014). In OECD countries, countries (IEA, 2014b). Reducing these subsidies would contribute to however, their main role is to incentivize the retrofit of existing reaching 1.5°C-consistent pathways, but raises similar issues as carbon buildings. In addition of the convergence of these codes to net zero pricing around long-term benefits and short-term costs (Jakob et al., energy buildings (D’Agostino, 2015), a new focus should be placed, 2015; Zeng and Chen, 2016), as well as social impacts. in the context of 1.5°C-consistent pathways, on public and private coordination to achieve better integration of building policies with the Explicit carbon prices remain a necessary condition of ambitious promotion of low-emission transportation modes (Bertoldi, 2017). climate policies, and some authors highlight the potential benefit brought by coordination among groups of countries (Weischer et al., The efficacy of regulatory instruments can be reinforced by economic 2012; Hermwille et al., 2017; Keohane et al., 2017). They could take the incentives, such as feed-in tariffs based on the quantity of renewable form of carbon pricing corridors (Bhattacharya et al., 2015). They are energy produced, subsidies or tax exemptions for energy savings a necessary ‘lubricant’ through fiscal reforms or direct compensating (Bertoldi et al., 2013; Ritzenhofen and Spinler, 2016; García-Álvarez et transfers to accommodate the general equilibrium effects of higher al., 2017; Pablo-Romero et al., 2017), fee-bates, and ‘bonus-malus’ that energy prices but may not suffice to trigger the low-carbon transition foster the penetration of low-emission options (Butler and Neuhoff, because of a persistent ‘implementation gap’ between the aspirational 2008). Economic incentives can also be combined with direct-use carbon prices and those that can practically be enforced. When systemic market-based instruments, for example combining, in the United changes, such as those needed for 1.5°C-consistent pathways, are at States and, in some EU countries, carbon trading schemes with energy play on many dimensions of development, price levels ‘depend on the savings obligations for energy retailers (Haoqi et al., 2017), or with path and the path depends on political decisions’ (Drèze and Stern, green certificates for renewable energy portfolio standards (Upton and 1990). Snyder, 2017). Scholars have investigated caps on utilities’ energy sales (Thomas et al., 2017) and emission caps implemented at a personal level (Fawcett et al., 2010). 377 Chapter 4 Strengthening and Implementing the Global Response In combination with the funding of public research institutes, grants green or climate bonds. The estimated value of the green bonds market or subsidies also support R&D, where risk and the uncertainty about in 2017 is 155 billion USD (BNEF, 2018). The bulk of these investments long-term perspectives can reduce the private sector’s willingness to are in renewable energy, energy efficiency and low-emission transport invest in low-emission innovation (see also Section 4.4.4). Subsidies can (Lazurko and Venema, 2017), with only 4% for adaptation (OECD, take the form of rebates on value-added tax (VAT), of direct support to 2017b). One major question is whether individual strategies based on investments (e.g., renewable energy or refurbishment of buildings) or improved climate-related information alone will enable the financial feed-in tariffs (Mir-Artigues and del Río, 2014). They can be provided system to allocate capital in an optimal way (Christophers, 2017) since by the public budget, via consumption levies, or via the revenues of climate change is a systemic risk (CISL, 2015; Schoenmaker and van carbon taxes or pricing. Fee-bates, introduced in some countries (e.g., Tilburg, 2016). for cars), have had a neutral impact on public budgets by incentivizing low-emission products and penalizing high-emission ones (de Haan et The readiness of financial actors to reduce investments in fossil fuels al., 2009). is a real trend (Platinga and Scholtens, 2016; Ayling and Gunningham, 2017), but they may not resist the attractiveness of carbon-intensive All policy instruments can benefit from information campaigns (e.g., TV investments in many regions. Hence, decarbonizing an investment ads) tailored to specific end-users. A vast majority of public campaigns on portfolio is not synonymous with investing massively in low-emission energy and climate have been delivered through mass-media channels infrastructure. Scaling up climate-friendly financial products may and advertising-based approaches (Corner and Randall, 2011; Doyle, depend upon a business context conducive to the reduction of the risk- 2011). Although some authors report large savings obtained by such weighted capital costs of low-emission projects. The typical leverage of campaigns, most agree that the effects are short-lived and decrease public funding mechanisms for low-emission investment is low (2 to 4) over time (Bertoldi et al., 2016). Recently, focus has been placed on the compared with other sectors (10 to 15) (Maclean et al., 2008; Ward et use of social norms to motivate behavioural changes (Allcott, 2011; Alló al., 2009; MDB, 2016). This is due to the interplay of the uncertainty of and Loureiro, 2014). More on strategies to change behaviour can be emerging low-emission technologies in the midst of their learning-by- found in Section 4.4.3. doing cycle with uncertain future revenues due to volatility of fossil fuel prices (Roques et al., 2008; Gross et al., 2010) as well as uncertainty 4.4.5.4 Scaling up climate finance and de-risking around regulatory policies. This inhibits low-emission investments by low-emission investments corporations functioning under a ‘shareholder value business regime’ (Berle and Means, 1932; Roe, 1996; Froud et al., 2000) and actors The redirection of savings towards low-emission investments may be with restricted access to capital (e.g. cities, local authorities, SMEs and constrained by enforceable carbon prices, implementation of technical households). standards and the short-term bias of financial systems (Miles, 1993; Bushee, 2001; Black and Fraser, 2002). The many causes of this bias are De-risking policy instruments to enable low-emission investment 4 extensively analysed in economic literature (Tehranian and Waegelein, encompasses interest rate subsidies, fee-bates, tax breaks, concessional 1985; Shleifer and Vishny, 1990; Bikhchandani and Sharma, 2000), loans from development banks, and public investment funds, including including their link with prevailing patterns of economic globalization revolving funds. Given the constraints on public budgets, public (Krugman, 2009; Rajan, 2011) and the chronic underinvestment in guarantees can be used to increase the leverage effect of public long-term infrastructure (IMF, 2014). Emerging literature explores how financing on private financing. Such de-risking instruments imply to overcome this through reforms targeted to bridge the gap between indeed a full direct burden on public budgets only in case of default short-term cash balances and long-term low-emission assets and to of the project. They could back for example various forms of green reduce the risk-weighted capital costs of climate-resilient investments. infrastructure funds (de Gouvello and Zelenko, 2010; Emin et al., 2014; This gap, which was qualified by the Governor of the Bank of England as Studart and Gallagher, 2015).10 a ‘tragedy of the horizon’ (Carney, 2016) that constitutes a threat to the stability of the financial system, is confirmed by the literature (Arezki et The risk of defaulting can be mitigated by strong measurement, reporting al., 2016; Christophers, 2017). This potential threat would encompass the and verifying (MRV) systems (Bellassen et al., 2015) and by the use of impact of climate events on the value of assets (Battiston et al., 2017), notional prices recommended in public economics (and currently in use liability risks (Heede, 2014) and the transition risk due to devaluation of in France and the UK) to calibrate public support to the provision of certain classes of assets (Platinga and Scholtens, 2016). public goods in case of persisting distortions in pricing (Stiglitz et al., 2017). Some suggest linking these notional prices to ‘social, economic The financial community’s attention to climate change grew after COP and environmental value of voluntary mitigation actions’ recognized by 15 (ESRB ASC, 2016). This led to the introduction of climate-related risk the COP 21 Decision accompanying the Paris Agreement (paragraph disclosure in financial portfolios (UNEP, 2015), placing it on the agenda 108) (Hourcade et al., 2015; La Rovere et al., 2017b; Shukla et al., 2017), of G20 Green Finance Study Group and of the Financial Stability Board. in order to incorporate the co-benefits of mitigation. This led to the creation of low-carbon financial indices that investors could consider as a ‘free option on carbon’ to hedge against risks of Such public guarantees ultimately amount to money issuance backed by stranded carbon-intensive assets (Andersson et al., 2016). This could also low-emission projects as collateral. This explains the potentially strong accelerate the emergence of climate-friendly financial products such as link between global climate finance and the evolution of the financial 10 One prototype is the World Bank’s Pilot Auction Facility on Methane and Climate Change 378 Strengthening and Implementing the Global Response Chapter 4 and monetary system. Amongst suggested mechanisms for this adaptation might be lower in a 1.5°C world (UNEP/Climate Analytics, evolution are the use of International Monetary Fund’s (IMF’s) Special 2015) they would be higher than the UNEP estimate of 22.5 billion Drawing Rights to fund the paid-in capital of the Green Climate Fund USD of bilateral and multilateral funding for climate change adaptation (Bredenkamp and Pattillo, 2010) and the creation of carbon remediation in 2014. Currently, 18–25% of climate finance flows to adaptation in assets at a predetermined face value per avoided tonne of emissions developing countries (OECD, 2015b, 2016; Shine and Campillo, 2016). It (Aglietta et al., 2015a, b). Such a predetermined value could hedge remains fragmented, with small proportions flowing through UNFCCC against the fragmentation of climate finance initiatives and support the channels (AdaptationWatch, 2015; Roberts and Weikmans, 2017). emergence of financial products backed by a new class of long-term assets. Means of raising resources for adaptation, achieving the SDGs and meeting basic needs (Durand et al., 2016; Roberts et al., 2017) include Combining public guarantees at a predetermined value of avoided the reduction of fossil fuel subsidies (Jakob et al., 2016), increasing emissions, in addition to improving the consistency of non-price revenues from carbon taxes (Jakob et al., 2016), levies on international measures, could support the emergence of financial products backed aviation and maritime transport, and sharing of the proceeds of financial by a new class of certified assets to attract savers in search of safe and arrangements supporting mitigation activities (Keen et al., 2013). Each ethical investments (Aglietta et al., 2015b). It could hedge against the have different redistribution implications. Challenges, however, include fragmentation of climate finance initiatives and provide a mechanism to the efficient use of resources, the emergence of long-term assets using compensate for the ‘stranded’ assets caused by divestment in carbon- infrastructure as collateral and the capacity to implement small-scale based activities and in lowering the systemic risk of stranded assets adaptation and the mainstreaming of adaptation in overall development (Safarzyńska and van den Bergh, 2017). These new assets could also policies. There is thus a need for greater policy coordination (Fankhauser facilitate a low-carbon transition for fossil fuel producers and help them and McDermott, 2014; Morita and Matsumoto, 2015; Sovacool et al., to overcome the ‘resource curse’ (Ross, 2015; Venables, 2016). 2015, 2017; Lemos et al., 2016; Adenle et al., 2017; Peake and Ekins, 2017) that includes robust mechanisms for tracking, reporting and Blended injection of liquidity has monetary implications. Some argue ensuring transparency of adaptation finance (Donner et al., 2016; Pauw that this questions the premise that money should remain neutral et al., 2016a; Roberts and Weikmans, 2017; Trabacchi and Buchner, (Annicchiarico and Di Dio, 2015, 2016; Nikiforos and Zezza, 2017). 2017) and its consistency with the provision of basic needs (Hallegatte Central banks or financial regulators could act as a facilitator of last et al., 2016). resort for low-emission financing instruments, which could in turn lower the systemic risk of stranded assets (Safarzyńska and van den Bergh, 4.4.5.6 Towards integrated policy packages and innovative 2017). This may, in time, lead to the use of carbon-based monetary forms of financial cooperation instruments to diversify reserve currencies (Jaeger et al., 2013) and differentiate reserve requirements (Rozenberg et al., 2013) in the Carbon prices, regulation and standards, improved information and context of a climate-friendly Bretton Woods (Sirkis et al., 2015; Stua, appropriate financial instruments can work synergistically to meet the 4 2017). challenge of ‘making finance flows consistent with a pathway towards low greenhouse gas emissions and climate-resilient development’, as in 4.4.5.5 Financial challenge for basic needs and adaptation Article 2 in the Paris Agreement. finance There is growing attention to the combination of policy instruments Adaptation finance is difficult to quantify for two reasons. The first is that address three domains of action: behavioural changes, economic that it is very difficult to isolate specific investment needs to enhance optimization and long-term strategies (Grubb et al., 2014). For example, climate resilience from the provision of basic infrastructure that are de-risking low-emission investments would result in higher volumes of currently underinvested (IMF, 2014; Gurara et al., 2017). The UNEP low-emission investments, and would in turn lead to a lower switching (2016) estimate of investment needs on adaptation in developing price for the same climate ambition (Hirth and Steckel, 2016). In the countries between 140–300 billion USD yr−1 in 2030, a major part reverse direction, higher explicit carbon prices may generate more being investment expenditures that are complementary with SDG- low-emission projects for a given quantum of de-risking. For example, related investments focused on universal access to infrastructure and efficiency standards for housing can increase the efficacy of carbon prices services and meeting basic needs. Many climate-adaptation-centric and overcome the barriers coming from the high discount rates used by financial incentives are relevant to non-market services, offering fewer households (Parry et al., 2014), while explicit and notional carbon prices opportunities for market revenues while they contribute to creating can lower the risk of arbitrary standards. The calibration of innovative resilience to climate impacts. financial instruments to notional carbon prices could encourage large multinational companies to increase their level of internal carbon prices Hence, adaptation investments and the provision of basic needs would (UNEP, 2016). These notional prices could be higher than explicit carbon typically have to be supported by national and sub-national government prices because they redirect new hardware investments without an budgets together with support from overseas development assistance immediate impact on existing capital stocks and associated interests. and multilateral development banks (Fankhauser and Schmidt-Traub, 2011; Adenle et al., 2017; Robinson and Dornan, 2017), and a slow Literature, however, shows that conflicts between poorly articulated increase of dedicated NGO and private climate funds (Nakhooda policy instruments can undermine their efficiency (Lecuyer and and Watson, 2016). Even though the UNEP estimates of the costs of Quirion, 2013; Bhattacharya et al., 2017; García-Álvarez et al., 2017). 379 Chapter 4 Strengthening and Implementing the Global Response As has been illustrated in Europe, commitment uncertainty and lack of Following the assessment framework developed in Chapter 1, economic credibility of regulation have consistently led to low carbon prices in and technological, institutional and socio-cultural, and environmental and the case of the EU Emission Trading System (Koch et al., 2014, 2016). A geophysical feasibility are considered and applied to system transitions comparative study shows how these conflicts can be avoided by policy (Sections 4.3.1–4.3.4), overarching adaptation options (Section 4.3.5) packages that integrate many dimensions of public policies and are and carbon dioxide removal (CDR) options (Section 4.3.7). This is done designed to match institutional and social context of each country and to assess the multidimensional feasibility of mitigation and adaptation region (Bataille et al., 2015). options that have seen considerable development and change since AR5. In the case of adaptation, the assessed AR5 options are typically Even though policy packages depend upon domestic political clustered. For example, all options related to energy infrastructure processes, they might not reinforce the NDCs at a level consistent with resilience, independently of the generation source, are categorized as the 1.5°C transition without a conducive international setting where ‘resilience of power infrastructure’. international development finance plays a critical role. Section 4.4.1 explores the means of mainstreaming climate finance in the current Table 4.10 presents sets of indicators against which the multidimensional evolution of the lending practices of national and multilateral banks feasibility of individual adaptation options relevant to warming of 1.5°C, (Badré, 2018). This could facilitate the access of developing countries and mitigation options along 1.5°C-consistent pathways, is assessed. to loans via bond markets at low interest rates, encouragement of the emergence of new business models for infrastructure, The feasibility assessment takes the following steps. First, each of and encouragement of financial markets to support small-scale the mitigation and adaptation options is assessed along the relevant investments (Déau and Touati, 2017). indicators grouped around six feasibility dimensions: economic, technological, institutional, socio-cultural, environmental/ecological These financial innovations may involve non-state public actors and geophysical. Three types of feasibility groupings were assessed like cities and regional public authorities that govern infrastructure from the underlying literature: first, if the indicator could block the investment, enable energy and food systems transitions and manage feasibility of this option; second, if the indicator has neither a positive urban dynamics (Cartwright, 2015). They would help, for example, in nor a negative effect on the feasibility of the option or the evidence raising the 4.5–5.4 trillion USD yr−1 from 2015 to 2030 announced is mixed; and third, if the indicator does not pose any barrier to the by the Cities Climate Finance Leadership Alliance (CCFLA, 2016) to feasibility of this option. The full assessment of each option under each achieve the commitments by the Covenant of Mayors of many cities to indicator, including the literature references on which the assessment long-term climate targets (Kona et al., 2018). is based, can be found in supplementary materials 4.SM.4.2 and 4.SM.4.3. When appropriate, it is indicated that there is no evidence The evolution of global climate financial cooperation may involve (NE), limited evidence (LE) or that the indicator is not applicable to the central banks, financial regulatory authorities, and multilateral and option (NA). 4 commercial banks. There are still knowledge gaps about the form, structure and potential of these arrangements. They could be viewed Next, for each feasibility dimension and option, the overall feasibility as a form of a burden-sharing between high-, medium- and low- for a given dimension is assessed as the mean of combined scores income countries to enhance the deployment of ambitious Nationally of the relevant underlying indicators and classified into ‘insignificant Determined Contributions (NDCs) and new forms of ‘common but barriers’ (2.5 to 3), ‘mixed or moderate but still existent barriers’ (1.5 differentiated responsibility and respective capabilities’ (Edenhofer et to 2.5) or ‘significant barriers’ (below 1.5) to feasibility. Indicators al., 2015; Hourcade et al., 2015; Ji and Sha, 2015). assessed as NA, LE or NE are not included in this overall assessment (see supplementary material 4.SM.4.1 for the averaging and weighing guidance). 4.5 Integration and Enabling Transformation The results are summarized in Table 4.11 (for mitigation options) and Table 4.12 (for adaptation options) for each of the six feasibility 4.5.1 Assessing Feasibility of Options for Accelerated dimensions: where dark shading indicates few feasibility barriers; Transitions moderate shading indicates that there are mixed or moderate but still existent barriers, and light shading indicates that multiple barriers, in Chapter 2 shows that 1.5°C-consistent pathways involve rapid, global this dimension, may block implementation. climate responses to reach net zero emissions by mid-century or earlier. Chapter 3 identifies climate change risks and impacts to which the A three-step process of independent validation and discussion by world would need to adapt during these transitions and additional risks authors was undertaken to make this assessment as robust as possible and impacts during potential 1.5°C overshoot pathways. The feasibility within the scope of this Special Report. It must, however, be recognized of these pathways is contingent upon systemic change (Section 4.3) that this is an indicative assessment at global scale, and both policy and enabling conditions (Section 4.4), including policy packages. This and implementation at regional, national and local level would need to section assesses the feasibility of options (technologies, actions and adapt and build on this knowledge, within the particular local context measures) that form part of global systems under transition that make and constraints. Some contextual factors are indicated in the rightmost up 1.5°C-consistent pathways. column in Tables 4.11 and 4.12. 380 Strengthening and Implementing the Global Response Chapter 4 Table 4.10 | Sets of indicators against which the feasibility of adaptation and mitigation options are assessed for each feasibility dimension. The options are discussed in Sections 4.3.1-4.3.5 and 4.3.7. Feasibility Dimensions Adaptation Indicators Mitigation Indicators Microeconomic viability Cost-effectiveness Macroeconomic viability Economic Absence of distributional effects Socio-economic vulnerability reduction potential Employment & productivity enhancement potential Employment & productivity enhancement potential Technical scalability Technical resource availability Maturity Technological Risks mitigation potential Simplicity Absence of risk Political acceptability Political acceptability Legal & regulatory feasibility Legal & administrative feasibility Institutional Institutional capacity & administrative feasibility Institutional capacity Transparency & accountability potential Transparency & accountability potential Social co-benefits (health, education) Social co-benefits (health, education) Public acceptance Socio-cultural acceptability Socio-cultural Social & regional inclusiveness Social & regional inclusiveness Intergenerational equity Intergenerational equity Human capabilities Reduction of air pollution Ecological capacity Reduction of toxic waste Environmental/Ecological Adaptive capacity/ resilience building potential Reduction of water use Improved biodiversity Physical feasibility (physical potentials) Physical feasibility Limited use of land Geophysical Land use change enhancement potential Limited use of scarce (geo)physical resources Hazard risk reduction potential Global spread 4.5.2 Implementing Mitigation section (Section 4.6). Nevertheless, in Table 4.11, an indicative attempt has been made to capture relevant contextual information. The ‘context’ This section builds on the insights on mitigation options in Section 4.3, column indicates which contextual factors may affect the feasibility of applies the assessment methodology along feasibility dimensions and an option, including regional differences. For instance, solar irradiation 4 indicators explained in Section 4.5.1, and synthesizes the assessment in an area impacts the cost-effectiveness of solar photovoltaic energy, of the enabling conditions in Section 4.4. so solar irradiation is mentioned in this column. 4.5.2.1 Assessing mitigation options for limiting warming 4.5.2.2 Enabling conditions for implementation to 1.5˚C against feasibility dimensions of mitigation options towards 1.5˚C An assessment of the degree to which examples of 1.5°C-relevant The feasibility assessment highlights six dimensions that could help mitigation options face barriers to implementation, and on which inform an agenda that could be addressed by the areas discussed in contexts this depends, is summarized in Table 4.11. An explanation of Section 4.4: governance, behaviour and lifestyles, innovation, enhancing the approach is given in Section 4.5.1 and in supplementary material institutional capacities, policy and finance. For instance, Section 4.4.3 on 4.SM.4.1. Selected options were mapped onto system transitions behaviour offers strategies for addressing public acceptance problems, and clustered through an iterative process of literature review, and how changes can be more effective when communication and expert feedback, and responses to reviewer comments. The detailed actions relate to people’s values. This section synthesizes the findings in assessment and the literature underpinning the assessment can be Section 4.4 in an attempt to link them to the assessment in Table 4.11. found in supplementary material 4.SM.4.2. The literature on which the discussion is based is found in Section 4.4. The feasibility framework in Cross-Chapter Box 3 in Chapter 1 highlights From Section 4.4, including the case studies presented in the Boxes that the feasibility of mitigation and adaptation options depends on 4.1 to 4.10, several main messages can be constructed. For instance, many factors. Many of those are captured in the indicators in Table 4.10, governance would have to be multilevel and engaging different actors, but many depend on the specific context in which an option features. This while being efficient, and choosing the form of cooperation based on Special Report did not have the mandate, space or the literature base the specific systemic challenge or option at hand. If institutional capacity to undertake a regionally specific assessment. Hence the assessment is for financing and governing the various transitions is not urgently built, caveated as providing a broad indication of the likely global barriers, many countries would lack the ability to change pathways from a ignoring significant regional diversity. Regional and context-specific high-emission scenario to a low- or zero-emission scenario. In terms of literature is also just emerging as is noted in the knowledge gaps innovation, governments, both national and multilateral, can contribute 381 Chapter 4 Strengthening and Implementing the Global Response Table 4.11 | Feasibility assessment of examples of 1.5°C-relevant mitigation options, with dark shading signifying the absence of barriers in the feasibility dimension, moderate shading indicating that, on average, the dimension does not have a positive or negative effect on the feasibility of the option, or the evidence is mixed, and faint shading the presence of potentially blocking barriers. No shading means that the literature found was not sufficient to make an assessment. Evidence and agreement assessment is undertaken at the option level. The context column on the far right indicates how the assessment might change if contextual factors were different. For the methodology and literature basis, see supplementary material 4.SM.4.1 and 4.SM.4.2. Abbreviations used: Ec: Economic - Tec: Technological - Inst: Institutional - Soc: Socio-cultural - Env: Environmental/Ecological - Geo: Geophysical System Mitigation Option Evidence Agreement Ec Tec Inst Soc Env Geo Context Wind regime, economic status, space for wind Wind energy (on-shore farms, and the existence of a legal framework Robust Medium & off-shore) for independent power producers affect uptake; cost-effectiveness affected by incentive regime Cost-effectiveness affected by solar irradiation and incentive regime. Also enhanced by legal Solar PV Robust High framework for independent power producers, which affects uptake Depends on availability of biomass and land and the Energy capability to manage sustainable land use.Bioenergy Robust Medium System Distributional effects depend on the agrarian Transitions (or other) system used to produce feedstock Batteries universal, but grid-flexible resources Electricity storage Robust High vary with area’s level of development Power sector carbon Varies with local CO2 storage capacity, presence of dioxide capture Robust High legal framework, level of development and and storage quality of public engagement Electricity market organization, legal framework, standardization & know-how, country’s ‘democratic Nuclear energy Robust High fabric’, institutional and technical capacity, and safety culture of public and private institutions Reduced food Will depend on the combination of wastage & efficient Robust High individual and institutional behaviour food production Land & Depends on individual behaviour, education, Dietary shifts Medium High Ecosystem cultural factors and institutional support 4 Transitions Sustainable Depends on development and deployment intensification Medium High of new technologies of agriculture Ecosystems restoration Medium High Depends on location and institutional factors Varies with urban fabric, not geography or economy; Land-use & urban Robust Medium requires capacitated local government and legitimate planning tenure system Varies with degree of government intervention; Electric cars and buses Medium High requires capacity to retrofit “fuelling” stations Historic schemes universal, but new ones depend Sharing schemes Limited Medium on ICT status; undermined by high crime and low levels of law enforcement Urban & Depends on presence of existing ‘informal’ taxi Infra systems, which may be more cost-effective and Public transport Robust Medium structure affordable than capital-intensive new build schemes, System as well as (local) government capabilities Transitions Non-motorized Viability rests on linkages with public transport, Robust High transport cultural factors, climate and geography Varies with technology, governance Aviation & shipping Medium Medium and accountability Varies with economic status and presence or quality Smart grids Medium Medium of existing grid Adoption varies with economic status and policy Efficient appliances Medium High framework Low/zero-energy Depends on size of existing building stock and growth Medium High buildings of building stock 382 Strengthening and Implementing the Global Response Chapter 4 Table 4.11 (continued) System Mitigation Option Evidence Agreement Ec Tec Inst Soc Env Geo Context Potential and adoption depend on existing efficiency, Energy efficiency Robust High energy prices and interest rates, as well as government incentives Faces barriers in terms of pressure on natural resources and biodiversity. Product substitution Bio-based & circularity Medium Medium depends on market organization and government Industrial incentivization System Transitions Depends on availability of large-scale, cheap, Electrification emission-free electricity (electrification, hydrogen) Medium High & hydrogen or CO2 storage nearby (hydrogen). Manufacturers’ appetite to embrace disruptive innovations Industrial carbon High concentration of CO2 in exhaust gas improve dioxide capture, Robust High economic and technical feasibility of CCUS in utilization and storage industry. CO2 storage or reuse possibilities Bioenergy and carbon Depends on biomass availability, CO2 storage dioxide capture Robust Medium capacity, legal framework, economic status and and storage social acceptance Direct air carbon Depends on CO2-free energy, CO2 storage capacity, dioxide capture Medium Medium legal framework, economic status and social Carbon and storage acceptance Dioxide Afforestation & Depends on location, mode of implementation, Removal Robust High reforestation and economic and institutional factors Soil carbon Robust High Depends on location, soil properties, time span sequestration & biochar Depends on CO -free energy, economic Enhanced weathering Medium Low 2 status and social acceptance to applying general-purpose technologies to mitigation purposes. incentives to change behaviour and technology, financial systems are If this is not managed, some reduction in emissions could happen an indispensable element of a systemic transition. If financial markets autonomously, but it may not lead to a 1.5°C-consistent pathway. do not acknowledge climate risk and the risk of transitions, regulatory International cooperation on technology, including technology transfer financial institutions, such as central banks, could intervene. 4 where this does not happen autonomously, is needed and can help create innovation capabilities in all countries that allow them to operate, Strengthening implementation revolves around more than addressing maintain, adapt and regulate a portfolio of mitigation technologies. barriers to feasibility. A system transition, be it in energy, industry, land Case studies in the various subsections highlight the opportunities and or a city, requires changing the core parameters of a system. These relate, challenges of doing this in practice. They indicate that it can be done in as introduced in Section 4.2 and further elaborated in Section 4.4, to specific circumstances, which can be created. how actors cooperate, how technologies are embedded, how resources are linked, how cultures relate and what values people associate with A combination of behaviour-oriented pricing policies and financing the transition and the current regime. options can help change technologies and social behaviour as it would challenge the existing, high-emission socio-technical regime on multiple 4.5.3 Implementing Adaptation levels across feasibility characteristics. For instance, for dietary change, combining supply-side measures with value-driven communication and Article 7 of the Paris Agreement provides an aspirational global goal for economic instruments may help make a lasting transition, while an adaptation, of ‘enhancing adaptive capacity, strengthening resilience, economic instrument, such as enhanced prices or taxation, on its own and reducing vulnerability’ (UNFCCC, 2016). Adaptation implementation may not be as robust. is gathering momentum in many regions, guided by national NDC’s and national adaptation plans (see Cross-Chapter Box 11 in this Chapter). Governments could benefit from enhanced carbon prices, as a price and innovation incentive and also a source of additional revenue to correct Operationalizing adaptation in a set of regional environments on distributional effects and subsidize the development of new, cost- pathways to a 1.5°C world requires strengthened global and differentiated effective negative-emission technology and infrastructure. However, regional and local capacities. It also needs rapid and decisive adaptation there is high evidence and medium agreement that pricing alone is actions to reduce the costs and magnitude of potential climate impacts insufficient. Even if prices rise significantly, they typically incentivize (Vergara et al., 2015). incremental change, but typically fail to provide the impetus for private actors to take the risk of engaging in the transformational changes This could be facilitated by: (i) enabling conditions, especially improved that would be needed to limit warming to 1.5°C. Apart from the governance, economic measures and financing (Section 4.4); (ii) 383 Chapter 4 Strengthening and Implementing the Global Response enhanced clarity on adaptation options to help identify strategic for which appropriate enabling conditions, such as for technological priorities, sequencing and timing of implementation (Section 4.3); innovations, are fundamentally important. Institutional capacities (iii) robust monitoring and evaluation frameworks; and (iv) political can be enhanced by expanding the role of actors as transformation leadership (Magnan et al., 2015; Magnan and Ribera, 2016; Lesnikowski catalysts (Erlinghagen and Markard, 2012). The integration of ethics et al., 2017; UNEP, 2017a). and justice within these transformations can help attain SDG7 on clean energy access (Jenkins et al., 2018), while inclusion of the cultural 4.5.3.1 Feasible adaptation options dimension and cultural legitimacy (Amars et al., 2017) can provide a more substantial base for societal transformation. Strengthening policy This section summarizes the feasibility (defined in Cross-Chapter Box 3, instruments and regulatory frameworks and enhancing multilevel Table 1 in Chapter 1 and Table 4.4) of select adaptation options using governance that focuses on resilience components can help secure evidence presented across this chapter and in supplementary material these transitions (Exner et al., 2016). 4.SM.4.3 and the expert-judgement of its authors (Table 4.12). The options assessed respond to risks and impacts identified in Chapter 3. For land and ecosystem transitions, the options of conservation They were selected based on options identified in AR5 (Noble et al., agriculture, efficient irrigation, agroforestry, ecosystem restoration 2014), focusing on those relevant to 1.5°C-compatible pathways, where and avoided deforestation, and coastal defence and hardening have sufficient literature exists. Selected options were mapped onto system between medium and robust evidence with medium to high agreement. transitions and clustered through an iterative process of literature The other options assessed have limited or no evidence across one review, expert feedback, and responses to reviewer comments. or more of the feasibility dimensions. Community-based adaptation is assessed as having medium evidence and high agreement to face Besides gaps in the literature around crucial adaptation questions scaling barriers. Scaling community-based adaptation may require on the transition to a 1.5°C world (Section 4.6), there is inadequate structural changes, implying the need for transformational adaptation in current literature to undertake a spatially differentiated assessment some regions. This would involve enhanced multilevel governance and (Cross-Chapter Box 3 in Chapter 1). There are also limited baselines institutional capacities by enabling anticipatory and flexible decision- for exposure, vulnerability and risk to help policy and implementation making systems that access and develop collaborative networks prioritization. Hence, the compiled results can at best provide a broad (Dowd et al., 2014), tackling root causes of vulnerability (Chung Tiam framework to inform policymaking. Given the bottom-up nature of Fook, 2017), and developing synergies between development and most adaptation implementation evidence, care needs to be taken in climate change (Burch et al., 2017). Case studies show the use of generalizing these findings. transformational adaptation approaches for fire management (Colloff et al., 2016a), floodplain and wetland management (Colloff et al., Options are considered as part of a systemic approach, recognizing that 2016b), and forest management (Chung Tiam Fook, 2017), in which no single solution exists to limit warming to 1.5°C and adapting to its the strengthening of policy instruments and climate finance are also 4 impacts. To respond to the local and regional context – and to synergies required. and trade-offs between adaptation, mitigation and sustainable development – packages of options suited to local enabling conditions There is growing recognition of the need for transformational can be implemented. adaptation within the agricultural sector but limited evidence on how to facilitate processes of deep, systemic change (Dowd et al., Table 4.12 summarizes the feasibility assessment through its six 2014). Case studies demonstrate that transformational adaptation in dimensions with levels of evidence and agreement and indicates how agriculture requires a sequencing and overlap between incremental and the feasibility of an adaptation option may be differentiated by certain transformational adaptation actions (Hadarits et al., 2017; Termeer et contextual factors (last column). al., 2017), e.g., incremental improvements to crop management while new crop varieties are being researched and field-tested (Rippke et al., When considered jointly, the description of adaptation options (Section 2016). Broader considerations include addressing stakeholder values 4.3), the feasibility assessment (summarized in Table 4.12), and and attitudes (Fleming et al., 2015a), understanding and leveraging the discussion of enabling conditions (Section 4.4) show us how options role of social capital, collaborative networks, and information (Dowd et can be implemented and lead towards transformational adaptation if al., 2014), and being inclusive with rural and urban communities, and and when needed. the social, political, and cultural environment (Rickards and Howden, 2012). Transformational adaptation in agriculture systems could have The adaptation options for energy system transitions focus on existing significant economic and institutional costs (Mushtaq, 2016), along with power infrastructure resilience and water management, when required, potential unintended negative consequences (Davidson, 2016; Rippke for any type of generation source. These options are not sufficient for et al., 2016; Gajjar et al., 2018; Mushtaq, 2018), and a need to focus the far-reaching transformations required in the energy sector, which on the transitional space between incremental and transformational have tended to focus on technologies to shift from a fossil-based to a adaptation (Hadarits et al., 2017), as well as the timing of the shift from renewable energy system (Erlinghagen and Markard, 2012; Muench one to the other (Läderach et al., 2017). et al., 2014; Brand and von Gleich, 2015; Monstadt and Wolff, 2015; Child and Breyer, 2017; Hermwille et al., 2017). There is also need for Within urban and infrastructure transitions, green infrastructure and integration of such energy system transitions with social-ecological sustainable water management are assessed as the most feasible systems transformations to increase the resilience of the energy sector, options, followed by sustainable land-use and urban planning. The 384 Strengthening and Implementing the Global Response Chapter 4 Table 4.12 | Feasibility assessment of examples of 1.5°C-relevant adaptation options, with dark shading signifying the absence of barriers in the feasibility dimension, moderate shading indicating that, on average, the dimension does not have a positive or negative effect on the feasibility of the option, or the evidence is mixed, and light shading indicating the presence of potentially blocking barriers. No shading means that sufficient literature could not be found to make the assessment. NA signifies that the dimension is not applicable to that adaptation option. For methodology and literature basis, see supplementary material 4.SM.4. Abbreviations used: Ec: Economic - Tec: Technological - Inst: Institutional - Soc: Socio-cultural - Env: Environmental/Ecological - Geo: Geophysical System Adaptation Option Evidence Agreement Ec Tec Inst Soc Env Geo Context Depends on existing power infrastructure, Energy System Power infrastructure, Medium High all generation sources and those with Transitions including water intensive water requirements Conservation Depends on irrigated/rainfed system, ecosystem Medium Medium agriculture characteristics, crop type, other farming practices Depends on agricultural system, technology used, Efficient irrigation Medium Medium regional institutional and biophysical context Efficient livestock Dependent on livestock breeds, feed practices, Limited High systems and biophysical context (e.g., carrying capacity) Depends on knowledge, financial support, and market Agroforestry Medium High Land & conditions Ecosystem Community-based Focus on rural areas and combined with ecosystems- Medium High Transitions adaptation based adaptation, does not include urban settings Ecosystem restoration Mostly focused on existing and evaluated REDD+ Robust Medium & avoided deforestation projects Biodiversity Focus on hotspots of biodiversity vulnerability and Medium Medium management high connectivity Coastal defence Depends on locations that require it as a first Robust Medium & hardening adaptation option Sustainable aquaculture Limited Medium Depends on locations at risk and socio-cultural context Sustainable land-use Depends on nature of planning systems Medium Medium & urban planning and enforcement mechanisms Urban & Sustainable water Balancing sustainable water supply and rising Robust Medium Infrastructure management demand, especially in low-income countries System Green infrastructure Depends on reconciliation of urban development Transitions Medium High& ecosystem services with green infrastructure 4 Building codes Adoption requires legal, educational, and Limited Medium & standards enforcement mechanisms to regulate buildings Industrial Intensive industry Depends on intensive industry, existing infrastructure System infrastructure resilience Limited High and using or requiring high demand of water Transitions and water management Disaster risk Requires institutional, technical, and financial Medium High management capacity in frontline agencies and government Risk spreading and Requires well-developed financial structures and public Medium Medium sharing: insurance understanding Type and mechanism of safety net, political priorities, Social safety nets Medium Medium institutional transparency Depends on climate information avail- Overarching Climate services Medium High ability and usability, local infrastructure Adaptation and institutions, national priorities Options Dependent on recognition of indigenous Indigenous knowledge Medium High rights, laws, and governance systems Education and learning Medium High Existing education system, funding Population health Medium High NA Requires basic health services and infrastructure and health system Hazard exposure, political and socio-cultural Human migration Medium Low acceptability (in destination), migrant skills and social networks 385 Chapter 4 Strengthening and Implementing the Global Response need for transformational adaptation in urban settings arises from the adaptation for the purposes of assessing progress (Dupuis and root causes of poverty, failures in sustainable development, and a lack Biesbroek, 2013; Biesbroek et al., 2015), an absence of comprehensive of focus on social justice (Revi et al., 2014a; Parnell, 2015; Simon and and systematically collected data on adaptation to support longitudinal Leck, 2015; Shi et al., 2016; Ziervogel et al., 2016a; Burch et al., 2017), assessment and comparison (Ford et al., 2015b; Lesnikowski et al., and necessitates a focus on governance structures and the inclusion of 2016), a lack of agreement on indicators to measure (Brooks et al., equity and justice concerns (Bos et al., 2015; Shi et al., 2016; Hölscher 2013; Bours et al., 2015; Lesnikowski et al., 2015), and challenges of et al., 2018). attributing altered vulnerability to adaptation actions (Ford et al., 2013; Bours et al., 2015; UNEP, 2017a). Current implementation of urban ecosystems-based adaptation (EbA) lacks a systems perspective of transformations and consideration of 4.5.4 Synergies and Trade-Offs between the normative and ethical aspects of EbA (Brink et al., 2016). Flexibility Adaptation and Mitigation within urban planning could help deal with the multiple uncertainties of implementing adaptation (Rosenzweig and Solecki, 2014; Implementing a particular mitigation or adaptation option may affect the Radhakrishnan et al., 2018), for example, urban adaptation pathways feasibility and effectiveness of other mitigation and adaptation options. were implemented in the aftermath of Superstorm Sandy in New York, Supplementary Material 4.SM.5.1 provides examples of possible positive which is considered as tipping point that led to the implementation of impacts (synergies) and negative impacts (trade-offs) of mitigation transformational adaptation practices. options for adaptation. For example, renewable energy sources such as wind energy and solar PV combined with electricity storage can increase Adaptation options for industry focus on infrastructure resilience resilience due to distributed grids, thereby enhancing both mitigation and water management. Like with energy system transitions, and adaptation. Yet, as another example, urban densification may reduce technological innovation would be required, but also the enhancement GHG emissions, enhancing mitigation, but can also intensify heat island of institutional capacities. Recent research illustrates transformational effects and inhibit restoration of local ecosystems if not accounted for, adaptation within industrial transitions focusing on the role of thereby increasing adaptation challenges. different actors and tools driving innovation, and points to the role of nationally appropriate mitigation actions in avoiding lock-ins and The table in Supplementary Material 4.SM.5.2 provides examples promoting system innovation (Boodoo and Olsen, 2017), the role of of synergies and trade-offs of adaptation options for mitigation. It private sector in sustainability governance in the socio-political context shows, for example, that conservation agriculture can reduce some (Burch et al., 2016), and of green entrepreneurs driving transformative GHG emissions and thus enhance mitigation, but at the same time can change in the green economy (Gibbs and O’Neill, 2014). Lim-Camacho increase other GHG emissions, thereby reducing mitigation potential. et al. (2015) suggest an analysis of the complete lifecycle of supply As another example, agroforestry can reduce GHG emissions through chains as a means of identifying additional adaptation strategies, as reduced deforestation and fossil fuel consumption but has a lower 4 opposed to the current focus on a part of the supply chain. Chain-wide carbon sequestration potential compared with natural and secondary strategies can modify the rest of the chain and present a win-win with forest. commercial objectives. Maladaptive actions could increase the risk of adverse climate-related The assessed adaptation options also have mitigation synergies outcomes. For example, biofuel targets could lead to indirect land use and trade-offs (assessed in Section 4.5.4) that need to be carefully change and influence local food security, through a shift in land use considered, while planning climate action. abroad in response to increased domestic biofuel demand, increasing global GHG emissions rather than decreasing them. 4.5.3.2 Monitoring and evaluation Various options enhance both climate change mitigation and Monitoring and evaluation (M&E) in adaptation implementation can adaptation, and would hence serve two 1.5°C-related goals: reducing promote accountability and transparency of adaptation financing, emissions while adapting to the associated climate change. Examples facilitate policy learning and sharing good practices, pressure laggards, of such options are reforestation, urban and spatial planning, and land and guide adaptation planning. The majority of research on M&E focuses and water management. on specific policies or programmes, and has typically been driven by the needs of development organizations, donors, and governments to Synergies between mitigation and adaptation may be enhanced, and measure the impact and attribution of adaptation initiatives (Ford and trade-offs reduced, by considering enabling conditions (Section 4.4), Berrang-Ford, 2016). There is growing research examining adaptation while trade-offs can be amplified when enabling conditions are not progress across nations, sectors, and scales (Reckien et al., 2014; Araos considered (C.A. Scott et al., 2015). For example, information that et al., 2016a, b; Austin et al., 2016; Heidrich et al., 2016; Lesnikowski et is tailored to the personal situation of individuals and communities, al., 2016; Robinson, 2017). In response to a need for global, regional including climate services that are credible and targeted at the point and local adaptation, the development of indicators and standardized of decision-making, can enable and promote both mitigation and approaches to evaluate and compare adaptation over time and adaptation actions (Section 4.4.3). Similarly, multilevel governance across regions, countries, and sectors would enhance comparability and community participation, respectively, can enable and promote and learning. A number of constraints continue to hamper progress both adaptation and mitigation actions (Section 4.4.1). Governance, on adaptation M&E, including a debate on what actually constitutes policies and institutions can facilitate the implementation of the water– 386 Strengthening and Implementing the Global Response Chapter 4 energy–food (WEF) nexus (Rasul and Sharma, 2016). The WEF nexus et al., 2015; Gwedla and Shackleton, 2015; Lwasa et al., 2015; Yang can enhance food, water and energy security, particularly in cities with et al., 2016; Sanesi et al., 2017). In the case of electricity generation, agricultural production areas (Biggs et al., 2015), electricity generation enabling conditions through a combination of carefully selected policy with intensive water requirements (Conway et al 2015), and in instruments can maximize the synergic benefits between low GHG agriculture (El Gafy et al., 2017) and livelihoods (Biggs et al., 2015). Such energy production and water for energy (Shang et al., 2018). Despite a nexus approach can reduce the transport energy that is embedded the multiple benefits of maximizing synergies between mitigation in food value chains (Villarroel Walker et al., 2014), providing diverse and adaptations options through the WEF nexus approach (Chen and sources of food in the face of changing climates (Tacoli et al., 2013). Chen, 2016), there are implementation challenges given institutional Urban agriculture, where integrated, can mitigate climate change and complexity, political economy, and interdependencies between actors support urban flood management (Angotti, 2015; Bell et al., 2015; Biggs (Leck et al., 2015). Box 4.10 | Bhutan: Synergies and Trade-Offs in Economic Growth, Carbon Neutrality and Happiness Bhutan has three national goals: improving its gross national happiness index (GNHI), improving its economic growth (gross domestic product, GDP) and maintaining its carbon neutrality. These goals increasingly interact and raise questions about whether they can be sustainably maintained into the future. Interventions in this enabling environment are required to comply with all three goals. Bhutan is well known for its GNHI, which is based on a variety of indicators covering psychological well-being, health, education, cultural and community vitality, living standards, ecological issues and good governance (RGoB, 2012; Schroeder and Schroeder, 2014; Ura, 2015). The GNHI is a precursor to the Sustainable Development Goals (SDGs) (Allison, 2012; Brooks, 2013) and reflects local enabling environments. The GNHI has been measured twice, in 2010 and 2015, and this showed an increase of 1.8% (CBS & GNH, 2016). Like most emerging countries, Bhutan wants to increase its wealth and become a middle-income country (RGoB, 2013, 2016), while remaining carbon-neutral – a goal which has been in place since 2009 at COP15 and was reiterated in its Intended Nationally Determined Contribution (NEC, 2015). Bhutan achieves its current carbon-neutral status through hydropower and forest cover (Yangka and Diesendorf, 2016), which are part of its resilience and adaptation strategy. Nevertheless, Bhutan faces rising GHG emissions. Transport and industry are the largest growth areas (NEC, 2011). Bhutan’s carbon- neutral status would be threatened by 2044 with business-as-usual approaches to economic growth (Yangka and Newman, 2018). Increases in hydropower are being planned based on climate change scenarios that suggest sufficient water supply will be available 4 (NEC, 2011). Forest cover is expected to remain sufficient to maintain co-benefits. The biggest challenge is to electrify both freight and passenger transport (ADB, 2013). Bhutan wants to be a model for achieving economic growth consistent with limiting climate change to 1.5°C and improving its GNHI (Michaelowa et al., 2018) through synthesizing all three goals and improving its adaptive capacity. 4.6 Knowledge Gaps and Key Uncertainties land transitions that are compliant with sustainable development, poverty eradication and addressing inequality? What are life-cycle The global response to limiting warming to 1.5°C is a new knowledge emissions and prospects of early-stage CDR options? How can climate area, which has emerged after the Paris Agreement. This section and sustainable development policies converge, and how can they presents a number of knowledge gaps that have emerged from the be organized within a global governance framework and financial assessment of mitigation, adaptation and carbon dioxide removal system, based on principles of justice and ethics (CBDR-RC), reciprocity (CDR) options and solar radiation modification (SRM) measures; and partnership? To what extent would limiting warming to 1.5°C enabling conditions; and synergies and trade-offs. Illustrative questions require a harmonization of macro-financial and fiscal policies, which that emerge synthesizing the more comprehensive Table 4.13 below could include central banks? How can different actors and processes include: how much can be realistically expected from innovation, in climate governance reinforce each other, and hedge against the behaviour and systemic political and economic change in improving fragmentation of initiatives? resilience, enhancing adaptation and reducing GHG emissions? How can rates of changes be accelerated and scaled up? What is These knowledge gaps are highlighted in Table 4.13 along with a cross- the outcome of realistic assessments of mitigation and adaptation reference to the respective sections in the last column. 387 Chapter 4 Strengthening and Implementing the Global Response Table 4.13 | Knowledge gaps and uncertainties Knowledge Area Mitigation Adaptation Reference • Lack of literature specific to 1.5°C on investment costs with • Lack of literature specific to 1.5°C on adaptation costs detailed breakdown by technology and need • Lack of literature specific to 1.5°C on mitigation costs in • Lack of literature on what overshoot means for adaptation terms of GDP and welfare • Lack of knowledge on avoided adaptation investments • Lack of literature on distributional implications of 1.5°C associated with limiting warming to 1.5°C, 2°C or 1.5°C Pathways and compared to 2°C or business-as-usual at sectoral business-as-usual 4.2 Ensuing Change and regional levels • Limited 1.5°C-specific case studies for adaptation • Limited 1.5°C-specific case studies for mitigation • Scant literature examining current or future adaptation options, • Limited knowledge on the systemic and dynamic aspects of or examining what different climate pathways mean for transitions to 1.5°C, including how vicious or virtuous circles adaptation success might work, how self-reinforcing aspects can be actively • Need for transformational adaptation at 1.5°C and beyond introduced and managed remains largely unexplored • The shift to variable renewables that many countries are • Relatively little literature on individual adaptation options implementing is just reaching a level where large-scale since AR5 storage systems or other grid flexibility options, e.g., demand • No evidence on socio-cultural acceptability of adaptation response, are required to enable resilient grid systems. Thus, options new knowledge on the opportunities and issues associated • Lack of regional research on the implementation of adaptation with scaling up zero-carbon grids would be needed, including options knowledge about how zero-carbon electric grids can integrate with the full-scale electrification of transport systems Energy • CCS suffers mostly from uncertainty about the feasibility 4.3.1 Systems of timely upscaling, both due to lack of regulatory capacity and concerns about storage safety and cost • There is not much literature on the distributional implications of large-scale bioenergy deployment, the assessment of environmental feasibility is hampered by a diversity of contexts of individual studies (type of feedstock, technology, land availability), which could be improved through emerging meta-studies • More knowledge would be needed on how land-based • Regional information on some options does not exist, mitigation can be reconciled with land demands for especially in the case of land-use transitions adaptation and development • Limited research examining socio-cultural perspectives and • While there is now more literature on the underlying impacts of adaptation options, especially for efficient irrigation, mechanisms of land transitions, data is often insufficient coastal defence and hardening, agroforestry and biodiversity to draw robust conclusions, and there is uncertainty about management 4 land availability • Lack of longitudinal, regional studies assessing the impacts of • The lack of data on social and institutional information certain adaptation options, such as conservation agriculture (largest knowledge gap indicated for ecosystems restoration and shifting to efficient livestock systems Options to in Table 4.11), which are therefore not widely integrated in • More knowledge is needed on the cost-effectiveness and Achieve land use modelling scalability of various adaptation options. For example, there and Adapt • Examples of successful policy implementation and institutions is no evidence for the macro-economic viability of community- to 1.5°C related to land-based mitigation leading to co-benefits for based adaptation (CbA) and biodiversity management, or on adaptation and development are missing from the literature employment and productivity enhancement potential for Land & • There is relatively little scientific literature on the effects biodiversity management and coastal defence and hardening. 4.3.2 ecosystems of dietary shifts and reduction of food wastage on mitigation, • More knowledge is needed on risk mitigation and the potential especially regarding the institutional, technical and of biodiversity management environmental concerns • Lack of evidence of the political acceptability of efficient livestock systems • Limited evidence on legal and regulatory feasibility of conservation agriculture and no evidence on coastal defence and hardening • For transparency and accountability potential, there is limited evidence for conservation agriculture and no evidence for biodiversity management, coastal defence and hardening and sustainable aquaculture • No evidence on hazard risk reduction potential of conservation agriculture and biodiversity management • Limited evidence of effective land-use planning in low-income • Regional and sectoral adaptation cost assessments are missing, cities where tenure and land zoning are contested, and the particularly in the context of welfare losses of households, risks of trying to implement land-use planning under across time and space Urban & communal tenure • More knowledge is needed on the political economy of infrastructure • Limited evidence on the governance of public transport from adaptation, particularly on how to impute different types of 4.3.3 systems an accountability and transparency perspective cost and benefit in a consistent manner, on adaptation performance indicators that could stimulate investment, and the impact of adaptation interventions on socio-economic and other types of inequality 388 Strengthening and Implementing the Global Response Chapter 4 Table 4.13 (continued) Knowledge Area Mitigation Adaptation Reference • Limited evidence on relationship between toxic waste • More evidence would be needed on hot-spots, for example and public transport the growth of peri-urban areas populated by large informal • Limited evidence on the impacts of electric vehicles and settlements non-motorized urban transport, as most schemes are too new • Major uncertainties emanate from the lack of knowledge on • As changes in shipping and aviation have been limited to the integration of climate adaptation and mitigation, disaster date, limited evidence of social impacts risk management, and urban poverty alleviation • Knowledge about how to facilitate disruptive, demand-based • There is limited evidence on the institutional, technological innovations that may be transformative in urban systems, and economic feasibility of green infrastructure and is needed environmental services and for socio-cultural and • Understanding of the urban form implications of combined environmental feasibility of codes and standards Urban & changes from electric, autonomous and shared/public mobility • In general, there is no evidence for the employment and infrastructure 4.3.3 systems, is needed productivity enhancement potential of most adaptation options. systems • Considering distributional consequences of climate responses • There is limited evidence on the economic feasibility of is an on-going need sustainable water management • Knowledge gaps in the application and scale up of combinations of new smart technologies, sustainable design, advanced construction techniques and new insulation materials, renewable energy and behaviour change in urban settlements • The potential for leapfrog technologies to be applied to slums and new urban developments in developing countries is weak. • Lack of knowledge on potential for scaling up and global • Very limited evidence on how industry would adapt to the diffusion of zero- and low-emission technologies in industry consequences of 1.5°C or 2°C temperature increases, in • Questions remain on the socio-cultural feasibility of industry particular large and immobile industrial clusters in low-lying options, including human capacity and private sector areas as well as availability of transportation and (cooling) acceptance of new, radically different technologies from water resources and infrastructure Options to current well-developed practices, as well as distributional • There is limited evidence on the economic, institutional and Achieve effects of potential new business models socio-cultural feasibility of adaptation options available and Adapt • As the industrial transition unfolds, lack of knowledge on to industry to 1.5°C its dynamic interactions with other sectors, in particular with the power sector (and infrastructure) for electrification of Industrial industry, with food production and other users of biomass 4.3.4 systems in case of bio-based industry developments, and with CDR technologies in the case of CC(U)S • Life-cycle assessment-based comparative analyses of CCUS options are missing, as well as life-cycle information on 4 electrification and hydrogen • Impacts of industrial system transitions are not well understood, especially on employment, identity and well-being, in particular in the case of substitution of conventional, high-carbon industrial products with lower-carbon alternatives, as well as electrification and use of hydrogen • There is no evidence on technical and institutional feasibility of educational options • There is limited evidence on employment and productivity enforcement potential of climate services Overarching • There is limited evidence on socio-cultural acceptability of social safety nets adaptation 4.3.5 • There is a small but growing literature on human migration as an adaptation strategy. Scant literature on the cost-effectiveness options of migration • Limited evidence of co-benefits and trade-offs of SLCF reduction (e.g., better health outcomes, agricultural productivity improvements) Short-lived • Integration of SLCFs into emissions accounting and climate 4.3.6 international reporting mechanisms enabling a better forcers understanding of the links between black carbon, air pollution, climate change and agricultural productivity 389 Chapter 4 Strengthening and Implementing the Global Response Table 4.13 (continued) Knowledge Area Mitigation Adaptation Reference • A bottom-up analysis of CDR options indicates that there are still key uncertainties around the individual technologies. Ocean-based options will be assessed in depth in the IPCC Special Report on the Ocean and Cryosphere in a Changing Climate (SROCC) • Assessments of environmental aspects are missing, especially for ‘newer’ options like enhanced weathering or direct air carbon capture • In order to obtain more information on realistically available and sustainable removal potentials, more bottom-up, regional Options Carbon studies, also taking into account also social issues, would to Achieve dioxide be needed. These can better inform the modelling of 1.5°C 4.3.7 and Adapt removal pathways to 1.5°C • Knowledge gaps on issues of governance and public acceptance, the impacts of large-scale removals on the carbon cycle, the potential to accelerate deployment and upscaling, and means of incentivization • Knowledge gaps on integrated systems of renewable energy and CDR technologies such as enhanced weathering and DACCS • Knowledge gaps on under which conditions the use of captured CO2 is generating negative emissions and would qualify as a mitigation option • In spite of increasing attention to the different SRM measures and their potential to keep global temperature below 1.5°C, Solar radiation knowledge gaps remain, not only with respect to the physical understanding of SRM measures but also concerning ethical issues 4.3.8 modification (SRM) • We do not know how to govern SRM in order to avoid unilateral action and how to prevent possible reductions in mitigation (‘moral hazard’) • As technological changes have begun to accelerate, there is • The ability to identify explanatory factors affecting the progress a lack of knowledge on new mechanisms that can enable of climate policy is constrained by a lack of data on adaptation private enterprise to mainstream this activity, and reasons actions across nations, regions, and sectors, compounded by an for success and failure need to be researched absence of frameworks for assessing progress. Most • Research is thin on effective multilevel governance, in hypotheses on what drives adaptation remain untested particular in developing countries, including participation • Limited empirical assessment of how governance affects by civil society, women and minorities adaptation across cases Governance 4.4.1 • Gaps in knowledge remain pertaining to partnerships within • Focus on ‘success’ stories and leading adaptors overlooks 4 local governance arrangements that may act as mediators lessons from situations where no or unsuccessful and drivers for achieving global ambition and local action adaptation is taking place • Methods for assessing contribution and aggregation of non-state actors in limiting warming to 1.5°C • Knowledge gap on an enhanced framework for assessment of the ambition of NDCs • Lack of 1.5°C-specific literature • Role of regulatory financial institutions and their capacity to guarantee financial stability of economies when investments potentially face risks, both because of climate impacts and because of the systems transitions if lower temperature scenarios are pursued • Knowledge gaps on how to build capabilities across all countries and regions globally to implement, maintain, manage, govern and further develop mitigation options for 1.5°C. Enabling • While importance of indigenous and local knowledge is recognized, the ability to scale up beyond the local remains challenging Conditions Institutions and little examined 4.4.2 • There is a lack of monitoring and evaluation (M&E) of adaptation measures, with most studies enumerating M&E challenges and emphasising the importance of context and social learning. Very few studies evaluate whether and why an adaptation initiative has been effective. One of the challenges of M&E for both mitigation and adaptation is a lack of high quality information for modelling. Adaptation M&E is additionally challenged by limited understanding on what indicators to measure and how to attribute altered vulnerability to adaptation actions • Whereas mitigation pathways studies address (implicitly or • Knowledge gaps on factors enabling adaptation behaviour, explicitly) the reduction or elimination of market failures except for behaviour in agriculture. (e.g., external costs, information asymmetries) via climate or • Little is known about cognitive and motivational factors energy policies, no study addresses behavioural change promoting adaptive behaviour. strategies in the relationship with mitigation and adaptation • Little is known about how potential adaptation actions might Lifestyle and actions in the 1.5°C context affect behaviour to influence vulnerability outcomes behavioural • Limited knowledge on GHG emissions reduction potential of 4.4.3 change diverse mitigation behaviour across the world • Most studies on factors enabling lifestyle changes have been conducted in high-income countries, more knowledge needed from low- and middle-income countries, and the focus is typically on enabling individual behaviour change, far less on enabling change in organizations and political systems 390 Strengthening and Implementing the Global Response Chapter 4 Table 4.13 (continued) Knowledge Area Mitigation Adaptation Reference • Limited understanding and treatment of behavioural change Lifestyle and and the potential effects of related policies in ambitious behavioural mitigation pathways, e.g., in Integrated Assessment Models 4.4.3 change Lack of insight on what can enable changes in adaptation and mitigation behaviour in organizations and political systems • Quantitative estimates for mitigation and adaptation potentials at economy or sector scale as a result of the combination of general purpose technologies and mitigation technologies have been scarce, except for some evidence in the transport sector Technological Enabling • Evidence on the role of international organizations, including the UNFCCC, in building capabilities and enhancing technological 4.4.4 innovation Conditions innovation for 1.5°C, except for some parts of the transport sector • Technology transfer trials to enable leapfrog applications in developing countries have limited evidence • More empirical research would be needed to derive • Understanding of what policies work (and do not work) is robust conclusions on effectiveness of policies for limited for adaptation in general and for 1.5°C in Policy 4.4.5 enabling transitions to 1.5°C and on which factors aid particular, beyond specific case studies decision-makers seeking to ratchet up their NDCs Finance Knowledge gaps persist with respect to the instruments to match finance to its most effective use in mitigation and adaptation 4.4.5 • Strong claims are made with respect to synergies and trade-offs, but there is little knowledge to underpin these, especially of co-benefits by region • Water–energy conservation relationships of individual conservation measures in industries other than the water and energy sectors have not been investigated in detail Synergies and Trade-Offs • There is no evidence on synergies with adaptation of CCS in the power sector and of enhanced weathering under carbon Between Adaptation dioxide removal 4.5.4 and Mitigation • There is no evidence on trade-offs with adaptation of low- and zero-energy buildings, and circularity and substitution and bio-based industrial system transitions • There is no evidence of synergies or trade-offs with mitigation of CbA • There is no evidence of trade-offs with mitigation of the built environment, on adaptation options for industrial energy, and climate services 4 391 Chapter 4 Strengthening and Implementing the Global Response Frequently Asked Questions FAQ 4.1 | What Transitions could Enable Limiting Global Warming to 1.5°C? Summary: In order to limit warming to 1.5°C above pre-industrial levels, the world would need to transform in a number of complex and connected ways. While transitions towards lower greenhouse gas emissions are underway in some cities, regions, countries, businesses and communities, there are few that are currently consistent with limiting warming to 1.5°C. Meeting this challenge would require a rapid escalation in the current scale and pace of change, particularly in the coming decades. There are many factors that affect the feasibility of different adaptation and mitigation options that could help limit warming to 1.5°C and with adapting to the consequences. There are actions across all sectors that can substantially reduce greenhouse gas emissions. This Special Report assesses energy, land and ecosystems, urban and infrastructure, and industry in developed and developing nations to see how they would need to be transformed to limit warming to 1.5°C. Examples of actions include shifting to low- or zero-emission power generation, such as renewables; changing food systems, such as diet changes away from land-intensive animal products; electrifying transport and developing ‘green infrastructure’, such as building green roofs, or improving energy efficiency by smart urban planning, which will change the layout of many cities. Because these different actions are connected, a ‘whole systems’ approach would be needed for the type of transformations that could limit warming to 1.5°C. This means that all relevant companies, industries and stakeholders would need to be involved to increase the support and chance of successful implementation. As an illustration, the deployment of low-emission technology (e.g., renewable energy projects or a bio-based chemical plants) would depend upon economic conditions (e.g., employment generation or capacity to mobilize investment), but also on social/cultural conditions (e.g., awareness and acceptability) and institutional conditions (e.g., political support and understanding). To limit warming to1.5°C, mitigation would have to be large-scale and rapid. Transitions can be transformative or incremental, and they often, but not always, go hand in hand. Transformative change can arise from growth in demand for a new product or market, such that it displaces an existing one. This is sometimes called ‘disruptive innovation’. For example, high demand for LED lighting is now making more energy-intensive, incandescent 4 lighting near-obsolete, with the support of policy action that spurred rapid industry innovation. Similarly, smart phones have become global in use within ten years. But electric cars, which were released around the same time, have not been adopted so quickly because the bigger, more connected transport and energy systems are harder to change. Renewable energy, especially solar and wind, is considered to be disruptive by some as it is rapidly being adopted and is transitioning faster than predicted. But its demand is not yet uniform. Urban systems that are moving towards transformation are coupling solar and wind with battery storage and electric vehicles in a more incremental transition, though this would still require changes in regulations, tax incentives, new standards, demonstration projects and education programmes to enable markets for this system to work. Transitional changes are already underway in many systems, but limiting warming to 1.5°C would require a rapid escalation in the scale and pace of transition, particularly in the next 10–20 years. While limiting warming to 1.5°C would involve many of the same types of transitions as limiting warming to 2°C, the pace of change would need to be much faster. While the pace of change that would be required to limit warming to 1.5°C can be found in the past, there is no historical precedent for the scale of the necessary transitions, in particular in a socially and economically sustainable way. Resolving such speed and scale issues would require people’s support, public-sector interventions and private-sector cooperation. Different types of transitions carry with them different associated costs and requirements for institutional or governmental support. Some are also easier to scale up than others, and some need more government support than others. Transitions between, and within, these systems are connected and none would be sufficient on its own to limit warming to 1.5°C. The ‘feasibility’ of adaptation and mitigation options or actions within each system that together can limit warming to 1.5°C within the context of sustainable development and efforts to eradicate poverty requires careful consideration of multiple different factors. These factors include: (i) whether sufficient natural systems and resources are available to support the various options for transitioning (known as environmental feasibility); (ii) the degree to which the required technologies are developed and available (known as technological feasibility); 392 Strengthening and Implementing the Global Response Chapter 4 FAQ 4.1 (continued) (iii) the economic conditions and implications (known as economic feasibility); (iv) what are the implications for human behaviour and health (known as social/cultural feasibility); and (v) what type of institutional support would be needed, such as governance, institutional capacity and political support (known as institutional feasibility). An additional factor (vi – known as the geophysical feasibility) addresses the capacity of physical systems to carry the option, for example, whether it is geophysically possible to implement large-scale afforestation consistent with 1.5°C. Promoting enabling conditions, such as finance, innovation and behaviour change, would reduce barriers to the options, make the required speed and scale of the system transitions more likely, and therefore would increase the overall feasibility limiting warming to 1.5°C. 4 FAQ 4.1, Figure 1 | The different dimensions to consider when assessing the ‘feasibility’ of adaptation and mitigation options or actions within each system that can help to limit warming to 1.5°C. These are: (i) the environmental feasibility; (ii) the technological feasibility; (iii) the economic feasibility; (iv) the social/cultural feasibility; (v) the institutional feasibility; and (vi) the geophysical feasibility. 393 Chapter 4 Strengthening and Implementing the Global Response Frequently Asked Questions FAQ 4.2 | What are Carbon Dioxide Removal and Negative Emissions? Summary: Carbon dioxide removal (CDR) refers to the process of removing CO2 from the atmosphere. Since this is the opposite of emissions, practices or technologies that remove CO2 are often described as achieving ‘negative emissions’. The process is sometimes referred to more broadly as greenhouse gas removal if it involves removing gases other than CO2. There are two main types of CDR: either enhancing existing natural processes that remove carbon from the atmosphere (e.g., by increasing its uptake by trees, soil, or other ‘carbon sinks’) or using chemical processes to, for example, capture CO2 directly from the ambient air and store it elsewhere (e.g., underground). All CDR methods are at different stages of development and some are more conceptual than others, as they have not been tested at scale. Limiting warming to 1.5°C above pre-industrial levels would require unprecedented rates of transformation in many areas, including in the energy and industrial sectors, for example. Conceptually, it is possible that techniques to draw CO2 out of the atmosphere (known as carbon dioxide removal, or CDR) could contribute to limiting warming to 1.5°C. One use of CDR could be to compensate for greenhouse gas emissions from sectors that cannot completely decarbonize, or which may take a long time to do so. If global temperature temporarily overshoots 1.5°C, CDR would be required to reduce the atmospheric concentration of CO2 to bring global temperature back down. To achieve this temperature reduction, the amount of CO2 drawn out of the atmosphere would need to be greater than the amount entering the atmosphere, resulting in ‘net negative emissions’. This would involve a greater amount of CDR than stabilizing atmospheric CO2 concentration – and, therefore, global temperature – at a certain level. The larger and longer an overshoot, the greater the reliance on practices that remove CO2 from the atmosphere. There are a number of CDR methods, each with different potentials for achieving negative emissions, as well as different associated costs and side effects. They are also at differing levels of development, with some more conceptual than others. One example of a CDR method in the demonstration phase is a process known as bioenergy with carbon capture and storage (BECCS), in which atmospheric CO2 is absorbed by plants and trees as they grow, and then the plant material (biomass) is burned to produce bioenergy. The CO2 released in the 4 production of bioenergy is captured before it reaches the atmosphere and stored in geological formations deep underground on very long time scales. Since the plants absorb CO2 as they grow and the process does not emit CO2, the overall effect can be to reduce atmospheric CO2. Afforestation (planting new trees) and reforestation (replanting trees where they previously existed) are also considered forms of CDR because they enhance natural CO2 ‘sinks’. Another category of CDR techniques uses chemical processes to capture CO2 from the air and store it away on very long time scales. In a process known as direct air carbon capture and storage (DACCS), CO2 is extracted directly from the air and stored in geological formations deep underground. Converting waste plant material into a charcoal-like substance called biochar and burying it in soil can also be used to store carbon away from the atmosphere for decades to centuries. There can be beneficial side effects of some types of CDR, other than removing CO2 from the atmosphere. For example, restoring forests or mangroves can enhance biodiversity and protect against flooding and storms. But there could also be risks involved with some CDR methods. For example, deploying BECCS at large scale would require a large amount of land to cultivate the biomass required for bioenergy. This could have consequences for sustainable development if the use of land competes with producing food to support a growing population, biodiversity conservation or land rights. There are also other considerations. For example, there are uncertainties about how much it would cost to deploy DACCS as a CDR technique, given that removing CO2 from the air requires considerable energy. 394 Strengthening and Implementing the Global Response Chapter 4 FAQ 4.2 (continued) FAQ 4.2, Figure 1 | Carbon dioxide removal (CDR) refers to the process of removing CO2 from the atmosphere. There are a number of CDR techniques, each with different potential for achieving ‘negative emissions’, as well as different associated costs and side effects. 4 395 Chapter 4 Strengthening and Implementing the Global Response Frequently Asked Questions FAQ 4.3 | Why is Adaptation Important in a 1.5°C-Warmer World? Summary: Adaptation is the process of adjusting to current or expected changes in climate and its effects. Even though climate change is a global problem, its impacts are experienced differently across the world. This means that responses are often specific to the local context, and so people in different regions are adapting in different ways. A rise in global temperature from the current 1°C above pre-industrial levels to 1.5°C, and beyond, increases the need for adaptation. Therefore, stabilizing global temperatures at 1.5°C above pre-industrial levels would require a smaller adaptation effort than at 2°C. Despite many successful examples around the world, progress in adaptation is, in many regions, in its infancy and unevenly distributed globally. Adaptation refers to the process of adjustment to actual or expected changes in climate and its effects. Since different parts of the world are experiencing the impacts of climate change differently, there is similar diversity in how people in a given region are adapting to those impacts. The world is already experiencing the impacts from 1°C of global warming above pre-industrial levels, and there are many examples of adaptation to impacts associated with this warming. Examples of adaptation efforts taking place around the world include investing in flood defences such as building sea walls or restoring mangroves, efforts to guide development away from high risk areas, modifying crops to avoid yield reductions, and using social learning (social interactions that change understanding on the community level) to modify agricultural practices, amongst many others. Adaptation also involves building capacity to respond better to climate change impacts, including making governance more flexible and strengthening financing mechanisms, such as by providing different types of insurance. In general, an increase in global temperature from present day to 1.5°C or 2°C (or higher) above pre-industrial temperatures would increase the need for adaptation. Stabilizing global temperature increase at 1.5°C would require a smaller adaptation effort than for 2°C. Since adaptation is still in early stages in many regions, there are questions about the capacity of vulnerable communities to cope with any amount of further warming. Successful adaptation can be supported at 4 the national and sub-national levels, with national governments playing an important role in coordination, planning, determining policy priorities, and distributing resources and support. However, given that the need for adaptation can be very different from one community to the next, the kinds of measures that can successfully reduce climate risks will also depend heavily on the local context. When done successfully, adaptation can allow individuals to adjust to the impacts of climate change in ways that minimize negative consequences and to maintain their livelihoods. This could involve, for example, a farmer switching to drought-tolerant crops to deal with increasing occurrences of heatwaves. In some cases, however, the impacts of climate change could result in entire systems changing significantly, such as moving to an entirely new agricultural system in areas where the climate is no longer suitable for current practices. Constructing sea walls to stop flooding due to sea level rise from climate change is another example of adaptation, but developing city planning to change how flood water is managed throughout the city would be an example of transformational adaptation. These actions require significantly more institutional, structural, and financial support. While this kind of transformational adaptation would not be needed everywhere in a 1.5°C world, the scale of change needed would be challenging to implement, as it requires additional support, such as through financial assistance and behavioural change. Few empirical examples exist to date. Examples from around the world show that adaptation is an iterative process. Adaptation pathways describe how communities can make decisions about adaptation in an ongoing and flexible way. Such pathways allow for pausing, evaluating the outcomes of specific adaptation actions, and modifying the strategy as appropriate. Due to their flexible nature, adaptation pathways can help to identify the most effective ways to minimise the impacts of present and future climate change for a given local context. This is important since adaptation can sometimes exacerbate vulnerabilities and existing inequalities if poorly designed. The unintended negative consequences of adaptation that can sometimes occur are known as ‘maladaptation’. Maladaptation can be seen if a particular adaptation option has negative consequences for some (e.g., rainwater harvesting upstream might reduce water availability downstream) or if an adaptation intervention in the present has trade-offs in the future (e.g., desalination plants may improve water availability in the present but have large energy demands over time). 396 Strengthening and Implementing the Global Response Chapter 4 FAQ 4.3 (continued) While adaptation is important to reduce the negative impacts from climate change, adaptation measures on their own are not enough to prevent climate change impacts entirely. The more global temperature rises, the more frequent, severe, and erratic the impacts will be, and adaptation may not protect against all risks. Examples of where limits may be reached include substantial loss of coral reefs, massive range losses for terrestrial species, more human deaths from extreme heat, and losses of coastal-dependent livelihoods in low lying islands and coasts. 4 FAQ 4.3, Figure 1 | Why is adaptation important in a world with global warming of 1.5°C? Examples of adaptation and transformational adaptation. Adapting to further warming requires action at national and sub-national levels and can mean different things to different people in different contexts. While transformational adaptation would not be needed everywhere in a world limited to 1.5°C warming, the scale of change needed would be challenging to implement. 397 Chapter 4 Strengthening and Implementing the Global Response References Aakre, S., S. Kallbekken, R. Van Dingenen, and D.G. Victor, 2018: Incentives for small Afionis, S., L.C. Stringer, N. Favretto, J. Tomei, and M.S. 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Suarez Rodriguez (Cuba) Contributing Authors: Fernando Aragón-Durand (Mexico), Mustapha Babiker (Sudan), Mook Bangalore (USA), Paolo Bertoldi (Italy), Bishwa Bhaskar Choudhary (India), Edward Byres (Austria/Brazil), Anton Cartwright (South Africa), Riyanti Djalante (Japan/Indonesia), Kristie L. Ebi (USA), Neville Ellis (Australia), Francois Engelbrecht (South Africa), Maria Figueroa (Denmark/Venezuela), Mukesh Gupta (India), Diana Hinge Salili (Vanuatu), Daniel Huppmann (Austria), Saleemul Huq (Bangladesh/UK), Daniela Jacob (Germany), Rachel James (UK), Debora Ley (Guatemala/Mexico), Peter Marcotullio (USA), Omar Massera (Mexico), Reinhard Mechler (Germany), Haileselassie Amaha Medhin (Ethiopia), Shagun Mehrotra (USA/India), Peter Newman (Australia), Karen Paiva Henrique (Brazil), Simon Parkinson (Canada), Aromar Revi (India), Wilfried Rickels (Germany), Lisa Schipper (UK/Sweden), Jörn Schmidt (Germany), Seth Schultz (USA), Pete Smith (UK), William Solecki (USA), Shreya Some (India), Nenenteiti Teariki-Ruatu (Kiribati), Adelle Thomas (Bahamas), Penny Urquhart (South Africa), Margaretha Wewerinke-Singh (Netherlands) Review Editors: Svitlana Krakovska (Ukraine), Ramon Pichs Madruga (Cuba), Roberto Sanchez (Mexico) Chapter Scientist: Neville Ellis (Australia) This chapter should be cited as: Roy, J., P. Tschakert, H. Waisman, S. Abdul Halim, P. Antwi-Agyei, P. Dasgupta, B. Hayward, M. Kanninen, D. Liverman, C. Okereke, P.F. Pinho, K. Riahi, and A.G. Suarez Rodriguez, 2018: Sustainable Development, Poverty Eradication and Reducing Inequalities. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)]. In Press. 445 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities Table of Contents Executive Summary ...................................................................447 5.5 Sustainable Development Pathways to 1.5°C .....466 5.1 Scope and Delineations ..............................................450 5.5.1 Integration of Adaptation, Mitigation and Sustainable Development ....................................467 5.1.1 Sustainable Development, SDGs, Poverty Eradication and Reducing Inequalities .......................450 5.5.2 Pathways for Adaptation, Mitigation and Sustainable Development ....................................467 5.1.2 Pathways to 1.5°C ......................................................450 5.5.3 Climate-Resilient Development Pathways ..................468 5.1.3 Types of evidence .......................................................451 Box 5.3: Republic of Vanuatu – National Planning for Development and Climate Resilience .............................471 5.2 Poverty, Equality and Equity Implications of a 1.5°C Warmer World ............................................451 Cross-Chapter Box 13: Cities and Urban Transformation ...472 5.2.1 Impacts and Risks of a 1.5°C Warmer World: Implications for Poverty and Livelihoods ....................452 5.6 Conditions for Achieving Sustainable Development, Eradicating Poverty 5.2.2 Avoided Impacts of 1.5°C Versus 2°C and Reducing Inequalities in Warming for Poverty and Inequality ...........................452 1.5°C Warmer Worlds ...................................................474 5.2.3 Risks from 1.5°C Versus 2°C Global Warming 5.6.1 Finance and Technology Aligned with Local Needs .....474 and the Sustainable Development Goals ....................453 5.6.2 Integration of Institutions...........................................474 Cross-Chapter Box 12: Residual Risks, Limits to Adaptation and Loss and Damage ........................454 5.6.3 Inclusive Processes .....................................................475 5.6.4 Attention to Issues of Power and Inequality ...............475 5.3 Climate Adaptation and Sustainable Development ..........................................456 5.6.5 Reconsidering Values..................................................475 5.3.1 Sustainable Development in Support of Climate Adaptation ................................................456 5.7 Synthesis and Research Gaps ...................................475 5.3.2 Synergies and Trade-Offs between Adaptation Options and Sustainable Development ......................457 Frequently Asked Questions 5.3.3 Adaptation Pathways towards a 1.5°C Warmer FAQ 5.1 What are the Connections between World and Implications for Inequalities ......................458 Sustainable Development and Limiting Box 5.1 : Ecosystem- and Community-Based Global Warming to 1.5°C above Practices in Drylands ...............................................................459 Pre-Industrial Levels? ..........................................477 FAQ 5.2 What are the Pathways to Achieving 5.4 Mitigation and Sustainable Development ............459 Poverty Reduction and Reducing Inequalities while Reaching a 1.5°C World? ..............................479 5.4.1 Synergies and Trade-Offs between Mitigation Options and Sustainable Development ......................459 References ...................................................................................510 5 Box 5.2: Challenges and Opportunities of 5 Low-Carbon Pathways in Gulf Cooperative Council Countries ....................................................................462 5.4.2 Sustainable Development Implications of 1.5°C and 2°C Mitigation Pathways .....................................463 446 Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 Executive Summary confidence). Many strategies for sustainable development enable transformational adaptation for a 1.5°C warmer world, provided attention is paid to reducing poverty in all its forms and to promoting This chapter takes sustainable development as the starting point equity and participation in decision-making (medium evidence, high and focus for analysis. It considers the broad and multifaceted agreement). As such, sustainable development has the potential bi-directional interplay between sustainable development, including to significantly reduce systemic vulnerability, enhance adaptive its focus on eradicating poverty and reducing inequality in their capacity, and promote livelihood security for poor and disadvantaged multidimensional aspects, and climate actions in a 1.5°C warmer world. populations (high confidence). {5.3.1} These fundamental connections are embedded in the Sustainable Development Goals (SDGs). The chapter also examines synergies Synergies between adaptation strategies and the SDGs are and trade-offs of adaptation and mitigation options with sustainable expected to hold true in a 1.5°C warmer world, across sectors development and the SDGs and offers insights into possible pathways, and contexts (medium evidence, medium agreement). Synergies especially climate-resilient development pathways towards a 1.5°C between adaptation and sustainable development are significant warmer world. for agriculture and health, advancing SDGs 1 (extreme poverty), 2 (hunger), 3 (healthy lives and well-being) and 6 (clean water) (robust Sustainable Development, Poverty and Inequality evidence, medium agreement). {5.3.2} Ecosystem- and community- in a 1.5°C Warmer World based adaptation, along with the incorporation of indigenous and local knowledge, advances synergies with SDGs 5 (gender equality), Limiting global warming to 1.5°C rather than 2°C above pre- 10 (reducing inequalities) and 16 (inclusive societies), as exemplified industrial levels would make it markedly easier to achieve many in drylands and the Arctic (high evidence, medium agreement). {5.3.2, aspects of sustainable development, with greater potential to Box 5.1, Cross-Chapter Box 10 in Chapter 4} eradicate poverty and reduce inequalities (medium evidence, high agreement). Impacts avoided with the lower temperature Adaptation strategies can result in trade-offs with and among limit could reduce the number of people exposed to climate risks and the SDGs (medium evidence, high agreement). Strategies that vulnerable to poverty by 62 to 457 million, and lessen the risks of advance one SDG may create negative consequences for other poor people to experience food and water insecurity, adverse health SDGs, for instance SDGs 3 (health) versus 7 (energy consumption) impacts, and economic losses, particularly in regions that already face and agricultural adaptation and SDG 2 (food security) versus SDGs 3 development challenges (medium evidence, medium agreement). (health), 5 (gender equality), 6 (clean water), 10 (reducing inequalities), {5.2.2, 5.2.3} Avoided impacts expected to occur between 1.5°C and 14 (life below water) and 15 (life on the land) (medium evidence, 2°C warming would also make it easier to achieve certain SDGs, such as medium agreement). {5.3.2} those that relate to poverty, hunger, health, water and sanitation, cities and ecosystems (SDGs 1, 2, 3, 6, 11, 14 and 15) (medium evidence, Pursuing place-specific adaptation pathways towards a 1.5°C high agreement). {5.2.3, Table 5.2 available at the end of the chapter} warmer world has the potential for significant positive outcomes for well-being in countries at all levels of development (medium Compared to current conditions, 1.5°C of global warming would evidence, high agreement). Positive outcomes emerge when nonetheless pose heightened risks to eradicating poverty, adaptation pathways (i) ensure a diversity of adaptation options based reducing inequalities and ensuring human and ecosystem well- on people’s values and the trade-offs they consider acceptable, (ii) being (medium evidence, high agreement). Warming of 1.5°C is maximize synergies with sustainable development through inclusive, not considered ‘safe’ for most nations, communities, ecosystems and participatory and deliberative processes, and (iii) facilitate equitable 5 sectors and poses significant risks to natural and human systems as transformation. Yet such pathways would be difficult to achieve 5 compared to the current warming of 1°C (high confidence). {Cross- without redistributive measures to overcome path dependencies, Chapter Box 12 in Chapter 5} The impacts of 1.5°C of warming would uneven power structures, and entrenched social inequalities (medium disproportionately affect disadvantaged and vulnerable populations evidence, high agreement). {5.3.3} through food insecurity, higher food prices, income losses, lost livelihood opportunities, adverse health impacts and population Mitigation and Sustainable Development displacements (medium evidence, high agreement). {5.2.1} Some of the worst impacts on sustainable development are expected to be The deployment of mitigation options consistent with 1.5°C felt among agricultural and coastal dependent livelihoods, indigenous pathways leads to multiple synergies across a range of people, children and the elderly, poor labourers, poor urban dwellers in sustainable development dimensions. At the same time, the African cities, and people and ecosystems in the Arctic and Small Island rapid pace and magnitude of change that would be required Developing States (SIDS) (medium evidence, high agreement). {5.2.1, to limit warming to 1.5°C, if not carefully managed, would lead Box 5.3, Chapter 3, Box 3.5, Cross-Chapter Box 9 in Chapter 4} to trade-offs with some sustainable development dimensions (high confidence). The number of synergies between mitigation Climate Adaptation and Sustainable Development response options and sustainable development exceeds the number of trade-offs in energy demand and supply sectors; agriculture, forestry Prioritization of sustainable development and meeting the and other land use (AFOLU); and for oceans (very high confidence). SDGs is consistent with efforts to adapt to climate change (high {Figure 5.2, Table 5.2 available at the end of the chapter} The 1.5°C 447 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities pathways indicate robust synergies, particularly for the SDGs 3 (health), evidence, high agreement). {5.4.1.2, Box 5.2} Targeted policies that 7 (energy), 12 (responsible consumption and production) and 14 promote diversification of the economy and the energy sector could (oceans) (very high confidence). {5.4.2, Figure 5.3} For SDGs 1 (poverty), ease this transition (medium evidence, high agreement). {5.4.1.2, 2 (hunger), 6 (water) and 7 (energy), there is a risk of trade-offs or Box 5.2} negative side effects from stringent mitigation actions compatible with 1.5°C of warming (medium evidence, high agreement). {5.4.2} Sustainable Development Pathways to 1.5°C Appropriately designed mitigation actions to reduce energy Sustainable development broadly supports and often enables demand can advance multiple SDGs simultaneously. Pathways the fundamental societal and systems transformations that compatible with 1.5°C that feature low energy demand show the would be required for limiting warming to 1.5°C above pre- most pronounced synergies and the lowest number of trade-offs industrial levels (high confidence). Simulated pathways that with respect to sustainable development and the SDGs (very high feature the most sustainable worlds (e.g., Shared Socio-Economic confidence). Accelerating energy efficiency in all sectors has synergies Pathways (SSP) 1) are associated with relatively lower mitigation and with SDGs 7 (energy), 9 (industry, innovation and infrastructure), adaptation challenges and limit warming to 1.5°C at comparatively 11 (sustainable cities and communities), 12 (responsible consumption lower mitigation costs. In contrast, development pathways with high and production), 16 (peace, justice and strong institutions), and fragmentation, inequality and poverty (e.g., SSP3) are associated with 17 (partnerships for the goals) (robust evidence, high agreement). comparatively higher mitigation and adaptation challenges. In such {5.4.1, Figure 5.2, Table 5.2} Low-demand pathways, which would pathways, it is not possible to limit warming to 1.5°C for the vast reduce or completely avoid the reliance on bioenergy with carbon majority of the integrated assessment models (medium evidence, capture and storage (BECCS) in 1.5°C pathways, would result in high agreement). {5.5.2} In all SSPs, mitigation costs substantially significantly reduced pressure on food security, lower food prices and increase in 1.5°C pathways compared to 2°C pathways. No pathway fewer people at risk of hunger (medium evidence, high agreement). in the literature integrates or achieves all 17 SDGs (high confidence). {5.4.2, Figure 5.3} {5.5.2} Real-world experiences at the project level show that the actual integration between adaptation, mitigation and sustainable The impacts of carbon dioxide removal options on SDGs depend development is challenging as it requires reconciling trade-offs across on the type of options and the scale of deployment (high sectors and spatial scales (very high confidence). {5.5.1} confidence). If poorly implemented, carbon dioxide removal (CDR) options such as bioenergy, BECCS and AFOLU would lead to trade- Without societal transformation and rapid implementation offs. Appropriate design and implementation requires considering of ambitious greenhouse gas reduction measures, pathways local people’s needs, biodiversity and other sustainable development to limiting warming to 1.5°C and achieving sustainable dimensions (very high confidence). {5.4.1.3, Cross-Chapter Box 7 in development will be exceedingly difficult, if not impossible, Chapter 3} to achieve (high confidence). The potential for pursuing such pathways differs between and within nations and regions, due to The design of the mitigation portfolios and policy instruments different development trajectories, opportunities and challenges (very to limit warming to 1.5°C will largely determine the overall high confidence). {5.5.3.2, Figure 5.1} Limiting warming to 1.5°C synergies and trade-offs between mitigation and sustainable would require all countries and non-state actors to strengthen their development (very high confidence). Redistributive policies contributions without delay. This could be achieved through sharing that shield the poor and vulnerable can resolve trade-offs for efforts based on bolder and more committed cooperation, with support a range of SDGs (medium evidence, high agreement). Individual for those with the least capacity to adapt, mitigate and transform 5 mitigation options are associated with both positive and negative (medium evidence, high agreement). {5.5.3.1, 5.5.3.2} Current 5 interactions with the SDGs (very high confidence). {5.4.1} However, efforts towards reconciling low-carbon trajectories and reducing appropriate choices across the mitigation portfolio can help to inequalities, including those that avoid difficult trade-offs associated maximize positive side effects while minimizing negative side effects with transformation, are partially successful yet demonstrate notable (high confidence). {5.4.2, 5.5.2} Investment needs for complementary obstacles (medium evidence, medium agreement). {5.5.3.3, Box 5.3, policies resolving trade-offs with a range of SDGs are only a small Cross-Chapter Box 13 in this chapter} fraction of the overall mitigation investments in 1.5°C pathways (medium evidence, high agreement). {5.4.2, Figure 5.4} Integration of Social justice and equity are core aspects of climate-resilient mitigation with adaptation and sustainable development compatible development pathways for transformational social change. with 1.5°C warming requires a systems perspective (high confidence). Addressing challenges and widening opportunities between {5.4.2, 5.5.2} and within countries and communities would be necessary to achieve sustainable development and limit warming to Mitigation consistent with 1.5°C of warming create high risks 1.5°C, without making the poor and disadvantaged worse off for sustainable development in countries with high dependency (high confidence). Identifying and navigating inclusive and socially on fossil fuels for revenue and employment generation (high acceptable pathways towards low-carbon, climate-resilient futures is a confidence). These risks are caused by the reduction of global demand challenging yet important endeavour, fraught with moral, practical and affecting mining activity and export revenues and challenges to rapidly political difficulties and inevitable trade-offs (very high confidence). decrease high carbon intensity of the domestic economy (robust {5.5.2, 5.5.3.3, Box 5.3} It entails deliberation and problem-solving 448 Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 processes to negotiate societal values, well-being, risks and resilience and to determine what is desirable and fair, and to whom (medium evidence, high agreement). Pathways that encompass joint, iterative planning and transformative visions, for instance in Pacific SIDS like Vanuatu and in urban contexts, show potential for liveable and sustainable futures (high confidence). {5.5.3.1, 5.5.3.3, Figure 5.5, Box 5.3, Cross-Chapter Box 13 in this chapter} The fundamental societal and systemic changes to achieve sustainable development, eradicate poverty and reduce inequalities while limiting warming to 1.5°C would require meeting a set of institutional, social, cultural, economic and technological conditions (high confidence). The coordination and monitoring of policy actions across sectors and spatial scales is essential to support sustainable development in 1.5°C warmer conditions (very high confidence). {5.6.2, Box 5.3} External funding and technology transfer better support these efforts when they consider recipients’ context-specific needs (medium evidence, high agreement). {5.6.1} Inclusive processes can facilitate transformations by ensuring participation, transparency, capacity building and iterative social learning (high confidence). {5.5.3.3, Cross-Chapter Box 13, 5.6.3} Attention to power asymmetries and unequal opportunities for development, among and within countries, is key to adopting 1.5°C-compatible development pathways that benefit all populations (high confidence). {5.5.3, 5.6.4, Box 5.3} Re-examining individual and collective values could help spur urgent, ambitious and cooperative change (medium evidence, high agreement). {5.5.3, 5.6.5} 5 5 449 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities 5.1 Scope and Delineations (Langford et al., 2013; Fukuda-Parr et al., 2014). While improvements in water security, slums and health may have reduced some aspects This chapter takes sustainable development as the starting point and of climate vulnerability, increases in incomes were linked to rising focus for analysis, considering the broader bi-directional interplay greenhouse gas (GHG) emissions and thus to a trade-off between and multifaceted interactions between development patterns and development and climate change (Janetos et al., 2012; UN, 2015a; climate actions in a 1.5°C warmer world and in the context of Hubacek et al., 2017). eradicating poverty and reducing inequality. It assesses the impacts of keeping temperatures at or below 1.5°C of global warming above While the SDGs capture many important aspects of sustainable pre-industrial levels on sustainable development and compares the development, including the explicit goals of poverty eradication impacts avoided at 1.5°C compared to 2°C (Section 5.2). It then and reducing inequality, there are direct connections from examines the interactions, synergies and trade-offs of adaptation climate to other measures of sustainable development including (Section 5.3) and mitigation (Section 5.4) measures with sustainable multidimensional poverty, equity, ethics, human security, well- development and the Sustainable Development Goals (SDGs). The being and climate-resilient development (Bebbington and chapter offers insights into possible pathways towards a 1.5°C Larrinaga, 2014; Robertson, 2014; Redclift and Springett, 2015; warmer world, especially through climate-resilient development Barrington-Leigh, 2016; Helliwell et al., 2018; Kirby and O’Mahony, pathways providing a comprehensive vision across different contexts 2018) (see Glossary). The UN proposes sustainable development (Section 5.5). The chapter also identifies the conditions that would be as ‘eradicating poverty in all its forms and dimensions, combating needed to simultaneously achieve sustainable development, poverty inequality within and among countries, preserving the planet, eradication, the reduction of inequalities, and the 1.5°C climate creating sustained, inclusive and sustainable economic growth and objective (Section 5.6). fostering social inclusion’ (UN, 2015b). There is robust evidence of the links between climate change and poverty (see Chapter 1, 5.1.1 Sustainable Development, SDGs, Poverty Cross-Chapter Box 4). The AR5 concluded with high confidence Eradication and Reducing Inequalities that disruptive levels of climate change would preclude reducing poverty (Denton et al., 2014; Fleurbaey et al., 2014). International Chapter 1 (see Cross-Chapter Box 4 in Chapter 1) defines sustainable organizations have since stated that climate changes ‘undermine development as ‘development that meets the needs of the present the ability of all countries to achieve sustainable development’ (UN, and future generations’ through balancing economic, social and 2015b) and can reverse or erase improvements in living conditions environmental considerations, and then introduces the United Nations and decades of development (Hallegatte et al., 2016). (UN) 2030 Agenda for Sustainable Development, which sets out 17 ambitious goals for sustainable development for all countries by Climate warming has unequal impacts on different people and places 2030. These SDGs are: no poverty (SDG 1), zero hunger (SDG 2), good as a result of differences in regional climate changes, vulnerabilities health and well-being (SDG 3), quality education (SDG 4), gender and impacts, and these differences then result in unequal impacts equality (SDG 5), clean water and sanitation (SDG 6), affordable and on sustainable development and poverty (Section 5.2). Responses to clean energy (SDG 7), decent work and economic growth (SDG 8), climate change also interact in complex ways with goals of poverty industry, innovation and infrastructure (SDG 9), reduced inequalities reduction. The benefits of adaptation and mitigation projects and (SDG 10), sustainable cities and communities (SDG 11), responsible funding may accrue to some and not others, responses may be costly consumption and production (SDG 12), climate action (SDG 13), life and unaffordable to some people and countries, and projects may below water (SDG 14), life on land (SDG 15), peace, justice and strong disadvantage some individuals, groups and development initiatives institutions (SDG 16) and partnerships for the goals (SDG 17). (Sections 5.3 and 5.4, Cross-Chapter Box 11 in Chapter 4). 5 5 The IPCC Fifth Assessment Report (AR5) included extensive discussion 5.1.2 Pathways to 1.5°C of links between climate and sustainable development, especially in Chapter 13 (Olsson et al., 2014) and Chapter 20 (Denton et al., 2014) Pathways to 1.5°C (see Chapter 1, Cross-Chapter Box 1 in Chapter 1, in Working Group II and Chapter 4 (Fleurbaey et al., 2014) in Working Glossary) include ambitious reductions in emissions and strategies for Group III. However, the AR5 preceded the 2015 adoption of the SDGs adaptation that are transformational, as well as complex interactions and the literature that argues for their fundamental links to climate with sustainable development, poverty eradication and reducing (Wright et al., 2015; Salleh, 2016; von Stechow et al., 2016; Hammill inequalities. The AR5 WGII introduced the concept of climate- and Price-Kelly, 2017; ICSU, 2017; Maupin, 2017; Gomez-Echeverri, resilient development pathways (CRDPs) (see Glossary) which 2018). combine adaptation and mitigation to reduce climate change and its impacts, and emphasize the importance of addressing structural The SDGs build on efforts under the UN Millennium Development Goals and intersecting inequalities, marginalization and multidimensional to reduce poverty, hunger, and other deprivations. According to the UN, poverty to ‘transform […] the development pathways themselves the Millennium Development Goals were successful in reducing poverty towards greater social and environmental sustainability, equity, and hunger and improving water security (UN, 2015a). However, critics resilience, and justice’ (Olsson et al., 2014). This chapter assesses argued that they failed to address within-country disparities, human literature on CRDPs relevant to 1.5°C global warming (Section 5.5.3), rights and key environmental concerns, focused only on developing to understand better the possible societal and systems transformations countries, and had numerous measurement and attribution problems (see Glossary) that reduce inequality and increase well-being 450 Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 (Figure 5.1). It also summarizes the knowledge on conditions to culture, values, financing and institutions that support low-carbon achieve such transformations, including changes in technologies, and resilient pathways and sustainable development (Section 5.6). Figure 5.1 | Climate-resilient development pathways (CRDPs) (green arrows) between a current world in which countries and communities exist at different levels of development (A) and future worlds that range from climate-resilient (bottom) to unsustainable (top) (D). CRDPs involve societal transformation rather than business-as-usual approaches, and all pathways involve adaptation and mitigation choices and trade-offs (B). Pathways that achieve the Sustainable Development Goals by 2030 and beyond, strive for net zero emissions around mid-21st century, and stay within the global 1.5°C warming target by the end of the 21st century, while ensuring equity and well-being for all, are best positioned to achieve climate-resilient futures (C). Overshooting on the path to 1.5°C will make achieving CRDPs and other sustainable trajectories more difficult; yet, the limited literature does not allow meaningful estimates. 5.1.3 Types of Evidence and enabling conditions (see Glossary) for integrating sustainable 5 development, poverty eradication and reducing inequalities in the 5 A variety of sources of evidence are used to assess the interactions context of 1.5°C. of sustainable development and the SDGs with the causes, impacts and responses to climate change of 1.5°C warming. This chapter builds 5.2 Poverty, Equality and Equity Implications on Chapter 3 to assess the sustainable development implications of of a 1.5°C Warmer World impacts at 1.5°C and 2°C, and on Chapter 4 to examine the implications of response measures. Scientific and grey literature, with a post- Climate change could lead to significant impacts on extreme poverty AR5 focus, and data that evaluate, measure and model sustainable by 2030 (Hallegatte et al., 2016; Hallegatte and Rozenberg, 2017). development–climate links from various perspectives, quantitatively The AR5 concluded, with very high confidence, that climate change and qualitatively, across scales, and through well-documented case and climate variability worsen existing poverty and exacerbate studies are assessed. inequalities, especially for those disadvantaged by gender, age, race, class, caste, indigeneity and (dis)ability (Olsson et al., 2014). New Literature that explicitly links 1.5°C global warming to sustainable literature on these links is substantial, showing that the poor will development across scales remains scarce; yet we find relevant insights continue to experience climate change severely, and climate change in many recent publications on climate and development that assess will exacerbate poverty (very high confidence) (Fankhauser and impacts across warming levels, the effects of adaptation and mitigation Stern, 2016; Hallegatte et al., 2016; O’Neill et al., 2017a; Winsemius response measures, and interactions with the SDGs. Relevant evidence et al., 2018). The understanding of regional impacts and risks of also stems from emerging literature on possible pathways, overshoot 1.5°C global warming and interactions with patterns of societal 451 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities vulnerability and poverty remains limited. Yet identifying and Africa (Winsemius et al., 2018). In urban Africa, a 1.5°C warming addressing poverty and inequality is at the core of staying within could expose many households to water poverty and increased a safe and just space for humanity (Raworth, 2017; Bathiany et al., flooding (Pelling et al., 2018). At 1.5ºC warming, fisheries-dependent 2018). Building on relevant findings from Chapter 3 (see Section 3.4), and coastal livelihoods, of often disadvantaged populations, would this section examines anticipated impacts and risks of 1.5°C and suffer from the loss of coral reefs (see Chapter 3, Box 3.4). higher warming on sustainable development, poverty, inequality and equity (see Glossary). Global heat stress is projected to increase in a 1.5°C warmer world, and by 2030, compared to 1961–1990, climate change could be 5.2.1 Impacts and Risks of a 1.5°C Warmer World: responsible for additional annual deaths of 38,000 people from heat Implications for Poverty and Livelihoods stress, particularly among the elderly, and 48,000 from diarrhoea, 60,000 from malaria, and 95,000 from childhood undernutrition (WHO, Global warming of 1.5°C will have consequences for sustainable 2014). Each 1°C increase could reduce work productivity by 1 to 3% development, poverty and inequalities. This includes residual risks, for people working outdoors or without air conditioning, typically the limits to adaptation, and losses and damages (Cross-Chapter Box 12 poorer segments of the workforce (Park et al., 2015). in this chapter; see Glossary). Some regions have already experienced a 1.5°C warming, with impacts on food and water security, health and The regional variation in the ‘warming experience at 1.5°C’ (see Chapter other components of sustainable development (medium evidence, 1, Section 1.3.1) is large (see Chapter 3, Section 3.3.2). Declines in crop medium agreement) (see Chapter 3, Section 3.4). Climate change is also yields are widely reported for Africa (60% of observations), with serious already affecting poorer subsistence communities through decreases consequences for subsistence and rain-fed agriculture and food security in crop production and quality, increases in crop pests and diseases, (Savo et al., 2016). In Bangladesh, by 2050, damages and losses are and disruption to culture (Savo et al., 2016). It disproportionally affects expected for poor households dependent on freshwater fish stocks due children and the elderly and can increase gender inequality (Kaijser to lack of mobility, limited access to land and strong reliance on local and Kronsell, 2014; Vinyeta et al., 2015; Carter et al., 2016; Hanna and ecosystems (Dasgupta et al., 2017). Small Island Developing States Oliva, 2016; Li et al., 2016). (SIDS) are expected to experience challenging conditions at 1.5°C warming due to increased risk of internal migration and displacement At 1.5°C warming, compared to current conditions, further negative and limits to adaptation (see Chapter 3, Box 3.5, Cross-Chapter Box consequences are expected for poor people, and inequality and 12 in this chapter). An anticipated decline of marine fisheries of vulnerability (medium evidence, high agreement). Hallegatte and 3 million metric tonnes per degree warming would have serious Rozenberg (2017) report that by 2030 (roughly approximating a 1.5°C regional impacts for the Indo-Pacific region and the Arctic (Cheung et warming), 122 million additional people could experience extreme al., 2016). poverty, based on a ‘poverty scenario’ of limited socio-economic progress, comparable to the Shared Socio-Economic Pathway (SSP) 5.2.2 Avoided Impacts of 1.5°C versus 2°C 4 (inequality), mainly due to higher food prices and declining health, Warming for Poverty and Inequality with substantial income losses for the poorest 20% across 92 countries. Pretis et al. (2018) estimate negative impacts on economic growth Avoided impacts between 1.5°C and 2°C warming are expected to in lower-income countries at 1.5°C warming, despite uncertainties. have significant positive implications for sustainable development, Impacts are likely to occur simultaneously across livelihood, food, and reducing poverty and inequality. Using the SSPs (see Chapter 1, human, water and ecosystem security (limited evidence, high Cross-Chapter Box 1 in Chapter 1, Section 5.5.2), Byers et al. (2018) agreement) (Byers et al., 2018), but the literature on interacting and model the number of people exposed to multi-sector climate risks 5 cascading effects remains scarce (Hallegatte et al., 2014; O’Neill et and vulnerable to poverty (income < $10/day), comparing 2°C and 5 al., 2017b; Reyer et al., 2017a, b). 1.5°C; the respective declines are from 86 million to 24 million for SSP1 (sustainability), from 498 million to 286 million for SSP2 (middle Chapter 3 outlines future impacts and risks for ecosystems and of the road), and from 1220 million to 763 million for SSP3 (regional human systems, many of which could also undermine sustainable rivalry), which suggests overall 62–457 million fewer people exposed development and efforts to eradicate poverty and hunger, and and vulnerable at 1.5°C warming. Across the SSPs, the largest to protect health and ecosystems. Chapter 3 findings (see Section populations exposed and vulnerable are in South Asia (Byers et 3.5.2.1) suggest increasing Reasons for Concern from moderate to al., 2018). The avoided impacts on poverty at 1.5°C relative to 2°C high at a warming of 1.1° to 1.6°C, including for indigenous people are projected to depend at least as much or more on development and their livelihoods, and ecosystems in the Arctic (O’Neill et al., scenarios than on warming (Wiebe et al., 2015; Hallegatte and 2017b). In 2050, based on the Hadley Centre Climate Prediction Rozenberg, 2017). Model 3 (HadCM3) and the Special Report on Emission Scenarios A1b scenario (roughly comparable to 1.5°C warming), 450 million more Limiting warming to 1.5°C is expected to reduce the number of people flood-prone people would be exposed to doubling in flood frequency, exposed to hunger, water stress and disease in Africa (Clements, and global flood risk would increase substantially (Arnell and 2009). It is also expected to limit the number of poor people exposed Gosling, 2016). For droughts, poor people are expected to be more to floods and droughts at higher degrees of warming, especially in exposed (85% in population terms) in a warming scenario greater African and Asian countries (Winsemius et al., 2018). Challenges for than 1.5°C for several countries in Asia and southern and western poor populations – relating to food and water security, clean energy 452 Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 access and environmental well-being – are projected to be less at heat waves and the associated health impacts in countries such as 1.5°C, particularly for vulnerable people in Africa and Asia (Byers et Australia and India (King et al., 2017; Mishra et al., 2017). al., 2018). The overall projected socio-economic losses compared to the present day are less at 1.5°C (8% loss of gross domestic product per Limiting warming to 1.5°C would make it markedly easier to achieve capita) compared to 2°C (13%), with lower-income countries projected the SDGs for poverty eradication, water access, safe cities, food to experience greater losses, which may increase economic inequality security, healthy lives and inclusive economic growth, and would help between countries (Pretis et al., 2018). to protect terrestrial ecosystems and biodiversity (medium evidence, high agreement) (Table 5.2 available at the end of the chapter). For 5.2.3 Risks from 1.5°C versus 2°C Global Warming example, limiting species loss and expanding climate refugia will and the Sustainable Development Goals make it easier to achieve SDG 15 (see Chapter 3, Section 3.4.3). One indication of how lower temperatures benefit the SDGs is to compare The risks that can be avoided by limiting global warming to 1.5ºC rather the impacts of Representative Concentration Pathway (RCP) 4.5 (lower than 2°C have many complex implications for sustainable development emissions) and RCP8.5 (higher emissions) on the SDGs (Ansuategi (ICSU, 2017; Gomez-Echeverri, 2018). There is high confidence that et al., 2015). A low emissions pathway allows for greater success in constraining warming to 1.5°C rather than 2°C would reduce risks achieving SDGs for reducing poverty and hunger, providing access for unique and threatened ecosystems, safeguarding the services they to clean energy, reducing inequality, ensuring education for all and provide for livelihoods and sustainable development and making making cities more sustainable. Even at lower emissions, a medium adaptation much easier (O’Neill et al., 2017b), particularly in Central risk of failure exists to meet goals for water and sanitation, and marine America, the Amazon, South Africa and Australia (Schleussner et al., and terrestrial ecosystems. 2016; O’Neill et al., 2017b; Reyer et al., 2017b; Bathiany et al., 2018). Action on climate change (SDG 13), including slowing the rate of In places that already bear disproportionate economic and social warming, would help reach the goals for water, energy, food and challenges to their sustainable development, people will face lower land (SDGs 6, 7, 2 and 15) (Obersteiner et al., 2016; ICSU, 2017) risks at 1.5°C compared to 2°C. These include North Africa and and contribute to poverty eradication (SDG 1) (Byers et al., 2018). the Levant (less water scarcity), West Africa (less crop loss), South Although the literature that connects 1.5°C to the SDGs is limited, a America and Southeast Asia (less intense heat), and many other pathway that stabilizes warming at 1.5°C by the end of the century is coastal nations and island states (lower sea level rise, less coral reef expected to increase the chances of achieving the SDGs by 2030, with loss) (Schleussner et al., 2016; Betts et al., 2018). The risks for food, greater potential to eradicate poverty, reduce inequality and foster water and ecosystems, particularly in subtropical regions such as equity (limited evidence, medium agreement). There are no studies Central America and countries such as South Africa and Australia, on overshoot and dimensions of sustainable development, although are expected to be lower at 1.5°C than at 2°C warming (Schleussner literature on 4°C of warming suggests the impacts would be severe et al., 2016). Fewer people would be exposed to droughts and (Reyer et al., 2017b). Table 5.1 | Sustainable development implications of avoided impacts between 1.5°C and 2°C global warming. Sustainable Development Goals Chapter 3 Impacts 1.5°C 2°C (SDGs) More Easily Achieved Section when Limiting Warming to 1.5°C 8% more people exposed to water stress, 3.4.2.1 4% more people exposed to water stress 5 with 184–270 million people more exposedWater scarcity SDG 6 water availability for all 5 496 (range 103–1159) million people exposed 586 (range 115–1347) million people exposed Table 3.4 and vulnerable to water stress and vulnerable to water stress 3.4.3, Around 7% of land area experiences biome Around 13% (range 8–20%) of land area Table 3.4 shifts experiences biome shifts SDG 15 to protect terrestrial ecosystems Ecosystems and halt biodiversity loss Box 3.5 70–90% of coral reefs at risk from bleaching 99% of coral reefs at risk from bleaching 31–69 million people exposed to coastal 3.4.5.1 32–79 million exposed to coastal flooding flooding SDG 11 to make cities and human Coastal cities Fewer cities and coasts exposed to sea level rise settlements safe and resilient 3.4.5.2 More people and cities exposed to flooding and extreme events 3.4.6, Significant declines in crop yields avoided, Average crop yields decline Box 3.1 some yields may increase SDG 2 to end hunger and Food systems achieve food security Table 3.4 32–36 million people exposed to lower yields 330–396 million people exposed to lower yields Higher risks of temperature-related morbidity Lower risk of temperature-related morbidity 3.4.5.1 and mortality and larger geographic range Health and smaller mosquito range of mosquitoes SDG 3 to ensure healthy lives for all 3.4.5.2 3546–4508 million people exposed to heat waves 5417–6710 million people exposed to heat waves 453 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities Cross-Chapter Box 12 | Residual Risks, Limits to Adaptation and Loss and Damage Lead Authors: Riyanti Djalante (Japan/Indonesia), Kristie L. Ebi (USA), Debora Ley (Guatemala/Mexico), Reinhard Mechler (Germany), Patricia Fernanda Pinho (Brazil), Aromar Revi (India), Petra Tschakert (Australia/Austria) Contributing Authors: Karen Paiva Henrique (Brazil), Saleemul Huq (Bangladesh/UK), Rachel James (UK), Adelle Thomas (Bahamas), Margaretha Wewerinke-Singh (Netherlands) Introduction Residual climate-related risks, limits to adaptation, and loss and damage (see Glossary) are increasingly assessed in the scientific literature (van der Geest and Warner, 2015; Boyd et al., 2017; Mechler et al., 2019). The AR5 (IPCC, 2013; Oppenheimer et al., 2014) documented impacts that have been detected and attributed to climate change, projected increasing climate-related risks with con- tinued global warming, and recognized barriers and limits to adaptation. It recognized that adaptation is constrained by biophysi- cal, institutional, financial, social and cultural factors, and that the interaction of these factors with climate change can lead to soft adaptation limits (adaptive actions currently not available) and hard adaptation limits (adaptive actions appear infeasible leading to unavoidable impacts) (Klein et al., 2014). Loss and damage: concepts and perspectives ‘Loss and Damage’ (L&D) has been discussed in international climate negotiations for three decades (INC, 1991; Calliari, 2016; Vanhala and Hestbaek, 2016). A work programme on L&D was established as part of the Cancun Adaptation Framework in 2010 supporting developing countries particularly vulnerable to climate change impacts (UNFCCC, 2011a). In 2013, the Conference of the Parties (COP) 19 established the Warsaw International Mechanism for Loss and Damage (WIM) as a formal part of the United Nations Framework Convention on Climate Change (UNFCCC) architecture (UNFCCC, 2014). It acknowledges that L&D ‘includes, and in some cases involves more than, that which can be reduced by adaptation’ (UNFCCC, 2014). The Paris Agreement recognized ‘the importance of averting, minimizing and addressing loss and damage associated with the adverse effects of climate change’ through Article 8 (UNFCCC, 2015). There is no one definition of L&D in climate policy, and analysis of policy documents and stakeholder views has demonstrated ambi- guity (Vanhala and Hestbaek, 2016; Boyd et al., 2017). UNFCCC documents suggest that L&D is associated with adverse impacts of climate change on human and natural systems, including impacts from extreme events and slow-onset processes (UNFCCC, 2011b, 2014, 2015). Some documents focus on impacts in developing or particularly vulnerable countries (UNFCCC, 2011b, 2014). They refer to economic (loss of assets and crops) and non-economic (biodiversity, culture, health) impacts, the latter also being an action area under the WIM workplan, and irreversible and permanent loss and damage. Lack of clarity of what the term addresses (avoidance through adaptation and mitigation, unavoidable losses, climate risk management, existential risk) was expressed among stakeholders, with further disagreement ensuing about what constitutes anthropogenic climate change versus natural climate vari- ability (Boyd et al., 2017). 5 5 Limits to adaptation and residual risks The AR5 described adaptation limits as points beyond which actors’ objectives are compromised by intolerable risks threatening key objectives such as good health or broad levels of well-being, thus requiring transformative adaptation for overcoming soft limits (see Chapter 4, Sections 4.2.2.3, 4.5.3 and Cross-Chapter Box 9, Section 5.3.1) (Dow et al., 2013; Klein et al., 2014). The AR5 WGII risk tables, based on expert judgment, depicted the potential for, and the limits of, additional adaptation to reduce risk. Near-term (2030–2040) risks can be used as a proxy for 1.5°C warming by the end of the century and compared to longer-term (2080–2100) risks associated with an approximate 2°C warming. Building on the AR5 risk approach, Cross-Chapter Box 12, Figure 1 provides a stylised application example to poverty and inequality. 454 Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 Cross-Chapter Box 12 (continued) Cross-Chapter Box 12, Figure 1 | Stylized reduced risk levels due to avoided impacts between 2°C and 1.5°C warming (in solid red-orange), additional avoided impacts with adaptation under 2°C (striped orange) and under 1.5°C (striped yellow), and unavoidable impacts (losses) with no or very limited potential for adaptation (grey), extracted from the AR5 WGII risk tables (Field et al., 2014), and underlying chapters by Adger et al. (2014) and Olsson et al. (2014). For some systems and sectors (A), achieving 1.5°C could reduce risks to low (with adaptation) from very high (without adaptation) and high (with adaptation) under 2°C. For other areas (C), no or very limited adaptation potential is anticipated, suggesting limits, with the same risks for 1.5°C and 2°C. Other risks are projected to be medium under 2°C with further potential for reduction, especially with adaptation, to very low levels (B). Limits to adaptation, residual risks, and losses in a 1.5°C warmer world The literature on risks at 1.5°C (versus 2°C and more) and potentials for adaptation remains limited, particularly for specific regions, sectors, and vulnerable and disadvantaged populations. Adaptation potential at 1.5°C and 2°C is rarely assessed explicitly, making an assessment of residual risk challenging. Substantial progress has been made since the AR5 to assess which climate change impacts on natural and human systems can be attributed to anthropogenic emissions (Hansen and Stone, 2016) and to examine the influence of anthropogenic emissions on extreme weather events (NASEM, 2016), and on consequent impacts on human life (Mitchell et al., 2016), but less so on monetary losses and risks (Schaller et al., 2016). There has also been some limited research to examine local-level limits to adaptation (Warner and Geest, 2013; Filho and Nalau, 2018). What constitutes losses and damages is context-dependent and often requires place-based research into what people value and consider worth protecting (Barnett et al., 2016; Tschakert et al., 2017). Yet assessments of non-material and intangible losses are particularly challenging, such as loss of sense of place, belonging, identity, and damage to emotional and mental well-being (Serdeczny et al., 2017; Wewerinke-Singh, 2018a). Warming of 1.5°C is not considered ‘safe’ for most nations, communities, ecosystems and sectors, and poses significant risks to natural and human systems as compared to the current warming of 1°C (high confidence) (see Chapter 3, Section 3.4, Box 3.4, Box 3.5, Table 3.5, Cross-Chapter Box 6 in Chapter 3). Table 5.2, drawing on findings from Chapters 3, 4 and 5, presents examples of soft and hard limits in natural and human systems in the context of 1.5°C and 2°C of warming. 5 Cross-Chapter Box 12, Table 1 | Soft and hard adaptation limits in the context of 1.5°C and 2°C of global warming. 5 System/Region Example Soft Limit Hard Limit Loss of 70–90% of tropical coral reefs by mid-century under 1.5°C scenario (total loss under 2°C ✓ Coral reefs scenario) (see Chapter 3, Sections 3.4.4 and 3.5.2.1, Box 3.4) 6% of insects, 8% of plants and 4% of vertebrates lose over 50% of the climatically determined ✓ Biodiversity geographic range at 1.5°C (18% of insects, 16% of plants and 8% of vertebrates at 2°C) (see Chapter 3, Section 3.4.3.3) 24–357 million people exposed to multi-sector climate risks and vulnerable to poverty at 1.5°C Poverty (86–1220 million at 2°C) (see Section 5.2.2) ✓ Twice as many megacities exposed to heat stress at 1.5°C compared to present, potentially exposing Human health 350 million additional people to deadly heat wave conditions by 2050 (see Chapter 3, Section 3.4.8) ✓ ✓ Large-scale changes in oceanic systems (temperature and acidification) inflict damage and losses to livelihoods, income, cultural identity and health for coastal-dependent communities at 1.5°C (potential ✓ ✓ Coastal livelihoods higher losses at 2°C) (see Chapter 3, Sections 3.4.4, 3.4.5, 3.4.6.3, Box 3.4, Box 3.5, Cross-Chapter Box 6, Chapter 4, Section 4.3.5; Section 5.2.3) Sea level rise and increased wave run up combined with increased aridity and decreased ✓ Small Island Developing States freshwater availability at 1.5°C warming potentially leaving several atoll islands uninhabitable (see Chapter 3, Sections 3.4.3, 3.4.5, Box 3.5, Chapter 4, Cross-Chapter Box 9) 455 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities Cross-Chapter Box 12 (continued) Approaches and policy options to address residual risk and loss and damage Conceptual and applied work since the AR5 has highlighted the synergies and differences with adaptation and disaster risk reduction policies (van der Geest and Warner, 2015; Thomas and Benjamin, 2017), suggesting more integration of existing mechanisms, yet careful consideration is advised for slow-onset and potentially irreversible impacts and risk (Mechler and Schinko, 2016). Scholarship on justice and equity has provided insight on compensatory, distributive and procedural equity considerations for policy and practice to address loss and damage (Roser et al., 2015; Wallimann-Helmer, 2015; Huggel et al., 2016). A growing body of legal literature considers the role of litigation in preventing and addressing loss and damage and finds that litigation risks for governments and business are bound to increase with improved understanding of impacts and risks as climate science evolves (high confidence) (Mayer, 2016; Banda and Fulton, 2017; Marjanac and Patton, 2018; Wewerinke-Singh, 2018b). Policy proposals include international support for experienced losses and damages (Crosland et al., 2016; Page and Heyward, 2017), addressing climate displacement, donor-supported implementation of regional public insurance systems (Surminski et al., 2016) and new global governance systems under the UNFCCC (Biermann and Boas, 2017). 5.3 Climate Adaptation and adopted, with inclusive, transparent decision-making, rather than Sustainable Development addressing current vulnerabilities as stand-alone climate problems (Mathur et al., 2014; Arthurson and Baum, 2015; Shackleton et al., Adaptation will be extremely important in a 1.5°C warmer world 2015; Lemos et al., 2016; Antwi-Agyei et al., 2017b). Ending poverty since substantial impacts will be felt in every region (high confidence) in its multiple dimensions (SDG 1) is often a highly effective form of (Chapter 3, Section 3.3), even if adaptation needs will be lower than climate adaptation (Fankhauser and McDermott, 2014; Leichenko in a 2°C warmer world (see Chapter 4, Sections 4.3.1 to 4.3.5, 4.5.3, and Silva, 2014; Hallegatte and Rozenberg, 2017). However, ending Cross-Chapter Box 10 in Chapter 4). Climate adaptation options poverty is not sufficient, and the positive outcome as an adaptation comprise structural, physical, institutional and social responses, with strategy depends on whether increased household wealth is actually their effectiveness depending largely on governance (see Glossary), directed towards risk reduction and management strategies (Nelson political will, adaptive capacities and availability of finance (see et al., 2016), as shown in urban municipalities (Colenbrander et al., Chapter 4, Sections 4.4.1 to 4.4.5) (Betzold and Weiler, 2017; Sonwa 2017; Rasch, 2017) and agrarian communities (Hashemi et al., 2017), et al., 2017; Sovacool et al., 2017). Even though the literature is scarce and whether finance for adaptation is made available (Section 5.6.1). on the expected impacts of future adaptation measures on sustainable development specific to warming experiences of 1.5°C, this section Second, local participation is effective when wider socio-economic assesses available literature on how (i) prioritising sustainable barriers are addressed via multiscale planning (McCubbin et al., development enhances or impedes climate adaptation efforts 2015; Nyantakyi-Frimpong and Bezner-Kerr, 2015; Toole et al., 2016). (Section 5.3.1); (ii) climate adaptation measures impact sustainable This is the case, for instance, when national education efforts (SDG 4) development and the SDGs in positive (synergies) or negative (trade- (Muttarak and Lutz, 2014; Striessnig and Loichinger, 2015) and offs) ways (Section 5.3.2); and (iii) adaptation pathways towards a 1.5°C indigenous knowledge (Nkomwa et al., 2014; Pandey and Kumar, 2018) warmer world affect sustainable development, poverty and inequalities enhance information sharing, which also builds resilience (Santos et al., 5 (Section 5.3.3). The section builds on Chapter 4 (see Section 4.3.5) 2016; Martinez-Baron et al., 2018) and reduces risks for maladaptation 5 regarding available adaptation options to reduce climate vulnerability (Antwi-Agyei et al., 2018; Gajjar et al., 2018). and build resilience (see Glossary) in the context of 1.5°C-compatible trajectories, with emphasis on sustainable development implications. Third, development promotes transformational adaptation when addressing social inequalities (Section 5.5.3, 5.6.4), as in SDGs 5.3.1 Sustainable Development in Support 4, 5, 16 and 17 (O’Brien, 2016; O’Brien, 2017). For example, SDG 5 of Climate Adaptation supports measures that reduce women’s vulnerabilities and allow women to benefit from adaptation (Antwi-Agyei et al., 2015; Van Aelst Making sustainable development a priority, and meeting the SDGs, and Holvoet, 2016; Cohen, 2017). Mobilization of climate finance, is consistent with efforts to adapt to climate change (very high carbon taxation and environmentally motivated subsidies can reduce confidence). Sustainable development is effective in building adaptive inequalities (SDG 10), advance climate mitigation and adaptation capacity if it addresses poverty and inequalities, social and economic (Chancel and Picketty, 2015), and be conducive to strengthening and exclusion, and inadequate institutional capacities (Noble et al., 2014; enabling environments for resilience building (Nhamo, 2016; Halonen Abel et al., 2016; Colloff et al., 2017). Four ways in which sustainable et al., 2017). development leads to effective adaptation are described below. Fourth, when sustainable development promotes livelihood security, First, sustainable development enables transformational adaptation it enhances the adaptive capacities of vulnerable communities and (see Chapter 4, Section 4.2.2.2) when an integrated approach is households. Examples include SDG 11 supporting adaptation in cities 456 Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 to reduce harm from disasters (Kelman, 2017; Parnell, 2017); access to et al., 2017a; Carr and Onzere, 2018). Agricultural adaptation measures water and sanitation (SDG 6) with strong institutions (SDG 16) (Rasul may increase workloads, especially for women, while changes in crop and Sharma, 2016); SDG 2 and its targets that promote adaptation mix can result in loss of income or culturally inappropriate food (Carr in agricultural and food systems (Lipper et al., 2014); and targets for and Thompson, 2014; Thompson-Hall et al., 2016; Bryan et al., 2017), SDG 3 such as reducing infectious diseases and providing health cover and they may benefit farmers with more land to the detriment of land- are consistent with health-related adaptation (ICSU, 2017; Gomez- poor farmers, as seen in the Mekong River Basin (see Chapter 3, Cross- Echeverri, 2018). Chapter Box 6 in Chapter 3). Sustainable development has the potential to significantly reduce Adaptation to protect human health: Adaptation options in the health systemic vulnerability, enhance adaptive capacity and promote sector are expected to reduce morbidity and mortality (Arbuthnott livelihood security for poor and disadvantaged populations (high et al., 2016; Ebi and Otmani del Barrio, 2017). Heat-early-warning confidence). Transformational adaptation (see Chapter 4, Sections systems help lower injuries, illnesses and deaths (Hess and Ebi, 2016), 4.2.2.2 and 4.5.3) would require development that takes into with positive impacts for SDG 3. Institutions better equipped to consideration multidimensional poverty and entrenched inequalities, share information, indicators for detecting climate-sensitive diseases, local cultural specificities and local knowledge in decision-making, improved provision of basic health care services and coordination thereby making it easier to achieve the SDGs in a 1.5°C warmer world with other sectors also improve risk management, thus reducing (medium evidence, high agreement). adverse health outcomes (Dasgupta et al., 2016; Dovie et al., 2017). Effective adaptation creates synergies via basic public health measures 5.3.2 Synergies and Trade-Offs between Adaptation (K.R. Smith et al., 2014; Dasgupta, 2016) and health infrastructure Options and Sustainable Development protected from extreme weather events (Watts et al., 2015). Yet trade- offs can occur when adaptation in one sector leads to negative impacts There are short-, medium-, and long-term positive impacts (synergies) in another sector. Examples include the creation of urban wetlands and negative impacts (trade-offs) between the dual goals of keeping through flood control measures which can breed mosquitoes, and temperatures below 1.5°C global warming and achieving sustainable migration eroding physical and mental well-being, hence adversely development. The extent of synergies between development and affecting SDG 3 (K.R. Smith et al., 2014; Watts et al., 2015). Similarly, adaptation goals will vary by the development process adopted for a increased use of air conditioning enhances resilience to heat stress particular SDG and underlying vulnerability contexts (medium evidence, (Petkova et al., 2017), yet it can result in higher energy consumption, high agreement). Overall, the impacts of adaptation on sustainable undermining SDG 13. development, poverty eradication and reducing inequalities in general, and the SDGs specifically, are expected to be largely positive, given Coastal adaptation: Adaptation to sea level rise remains essential that the inherent purpose of adaptation is to lower risks. Building on in coastal areas even under a climate stabilization scenario of 1.5°C Chapter 4 (see Section 4.3.5), this section examines synergies and (Nicholls et al., 2018). Coastal adaptation to restore ecosystems (for trade-offs between adaptation and sustainable development for some instance by planting mangrove forests) supports SDGs for enhancing key sectors and approaches. life and livelihoods on land and oceans (see Chapter 4, Sections 4.3.2.3). Synergistic outcomes between development and relocation Agricultural adaptation: The most direct synergy is between SDG 2 of coastal communities are enhanced by participatory decision-making (zero hunger) and adaptation in cropping, livestock and food systems, and settlement designs that promote equity and sustainability (van der designed to maintain or increase production (Lipper et al., 2014; Voorn et al., 2017). Limits to coastal adaptation may rise, for instance Rockström et al., 2017). Farmers with effective adaptation strategies in low-lying islands in the Pacific, Caribbean and Indian Ocean, with 5 tend to enjoy higher food security and experience lower levels of attendant implications for loss and damage (see Chapter 3 Box 3.5, 5 poverty (FAO, 2015; Douxchamps et al., 2016; Ali and Erenstein, 2017). Chapter 4, Cross-Chapter Box 9 in Chapter 4, Cross-Chapter Box 12 in Vermeulen et al. (2016) report strong positive returns on investment Chapter 5, Box 5.3). across the world from agricultural adaptation with side benefits for environment and economic well-being. Well-adapted agricultural Migration as adaptation: Migration has been used in various contexts systems contribute to safe drinking water, health, biodiversity and to protect livelihoods from challenges related to climate change equity goals (DeClerck et al., 2016; Myers et al., 2017). Climate-smart (Marsh, 2015; Jha et al., 2017), including through remittances (Betzold agriculture has synergies with food security, though it can be biased and Weiler, 2017). Synergies between migration and the achievement towards technological solutions, may not be gender sensitive, and can of sustainable development depend on adaptive measures and create specific challenges for institutional and distributional aspects conditions in both sending and receiving regions (Fatima et al., 2014; (Lipper et al., 2014; Arakelyan et al., 2017; Taylor, 2017). McNamara, 2015; Entzinger and Scholten, 2016; Ober and Sakdapolrak, 2017; Schwan and Yu, 2017). Adverse developmental impacts arise At the same time, adaptation options increase risks for human when vulnerable women or the elderly are left behind or if migration health, oceans and access to water if fertiliser and pesticides are used is culturally disruptive (Wilkinson et al., 2016; Albert et al., 2017; Islam without regulation or when irrigation reduces water availability for and Shamsuddoha, 2017). other purposes (Shackleton et al., 2015; Campbell et al., 2016). When agricultural insurance and climate services overlook the poor, inequality Ecosystem-based adaptation: Ecosystem-based adaptation (EBA) can may rise (Dinku et al., 2014; Carr and Owusu-Daaku, 2015; Georgeson offer synergies with sustainable development (Morita and Matsumoto, 457 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities 2015; Ojea, 2015; Szabo et al., 2015; Brink et al., 2016; Butt et al., 5.3.3 Adaptation Pathways towards a 1.5°C Warmer 2016; Conservation International, 2016; Huq et al., 2017), although World and Implications for Inequalities assessments remain difficult (see Chapter 4, Section 4.3.2.2) (Doswald et al., 2014). Examples include mangrove restoration reducing In a 1.5°C warmer world, adaptation measures and options would coastal vulnerability, protecting marine and terrestrial ecosystems, need to be intensified, accelerated and scaled up. This entails not only and increasing local food security, as well as watershed management the right ‘mix’ of options (asking ‘right for whom and for what?’) but reducing flood risks and improving water quality (Chong, 2014). also a forward-looking understanding of dynamic trajectories, that is In drylands, EBA practices, combined with community-based adaptation pathways (see Chapter 1, Cross-Chapter Box 1 in Chapter adaptation, have shown how to link adaptation with mitigation to 1), best understood as decision-making processes over sets of potential improve livelihood conditions of poor farmers (Box 5.1). Synergistic action sequenced over time (Câmpeanu and Fazey, 2014; Wise et al., developmental outcomes arise where EBA is cost effective, inclusive 2014). Given the scarcity of literature on adaptation pathways that of indigenous and local knowledge and easily accessible by the poor navigate place-specific warming experiences at 1.5°C, this section (Ojea, 2015; Daigneault et al., 2016; Estrella et al., 2016). Payment for presents insights into current local decision-making for adaptation ecosystem services can provide incentives to land owners and natural futures. This grounded evidence shows that choices between possible resource managers to preserve environmental services with synergies pathways, at different scales and for different groups of people, are with SDGs 1 and 13 (Arriagada et al., 2015), when implementation shaped by uneven power structures and historical legacies that create challenges are overcome (Calvet-Mir et al., 2015; Wegner, 2016; Chan their own, often unforeseen change (Fazey et al., 2016; Bosomworth et al., 2017). Trade-offs include loss of other economic land use types, et al., 2017; Lin et al., 2017; Murphy et al., 2017; Pelling et al., 2018). tension between biodiversity and adaptation priorities, and conflicts over governance (Wamsler et al., 2014; Ojea, 2015). Pursuing a place-specific adaptation pathway approach towards a 1.5°C warmer world harbours the potential for significant positive Community-based adaptation: Community-based adaptation (CBA) outcomes, with synergies for well-being possibilities to ‘leap-frog the (see Chapter 4, Sections 4.3.3.2) enhances resilience and sustainability SDGs’ (J.R.A. Butler et al., 2016), in countries at all levels of development of adaptation plans (Ford et al., 2016; Fernandes-Jesus et al., 2017; (medium evidence, high agreement). It allows for identifying local, Grantham and Rudd, 2017; Gustafson et al., 2017). Yet negative socially salient tipping points before they are crossed, based on what impacts occur if it fails to fairly represent vulnerable populations people value and trade-offs that are acceptable to them (Barnett et al., and to foster long-term social resilience (Ensor, 2016; Taylor Aiken 2014, 2016; Gorddard et al., 2016; Tschakert et al., 2017). Yet evidence et al., 2017). Mainstreaming CBA into planning and decision-making also reveals adverse impacts that reinforce rather than reduce existing enables the attainment of SDGs 5, 10 and 16 (Archer et al., 2014; social inequalities and hence may lead to poverty traps (medium Reid and Huq, 2014; Vardakoulias and Nicholles, 2014; Cutter, 2016; evidence, high agreement) (Nagoda, 2015; Warner et al., 2015; Barnett Kim et al., 2017). Incorporating multiple forms of indigenous and et al., 2016; J.R.A. Butler et al., 2016; Godfrey-Wood and Naess, 2016; local knowledge is an important element of CBA, as shown for Pelling et al., 2016; Albert et al., 2017; Murphy et al., 2017). instance in the Arctic region (see Chapter 4, Section 4.3.5.5, Box 4.3, Cross-Chapter Box 9) (Apgar et al., 2015; Armitage, 2015; Pearce Past development trajectories as well as transformational adaptation et al., 2015; Chief et al., 2016; Cobbinah and Anane, 2016; Ford et plans can constrain adaptation futures by reinforcing dominant al., 2016). Indigenous and local knowledge can be synergistic with political-economic structures and processes, and narrowing option achieving SDGs 2, 6 and 10 (Ayers et al., 2014; Lasage et al., 2015; spaces; this leads to maladaptive pathways that preclude alternative, Regmi and Star, 2015; Berner et al., 2016; Chief et al., 2016; Murtinho, locally relevant and sustainable development initiatives and increase 2016; Reid, 2016). vulnerabilities (Warner and Kuzdas, 2017; Gajjar et al., 2018). Such 5 dominant pathways tend to validate the practices, visions and 5 There are clear synergies between adaptation options and several values of existing governance regimes and powerful members of a SDGs, such as poverty eradication, elimination of hunger, clean water community while devaluing those of less privileged stakeholders. and health (robust evidence, high agreement), as well-integrated Examples from Romania, the Solomon Islands and Australia illustrate adaptation supports sustainable development (Eakin et al., 2014; such pathway dynamics in which individual economic gains and Weisser et al., 2014; Adam, 2015; Smucker et al., 2015). Substantial prosperity matter more than community cohesion and solidarity; this synergies are observed in the agricultural and health sectors, and discourages innovation, exacerbates inequalities and further erodes in ecosystem-based adaptations. However, particular adaptation adaptive capacities of the most vulnerable (Davies et al., 2014; Fazey strategies can lead to adverse consequences for developmental et al., 2016; Bosomworth et al., 2017). In the city of London, United outcomes (medium evidence, high agreement). Adaptation strategies Kingdom, the dominant adaptation and disaster risk management that advance one SDG can result in trade-offs with other SDGs; for pathway promotes resilience that emphasizes self-reliance; yet it instance, agricultural adaptation to enhance food security (SDG 2) intensifies the burden on low-income citizens, the elderly, migrants causing negative impacts for health, equality and healthy ecosystems and others unable to afford flood insurance or protect themselves (SDGs 3, 5, 6, 10, 14 and 15), and resilience to heat stress increasing against heat waves (Pelling et al., 2016). Adaptation pathways in the energy consumption (SDGs 3 and 7) and high-cost adaptation Bolivian Altiplano have transformed subsistence farmers into world- in resource-constrained contexts (medium evidence, medium leading quinoa producers, but loss of social cohesion and traditional agreement). values, dispossession and loss of ecosystem services now constitute undesirable trade-offs (Chelleri et al., 2016). 458 Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 A narrow view of adaptation decision-making, for example focused on from place (Fincher et al., 2014; Wyborn et al., 2015; Murphy et al., technical solutions, tends to crowd out more participatory processes 2017; Gajjar et al., 2018). These insights suggest that adaptation (Lawrence and Haasnoot, 2017; Lin et al., 2017), obscures contested pathway approaches to prepare for 1.5°C warmer futures would be values and reinforces power asymmetries (Bosomworth et al., 2017; difficult to achieve without considerations for inclusiveness, place- Singh, 2018). A situated and context-specific understanding of specific trade-off deliberations, redistributive measures and procedural adaptation pathways that galvanizes diverse knowledge, values and justice mechanisms to facilitate equitable transformation (medium joint initiatives helps to overcome dominant path dependencies, avoid evidence, high agreement). trade-offs that intensify inequities and challenge policies detached Box 5.1 | Ecosystem- and Community-Based Practices in Drylands Drylands face severe challenges in building climate resilience (Fuller and Lain, 2017), yet small-scale farmers can play a crucial role as agents of change through ecosystem- and community-based practices that combine adaptation, mitigation and sustainable development. Farmer managed natural regeneration (FMNR) of trees in cropland is practised in 18 countries across sub-Saharan Africa, Southeast Asia, Timor-Leste, India and Haiti and has, for example, permitted the restoration of over five million hectares of land in the Sahel (Niang et al., 2014; Bado et al., 2016). In Ethiopia, the Managing Environmental Resources to Enable Transitions programme, which entails community-based watershed rehabilitation in rural landscapes, supported around 648,000 people, resulting in the rehabilitation of 25,400,000 hectares of land in 72 severely food-insecure districts across Ethiopia between 2012 and 2015 (Gebrehaweria et al., 2016). In India, local farmers have benefitted from watershed programmes across different agro-ecological regions (Singh et al., 2014; Datta, 2015). These low-cost, flexible community-based practices represent low-regrets adaptation and mitigation strategies. These strategies often contribute to strengthened ecosystem resilience and biodiversity, increased agricultural productivity and food security, reduced household poverty and drudgery for women, and enhanced agency and social capital (Niang et al., 2014; Francis et al., 2015; Kassie et al., 2015; Mbow et al., 2015; Reij and Winterbottom, 2015; Weston et al., 2015; Bado et al., 2016; Dumont et al., 2017). Small check dams in dryland areas and conservation agriculture can significantly increase agricultural output (Kumar et al., 2014; Agoramoorthy and Hsu, 2016; Pradhan et al., 2018). Mitigation benefits have also been quantified (Weston et al., 2015); for example, FMNR of more than five million hectares in Niger has sequestered 25–30 Mtonnes of carbon over 30 years (Stevens et al., 2014). However, several constraints hinder scaling-up efforts: inadequate attention to the socio-technical processes of innovation (Grist et al., 2017; Scoones et al., 2017), difficulties in measuring the benefits of an innovation (Coe et al., 2017), farmers’ inability to deal with long-term climate risk (Singh et al., 2017), and difficulties for matching practices with agro-ecological conditions and complementary modern inputs (Kassie et al., 2015). Key conditions to overcome these challenges include: developing agroforestry value chains and markets (Reij and Winterbottom, 2015) and adaptive planning and management (Gray et al., 2016). Others include 5 inclusive processes giving greater voice to women and marginalized groups (MRFCJ, 2015a; UN Women and MRFCJ, 2016; Dumont 5 et al., 2017), strengthening community land and forest rights (Stevens et al., 2014; Vermeulen et al., 2016), and co-learning among communities of practice at different scales (Coe et al., 2014; Reij and Winterbottom, 2015; Sinclair, 2016; Binam et al., 2017; Dumont et al., 2017; Epule et al., 2017). 5.4 Mitigation and Sustainable Development 5.4.1 Synergies and Trade-Offs between Mitigation Options and Sustainable Development The AR5 WGIII examined the potential of various mitigation options for specific sectors (energy supply, industry, buildings, transport, and Adopting stringent climate mitigation options can generate multiple agriculture, forestry, and other land use; AFOLU); it provided a narrative positive non-climate benefits that have the potential to reduce the of dimensions of sustainable development and equity as a framing for costs of achieving sustainable development (IPCC, 2014b; Ürge- evaluating climate responses and policies, respectively, in Chapters 4, Vorsatz et al., 2014, 2016; Schaeffer et al., 2015; von Stechow et al., 7, 8, 9, 10 and 11 (IPCC, 2014a). This section builds on the analyses of 2015). Understanding the positive impacts (synergies) but also the Chapters 2 and 4 of this report to re-assess mitigation and sustainable negative impacts (trade-offs) is key for selecting mitigation options development in the context of 1.5°C global warming as well as the and policy choices that maximize the synergies between mitigation SDGs. and developmental actions (Hildingsson and Johansson, 2015; Nilsson 459 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities et al., 2016; Delponte et al., 2017; van Vuuren et al., 2017b; McCollum 2015; Fay et al., 2015; Liddell and Guiney, 2015; Shah et al., 2015; et al., 2018b). Aligning mitigation response options to sustainable Sharpe et al., 2015; Wells et al., 2015; Willand et al., 2015; Hallegatte development objectives can ensure public acceptance (IPCC, 2014a), et al., 2016; Kusumaningtyas and Aldrian, 2016; Berrueta et al., 2017; encourage faster action (Lechtenboehmer and Knoop, 2017) and McCollum et al., 2018a). support the design of equitable mitigation (Holz et al., 2018; Winkler et al., 2018) that protect human rights (MRFCJ, 2015b) (Section 5.5.3). In energy-intensive processing industries, 1.5ºC-compatible trajectories require radical technology innovation through maximum electrification, This sub-section assesses available literature on the interactions of shift to other low emissions energy carriers such as hydrogen or individual mitigation options (see Chapter 2, Section 2.3.1.2, Chapter biomass, integration of carbon capture and storage (CCS) and 4, Sections 4.2 and 4.3) with sustainable development and the SDGs innovations for carbon capture and utilization (CCU) (see Chapter 4, and underlying targets. Table 5.2 presents an assessment of these Section 4.3.4.5). These transformations have strong synergies with synergies and trade-offs and the strength of the interaction using an innovation and sustainable industrialization (SDG 9), supranational SDG-interaction score (see Glossary) (McCollum et al., 2018b), with partnerships (SDGs 16 and 17) and sustainable production (SDG 12). evidence and agreements levels. Figure 5.2 presents the information However, possible trade-offs due to risks of CCS-based carbon of Table 5.2, showing gross (not net) interactions with the SDGs. This leakage, increased electricity demands, and associated price impacts detailed assessment of synergies and trade-offs of individual mitigation affecting energy access and poverty (SDGs 7 and 1) would need careful options with the SDGs (Table 5.2 a–d and Figure 5.2) reveals that the regulatory attention (Wesseling et al., 2017). In the mining industry, number of synergies exceeds that of trade-offs. Mitigation response energy efficiency can be synergetic or face trade-offs with sustainable options in the energy demand sector, AFOLU and oceans have more management (SDG 6), depending on the option retained for water positive interactions with a larger number of SDGs compared to those management (Nguyen et al., 2014). Substitution and recycling are on the energy supply side (robust evidence, high agreement). also an important driver of 1.5ºC-compatible trajectories in industrial systems (see Chapter 4, Section 4.3.4.2). Structural changes and 5.4.1.1 Energy Demand: Mitigation Options to Accelerate reorganization of economic activities in industrial park/clusters Reduction in Energy Use and Fuel Switch following the principles of industrial symbiosis (circular economy) improves the overall sustainability by reducing energy and waste For mitigation options in the energy demand sectors, the number (Fan et al., 2017; Preston and Lehne, 2017) and reinforces responsible of synergies with all sixteen SDGs exceeds the number of trade-offs production and consumption (SDG 12) through recycling, water use (Figure 5.2 and Table 5.2) (robust evidence, high agreement). Most efficiency (SDG 6), energy access (SDG 7) and ecosystem protection of the interactions are of a reinforcing nature, hence facilitating the and restoration (SDG 15) (Karner et al., 2015; Zeng et al., 2017). achievement of the goals. In the transport sector, deep electrification may trigger increases of Accelerating energy efficiency in all sectors, which is a necessary electricity prices and adversely affect poor populations (SDG 1), unless condition for a 1.5°C warmer world (see Chapters 2 and 4), has pro-poor redistributive policies are in place (Klausbruckner et al., 2016). In synergies with a large number of SDGs (robust evidence, high cities, governments can lay the foundations for compact, connected low- agreement) (Figure 5.2 and Table 5.2). The diffusion of efficient carbon cities, which are an important component of 1.5ºC-compatible equipment and appliances across end use sectors has synergies with transformations (see Chapter 4, Section 4.3.3) and show synergies with international partnership (SDG 17) and participatory and transparent sustainable cities (SDG 11) (Colenbrander et al., 2016). institutions (SDG 16) because innovations and deployment of new technologies require transnational capacity building and knowledge Behavioural responses are important determinants of the ultimate 5 sharing. Resource and energy savings support sustainable production outcome of energy efficiency on emission reductions and energy access 5 and consumption (SDG 12), energy access (SDG 7), innovation and (SDG 7) and their management requires a detailed understanding infrastructure development (SDG 9) and sustainable city development of the drivers of consumption and the potential for and barriers to (SDG 11). Energy efficiency supports the creation of decent jobs by new absolute reductions (Fuchs et al., 2016). Notably, the rebound effect service companies providing services for energy efficiency, but the net tends to offset the benefits of efficiency for emissions reductions employment effect of efficiency improvement remains uncertain due to through growing demand for energy services (Sorrell, 2015; Suffolk and macro-economic feedback (SDG 8) (McCollum et al., 2018b). Poortinga, 2016). However, high rebound can help in providing faster access to affordable energy (SDG 7.1) where the goal is to reduce energy In the buildings sector, accelerating energy efficiency by way of, poverty and unmet energy demand (see Chapter 2, Section 2.4.3) for example, enhancing the use of efficient appliances, refrigerant (Chakravarty et al., 2013). Comprehensive policy design – including transition, insulation, retrofitting and low- or zero-energy buildings rebound supressing policies, such as carbon pricing and policies that generates benefits across multiple SDG targets. For example, encourage awareness building and promotional material design – is improved cook stoves make fuel endowments last longer and needed to tap the full potential of energy savings, as applicable to a hence reduce deforestation (SDG 15), support equal opportunity by 1.5°C warming context (Chakravarty and Tavoni, 2013; IPCC, 2014b; reducing school absences due to asthma among children (SDGs 3 Karner et al., 2015; Zhang et al., 2015; Altieri et al., 2016; Santarius and 4) and empower rural and indigenous women by reducing drudgery et al., 2016) and to address policy-related trade-offs and welfare- (SDG 5) (robust evidence, high agreement) (Derbez et al., 2014; Lucon enhancing benefits (robust evidence, high agreement) (Chakravarty et et al., 2014; Maidment et al., 2014; Scott et al., 2014; Cameron et al., al., 2013; Chakravarty and Roy, 2016; Gillingham et al., 2016). 460 Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 Other behavioural responses will affect the interplay between energy (e.g., for water use; SDG 6) and have mixed effects for human health efficiency and sustainable development. Building occupants reluctant when replacing fossil fuels (SDGs 7 and 3) (see Table 5.2). The use of to change their habits may miss out on welfare-enhancing energy fossil CCS, which plays an important role in deep mitigation pathways efficiency opportunities (Zhao et al., 2017). Preferences for new (see Chapter 2, Section 2.4.2.3), implies continued adverse impacts products and premature obsolescence for appliances is expected to of upstream supply-chain activities in the coal sector, and because of adversely affect sustainable consumption and production (SDG 12) with lower efficiency of CCS coal power plants (SDG 12), upstream impacts ramifications for resource use efficiency (Echegaray, 2016). Changes and local air pollution are likely to be exacerbated (SDG 3). Furthermore, in user behaviour towards increased physical activity, less reliance on there is a non-negligible risk of carbon dioxide leakage from geological motorized travel over short distances and the use of public transport storage and the carbon dioxide transport infrastructure (SDG 3) would help to decarbonize the transport sector in a synergetic manner (Table 5.2). with SDGs 3, 11 and 12 (Shaw et al., 2014; Ajanovic, 2015; Chakrabarti and Shin, 2017), while reducing inequality in access to basic facilities Economies dependent upon fossil fuel-based energy generation and/or (SDG 10) (Lucas and Pangbourne, 2014; Kagawa et al., 2015). However, export revenue are expected to be disproportionally affected by future infrastructure design and regulations would need to ensure road safety restrictions on the use of fossil fuels under stringent climate goals and and address risks of road accidents for pedestrians (Hwang et al., higher carbon prices; this includes impacts on employment, stranded 2017; Khreis et al., 2017) to ensure sustainable infrastructure growth assets, resources left underground, lower capacity use and early phasing in human settlements (SDGs 9 and 11) (Lin et al., 2015; SLoCaT, 2017). out of large infrastructure already under construction (robust evidence, high agreement) (Box 5.2) (Johnson et al., 2015; McGlade and Ekins, 5.4.1.2 Energy Supply: Accelerated Decarbonization 2015; UNEP, 2017; Spencer et al., 2018). Investment in coal continues to be attractive in many countries as it is a mature technology and Decreasing the share of coal in energy supply in line with 1.5ºC-compatible provides cheap energy supplies, large-scale employment and energy scenarios (see Chapter 2, Section 2.4.2) reduces adverse impacts of security (Jakob and Steckel, 2016; Vogt-Schilb and Hallegatte, 2017; upstream supply-chain activities, in particular air and water pollution and Spencer et al., 2018). Hence, accompanying policies and measures coal mining accidents, and enhances health by reducing air pollution, would be required to ease job losses and correct for relatively higher notably in cities, showing synergies with SDGs 3, 11 and 12 (Yang et al., prices of alternative energy (Oosterhuis and Ten Brink, 2014; Oei and 2016; UNEP, 2017). Mendelevitch, 2016; Garg et al., 2017; HLCCP, 2017; Jordaan et al., 2017; OECD, 2017; UNEP, 2017; Blondeel and van de Graaf, 2018; Fast deployment of renewables such as solar, wind, hydro and modern Green, 2018). Research on historical transitions shows that managing biomass, together with the decrease of fossil fuels in energy supply (see the impacts on workers through retraining programmes is essential Chapter 2, Section 2.4.2.1), is aligned with the doubling of renewables in order to align the phase-down of mining industries with meeting in the global energy mix (SDG 7.2). Renewables could also support ambitious climate targets, and the objectives of a ‘just transition’ progress on SDGs 1, 10, 11 and 12 and supplement new technology (Galgóczi, 2014; Caldecott et al., 2017; Healy and Barry, 2017). This (robust evidence, high agreement) (Chaturvedi and Shukla, 2014; Rose aspect is even more important in developing countries where the et al., 2014; Smith and Sagar, 2014; Riahi et al., 2015; IEA, 2016; van mining workforce is largely semi- or unskilled (Altieri et al., 2016; Tung, Vuuren et al., 2017a; McCollum et al., 2018a). However, some trade- 2016). Ambitious emissions reduction targets can unlock very strong offs with the SDGs can emerge from offshore installations, particularly decoupling potentials in industrialized fossil exporting economies SDG 14 in local contexts (McCollum et al., 2018a). Moreover, trade- (Hatfield-Dodds et al., 2015). offs between renewable energy production and affordability (SDG 7) (Labordena et al., 2017) and other environmental objectives would 5 need to be scrutinised for potential negative social outcomes. Policy 5 interventions through regional cooperation-building (SDG 17) and institutional capacity (SDG 16) can enhance affordability (SDG 7) (Labordena et al., 2017). The deployment of small-scale renewables, or off-grid solutions for people in remote areas (Sánchez and Izzo, 2017), has strong potential for synergies with access to energy (SDG 7), but the actualization of these potentials requires measures to overcome technology and reliability risks associated with large-scale deployment of renewables (Giwa et al., 2017; Heard et al., 2017). Bundling energy- efficient appliances and lighting with off-grid renewables can lead to substantial cost reduction while increasing reliability (IEA, 2017). Low-income populations in industrialized countries are often left out of renewable energy generation schemes, either because of high start-up costs or lack of home ownership (UNRISD, 2016). Nuclear energy, the share of which increases in most of the 1.5ºC-compatible pathways (see Chapter 2, Section 2.4.2.1), can increase the risks of proliferation (SDG 16), have negative environmental effects 461 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities Box 5.2 | Challenges and Opportunities of Low-Carbon Pathways in Gulf Cooperative Council Countries The Gulf Cooperative Council (GCC) region (Bahrain, Kuwait, Oman, Qatar, Saudi Arabia and United Arab Emirates) is characterized by high dependency on hydrocarbon resources (natural oil and gas), with high risks of socio-economic impacts of policies and response measures to address climate change. The region is also vulnerable to the decrease of the global demand and price of hydrocarbons as a result of climate change response measures. The projected declining use of oil and gas under low emissions pathways creates risks of significant economic losses for the GCC region (e.g., Waisman et al., 2013; Van de Graaf and Verbruggen, 2015; Al-Maamary et al., 2016; Bauer et al., 2016), given that natural gas and oil revenues contributed to about 70% of government budgets and > 35% of the gross domestic product in 2010 (Callen et al., 2014). The current high energy intensity of the domestic economies (Al-Maamary et al., 2017), triggered mainly by low domestic energy prices (Alshehry and Belloumi, 2015), suggests specific challenges for aligning mitigation towards 1.5°C-consistent trajectories, which would require strong energy efficiency and economic development for the region. The region’s economies are highly reliant on fossil fuel for their domestic activities. Yet the renewables deployment potentials are large, deployment is already happening (Cugurullo, 2013; IRENA, 2016) and positive economic benefits can be envisaged (Sgouridis et al., 2016). Nonetheless, the use of renewables is currently limited by economics and structural challenges (Lilliestam and Patt, 2015; Griffiths, 2017a). Carbon capture and storage (CCS) is also envisaged with concrete steps towards implementation (Alsheyab, 2017; Ustadi et al., 2017); yet the real potential of this technology in terms of scale and economic dimensions is still uncertain. Beyond the above mitigation-related challenges, the region’s human societies and fragile ecosystems are highly vulnerable to the impacts of climate change, such as water stress (Evans et al., 2004; Shaffrey et al., 2009), desertification (Bayram and Öztürk, 2014), sea level rise affecting vast low coastal lands, and high temperature and humidity with future levels potentially beyond adaptive capacities (Pal and Eltahir, 2016). A low-carbon pathway that manages climate-related risks within the context of sustainable development requires an approach that jointly addresses both types of vulnerabilities (Al Ansari, 2013; Lilliestam and Patt, 2015; Babiker, 2016; Griffiths, 2017b). The Nationally Determined Contributions (NDCs) for GCC countries identified energy efficiency, deployment of renewables and technology transfer to enhance agriculture, food security, protection of marine resources, and management of water and costal zones (Babiker, 2016). Strategic vision documents, such as Saudi Arabia’s ‘Vision 2030’, identify emergent opportunities for energy price reforms, energy efficiency, turning emissions into valuable products, and deployment of renewables and other clean technologies, if accompanied with appropriate policies to manage the transition and in the context of economic diversification (Luomi, 2014; Atalay et al., 2016; Griffiths, 2017b; Howarth et al., 2017). 5.4.1.3 Land-based agriculture, forestry and ocean: mitigation Emerging evidence indicates that future mitigation efforts that would response options and carbon dioxide removal be required to reach stringent climate targets, particularly those 5 associated with carbon dioxide removal (CDR) (e.g., afforestation and 5 In the AFOLU sector, dietary change towards global healthy diets, that reforestation and bioenergy with carbon capture and storage; BECCS), is, a shift from over-consumption of animal-related to plant-related may also impose significant constraints upon poor and vulnerable diets, and food waste reduction (see Chapter 4, Section 4.3.2.1) are communities (SDG 1) via increased food prices and competition for in synergy with SDGs 2 and 6, and SDG 3 through lower consumption arable land, land appropriation and dispossession (Cavanagh and of animal products and reduced losses and waste throughout the food Benjaminsen, 2014; Hunsberger et al., 2014; Work, 2015; Muratori et system, contributing to achieving SDGs 12 and 15 (Bajželj et al., 2014; al., 2016; Smith et al., 2016; Burns and Nicholson, 2017; Corbera et Bustamante et al., 2014; Tilman and Clark, 2014; Hiç et al., 2016). al., 2017) with disproportionate negative impacts upon rural poor and indigenous populations (SDG 1) (robust evidence, high agreement) Power dynamics play an important role in achieving behavioural change (Section 5.4.2.2, Table 5.2, Figure 5.2) (Grubert et al., 2014; Grill et al., and sustainable consumption (Fuchs et al., 2016). In forest management 2015; Zhang and Chen, 2015; Fricko et al., 2016; Johansson et al., 2016; (see Chapter 4, Section 4.3.2.2), encouraging responsible sourcing of Aha and Ayitey, 2017; De Stefano et al., 2017; Shi et al., 2017). Crops forest products and securing indigenous land tenure has the potential to for bioenergy may increase irrigation needs and exacerbate water increase economic benefits by creating decent jobs (SDG 8), maintaining stress with negative associated impacts on SDGs 6 and 10 (Boysen et biodiversity (SDG 15), facilitating innovation and upgrading technology al., 2017). (SDG 9), and encouraging responsible and just decision-making (SDG 16) (medium evidence, high agreement) (Ding et al., 2016; WWF, Ocean iron fertilization and enhanced weathering have two-way 2017). interactions with life under water and on land and food security (SDGs 462 Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 2, 14 and 15) (Table 5.2). Development of blue carbon resources through reduction (SDG 1) (Schirmer and Bull, 2014; Lamb et al., 2016); and food coastal (mangrove) and marine (seaweed) vegetative ecosystems security (SDG 2) (Ahmed et al., 2017a, b; Duarte et al., 2017; Sondak et encourages: integrated water resource management (SDG 6) (Vierros, al., 2017; Vierros, 2017; Zhang et al., 2017). 2017); promotes life on land (SDG 15) (Potouroglou et al., 2017); poverty 5 Figure 5.2 | Synergies and trade-offs and gross Sustainable Development Goal (SDG)-interaction with individual mitigation options. The top three wheels represent synergies 5 and the bottom three wheels show trade-offs. The colours on the border of the wheels correspond to the SDGs listed above, starting at the 9 o’clock position, with reading guidance in the top-left corner with the quarter circle (Note 1). Mitigation (climate action, SDG 13) is at the centre of the circle. The coloured segments inside the circles can be counted to arrive at the number of synergies (green) and trade-offs (red). The length of the coloured segments shows the strength of the synergies or trade-offs (Note 3) and the shading indicates confidence (Note 2). Various mitigation options within the energy demand sector, energy supply sector, and land and ocean sector, and how to read them within a segment are shown in grey (Note 4). See also Table 5.2. 5.4.2 Sustainable Development Implications of Both 1.5°C and 2°C pathways would require deep cuts in greenhouse 1.5°C and 2°C Mitigation Pathways gas (GHG) emissions and large-scale changes of energy supply and demand, as well as in agriculture and forestry systems (see Chapter While previous sections have focused on individual mitigation options 2, Section 2.4). For the assessment of the sustainable development and their interaction with sustainable development and the SDGs, implications of these pathways, this chapter draws upon studies that this section takes a systems perspective. Emphasis is on quantitative show the aggregated impact of mitigation for multiple sustainable pathways depicting path-dependent evolutions of human and development dimensions (Grubler et al., 2018; McCollum et al., natural systems over time. Specifically, the focus is on fundamental 2018b; Rogelj et al., 2018) and across multiple integrated assessment transformations and thus stringent mitigation policies consistent with modelling (IAM) frameworks. Often these tools are linked to 1.5°C or 2°C, and the differential synergies and trade-offs with respect disciplinary models covering specific SDGs in more detail (Cameron to the various sustainable development dimensions. et al., 2016; Rao et al., 2017; Grubler et al., 2018; McCollum et al., 463 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities 2018b). Using multiple IAMs and disciplinary models is important at risk of hunger, including through the adoption of different for a robust assessment of the sustainable development implications complementary measures, such as food price support. The investment of different pathways. Emphasis is on multi-regional studies, which needs of complementary food price policies are found to be globally can be aggregated to the global scale. The recent literature on 1.5°C relatively much smaller than the associated mitigation investments mitigation pathways has begun to provide quantifications for a range of 1.5°C pathways (Figure 5.3) (McCollum et al., 2018b). Besides of sustainable development dimensions, including air pollution and food support price, other measures include improving productivity health, food security and hunger, energy access, water security, and and efficiency of agricultural production systems (FAO and NZAGRC, multidimensional poverty and equity. 2017a, b; Frank et al., 2017) and programmes focusing on forest land- use change (Havlík et al., 2014). All these lead to additional benefits of 5.4.2.1 Air pollution and health mitigation, improving resilience and livelihoods. GHGs and air pollutants are typically emitted by the same sources. Van Vuuren et al. (2018) and Grubler et al. (2018) show that 1.5°C Hence, mitigation strategies that reduce GHGs or the use of fossil fuels pathways without reliance on BECCS can be achieved through a typically also reduce emissions of pollutants, such as particulate matter fundamental transformation of the service sectors which would (e.g., PM2.5 and PM10), black carbon (BC), sulphur dioxide (SO2), significantly reduce energy and food demand (see Chapter 2, Sections nitrogen oxides (NOx) and other harmful species (Clarke et al., 2014) 2.1.1, 2.3.1 and 2.4.3). Such low energy demand (LED) pathways (Figure 5.3), causing adverse health and ecosystem effects at various would result in significantly reduced pressure on food security, lower scales (Kusumaningtyas and Aldrian, 2016). food prices and fewer people at risk of hunger. Importantly, the trade- offs with food security would be reduced by the avoided impacts in the Mitigation pathways typically show that there are significant synergies agricultural sector due to the reduced warming associated with the for air pollution, and that the synergies increase with the stringency of 1.5°C pathways (see Chapter 3, Section 3.5). However, such feedbacks the mitigation policies (Amann et al., 2011; Rao et al., 2016; Klimont are not comprehensively captured in the studies on mitigation. et al., 2017; Shindell et al., 2017; Markandya et al., 2018). Recent multimodel comparisons indicate that mitigation pathways consistent 5.4.2.3 Lack of energy access/energy poverty with 1.5°C would result in higher synergies with air pollution compared to pathways that are consistent with 2°C (Figures 5.4 and 5.5). Shindell A lack of access to clean and affordable energy (especially for cooking) et al. (2018) indicate that health benefits worldwide over the century is a major policy concern in many countries, especially in those in South of 1.5°C pathways could be in the range of 110 to 190 million fewer Asia and Africa where major parts of the population still rely primarily premature deaths compared to 2°C pathways. The synergies for air on solid fuels for cooking (IEA and World Bank, 2017). Scenario studies pollution are highest in the developing world, particularly in Asia. In which quantify the interactions between climate mitigation and energy addition to significant health benefits, there are also economic benefits access indicate that stringent climate policy which would affect energy from mitigation, reducing the investment needs in air pollution control prices could significantly slow down the transition to clean cooking technologies by about 35% globally (or about 100 billion USD2010 per fuels, such as liquefied petroleum gas or electricity (Cameron et al., year to 2030 in 1.5°C pathways; McCollum et al., 2018b) (Figure 5.4). 2016). 5.4.2.2 Food security and hunger Estimates across six different IAMs (McCollum et al., 2018b) indicate that, in the absence of compensatory measures, the number of people Stringent climate mitigation pathways in line with ‘well below 2°C’ or without access to clean cooking fuels may increase. Redistributional ‘1.5°C’ goals often rely on the deployment of large-scale land-related measures, such as subsidies on cleaner fuels and stoves, could 5 measures, like afforestation and/or bioenergy supply (Popp et al., 2014; compensate for the negative effects of mitigation on energy access. 5 Rose et al., 2014; Creutzig et al., 2015). These land-related measures Investment costs of the redistributional measures in 1.5°C pathways can compete with food production and hence raise food security (on average around 120 billion USD2010 per year to 2030; Figure 5.4) concerns (Section 5.4.1.3) (P. Smith et al., 2014). Mitigation studies are much smaller than the mitigation investments of 1.5°C pathways indicate that so-called ‘single-minded’ climate policy, aiming solely (McCollum et al., 2018b). The recycling of revenues from climate policy at limiting warming to 1.5°C or 2°C without concurrent measures in might act as a means to help finance the costs of providing energy the food sector, can have negative impacts for global food security access to the poor (Cameron et al., 2016). (Hasegawa et al., 2015; McCollum et al., 2018b). Impacts of 1.5°C mitigation pathways can be significantly higher than those of 2°C 5.4.2.4 Water security pathways (Figures 5.4 and 5.5). An important driver of the food security impacts in these scenarios is the increase of food prices and the effect Transformations towards low emissions energy and agricultural of mitigation on disposable income and wealth due to GHG pricing. A systems can have major implications for freshwater demand as well as recent study indicates that, on aggregate, the price and income effects water pollution. The scaling up of renewables and energy efficiency as on food may be bigger than the effect due to competition over land depicted by low emissions pathways would, in most instances, lower between food and bioenergy (Hasegawa et al., 2015). water demands for thermal energy supply facilities (‘water-for-energy’) compared to fossil energy technologies, and thus reinforce targets In order to address the issue of trade-offs with food security, mitigation related to water access and scarcity (see Chapter 4, Section 4.2.1). policies would need to be designed in a way that shields the population However, some low-carbon options such as bioenergy, centralized solar 464 Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 5 5 Figure 5.3 | Sustainable development implications of mitigation actions in 1.5°C pathways. Panel (a) shows ranges for 1.5°C pathways for selected sustainable development dimensions compared to the ranges of 2°C pathways and baseline pathways. The panel (a) depicts interquartile and the full range across the scenarios for Sustainable Development Goal (SDG) 2 (hunger), SDG 3 (health), SDG 6 (water), SDG 7 (energy), SDG 12 (resources), SDG 13/14 (climate/ocean) and SDG 15 (land). Progress towards achieving the SDGs is denoted by arrow symbols (increase or decrease of indicator). Black horizontal lines show 2015 values for comparison. Note that sustainable development effects are estimated for the effect of mitigation and do not include benefits from avoided impacts (see Chapter 3, Section 3.5). Low energy demand (LED) denotes estimates from a pathway with extremely low energy demand reaching 1.5°C without bioenergy with carbon capture and storage (BECCS). Panel (b) presents the resulting full range for synergies and trade-offs of 1.5°C pathways compared to the corresponding baseline scenarios. The y-axis in panel (b) indicates the factor change in the 1.5°C pathway compared to the baseline. Note that the figure shows gross impacts of mitigation and does not include feedbacks due to avoided impacts. The realization of the side effects will critically depend on local circumstances and implementation practice. Trade-offs across many sustainable development dimensions can be reduced through complementary/ re-distributional measures. The figure is not comprehensive and focuses on those sustainable development dimensions for which quantifications across models are available. Sources: 1.5°C pathways database from Chapter 2 (Grubler et al., 2018; McCollum et al., 2018b). 465 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities power, nuclear and hydropower technologies could, if not managed properly, have counteracting effects that compound existing water- related problems in a given locale (Byers et al., 2014; Fricko et al., 2016; IEA, 2016; Fujimori et al., 2017a; Wang, 2017; McCollum et al., 2018a). Under stringent mitigation efforts, the demand for bioenergy can result in a substantial increase of water demand for irrigation, thereby potentially contributing to water scarcity in water-stressed regions (Berger et al., 2015; Bonsch et al., 2016; Jägermeyr et al., 2017). However, this risk can be reduced by prioritizing rain-fed production of bioenergy (Hayashi et al., 2015, 2018; Bonsch et al., 2016), but might have adverse effects for food security (Boysen et al., 2017). Reducing food and energy demand without compromising the needs of the poor emerges as a robust strategy for both water conservation Figure 5.4 | Investment into mitigation up until 2030 and implications for and GHG emissions reductions (von Stechow et al., 2015; IEA, 2016; investments for four sustainable development dimensions. Cross-hatched bars show Parkinson et al., 2016; Grubler et al., 2018). The results underscore the the median investment in 1.5°C pathways across results from different models, and importance of an integrated approach when developing water, energy solid bars for 2°C pathways, respectively. Whiskers on bars represent minima and and climate policy (IEA, 2016). maxima across estimates from six models. Clean water and air pollution investments are available only from one model. Mitigation investments show the change in investments across mitigation options compared to the baseline. Negative mitigation Estimates across different models for the impacts of stringent investments (grey bars) denote disinvestment (reduced investment needs) into mitigation pathways on energy-related water uses seem ambiguous. fossil fuel sectors compared to the baseline. Investments for different sustainable Some pathways show synergies (Mouratiadou et al., 2018) while development dimensions denote the investment needs for complementary measures others indicate trade-offs and thus increases of water use due to in order to avoid trade-offs (negative impacts) of mitigation. Negative sustainable mitigation (Fricko et al., 2016). The synergies depend on the adopted development investments for air pollution indicate cost savings, and thus synergies of mitigation for air pollution control costs. The values compare to about 2 trillion policy implementation or mitigation strategies and technology USD2010 (range of 1.4 to 3 trillion) of total energy-related investments in the 1.5°C portfolio. A number of adaptation options exist (e.g., dry cooling), pathways. Source: Estimates from CD-LINKS scenarios summarised by McCollum et which can effectively reduce electricity-related water trade-offs (Fricko al., 2018b. et al., 2016; IEA, 2016). Similarly, irrigation water use will depend on the regions where crops are produced, the sources of bioenergy (e.g., trade-offs between mitigation and other sustainable development agriculture vs. forestry) and dietary change induced by climate policy. dimensions (von Stechow et al., 2015; Grubler et al., 2018; van Vuuren Overall, and also considering other water-related SDGs, including et al., 2018). Reliance on demand-side measures only, however, would access to safe drinking water and sanitation as well as waste-water not be sufficient for meeting stringent targets, such as 1.5°C and 2°C treatment, investments into the water sector seem to be only modestly (Clarke et al., 2014). affected by stringent climate policy compatible with 1.5°C (Figure 5.4) (McCollum et al., 2018b). In summary, the assessment of mitigation pathways shows that to 5.5 Sustainable Development meet the 1.5°C target, a wide range of mitigation options would need Pathways to 1.5°C 5 to be deployed (see Chapter 2, Sections 2.3 and 2.4). While pathways 5 aiming at 1.5°C are associated with high synergies for some sustainable This section assesses what is known in the literature on development development dimensions (such as human health and air pollution, forest pathways that are sustainable and climate-resilient and relevant to preservation), the rapid pace and magnitude of the required changes a 1.5°C warmer world. Pathways, transitions from today’s world to would also lead to increased risks for trade-offs for other sustainable achieving a set of future goals (see Chapter 1, Section 1.2.3, Cross- development dimensions (particularly food security) (Figures 5.4 and Chapter Box 1), follow broadly two main traditions: first, as integrated 5.5). Synergies and trade-offs are expected to be unevenly distributed pathways describing the required societal and systems transformations, between regions and nations (Box 5.2), though little literature has combining quantitative modelling and qualitative narratives at multiple formally examined such distributions under 1.5°C-consistent mitigation spatial scales (global to sub-national); and second, as country- and scenarios. Reducing these risks requires smart policy designs and community-level, solution-oriented trajectories and decision-making mechanisms that shield the poor and redistribute the burden so that the processes about context- and place-specific opportunities, challenges most vulnerable are not disproportionately affected. Recent scenario and trade-offs. These two notions of pathways offer different, though analyses show that associated investments for reducing the trade-offs complementary, insights into the nature of 1.5°C-relevant trajectories for, for example, food, water and energy access to be significantly lower and the short-term actions that enable long-term goals. Both highlight than the required mitigation investments (McCollum et al., 2018b). to varying degrees the urgency, ethics and equity dimensions of Fundamental transformation of demand, including efficiency and possible trajectories and society- and system-wide transformations, yet behavioural changes, can help to significantly reduce the reliance on at different scales, building on Chapter 2 (see Section 2.4) and Chapter risky technologies, such as BECCS, and thus reduce the risk of potential 4 (see Section 4.5). 466 Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 5.5.1 Integration of Adaptation, Mitigation Quantitative pathways studies now better represent ‘nexus’ and Sustainable Development approaches to assess sustainable development dimensions. In such approaches (see Chapter 4, Section 4.3.3.8), a subset of sustainable Insights into climate-compatible development (see Glossary) development dimensions are investigated together because of their illustrate how integration between adaptation, mitigation and close relationships (Welsch et al., 2014; Conway et al., 2015; Keairns sustainable development works in context-specific projects, how et al., 2016; Parkinson et al., 2016; Rasul and Sharma, 2016; Howarth synergies are achieved and what challenges are encountered during and Monasterolo, 2017). Compared to single-objective climate–SDG implementation (Stringer et al., 2014; Suckall et al., 2014; Antwi-Agyei assessments (Section 5.4.2), nexus solutions attempt to integrate et al., 2017a; Bickersteth et al., 2017; Kalafatis, 2017; Nunan, 2017). complex interdependencies across diverse sectors in a systems The operationalization of climate-compatible development, including approach for consistent analysis. Recent pathways studies show how climate-smart agriculture and carbon-forestry projects (Lipper et al., water, energy and climate (SDGs 6, 7 and 13) interact (Parkinson et al., 2014; Campbell et al., 2016; Quan et al., 2017), shows multilevel 2016; McCollum et al., 2018b) and call for integrated water–energy and multisector trade-offs involving ‘winners’ and ‘losers’ across investment decisions to manage systemic risks. For instance, the governance levels (high confidence) (Kongsager and Corbera, 2015; provision of bioenergy, important in many 1.5°C-consistent pathways, Naess et al., 2015; Karlsson et al., 2017; Tanner et al., 2017; Taylor, can help resolve ‘nexus challenges’ by alleviating energy security 2017; Wood, 2017; Ficklin et al., 2018). Issues of power, participation, concerns, but can also have adverse ‘nexus impacts’ on food security, values, equity, inequality and justice transcend case study examples of water use and biodiversity (Lotze-Campen et al., 2014; Bonsch et al., attempted integrated approaches (Nunan, 2017; Phillips et al., 2017; 2016). Policies that improve resource use efficiency across sectors can Stringer et al., 2017; Wood, 2017), also reflected in policy frameworks maximize synergies for sustainable development (Bartos and Chester, for integrated outcomes (Stringer et al., 2014; Di Gregorio et al., 2017; 2014; McCollum et al., 2018b; van Vuuren et al., 2018). Mitigation Few et al., 2017; Tanner et al., 2017). compatible with 1.5°C can significantly reduce impacts and adaptation needs in the nexus sectors compared to 2°C (Byers et al., 2018). In Ultimately, reconciling trade-offs between development needs and order to avoid trade-offs due to high carbon pricing of 1.5°C pathways, emissions reductions towards a 1.5°C warmer world requires a regulation in specific areas may complement price-based instruments. dynamic view of the interlinkages between adaptation, mitigation Such combined policies generally lead also to more early action and sustainable development (Nunan, 2017). This entails recognition maximizing synergies and avoiding some of the adverse climate effects of the ways in which development contexts shape the choice and for sustainable development (Bertram et al., 2018). effectiveness of interventions, limit the range of responses afforded to communities and governments, and potentially impose injustices The comprehensive analysis of climate change in the context of upon vulnerable groups (UNRISD, 2016; Thornton and Comberti, 2017). sustainable development requires suitable reference scenarios that A variety of approaches, both quantitative and qualitative, exist to lend themselves to broader sustainable development analyses. examine possible sustainable development pathways under which The Shared Socio-Economic Pathways (SSPs) (Chapter 1, Cross- climate and sustainable development goals can be achieved, and Chapter Box 1 in Chapter 1) (O’Neill et al., 2017a; Riahi et al., 2017) synergies and trade-offs for transformation identified (Sections 5.3 constitute an important first step in providing a framework for and 5.4). the integrated assessment of adaptation and mitigation and their climate–development linkages (Ebi et al., 2014). The five underlying 5.5.2 Pathways for Adaptation, Mitigation SSP narratives (O’Neill et al., 2017a) map well into some of the key and Sustainable Development SDG dimensions, with one of the pathways (SSP1) explicitly depicting sustainability as the main theme (van Vuuren et al., 2017b). 5 This section focuses on the growing body of pathways literature 5 describing the dynamic and systemic integration of mitigation To date, no pathway in the literature proves to achieve all 17 SDGs and adaptation with sustainable development in the context of a because several targets are not met or not sufficiently covered in the 1.5°C warmer world. These studies are critically important for the analysis, hence resulting in a sustainability gap (Zimm et al., 2018). identification of ‘enabling’ conditions under which climate and the The SSPs facilitate the systematic exploration of different sustainable SDGs can be achieved, and thus help the design of transformation dimensions under ambitious climate objectives. SSP1 proves to be in strategies that maximize synergies and avoid potential trade-offs line with eight SDGs (3, 7, 8, 9, 10, 11, 13 and 15) and several of their (Sections 5.3 and 5.4). Full integration of sustainable development targets in a 2°C warmer world (van Vuuren et al., 2017b; Zimm et al., dimensions is, however, challenging, given their diversity and the need 2018). However, important targets for SDGs 1, 2 and 4 (i.e., people for high temporal, spatial and social resolution to address local effects, living in extreme poverty, people living at the risk of hunger and gender including heterogeneity related to poverty and equity (von Stechow gap in years of schooling) are not met in this scenario. et al., 2015). Research on long-term climate change mitigation and adaptation pathways has covered individual SDGs to different degrees. The SSPs show that sustainable socio-economic conditions will play a Interactions between climate and other SDGs have been explored for key role in reaching stringent climate targets (Riahi et al., 2017; Rogelj SDGs 2, 3, 4, 6, 7, 8, 12, 14 and 15 (Clarke et al., 2014; Abel et al., 2016; et al., 2018). Recent modelling work has examined 1.5°C-consistent, von Stechow et al., 2016; Rao et al., 2017), while interactions with stringent mitigation scenarios for 2100 applied to the SSPs, using SDGs 1, 5, 11 and 16 remain largely underexplored in integrated long- six different IAMs. Despite the limitations of these models, which term scenarios (Zimm et al., 2018). are coarse approximations of reality, robust trends can be identified 467 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities (Rogelj et al., 2018). SSP1 – which depicts broader ‘sustainability’ as 5.5.3 Climate-Resilient Development Pathways well as enhancing equity and poverty reductions – is the only pathway where all models could reach 1.5°C and is associated with the lowest This section assesses the literature on pathways as solution- mitigation costs across all SSPs. A decreasing number of models was oriented trajectories and decision-making processes for attaining successful for SSP2, SSP4 and SSP5, respectively, indicating distinctly transformative visions for a 1.5°C warmer world. It builds on climate- higher risks of failure due to high growth and energy intensity as resilient development pathways (CRDPs) introduced in the AR5 well as geographical and social inequalities and uneven regional (Section 5.1.2) (Olsson et al., 2014) as well as growing literature development. And reaching 1.5°C has even been found infeasible in (e.g., Eriksen et al., 2017; Johnson, 2017; Orindi et al., 2017; Kirby and the less sustainable SSP3 – ‘regional rivalry’ (Fujimori et al., 2017b; O’Mahony, 2018; Solecki et al., 2018) that uses CRDPs as a conceptual Riahi et al., 2017). All these conclusions hold true if a 2°C objective is and aspirational idea for steering societies towards low-carbon, considered (Calvin et al., 2017; Fujimori et al., 2017b; Popp et al., 2017; prosperous and ecologically safe futures. Such a notion of pathways Riahi et al., 2017). Rogelj et al. (2018) also show that fewer scenarios foregrounds decision-making processes at local to national levels to are, however, feasible across different SSPs in case of 1.5°C, and situate transformation, resilience, equity and well-being in the complex mitigation costs substantially increase in 1.5°C pathways compared reality of specific places, nations and communities (Harris et al., 2017; to 2°C pathways. Ziervogel et al., 2017; Fazey et al., 2018; Gajjar et al., 2018; Klinsky and Winkler, 2018; Patterson et al., 2018; Tàbara et al., 2018). There is a wide range of SSP-based studies focusing on the connections between adaptation/impacts and different sustainable development Pathways compatible with 1.5°C warming are not merely scenarios dimensions (Hasegawa et al., 2014; Ishida et al., 2014; Arnell et al., to envision possible futures but processes of deliberation and 2015; Bowyer et al., 2015; Burke et al., 2015; Lemoine and Kapnick, implementation that address societal values, local priorities and 2016; Rozenberg and Hallegatte, 2016; Blanco et al., 2017; Hallegatte inevitable trade-offs. This includes attention to politics and power that and Rozenberg, 2017; O’Neill et al., 2017a; Rutledge et al., 2017; perpetuate business-as-usual trajectories (O’Brien, 2016; Harris et al., Byers et al., 2018). New methods for projecting inequality and poverty 2017), the politics that shape sustainability and capabilities of everyday (downscaled to sub-national rural and urban levels as well as spatially life (Agyeman et al., 2016; Schlosberg et al., 2017), and ingredients explicit levels) have enabled advanced SSP-based assessments of for community resilience and transformative change (Fazey et al., locally sustainable development implications of avoided impacts 2018). Chartering CRDPs encourages locally situated and problem- and related adaptation needs. For instance, Byers et al. (2018) find solving processes to negotiate and operationalize resilience ‘on the that, in a 1.5°C warmer world, a focus on sustainable development ground’ (Beilin and Wilkinson, 2015; Harris et al., 2017; Ziervogel et can reduce the climate risk exposure of populations vulnerable to al., 2017). This entails contestation, inclusive governance and iterative poverty by more than an order of magnitude (Section 5.2.2). Moreover, engagement of diverse populations with varied needs, aspirations, aggressive reductions in between-country inequality may decrease agency and rights claims, including those most affected, to deliberate the emissions intensity of global economic growth (Rao and Min, trade-offs in a multiplicity of possible pathways (high confidence) (see 2018). This is due to the higher potential for decoupling of energy Figure 5.5) (Stirling, 2014; Vale, 2014; Walsh-Dilley and Wolford, 2015; from income growth in lower-income countries, due to high potential Biermann et al., 2016; J.R.A. Butler et al., 2016; O’Brien, 2016, 2018; for technological advancements that reduce the energy intensity of Harris et al., 2017; Jones and Tanner, 2017; Mapfumo et al., 2017; growth of poor countries – critical also for reaching 1.5°C in a socially Rosenbloom, 2017; Gajjar et al., 2018; Klinsky and Winkler, 2018; Lyon, and economically equitable way. Participatory downscaling of SSPs in 2018; Tàbara et al., 2018). several European Union countries and in Central Asia shows numerous possible pathways of solutions to the 2°C–1.5°C goal, depending on 5.5.3.1 Transformations, equity and well-being 5 differential visions (Tàbara et al., 2018). Other participatory applications 5 of the SSPs, for example in West Africa (Palazzo et al., 2017) and the Most literature related to CRDPs invokes the concept of transformation, southeastern United States (Absar and Preston, 2015), illustrate the underscoring the need for urgent and far-reaching changes in practices, potentially large differences in adaptive capacity within regions and institutions and social relations in society. Transformations towards a between sectors. 1.5°C warmer world would need to address considerations for equity and well-being, including in trade-off decisions (see Figure 5.1). Harnessing the full potential of the SSP framework to inform sustainable development requires: (i) further elaboration and extension of the To attain the anticipated transformations, all countries as well as non- current SSPs to cover sustainable development objectives explicitly; (ii) state actors would need to strengthen their contributions, through the development of new or variants of current narratives that would bolder and more committed cooperation and equitable effort-sharing facilitate more SDG-focused analyses with climate as one objective (medium evidence, high agreement) (Rao, 2014; Frumhoff et al., 2015; (among other SDGs) (Riahi et al., 2017); (iii) scenarios with high regional Ekwurzel et al., 2017; Millar et al., 2017; Shue, 2017; Holz et al., 2018; resolution (Fujimori et al., 2017b); (iv) a more explicit representation Robinson and Shine, 2018). Sustaining decarbonization rates at a of institutional and governance change associated with the SSPs 1.5°C-compatible level would be unprecedented and not possible (Zimm et al., 2018); and (v) a scale-up of localized and spatially explicit without rapid transformations to a net-zero-emissions global economy vulnerability, poverty and inequality estimates, which have emerged by mid-century or the later half of the century (see Chapters 2 and in recent publications based on the SSPs (Byers et al., 2018) and are 4). Such efforts would entail overcoming technical, infrastructural, essential to investigate equity dimensions (Klinsky and Winkler, 2018). institutional and behavioural barriers across all sectors and levels 468 Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 Figure 5.5 | Pathways into the future, with path dependencies and iterative problem-solving and decision-making (after Fazey et al., 2016). of society (Pfeiffer et al., 2016; Seto et al., 2016) and defeating path equality and political voices (Raworth, 2017). It is in alignment with dependencies, including poverty traps (Boonstra et al., 2016; Enqvist transformative social development (UNRISD, 2016) and the 2030 et al., 2016; Lade et al., 2017; Haider et al., 2018). Transformation also Agenda of ‘leaving no one behind’. The social conditions to enable well- entails ensuring that 1.5°C-compatible pathways are inclusive and being for all are to reduce entrenched inequalities within and between desirable, build solidarity and alliances, and protect vulnerable groups, countries (Klinsky and Winkler, 2018); rethink prevailing values, ethics including against disruptions of transformation (Patterson et al., 2018). and behaviours (Holden et al., 2017); allow people to live a life in dignity while avoiding actions that undermine capabilities (Klinsky There is growing emphasis on the role of equity, fairness and justice (see and Golub, 2016); transform economies (Popescu and Ciurlau, 2016; Glossary) regarding context-specific transformations and pathways Tàbara et al., 2018); overcome uneven consumption and production to a 1.5°C warmer world (medium evidence, high agreement) (Shue, patterns (Dearing et al., 2014; Häyhä et al., 2016; Raworth, 2017) and 2014; Thorp, 2014; Dennig et al., 2015; Moellendorf, 2015; Klinsky et conceptualize development as well-being rather than mere economic 5 al., 2017b; Roser and Seidel, 2017; Sealey-Huggins, 2017; Klinsky and growth (medium evidence, high agreement) (Gupta and Pouw, 2017). 5 Winkler, 2018; Robinson and Shine, 2018). Consideration for what is equitable and fair suggests the need for stringent decarbonization 5.5.3.2 Development trajectories, sharing and up-scaled adaptation that do not exacerbate social injustices, of efforts and cooperation locally and at national levels (Okereke and Coventry, 2016), uphold human rights (Robinson and Shine, 2018), are socially desirable and The potential for pursuing sustainable and climate-resilient development acceptable (von Stechow et al., 2016; Rosenbloom, 2017), address pathways towards a 1.5°C warmer world differs between and within values and beliefs (O’Brien, 2018), and overcome vested interests nations, due to differential development achievements and trajectories, (Normann, 2015; Patterson et al., 2016). Attention is often drawn to and opportunities and challenges (very high confidence) (Figure 5.1). huge disparities in the cost, benefits, opportunities and challenges There are clear differences between high-income countries where involved in transformation within and between countries, and the social achievements are high, albeit often with negative effects on fact that the suffering of already poor, vulnerable and disadvantaged the environment, and most developing nations where vulnerabilities populations may be worsened, if care to protect them is not taken to climate change are high and social support and life satisfaction (Holden et al., 2017; Klinsky and Winkler, 2018; Patterson et al., 2018). are low, especially in the Least Developed Countries (LDCs) (Sachs et al., 2017; O’Neill et al., 2018). Differential starting points for CRDPs Well-being for all (Dearing et al., 2014; Raworth, 2017) is at the between and within countries, including path dependencies (Figure core of an ecologically safe and socially just space for humanity, 5.5), call for sensitivity to context (Klinsky and Winkler, 2018). For the including health and housing, peace and justice, social equity, gender developing world, limiting warming to 1.5°C also means potentially 469 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities severely curtailed development prospects (Okereke and Coventry, contribute to investments in and support for mitigation and adaptation 2016) and risks to human rights from both climate action and inaction (Heede, 2014; Ekwurzel et al., 2017; Shue, 2017) (Sections 5.6.1 and to achieve this goal (Robinson and Shine, 2018) (Section 5.2). Within- 5.6.2). country development differences remain, despite efforts to ensure inclusive societies (Gupta and Arts, 2017; Gupta and Pouw, 2017). Cole At the level of groups and individuals, equity in pursuing climate et al. (2017), for instance, show how differences between provinces in resilience for a 1.5°C warmer world means addressing disadvantage, South Africa constitute barriers to sustainable development trajectories inequities and empowerment that shape transformative processes and for operationalising nation-level SDGs, across various dimensions and pathways (Fazey et al., 2018), and deliberate efforts to strengthen of social deprivation and environmental stress, reflecting historic the capabilities, capacities and well-being of poor, marginalized and disadvantages. vulnerable people (Byrnes, 2014; Tokar, 2014; Harris et al., 2017; Klinsky et al., 2017a; Klinsky and Winkler, 2018). Community-driven Moreover, various equity and effort- or burden-sharing approaches to CRDPs can flag potential negative impacts of national trajectories on climate stabilization in the literature describe how to sketch national disadvantaged groups, such as low-income families and communities potentials for a 1.5°C warmer world (e.g., Anand, 2004; CSO Equity of colour (Rao, 2014). They emphasize social equity, participatory Review, 2015; Meinshausen et al., 2015; Okereke and Coventry, 2016; governance, social inclusion and human rights, as well as innovation, Bexell and Jönsson, 2017; Otto et al., 2017; Pan et al., 2017; Robiou du experimentation and social learning (see Glossary) (medium evidence, Pont et al., 2017; Holz et al., 2018; Kartha et al., 2018; Winkler et al., high agreement) (Sections 5.5.3.3 and 5.6). 2018;). Many approaches build on the AR5 ‘responsibility – capacity – need’ assessment (Clarke et al., 2014), complement other proposed 5.5.3.3 Country and community strategies and experiences national-level metrics for capabilities, equity and fairness (Heyward and Roser, 2016; Klinsky et al., 2017a), or fall under the wider umbrella There are many possible pathways towards climate-resilient futures of fair share debates on responsibility, capability and the right to (O’Brien, 2018; Tàbara et al., 2018). Literature depicting different development in climate policy (Fuglestvedt and Kallbekken, 2016). sustainable development trajectories in line with CRDPs is growing, with Importantly, different principles and methodologies generate different some of it being specific to 1.5°C global warming. Most experiences calculated contributions, responsibilities and capacities (Skeie et al., to date are at local and sub-national levels (Cross-Chapter Box 13 in 2017). this chapter), while state-level efforts align largely with green economy trajectories or planning for climate resilience (Box 5.3). Due to the fact The notion of nation-level fair shares is now also discussed in the that these strategies are context-specific, the literature is scarce on context of limiting global warming to 1.5°C and the Nationally comparisons, efforts to scale up and systematic monitoring. Determined Contributions (NDCs) (see Chapter 4, Cross-Chapter Box 11 in Chapter 4) (CSO Equity Review, 2015; Mace, 2016; Pan et al., States can play an enabling or hindering role in a transition to a 1.5°C 2017; Robiou du Pont et al., 2017; Holz et al., 2018; Kartha et al., 2018; warmer world (Patterson et al., 2018). The literature on strategies to Winkler et al., 2018). A study by Pan et al. (2017) concluded that all reconcile low-carbon trajectories with sustainable development and countries would need to contribute to ambitious emissions reductions ecological sustainability through green growth, inclusive growth, and that current pledges for 2030 by seven out of eight high-emitting de-growth, post-growth and development as well-being shows low countries would be insufficient to meet 1.5°C. Emerging literature on agreement (see Chapter 4, Section 4.5). Efforts that align best with justice-centred pathways to 1.5°C points towards ambitious emissions CRDPs are described as ‘transformational’ and ‘strong’ (Ferguson, reductions domestically and committed cooperation internationally 2015). Some view ‘thick green’ perspectives as enabling equity, whereby wealthier countries support poorer ones, technologically, democracy and agency building (Lorek and Spangenberg, 2014; Stirling, 5 financially and otherwise to enhance capacities (Okereke and Coventry, 2014; Ehresman and Okereke, 2015; Buch-Hansen, 2018), others show 5 2016; Holz et al., 2018; Robinson and Shine, 2018; Shue, 2018). These how green economy and sustainable development pathways can align findings suggest that equitable and 1.5°C-compatible pathways would (Brown et al., 2014; Georgeson et al., 2017b), and how a green economy require fast action across all countries at all levels of development can help link the SDGs with NDCs, for instance in Mongolia, Kenya and rather than late accession of developing countries (as assumed under Sweden (Shine, 2017). Others still critique the continuous reliance on SSP3, see Chapter 2), with external support for prompt mitigation and market mechanisms (Wanner, 2014; Brockington and Ponte, 2015) and resilience-building efforts in the latter (medium evidence, medium disregard for equity and distributional and procedural justice (Stirling, agreement). 2014; Bell, 2015). Scientific advances since the AR5 now also make it possible to determine Country-level pathways and achievements vary significantly (robust contributions to climate change for non-state actors (see Chapter 4, evidence, medium agreement). For instance, the Scandinavian countries Section 4.4.1) and their potential to contribute to CRDPs (medium rank at the top of the Global Green Economy Index (Dual Citizen LLC, evidence, medium agreement). These non-state actors includes cities 2016), although they also tend to show high spill-over effects (Holz et al., (Bulkeley et al., 2013, 2014; Byrne et al., 2016), businesses (Heede, 2018) and transgress their biophysical boundaries (O’Neill et al., 2018). 2014; Frumhoff et al., 2015; Shue, 2017), transnational initiatives State-driven efforts in non-member countries of the Organisation for (Castro, 2016; Andonova et al., 2017) and industries. Recent work Economic Co-operation and Development include Ethiopia’s ‘Climate- demonstrates the contributions of 90 industrial carbon producers to resilient Green Economy Strategy’, Mozambique’s ‘Green Economy global temperature and sea level rise, and their responsibilities to Action Plan’ and Costa Rica’s ecosystem- and conservation-driven 470 Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 green transition paths. China and India have adopted technology and Chapter 3 Box 3.5, Chapter 4 Box 4.3, Box 5.3), examples of CRDPs renewables pathways (Brown et al., 2014; Death, 2014, 2015, 2016; have emerged since the AR5. This includes the SAMOA Pathway: SIDS Khanna et al., 2014; Chen et al., 2015; Kim and Thurbon, 2015; Wang Accelerated Modalities of Action (see Chapter 4, Box 4.3) (UNGA, 2014; et al., 2015; Weng et al., 2015). Brazil promotes low per capita GHG Government of Kiribati, 2016; Steering Committee on Partnerships for emissions, clean energy sources, green jobs, renewables and sustainable SIDS and UN DESA, 2016; Lefale et al., 2017) and the Framework for transportation, while slowing rates of deforestation (see Chapter 4, Box Resilient Development in the Pacific, a leading example of integrated 4.7) (Brown et al., 2014; La Rovere, 2017). Yet concerns remain regarding regional climate change adaptation planning for mitigation and persistent inequalities, ecosystem monetization, lack of participation sustainable development, disaster risk management and low-carbon in green-style projects (Brown et al., 2014) and labour conditions and economies (SPC, 2016). Small islands of the Pacific vary significantly risk of displacement in the sugarcane ethanol sector (McKay et al., in their capacity and resources to support effective integrated planning 2016). Experiences with low-carbon development pathways in LDCs (McCubbin et al., 2015; Barnett and Walters, 2016; Cvitanovic et al., highlight the crucial role of identifying synergies across scale, removing 2016; Hemstock et al., 2017; Robinson and Dornan, 2017). Vanuatu (Box institutional barriers and ensuring equity and fairness in distributing 5.3) has developed a significant coordinated national adaptation plan benefits as part of the right to development (Rai and Fisher, 2017). to advance the 2030 Agenda for Sustainable Development, respond to the Paris Agreement and reduce the risk of disasters in line with the In small islands states, for many of which climate change hazards and Sendai targets (UNDP, 2016; Republic of Vanuatu, 2017). impacts at 1.5°C pose significant risks to sustainable development (see Box 5.3 | Republic of Vanuatu – National Planning for Development and Climate Resilience The Republic of Vanuatu is leading Pacific Small Island Developing States (SIDS) to develop a nationally coordinated plan for climate- resilient development in the context of high exposure to hazard risk (MoCC, 2016; UNU-EHS, 2016). The majority of the population depends on subsistence, rain-fed agriculture and coastal fisheries for food security (Sovacool et al., 2017). Sea level rise, increased prolonged drought, water shortages, intense storms, cyclone events and degraded coral reef environments threaten human security in a 1.5°C warmer world (see Chapter 3, Box 3.5) (SPC, 2015; Aipira et al., 2017). Given Vanuatu’s long history of climate hazards and disasters, local adaptive capacity is relatively high, despite barriers to the use of local knowledge and technology, and low rates of literacy and women’s participation (McNamara and Prasad, 2014; Aipira et al., 2017; Granderson, 2017). However, the adaptive capacity of Vanuatu and other SIDS is increasingly constrained due to more frequent severe weather events (see Chapter 3, Box 3.5, Chapter 4, Cross-Chapter Box 9 in Chapter 4) (Gero et al., 2013; Kuruppu and Willie, 2015; SPC, 2015; Sovacool et al., 2017). Vanuatu has developed a national sustainable development plan for 2016–2030: the People’s Plan (Republic of Vanuatu, 2016). This coordinated, inclusive plan of action on economy, environment and society aims to strengthen adaptive capacity and resilience to climate change and disasters. It emphasizes rights of all Ni-Vanuatu, including women, youth, the elderly and vulnerable groups (Nalau et al., 2016). Vanuatu has also developed a Coastal Adaptation Plan (Republic of Vanuatu, 2016), an integrated Climate Change and Disaster Risk Reduction Policy (2016–2030) (SPC, 2015) and the first South Pacific National Advisory Board on Climate Change & Disaster Risk Reduction (SPC, 2015; UNDP, 2016). 5 Vanuatu aims to integrate planning at multiple scales, and increase climate resilience by supporting local coping capacities and 5 iterative processes of planning for sustainable development and integrated risk assessment (Aipira et al., 2017; Eriksson et al., 2017; Granderson, 2017). Climate-resilient development is also supported by non-state partnerships, for example, the ‘Yumi stap redi long climate change’–the Vanuatu non-governmental organization Climate Change Adaptation Program (Maclellan, 2015). This programme focuses on equitable governance, with particular attention to supporting women’s voices in decision-making through allied programmes addressing domestic violence, and rights-based education to reduce social marginalization; alongside institutional reforms for greater transparency, accountability and community participation in decision-making (Davies, 2015; Maclellan, 2015; Sterrett, 2015; Ensor, 2016; UN Women, 2016). Power imbalances embedded in the political economy of development (Nunn et al., 2014), gender discrimination (Aipira et al., 2017) and the priorities of climate finance (Cabezon et al., 2016) may marginalize the priorities of local communities and influence how local risks are understood, prioritised and managed (Kuruppu and Willie, 2015; Baldacchino, 2017; Sovacool et al., 2017). However, the experience of the low death toll after Cyclone Pam suggests effective use of local knowledge in planning and early warning may support resilience at least in the absence of storm surge flooding (Handmer and Iveson, 2017; Nalau et al., 2017). Nevertheless, the very severe infrastructure damage of Cyclone Pam 2015 highlights the limits of individual Pacific SIDS efforts and the need for global and regional responses to a 1.5°C warmer world (see Chapter 3, Box 3.5, Chapter 4, Box 4.3) (Dilling et al., 2015; Ensor, 2016; Shultz et al., 2016; Rey et al., 2017). 471 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities Communities, towns and cities also contribute to low-carbon pathways, iterative, consultative planning in flood-prone cities in India; vulnerable sustainable development and fair and equitable climate resilience, communities, municipal governmental agents, entrepreneurs and often focused on processes of power, learning and contestation as entry technical experts negotiate different visions, trade-offs and local politics points to more localised CRDPs (medium evidence, high agreement) to identify desirable pathways (Harris et al., 2017). (Cross-Chapter Box 13 in this chapter, Box 5.2). In the Scottish Borders Climate Resilient Communities Project (United Kingdom), local flood Transforming our societies and systems to limit global warming to management is linked with national policies to foster cross-scalar 1.5°C and ensuring equity and well-being for human populations and inclusive governance, with attention to systemic disadvantages, and ecosystems in a 1.5°C warmer world would require ambitious shocks and stressors, capacity building, learning for change and climate and well-integrated adaptation–mitigation–development pathways narratives to inspire hope and action, all of which are essential for that deviate fundamentally from high-carbon, business-as-usual community resilience in a 1.5°C warmer world (Fazey et al., 2018). futures (Okereke and Coventry, 2016; Arts, 2017; Gupta and Arts, Narratives and storytelling are vital for realizing place-based 1.5°C 2017; Sealey-Huggins, 2017). Identifying and negotiating socially futures as they create space for agency, deliberation, co-constructing acceptable, inclusive and equitable pathways towards climate- meaning, imagination and desirable and dignified pathways (Veland resilient futures is a challenging, yet important, endeavour, fraught et al., 2018). Engagement with possible futures, identity and self- with complex moral, practical and political difficulties and inevitable reliance is also documented for Alaska, where warming has already trade-offs (very high confidence). The ultimate questions are: what exceeded 1.5°C and indigenous communities invest in renewable futures do we want (Bai et al., 2016; Tàbara et al., 2017; Klinsky and energy, greenhouses for food security and new fishing practices to Winkler, 2018; O’Brien, 2018; Veland et al., 2018), whose resilience overcome loss of sea ice, flooding and erosion (Chapin et al., 2016; matters, for what, where, when and why (Meerow and Newell, 2016), Fazey et al., 2018). The Asian Cities Climate Change Resilience Network and ‘whose vision … is being pursued and along which pathways’ facilitates shared learning dialogues, risk-to-resilience workshops, and (Gillard et al., 2016). Cross-Chapter Box 13 | Cities and Urban Transformation Lead Authors: Fernando Aragon-Durand (Mexico), Paolo Bertoldi (Italy), Anton Cartwright (South Africa), François Engelbrecht (South Africa), Bronwyn Hayward (New Zealand), Daniela Jacob (Germany), Debora Ley (Guatemala/Mexico), Shagun Mehrotra (USA/India), Peter Newman (Australia), Aromar Revi (India), Seth Schultz (USA), William Solecki (USA), Petra Tschakert (Australia/Austria) Contributor: Peter Marcotullio (USA) Global Urbanization in a 1.5°C Warmer World The concentration of economic activity, dense social networks, human resource capacity, investment in infrastructure and buildings, relatively nimble local governments, close connection to surrounding rural and natural environments, and a tradition of innovation provide urban areas with transformational potential (see Chapter 4, Section 4.3.3) (Castán Broto, 2017). In this sense, the urbanization megatrend that will take place over the next three decades, and add approximately 2 billion people to the global urban population (UN, 2014), offers opportunities for efforts to limit warming to 1.5°C. 5 5 Cities can also, however, concentrate the risks of flooding, landslides, fire and infectious and parasitic disease that are expected to heighten in a 1.5°C warmer world (Chapter 3). In African and Asian countries where urbanization rates are highest, these risks could expose and amplify pre-existing stresses related to poverty, exclusion, and governance (Gore, 2015; Dodman et al., 2017; Jiang and O’Neill, 2017; Pelling et al., 2018; Solecki et al., 2018). Through its impact on economic development and investment, urbanization often leads to increased consumption and environmental degradation and enhanced vulnerability and risk (Rosenzweig et al., 2018). In the absence of innovation, the combination of urbanization and urban economic development could contribute 226 GtCO2 in emissions by 2050 (Bai et al., 2018). At the same time, some new urban developments are demonstrating combined carbon and Sustainable Development Goals (SDG) benefits (Wiktorowicz et al., 2018), and it is in towns and cities that building renovation rates can be most easily accelerated to support the transition to 1.5°C pathways (Kuramochi et al., 2018), including through voluntary programmes (Van der Heijden, 2018). Urban transformations and emerging climate-resilient development pathways The 1.5°C pathways require action in all cities and urban contexts. Recent literature emphasizes the need to deliberate and negotiate how resilience and climate-resilient pathways can be fostered in the context of people’s daily lives, including the failings of everyday development such as unemployment, inadequate housing and a growing informal sector and settlements (informality), in order 472 Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 Cross-Chapter Box 13 (continued) to acknowledge local priorities and foster transformative learning (Vale, 2014; Shi et al., 2016; Harris et al., 2017; Ziervogel et al., 2017; Fazey et al., 2018; Macintyre et al., 2018). Enhancing deliberate transformative capacities in urban contexts also entails new and relational forms of envisioning agency, equity, resilience, social cohesion and well-being (Section 5.5.3) (Gillard et al., 2016; Ziervogel et al., 2016). Two examples of urban transformation are explored here. The built environment, spatial planning, infrastructure, energy services, mobility and urban–rural linkages necessary in rapidly growing cities in South Asia and Africa in the next three decades present mitigation, adaptation and development opportunities that are crucial for a 1.5°C world (Newman et al., 2017; Lwasa et al., 2018; Teferi and Newman, 2018). Realizing these opportunities would require the structural challenges of poverty, weak and contested local governance, and low levels of local government investment to be addressed on an unprecedented scale (Wachsmuth et al., 2016; Chu et al., 2017; van Noorloos and Kloosterboer, 2017; Pelling et al., 2018). Urban governance is critical to ensuring that the necessary urban transitions deliver economic growth and equity (Hughes et al., 2018). The proximity of local governments to citizens and their needs can make them powerful agents of climate action (Melica et al., 2018), but urban governance is enhanced when it involves multiple actors (Ziervogel et al., 2016; Pelling et al., 2018), supportive national governments (Tait and Euston-Brown, 2017), and sub-national climate networks (see Chapter 4, Section 4.4.1). Governance is complicated for the urban population currently living in informality. This population is expected to triple, to three billion, by 2050 (Satterthwaite et al., 2018), placing a significant portion of the world’s population beyond the direct reach of formal climate mitigation and adaptation policies (Revi et al., 2014). How to address the co-evolved and structural conditions that lead to urban informality and associated vulnerability to 1.5°C of warming is a central question for this report. Brown and McGranahan (2016) cite evidence that the informal urban ‘green economy’ that has emerged out of necessity in the absence of formal service provisions is frequently low-carbon and resource-efficient. Realising the potential for low carbon transitions in informal urban settlements would require an express recognition of the unpaid- for contributions of women in the informal economy, and new partnerships between the state and communities (Ziervogel et al., 2017; Pelling et al., 2018; Satterthwaite et al., 2018). There is no guarantee that these partnerships will evolve or cohere into the type of service delivery and climate governance system that could steer the change on a scale required to limit to warming to 1.5°C (Jaglin, 2014). However, work by transnational networks, such as Shack/Slum Dwellers International, C40, the Global Covenant of Mayors, and the International Council for Local Environmental Initiatives, as well as efforts to combine in-country planning for Nationally Determined Contributions (NDCs) (Andonova et al., 2017; Fuhr et al., 2018) with those taking place to support the New Urban Agenda and National Urban Policies, represent one step towards realizing the potential (Tait and Euston-Brown, 2017). So too do ‘old urban agendas’, such as slum upgrading and universal water and sanitation provision (McGranahan et al., 2016; Satterthwaite, 2016; Satterthwaite et al., 2018). Transition Towns (TTs) are a type of urban transformation that have emerged mainly in high-income countries. The grassroots TT movement (origin in the United Kingdom) combines adaptation, mitigation and just transitions, mainly at the level of communities 5 and small towns. It now has more than 1,300 registered local initiatives in more than 40 countries (Grossmann and Creamer, 5 2017), many of them in the United Kingdom, the United States, and other high-income countries. TTs are described as ‘progressive localism’ (Cretney et al., 2016), aiming to foster a ‘communitarian ecological citizenship’ that goes beyond changes in consumption and lifestyle (Kenis, 2016). They aspire to promote equitable communities resilient to the impacts of climate change, peak oil and unstable global markets; re-localization of production and consumption; and transition pathways to a post-carbon future (Feola and Nunes, 2014; Evans and Phelan, 2016; Grossmann and Creamer, 2017). TT initiatives typically pursue lifestyle-related low-carbon living and economies, food self-sufficiency, energy efficiency through renewables, construction with locally sourced material and cottage industries (Barnes, 2015; Staggenborg and Ogrodnik, 2015; Taylor Aiken, 2016). Social and iterative learning through the collective involves dialogue, deliberation, capacity building, citizen science engagements, technical re-skilling to increase self-reliance, for example canning and preserving food and permaculture, future visioning and emotional training to share difficulties and loss (Feola and Nunes, 2014; Barnes, 2015; Boke, 2015; Taylor Aiken, 2015; Kenis, 2016; Mehmood, 2016; Grossmann and Creamer, 2017). Important conditions for successful transition groups include flexibility, participatory democracy, care ethics, inclusiveness and consensus-building, assuming bridging or brokering roles, and community alliances and partnerships (Feola and Nunes, 2014; Mehmood, 2016; Taylor Aiken, 2016; Grossmann and Creamer, 2017). Smaller scale rural initiatives allow for more experimentation 473 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities Cross-Chapter Box 13 (continued) (Cretney et al., 2016), while those in urban centres benefit from stronger networks and proximity to power structures (North and Longhurst, 2013; Nicolosi and Feola, 2016). Increasingly, TTs recognize the need to participate in policymaking (Kenis and Mathijs, 2014; Barnes, 2015). Despite high self-ratings of success, some TT initiatives are too inwardly focused and geographically isolated (Feola and Nunes, 2014), while others have difficulties in engaging marginalized, non-white, non-middle-class community members (Evans and Phelan, 2016; Nicolosi and Feola, 2016; Grossmann and Creamer, 2017). In the United Kingdom, expectations of innovations growing in scale (Taylor Aiken, 2015) and carbon accounting methods required by funding bodies (Taylor Aiken, 2016) undermine local resilience building. Tension between explicit engagements with climate change action and efforts to appeal to more people have resulted in difficult trade-offs and strained member relations (Grossmann and Creamer, 2017) though the contribution to changing an urban culture that prioritizes climate change is sometimes underestimated (Wiktorowicz et al., 2018). Urban actions that can highlight the 1.5°C agenda include individual actions within homes (Werfel, 2017; Buntaine and Prather, 2018); demonstration zero carbon developments (Wiktorowicz et al., 2018); new partnerships between communities, government and business to build mass transit and electrify transport (Glazebrook and Newman, 2018); city plans to include climate outcomes (Millard-Ball, 2013); and support for transformative change across political, professional and sectoral divides (Bai et al., 2018). shown positive effects on sustainable development but also adverse 5.6 Conditions for Achieving Sustainable consequences, for example, on adaptive capacities of rural households Development, Eradicating Poverty and uneven distribution of costs and benefits, often exacerbating and Reducing Inequalities in inequalities (robust evidence, high agreement) (Aggarwal, 2014; 1.5°C Warmer Worlds Brohé, 2014; He et al., 2014; Schade and Obergassel, 2014; Smits and Middleton, 2014; Wood et al., 2016a; Horstmann and Hein, 2017; This chapter has described the fundamental, urgent and systemic Kreibich et al., 2017). Close consideration of recipients’ context- transformations that would be needed to achieve sustainable specific needs when designing financial support helps to overcome development, eradicate poverty and reduce inequalities in a 1.5°C these limitations as it better aligns community needs, national policy warmer world, in various contexts and across scales. In particular, it objectives and donors’ priorities; puts the emphasis on the increase of has highlighted the societal dimensions, putting at the centre people’s transparency and predictability of support; and fosters local capacity needs and aspirations in their specific contexts. Here we synthesize building (medium evidence, high agreement) (Barrett, 2013; Boyle et some of the most pertinent enabling conditions (see Glossary) to al., 2013; Shine and Campillo, 2016; Ley, 2017; Sánchez and Izzo, 2017). support these profound transformations. These conditions are closely interlinked and connected by the overarching concept of governance, The development and transfer of technologies is another enabler for which broadly includes institutional, socio-economic, cultural and developing countries to contribute to the requirements of the 1.5°C technological elements (see Chapter 1, Cross-Chapter Box 4 in objective while achieving climate resilience and their socio-economic Chapter 1). development goals (see Chapter 4, Section 4.4.4). International- 5 level governance would be needed to boost domestic innovation 5 5.6.1 Finance and Technology Aligned with Local Needs and the deployment of new technologies, such as negative emission technologies, towards the 1.5°C objective (see Chapter 4, Section 4.3.7), Significant gaps in green investment constrain transitions to a low- but the alignment with local needs depends on close consideration carbon economy aligned with development objectives (Volz et al., of the specificities of the domestic context in countries at all levels 2015; Campiglio, 2016). Hence, unlocking new forms of public, private of development (de Coninck and Sagar, 2015; IEA, 2015; Parikh et al., and public–private financing is essential to support environmental 2018). Technology transfer supporting development in developing sustainability of the economic system (Croce et al., 2011; Blyth et al., countries would require an understanding of local and national actors 2015; Falcone et al., 2018) (see Chapter 4, Section 4.4.5). To avoid risks and institutions (de Coninck and Puig, 2015; de Coninck and Sagar, of undesirable trade-offs with the SDGs caused by national budget 2017; Michaelowa et al., 2018), careful attention to the capacities in constraints, improved access to international climate finance is essential the entire innovation chain (Khosla et al., 2017; Olawuyi, 2017) and for supporting adaptation, mitigation and sustainable development, transfer of not only equipment but also knowledge (medium evidence, especially for LDCs and SIDS (medium evidence, high agreement) high agreement) (Murphy et al., 2015). (Shine and Campillo, 2016; Wood, 2017). Care needs to be taken when international donors or partnership arrangements influence project 5.6.2 Integration of Institutions financing structures (Kongsager and Corbera, 2015; Purdon, 2015; Phillips et al., 2017; Ficklin et al., 2018). Conventional climate funding Multilevel governance in climate change has emerged as a key enabler schemes, especially the Clean Development Mechanism (CDM), have for systemic transformation and effective governance (see Chapter 4, 474 Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 Section 4.4.1). On the one hand, low-carbon and climate-resilient al., 2014; Fazey et al., 2016; Tschakert et al., 2016; Winkler and Dubash, development actions are often well aligned at the lowest scale 2016; Wood et al., 2016b; Karlsson et al., 2017; Quan et al., 2017; possible (Suckall et al., 2015; Sánchez and Izzo, 2017), and informal, Tanner et al., 2017). Each development pathway, including legacies and local institutions are critical in enhancing the adaptive capacity path dependencies, creates its own set of opportunities and challenges of countries and marginalized communities (Yaro et al., 2015). On and winners and losers, both within and across countries (Figure 5.5) the other hand, international and national institutions can provide (robust evidence, high agreement) (Mathur et al., 2014; Phillips et al., incentives for projects to harness synergies and avoid trade-offs 2017; Stringer et al., 2017; Wood, 2017; Ficklin et al., 2018; Gajjar et (Kongsager et al., 2016). al., 2018). Governance approaches that coordinate and monitor multiscale Addressing the uneven distribution of power is critical to ensure policy actions and trade-offs across sectoral, local, national, regional that societal transformation towards a 1.5°C warmer world does and international levels are therefore best suited to implement goals not exacerbate poverty and vulnerability or create new injustices but towards 1.5°C warmer conditions and sustainable development (Ayers rather encourages equitable transformational change (Patterson et et al., 2014; Stringer et al., 2014; von Stechow et al., 2016; Gwimbi, al., 2018). Equitable outcomes are enhanced when they pay attention 2017; Hayward, 2017; Maor et al., 2017; Roger et al., 2017; Michaelowa to just outcomes for those negatively affected by change (Newell et et al., 2018). Vertical and horizontal policy integration and coordination al., 2014; Dilling et al., 2015; Naess et al., 2015; Sovacool et al., 2015; is essential to take into account the interplay and trade-offs between Cervigni and Morris, 2016; Keohane and Victor, 2016) and promote sectors and spatial scales (Duguma et al., 2014; Naess et al., 2015; von human rights, increase equality and reduce power asymmetries within Stechow et al., 2015; Antwi-Agyei et al., 2017a; Di Gregorio et al., 2017; societies (robust evidence, high agreement) (UNRISD, 2016; Robinson Runhaar et al., 2018), enable the dialogue between local communities and Shine, 2018). and institutional bodies (Colenbrander et al., 2016), and involve non- state actors such as business, local governments and civil society 5.6.5 Reconsidering Values operating across different scales (robust evidence, high agreement) (Hajer et al., 2015; Labriet et al., 2015; Hale, 2016; Pelling et al., 2016; The profound transformations that would be needed to integrate Kalafatis, 2017; Lyon, 2018). sustainable development and 1.5°C-compatible pathways call for examining the values, ethics, attitudes and behaviours that underpin 5.6.3 Inclusive Processes societies (Hartzell-Nichols, 2017; O’Brien, 2018; Patterson et al., 2018). Infusing values that promote sustainable development (Holden et al., Inclusive governance processes are critical for preparing for a 1.5°C 2017), overcome individual economic interests and go beyond economic warmer world (Fazey et al., 2018; O’Brien, 2018; Patterson et al., 2018). growth (Hackmann, 2016), encourage desirable and transformative These processes have been shown to serve the interests of diverse visions (Tàbara et al., 2018), and care for the less fortunate (Howell groups of people and enhance empowerment of often excluded and Allen, 2017) is part and parcel of climate-resilient and sustainable stakeholders, notably women and youth (MRFCJ, 2015a; Dumont et development pathways. This entails helping societies and individuals al., 2017). They also enhance social- and co-learning which, in turn, to strive for sufficiency in resource consumption within planetary facilitates accelerated and adaptive management and the scaling up boundaries alongside sustainable and equitable well-being (O’Neill of capacities for resilience building (Ensor and Harvey, 2015; Reij and et al., 2018). Navigating 1.5°C societal transformations, characterized Winterbottom, 2015; Tschakert et al., 2016; Binam et al., 2017; Dumont by action from local to global, stresses the core commitment to et al., 2017; Fazey et al., 2018; Lyon, 2018; O’Brien, 2018), and provides social justice, solidarity and cooperation, particularly regarding the opportunities to blend indigenous, local and scientific knowledge distribution of responsibilities, rights and mutual obligations between 5 (robust evidence, high agreement) (see Chapter 4, Section 4.3.5.5, nations (medium evidence, high agreement) (Patterson et al., 2018; 5 Box 4.3, Section 5.3) (Antwi-Agyei et al., 2017a; Coe et al., 2017; Robinson and Shine, 2018). Thornton and Comberti, 2017) . Such co-learning has been effective in improving deliberative decision-making processes that incorporate different values and world views (Cundill et al., 2014; C. Butler et al., 2016; Ensor, 2016; Fazey et al., 2016; Gorddard et al., 2016; Aipira et 5.7 Synthesis and Research Gaps al., 2017; Chung Tiam Fook, 2017; Maor et al., 2017), and create space for negotiating diverse interests and preferences (robust evidence, high The assessment in Chapter 5 illustrates that limiting global warming agreement) (O’Brien et al., 2015; Gillard et al., 2016; DeCaro et al., to 1.5°C above pre-industrial levels is fundamentally connected with 2017; Harris et al., 2017; Lahn, 2018). achieving sustainable development, poverty eradication and reducing inequalities. It shows that avoided impacts between 1.5°C and 2°C 5.6.4 Attention to Issues of Power and Inequality temperature stabilization would make it easier to achieve many aspects of sustainable development, although important risks would remain Societal transformations to limit global warming to 1.5°C and strive at 1.5°C (Section 5.2). Synergies between adaptation and mitigation for equity and well-being for all are not power neutral (Section 5.5.3). response measures with sustainable development and the SDGs can Development preferences are often shaped by powerful interests that often be enhanced when attention is paid to well-being and equity determine the direction and pace of change, anticipated benefits and while, when unaddressed, poverty and inequalities may be exacerbated beneficiaries, and acceptable and unacceptable trade-offs (Newell et (Section 5.3 and 5.4). Climate-resilient development pathways (CRDPs) 475 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities open up routes towards socially desirable futures that are sustainable hampers the ability to inform decision-making and fair and robust policy and liveable, but concrete evidence reveals complex trade-offs along packages adapted to different local, regional or national circumstances. a continuum of different pathways, highlighting the role of societal More research is required to understand how trade-offs and synergies values, internal contestations and political dynamics (Section 5.5). The will intensify or decrease, differentially across geographic regions and transformations towards sustainable development in a 1.5°C warmer time, in a 1.5°C warmer world and as compared to higher temperatures. world, in all contexts, involve fundamental societal and systemic changes over time and across scale, and a set of enabling conditions Limited availability of interdisciplinary studies also poses a challenge without which the dual goal is difficult if not impossible to achieve for connecting the socio-economic transformations and the governance (Sections 5.5 and 5.6). aspects of low emissions, climate-resilient transformations. For example, it remains unclear how governance structures enable or This assessment is supported by growing knowledge on the linkages hinder different groups of people and countries to negotiate pathway between a 1.5°C warmer world and different dimensions of sustainable options, values and priorities. development. However, several gaps in the literature remain: The literature does not demonstrate the existence of 1.5°C-compatible Limited evidence exists that explicitly examines the real-world pathways achieving the ‘universal and indivisible’ agenda of the implications of a 1.5°C warmer world (and overshoots) as well as 17 SDGs, and hence does not show whether and how the nature avoided impacts between 1.5°C versus 2°C for the SDGs and sustainable and pace of changes that would be required to meet 1.5°C climate development more broadly. Few projections are available for stabilization could be fully synergetic with all the SDGs. households, livelihoods and communities. And literature on differential localized impacts and their cross-sector interacting and cascading The literature on low emissions and CRDPs in local, regional and national effects with multidimensional patterns of societal vulnerability, poverty contexts is growing. Yet the lack of standard indicators to monitor such and inequalities remains scarce. Hence, caution is needed when global- pathways makes it difficult to compare evidence grounded in specific level conclusions about adaptation and mitigation measures in a 1.5°C contexts with differential circumstances, and therefore to derive warmer world are applied to sustainable development in local, national generic lessons on the outcome of decisions on specific indicators. This and regional settings. knowledge gap poses a challenge for connecting local-level visions with global-level trajectories to better understand key conditions for Limited literature has systematically evaluated context-specific societal and systems transformations that reconcile urgent climate synergies and trade-offs between and across adaptation and mitigation action with well-being for all. response measures in 1.5°C-compatible pathways and the SDGs. This 5 5 476 Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 Frequently Asked Questions FAQ 5.1 | What are the Connections between Sustainable Development and Limiting Global Warming to 1.5°C above Pre-Industrial Levels? Summary: Sustainable development seeks to meet the needs of people living today without compromising the needs of future generations, while balancing social, economic and environmental considerations. The 17 UN Sustainable Development Goals (SDGs) include targets for eradicating poverty; ensuring health, energy and food security; reducing inequality; protecting ecosystems; pursuing sustainable cities and economies; and a goal for climate action (SDG 13). Climate change affects the ability to achieve sustainable development goals, and limiting warming to 1.5°C will help meet some sustainable development targets. Pursuing sustainable development will influence emissions, impacts and vulnerabilities. Responses to climate change in the form of adaptation and mitigation will also interact with sustainable development with positive effects, known as synergies, or negative effects, known as trade-offs. Responses to climate change can be planned to maximize synergies and limit trade- offs with sustainable development. For more than 25 years, the United Nations (UN) and other international organizations have embraced the concept of sustainable development to promote well-being and meet the needs of today’s population without compromising the needs of future generations. This concept spans economic, social and environmental objectives including poverty and hunger alleviation, equitable economic growth, access to resources, and the protection of water, air and ecosystems. Between 1990 and 2015, the UN monitored a set of eight Millennium Development Goals (MDGs). They reported progress in reducing poverty, easing hunger and child mortality, and improving access to clean water and sanitation. But with millions remaining in poor health, living in poverty and facing serious problems associated with climate change, pollution and land-use change, the UN decided that more needed to be done. In 2015, the UN Sustainable Development Goals (SDGs) were endorsed as part of the 2030 Agenda for Sustainable Development. The 17 SDGs (Figure FAQ 5.1) apply to all countries and have a timeline for success by 2030. The SDGs seek to eliminate extreme poverty and hunger; ensure health, education, peace, safe water and clean energy for all; promote inclusive and sustainable consumption, cities, infrastructure and economic growth; reduce inequality including gender inequality; combat climate change and protect oceans and terrestrial ecosystems. Climate change and sustainable development are fundamentally connected. Previous IPCC reports found that climate change can undermine sustainable development, and that well-designed mitigation and adaptation responses can support poverty alleviation, food security, healthy ecosystems, equality and other dimensions of sustainable development. Limiting global warming to 1.5°C would require mitigation actions and adaptation measures to be taken at all levels. These adaptation and mitigation actions would include reducing emissions and increasing resilience through technology and infrastructure choices, as well as changing behaviour and policy. These actions can interact with sustainable development objectives in positive ways that strengthen sustainable development, known as synergies. Or they can interact in negative ways, where sustainable development is 5 hindered or reversed, known as trade-offs. 5 An example of a synergy is sustainable forest management, which can prevent emissions from deforestation and take up carbon to reduce warming at reasonable cost. It can work synergistically with other dimensions of sustainable development by providing food (SDG 2) and clean water (SDG 6) and protecting ecosystems (SDG 15). Other examples of synergies are when climate adaptation measures, such as coastal or agricultural projects, empower women and benefit local incomes, health and ecosystems. An example of a trade-off can occur if ambitious climate change mitigation compatible with 1.5°C changes land use in ways that have negative impacts on sustainable development. An example could be turning natural forests, agricultural areas, or land under indigenous or local ownership to plantations for bioenergy production. If not managed carefully, such changes could undermine dimensions of sustainable development by threatening food and water security, creating conflict over land rights and causing biodiversity loss. Another trade-off could occur for some countries, assets, workers and infrastructure already in place if a switch is made from fossil fuels to other energy sources without adequate planning for such a transition. Trade-offs can be minimized if effectively managed, as when care is taken to improve bioenergy crop yields to reduce harmful land-use change or where workers are retrained for employment in lower carbon sectors. (continued on next page) 477 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities FAQ 5.1 (continued) Limiting temperature increase to 1.5°C can make it much easier to achieve the SDGs, but it is also possible that pursuing the SDGs could result in trade-offs with efforts to limit climate change. There are trade-offs when people escaping from poverty and hunger consume more energy or land and thus increase emissions, or if goals for economic growth and industrialization increase fossil fuel consumption and greenhouse gas emissions. Conversely, efforts to reduce poverty and gender inequalities and to enhance food, health and water security can reduce vulnerability to climate change. Other synergies can occur when coastal and ocean ecosystem protection reduces the impacts of climate change on these systems. The sustainable development goal of affordable and clean energy (SDG 7) specifically targets access to renewable energy and energy efficiency, which are important to ambitious mitigation and limiting warming to 1.5°C. The link between sustainable development and limiting global warming to 1.5°C is recognized by the SDG for climate action (SDG 13), which seeks to combat climate change and its impacts while acknowledging that the United Nations Framework Convention on Climate Change (UNFCCC) is the primary international, intergovernmental forum for negotiating the global response to climate change. The challenge is to put in place sustainable development policies and actions that reduce deprivation, alleviate poverty and ease ecosystem degradation while also lowering emissions, reducing climate change impacts and facilitating adaptation. It is important to strengthen synergies and minimize trade-offs when planning climate change adaptation and mitigation actions. Unfortunately, not all trade-offs can be avoided or minimized, but careful planning and implementation can build the enabling conditions for long-term sustainable development. 5 5 FAQ 5.1, Figure 1 | Climate change action is one of the United Nations Sustainable Development Goals (SDGs) and is connected to sustainable development more broadly. Actions to reduce climate risk can interact with other sustainable development objectives in positive ways (synergies) and negative ways (trade-offs). 478 Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 Frequently Asked Questions FAQ 5.2 | What are the Pathways to Achieving Poverty Reduction and Reducing Inequalities while Reaching a 1.5°C World? Summary: There are ways to limit global warming to 1.5°C above pre-industrial levels. Of the pathways that exist, some simultaneously achieve sustainable development. They entail a mix of measures that lower emissions and reduce the impacts of climate change, while contributing to poverty eradication and reducing inequalities. Which pathways are possible and desirable will differ between and within regions and nations. This is due to the fact that development progress to date has been uneven and climate-related risks are unevenly distributed. Flexible governance would be needed to ensure that such pathways are inclusive, fair and equitable to avoid poor and disadvantaged populations becoming worse off. Climate-resilient development pathways (CRDPs) offer possibilities to achieve both equitable and low-carbon futures. Issues of equity and fairness have long been central to climate change and sustainable development. Equity, like equality, aims to promote justness and fairness for all. This is not necessarily the same as treating everyone equally, since not everyone comes from the same starting point. Often used interchangeably with fairness and justice, equity implies implementing different actions in different places, all with a view to creating an equal world that is fair for all and where no one is left behind. The Paris Agreement states that it ‘will be implemented to reflect equity… in the light of different national circumstances’ and calls for ‘rapid reductions’ of greenhouse gases to be achieved ‘on the basis of equity, and in the context of sustainable development and efforts to eradicate poverty’. Similarly, the UN SDGs include targets to reduce poverty and inequalities, and to ensure equitable and affordable access to health, water and energy for all. Equity and fairness are important for considering pathways that limit warming to 1.5°C in a way that is liveable for every person and species. They recognize the uneven development status between richer and poorer nations, the uneven distribution of climate impacts (including on future generations) and the uneven capacity of different nations and people to respond to climate risks. This is particularly true for those who are highly vulnerable to climate change, such as indigenous communities in the Arctic, people whose livelihoods depend on agriculture or coastal and marine ecosystems, and inhabitants of small island developing states. The poorest people will continue to experience climate change through the loss of income and livelihood opportunities, hunger, adverse health effects and displacement. Well-planned adaptation and mitigation measures are essential to avoid exacerbating inequalities or creating new injustices. Pathways that are compatible with limiting warming to 1.5°C and aligned with the SDGs consider mitigation and adaptation options that reduce inequalities in terms of who benefits, who pays the costs and who is affected by possible negative consequences. Attention to equity ensures that disadvantaged people can secure their livelihoods and live in dignity, and that those who experience mitigation or adaptation costs have financial and technical support to enable fair transitions. 5 CRDPs describe trajectories that pursue the dual goal of limiting warming to 1.5°C while strengthening sustainable 5 development. This includes eradicating poverty as well as reducing vulnerabilities and inequalities for regions, countries, communities, businesses and cities. These trajectories entail a mix of adaptation and mitigation measures consistent with profound societal and systems transformations. The goals are to meet the short-term SDGs, achieve longer-term sustainable development, reduce emissions towards net zero around the middle of the century, build resilience and enhance human capacities to adapt, all while paying close attention to equity and well-being for all. The characteristics of CRDPs will differ across communities and nations, and will be based on deliberations with a diverse range of people, including those most affected by climate change and by possible routes towards transformation. For this reason, there are no standard methods for designing CRDPs or for monitoring their progress towards climate-resilient futures. However, examples from around the world demonstrate that flexible and inclusive governance structures and broad participation often help support iterative decision-making, continuous learning and experimentation. Such inclusive processes can also help to overcome weak institutional arrangements and power structures that may further exacerbate inequalities. (continued on next page) 479 Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities FAQ 5.2 (continued) FAQ 5.2, Figure 1 | Climate-resilient development pathways (CRDPs) describe trajectories that pursue the dual goals of limiting warming to 1.5°C while strengthening sustainable development. Decision-making that achieves the SDGs, lowers greenhouse gas emissions and limits global warming could help lead to a climate-resilient world, within the context of enhancing adaptation. Ambitious actions already underway around the world can offer insight into CRDPs for limiting warming to 1.5°C. For example, some countries have adopted clean energy and sustainable transport while creating environmentally friendly jobs and supporting social welfare programmes to reduce domestic poverty. Other examples teach us about different ways to promote development through practices inspired by community values. For instance, Buen Vivir, a Latin American concept based on indigenous ideas of communities living in harmony with nature, is aligned with peace; diversity; solidarity; rights to education, health, and safe food, water, and energy; and well-being and justice for all. The Transition Movement, with origins in Europe, promotes equitable and resilient communities through low-carbon living, food self-sufficiency and citizen science. Such examples indicate that pathways that reduce poverty and inequalities while limiting warming to 1.5°C are possible and that they can provide guidance on pathways towards socially desirable, equitable and low-carbon futures. 5 5 480 Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 5 5 481 Table 5.2 | Mitigation – SDG table Social-Demand Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Reduces Poverty Air, Water Pollution Reduction and Better Health (3.9) Technical Education, Vocational Training, Education for Sustainability (4.3/4.4/4.5/4.7) ↑ [+2]    [0] ↑  [+2]    ↑  [+1]    % of people living below poverty line declines from 49% to 18% in People living in deprived communities feel positive and predict Awareness, knowledge, technical and managerial capability are closely South African context. considerable financial savings. Efficiency changes in the industrial sector linked, energy audit, information for trade unions, product/appliance that lead to reduced energy demand can lead to reduced requirements labeling help in sustainability education. on energy supply. As water is used to convert energy into useful forms, the reduction in industrial demand is anticipated to reduce water consumption and wastewater, resulting in more clean water for other No direct interaction sectors and the environment. In extractive industries there are trade-off unless strategically managed. Behavioural changes in the industrial sector that lead to reduced energy demand can lead to reduced requirements on energy supply. As water is used to convert energy into useful forms, the reduction in industrial demand is anticipated to reduce water consumption and wastewater, resulting in more clean water for other sectors and the environment. Altieri et al., 2016 Vassolo and Döll, 2005; Xi et al., 2013; Nguyen et al., 2014; Holland et Apeaning and Thollander, 2013; Fernando and Evans, 2015; Roy et al., al., 2015; Zhang et al., 2015; Fricko et al., 2016 2018 Water and Air Pollution Reduction and Better Health (3.9) Technical Education, Vocational Training, Education for Sustainability (4.b/4.7)   [0] [0] ↑  [+2]    ↑  [+1]    Industries are becoming suppliers of energy, waste heat, water and roof New technology deployment creates demand for awareness and No direct interaction No direct interaction tops for solar energy generation, and hence helping to improve air and knowledge with technical and managerial capability; otherwise acts as water quality. barrier for rapid expansion. Vassolo and Döll, 2005; Nguyen et al., 2014; Holland et al., 2015; Apeaning and Thollander, 2013; Fernando and Evans, 2015; Roy et al., Karner et al., 2015; Fricko et al., 2016 2018 Disease and Mortality (3.1/3.2/3.3/3.4)   [0]   [0] ↓ [‐1]      [0] There is a risk of CO2 leakage both from geological formations as well No direct interaction No direct interaction as from the transportation infrastructure from source to sequestration No direct interaction locations. Wang and Jaffe, 2004; Hertwich et al., 2008; Apps et al., 2010; Veltman et al., 2010; Koornneef et al., 2011; Singh et al., 2011; Siirila et al., 2012; Atchley et al., 2013; Corsten et al., 2013; IPCC, 2014 I n d u s t r y D e c a r b o n i z a t i o n / C C S / C C U L o w - c a r b o n F u e l S w i t c h A c c e l e r a t i n g E n e r g y E f f i c i e n c y I m p r o v e m e n t Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities 5 5 482 Social-Demand (continued) Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Poverty Reduction via Financial Savings (1.1) Improved Warmth and Comforts ↑  [+2]      [0] ↑  [+2]      [0] People living in deprived communities feel positive and predict Home occupants reported warmth as the most important aspect of considerable financial savings. comfort which was largely temperature-related and low in energy costs. No direct interaction Residents living in deprived areas expect improved warmth in their No direct interaction properties after energy efficiency measures are employed. Scott et al., 2014 Huebner et al., 2013; Yue et al., 2013; Scott et al., 2014; Zhao et al., 2017 Poverty and Development (1.1/1.2/1.3/1.4) Food Security (2.1) Healthy Lives and Well-being for All at All Ages (3.2/3.9) Equal Access to Educational Institutions (4.1/4.2/4.3/4.5) ↑ / ↓ [+2,‐1]    ↑  [+2] ↑  [+2]      ↑  [+2]     Energy efficiency interventions lead to cost savings which are realized Using the improved stoves supports local food security and has Efficient stoves improve health, especially for indigenous and poor rural Household energy efficiency measures reduce school absences for due to reduced energy bills that further lead to poverty reduction. significantly impacted on food security. By making fuel last longer, the communities. Household energy efficiency has positive health impacts children with asthma due to indoor pollution. Participants with low incomes experience greater benefits. 'Energy improved stoves help improve food security and also provide a better on children’s respiratory health, weight and susceptibility to illness, and efficiency and biomass strategies benefitted the poor more than wind buffer against fuel shortages induced by climate change-related events the mental health of adults. Household energy efficiency improves and solar, whose benefits are captured by industry. Carbon mitigation such as droughts, floods or hurricanes (Berrueta et al. 2017). winter warmth, lowers relative humidity with benefits for cardiovascular can increase or decrease inequalities. The distributional costs of new and respiratory health. Further improved indoor air quality by thermal energy policies (e.g., supporting renewables and energy efficiency) are regulation and occupant comfort are realised. However, in one instance, dependent on instrument design. If costs fall disproportionately on the negative health impacts (asthma) of increased household energy poor, then this could impair progress towards universal energy access efficiency were also noted when housing upgrades took place without and, by extension, counteract the fight to eliminate poverty. (Quote from changes in occupant behaviours. Home occupants reported warmth as McCollum et al., 2018). the most important aspect of comfort which was largely temperature- related and low in energy costs. Residents living in the deprived areas expect improved warmth in their properties after energy efficiency measures are employed. Casillas and Kammen, 2012; Hirth and Ueckerdt, 2013; Jakob and Berrueta et al., 2017 Djamila et al., 2013; Huebner et al., 2013; Yue et al., 2013; Bhojvaid et Maidment et al., 2014 Steckel, 2014; Maidment et al., 2014; Scott et al., 2014; Fay et al., al., 2014; Derbez et al., 2014; Maidment et al., 2014; Scott et al., 2014; 2015; Cameron et al., 2016; Hallegatte et al., 2016b; Berrueta et al., Cameron et al., 2015; Liddell and Guiney, 2015; Sharpe et al., 2015; 2017; McCollum et al., 2018 Wells et al., 2015; Willand et al., 2015; Berrueta et al., 2017; Zhao et al., 2017 Poverty and Development (1.1/1.2/1.3/1.4) Food Security and Agricultural Productivity (2.1/2.4) Disease and Mortality (3.1/3.2/3.3/3.4) Equal Access to Educational Institutions (4.1/4.2/4.3/4.5) ↑  [+2]    ~  / ↓ [0,‐1]    ↑ [+2]    ↑ [+1]    Access to modern energy forms (electricity, clean stoves, high-quality Modern energy access is critical to enhance agricultural Access to modern energy services can contribute to fewer injuries and Access to modern energy is necessary for schools to have quality lighting) is fundamental to human development since the energy yields/productivity, decrease post-harvest losses and mechanize agri- diseases related to traditional solid fuel collection and burning, as well lighting and thermal comfort, as well as modern information and services made possible by them help alleviate chronic and persistent processing – all of which can aid food security. However, large-scale as utilization of kerosene lanterns. Access to modern energy services communication technologies. Access to modern lighting and energy poverty. Strength of the impact varies in the literature. (Quote from bioenergy and food production may compete for scarce land and other can facilitate improved health care provision, medicine and vaccine allows for studying after sundown and frees constraints on time McCollum et al., 2018) inputs (e.g., water, fertilizers), depending on how and where biomass storage, utilization of powered medical equipment, and dissemination of management that allow for higher school enrolment rates and better supplies are grown and the indirect land use change impacts that result. health-related information and education. Such services can also enable literacy outcomes. (Quote from McCollum et al., 2018) If not implemented thoughtfully, this could lead to higher food prices thermal comfort in homes and contribute to food preservation and globally, and thus reduce access to affordable food for the poor. safety. (Quote from McCollum et al., 2018) Enhanced agricultural productivities can ameliorate the situation by allowing as much bioenergy to be produced on as little land as possible. Kirubi et al., 2009; Casillas and Kammen, 2010; Cook, 2011; Pachauri et Cabraal et al., 2005; Tilman et al., 2009; van Vuuren et al., 2009; Lam et al., 2012; Lim et al., 2012; Smith et al., 2013; Aranda et al., Lipscomb et al., 2013; van de Walle et al., 2013; McCollum et al., 2018 al., 2012; Pode, 2013; Pueyo et al., 2013; Zulu and Richardson, 2013; Asaduzzaman et al., 2010; Finco and Doppler, 2010; Msangi et al., 2014; McCollum et al., 2018 Bonan et al., 2014; Rao et al., 2014; Burlig and Preonas, 2016; 2010; Smith et al., 2013, 2014; Lotze-Campen et al., 2014; Hasegawa et McCollum et al., 2018 al., 2015; Sola et al., 2016; McCollum et al., 2018 B u i l d i n g s I m p r o v e d A c c e s s a n d F u e l S w i t c h t o M o d e r n L o w - A c c e l e r a t i n g E n e r g y E f f i c i e n c y I m p r o v e m e n t B e h a v i o u r a l R e s p o n s e c a r b o n E n e r g y Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 5 5 483 Social-Demand (continued) Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Equal Right to Economic Resources Access Basic Services Ensure Access to Safe Nutritious Food (2.1/2.2) Road Traffic Accidents (3.4/3.6) Equal Safe Access to Educational Institutions (4.1/4.2/4.3/4.5) (1.1/1.4/1.a/1.b) ↑ / ↓ [+2,‐1]    ↑  [+2]    ↑ / ↓ [+2,‐1]    ↑ [+1]    The costs of daily mobility can have important economic stress impacts, Low-income community residents (non-white) who lack local access to Active travel modes, such as walking and cycling, represent strategies Poor road quality affects school travel safety, so collaborative efforts not only impacting carless families with low-mobility, but in countries affordable, quality sources of nutrition have to travel outside their not only for boosting energy efficiency but also, potentially, for need to address safety issues from a dual perspective, first by working with high immediate neighbourhood to find better sources of food to feed improving health and well-being (e.g., lowering rates of diabetes, to change the existing infrastructure and use of roads to better address levels of car dependence, the costs of motoring can be burdensome, themselves and their families. Lack of locally available healthy food obesity, heart disease, dementia and some cancers). However, a risk the traffic problems that children currently face walking to school, and raising questions of affordability for households with limited economic often exacerbates the rates of obesity in many of these communities associated with these measures is that they could increase rates of road then to better situate schools and control the roadways and land uses resources. During economic crisis, public transport authorities may react since it is often difficult or expensive to travel long distances on a traffic accidents, if the existing infrastructure is unsatisfactory. Overall around them in the future. by reducing levels of service and increasing fares, likely exacerbating the regular basis to shop for food. health effects will depend on the severity of the injuries sustained from situation for low-income households. these potential accidents relative to the health benefits accruing from increased exercise (McCollum et al., 2018). Dodson et al., 2004; Cascajo et al., 2017 Clifton, 2004; Hillier, 2011; Krukowski et al., 2013; LeDoux and Woodcock et al., 2009; Creutzig et al., 2012; Haines and Dora, 2012; Yu, 2015 Vojnovic, 2013; Ghosh-Dastidar et al., 2014; Zenk et al., 2015; Lowery Saunders et al., 2013; Shaw et al., 2014, 2017; Chakrabarti and Shin, et al., 2016 2017; Hwang et al., 2017; McCollum et al., 2018 End Poverty in all its Forms Everywhere (1.1/1.4/1.a/1.b) Reduce Illnesses from Hazardous Air, Water and Soil Pollution (3.9) ↑ / ↓ [+2,‐1]    [0] ↑  [+2]    [0] Decarbonization of public buses in Sweden is receiving attention more Locally relevant policies targeting traffic reductions and ambitious than efficiency improvement. With more electrification, electricity prices diffusion of electric vehicles results in measured changes in non-climatic go up and affordability can worsen for the poor unless redistributive exposure for population, including ambient air pollution, physical policies are in place. activity and noise. The transition to low-carbon equitable and sustainable transport can be fostered by numerous short- and medium- No direct interaction term strategies that would benefit energy security, health, productivity No direct interaction and sustainability. An evidence-based approach that takes into account GHG emissions, ambient air pollutants, economic factors (affordability, cost optimization), social factors (poverty alleviations, public health benefits) and political acceptability is needed to tackle these challenges. Xylia and Silveira, 2017 Figueroa et al., 2014; Schucht et al., 2015; Klausbruckner et al., 2016; Peng et al., 2017 End Poverty in all its Forms Everywhere (1.1/1.4/1.a/1.b) Ensure Access to Food Security (2.1/2.3/2.a/2.b/2.c) Reduce Illnesses from Hazardous Air Pollution (3.9) ↑ / ↓ [+2,‐1]    ~ [0]    ↑ [+2]    [0] Increasingly volatile global oil prices have raised concerns for the 21 projects aiming at resilient transport infrastructure development to Projects aiming at resilient transport infrastructure development (e.g., vulnerability of households to fuel price increases. Pricing measures as a improve access (e.g., C40 Cities Clean Bus Declaration, UITP Declaration C40 Cities Clean Bus Declaration, UITP Declaration on Climate key component of sustainable transport policy need to consider equity. on Climate Leadership, Cycling Delivers on the Global Goals, Global Leadership, Cycling Delivers on the Global Goals, Global Sidewalk Pro-poor mitigation policies are needed to reduce climate impact and Sidewalk Challenge) do not substantially contribute to realizing the Challenge) are targeted at reducing air pollution; electric vehicles using reduce threat; for example, investing more and better in infrastructure (indirect) transport targets with mostly a rural focus: agricultural electricity from renewables or low carbon sources combined with e- by leveraging private resources and using designs that account for productivity (SDG 2) and access to safe drinking water (SDG 6). mobility options such as trolley buses, metros, trams and electro buses, future climate change and the related uncertainty. Communities in poor as well as promoting walking and biking, especially for short distances, No direct interaction areas cope with and adapt to multiple-stressors including climate need consideration. change. Coping strategies provide short-term relief but in the long-term may negatively affect development goals. And responses generate a trade-off between adaptation, mitigation and development. For African cities with slums, due to high commuting costs, many walk to work places which limit access. In Latin America triple informality leading to low productivity and living standards. Dodson and Sipe, 2008; Suckall et al., 2014; Hallegatte et al., 2016a; SLoCaT, 2017 Ajanovic, 2015; SLoCaT, 2017 Klausbruckner et al., 2016; CAF, 2017; Lall et al., 2017 T r a n s p o r t I m p r o v e d A c c e s s a n d F u e l S w i t c h t o M o d e r n L o w - A c c e l e r a t i n g E n e r g y E f f i c i e n c y I m p r o v e m e n t B e h a v i o u r a l R e s p o n s e c a r b o n E n e r g y Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities 5 5 484 Social-Supply Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Poverty and Development (1.1/1.2/1.3/1.4) Air Pollution (3.9) Vocational Trainig, Education for Sustainability (4.b/4.7) ↑ [+2]    [0] ↑ [+2]    ↑ [+1]    Deployment of renewable energy and improvements in energy efficiency Promoting most types of renewables and boosting efficiency greatly aids Decentralized renewable energy systems (e.g., home- or village-scale globally will aid climate change mitigation efforts, and this, in turn, can the achievement of targets to reduce local air pollution and improve air solar power) can support education and vocational training. help to reduce the exposure of the world’s poor to climate-related quality; however, the order of magnitude of the effects, both in terms of extreme events, negative health impacts and other environmental avoided emissions and monetary valuation, varies significantly between shocks (McCollum et al., 2018). different parts of the world. Benefits would especially accrue to those living in the dense urban centres of rapidly developing countries. No direct interaction Utilization of biomass and biofuels might not lead to any air pollution benefits, however, depending on the control measures applied. In addition, household air quality can be significantly improved through lowered particulate emissions from access to modern energy services (McCollum et al., 2018). Riahi et al., 2012; IPCC, 2014; Hallegatte et al., 2016b; McCollum et al., Haines et al., 2007; Nemet et al., 2010; Kaygusuz, 2011; Riahi et al., Anderson et al., 2017 2018 2012; van Vliet et al., 2012; Anenberg et al., 2013; Rafaj et al., 2013; Rao et al., 2013, 2016; West et al., 2013; Chaturvedi and Shukla, 2014; Rose et al., 2014; Smith and Sagar, 2014; IEA, 2016; McCollum et al., 2018 Poverty and Development (1.1/1.2/1.3/1.4) Farm Employment and Incomes (2.3) Disease and Mortality (3.1/3.2/3.3/3.4), Air Pollution (3.9) ↑ / ↓ [+2,‐2]    ↑ / ↓ [+2,‐2]    ↑ [+2]    [0] Large-scale bioenergy production could lead to the creation of Large-scale bioenergy production could lead to the creation of Replacing coal by biomass can reduce adverse impacts of upstream agricultural jobs, as well as higher farm wages and more diversified agricultural jobs, as well as higher farm wages and more diversified supply-chain activities, in particular local air and water pollution, and income streams for farmers. Modern energy access can make marginal income streams for farmers. Modern energy access can make marginal prevent coal mining accidents. Improvements to local air pollution in lands more cultivable, thus potentially generating on-farm jobs and lands more cultivable, thus potentially generating on-farm jobs and power generation compared to coal-fired power plants depend on the incomes; on the other hand, greater farm mechanization can also incomes; on the other hand, greater farm mechanization can also technology and fuel of biomass power plants, but could be significant displace labour. However, large-scale bioenergy production could alter displace labour. However, large-scale bioenergy production could alter when switching from outdated coal combustion technologies to state-of- No direct interaction the structure of global agricultural markets in a way that is, potentially, the structure of global agricultural markets in a way that is, potentially, the-art biogas power generation. unfavourable to small-scale food producers. See SDG2 (McCollum et al., unfavourable to small-scale food producers. The distributional effects of 2018). bioenergy production are underexplored in the literature (McCollum et al., 2018). Balishter and Singh, 1991; Gohin, 2008; de Moraes et al., 2010; van der Balishter and Singh, 1991; Gohin, 2008; de Moraes et al., 2010; van der IPCC, 2005, 2014; Miller et al., 2007; Hertwich et al., 2008; de Best- Horst and Vermeylen, 2011; Corbera and Pascual, 2012; Rud, 2012; Horst and Vermeylen, 2011; Corbera and Pascual, 2012; Rud, 2012; Waldhober et al., 2009; Shackley et al., 2009; Wallquist et al., 2009, Creutzig et al., 2013; Davis et al., 2013; Satolo and Bacchi, 2013; Muys Creutzig et al., 2013; Davis et al., 2013; Satolo and Bacchi, 2013; Muys 2010; Wong-Parodi and Ray, 2009; Chan and Griffiths, 2010; Veltman et et al., 2014; Ertem et al., 2017; McCollum et al., 2018 et al., 2014; Ertem et al., 2017; McCollum et al., 2018 al., 2010; Epstein et al., 2011; Koornneef et al., 2011; Reiner and Nuttall, 2011; Singh et al., 2011; Ashworth et al., 2012; Burgherr et al., 2012; Chen et al., 2012; Asfaw et al., 2013; Corsten et al., 2013; Einsiedel et al., 2013 R e p l a c i n g C o a l I n c r e a s e d U s e o f B i o m a s s N o n - b i o m a s s R e n e w a b l e s - s o l a r , w i n d , h y d r o Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 5 5 485 Social-Supply (continued) Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Disease and Mortality (3.1/3.2/3.3/3.4) [0] [0] ↓ [‐1]    [0] In spite of the industry's overall safety track record, a non-negligible risk for accidents in nuclear power plants and waste treatment facilities remains. The long-term storage of nuclear waste is a politically fraught subject, with no large-scale long-term storage operational worldwide. Negative impacts from upstream uranium mining and milling are comparable to those of coal, hence replacing fossil fuel combustion by No direct interaction No direct interaction nuclear power would be neutral in that aspect. Increased occurrence of No direct interaction childhood leukaemia in populations living within 5 km of nuclear power plants was identified by some studies, even though a direct causal relation to ionizing radiation could not be established and other studies could not confirm any correlation (low evidence/agreement on this issue). Abdelouas, 2006; Cardis et al., 2006; Kaatsch et al., 2008; Al-Zoughool and Krewski, 2009; Heinävaara et al., 2010; Schnelzer et al., 2010; Brugge and Buchner, 2011; Møller and Mousseau, 2011; Møller et al., 2011, 2012; Moomaw et al., 2011; UNSCEAR, 2011; Sermage-Faure et al., 2012; Ten Hoeve and Jacobson, 2012; Tirmarche et al., 2012; Hiyama et al., 2013; Mousseau and Møller, 2013; Smith et al., 2013; WHO, 2013; IPCC, 2014; von Stechow et al., 2016 Poverty and Development (1.1/1.2/1.3/1.4) Farm Employment and Incomes (2.3) Disease and Mortality (3.1/3.2/3.3/3.4) ↑ / ↓ [+2,‐2]    ↑ / ↓ [+1,‐2]    ↑ / ↓ [+2,‐1]    [0] See effects of increased bioenergy use. See increased use of biomass effects. In addition, the concern that more See positive impacts of increased biomass use. At the same time, there bioenergy (for BECCS) necessarily leads to unacceptably high food prices is a non-negligible risk of CO2 leakage both from geological formations is not founded on large agreement in the literature. AR5, for example, as well as from the transportation infrastructure from source to finds a significantly lower effect of large-scale bioenergy deployment on sequestration locations. food prices by mid-century than the effect of climate change on crop yields. Also, Muratori et al. (2016) show that BECCS reduces the upward pressure on food crop prices by lowering carbon prices and lowering the No direct interaction total biomass demand in climate change mitigation scenarios. On the other hand, competition for land use may increase food prices and thereby increase risk of hunger. Use of agricultural residue for bioenergy can reduce soil carbon, thereby threatening agricultural productivity. See literature on increased biomass use: IPCC, 2014; Muratori et al., Wang and Jaffe, 2004; Hertwich et al., 2008; Apps et al., 2010; Veltman 2016; Dooley and Kartha, 2018 et al., 2010; Koornneef et al., 2011; Singh et al., 2011; Siirila et al., 2012; Atchley et al., 2013; Corsten et al., 2013; IPCC, 2014 Disease and Mortality (3.1/3.2/3.3/3.4) [0] [0] ↓ [‐1]    [0] The use of fossil CCS implies continued adverse impacts of upstream supply-chain activities in the coal sector, and because of lower efficiency of CCS coal power plants, upstream impacts and local air pollution are No direct interaction No direct interaction likely to be exacerbated. Furthermore, there is a non-negligible risk of No direct interaction CO2 leakage from geological storage or the CO2 transport infrastructure from source to sequestration location. Wang and Jaffe, 2004; Hertwich et al., 2008; Apps et al., 2010; Veltman et al., 2010; Koornneef et al., 2011; Singh et al., 2011; Siirila et al., 2012; Atchley et al., 2013; Corsten et al., 2013; IPCC, 2014 A d v a n c e d C o a l R e p l a c i n g C o a l C C S : F o s s i l C C S : B i o e n e r g y N u c l e a r / A d v a n c e d N u c l e a r Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities 5 5 486 Social-Other Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Poverty and Development (1.1/1.2/1.3/1.4) Food Security, Promoting Sustainable Agriculture (2.1/2.4/2a) Tobacco Control (3.a/3.a.1) ~  / ↓ [0,‐1]    ↑ [+2]   ↑ [+1]    [0]  Cutting livestock consumption can increase food security for some if Curbing consumer waste of major food crops (i.e., wheat, rice and Consume fewer foods with low nutritional value, e.g., alcohol (Garnett, land grows food not feed, but can also undermine livelihoods and vegetables) and meats (i.e., beef, pork and poultry) in China, USA and 2011). Demand-side measures aimed at reducing the proportion of culture where livestock has long been the best use of land, such as in India alone could feed ~413 million people per year (West et al., 2014). livestock products in human diets, where the consumption of animal parts of Sub-Saharan Africa. One billion extra people could be fed if food crop losses could be halved products is higher than recommended, are associated with multiple (Kummu et al., 2012). Reducing waste, especially from meat and dairy, health benefits, especially in industrialized countries (Bustamante et al., No direct interaction could play a role in delivering food security and reduce the need for 2014). sustainable intensification (Smith, 2013). Dietary change toward global healthy diets could improve nutritional health, food security and reduce emissions. IPCC, 2014 Garnett, 2011; Beddington et al., 2012; Kummu et al., 2012; Smith, Garnett, 2011; Bustamante et al., 2014 2013; Bajželj et al., 2014; Tilman and Clark, 2014; West et al., 2014; Lamb et al., 2016 Poverty and Development (1.1/1.2/1.3/1.4) Food Security, Promoting Sustainable Agriculture (2.1/2.4/2a) Ensure Healthy Lives (3.c) Ensure Inclusive and Quality Education (4.4/4.7) ↑ [+2]    ↑ [+2]    ↑ / ↓ [+2,‐2]    ↑ / ↓ [+2,‐2]      Many CSA interventions aim to improve rural livelihoods, thereby Safe application of biotechnology, both conventional and modern Growing crops such as cassava, sorghum and millet, even in harsh Science-based action within CSA is required to integrate data sets and contributing to poverty alleviation. Agroforestry or integrated methods, can help to improve agricultural productivity, improving crop conditions, is important to the diets of very poor people. Policy sound metrics for testing hypotheses about feedback regarding climate, crop–livestock–biogas systems can substitute costly, external inputs, adaptability and thereby catering to food security. Reducing tillage, scenarios show that reduced research support, delayed industrialization, weather data products and agricultural productivity, such as the saving on household expenditures – or even lead to the selling of some eliminating fallow and keeping the soil covered with residue, cover delayed biotechnology and climate change will delay progress in nonlinearity of temperature effects on crop yield and the assessment of of the products, providing the farmer with extra income, leading to crops or perennial vegetation helps prevent soil erosion and has the reducing childhood malnutrition. The global effects are small, but local trade-offs and synergies that arise from different agricultural increased adaptive capacity (Bogdanski, 2012). potential to increase soil organic matter. Efficient land-management effects for some countries, e.g., Bangladesh and Nigeria, are significant intensification strategies (Steenwerth et al., 2014). Low commodity techniques can help in increasing crop yields, and so food security issues (Evenson, 1999). prices have led to declining investment in research and development, can be addressed. Yield projections are actually higher for developing farmer education, etc. (Lamb et al., 2016). countries than for developed countries, reflecting the fact that they have more 'catch-up' potential (Evenson, 1999). Action is needed throughout the food system on moderating demand, reducing waste, improving governance and producing more food (Godfray and Garnett, 2014). Improving cropland management is the key to increase crop productivity without further degrading soil and water resources (Branca et al., 2011). CSA practices increase productivity and prioritize food security. Branca et al., 2011; Bogdanski, 2012; Scherr et al., 2012; Vermeulen et Evenson, 1999; West and Post, 2002; Johnson et al., 2007; Branca et al., Evenson, 1999; Godfray and Garnett, 2014 Steenwerth et al., 2014; Lamb et al., 2016 al., 2012; Campbell et al., 2014; Lipper et al., 2014; Mbow et al., 2014; 2011; McCarthy et al., 2011; Behnassi et al., 2014; Campbell et al., Steenwerth et al., 2014; Hammond et al., 2017 2014; Godfray and Garnett, 2014; Harvey et al., 2014; Lipper et al., 2014 Poverty Reduction and Minimize Exposure to Risk (1.5) Food Security, Promoting Sustainable Agriculture (2.1/2.4/2a) Ensure Healthy Lives (3.c) ↑ [+2] & J « ↑ [+2] &&&& JJJJ «««« ↑ / ↓ [+2,-2] && JJ «« [0] With mixed-farming systems farmers can not only mitigate risks by Fostering transitions towards more productive livestock production Biodigestion, which has positive public health aspects, particularly producing a multitude of commodities, but they can also increase the systems targeting land-use change appears to be the most efficient lever where toilets are coupled with the biodigester; anaerobic conditions kill productivity of both crops and animals in a more profitable and to deliver food availability outcomes. Genomic selection should be able pathogenic organisms as well as digestive toxins. Separation processes sustainable way. to at least double the rate of genetic gain in the dairy industry. Given can improve or worsen health risks related to food crops or to livestock. the prevalence of mixed crop–livestock systems in many parts of the world, closer integration of crops and livestock in such systems can give rise to increased productivity and increased soil fertility (Thornton, 2010). Managing the indirect effects of livestock systems intensification No direct interaction is critical for the sustainability of the global food system: such as improving productivity and the close link to land sparing (Herrero and Thornton, 2013). In East Africa pastoralists have shifted from cows to camels, which are better adapted to survive periods of water scarcity and able to consistently provide more milk (Steenwerth et al., 2014). Scenarios where zero human-edible concentrate feed is used for livestock, soil erosion potential reduces by 12%. Sansoucy, 1995 Thornton, 2010, 2013; Herrero and Thornton, 2013; Havlík et al., 2014; Sansoucy, 1995; Burton, 2007 Steenwerth et al., 2014; Schader et al., 2015 A g r i c u l t u r e a n d L i v e s t o c k G r e e n h o u s e G a s R e d u c t i o n f r o m I m p r o v e d L i v e s t o c k B e h a v i o u r a l R e s p o n s e : S u s t a i n a b l e L a n d - b a s e d G H G R e d u c t i o n a n d S o i l C a r b o n S e q u e s t r a t i o n P r o d u c t i o n a n d M a n u r e M a n a g e m e n t S y s t e m s H e a l t h y D i e t s a n d R e d u c e d F o o d W a s t e Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 5 5 487 Social-Other (continued) Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Poverty Reduction (1.5) Food Security, Promoting Sustainable Agriculture (2.1/2.4/2a) Ensure Inclusive and Quality Education (4.4/4.7) ↑ [+2]    ↑ / ↓ [+1,‐2]    [0] ↑ [+1]    Partnerships between local forest managers, community enterprises and Food security may lead to the conversion of productive land under Local forest users learn to understand laws, regulations and policies private sector companies can support local economies and livelihoods, forest, including community forests, into agricultural production. In a which facilitate their participation in society. Education and capacity and boost regional and national economic growth. similar fashion, the production of biomass for energy purposes (SDG 7) building provide technical skill and knowledge (Katila et al., 2017). may reduce land available for food production and/or for community No direct interaction forest activities . Efforts by the Government of Zambia to reduce emissions by REDD+ have contributed erosion control, ecotourism and pollination valued at 2.5% of the country's GDP. Katila et al., 2017 Turpie et al., 2015; Epstein and Theuer, 2017; Katila et al., 2017; Dooley Katila et al., 2017 and Kartha, 2018 Poverty and Development (1.1/1.2/1.3/1.4) Food Security (2.1) Ensure Healthy Lives (3.c) Promote Knowledge and Skill to Promote SD (4.7) ↑ / ↓ [+2,‐2]    ↑ / ↓ [+1,‐1]    ↑ [+1]    ↓ [‐1]    Clean Development Mechanism (CDM) can have different implications CDM can have different implications on local to regional food security Urban trees are increasingly seen as a way to reduce harmful air Most landholders reported having low levels of knowledge about tree on local community livelihoods. For example, willingness to adopt and local community livelihoods. pollutants and therefore improve cardio-respiratory health. planting for carbon sequestration – particularly available programmes, afforestation is influenced in particular by Australian landholder’s prices and markets, and government rules and regulations . perceptions of its potential to provide a diversified income stream, and its impacts on flexibility of land management ; land sparing would have far reaching implications for the UK countryside and would affect landowners and rural communities ; and livelihoods could be threatened if subsistence agriculture is targeted . Zomer et al., 2008; Schirmer and Bull, 2014; Lamb et al., 2016; Dooley Zomer et al., 2008; Dooley and Kartha, 2018 Jones and McDermott, 2018 Schirmer and Bull, 2014 and Kartha, 2018 [0] [0] [0] [0] No direct interaction No direct interaction No direct interaction No direct interaction Food Security (2.2/2.3) [0] ↑ / ↓ [+1,‐1]    [0] [0] OIF can have different implications on fish stocks and aquaculture, and it might actually increase food availability for fish stocks (increasing No direct interaction yields); but potentially at the cost of reducing the yields of fisheries No direct interaction No direct interaction outside the enhancement region by depleting other nutrients. Lampitt et al., 2008; Smetacek and Naqvi, 2008; Williamson et al., 2012 Poverty and Development (1.1/1.2/1.5) Food Production (2.3/2.4) ↑ [+3]    ↑ [+3]    [0] [0] Avoiding loss of mangroves and maintaining the 2000 stock could save Avoiding loss of mangroves and maintaining the 2000 stock could save a value of ecosystem services from mangroves in South East Asia of a value of ecosystem services from mangroves in South East Asia approximately 2.16 billion USD until 2050 (2007 prices), with a 95% including fisheries; seaweed aquaculture will provide employment; prediction interval of 1.58–2.76 billion USD (case study area South East traditional management systems provide livelihoods for local Asia); seaweed aquaculture will enhance carbon uptake and provide communities; greening of aquaculture can increase income and well- employment; traditional management systems provide benefits for blue being; and mariculture is a promising approach for China. No direct interaction No direct interaction carbon and support livelihoods for local communities; greening of aquaculture can significantly enhance carbon storage; PES schemes could help capture the benefits derived from multiple ecosystem services beyond carbon sequestration. Zomer et al., 2008; Schirmer and Bull, 2014; Lamb et al., 2016 Brander et al., 2012; Ahmed et al., 2017a, 2017b; Duarte et al., 2017; Sondak et al., 2017; Vierros, 2017; Zhang et al., 2017 [0] [0] [0] [0] No direct interaction No direct interaction No direct interaction No direct interaction O c e a n s F o r e s t B e h a v i o u r a l E n h a n c e d B l u e C a r b o n O c e a n I r o n F e r t i l i z a t i o n R e s p o n s e A f f o r e s t a t i o n a n d R e f o r e s t a t i o n R e d u c e d D e f o r e s t a t i o n , R E D D + W e a t h e r i n g ( R e s p o n s i b l e Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities 5 5 488 Social 2-Demand Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Knowledge and Skills Needed to Promote SD (4.7) Global Partnership (17.6/17.7) [0] ↑  [+1]    [0] ↑  [+2]    There is need for skill in managing in-house energy efficiency. A driving force for energy efficiency is collaboration among companies, Sometimes ESCOs also help. Energy audits, but many times absence of networks, experience sharing and management tools. Sharing among No direct interaction skill acts as barrier for energy efficiency improvement. In many No direct interaction countries can help accelerate managerial action. Absence of countries, especially developing countries, these act as barriers. information, budgetary funding, lack of access to capital, etc. are Apeaning and Thollander, 2013; Johansson and Thollander, 2018 iApeantingt abnd iTholtlandetir, 20C13; Grifftini et atl., 20i 18; lJohalnsson anld Thollander, 2018; Lawrence et al., 2018 Global Partnership (17.6/17.7) [0] [0] [0] ↑  [+2]    Ultra-low carbon steel making and breakthrough technologies are under No direct interaction No direct interaction No direct interaction trial across many countries and helping in enhancing the learning. Abdul Quader et al., 2016 Global Partnership (17.6/17.7) [0] [0] [0] ↑  [+2]    EPI plants are capital intensive and are mostly operated by multinationals with long investment cycles. In developed countries new innovation investments are happening in brown fields. Such large innovation investments need strong collaboration among No direct interaction No direct interaction No direct interaction partners/competitors which can be facilitated by public funds. They happen at national and supranational scales and across sectors, needs fresh revisit at Intellectual Property Rights issues. Global production of bio-based polymers increasingly need public support and incentives to push forward. Wesseling et al., 2017; Griffin et al., 2018 I n d u s t r y L o w - c a r b o n F u e l A c c e l e r a t i n g E n e r g y D e c a r b o n i z a t i o n / C C S / C C U S w i t c h E f f i c i e n c y I m p r o v e m e n t Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 5 5 489 Social 2-Demand (continued) Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Environmental Justice (16.7) [0] [0] ↑  [+2]    [0] Consumption perspectives strengthen environmental justice discourse (as it claims to be a more just way of calculating global and local No direct interaction No direct interaction No direct interaction environmental effects) while possibly also increasing the participatory environmental discourse. Hult and Larsson, 2016 Gender Equality and Women's Empowerment (5.1/5.4) Empowerment and Inclusion (10.1/10.2/10.3/10.4) Capacity and Accountability (16.1/16.3/16.5/16.6/16.7/16.8) Enhance Policy Coherence for Sustainable Development (17.4) ↑  [+1]    ↑ / ↓ [1,‐1]    ↑ [+2]    ↑ [+2]    Efficient stoves lead to empowerment of rural and indigenous women. Energy efficiency measures and the provision of energy access can free Institutions that are effective, accountable and transparent are needed Implementing refrigerant transition and energy efficiency improvement up resources that can then be put towards other productive uses (e.g., at all levels of government (local to national to international) for policies in parallel for room ACs, roughly doubles the benefit of either educational and employment opportunities), especially for women and providing energy access, promoting modern renewables and boosting policy implemented in isolation. children in poor, rural areas. The distributional costs of new energy efficiency. Strengthening the participation of developing countries in policies are dependent on instrument design. If costs fall international institutions (e.g., international energy agencies, UN disproportionately on the poor, then this could work against the organizations, WTO, regional development banks and beyond) will be promotion of social, economic and political equality for all. The impacts important for issues related to energy trade, foreign direct investment, of energy efficiency measures and policies on inequality can be both labour migration and knowledge and technology transfer. Reducing positive, if they reduce energy costs, or negative, if mandatory standards corruption, where it exists, will help these bodies and related domestic increase the need for purchasing more expensive equipment and institutions maximize their societal impacts. Limiting armed conflict and appliances. violence will aid most efforts related to sustainable development, including progress in the energy dimension. Bhojvaid et al., 2014; Berrueta et al., 2017 Dinkelman, 2011; Casillas and Kammen, 2012; Pachauri et al., 2012; Acemoglu, 2009; Tabellini, 2010; Acemoglu et al., 2014; ICSU and ISSC, Shah et al., 2015 Cayla and Osso, 2013; Hirth and Ueckerdt, 2013; Pueyo et al., 2013; 2015; McCollum et al., 2018 Jakob and Steckel, 2014; Fay et al., 2015; Cameron et al., 2016; Hallegatte et al., 2016b; McCollum et al., 2018 Women's Safety and Worth (5.1/5.2/5.4)/Opportunities for Capacity and Accountability (16.1/16.3/16.5/16.6/16.7/16.8) Promote Transfer and Diffusion of Technology (17.6/17.7) Women (5.1/5.5) ↑ [+1]    [0] ↑ [+2]    ↑ [+2]    Improved access to electric lighting can improve women's safety and Institutions that are effective, accountable and transparent are needed Green building technology in Kazakhstan was based on transfer of girls' school enrolment. Cleaner cooking fuel and lighting access can at all levels of government (local to national to international) for knowledge among various parties. reduce health risks and drudgery, which women disproportionately face. providing energy access, promoting modern renewables and boosting Access to modern energy services has the potential to empower women efficiency. Strengthening the participation of developing countries in by improving their income-earning and entrepreneurial opportunities international institutions (e.g., international energy agencies, UN and reducing drudgery. Participating in energy supply chains can organizations, WTO, regional development banks and beyond) will be increase women's opportunities and agency and improve business No direct interaction important for issues related to energy trade, foreign direct investment, outcomes. labour migration, and knowledge and technology transfer. Reducing corruption, where it exists, will help these bodies and related domestic institutions maximize their societal impacts. Limiting armed conflict and violence will aid most efforts related to sustainable development, including progress in the energy dimension. Chowdhury, 2010; Dinkelman, 2011; Kaygusuz, 2011; Köhlin et al., Acemoglu, 2009; Tabellini, 2010; Acemoglu et al., 2014; ICSU and ISSC, Kim and Sun, 2017 2011; Clancy et al., 2012; Haves, 2012; Matinga, 2012; Anenberg et al., 2015; McCollum et al., 2018 2013; Pachauri and Rao, 2013; Burney et al., 2017; McCollum et al., 2018 B u i l d i n g s I m p r o v e d A c c e s s a n d F u e l S w i t c h t o M o d e r n L o w - A c c e l e r a t i n g E n e r g y E f f i c i e n c y I m p r o v e m e n t B e h a v i o u r a l R e s p o n s e c a r b o n E n e r g y Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities 5 5 490 Social 2-Demand (continued) Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Recognize Women's Unpaid Work (5.1/5.4)/Opportunities for Reduce Inequality (10.2) Accountable and Transparent Institutions at All Levels Help Promote Global Partnership (17.1/17.3/17.5/17.6/17.7) Women (5.1/5.5) (16.6/16.8) ↑ [+1]    ↑  [+2]    ↑ / ↓ [+1, ‐1]    ↑ [+2]    The woman's average trip to work differs markedly from the man's The equity impacts of climate change mitigation measures for transport, With behavioural change towards walking for short distances, Projects aiming at resilient transport infrastructure development (e.g., average trip. Working-poor women rely on extensive social networks and indeed of transport policy intervention overall, are poorly pedestrian safety on the road might reduce, unless public policy is C40 Cities Clean Bus Declaration, UITP Declaration on Climate creating communities of spatial necessity, bartering for basic needs to understood by policymakers. This is in large part because standard appropriately formulated. Prevalence of high levels of triple forms of Leadership, Cycling Delivers on the Global Goals, Global Sidewalk overcome transportation constraints. Women earn lower wages and so assessment of these impacts is not a statutory requirement of current informality, in jobs, housing and transportation, are responsible for low Challenge) are happening through multi-stakeholder coalitions. are less likely to justify longer commutes. Many women need to manage policymaking. Managing transport energy demand growth will have to productivity and low standards of living, and are a major challenge for dual roles as workers and mothers. Women tend to perform multi- be advanced alongside efforts in passenger travel towards reducing the policies targeting urban growth in Latin America. purpose commuting, combining both work and household needs . deep inequalities in access to transport services that currently affect the poor worldwide. Free provision of roads and parking spaces converts vast amounts of public land and capital into under-priced space for cars, in extreme cases like Los Angeles, USA, roads and streets free for parking and driving are 20% of land area; as governments give drivers free land, people drive more than they would otherwise. High levels of car dependence and the costs of motoring can be burdensome, and lead to increasing debt, raising questions of affordability for households with limited resources, particularly low-income houses located in suburban areas Crane, 2007; Rogalsky, 2010 Figueroa et al., 2014; Lucas and Pangbourne, 2014; Walks, 2015; CAF, 2017; SLoCaT, 2017 SLoCaT, 2017 Manville, 2017; Belton Chevallier et al., 2018 Responsive, Inclusive, Participatory Decision-making (16.7) Help Promote Global Partnership (17.1/17.3/17.5/17.6/17.7) [0] [0] ↑ [+2]    ↑ [+2]    In transport mitigation it is necessary to conduct needs assessments and Projects aiming at resilient transport infrastructure development and stakeholder consultation to determine plausible challenges, prior to technology adoption (e.g. C40 Cities Clean Bus Declaration, UITP introducing desired planning reforms. Further, the involved personnel Declaration on Climate Leadership, Cycling Delivers on the Global No direct interaction No direct interaction should actively engage transport-based stakeholders during policy Goals, Global Sidewalk Challenge) are happening through multi- identification and its implementation to achieve the desired results. User stakeholder coalitions. behaviour and stakeholder integration are key for successful transport policy implementation. Aggarwal, 2017; AlSabbagh et al., 2017 SLoCaT, 2017 Reduce Inequality (10.2) Responsive, Inclusive, Participatory Decision-making (16.7) Help Promote Global Partnership (17.1/17.3/17.5/17.6/17.7) [0] ↑  [+2]    ↑ / ↓ [+1, ‐1]    ↑ [+2]    The equity impacts of climate change mitigation measures for transport, Formal transport infrastructure improvement in many cities in Projects aiming at resilient transport infrastructure development (e.g. and indeed of transport policy intervention overall, are poorly developing countries leads to eviction from informal settlements; need C40 Cities Clean Bus Declaration, UITP Declaration on Climate understood by policymakers. This is in large part because standard for appropriate redistributive policies and cooperation and partnerships Leadership, Cycling Delivers on the Global Goals, Global Sidewalk assessment of these impacts is not a statutory requirement of current with all stakeholders. Challenge) are happening through multi-stakeholder coalitions. No direct interaction policymaking. Managing transport energy demand growth will have to be advanced alongside efforts in passenger travel towards reducing the deep inequalities in access to transport services that currently affect the poor worldwide. Figueroa et al., 2014; Lucas and Pangbourne, 2014 Colenbrander et al., 2016 SLoCaT, 2017 T r a n s p o r t I m p r o v e d A c c e s s a n d F u e l S w i t c h A c c e l e r a t i n g E n e r g y E f f i c i e n c y B e h a v i o u r a l r e s p o n s e t o M o d e r n L o w - c a r b o n E n e r g y I m p r o v e m e n t Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 5 5 491 Social 2-Supply Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Gender Equality and Women's Empowerment (5.1/5.4) Empowerment and Inclusion (10.1/10.2/10.3/10.4) Energy Justice International Cooperation (All Goals) ↑ [+1]    ↑ [+1]    ↑  [+2]    ↑ / ~ [+2,0]    Decentralized renewable energy systems (e.g., home- or village-scale Decentralized renewable energy systems (e.g., home- or village-scale The energy justice framework serves as an important decision-making International cooperation (in policy) and collaboration (in science) is solar power) can reduce the burden on girls and women of procuring solar power) can enable a more participatory, democratic process for tool in order to understand how different principles of justice can inform required for the protection of shared resources. Fragmented approaches traditional biomass. managing energy-related decisions within communities. energy systems and policies. Islar et al. (2017) state that off-grid and have been shown to be more costly. Specific to SDG7, to achieve the micro-scale energy development offers an alternative path to fossil-fuel targets for energy access, renewables and efficiency, it will be critical use and top-down resource management as they democratize the grid that all countries: (i) are able to mobilize the necessary financial and increase marginalized communities' access to renewable energy, resources (e.g., via taxes on fossil energy, sustainable financing, foreign education and health care. direct investment, financial transfers from industrialized to developing countries); (ii) are willing to disseminate knowledge and share innovative technologies between each other; (iii) follow recognized international trade rules while at the same time ensuring that the least developed countries are able to take part in that trade; (iv) respect each other’s policy space and decisions; (v) forge new partnerships between their public and private entities and within civil society; and (vi) support the collection of high-quality, timely and reliable data relevant to furthering their missions. There is some disagreement in the literature on the effect of some of the above strategies, such as free trade. Regarding international agreements, 'no-regrets options', where all sides gain through cooperation, are seen as particularly beneficial (e.g., nuclear test ban treaties) (McCollum et al., 2018). Schwerhoff and Sy, 2017 Walker and Devine-Wright, 2008; Cass et al., 2010; Cumbers, 2012; Islar et al., 2017 UN, 1989; Ramaker et al., 2003; Clarke et al., 2009; NCE, 2015; Riahi et Kunze and Becker, 2015; McCollum et al., 2018 al., 2015, 2017; Eis et al., 2016; O’Neill et al., 2017; McCollum et al., 2018 [0] [0] [0] [0] No direct interaction No direct interaction No direct interaction No direct interaction Reduce Illicit Arms Trade (16.4) [0] [0] ↓ [‐1]    [0] No direct interaction No direct interaction Continued use of nuclear power poses a constant risk of proliferation. No direct interaction Adamantiades and Kessides, 2009; Rogner, 2010; Sagan, 2011; von Hippel et al., 2011, 2012; Yim and Li, 2013; IPCC, 2014 [0] [0] [0] [0] No direct interaction No direct interaction No direct interaction No direct interaction [0] [0] [0] [0] No direct interaction No direct interaction No direct interaction No direct interaction A d v a n c e d C o a l R e p l a c i n g C o a l C C S : N u c l e a r / A d v a n c e I n c r e a s e d u s e C C S : F o s s i l N o n - b i o m a s s R e n e w a b l e s - s o l a r , w i n d , h y d r o B i o e n e r g y d N u c l e a r o f B i o m a s s Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities 5 5 492 Social 2-Other Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interacgtion Score Evidence Agrepement Confidence Interaction Score Evidence Agreement Confidence making (16.6/16.7/16.a) Resource Mobilization and Strengthen Partnership (17 1/17 14) [0] [0] ↑ / ↓ [+1,‐1]    ↑ / ↓ [+1,‐1]    Appropriate incentives to reduce food waste may require some policy Decision makers should try to integrate agricultural, environmental and innovation and experimentation, but a strong commitment for devising nutritional objectives through appropriate policy measures to achieve and monitoring them seems essential. sustainable healthy diets coupled with reduction in food waste. It is A financial incentive to minimize waste could be created through surprising that politicians and policymakers demonstrate little regarding effective taxation (e.g., by taxing foods with the highest wastage rates, the need to have strategies to reduce meat consumption and to or by increasing taxes on waste disposal). Decision makers should try to encourage more sustainable eating practices . No direct interaction No direct interaction integrate agricultural, environmental and nutritional objectives through appropriate policy measures to achieve sustainable healthy diets coupled with reduction in food waste. It is surprising that politicians and policymakers demonstrate little regarding the need to have strategies to reduce meat consumption and to encourage more sustainable eating practices. Garnett, 2011; Dagevos and Voordouw, 2013; Bajželj et al., 2014; Lamb Garnett, 2011; Dagevos and Voordouw, 2013 et al., 2016 Equal Access, Empowerment of Women (5.5) Empower Economic and Political Inclusion of All, Irrespective Build Effective, Accountable and Inclusive Institutions Resource Mobilization and Strengthen Multi-stakeholder of Sex (10.2) (16.6/16.7/16.8) Partnership (17.1/ 17.3/17.5/17.17) ↑ / ~ [+2,0]    ↑ / ~ [+1,0]    ~  / ↓ [0,‐1]    ↑ [+2]    Many programmes for CSA have been used to empower women and to In many rural societies women are side-lined from decisions regarding Action is needed throughout the food system for improving governance CSA requires more careful adjustment of agricultural practices to natural improve gender equality. Women often have an especially important agriculture even when male household heads are absent, and they often and producing more food (Godfray and Garnett, 2014). CSA requires conditions, a knowledge-intensive approach, huge financial investment role to play in adaptation, because of their gendered indigenous lack access to important inputs such as irrigation water, credit, tools policy intervention for careful adjustment of agricultural practices to and policy and institutional innovation, etc. Besides private investment, knowledge on matters such as agriculture (Terry, 2009). Without access and fertilizer. To be effective, agricultural mitigation strategies need to natural conditions, a knowledge-intensive approach, huge financial quality of public investment is also important (Behnass et al., 2014). to land, credit and agricultural technologies, women farmers face major take these and other aspects of local gender relations into account investment, etc., so having strong institutional frameworks is very Sources of climate finance for CSA in developing countries include constraints in their capacity to diversify into alternative livelihoods (Terry, 2009). Women's key role in maintaining biodiversity, through important. The main source of climate finance for CSA in developing bilateral donors and multilateral financial institutions, besides public (Demetriades and Esplen, 2008). conserving and domesticating wild edible plant seed, and in food crop countries is the public sector. Lack of institutional capacity (as a means sector finance. CSA is committed to new ways of engaging in breeding, is not sufficiently recognized in agricultural and economic for securing creation of equal institutions among social groups and participatory research and partnerships with producers (Steenwerth et policymaking; nor is the importance of biodiversity to sustainable rural individuals) can reduce feasibility of AFOLU mitigation measures in the al., 2014). livelihoods in the face of predicted climate changes (Nelson et al., near future, especially in areas where small-scale farmers or forest users 2002). are the main stakeholders (Bustamante et al., 2014). Denton, 2002; Nelson et al., 2002; Morton, 2007; Demetriades and Nelson et al., 2002; Demetriades and Esplen, 2009; Terry, 2009 Behnassi et al., 2014; Bustamante et al., 2014; Godfray and Garnett, Behnassi et al., 2014; Lipper et al., 2014; Steenwerth et al., 2014 Esplen, 2009; Terry, 2009; Bernier et al., 2013; Jost et al., 2016 2014; Lipper et al., 2014; Steenwerth et al., 2014 Equal Access to Economic Resources, Promote Empowerment Empower Economic and Political Inclusion of All, Irrespective Responsible Decision-making (16.7) Improve Domestic Capacity for Tax Collection (17.1) of Women (5.5/5.a/5.b) of Sex (10.2) ↑ / ~ [+2,0]    ↑ / ~ [+1,0]    ↑ [+1]    ↑ [+2]    Most of the animal farming activities such as fodder collection and Livestock ownership is increasing women’s decision-making and To minimize the economic and social cost, policies should target The role of livestock system transitions in emission reductions depends feeding are performed by women. Alongside the considerable economic power within both the household and the community. Access emissions at their source—on the supply side—rather than on the on the level of the carbon price and which emissions sector is targeted involvement and contribution of women, gender inequalities are to and control and management of small ruminants, grazing areas and demand side as supply-side policies have lower calorie cost than by the policies (Havlík et al., 2014). Mechanisms for affecting pervasive in Indian villages in terms of accessing natural resources, feed resources empower women and lead to an overall positive impact demand-side policies. The role of livestock system transitions in behavioural change in livestock systems need to be better understood by extension services, marketing opportunities and financial services as on the welfare of the household. emission reductions depends on the level of the carbon price and which implementing combinations of incentives and taxes simultaneously in well as in exercising their decision-making powers. Therefore, there is a emissions sector is targeted by the policies. different parts of the world (Herrero and Thornton, 2013). need to correct gender bias in the farming sector. Efforts are needed to increase the capacity of women to negotiate with confidence and meet their strategic needs. Access to and control and management of small ruminants, grazing areas and feed resources empower women and lead to an overall positive impact on the welfare of the household. Patel et al., 2016 Patel et al., 2016 Havlík et al., 2014 Herrero and Thornton, 2013; Havlík et al., 2014 A g r i c u l t u r e a n d L i v e s t o c k G r e e n h o u s e G a s R e d u c t i o n f r o m I m p r o v e d L a n d - b a s e d G r e e n h o u s e G a s R e d u c t i o n a n d S o i l B e h a v i o u r a l R e s p o n s e : S u s t a i n a b l e H e a l t h y L i v e s t o c k P r o d u c t i o n a n d M a n u r e C a r b o n S e q u e s t r a t i o n D i e t s a n d R e d u c e d F o o d W a s t e M a n a g e m e n t S y s t e m s Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 5 5 493 Social 2-Other (continued) Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interacgtion Score Evidence Agrepement Confidence Interaction Score Evidence Agreement Confidence Opportunities for Women (5.1/5.5) Reduced Inequality, Empowerment and Inclusion Build Effective, Accountable and Inclusive Institutions, Resource Mobilization and Strengthen Multi-stakeholder (10.1/10.2/10.3/10.4) Responsible Decision-making (16.6/16.7/16.8) Partnership (17.1/ 17.3/17.5/17.17) ↑ / ↓ [+1,‐1]    ↑ [+2]    ↑ [+2]    ↑ / ↓ [+1,‐1]    Women have been less involved in REDD+ initiative (pilot project) Urges developed countries to support, through multilateral and bilateral Institutional building (National Forest Monitoring Systems, Safeguard To provide finance and technology to developing countries to support design decisions and processes than men. Girls and women have an channels, the development of REDD+ national strategies or action plans Information Systems, etc.), with full and effective participation of all emissions reductions. Be supported by adequate and predictable important role in forestry activities, related to fuel-wood, forest-food and implementation . Girls and women have an important role in relevant countries . REDD+ actions also deliver non-carbon benefits (e.g. financial and technology support, including support for capacity building and pharmaceutical. Their empowerment contributes to sustainable forestry activities, related to fuel-wood, forest-food and medicine. Their local socioeconomic benefits, governance improvements). Forest . Partnerships in the form of significant aid money from, e.g., Norway, forestry as well as reducing inequality . empowerment contributes to sustainable forestry as well as reducing governance is another central aspect in recent studies, including the other bilateral donors and the World Bank’s Forest Carbon Partnership inequality . debate on decentralization of forest management, logging concessions Facility (FCPF) are forthcoming . Estimates of opportunity cost for in public-owned commercially valuable forests and timber certification, REDD+ are very low. Lower costs and/or higher carbon prices could primarily in temperate forests . combine to protect more forests, including those with lower carbon content. Conversely, where the cost of action is high, a large amount of additional funding would be required for the forest to be protected (Miles and Kapos, 2008). Forest governance is another central aspect in recent studies, including debate on decentralization of forest management, logging concessions in public-owned commercially valuable forests and timber certification, primarily in temperate forests . Partnerships between local forest managers, community enterprises and private sector companies can support local economies and livelihoods and boost regional and national economic growth . Brown, 2011; Larson et al., 2014; Katila et al., 2017 Bastos Lima et al., 2017; Katila et al., 2017 Bustamante et al., 2014; Bastos Lima et al., 2015, 2017 Miles and Kapos, 2008; Bustamante et al., 2014; Andrew, 2017; Bastos Lima et al., 2017; Katila et al., 2017 Opportunities for Women (5.1/5.5) Empower Economic and Political Inclusion of All, Irrespective Responsible Decision-making (16.7) Resource Mobilization and Strengthen Partnership of Sex (10.2) (17.1/17.14) ↑ [+1]    ↑ [+1]    ↑ [+1]    ↑ [+2]    Many women in developing countries are already prominently engaged Women’s participation in the decision-making process of forest Land-related mitigation, such as biofuel production, as well as Financing at the national and international level is required to grow in economic sectors related to climate adaptation and mitigation efforts management, for example, has been shown to increase rates of conservation and reforestation action can increase competition for land more seedlings/sapling, restore land, create awareness and education such as agriculture, renewable energy and forest management and are reforestation while decreasing the illegal extraction of forest products. and natural resources, so these measures should be accompanied by factsheets, provide training to local communities regarding the benefits important drivers and leaders in climate responses that are innovative complementary policies. (Quoted from Epstein and Theur, 2017) of afforestation and reforestation. Article 12 of the Kyoto Protocol and effective, benefitting not only their families but also their wider further sets a Clean Development Mechanism through which countries communities. Women’s participation in the decision-making process of in Annex I earn ‘certified emissions reductions’ through projects forest management, for example, has been shown to increase rates of implemented in developing countries (Montanarella and Alva, 2015). reforestation while decreasing the illegal extraction of forest products. Afforestation and reforestation in India are being carried out under various programmes, namely social forestry initiated in the early 1980s, the Joint Forest Management Programme initiated in 1990, afforestation under National Afforestation and Eco-development Board programmes since 1992, and private farmer and industry initiated plantation forestry. If the current rate of afforestation and reforestation is assumed to continue, the carbon stock could increase by 11% by 2030 (Ravindranath et al 2008) UN-Women et al., 2015 UN-Women et al., 2015 Epstein and Theuer, 2017 Ravindranath et al., 2008; Kibria, 2015; Montanarella and Alva, 2015 Responsible Decision-making (16.7) Finance and Trade (17.1/17.10) [0] [0] ↑ [+1]    ↑ [+1]    Indonesian factories may seek advantages through non-price Private certification initiatives for wood product and biomass sourcing competition—perhaps by highlighting decent working conditions or the may extend their schemes with criteria for 'leakage' (external GHG existence of a union—or to see trade associations or government effects). Also recycling of waste wood in pellets is not yet practiced, due agencies promoting the country as a responsible sourcing location to unclear rules in the EU Waste Directive about overseas shipping (Bartley, 2010). In the absence of domestic legal instruments providing (Sikkema et al., 2014). Engagement of Chinese government and private No direct interaction No direct interaction incentives to improve sustainability of sourcing, it appears that sector stakeholders in supply-country sustainability initiatives may be initiatives to engage the major importing enterprises in developing the best way to support this gradual process of improvement. Although responsible sourcing practices and policies is a practical approach. carrying out due diligence in timber sourcing can require considerable Unless initiatives involve all the major importers, they are unlikely to be internal resources, it may be substantially less of a financial burden than successful since the high costs associated with accreditation would the potential fines and reputational damage resulting from sourcing increase production costs for these firms relative to their competitors unknown or controversial timber (Huang et al., 2013). (Huang et al., 2013). Bartley, 2010; Huang et al., 2013 Huang et al., 2013; Sikkema et al., 2014 F o r e s t B e h a v i o u r a l R e s p o n s e ( R e s p o n s i b l e A f f o r e s t a t i o n a n d R e f o r e s t a t i o n R e d u c e d D e f o r e s t a t i o n , R E D D + S o u r c i n g ) Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities 5 5 494 Social 2-Other (continued) Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interacgtion Score Evidence Agrepement Confidence Interaction Score Evidence Agreement Confidence [0] [0] [0] [0] No direct interaction No direct interaction No direct interaction No direct interaction [0] [0] [0] [0] No direct interaction No direct interaction No direct interaction No direct interaction [0] [0] [0] [0] No direct interaction No direct interaction No direct interaction No direct interaction Oceans E n h a n c e d O c e a n I r o n B l u e C a r b o n W e a t h e r i n g F e r t i l i z a t i o n Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 5 5 495 Environment-Demand Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Water Efficiency and Pollution Prevention (6.3/6.4/6.6) Sustainable and Efficient Resource (12.2/12.5/12.6/12.7/12.a) ↑ / ↓ [+2,‐1]    ↑ [+1]    [0] [0] Efficiency and behavioural changes in the industrial sector that lead to Once started leads to chain of actions within the sector and policy space reduced energy demand can lead to reduced requirements on energy to sustain the effort. Helps in expansion of sustainable industrial supply. As water is used to convert energy into useful forms, the production (Ghana). reduction in industrial demand is anticipated to reduce water consumption and waste water, resulting in more clean water for other sectors and the environment. Likewise, reducing material inputs for No direct interaction No direct interaction industrial processes through efficiency and behavioural changes will reduce water inputs in the material supply chains. In extractive industries there can be a trade-off with production unless strategically managed. Vassolo and Döll, 2005; Nguyen et al., 2014; Holland et al., 2015; Fricko Apeaning and Thollander, 2013; Fernando et al., 2017 et al., 2016 Water Efficiency and Pollution Prevention (6.3/6.4/6.6) Sustainable Production (12.2/12.3/12.a) Sustainable Production (15.1/15.5/15.9/15.10) ↑ / ↓ [+2,‐2]    ↑ [+2]    [0] ↑ [+1,‐1]     A switch to low-carbon fuels can lead to a reduction in water demand A circular economy instead of linear global economy can achieve A circular economy help in managing local biodiversity better by having and waste water if the existing higher-carbon fuel is associated with a climate goals and can help in economic growth through industrialization less resource use footprint higher water intensity than the lower-carbon fuel. However, in some which saves on resources, the environment and supports small, medium situations the switch to a low-carbon fuel such as, for example, biofuel and even large industries, and can lead to employment generation. So could increase water use compared to existing conditions if the biofuel new regulations, incentives and a tax regime can help in achieving the No direct interaction comes from a water-intensive feedstock. goal, especially in newly emerging developing countries - although also applicable for large industrialized countries. Hejazi et al., 2015; Fricko et al., 2016; Song et al., 2016 Liu and Bai, 2014; Lieder and Rashid, 2016; Stahel, 2016; Supino et al., Shi et al., 2017 2016; Fan et al., 2017; Shi et al., 2017; Zeng et al., 2017 Water Efficiency and Pollution Prevention (6.3/6.4/6.6) Sustainable Production and Consumption (12.1/12.6/12.a) Conserve and Sustainably Use Ocean (14.1/14.5) ↑ / ↓ [+1,‐1]    ↑ [+2]    ↓ [‐1]    [0] CCU/S requires access to water for cooling and processing which could EPI plants are capital intensive and are mostly operated by CCU/S in the chemical industry faces challenges for transport costs and contribute to localized water stress. CCS/U processes can potentially be multinationals with long investment cycles. In developed countries new storage. In the UK cluster region have been identified for storage under configured for increased water efficiency compared to a system without investments are happening in brown fields, while in developing sea. carbon capture via process integration. countries these are in green fields. Collaboration among partners and No direct interaction user demand change, policy change is essential for encouraging these large risky investments. Meldrum et al., 2013; Byers et al., 2016; Fricko et al., 2016; Brandl et Wesseling et al., 2017 Griffin et al., 2018 al., 2017 I n d u s t r y A c c e l e r a t i n g E n e r g y E f f i c i e n c y D e c a r b o n i s a t i o n / C C S / C C U L o w - c a r b o n F u e l S w i t c h I m p r o v e m e n t Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities 5 5 496 Environment-Demand (continued) Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Water Efficiency and Pollution Prevention (6.3/6.4/6.6) Responsible and Sustainable Consumption ↑ [+2]    ↑  [+2]    [0] [0] Behavioural changes in the residential sector that lead to reduced Technological improvements alone are not sufficient to increase energy energy demand can lead to reduced requirements on energy supply. As savings. Zhao et al. (2017) found that building technology and occupant water is used to convert energy into useful forms, the reduction in behaviours interact with each other and finally affect energy residential demand is anticipated to reduce water consumption and consumption from home. They found that occupant habits could not waste water, resulting in more clean water for other sectors and the take advantage of more than 50% of energy efficiency potential allowed environment. by an efficient building. In the electronic segment, product obsolescence represents a key challenge for sustainability. Echegaray (2016) discusses the dissonance between consumers' product durability experience, orientations to replace devices before terminal technical failure, and No direct interaction No direct interaction perceptions of industry responsibility and performance. The results from their urban sample survey indicate that technical failure is far surpassed by subjective obsolescence as a cause for fast product replacement. At the same time Liu et al. (2017) suggest that we need to go beyond individualist and structuralist perspectives to analyse sustainable consumption (i.e., combines both human agency paradigm and social structural perspective). Bartos and Chester (2014); Fricko et al. (2016); Holland et al. (2016) Sweeney et al., 2013; Webb et al., 2013; Allen et al., 2015; Echegaray (2015); He et al., 2016; Hult and Larsson, 2016; Isenhour and Feng, 2016; van Sluisveld et al., 2016; Zhao et al., 2017; Liu et al., 2017; Sommerfeld et al., 2017 Water Efficiency and Pollution Prevention (6.3/6.4/6.6) Sustainable Practices and Lifestyles (12.6/12.7/12.8) Reduced Deforestation (15.2) ↑ [+2]    ↑ [+1]    [0] ↑ [+2]    Efficiency changes in the residential sector that lead to reduced energy Sustainable practices adopted by public and private bodies in their Improved stoves has helped halt deforestation in rural India. demand can lead to reduced requirements on energy supply. As water is operations (e.g., for goods procurement, supply chain management and used to convert energy into useful forms, the reduction in residential accounting) create an enabling environment in which renewable energy demand is anticipated to reduce water consumption and waste water, and energy efficiency measures may gain greater traction (McCollum et resulting in more clean water for other sectors and the environment. A al., 2018). switch to low-carbon fuels in the residential sector can lead to a reduction in water demand and waste water if the existing higher- carbon fuel is associated with a higher water intensity than the lower- carbon fuel. However, in some situations the switch to a low-carbon fuel such as, for example, biofuel could increase water use compared to No direct interaction existing conditions if the biofuel comes from a water-intensive feedstock. As water is used to convert energy into useful forms, energy efficiency is anticipated to reduce water consumption and waste water, resulting in more clean water for other sectors and the environment. Subsidies for renewables are anticipated to lead to the benefits and trade-offs outlined when deploying renewables. Subsidies for renewables could lead to improved water access and treatment if subsidies support projects that provide both water and energy services (e.g., solar desalination). Bilton et al., 2011; Scott, 2011; Kumar et al., 2012; Meldrum et al., Stefan and Paul, 2008; ECF, 2014; CDP, 2015; Khan et al., 2015; NCE, Bhojvaid et al., 2014 2013; Bartos and Chester, 2014; Hendrickson and Horvath, 2014; Kern 2015; McCollum et al., 2018 et al., 2014; Holland et al., 2015; Fricko et al., 2016; Kim et al., 2017 B u i l d i n g s A c c e l e r a t i n g E n e r g y E f f i c i e n c y I m p r o v e m e n t B e h a v i o u r a l R e s p o n s e Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 5 5 497 Environment-Demand (continued) Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Access to Improved Water and Sanitation (6.1/6.2), Water Sustainable Use and Management of Natural Resource (12.2) Healthy Terrestrial Ecosystems (15.1/15.2/15.4/15.5/15.8) Efficiency and Pollution Prevention (6.3/6.4/6.6) ↑ / ↓ [+2,‐1]    ↑ / ↓ [+2,‐1]    [0] ↑ [+2]    A switch to low-carbon fuels in the residential sector can lead to a A switch to low-carbon fuels in the residential sector can lead to a Ensuring that the world’s poor have access to modern energy services reduction in water demand and waste water if the existing higher- reduction in water demand and waste water if the existing higher- would reinforce the objective of halting deforestation, since firewood carbon fuel is associated with a higher water intensity than the lower- carbon fuel is associated with a higher water intensity than the lower- taken from forests is a commonly used energy resource among the poor carbon fuel. However, in some situations the switch to a low-carbon fuel carbon fuel. However, in some situations the switch to a low-carbon fuel (McCollum et al., 2018). such as, for example, biofuel could increase water use compared to such as, for example, biofuel could increase water use compared to existing conditions if the biofuel comes from a water-intensive existing conditions if the biofuel comes from a water-intensive No direct interaction feedstock. Improved access to energy can support clean water and feedstock. Improved access to energy can support clean water and sanitation technologies. If energy access is supported with water- sanitation technologies. If energy access is supported with water- intensive energy sources, there could be trade-offs with water efficiency intensive energy sources, there could be trade-offs with water efficiency targets. targets. Hejazi et al., 2015; Cibin et al., 2016; Fricko et al., 2016; Song et al., Hejazi et al., 2015; Cibin et al., 2016; Fricko et al., 2016; Song et al., Bazilian et al., 2011; Karekezi et al., 2012; Bailis et al., 2015; Winter et 2016; Rao and Pachauri, 2017 2016; Rao and Pachauri, 2017 al., 2015; McCollum et al., 2018 Water Efficiency and Pollution Prevention (6.3/6.4/6.6) Ensure Sustainable Consumption amd Production Patterns (12.3) ↑ [+2]    ↑  [+2]    [0] [0] Behavioural changes in the transport sector that lead to reduced Urban carbon mitigation must consider the supply chain management of transport demand can lead to reduced transport energy supply. As water imported goods, the production efficiency within the city, the is used to produce a number of important transport fuels, the reduction consumption patterns of urban consumers, and the responsibility of the in transport demand is anticipated to reduce water consumption and ultimate consumers outside the city. Important for climate policy of No direct interaction No direct interaction waste water, resulting in more clean water for other sectors and the monitoring the CO2 clusters that dominate CO2 emissions in global environment. supply chains, because they offer insights on where climate policy can be effectively directed. Vidic et al., 2013; Holland et al., 2015; Fricko et al., 2016; Tiedeman et Kagawa et al., 2015; Lin et al., 2015; Creutzig et al., 2016 al., 2016 Water Efficiency and Pollution Prevention (6.3/6.4/6.6) Sustainable Consumption (12.2/12.8) ↑ [+2]    ↑  [+2]    [0] [0] Similar to behavioural changes, efficiency measures in the transport Relational complex transport behaviour resulting in significant growth in sector that lead to reduced transport demand can lead to reduced energy-inefficient car choices, as well as differences in mobility patterns transport energy supply. As water is used to produce a number of (distances driven, driving styles) and actual fuel consumption between important transport fuels, the reduction in transport demand is different car segments all affect non-progress on transport anticipated to reduce water consumption and waste water, resulting in decarbonization. Consumption choices and individual lifestyles are more clean water for other sectors and the environment. situated and tied to the form of the surrounding urbanization. Major No direct interaction No direct interaction behavioural changes and emissions reductions require understanding of this relational complexity, consideration of potential interactions with other policies, and the local context and implementation of both command-and-control as well as market-based measures. Vidic et al., 2013; Holland et al., 2015; Fricko et al., 2016; Tiedeman et Stanley et al., 2011; Gallego et al., 2013; Heinonen et al., 2013; Aamaas al., 2016 and Peters, 2017; Azevedo and Leal, 2017; Gössling and Metzler, 2017 T r a n s p o r t B u i l d i n g s I m p r o v e d A c c e s s a n d F u e l S w i t c h t o M o d e r n A c c e l e r a t i n g E n e r g y E f f i c i e n c y I m p r o v e m e n t B e h a v i o u r a l R e s p o n s e L o w - c a r b o n E n e r g y Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities 5 5 498 Environment-Demand (continued) Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Water Efficiency and Pollution Prevention (6.3/6.4/6.6) Ensure Sustainable Consumption and Production Patterns (12.3) ↑ / ↓ [+2,‐1]    ↑  [+2]    [0] [0] A switch to low-carbon fuels in the transport sector can lead to a Due to persistent reliance on fossil fuels, it is posited that transport is reduction in water demand and waste water if the existing higher- more difficult to decarbonize than other sectors. This study partially carbon fuel is associated with a higher water intensity than the lower- confirms that transport is less reactive to a given carbon tax than the carbon fuel. However, in some situations the switch to a low-carbon fuel non-transport sectors: in the first half of the century, transport such as, for example, biofuel could increase water use compared to mitigation is delayed by 10–30 years compared to non-transport No direct interaction No direct interaction existing conditions if the biofuel comes from a water-intensive mitigation. The extent to which earlier mitigation is possible strongly feedstock. Transport electrification could lead to trade-offs with water depends on implemented technologies and model structures. use if the electricity is provided with water intensive power generation. Hejazi et al., 2015; Fricko et al., 2016; Song et al., 2016 Figueroa et al., 2014; IPCC, 2014; Pietzcker et al., 2014; Creutzig et al., 2015 T r a n s p o r t I m p r o v e d A c c e s s a n d F u e l S w i t c h t o M o d e r n L o w - c a r b o n E n e r g y Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 5 5 499 Environement-Supply Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Water Efficiency and Pollution Prevention (6.3/6.4/6.6)/ Access Natural Resource Protection (12.2/12.3/12.4/12.5) Marine Economies (14.7)/ Marine Protection Healthy Terrestrial Ecosystems (15.1/15.2/15.4/15.5/15.8) to Improved Water and Sanitation (6.1/6.2) (14.1/14.2/14.4/14.5) ↑ / ↓ [+2,‐2]    ↑ [+2]    ↑ / ↓ [2,‐1]    ↓ [‐1]     Wind/solar renewable energy technologies are associated with very low Renewable energy and energy efficiency slow the depletion of several Ocean-based energy from renewable sources (e.g., offshore wind farms, Landscape and wildlife impact for wind; habitat impact for hydropower. water requirements compared to existing thermal power plant types of natural resources, namely coal, oil, natural gas and uranium. In wave and tidal power) are potentially significant energy resource bases technologies. Widespread deployment is therefore anticipated to lead to addition, the phasing-out of fossil fuel subsidies encourages less for island countries and countries situated along coastlines. Multi-use improved water efficiency and avoided thermal pollution. However, wasteful energy consumption; but if that is done, then the policies platforms combining renewable energy generation, aqua-culture, managing wind and solar variability can increase water use at thermal implemented must take care to minimize any counteracting adverse side- transport services and leisure activities can lay the groundwork for more power plants and can cause poor water quality downstream from effects on the poor (e.g., fuel price rises). (Quote from McCollum et al., diversified marine economies. Depending on the local context and hydropower plants. Access to distributed renewables can provide power 2018) prevailing regulations, ocean-based energy installations could either to improve water access, but could also lead to increased groundwater induce spatial competition with other marine activities, such as tourism, pumping and stress if mismanaged. Developing dams to support reliable shipping, resources exploitation, and marine and coastal habitats and hydropower production can fragment rivers and alter natural flows protected areas, or provide further grounds for protecting those exact reducing water and ecosystem quality. Developing dams to support habitats, therefore enabling marine protection. (Quote from McCollum reliable hydropower production can result in disputes for water in basins et al., 2018) Hydropower disrupts the integrity and connectivity of with up- and down-stream users. Storing water in reservoirs increases aquatic habitats and impacts the productivity of inland waters and their evaporation, which could offset water conservation targets and reduce fisheries. availability of water downstream. However, hydropower plays an important role in energy access for water supply in developing regions, can support water security, and has the potential to reduce water demands if used without reservoir storage to displace other water intensive energy processes. Bilton et al., 2011; Scott et al., 2011; Kumar et al., 2012; Ziv et al., Banerjee et al., 2012; Riahi et al., 2012; Schwanitz et al., 2014; Inger et al., 2009; Michler-Cieluch et al., 2009; Buck and Krause, 2012; Alho, 2011; Garvin et al., 2011; Grodsky et al., 2011; Jain et al., 2011; 2012; Meldrum et al., 2013; Kern et al., 2014; Grill et al., 2015; Fricko Bhattacharyya et al., 2016; Cameron et al., 2016; McCollum et al., 2018 WBGU, 2013; Cooke et al., 2016; Matthews and McCartney, 2018; Kumar et al., 2011; Kunz et al., 2011; Wiser et al., 2011; Dahl et al., et al., 2016; Grubert, 2016; De Stefano et al., 2017 McCollum et al., 2018 2012; de Lucas et al., 2012; Ziv et al., 2012; Lovich and Ennen, 2013; Smith et al., 2013; Matthews and McCartney, 2018 Water Efficiency and Pollution Prevention (6.3/6.4/6.6) Natural Resource Protection (12.2/12.3/12.4/12.5) Healthy Terrestrial Ecosystems (15.1/15.2/15.4/15.5/15.8) ↑ / ↓ [+1,‐2]    ↑ [+2]    [0] ↑ / ↓ [+1,‐2]     Biomass expansion could lead to increased water stress when irrigated Switching to renewable energy reduces the depletion of finite natural Protecting terrestrial ecosystems, sustainably managing forests, halting feedstocks and water-intensive processing steps are used. Bioenergy resources. deforestation, preventing biodiversity loss and controlling invasive alien crops can alter flow over land and through soils as well as require species could potentially clash with renewable energy expansion, if that fertilizer, and this can reduce water availability and quality. Planting No direct interaction would mean constraining large-scale utilization of bioenergy or bioenergy crops on marginal lands or in some situations to replace hydropower. Good governance, cross-jurisdictional coordination and existing crops can lead to reductions in soil erosion and fertilizer inputs, sound implementation practices are critical for minimizing trade-offs improving water quality. (McCollum et al., 2018). Hejazi et al., 2015; Bonsch et al., 2016; Cibin et al., 2016; Song et al., Banerjee et al., 2012; Riahi et al., 2012; Schwanitz et al., 2014; Smith et al., 2010, 2014; Acheampong et al., 2017; McCollum et al., 2016; Gao and Bryan, 2017; Griffiths et al., 2017; Ha and Wu, 2017; Bhattacharyya et al., 2016; Cameron et al., 2016; McCollum et al., 2018 2018 Taniwaki et al., 2017; Woodbury et al., 2018 R e p l a c i n g C o a l I n c r e a s e d U s e o f B i o m a s s N o n - b i o m a s s R e n e w a b l e s - s o l a r , w i n d h y d r o Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities 5 5 500 Environement-Supply (continued) Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Water Efficiency and Pollution Prevention (6.3/6.4/6.6) Healthy Terrestrial Ecosystems (15.1/15.2/15.4/15.5/15.8) ↑ / ↓ [+2,-1] &&& JJJ ««« [0] [0] ↓ [-1] && JJ «« Nuclear power generation requires water for cooling which can lead to Safety and waste concerns from uranium mining and milling. localized water stress and the resulting cooling effluents can cause No direct interaction No direct interaction thermal pollution in rivers and oceans. Webster et al., 2013; Holland et al., 2015; Fricko et al., 2016; Raptis et Bickerstaff et al., 2008; Sjoberg and Sjoberg, 2009; Ahearne, 2011; al., 2016 Corner et al., 2011; Visschers and Siegrist, 2012; IPCC, 2014 Water Efficiency and Pollution Prevention (6.3/6.4/6.6) Natural Resource Protection (12.2/12.3/12.4/12.5) Healthy Terrestrial Ecosystems (15.1/15.2/15.4/15.5/15.8) ↑ / ↓ [+1,‐2]    ↑ [+1]    [0] ↑ / ↓ [+1,‐2]    CCU/S requires access to water for cooling and processing which could Switching to renewable energy reduces the depletion of finite natural Protecting terrestrial ecosystems, sustainably managing forests, halting contribute to localized water stress. However, CCS/U processes can resources. On the other hand, the availability of underground storage is deforestation, preventing biodiversity loss and controlling invasive alien potentially be configured for increased water efficiency compared to a limited and therefore reduces the benefits of switching from finite species could potentially clash with renewable energy expansion, if that system without carbon capture via process integration. The bioenergy resources to bioenergy. would mean constraining large-scale utilization of bioenergy or component adds the additional trade-offs associated with bioenergy No direct interaction hydropower. Good governance, cross-jurisdictional coordination and use. Large-scale bioenergy increases input demand, resulting in sound implementation practices are critical for minimizing trade-offs environmental degradation and water stress. (McCollum et al., 2018). Large-scale bioenergy increases input demand, resulting in environmental degradation and water stress. Meldrum et al., 2013; Byers et al., 2016; Fricko et al., 2016; Brandl et Banerjee et al., 2012; Riahi et al., 2012; Schwanitz et al., 2014; Smith et al., 2010, 2014; Acheampong et al., 2017; Dooley and Kartha, al., 2017; Dooley and Kartha, 2018 Bhattacharyya et al., 2016; Cameron et al., 2016; McCollum et al., 2018 2018, McCollum et al., 2018) Water Efficiency and Pollution Prevention (6.3/6.4/6.6) ↑ / ↓ [+1,‐2]    [0] [0] [0] CCU/S requires access to water for cooling and processing which could contribute to localized water stress. However, CCS/U processes can potentially be configured for increased water efficiency compared to a system without carbon capture via process integration. Coal mining to No direct interaction No direct interaction No direct interaction support clean coal CCS will negatively impact water resources due to the associated water demands, waste water and land-use requirements. Meldrum et al., 2013; Byers et al., 2016; Fricko et al., 2016; Brandl et al., 2017 A d v a n c e d C o a l R e p l a c i n g C o a l N u c l e a r / A d v a n c e d C C S : F o s s i l C C S : B i o e n e r g y N u c l e a r Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 5 5 501 Environement-Other Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Water Efficiency and Pollution Prevention (6.3/6.4/6.6) Ensure Sustainable Consumption and Production Patterns, Conservation of Biodiversity and Restoration of Land (15.1/ Sustainable Practices and Lifestyle (12.3/12.4/12.6/12.7/12.8) 15.5/15.9) ↑ / ↓ [+2,‐1]    ↑ [+2]    [0] ↑ [+1]      Reduced food waste avoids direct water demand and waste water for Reduce loss and waste in food systems, processing, distribution and by Reducing food waste has secondary benefits like protecting soil from crops and food processing, and avoids water used for energy supply by changing household habits. To reduce environmental impact of livestock degradation, and decreasing pressure for land conversion into reducing agricultural, food processing and waste management energy both production and consumption trends in this sector should be traced. agriculture and thereby protecting biodiversity. inputs. Healthy diets will support water efficiency targets if the shift Livestock production needs to be intensified in a responsible way (i.e., The agricultural area that becomes redundant through the dietary towards healthy foods results in food supply chains that are less water be made more efficient in the way that it uses natural resources). transitions can be used for other agricultural purposes such as energy intensive than the supply chains supporting the historical dietary Wasted food represents a waste of all the emissions generated during crop production, or will revert to natural vegetation. A global food pattern. the course of producing and distributing that food. Mitigation measures transition to less meat, or even a complete switch to plant-based protein include: eat no more than needed to maintain a healthy body weight; food, could have a dramatic effect on land use. Up to 2,700 Mha of eat seasonal, robust, field-grown vegetables rather than protected, pasture and 100 Mha of crop land could be abandoned (Quoted from fragile foods prone to spoilage and requiring heating and lighting in No direct interaction Stehfest et al., 2009) their cultivation, refrigeration stage; consume fewer foods with low nutritional value e.g., alcohol, tea, coffee, chocolate and bottled water (these foods are not needed in our diet and need not be produced); shop on foot or over the Internet (reduced energy use). Reduction in food waste will not only pave the path for sustainable production but will also help in achieving sustainable consumption (Garnett, 2011). Reduce meat consumption to encourage more sustainable eating practices. Khan et al., 2009; Ingram, 2011; Kummu et al., 2012; Haileselassie et Stehfest et al., 2009; Steinfeld and Gerber, 2010; Garnett, 2011; Ingram, Stehfest et al., 2009; Kummu et al., 2012 al., 2013; Bajželj et al., 2014; Tilman and Clark, 2014; Walker et al., 2011; Beddington et al., 2012; Kummu et al., 2012; Bellarby et al., 2014; Ran et al., 2016 2013; Dagevos and Voordouw, 2013; Smith, 2013; Bajželj et al., 2014; Hedenus et al., 2014; Tilman and Clark, 2014; West et al., 2014; Hiç et al., 2016; Lamb et al., 2016 Water Efficiency and Pollution Prevention (6.3/6.4/6.6) Ensure Sustainable Production Patterns (12.3) Conservation of Biodiversity and Restoration of Land (15.1/15.5/15.9) ↑ / ↓ [+1,‐1]    ↑ [+1]    [0] ↑ / ↓ [+1,‐1]    Soil carbon sequestration can alter the capacity of soils to store water, Millet or sorghum yield can double as compared with unimproved land Agricultural intensification can promote conservation of biological which impacts the hydrological cycle and could be positive or negative by more than 1 tonne per hectare due to sustainable intensification. An diversity by reducing deforestation, and by rehabilitation and restoration from a water perspective, dependent on existing conditions. CSA enrich integrated approach to safe applications of both conventional and of biodiverse communities on previously developed farm or pasture linkages across sectors including management of water resources. modern agricultural biotechnologies will contribute to increased yield land. However, planting monocultures on biodiversity hot spots can Minimum tillage systems have been reported to reduce water erosion (Lakshmi et al., 2015). have adverse side-effects, reducing biodiversity. Genetically modified and thus sedimentation of water courses (Bustamante et al., 2014). crops reduce demand for cultivated land. Adaptation of integrated landscape approaches can provide various ecosystem services. CSA No direct interaction enrich linkages across sectors including management of land and bio- resources. Land sparing has the potential to be beneficial for biodiversity, including for many species of conservation concern, but benefits will depend strongly on the use of spared land. In addition, high yield farming involves trade-offs and is likely to be detrimental for wild species associated with farm land (Lamb et al., 2016). Behnassi et al., 2014; Bustamante et al., 2014; P. Smith et al., 2016b Campbell et al., 2014; Lakshmi et al., 2015 Lybbert and Sumner, 2010; Behnassi et al., 2014; Harvey et al., 2014; IPCC, 2014; Lamb et al., 2016) A g r i c u l t u r e a n d L i v e s t o c k L a n d - b a s e d G r e e n h o u s e G a s R e d u c t i o n a n d S o i l C a r b o n B e h a v i o u r a l R e s p o n s e : S u s t a i n a b l e H e a l t h y D i e t s a n d R e d u c e d F o o d W a s t e S e q u e s t r a t i o n Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities 5 5 502 Environement-Other (continued) Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Water Efficiency and Pollution Prevention (6.3/6.4/6.6) Ensure Sustainable Production Patterns and Restructing Restoration of Land (15.1) Taxation (12.3/12c) ↑ / ↓ [+2,‐1]    ↑  [+1]    [0] ↑ [+1]    Livestock efficiency measures are expected to reduce water required for In the future, many developed countries will see a continuing trend in Grasslands are valuable, but improved management is required as grass livestock systems as well as associated livestock waste water flows. which livestock breeding focuses on other attributes in addition to accounts for close to 50% of feed use in livestock systems . The scenario However, efficiency measures that include agricultural intensification production and productivity, such as product quality, increasing animal with 100% reduction of food-competing-feedstuffs resulted in a 335 could increase water demands locally, leading to increased water stress welfare, disease resistance (Thornton, 2010). Diet composition and Mha decrease in arable land area, which corresponds to a decrease of if the intensification is mismanaged. In scenarios where zero human- quality are key determinants of the productivity and feed-use efficiency 22% in arable and 7% in the total agricultural area . edible concentrate feed is used for livestock, freshwater use reduces by of farm animals (Herrero, et al., 2013). Mechanisms for effecting 21%. behavioural change in livestock systems need to be better understood by No direct interaction implementing combinations of incentives and taxes simultaneously in different parts of the world (Herrero and Thornton, 2013). Reducing the amount of human-edible crops that are fed to livestock represents a reversal of the current trend of steep increases in livestock production, and especially of monogastrics, so would require drastic changes in production and consumption (Schader et al., 2015). Haileselassie et al., 2013; Schader et al., 2015; Kong et al., 2016; Ran et Thornton, 2010; Herrero and Thornton, 2013; Herrero et al., 2013; Herrero et al., 2013; Schader et al., 2015 al., 2016 Schader et al., 2015 Water Efficiency and Pollution Prevention (6.3/6.4/6.6) Ensure Sustainable Consumption (12.3) Conservation of Biodiversity, Sustainability of Terrestrial Ecosystems (15.2/15.3/15.4/15.5/15.9) ↑ / ↓ [+1,‐1]    ↑  [+1]    [0] ↑ [+1]    Forest management alters the hydrological cycle which could be positive Reduce the human pressure on forests, including actions to address Policies and programmes for reducing deforestation and forest or negative from a water perspective and is dependent on existing drivers of deforestation. degradation for rehabilitation and restoration of degraded lands can conditions. Conservation of ecosystem services indirectly could help promote conservation of biological diversity. Reduce the human countries maintain watershed integrity. Forests provide sustainable and No direct interaction pressure on forests, including actions to address drivers of deforestation. regulated provision and help in water purification. Efforts by the Government of Zambia to reduce emissions by REDD+ have contributed erosion control, ecotourism and pollination valued at 2.5% of the country's GDP. Zomer et al., 2008; Kibria, 2015; Bonsch et al., 2016; Gao and Bryan, Bastos Lima et al., 2017 Miles and Kapos, 2008; IPCC, 2014; Bastos Lima et al., 2015; Turpie et 2017; Griffiths et al., 2017; Katila et al., 2017 al., 2015; Epstein and Theuer, 2017; Katila et al., 2017 Enhance Water Quality (6.3) Marine Economies (14.7)/Marine Protection and Income Conservation of Biodiversity and Restoration of Land Generation (14.1/14.2/14.4/14.5) (15.1/15.5/15.9) ↑ / ↓ [+2,‐1]    [0] ↑ [+2]    ↑ [+2]    Similar to REDD+, forest management alters the hydrological cycle Mangroves would help to enhance fisheries and tourism businesses. Identified large amounts of land (749 Mha) globally as biophysically which could be positive or negative from a water perspective and is suitable and meeting the CDM eligibility criteria . Forest landscape dependent on existing conditions. Forest landscape restoration can have restoration can conserve biodiversity and reduce land degradation. a large impact on water cycles. Strategic placement of tree belts in lands Mangroves reduce impacts of disasters (cyclones/storms/floods) acting affected by dryland salinity can remediate the affected lands by as live seawalls and enhance forest resources/biodiversity. Forest goal modifying landscape water balances. Watershed scale reforestation can can conserve/restore 3.9–8.8 m ha/year average, 77.2–176.9 m ha in result in the restoration of water quality. Fast-growing species can total and 7.7–17.7 m ha /year in 2030 of forest area by 2030 (Wolosin, increase nutrient input and water inputs that can cause ecological 2014). Forest and biodiversity conservation, protected area formation damage and alter local hydrological patterns. Reforestation of mixed and forestry-based afforestation are practices that enhance resilience of No direct interaction native species and in carefully chosen sites could increase biodiversity forest ecosystems to climate change (IPCC, 2014). Strategic placement and restore waterways, reducing run-off and erosion (Dooley and of tree belts in lands affected by dryland salinity can remediate the Kartha, 2018). affected lands by modifying landscape water balances and protect livestock. It can restore biologically diverse communities on previously developed farmland . Large-scale restoration is likely to benefit ecosystem service provision, including recreation, biodiversity, conservation and flood mitigation. Reforestation of mixed native species and in carefully chosen sites could increase biodiversity, reducing run-off and erosion . Zomer et al., 2008; Bustamante et al., 2014; Kibria, 2015; Lamb et al., Kibria, 2015 Zomer et al., 2008; Bustamante et al., 2014; IPCC, 2014; Kibria, 2015; 2016; Dooley and Kartha, 2018 Lamb et al., 2016; Epstein and Theuer, 2017; Dooley and Kartha, 2018 F o r e s t A g r i c u l t u r e a n d L i v e s t o c k G r e e n h o u s e G a s R e d u c t i o n f r o m I m p r o v e d L i v e s t o c k A f f o r e s t a t i o n a n d R e f o r e s t a t i o n R e d u c e d D e f o r e s t a t i o n , R E D D + P r o d u c t i o n a n d M a n u r e M a n a g e m e n t S y s t e m s Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 5 5 503 Environement-Other (continued) Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Water Efficiency and Pollution Prevention (6.3/6.4/6.6) Ensure Sustainable Production Patterns (12.3) Sustainability and Conservation (15.1/15.2/15.3) ↑ / ↓ [+2,‐1]    ↑  [+1]    [0] ↑ / ↓ [+1,‐1]    Responsible sourcing will have co-benefits for water efficiency and At local levels, forest certification programmes and practicing At the macro level, forest certification has done little to stem the tide of pollution prevention if the sourcing strategies incorporate water metrics. sustainable forest management provide the provision of raw materials forest degradation, conversion of forest land to agriculture, and illegal There is a risk that shifting supply sources could lead to increased water for a ‘low ecological footprint’ economy. logging—all of which remain serious threats to Indonesian forests use in another part of the economy. At local levels, forest certification No direct interaction (Bartley, 2010). At local levels, forest certification programmes and programmes and practicing sustainable forest management provide practicing sustainable forest management help in biodiversity freshwater supplies. protection. van Oel and Hoekstra, 2012; Launiainen et al., 2014; Hontelez, 2016 Hontelez, 2016 Bartley, 2010; Hontelez, 2016 Nutrient Pollution, Ocean Acidification, Fish Stocks, MPAs, SISD (14.1/14.3/14.4/14.5/14.7) [0] [0] ↑ / ↓ [+1,‐2]    [0] OIF could exacerbate or reduce nutrient pollution, increase the likelihood of mid-water deoxygenation, increase ocean acidification, No direct interaction No direct interaction might contribute to the rebuilding of fish stocks in producing plankton, No direct interaction therefore generating benefits for SISD, but might also be in conflict with designing MPAs. Gnanadesikan et al., 2003; Jin and Gruber, 2003; Denman, 2008; Lampitt et al., 2008; Smetacek and Naqvi, 2008; Güssow et al., 2010; Oschlies et al., 2010; Trick et al., 2010; Williamson et al., 2012 Integrated Water Resources Management (6.3/6.5) Ocean Acidification, Nutrient Pollution (14.3/14.1) Conservation of Biodiversity and Restoration of Land (15.1/15.2/15.3/15.4/15.9) ↑ [+2]    [0] ↑ / ~  [+2,0]    ↑ [+3]    Development of blue carbon resources (coastal and marine vegetated Mangroves could buffer acidification in their immediate vicinity; Average difference of 31 mm per year in elevation rates between areas ecosystems) can lead to coordinated management of water in coastal seaweeds have not been able to mitigate the effect on ocean with seagrass and unvegetated areas (case study areas: Scotland, areas. No direct interaction foraminifera. Kenya, Tanzania and Saudi Arabia); mangroves fostering sediment accretion of about 5mm a year. Vierros et al., 2015 Pettit et al., 2015; Sippo et al., 2016 Alongi, 2012; Potouroglou et al., 2017 Ocean Acidification, Nutrient Pollution (14.3/14.1) Protect Inland Freshwater Systems (14.1) [0] [0] ↑ / ↓ [+2,‐1]    ↓ [‐2]    Enhanced weathering (either by spreading lime or quicklime, in Olivine can contain toxic metals such as nickel which could accumulate combination with CCS, over the ocean or olivine at beaches or the in the environment or disrupt the local ecosystem by changing the pH of catchment area of rivers) opposes ocean acidification. "End-of-century the water (in case of spreading in the catchment area of rivers). ocean acidification is reversed under RCP4.5 and reduced by about two- thirds under RCP8.5; additionally, surface ocean aragonite saturation No direct interaction No direct interaction state, a key control on coral calcification rates, is maintained above 3.5 throughout the low latitudes, thereby helping maintain the viability of tropical coral reef ecosystems ." However, marine biology would also be affected, in particular if spreading olivine is used, which works like ocean (iron) fertilization. Köhler et al., 2010, 2013; Hartmann et al., 2013; Paquay and Zeebe, Hartmann et al., 2013 2013; P. Smith et al., 2016a; Taylor et al., 2016 O c e a n s F o r e s t B e h a v i o u r a l R e s p o n s e E n h a n c e d W e a t h e r i n g B l u e C a r b o n O c e a n I r o n F e r t i l i z a t i o n ( R e s p o n s i b l e S o u r c i n g ) Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities 5 5 504 Economic-Demand Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Energy Savings (7.1/7.3/7.a/7.b) Reduces Unemployment (8.2/8.3/8.4/8.5/8.6) Infrastructure Renewal (9.1/9.3/9.5/9.a) Sustainable Cities (15.6/15.8/15.9) ↑ [+2]    ↑ [+1]    ↑ [+1]    ↑ [+2]     Energy efficiency leads to reduced energy demand and hence energy Unemployment rate reduction from 25% to 12% in South Africa. Transitioning to a more renewables-based energy system that is highly Industries are becoming suppliers of energy, waste heat and water to supply and energy security, reduces import. Positive rebound effect can Enhances firm productivity and technical and managerial capacity of the energy efficient is well-aligned with the goal of upgrading energy neighbourial human settlements, and therefore there is a reduced raise demand but to a very less extent due to low rebound effect in employees. New jobs for managing energy efficiency opens up infrastructure and making the energy industry more sustainable. At the primary energy demand, which also makes towns and cities grow industry sector in many countries and by appropriate mix of industries opportunities in energy service delivery sector. same time, infrastructure upgrades in other parts of the economy, such sustainably. (China) can maintain energy savings gain. Supplying surplus energy to as modernized telecommunications networks, can create the conditions cities is also happening, proving maintenance culture, switching off idle for a successful expansion of renewable energy and energy efficiency equipment helps in saving energy (e.g Ghana). measures (e.g., smart metering and demand-side management; McCollum et al., 2018). Apeaning and Thollander, 2013; Chakravarty et al., 2013; IPCC, 2014; Altieri et al., 2016; Fernando et al., 2017; Johansson and Thollander, Riahi et al., 2012; Apeaning and Thollander, 2013; Goldthau, 2014; Karner et al., 2015 Karner et al., 2015; Zhang et al., 2015; Li et al., 2016; Fernando et al., 2018 Bhattacharyya et al., 2016; Meltzer, 2016; McCollum et al., 2018 2017; Wesseling et al., 2017 Sustainable and Modern (7.2/7.a) Economic Growth with Decent Employment (8.1/8.2/8.3/8.4) Innovation and New Infrastructure (9.2/9.3/9.4/9.5/9.a) Sustainable Cities (15.6/15.8/15.9) ↑ [+2] ↑ [+2]      ↑ [+2]    ↑ [+2]      Industries are becoming suppliers of energy, waste heat, water and roof The circular economy instead of linear global economy can achieve A circular economy instead of linear global economy is helping new Industries are becoming suppliers of energy, waste heat, water and roof tops used for solar energy generation, and therefore helping to reduce climate goals and can help in economic growth through innovation, and infrastructure can achieve climate goals and can help in tops used for solar energy generation, and supply to neighbourial primary energy demand. CHP in chemical industries can help in industrialization, which saves on resources and the environment and economic growth through industrialization which saves on resources human settlements, therefore reducing primary energy demand, which providing surplus power in the grid. supports small, medium and even large industries, which can lead to and the environment and supports small, medium and even large also makes towns and cities grow sustainably. employment generation. So new regulations, incentives and a revised industries, which can lead to employment generation. So new tax regime can help in achieving the goal. regulations, incentives and revised tax regime can help in achieving the goal. Karner et al., 2015; Griffin et al., 2018 Stahel, 2013, 2017; Liu et al., 2014; Leider et al., 2015; Supino et al., Stahel, 2013, 2017; Liu et al., 2014; Leider et al., 2015; Supino et al., Karner et al., 2015 2015; Zheng et al., 2016; Fan et al., 2017; Shi et al., 2017 2015; Zheng et al., 2016; Fan et al., 2017; Shi et al., 2017 Affordable and Sustainable Energy Sources Decouple Growth from Environmental Degradation Innovation and New Infrastructure (9.2/9.4/9.5) (8.1/8.2/8.4) ↑ / ↓ [+2,‐2]    ↑ [+2]    ↑ [+2]    [0] CCS for EPIs can be incremental, but need additional space and can EPI s are important players for economic growth. Deep decarbonization Deep decarbonization through radical technological change in EPI will need additional energy, sometimes compensating for higher efficiency. of EPIs through radical innovation is consistent with well-below 2°C lead to radical innovations, for example, in completely changing For example, recirculating blast R furnace and CCS for iron steel means scenarios. industries' innovation strategies, plants and equipment, skills, high energy demand; electric melting in glass can mean higher production techniques, design, etc. Radical CCS will need new electricity prices; in the paper industry, new separation and drying infrastructure to transport CO2. technologies are key to reducing the energy intensity, allowing for carbon neutral operation in the future; bio-refineries can reduce petro- No direct interaction refineries; DRI in iron and steel with H2 encourages innovation in hydrogen infrastructure; and the chemicals industry also encourage renewable electricity and hydrogen as bio-based polymers can increase biomass price. Griffin et al., 2017; Wesseling et al., 2017 Denis-Ryan et al., 2016; Åhman et al., 2017; Wesseling et al., 2017 Denis-Ryan et al., 2016; Åhman et al., 2017; Wesseling et al., 2017; Griffin et al., 2018 I n d u s t r y A c c e l e r a t i n g E n e r g y E f f i c i e n c y D e c a r b o n i z a t i o n / C C S / C C U L o w - C a r b o n F u e l S w i t c h I m p r o v e m e n t Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 5 5 505 Economic-Demand (continued) Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Saving Energy, Improvement in Energy Efficiency (7.3/7.a/7.b) Progressively Improve Resource Efficiency (8.4), Employment Innovation and New Infrastructure (9.2/9.4/9.5) Sustainable Cities (15.6/15.8/15.9) Opportunities (8.2/8.3/8.5/8.6) ↑ [+2]    ↑ [+2]    ↑ [+2]    ↑ [+2]     Lifestyle change measures and adoption behaviour affect residential Behavioural change programmes help in sustaining energy savings Adoption of smart meters and smart grids following community-based Behavioural change programmes help in making cities more sustainable. energy use and implementation of efficient technologies as residential through new infrastructure developments. social marketing help with infrastructure expansion. People are adopting HVAC systems. Also, social influence can drive energy savings in users solar rooftops, white roof/vertical garden/green roofs at much faster exposed to energy consumption feedback. Effect of autonomous rates due to new innovations and regulations. motivation on energy savings behaviour is greater than that of other more established predictors, such as intentions, subjective norms, perceived behavioural control and past behaviour. Use of a hybrid engineering approach using social psychology and economic behaviour models are suggested for residential peak electricity demand response. However, some take-back in energy savings can happen due to rebound effects unless managed appropriately or accounted for welfare improvement. Adjusting thermostats helps in saving energy. Uptake of energy efficient appliances by households with an introduction to appliance standards, training, promotional material dissemination and the desire to save on energy bills are helping to change acquisition behaviour. Chakravarty et al., 2013; Gyamfi et al., 2013; Hori et al., 2013; Huebner Anda and Temmen, 2014 Anda and Temmen, 2014; Roy et al., 2018 Anda and Temmen, 2014; Roy et al., 2018 et al., 2013; Jain et al., 2013; Sweeney et al., 2013; Webb et al., 2013; Yue et al., 2013; Anda and Temmen, 2014; Allen et al., 2015; Noonan et al., 2015; de Koning et al., 2016; Isenhour and Feng, 2016; Santarius et al., 2016; Song et al., 2016; van Sluisveld et al., 2016; Sommerfeld et al., 2017; Zhao et al., 2017; Roy et al., 2018 Increase in Energy Savings (7.3) Employment Opportunities (8.2/8.3/8.5/8.6)/Strong Financial Innovation and New Infrastructure (9.2/9.4/9.5) Urban Environmental Sustainability (11.3/11.6/11.b/11.c) Institutions (8.10) ↑  [+2]    ↑ / ↓ [+2,‐1]    ↑ [+2]    ↑ [+2]    There is high agreement among researchers based on a great deal of Deploying renewables and energy efficient technologies, when Adoption of smart meters and smart grids following community-based Renewable energy technologies and energy efficient urban infrastructure evidence across various countries that energy efficiency improvement combined with other targeted monetary and fiscal policies, can help social marketing help in infrastructure expansion. Statutory norms to solutions (e.g., public transit) can also promote urban environmental reduces energy consumption and therefore leads to energy savings (e.g., spur innovation and reinforce local, regional and national industrial and enhance energy and resource efficiency in buildings is encouraging sustainability by improving air quality and reducing noise. Efficient efficient stoves save bioenergy). Countries with higher hours of use due employment objectives. Gross employment effects seem likely to be green building projects. transportation technologies powered by renewably based energy carriers to higher ambient temperatures or more carbon intensive electricity positive; however, uncertainty remains regarding the net employment will be a key building block of any sustainable transport system grids benefit more from available improvements in energy efficiency and effects due to several uncertainties surrounding macro-economic (McCollum et al., 2018). Green buildings help in sustainable use of refrigerant transition. feedback loops playing out at the global level. Moreover, the construction. distributional effects experienced by individual actors may vary significantly. Strategic measures may need to be taken to ensure that a large-scale switch to renewable energy minimizes any negative impacts on those currently engaged in the business of fossil fuels (e.g., government support could help businesses re-tool and workers re-train). To support clean energy and energy efficiency efforts, strengthened financial institutions in developing country communities are necessary for providing capital, credit and insurance to local entrepreneurs attempting to enact change (McCollum et al., 2018). McLeod et al., 2013; Noris et al., 2013; Bhojvaid et al., 2014; Babiker and Eckaus, 2007; Fankhauser and Tepic, 2007; Gohin, 2008; Anda and Temmen, 2014; Roy et al., 2018 Creutzig et al., 2012; Kahn Ribeiro et al., 2012; Riahi et al., 2012; Holopainen et al., 2014; Kwong et al., 2014; Yang et al., 2014; Cameron Frondel et al., 2010; Dinkelman, 2011; Guivarch et al., 2011; Jackson Bongardt et al., 2013; Grubler and Fisk, 2013; Raji et al., 2015; Kim et et al., 2015; Liddell and Guiney, 2015; Shah et al., 2015; Berrueta et al., and Senker, 2011; Borenstein, 2012; Creutzig et al., 2013; Blyth et al., al., 2017; McCollum et al., 2018 2017; Kim et al., 2017; Salvalai et al., 2017 2014; Clarke et al., 2014; Dechezleprêtre and Sato, 2014; Bertram et al., 2015; Johnson et al., 2015; IRENA, 2016; A. Smith et al., 2016; Berrueta et al., 2017; McCollum et al., 2018 B u i l d i n g s A c c e l e r a t i n g E n e r g y E f f i c i e n c y I m p r o v e m e n t B e h a v i o u r a l R e s p o n s e Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities 5 5 506 Economic-Demand (continued) Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Meeting Energy Demand Sustainable Economic Growth and Employment Innovation and New Infrastructure (9.2/9.4/9.5) Housing (11.1) ↑  [+2]    ↑  [+2]    ↑ [+2]    ↑ [+3]    Renewable energies could potentially serve as the main source to meet Creutzig et al. (2014) assessed the potential for renewable energies in Adoption of smart meters and smart grids following community-based Ensuring access to basic housing services implies that households have energy demand in rapidly growing developing country cities. Ali et al. the European region. They found that a European energy transition with social marketing help in infrastructure expansion. Statutory norms to access to modern energy forms. (Quote from McCollum et al., 2018) (2015) estimated the potential of solar, wind and biomass renewable a high-level of renewable energy installations in the periphery could act enhance energy and resource efficiency in buildings is encouraging Solar roof tops in Macau make cities sustainable. Introduction of energy options to meet part of the electricity demand in Karachi, as an economic stimulus, decrease trade deficits and possibly have green building projects. Introduction of incentives and norms for solar incentives and norms for solar/white/green rooftops in cities are helping Pakistan. positive employment effects. Provision of energy access can play a rooftops/white/green roofs in cities are helping to accelerate innovation to accelerate the expansion of the infrastructure. critical enabling role for new productive activities, livelihoods and and the expansion of infrastructure. employment. Reliable access to modern energy services can have an important influence on productivity and earnings (McCollum et al., 2018). Li et al., 2013; Peng and Lu, 2013; Pietzcker, 2013; Pode, 2013; Yanine Grogan and Sadanand, 2013; Pueyo et al., 2013; Rao et al., 2013; Roy et al., 2018; Anda and Temmen, 2014 Bhattacharyya et al., 2016; Song et al., 2016; UN, 2016; McCollum et and Sauma, 2013; Zulu and Richardson, 2013; Connolly et al., 2014; Chakravorty et al., 2014; Creutzig et al., 2014; Ali et al., 2015; Bernard al., 2018; Roy et al., 2018 Creutzig et al., 2014; Pietzcker et al., 2014; Ali et al., 2015; O’Mahony and Torero, 2015; Byravan et al., 2017; McCollum et al., 2018 and Dufour, 2015; Abanda et al., 2016; Mittlefehldt, 2016; Biligii et al., 2017; Byravan et al., 2017; Islar et al., 2017; Ozturk et al., 2017 Energy Savings ( 7.3/7.a/7.b) Promote Sustained, Inclusive Economic Growth (8.3) Build Resilient Infrastructure (9.1) Make Cities and Human Settlements Inclusive, Safe, Resilient ↑  [+2]    ↓ [‐2]    ↑  [+2]    ↑  [+2]    Behavioural responses will reduce the volume of transport needs and, by Policy contradictions (e.g., standards, efficient technologies leading to As people prefer more mass transportation – train lines, tram lines, Climate change threatens to worsen poverty, therefore pro-poor extension, energy demand. increased electricity prices leading the poor to switch away from BRTs, gondola lift systems, bicycle-sharing systems and hybrid buses – mitigation policies are needed to reduce this threat; for example, clean(er) fuels) and unintended outcomes (e.g., redistribution of income and telecommuting, the need for new infrastructure increases. investing more and better in infrastructure by leveraging private generated by carbon taxes) results in contradictions of the primary aims resources and using designs that account for future climate change and of (productive) job creation and poverty alleviation, and in trade-offs the related uncertainty. between mitigation, adaptation and development policies. Detailed assessments of mitigation policies consequences requires developing methods and reliable evidence to enable policymakers to more systematically identify how different social groups may be affected by the different available policy options. Figueroa and Ribeiro, 2013; Ahmad and Puppim de Oliveira, 2016 Lucas and Pangbourne, 2014; Suckall et al., 2014; Klausbruckner et al., Dulac, 2013; Aamaas and Peters, 2017; Martínez-Jaramillo et al., 2017; Ahmad and Puppim de Oliveira, 2016; Hallegatte et al., 2016a 2016 Xylia and Silveira, 2017 Energy Savings ( 7.3/7.a/7.b) Promote Sustained, Inclusive Economic Growth (8.3) Build Resilient Infrastructure (9.1) Make Cities Sustainable (11.2/11.3) ↑  [+2]    ↑ / ↓ [+2,‐2]    ↑  [+2]    ↑  [+2]    Accelerating efficiency in tourism transport reduces energy demand Significant opportunities to slow travel growth and improve efficiency Combining promotion of mass transportation – train lines, tram lines, The two most important elements of making cities sustainable are (China). exist and, similarly, alternatives to petroleum exist but have different BRTs, gondola lift systems, bicycle-sharing systems and hybrid buses – efficient buildings and transport (e.g., Macau). characteristics in terms of availability, cost, distribution, infrastructure, and telecommuting reduces traffic and significantly contributes to storage and public acceptability. Production of new technologies, fuels meeting climate targets. A comprehensive package of complementary and infrastructure can favour economic growth; however, efficient mitigation options is necessary for deep and sustained emissions financing of increased capital spending and infrastructure is critical. reductions. In Sweden, a public bus fleet is aiming more towards decarbonization than efficiency. Shukxin et al., 2016 Gouldson et al., 2015; Karkatsoulis et al., 2016 Dulac, 2013; Aamaas and Peters, 2017; Martínez-Jaramillo et al., 2017; Song et al., 2016 Xylia and Silveira, 2017 Increase Share of Renewable (7.2) Promote Sustained, Inclusive Economic Growth (8.3) Help Building Inclusive Infrastructure (9.1/9.a) Make Cities and Human Settlements Inclusive, Safe, Resilient ↑  [+2]    ↑ / ↓ [+2,‐2]    ↑  [+2]    ↑  [+2]    Biofuel increases share of the renewables but can perform poorly if too The decarbonization of the freight sector tends to occur in the second Lack of appropriate infrastructure leads to limited access to jobs for the In rapidly growing cities, the carbon savings from investments at scale, many countries increase their use of biofuel, whereas electrification part of the century, and the sector decarbonizes by a lower extent than urban poor (Africa, Latin America, India). in cost-effective low-carbon measures, could be quickly overwhelmed – performs best when many other countries implement this technology. the rest of the economy. Decarbonizing road freight on a global scale in as little as 7 years – by the impacts of sustained population and The strategies are not mutually exclusive and simultaneous remains a challenge even when notable progress in biofuels and electric economic growth, highlighting the need to build capacities that enable implementation of some provides synergies for national energy security. vehicles has been accounted for. the exploitation not only of the economically attractive options in the Therefore, it is important to consider the results of material and short term but also of those deeper and more structural changes that are contextual factors that co-evolve. Electric vehicles using electricity from likely to be needed in the longer term. With hybrid electric vehicles and renewables or low carbon sources combined with e-mobility options plug-in electric vehicles, there is the emergence of new concepts in such as trolley buses, metros, trams and electro buses, as well as transportation, such as electric highways. promote walking and biking, especially for short distances, need consideration. Ajanovic, 2015; Månsson, 2016; Alahakoon, 2017; Wolfram et al., 2017 IPCC, 2014; Creutzig et al., 2015; Carrara and Longden, 2017 Figueroa et al., 2013; Gouldson et al., 2015; Vasconcellos and Figueroa et al., 2013; Gouldson et al., 2015; Vasconcellos and Mendonça, 2016; Lall et al., 2017 Mendonça, 2016; Alahakoon, 2017 T r a n s p o r t B u i l d i n g s I m p r o v e d A c c e s s a n d F u e l S w i t c h t o A c c e l e r a t i n g E n e r g y E f f i c i e n c y I m p r o v e d A c c e s s a n d F u e l S w i t c h t o M o d e r n B e h a v i o u r a l R e s p o n s e M o d e r n L o w - c a r b o n E n e r g y I m p r o v e m e n t L o w - c a r b o n E n e r g y Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 5 5 507 Economic-Supply Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Sustainable and Modern Energy (7.2/7.a) Innovation and Growth (8.1/8.2/8.4) Inclusive and Sustainable Industrialization (9.2/9.4) Disaster Preparedness and Prevention (11.5) ↑ [+3]    ~ [0]    ~  / ↓ [0,‐1]    ↑ [+2]    Decarbonization of the energy system through an upscaling of Decarbonization of the energy system through an upscaling of A rapid upscaling of renewable energies could necessitate the early Deployment of renewable energy and improvements in energy efficiency renewables will greatly facilitate access to clean, affordable and reliable renewables and energy efficiency is consistent with sustained economic retirement of fossil energy infrastructure (e.g., power plants, refineries, globally will aid climate change mitigation efforts, and this, in turn, can energy. Hydropower plays an increasingly important role for the global growth and resource decoupling. Long-term scenarios point towards pipelines) on a large scale. The implications of this could in some cases help to reduce the exposure of people to certain types of disasters and electricity supply. This mitigation option is in line with the targets of slight consumption losses caused by a rapid and pervasive expansion of be negative, unless targeted policies can help alleviate the burden on extreme events (McCollum et al., 2018). SDG7 under the caveat of a transition to modern biomass. such energy solutions. Whether sustainable growth, as an overarching industry (McCollum et al., 2018). concept, is attainable or not is more disputed in the literature. Existing literature is also undecided as to whether or not access to modern energy services causes economic growth (McCollum et al., 2018). Rogelj et al., 2013; Cherian, 2015; Jingura and Kamusoko, 2016 Jackson and Senker, 2011; Bonan et al., 2014; Clarke et al., 2014; NCE, Fankhaeser et al., 2008; McCollum et al., 2008; Guivarch et al., 2011; Tully, 2006; Riahi et al., 2012; Daut et al., 2013; IPCC, 2014; Hallegatte 2014; OECD, 2017; York and McGee, 2017; McCollum et al., 2018 Bertram et al., 2015; Johnson et al., 2015 et al., 2016b; McCollum et al., 2018 Sustainable and Modern Energy (7.2/7.a) Innovation and Growth (8.1/8.2/8.4) Innovation and New Infrastructure (9.2/9.4/9.5) ↑ [+3]    ↑ [+1]    ↑ [+1]    [0] Increased use of modern biomass will facilitate access to clean, Decarbonization of the energy system through an upscaling of Access to modern and sustainable energy will be critical to sustain affordable and reliable energy. This mitigation option is in line with the renewables will greatly facilitate access to clean, affordable and reliable economic growth. No direct interaction targets of SDG7. energy. Rogelj et al., 2013; Cherian, 2015; Jingura and Kamusoko, 2016 Jingura and Kamusoko, 2016 Jingura and Kamusoko, 2016; Shahbaz et al., 2016 Sustainable and Modern Energy (7.2/7.a) Innovation and Growth (8.1/8.2/8.4) Innovation and New Infrastructure (9.2/9.4/9.5) ↑ [1]    ↑ [1]    ↓ [‐1]    [0] Increased use of nuclear power can provide stable baseload power Local employment impact and reduced price volatility. Legacy cost of waste and abandoned reactors. supply and reduce price volatility. No direct interaction IPCC, 2014 IPCC, 2014 Marra and Palmer, 2011; Greenberg et al., 2013; Schwenk-Ferrero, 2013; Skipperud et al., 2013; Tyler et al., 2013; IPCC, 2014 Sustainable and Modern Energy (7.2/7.a) Innovation and Growth (8.1/8.2/8.4) Innovation and New Infrastructure (9.2/9.4/9.5) ↑ [+2]    ↑ [+1]    ↑ [+1]    [0] Increased use of modern biomass will facilitate access to clean, See positive impacts of bioenergy use. See positive impacts of bioenergy use and CCS/CCU in industrial affordable and reliable energy. demand. No direct interaction IPCC, 2014 Ensure energy access and promote investment in new Innovation and Growth (8.1/8.2/8.4) Innovation and New Infrastructure (9.2/9.4/9.5) technologies (7.1/7.b) ↑ [+2]    ↓ [‐1]    ↑ [+1]    [0] Advanced and cleaner fossil fuel technology is in line with the targets of Lock-in of human and physical capital in the fossil resources industry. See positive impacts of CCS/CCU in industrial demand. SDG7. No direct interaction IPCC, 2014 IPCC, 2005, 2014; Benson and Cole, 2008; Fankhaeser et al., 2008; Vergragt et al., 2011; Markusson et al., 2012; Shackley and Thompson, 2012; Bertram et al., 2015; Johnson et al., 2015 A d v a n c e d C o a l R e p l a c i n g C o a l N u c l e a r / A d v a n c e d I n c r e a s e d U s e o f N o n - b i o m a s s R e n e w a b l e s - s o l a r , C C S : F o s s i l C C S : B i o e n e r g y N u c l e a r B i o m a s s w i n d , h y d r o Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities 5 5 508 Economic-Other Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Energy Efficiency, Universal Access (7.1/7.3) Sustained and Inclusive Economic Growth (8.2) Infrastructure Building and Promotion of Inclusive Industrialization (9.1/9.2) ↑  [+1]    ↑ [+1]    ↑ [+1]    [0] Reducing global food supply chain losses have several important 23–24% of total cropland and fertilizers are used to produce losses. So By targeting infrastructure, processing and distribution losses, wastage secondary benefits like conserving energy. reduction in food losses will help to diversify these valuable resources in food systems can be minimized. 23–24% of total cropland and into other productive activities. fertilizers are used to produce losses. So reduction in food losses will No interaction help to diversify these valuable resources into other productive activities. Kummu et al., 2012 Kummu et al., 2012; Hiç et al., 2016 Ingram, 2011; Beddington et al., 2012; Kummu et al., 2012; Hiç et al., 2016; Lamb et al., 2016 Sustainable and Modern Energy (7.b) Sustainable Growth (8.2) Infrastructure Building, Promotion of Inclusive Industrialization and Innovation (9.1/9.2/9.5/9.b) ↑  [+1]    ↑ / ↓ [+2,‐1]    ↑ / ↓ [+2,‐2]    [0] Conventional agricultural biotechnology methods such as energy Many developing countries including Gulf States will benefit from CSA Reduced research support and delayed industrialization will have an efficient farming can help in sequestration of soil carbon. Modern given the central role of agriculture in their economic and social adverse effect on food security and nourishment of children. Organic biotechnologies such as green energy and N-efficient GM crops can also development. (Quoted from Behnassi et al. 2014). Low commodity farming technologies utilizing bio-based fertilizers (composted human help in C-sequestration. Biotech crops allow farmers to use less – and prices have reduced the incentive to invest in yield growth and have led and animal manure) are some of the conventional biotechnological environmentally friendly – energy and practice soil carbon to declining farm labour and farm capital investment. (Quoted from options for reducing artificial fertilizer use (Lakshmi et al., 2015). CSA sequestration. Biofuels, both from traditional and GMO crops, such as Lamb et al., 2016) requires huge financial investment and institutional innovation. CSA is sugar cane, oilseed, rapeseed and jatropha, can be produced. Green committed to new ways of engaging in participatory research and energy programmes through plantations of perennial nonedible oilseed partnerships with producers (Steenwerth et al., 2014). Technologies producing plants and production of biodiesel for direct use in the energy used on-farm and during food processing to increase productivity which no direct interaction sector or blending biofuels with fossil fuels in certain proportions can also helps in adaptation and/or mitigation are new, so convincing thereby minimize fossil fuel use. (Quoted from Lakshmi et al., 2015) GM potential customers is difficult. Also, low-awareness of CSA, crops reduce demand for fossil fuel-based inputs. inaccessible language, high costs, lack of verified impact of technologies, hard to reach and train farmers, low consumer demand and unequal distribution of costs/benefits across supply chains are barriers to CSA technology adoption (Long et al., 2016). Low commodity prices have reduced the incentive to invest in yield growth and have led to declining investment in research and development (Lamb et al., Johnson et al., 2007; Sarin et al., 2007; Treasury, 2009; Jain and Behnassi et al., 2014; Lamb et al., 2016 E2v0e1n6s)on, 1999; Behnassi et al., 2014; Steenwerth et al., 2014; Lakshmi Sharma, 2010; Lybbert and Sumner, 2010; Mtui, 2011; Lakshmi et al., et al., 2015; Lamb et al., 2016; Long et al., 2016 2015 Energy Efficiency (7.3) Sustainable Economic Growth (8.4) Technological Upgradation and Innovation (9.2) ↑  [+1] & J « ↑  [+1] & J « ↑  [+2]    [0] Scenarios where zero human-edible concentrate feed is used for Exploiting the increasingly decoupled interactions between crops and Complete genome maps for poultry and cattle now exist, and these livestock, non-renewable energy use is reduced by 36%. livestock could be beneficial for promoting structural changes in the open up the way to possible advances in evolutionary biology, animal livestock sector and is a prerequisite for the sustainable growth of the breeding and animal models for human diseases. Genomic selection sector. (Quoted from Herrero et al., 2013) should be able to at least double the rate of genetic gain in the dairy No direct interaction industry. (Quoted from Thornton, 2010) Nanotechnology, biogas technology and separation technologies are disruptive technologies that enhance biogas production from anaerobic digesters or to reduce odours Schader et al., 2015 Herrero and Thornton, 2013; Herrero et al., 2013 Sansoucy, 1995; Burton, 2007; Thornton, 2010 A g r i c u l t u r e a n d L i v e s t o c k G r e e n h o u s e G a s R e d u c t i o n B e h a v i o u r a l R e s p o n s e : L a n d - b a s e d G r e e n h o u s e G a s R e d u c t i o n a n d S o i l C a r b o n f r o m I m p r o v e d L i v e s t o c k S u s t a i n a b l e H e a l t h y D i e t s a n d S e q u e s t r a t i o n P r o d u c t i o n a n d M a n u r e R e d u c e d F o o d W a s t e Sustainable Development, Poverty Eradication and Reducing Inequalities Chapter 5 5 5 509 Economic-Other (continued) Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Interaction Score Evidence Agreement Confidence Energy Efficiency (7.3) Sustainable Economic Growth (8.4) Infrastructure, Promotion of Inclusive Industrialization (9.1/9.2/9.5) ↑ / ↓ [+1,‐1]    ↑  [+1]    ↑ / ↓ [+1,‐1]    [0] Consider the entire sinks and reservoirs of GHG while developing the Efforts by the Government of Zambia to reduce emissions by REDD+ Expanding road networks are recognized as one of the main drivers of nationally appropriate mitigation actions. For countries with a have contributed to erosion control, ecotourism and pollination valued deforesting and forest degradation, diminishing forest benefits to significant contribution of forest degradation (and GHG emissions) from at 2.5% of the country's GDP. Partnerships between local forest communities, On the other hand, roads can enhance market access, wood fuels, this should be considered. (Quoted from Bastos Lima et al., managers, community enterprises and private sector companies can thereby boosting local benefits (SDG 1) from the commercialization of No direct interaction 2017). Biomass for energy is recognized as often being inefficient, and is support local economies and livelihoods, and boost regional and forest products. (Quoted from Katila et al., 2017). Efforts by the often harvested in an unsustainable manner, but is a renewable energy national economic growth. Government of Zambia to reduce emissions by REDD+ have contributed source. to erosion control, ecotourism and pollination valued at 2.5% of the country's GDP Bastos Lima et al., 2017; Katila et al., 2017 Turpie et al., 2015; Epstein and Theuer, 2017; Katila et al., 2017 Turpie et al., 2015; Epstein and Theuer, 2017; Katila et al., 2017 Energy Conservation (7.3/7.b) Decent Job Creation and Sustainable Economic Growth Improving Air Quality, Green and Public Spaces (8.3/8.4) (11.6/11.7/11.a/11.b) ↑  [+1]    ↑  [+2]    [0] ↑  [+2]     The US Forest Service estimates that an average NYC street tree (urban Many tree plantations worldwide have higher growth rates which can Many urban tree plantations worldwide are created with a focus on afforestation) produces 209 USD in annual benefits, which is primarily provide higher rates of returns for investors. Agroforestry initiatives that multiple benefits, like air quality improvement, cultural preference for driven by aesthetic (90 USD per tree) and energy savings (from shade) offer significant opportunities for projects to provide benefits to green nature, healthy community interaction as well as temperature benefits (47.63 USD per tree). smallholder farmers can also help address land degradation through No direct interaction control and biodiversity enhancement goals. community-based efforts in more marginal areas. Mangroves reduce impacts of disasters (cyclones/storms/floods) and enhance water quality, fisheries, tourism businesses and livelihoods. Jones and McDermott, 2018 Zomer et al., 2008; Kibria, 2015 Chen and Qi, 2018; Fu et al., 2018; Kowarik, 2018; McKinney and Ingo, 2018; McPherson et al., 2018; Pei et al., 2018 Universal Access (7.3) Decent Job Creation and Sustainable Economic Growth Technological Upgradation and Innovation, Promotion of Improving Air Quality, Green and Public Spaces, Peri-urban (8.3/8.4) Inclusive Industrialization (9.1/9.2/9.5) Spaces (11.6/11.7/11.a/11.b) ↑  [+1]    ↑  [+2]    ↑  [+2]    ↑  [+2]    The trade of wood pellets from clean wood waste should be facilitated Some standards seek primarily to coordinate global trade, many purport Capacity for processing certified timber is often underutilized, due to the Many urban tree plantations worldwide are created with a focus on with less administrative import barriers by the EU, in order to have this to promote ecological sustainability and social justice or to limited supply available. As a result, manufacturing firms that are multiple benefits, like air quality improvement, cultural preference for new option seriously accounted for as a future resource for energy. institutionalize CSR, for example, labour standards developed in the seeking to tap into green markets often turn to other sources of timber. green nature, healthy community interaction as well as temperature (Quoted from Sikkema et al., 2014) Recommends further harmonization wake of sweatshops and child labour scandals. Environmental standards (Quoted from Bartley, 2010) Responsible sourcing, when integrated into control and biodiversity enhancement goals. People's preference for of legal harvesting, sustainable sourcing and cascaded use requirements for pollution control, etc. Indonesian factories may seek advantages business practices, can enable retailers to better manage brand value urban forest gardens are encouraging new urban green spaces, and tree for woody biomass for energy with the current requirements of through non-price competition—perhaps by highlighting decent and reputation by avoiding negative public relations, as well as selection helps in building resilience to disaster. voluntary SFM certification schemes. working conditions or the existence of a union—or to see trade maintaining and enhancing brand integrity (Huang et al., 2013). associations or government promoting the country as a responsible sourcing location. Sikkema et al., 2014 Bartley, 2010 Bartley, 2010; Huang et al., 2013 Chen and Qi, 2018; Fu et al., 2018; Kowarik, 2018; McKinney and Ingo, 2018; McPherson et al., 2018; Pei et al., 2018 [0] [0] [0] [0] No direct interaction No direct interaction No direct interaction No direct interaction [0] [0] [0] [0] No direct interaction No direct interaction No direct interaction No direct interaction [0] [0] [0] [0] No direct interaction No direct interaction No direct interaction No direct interaction O c e a n s F o r e s t E n h a n c e d O c e a n I r o n B e h a v i o u r a l R e s p o n s e ( R e s p o n s i b l e B l u e C a r b o n A f f o r e s t a t i o n a n d R e f o r e s t a t i o n R e d u c e d D e f o r e s t a t i o n , R E D D + W e a t h e r i n g F e r t i l i z a t i o n S o u r c i n g ) Chapter 5 Sustainable Development, Poverty Eradication and Reducing Inequalities References Note that this reference list does not account for the references in Table 5.2, for which a separate reference list is provided. 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Ebi (USA), Neville Ellis (Australia), Andreas Fischlin (Switzerland), Tania Guillén Bolaños (Germany/Nicaragua), Kiane de Kleijne (Netherlands/EU), Valérie Masson-Delmotte (France), Richard Millar (UK), Elvira S. Poloczanska (Germany/UK), Hans-Otto Pörtner (Germany), Andy Reisinger (New Zealand), Joeri Rogelj (Austria/Belgium), Sonia I. Seneviratne (Switzerland), Chandni Singh (India), Petra Tschakert (Australia/Austria), Nora M. Weyer (Germany) Notes: Note that subterms are in italics beneath main terms. This glossary defines some specific terms as the Lead Authors intend them to be interpreted in the context of this report. Blue, italicized words indicate that the term is defined in the Glossary. This annex should be cited as: IPCC, 2018: Annex I: Glossary [Matthews, J.B.R. (ed.)]. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)]. In Press 541 Annex I Glossary 1.5°C pathway See Pathways. ecological or behavioural. See also Adaptation, Adaptive capacity and Maladaptive actions (Maladaptation). 1.5°C warmer worlds Projected worlds in which global warming has reached and, unless otherwise indicated, been limited to 1.5°C Adaptation pathways See Pathways. above pre-industrial levels. There is no single 1.5°C warmer world, Adaptive capacity The ability of systems, institutions, humans and and projections of 1.5°C warmer worlds look different depending on other organisms to adjust to potential damage, to take advantage of whether it is considered on a near-term transient trajectory or at climate opportunities, or to respond to consequences. This glossary entry builds AI equilibrium after several millennia, and, in both cases, if it occurs with or from definitions used in previous IPCC reports and the Millennium without overshoot. Within the 21st century, several aspects play a role Ecosystem Assessment (MEA, 2005). See also Adaptation, Adaptation for the assessment of risk and potential impacts in 1.5°C warmer worlds: options and Maladaptive actions (Maladaptation). the possible occurrence, magnitude and duration of an overshoot; the way in which emissions reductions are achieved; the ways in which Adaptive governance See Governance. policies might be able to influence the resilience of human and natural Aerosol A suspension of airborne solid or liquid particles, with a systems; and the nature of the regional and sub-regional risks. Beyond typical size between a few nanometres and 10 μm that reside in the the 21st century, several elements of the climate system would continue atmosphere for at least several hours. The term aerosol, which includes to change even if the global mean temperatures remain stable, including both the particles and the suspending gas, is often used in this report further increases of sea level. in its plural form to mean aerosol particles. Aerosols may be of either 2030 Agenda for Sustainable Development A UN resolution natural or anthropogenic origin. Aerosols may influence climate in in September 2015 adopting a plan of action for people, planet and several ways: through both interactions that scatter and/or absorb prosperity in a new global development framework anchored in 17 radiation and through interactions with cloud microphysics and other Sustainable Development Goals (UN, 2015). See also Sustainable cloud properties, or upon deposition on snow- or ice-covered surfaces Development Goals (SDGs). thereby altering their albedo and contributing to climate feedback. Atmospheric aerosols, whether natural or anthropogenic, originate from Acceptability of policy or system change The extent to which two different pathways: emissions of primary particulate matter (PM), a policy or system change is evaluated unfavourably or favourably, and formation of secondary PM from gaseous precursors. The bulk of or rejected or supported, by members of the general public (public aerosols are of natural origin. Some scientists use group labels that refer acceptability) or politicians or governments (political acceptability). to the chemical composition, namely: sea salt, organic carbon, black Acceptability may vary from totally unacceptable/fully rejected to totally carbon (BC), mineral species (mainly desert dust), sulphate, nitrate, and acceptable/fully supported; individuals may differ in how acceptable ammonium. These labels are, however, imperfect as aerosols combine policies or system changes are believed to be. particles to create complex mixtures. See also Short-lived climate forcers Adaptability See Adaptive capacity. (SLCF) and Black carbon (BC). Adaptation In human systems, the process of adjustment to actual Afforestation Planting of new forests on lands that historically have or expected climate and its effects, in order to moderate harm or exploit not contained forests. For a discussion of the term forest and related beneficial opportunities. In natural systems, the process of adjustment terms such as afforestation, reforestation and deforestation, see the IPCC to actual climate and its effects; human intervention may facilitate Special Report on Land Use, Land-Use Change, and Forestry (IPCC, 2000), adjustment to expected climate and its effects. information provided by the United Nations Framework Convention on Climate Change (UNFCCC, 2013) and the report on Definitions and Incremental adaptation Methodological Options to Inventory Emissions from Direct Human- Adaptation that maintains the essence and integrity of a system or induced Degradation of Forests and Devegetation of Other Vegetation process at a given scale. In some cases, incremental adaptation can Types (IPCC, 2003). See also Reforestation, Deforestation, and Reducing accrue to result in transformational adaptation (Termeer et al., 2017; Emissions from Deforestation and Forest Degradation (REDD+). Tàbara et al., 2018). Agreement In this report, the degree of agreement within the Transformational adaptation scientific body of knowledge on a particular finding is assessed based on Adaptation that changes the fundamental attributes of a socio- multiple lines of evidence (e.g., mechanistic understanding, theory, data, ecological system in anticipation of climate change and its impacts. models, expert judgement) and expressed qualitatively (Mastrandrea et Adaptation limits al., 2010). See also Evidence, Confidence, Likelihood and Uncertainty. The point at which an actor’s objectives (or system needs) cannot be Air pollution Degradation of air quality with negative effects secured from intolerable risks through adaptive actions. on human health or the natural or built environment due to the • Hard adaptation limit: No adaptive actions are possible to avoid introduction, by natural processes or human activity, into the atmosphere intolerable risks. of substances (gases, aerosols) which have a direct (primary pollutants) • Soft adaptation limit: Options are currently not available to avoid or indirect (secondary pollutants) harmful effect. See also Aerosol and intolerable risks through adaptive action. Short-lived climate forcers (SLCF). See also Adaptation options, Adaptive capacity and Maladaptive Albedo The fraction of solar radiation reflected by a surface or actions (Maladaptation). object, often expressed as a percentage. Snow-covered surfaces have a Adaptation behaviour See Human behaviour. high albedo, the surface albedo of soils ranges from high to low, and vegetation-covered surfaces and the oceans have a low albedo. The Adaptation limits See Adaptation. Earth’s planetary albedo changes mainly through varying cloudiness and Adaptation options The array of strategies and measures that are changes in snow, ice, leaf area and land cover. available and appropriate for addressing adaptation. They include a Ambient persuasive technology Technological systems and wide range of actions that can be categorized as structural, institutional, environments that are designed to change human cognitive processing, 542 Glossary Annex I attitudes and behaviours without the need for the user’s conscious the term BAU has fallen out of favour because the idea of business as attention. usual in century-long socio-economic projections is hard to fathom. In the context of transformation pathways, the term baseline scenarios Anomaly The deviation of a variable from its value averaged over a refers to scenarios that are based on the assumption that no mitigation reference period. policies or measures will be implemented beyond those that are already Anthropocene The ‘Anthropocene’ is a proposed new geological in force and/or are legislated or planned to be adopted. Baseline epoch resulting from significant human-driven changes to the structure scenarios are not intended to be predictions of the future, but rather AI and functioning of the Earth System, including the climate system. counterfactual constructions that can serve to highlight the level of Originally proposed in the Earth System science community in 2000, the emissions that would occur without further policy effort. Typically, proposed new epoch is undergoing a formalization process within the baseline scenarios are then compared to mitigation scenarios that are geological community based on the stratigraphic evidence that human constructed to meet different goals for greenhouse gas (GHG) emissions, activities have changed the Earth System to the extent of forming atmospheric concentrations or temperature change. The term baseline geological deposits with a signature that is distinct from those of the scenario is often used interchangeably with reference scenario and no Holocene, and which will remain in the geological record. Both the policy scenario. See also Emission scenario and Mitigation scenario. stratigraphic and Earth System approaches to defining the Anthropocene Battery electric vehicle (BEV) See Electric vehicle (EV). consider the mid-20th Century to be the most appropriate starting date, although others have been proposed and continue to be discussed. The Biochar Stable, carbon-rich material produced by heating biomass Anthropocene concept has been taken up by a diversity of disciplines in an oxygen-limited environment. Biochar may be added to soils to and the public to denote the substantive influence humans have had on improve soil functions and to reduce greenhouse gas emissions from the state, dynamics and future of the Earth System. See also Holocene. biomass and soils, and for carbon sequestration. This definition builds from IBI (2018). Anthropogenic Resulting from or produced by human activities. See also Anthropogenic emissions and Anthropogenic removals. Biodiversity Biological diversity means the variability among living organisms from all sources, including, inter alia, terrestrial, marine and Anthropogenic emissions Emissions of greenhouse gases (GHGs), other aquatic ecosystems and the ecological complexes of which they precursors of GHGs and aerosols caused by human activities. These are part; this includes diversity within species, between species and of activities include the burning of fossil fuels, deforestation, land use ecosystems (UN, 1992). and land-use changes (LULUC), livestock production, fertilisation, waste management and industrial processes. See also Anthropogenic and Bioenergy Energy derived from any form of biomass or its metabolic Anthropogenic removals. by-products. See also Biomass and Biofuel. Anthropogenic removals Anthropogenic removals refer to the Bioenergy with carbon dioxide capture and storage withdrawal of GHGs from the atmosphere as a result of deliberate (BECCS) Carbon dioxide capture and storage (CCS) technology applied human activities. These include enhancing biological sinks of CO2 and to a bioenergy facility. Note that depending on the total emissions of using chemical engineering to achieve long-term removal and storage. the BECCS supply chain, carbon dioxide (CO2) can be removed from the Carbon capture and storage (CCS) from industrial and energy-related atmosphere. See also Bioenergy and Carbon dioxide capture and storage sources, which alone does not remove CO2 in the atmosphere, can reduce (CCS). atmospheric CO2 if it is combined with bioenergy production (BECCS). See Biofuel A fuel, generally in liquid form, produced from biomass. also Anthropogenic emissions, Bioenergy with carbon dioxide capture Biofuels currently include bioethanol from sugarcane or maize, biodiesel and storage (BECCS) and Carbon dioxide capture and storage (CCS). from canola or soybeans, and black liquor from the paper-manufacturing Artificial intelligence (AI) Computer systems able to perform tasks process. See also Biomass and Bioenergy. normally requiring human intelligence, such as visual perception and Biomass Living or recently dead organic material. See also Bioenergy speech recognition. and Biofuel. Atmosphere The gaseous envelope surrounding the earth, divided Biophilic urbanism Designing cities with green roofs, green walls into five layers – the troposphere which contains half of the Earth’s and green balconies to bring nature into the densest parts of cities in atmosphere, the stratosphere, the mesosphere, the thermosphere, order to provide green infrastructure and human health benefits. See also and the exosphere, which is the outer limit of the atmosphere. The dry Green infrastructure. atmosphere consists almost entirely of nitrogen (78.1% volume mixing ratio) and oxygen (20.9% volume mixing ratio), together with a number Black carbon (BC) Operationally defined aerosol species based on of trace gases, such as argon (0.93 % volume mixing ratio), helium and measurement of light absorption and chemical reactivity and/or thermal radiatively active greenhouse gases (GHGs) such as carbon dioxide (CO2) stability. It is sometimes referred to as soot. BC is mostly formed by the (0.04% volume mixing ratio) and ozone (O3). In addition, the atmosphere incomplete combustion of fossil fuels, biofuels and biomass but it also contains the GHG water vapour (H2O), whose amounts are highly occurs naturally. It stays in the atmosphere only for days or weeks. It is variable but typically around 1% volume mixing ratio. The atmosphere the most strongly light-absorbing component of particulate matter (PM) also contains clouds and aerosols. See also Troposphere, Stratosphere, and has a warming effect by absorbing heat into the atmosphere and Greenhouse gas (GHG) and Hydrological cycle. reducing the albedo when deposited on snow or ice. See also Aerosol. Atmosphere–ocean general circulation model (AOGCM) See Blue carbon Blue carbon is the carbon captured by living organisms Climate model. in coastal (e.g., mangroves, salt marshes, seagrasses) and marine ecosystems, and stored in biomass and sediments. Attribution See Detection and attribution. Burden sharing (also referred to as Effort sharing) In the Baseline scenario In much of the literature the term is also context of mitigation, burden sharing refers to sharing the effort of synonymous with the term business-as-usual (BAU) scenario, although reducing the sources or enhancing the sinks of greenhouse gases (GHGs) 543 Annex I Glossary from historical or projected levels, usually allocated by some criteria, as Carbon neutrality See Net zero CO emissions. well as sharing the cost burden across countries. 2 Business as usual (BAU) Carbon price The price for avoided or released carbon dioxide (CO2) See Baseline scenario. or CO2-equivalent emissions. This may refer to the rate of a carbon tax, Carbon budget This term refers to three concepts in the literature: or the price of emission permits. In many models that are used to assess (1) an assessment of carbon cycle sources and sinks on a global level, the economic costs of mitigation, carbon prices are used as a proxy to through the synthesis of evidence for fossil fuel and cement emissions, represent the level of effort in mitigation policies. AI land-use change emissions, ocean and land CO2 sinks, and the resulting Carbon sequestration The process of storing carbon in a carbon atmospheric CO2 growth rate. This is referred to as the global carbon pool. See also Blue carbon, Carbon dioxide capture and storage (CCS), budget; (2) the estimated cumulative amount of global carbon dioxide Uptake and Sink. emissions that that is estimated to limit global surface temperature to a given level above a reference period, taking into account global Carbon sink See Sink. surface temperature contributions of other GHGs and climate forcers; (3) Clean Development Mechanism (CDM) A mechanism defined the distribution of the carbon budget defined under (2) to the regional, under Article 12 of the Kyoto Protocol through which investors national, or sub-national level based on considerations of equity, costs or (governments or companies) from developed (Annex B) countries may efficiency. See also Remaining carbon budget. finance greenhouse gas (GHG) emission reduction or removal projects Carbon cycle The term used to describe the flow of carbon (in in developing countries (Non-Annex B), and receive Certified Emission various forms, e.g., as carbon dioxide (CO2), carbon in biomass, and Reduction Units (CERs) for doing so. The CERs can be credited towards the carbon dissolved in the ocean as carbonate and bicarbonate) through commitments of the respective developed countries. The CDM is intended the atmosphere, hydrosphere, terrestrial and marine biosphere and to facilitate the two objectives of promoting sustainable development lithosphere. In this report, the reference unit for the global carbon cycle (SD) in developing countries and of helping industrialised countries to is GtCO2 or GtC (Gigatonne of carbon = 1 GtC = 1015 grams of carbon. reach their emissions commitments in a cost-effective way. This corresponds to 3.667 GtCO2). Climate Climate in a narrow sense is usually defined as the average Carbon dioxide (CO2) A naturally occurring gas, CO2 is also a weather, or more rigorously, as the statistical description in terms of by-product of burning fossil fuels (such as oil, gas and coal), of burning the mean and variability of relevant quantities over a period of time biomass, of land-use changes (LUC) and of industrial processes (e.g., ranging from months to thousands or millions of years. The classical cement production). It is the principal anthropogenic greenhouse gas period for averaging these variables is 30 years, as defined by the World (GHG) that affects the Earth’s radiative balance. It is the reference gas Meteorological Organization. The relevant quantities are most often against which other GHGs are measured and therefore has a global surface variables such as temperature, precipitation and wind. Climate warming potential (GWP) of 1. See also Greenhouse gas (GHG). in a wider sense is the state, including a statistical description, of the Carbon dioxide capture and storage (CCS) climate system.A process in which a relatively pure stream of carbon dioxide (CO2) from industrial and Climate change Climate change refers to a change in the state of the energy-related sources is separated (captured), conditioned, compressed climate that can be identified (e.g., by using statistical tests) by changes and transported to a storage location for long-term isolation from the in the mean and/or the variability of its properties and that persists for an atmosphere. Sometimes referred to as Carbon capture and storage. See extended period, typically decades or longer. Climate change may be due also Carbon dioxide capture and utilisation (CCU), Bioenergy with carbon to natural internal processes or external forcings such as modulations dioxide capture and storage (BECCS) and Uptake. of the solar cycles, volcanic eruptions and persistent anthropogenic Carbon dioxide capture and utilisation (CCU) changes in the composition of the atmosphere or in land use. Note that A process in which the Framework Convention on Climate Change (UNFCCC), in its Article CO2 is captured and then used to produce a new product. If the CO2 is 1, defines climate change as: ‘a change of climate which is attributed stored in a product for a climate-relevant time horizon, this is referred directly or indirectly to human activity that alters the composition of the to as carbon dioxide capture, utilisation and storage (CCUS). Only then, global atmosphere and which is in addition to natural climate variability and only combined with CO2 recently removed from the atmosphere, can observed over comparable time periods.’ The UNFCCC thus makes a CCUS lead to carbon dioxide removal. CCU is sometimes referred to as distinction between climate change attributable to human activities carbon dioxide capture and use. See also Carbon dioxide capture and altering the atmospheric composition and climate variability attributable storage (CCS). to natural causes. See also Climate variability, Global warming, Ocean Carbon dioxide capture, utilisation and storage (CCUS) See acidification (OA) and Detection and attribution. Carbon dioxide capture and utilisation (CCU). Climate change commitment Climate change commitment is Carbon dioxide removal (CDR) Anthropogenic activities removing defined as the unavoidable future climate change resulting from inertia CO2 from the atmosphere and durably storing it in geological, terrestrial, in the geophysical and socio-economic systems. Different types of climate or ocean reservoirs, or in products. It includes existing and potential change commitment are discussed in the literature (see subterms). anthropogenic enhancement of biological or geochemical sinks and Climate change commitment is usually quantified in terms of the further direct air capture and storage, but excludes natural CO2 uptake not change in temperature, but it includes other future changes, for example directly caused by human activities. See also Mitigation (of climate in the hydrological cycle, in extreme weather events, in extreme climate change), Greenhouse gas removal (GGR), Negative emissions, Direct air events, and in sea level. carbon dioxide capture and storage (DACCS) and Sink. Constant composition commitment Carbon intensity The amount of emissions of carbon dioxide (CO2) The constant composition commitment is the remaining climate change released per unit of another variable such as gross domestic product that would result if atmospheric composition, and hence radiative forcing, (GDP), output energy use or transport. were held fixed at a given value. It results from the thermal inertia of the ocean and slow processes in the cryosphere and land surface. 544 Glossary Annex I Constant emissions commitment greenhouse gases (GHGs) and aerosols, generally derived using climate The constant emissions commitment is the committed climate change models. Climate projections are distinguished from climate predictions that would result from keeping anthropogenic emissions constant. by their dependence on the emission/concentration/radiative forcing scenario used, which is in turn based on assumptions concerning, for Zero emissions commitment example, future socioeconomic and technological developments that The zero emissions commitment is the climate change commitment may or may not be realized. that would result from setting anthropogenic emissions to zero. It is determined by both inertia in physical climate system components Climate-resilient development pathways (CRDPs) Trajectories AI (ocean, cryosphere, land surface) and carbon cycle inertia. that strengthen sustainable development and efforts to eradicate poverty and reduce inequalities while promoting fair and cross-scalar Feasible scenario commitment adaptation to and resilience in a changing climate. They raise the ethics, The feasible scenario commitment is the climate change that corresponds equity and feasibility aspects of the deep societal transformation needed to the lowest emission scenario judged feasible. to drastically reduce emissions to limit global warming (e.g., to 1.5°C) Infrastructure commitment and achieve desirable and liveable futures and well-being for all. The infrastructure commitment is the climate change that would result Climate-resilient pathways Iterative processes for managing if existing greenhouse gas and aerosol emitting infrastructure were used change within complex systems in order to reduce disruptions and until the end of its expected lifetime. enhance opportunities associated with climate change. See also Climate-compatible development (CCD) A form of development Development pathways (under Pathways), Transformation pathways building on climate strategies that embrace development goals and (under Pathways), and Climate-resilient development pathways (CRDPs). development strategies that integrate climate risk management, Climate sensitivity Climate sensitivity refers to the change in the adaptation and mitigation. This definition builds from Mitchell and annual global mean surface temperature in response to a change in the Maxwell (2010). atmospheric CO2 concentration or other radiative forcing. Climate extreme (extreme weather or climate event) The Equilibrium climate sensitivity occurrence of a value of a weather or climate variable above (or below) a Refers to the equilibrium (steady state) change in the annual global threshold value near the upper (or lower) ends of the range of observed mean surface temperature following a doubling of the atmospheric values of the variable. For simplicity, both extreme weather events and carbon dioxide (CO2) concentration. As a true equilibrium is challenging extreme climate events are referred to collectively as ‘climate extremes’. to define in climate models with dynamic oceans, the equilibrium climate See also Extreme weather event. sensitivity is often estimated through experiments in AOGCMs where CO2 Climate feedback An interaction in which a perturbation in one levels are either quadrupled or doubled from pre-industrial levels and climate quantity causes a change in a second and the change in the which are integrated for 100-200 years. The climate sensitivity parameter second quantity ultimately leads to an additional change in the first. A (units: °C (W m–2)–1) refers to the equilibrium change in the annual global negative feedback is one in which the initial perturbation is weakened mean surface temperature following a unit change in radiative forcing. by the changes it causes; a positive feedback is one in which the initial Effective climate sensitivity perturbation is enhanced. The initial perturbation can either be externally An estimate of the global mean surface temperature response to a forced or arise as part of internal variability. doubling of the atmospheric carbon dioxide (CO2) concentration that is Climate governance See Governance. evaluated from model output or observations for evolving non-equilibrium conditions. It is a measure of the strengths of the climate feedbacks at a Climate justice See Justice. particular time and may vary with forcing history and climate state, and Climate model A numerical representation of the climate system therefore may differ from equilibrium climate sensitivity. based on the physical, chemical and biological properties of its Transient climate response components, their interactions and feedback processes, and accounting The change in the global mean surface temperature, averaged over a for some of its known properties. The climate system can be represented 20-year period, centered at the time of atmospheric CO doubling, in a by models of varying complexity; that is, for any one component or 2 climate model simulation in which CO2 increases at 1% yr-1 from pre-combination of components a spectrum or hierarchy of models can be industrial. It is a measure of the strength of climate feedbacks and the identified, differing in such aspects as the number of spatial dimensions, timescale of ocean heat uptake. the extent to which physical, chemical or biological processes are explicitly represented, or the level at which empirical parametrizations Climate services Climate services refers to information and products are involved. There is an evolution towards more complex models that enhance users’ knowledge and understanding about the impacts of with interactive chemistry and biology. Climate models are applied as climate change and/or climate variability so as to aid decision-making of a research tool to study and simulate the climate and for operational individuals and organizations and enable preparedness and early climate purposes, including monthly, seasonal and interannual climate change action. Products can include climate data products. predictions. See also Earth system model (ESM). Climate-smart agriculture (CSA) Climate-smart agriculture (CSA) Climate neutrality Concept of a state in which human activities is an approach that helps to guide actions needed to transform and result in no net effect on the climate system. Achieving such a state would reorient agricultural systems to effectively support development and require balancing of residual emissions with emission (carbon dioxide) ensure food security in a changing climate. CSA aims to tackle three main removal as well as accounting for regional or local biogeophysical effects objectives: sustainably increasing agricultural productivity and incomes, of human activities that, for example, affect surface albedo or local adapting and building resilience to climate change, and reducing and/or climate. See also Net zero CO2 emissions. removing greenhouse gas emissions, where possible (FAO, 2018). Climate projection A climate projection is the simulated response Climate system The climate system is the highly complex system of the climate system to a scenario of future emission or concentration of consisting of five major components: the atmosphere, the hydrosphere, 545 Annex I Glossary the cryosphere, the lithosphere and the biosphere and the interactions qualitatively (Mastrandrea et al., 2010). See Section 1.6 for the list of between them. The climate system evolves in time under the influence confidence levels used. See also Agreement, Evidence, Likelihood and of its own internal dynamics and because of external forcings such as Uncertainty. volcanic eruptions, solar variations and anthropogenic forcings such as Conservation agriculture A coherent group of agronomic and soil the changing composition of the atmosphere and land-use change. management practices that reduce the disruption of soil structure and Climate target Climate target refers to a temperature limit, biota. concentration level, or emissions reduction goal used towards the aim of AI Constant composition commitment See Climate change avoiding dangerous anthropogenic interference with the climate system. commitment. For example, national climate targets may aim to reduce greenhouse gas emissions by a certain amount over a given time horizon, for example Constant emissions commitment See Climate change commitment. those under the Kyoto Protocol. Coping capacity The ability of people, institutions, organizations, Climate variability Climate variability refers to variations in and systems, using available skills, values, beliefs, resources, and the mean state and other statistics (such as standard deviations, the opportunities, to address, manage, and overcome adverse conditions in occurrence of extremes, etc.) of the climate on all spatial and temporal the short to medium term. This glossary entry builds from the definition scales beyond that of individual weather events. Variability may be due to used in UNISDR (2009) and IPCC (2012a). See also Resilience. natural internal processes within the climate system (internal variability), Cost–benefit analysis Monetary assessment of all negative and or to variations in natural or anthropogenic external forcing (external positive impacts associated with a given action. Cost–benefit analysis variability). See also Climate change. enables comparison of different interventions, investments or strategies CO2 equivalent (CO2-eq) emission The amount of carbon dioxide and reveals how a given investment or policy effort pays off for a particular (CO2) emission that would cause the same integrated radiative forcing person, company or country. Cost–benefit analyses representing society’s or temperature change, over a given time horizon, as an emitted amount point of view are important for climate change decision-making, but of a greenhouse gas (GHG) or a mixture of GHGs. There are a number there are difficulties in aggregating costs and benefits across different of ways to compute such equivalent emissions and choose appropriate actors and across timescales. See also Discounting. time horizons. Most typically, the CO2-equivalent emission is obtained by Cost-effectiveness A measure of the cost at which policy goal or multiplying the emission of a GHG by its global warming potential (GWP) outcome is achieved. The lower the cost the greater the cost-effectiveness. for a 100-year time horizon. For a mix of GHGs it is obtained by summing the CO2-equivalent emissions of each gas. CO2-equivalent emission is Coupled Model Intercomparison Project (CMIP) The Coupled a common scale for comparing emissions of different GHGs but does Model Intercomparison Project (CMIP) is a climate modelling activity not imply equivalence of the corresponding climate change responses. from the World Climate Research Programme (WCRP) which coordinates There is generally no connection between CO2-equivalent emissions and and archives climate model simulations based on shared model inputs by resulting CO2-equivalent concentrations. modelling groups from around the world. The CMIP3 multimodel data set includes projections using SRES scenarios. The CMIP5 data set includes Co-benefits The positive effects that a policy or measure aimed at projections using the Representative Concentration Pathways (RCPs). The one objective might have on other objectives, thereby increasing the total CMIP6 phase involves a suite of common model experiments as well as benefits for society or the environment. Co-benefits are often subject an ensemble of CMIP-endorsed model intercomparison projects (MIPs). to uncertainty and depend on local circumstances and implementation practices, among other factors. Co-benefits are also referred to as Cumulative emissions The total amount of emissions released over ancillary benefits. a specified period of time. See also Carbon budget, and Transient climate response to cumulative CO2 emissions (TCRE).Common but Differentiated Responsibilities and Respective Capabilities (CBDR-RC) Common but Differentiated Responsibilities Decarbonization The process by which countries, individuals or and Respective Capabilities (CBDR–RC) is a key principle in the United other entities aim to achieve zero fossil carbon existence. Typically Nations Framework Convention on Climate Change (UNFCCC) that refers to a reduction of the carbon emissions associated with electricity, recognises the different capabilities and differing responsibilities of industry and transport. individual countries in tacking climate change. The principle of CBDR– Decoupling Decoupling (in relation to climate change) is where RC is embedded in the 1992 UNFCCC treaty. The convention states: economic growth is no longer strongly associated with consumption of “… the global nature of climate change calls for the widest possible fossil fuels. Relative decoupling is where both grow but at different rates. cooperation by all countries and their participation in an effective and Absolute decoupling is where economic growth happens but fossil fuels appropriate international response, in accordance with their common but decline. differentiated responsibilities and respective capabilities and their social and economic conditions.” Since then the CBDR-RC principle has guided Deforestation Conversion of forest to non-forest. For a discussion the UN climate negotiations. of the term forest and related terms such as afforestation, reforestation and deforestation, see the IPCC Special Report on Land Use, Land-Use Conference of the Parties (COP) The supreme body of UN Change, and Forestry (IPCC, 2000). See also information provided by the conventions, such as the United Nations Framework Convention on United Nations Framework Convention on Climate Change (UNFCCC, Climate Change (UNFCCC), comprising parties with a right to vote that 2013) and the report on Definitions and Methodological Options to have ratified or acceded to the convention. See also United Nations Inventory Emissions from Direct Human-induced Degradation of Forests Framework Convention on Climate Change (UNFCCC). and Devegetation of Other Vegetation Types (IPCC, 2003). See also Confidence The robustness of a finding based on the type, amount, Afforestation, Reforestation and Reducing Emissions from Deforestation quality and consistency of evidence (e.g., mechanistic understanding, and Forest Degradation (REDD+). theory, data, models, expert judgment) and on the degree of agreement Deliberative governance See Governance. across multiple lines of evidence. In this report, confidence is expressed 546 Glossary Annex I Demand- and supply-side measures Disruptive innovation Disruptive innovation is demand-led technological change that leads to significant system change and is Demand-side measures characterized by strong exponential growth. Policies and programmes for influencing the demand for goods and/ or services. In the energy sector, demand-side management aims at Distributive equity See Equity. reducing the demand for electricity and other forms of energy required Distributive justice See Justice. to deliver energy services. Double dividend The extent to which revenues generated by policy Supply-side measures AI instruments, such as carbon taxes or auctioned (tradeable) emission Policies and programmes for influencing how a certain demand for permits can (1) contribute to mitigation and (2) offset part of the goods and/or services is met. In the energy sector, for example, supply- potential welfare losses of climate policies through recycling the revenue side mitigation measures aim at reducing the amount of greenhouse gas in the economy by reducing other distortionary taxes. emissions emitted per unit of energy produced. Downscaling Downscaling is a method that derives local- to See also Mitigation measures. regional-scale (up to 100 km) information from larger-scale models or Demand-side measures See Demand- and supply-side measures. data analyses. Two main methods exist: dynamical downscaling and empirical/statistical downscaling. The dynamical method uses the output Detection See Detection and attribution. of regional climate models, global models with variable spatial resolution, Detection and attribution Detection of change is defined as the or high-resolution global models. The empirical/statistical methods are process of demonstrating that climate or a system affected by climate based on observations and develop statistical relationships that link the has changed in some defined statistical sense, without providing a large-scale atmospheric variables with local/regional climate variables. In reason for that change. An identified change is detected in observations all cases, the quality of the driving model remains an important limitation if its likelihood of occurrence by chance due to internal variability alone is on quality of the downscaled information. The two methods can be determined to be small, for example, <10%. Attribution is defined as the combined, e.g., applying empirical/statistical downscaling to the output process of evaluating the relative contributions of multiple causal factors of a regional climate model, consisting of a dynamical downscaling of a to a change or event with a formal assessment of confidence. global climate model. Development pathways See Pathways. Drought A period of abnormally dry weather long enough to cause a serious hydrological imbalance. Drought is a relative term, therefore any Direct air carbon dioxide capture and storage (DACCS) Chemical discussion in terms of precipitation deficit must refer to the particular process by which CO2 is captured directly from the ambient air, with precipitation-related activity that is under discussion. For example, subsequent storage. Also known as direct air capture and storage (DACS). shortage of precipitation during the growing season impinges on crop Disaster Severe alterations in the normal functioning of a community production or ecosystem function in general (due to soil moisture drought, or a society due to hazardous physical events interacting with vulnerable also termed agricultural drought), and during the runoff and percolation social conditions, leading to widespread adverse human, material, season primarily affects water supplies (hydrological drought). Storage economic or environmental effects that require immediate emergency changes in soil moisture and groundwater are also affected by increases response to satisfy critical human needs and that may require external in actual evapotranspiration in addition to reductions in precipitation. support for recovery. See also Hazard and Vulnerability. A period with an abnormal precipitation deficit is defined as a meteorological drought. See also Soil moisture. Disaster risk management (DRM) Processes for designing, implementing, and evaluating strategies, policies, and measures to Megadrought improve the understanding of disaster risk, foster disaster risk reduction A megadrought is a very lengthy and pervasive drought, lasting much and transfer, and promote continuous improvement in disaster longer than normal, usually a decade or more. preparedness, response, and recovery practices, with the explicit purpose Early warning systems (EWS) The set of technical, financial and of increasing human security, well-being, quality of life, and sustainable institutional capacities needed to generate and disseminate timely and development. meaningful warning information to enable individuals, communities and Discount rate See Discounting. organizations threatened by a hazard to prepare to act promptly and appropriately to reduce the possibility of harm or loss. Dependent upon Discounting A mathematical operation that aims to make monetary context, EWS may draw upon scientific and/or Indigenous knowledge. (or other) amounts received or expended at different times (years) EWS are also considered for ecological applications e.g., conservation, comparable across time. The discounter uses a fixed or possibly time- where the organization itself is not threatened by hazard but the varying discount rate from year to year that makes future value worth ecosystem under conservation is (an example is coral bleaching alerts), less today (if the discount rate is positive). The choice of discount rate(s) in agriculture (for example, warnings of ground frost, hailstorms) and in is debated as it is a judgement based on hidden and/or explicit values. fisheries (storm and tsunami warnings). This glossary entry builds from (Internal) Displacement Internal displacement refers to the forced the definitions used in UNISDR (2009) and IPCC (2012a). movement of people within the country they live in. Internally displaced Earth system feedbacks See Climate feedback. persons (IDPs) are ‘Persons or groups of persons who have been forced or obliged to flee or to leave their homes or places of habitual residence, in Earth system model (ESM) A coupled atmosphere–ocean general particular as a result of or in order to avoid the effects of armed conflict, circulation model in which a representation of the carbon cycle is situations of generalized violence, violations of human rights or natural included, allowing for interactive calculation of atmospheric CO2 or human-made disasters, and who have not crossed an internationally or compatible emissions. Additional components (e.g., atmospheric recognized State border.’ (UN, 1998). See also Migration. chemistry, ice sheets, dynamic vegetation, nitrogen cycle, but also urban or crop models) may be included. See also Climate model. 547 Annex I Glossary Ecosystem An ecosystem is a functional unit consisting of living Emission trajectories A projected development in time of the organisms, their non-living environment and the interactions within and emission of a greenhouse gas (GHG) or group of GHGs, aerosols, and between them. The components included in a given ecosystem and its GHG precursors. See also Emission pathways (under Pathways). spatial boundaries depend on the purpose for which the ecosystem is Emissions trading A market-based instrument aiming at meeting defined: in some cases they are relatively sharp, while in others they a mitigation objective in an efficient way. A cap on GHG emissions is are diffuse. Ecosystem boundaries can change over time. Ecosystems divided in tradeable emission permits that are allocated by a combination are nested within other ecosystems and their scale can range from very of auctioning and handing out free allowances to entities within the AI small to the entire biosphere. In the current era, most ecosystems either jurisdiction of the trading scheme. Entities need to surrender emission contain people as key organisms, or are influenced by the effects of permits equal to the amount of their emissions (e.g., tonnes of CO ). human activities in their environment. See also Ecosystem services. 2 An entity may sell excess permits to entities that can avoid the same Ecosystem services Ecological processes or functions having amount of emissions in a cheaper way. Trading schemes may occur at monetary or non-monetary value to individuals or society at large. These the intra-company, domestic, or international level (e.g., the flexibility are frequently classified as (1) supporting services such as productivity mechanisms under the Kyoto Protocol and the EU-ETS) and may apply or biodiversity maintenance, (2) provisioning services such as food to carbon dioxide (CO2), other greenhouse gases (GHGs), or other or fibre, (3) regulating services such as climate regulation or carbon substances. sequestration, and (4) cultural services such as tourism or spiritual and Enabling conditions Conditions that affect the feasibility of aesthetic appreciation. adaptation and mitigation options, and can accelerate and scale-up Effective climate sensitivity See Climate sensitivity. systemic transitions that would limit temperature increase to 1.5°C and enhance capacities of systems and societies to adapt to the associated Effective radiative forcing See Radiative forcing. climate change, while achieving sustainable development, eradicating El Niño-Southern Oscillation (ENSO) The term El Niño was poverty and reducing inequalities. Enabling conditions include finance, initially used to describe a warm-water current that periodically flows technological innovation, strengthening policy instruments, institutional along the coast of Ecuador and Peru, disrupting the local fishery. It has capacity, multilevel governance, and changes in human behaviour since become identified with warming of the tropical Pacific Ocean east and lifestyles. They also include inclusive processes, attention to of the dateline. This oceanic event is associated with a fluctuation of power asymmetries and unequal opportunities for development and a global-scale tropical and subtropical surface pressure pattern called reconsideration of values. See also Feasibility. the Southern Oscillation. This coupled atmosphere–ocean phenomenon, Energy efficiency The ratio of output or useful energy or energy with preferred time scales of two to about seven years, is known as the services or other useful physical outputs obtained from a system, El Niño-Southern Oscillation (ENSO). It is often measured by the surface conversion process, transmission or storage activity to the input of energy pressure anomaly difference between Tahiti and Darwin and/or the sea (measured as kWh kWh-1, tonnes kWh-1 or any other physical measure surface temperatures in the central and eastern equatorial Pacific. During of useful output like tonne-km transported). Energy efficiency is often an ENSO event, the prevailing trade winds weaken, reducing upwelling described by energy intensity. In economics, energy intensity describes and altering ocean currents such that the sea surface temperatures the ratio of economic output to energy input. Most commonly energy warm, further weakening the trade winds. This phenomenon has a great efficiency is measured as input energy over a physical or economic unit, impact on the wind, sea surface temperature and precipitation patterns i.e., kWh USD-1 (energy intensity), kWh tonne-1. For buildings, it is often in the tropical Pacific. It has climatic effects throughout the Pacific region measured as kWh m-2, and for vehicles as km liter-1 or liter km-1. Very often and in many other parts of the world, through global teleconnections. The in policy ‘energy efficiency’ is intended as the measures to reduce energy cold phase of ENSO is called La Niña. demand through technological options such as insulating buildings, more Electric vehicle (EV) A vehicle whose propulsion is powered fully or efficient appliances, efficient lighting, efficient vehicles, etc. mostly by electricity. Energy security The goal of a given country, or the global community Battery electric vehicle (BEV) as a whole, to maintain an adequate, stable and predictable energy supply. A vehicle whose propulsion is entirely electric without any internal Measures encompass safeguarding the sufficiency of energy resources to combustion engine. meet national energy demand at competitive and stable prices and the resilience of the energy supply; enabling development and deployment Plug-in hybrid electric vehicle (PHEV) of technologies; building sufficient infrastructure to generate, store and A vehicle whose propulsion is mostly electric with batteries re-charged transmit energy supplies; and ensuring enforceable contracts of delivery. from an electric source but extra power and distance are provided by a hybrid internal combustion engine. Enhanced weathering Enhancing the removal of carbon dioxide (CO2) from the atmosphere through dissolution of silicate and carbonate Emission pathways See Pathways. rocks by grinding these minerals to small particles and actively applying Emission scenario A plausible representation of the future them to soils, coasts or oceans. development of emissions of substances that are radiatively active (e.g., (Model) Ensemble A group of parallel model simulations greenhouse gases (GHGs), aerosols) based on a coherent and internally characterising historical climate conditions, climate predictions, or consistent set of assumptions about driving forces (such as demographic climate projections. Variation of the results across the ensemble members and socio-economic development, technological change, energy and land may give an estimate of modelling-based uncertainty. Ensembles made use) and their key relationships. Concentration scenarios, derived from with the same model but different initial conditions only characterize emission scenarios, are often used as input to a climate model to compute the uncertainty associated with internal climate variability, whereas climate projections. See also Baseline scenario, Mitigation scenario, multimodel ensembles including simulations by several models Socio-economic scenario, Scenario, Representative Concentration also include the impact of model differences. Perturbed parameter Pathways (RCPs) (under Pathways), Shared Socio-economic Pathways ensembles, in which model parameters are varied in a systematic (SSPs) (under Pathways) and Transformation pathways (under Pathways). 548 Glossary Annex I manner, aim to assess the uncertainty resulting from internal model Extratropical cyclone Any cyclonic-scale storm that is not a tropical specifications within a single model. Remaining sources of uncertainty cyclone. Usually refers to a middle- or high-latitude migratory storm system unaddressed with model ensembles are related to systematic model formed in regions of large horizontal temperature variations. Sometimes errors or biases, which may be assessed from systematic comparisons called extratropical storm or extratropical low. See also Tropical cyclone. of model simulations with observations wherever available. See also Extreme weather event An extreme weather event is an event that Climate projection. is rare at a particular place and time of year. Definitions of rare vary, but Equality A principle that ascribes equal worth to all human beings, an extreme weather event would normally be as rare as or rarer than the AI including equal opportunities, rights, and obligations, irrespective of origins. 10th or 90th percentile of a probability density function estimated from observations. By definition, the characteristics of what is called extreme Inequality weather may vary from place to place in an absolute sense. When a Uneven opportunities and social positions, and processes of discrimination pattern of extreme weather persists for some time, such as a season, within a group or society, based on gender, class, ethnicity, age, and (dis) it may be classed as an extreme climate event, especially if it yields an ability, often produced by uneven development. Income inequality refers average or total that is itself extreme (e.g., drought or heavy rainfall over to gaps between highest and lowest income earners within a country a season). See also Heatwave and Climate extreme (extreme weather or and between countries. See also Equity, Ethics and Fairness. climate event). Equilibrium climate sensitivity See Climate sensitivity. Extreme weather or climate event See Climate extreme (extreme Equity Equity is the principle of fairness in burden sharing and is a weather or climate event). basis for understanding how the impacts and responses to climate Fairness Impartial and just treatment without favouritism or change, including costs and benefits, are distributed in and by society in discrimination in which each person is considered of equal worth with more or less equal ways. It is often aligned with ideas of equality, fairness equal opportunity. See also Equity, Equality and Ethics. and justice and applied with respect to equity in the responsibility for, and distribution of, climate impacts and policies across society, generations, Feasibility The degree to which climate goals and response options and gender, and in the sense of who participates and controls the are considered possible and/or desirable. Feasibility depends on processes of decision-making. geophysical, ecological, technological, economic, social and institutional conditions for change. Conditions underpinning feasibility are dynamic, Distributive equity spatially variable, and may vary between different groups. See also Equity in the consequences, outcomes, costs and benefits of actions or Enabling conditions. policies. In the case of climate change or climate policies for different people, places and countries, including equity aspects of sharing burdens Feasible scenario commitment See Climate change commitment. and benefits for mitigation and adaptation. Feedback See Climate feedback. Gender equity Flexible governance See Governance. Ensuring equity in that women and men have the same rights, resources and opportunities. In the case of climate change gender equity recognizes Flood The overflowing of the normal confines of a stream or other that women are often more vulnerable to the impacts of climate change body of water, or the accumulation of water over areas that are not and may be disadvantaged in the process and outcomes of climate normally submerged. Floods include river (fluvial) floods, flash floods, policy. urban floods, pluvial floods, sewer floods, coastal floods, and glacial lake outburst floods. Inter-generational equity Equity between generations that acknowledges that the effects of past Food security A situation that exists when all people, at all times, and present emissions, vulnerabilities and policies impose costs and have physical, social and economic access to sufficient, safe and benefits for people in the future and of different age groups. nutritious food that meets their dietary needs and food preferences for an active and healthy life (FAO, 2001). Procedural equity Equity in the process of decision-making, including recognition and Food wastage Food wastage encompasses food loss (the loss of inclusiveness in participation, equal representation, bargaining power, food during production and transportation) and food waste (the waste of voice and equitable access to knowledge and resources to participate. food by the consumer) (FAO, 2013). See also Equality, Ethics and Fairness. Forcing See Radiative forcing. Ethics Ethics involves questions of justice and value. Justice is Forest A vegetation type dominated by trees. Many definitions of the concerned with right and wrong, equity and fairness, and, in general, term forest are in use throughout the world, reflecting wide differences in with the rights to which people and living beings are entitled. Value is a biogeophysical conditions, social structure and economics. For a discussion matter of worth, benefit, or good. See also Equality, Equity and Fairness. of the term forest and related terms such as afforestation, reforestation and deforestation, see the IPCC Special Report on Land Use, Land-Use Evidence Data and information used in the scientific process to Change, and Forestry (IPCC, 2000). See also information provided by the establish findings. In this report, the degree of evidence reflects the United Nations Framework Convention on Climate Change (UNFCCC, amount, quality and consistency of scientific/technical information on 2013) and the Report on Definitions and Methodological Options to which the Lead Authors are basing their findings. See also Agreement, Inventory Emissions from Direct Human-induced Degradation of Forests Confidence, Likelihood and Uncertainty. and Devegetation of Other Vegetation Types (IPCC, 2003). See also Exposure The presence of people; livelihoods; species or ecosystems; Afforestation, Deforestation and Reforestation. environmental functions, services, and resources; infrastructure; or Fossil fuels Carbon-based fuels from fossil hydrocarbon deposits, economic, social, or cultural assets in places and settings that could be including coal, oil, and natural gas. adversely affected. See also Hazard, Risk and Vulnerability. 549 Annex I Glossary Framework Convention on Climate Change See United Nations ecosystem services and common pool natural resources, particularly in Framework Convention on Climate Change (UNFCCC). situations of complexity and uncertainty. Gender equity See Equity. Climate governance Purposeful mechanisms and measures aimed at steering social systems General purpose technologies (GPT) General purpose technologies towards preventing, mitigating, or adapting to the risks posed by climate can be or are used pervasively in a wide range of sectors in ways that change (Jagers and Stripple, 2003). fundamentally change the modes of operation of those sectors (Helpman, AI 1998). Examples include the steam engine, power generator and motor, Deliberative governance ICT, and biotechnology. Deliberative governance involves decision-making through inclusive public conversation, which allows opportunity for developing policy Geoengineering In this report, separate consideration is given to options through public discussion rather than collating individual the two main approaches considered as ‘geoengineering’ in some of the preferences through voting or referenda (although the latter governance literature: solar radiation modification (SRM) and carbon dioxide removal mechanisms can also be proceeded and legitimated by public deliberation (CDR). Because of this separation, the term ‘geoengineering’ is not used processes). in this report. See also Carbon dioxide removal (CDR) and Solar radiation modification (SRM). Flexible governance Strategies of governance at various levels, which prioritize the use Glacier A perennial mass of ice, and possibly firn and snow, of social learning and rapid feedback mechanisms in planning and originating on the land surface by the recrystallisation of snow and policy making, often through incremental, experimental and iterative showing evidence of past or present flow. A glacier typically gains mass management processes. by accumulation of snow, and loses mass by melting and ice discharge into the sea or a lake if the glacier terminates in a body of water. Land ice Governance capacity masses of continental size (>50,000 km2) are referred to as ice sheets. The ability of governance institutions, leaders, and non-state and civil See also Ice sheet. society to plan, co-ordinate, fund, implement, evaluate and adjust policies and measures over the short, medium and long term, adjusting Global climate model (also referred to as general circulation for uncertainty, rapid change and wide-ranging impacts and multiple model, both abbreviated as GCM) See Climate model. actors and demands. Global mean surface temperature (GMST) Estimated global Multilevel governance average of near-surface air temperatures over land and sea-ice, and Multilevel governance refers to negotiated, non-hierarchical exchanges sea surface temperatures over ice-free ocean regions, with changes between institutions at the transnational, national, regional and local normally expressed as departures from a value over a specified reference levels. Multilevel governance identifies relationships among governance period. When estimating changes in GMST, near-surface air temperature processes at these different levels. Multilevel governance does include over both land and oceans are also used.1 See also Land surface air negotiated relationships among institutions at different institutional temperature, Sea surface temperature (SST) and Global mean surface air levels and also a vertical ‘layering’ of governance processes at temperature (GSAT). different levels. Institutional relationships take place directly between Global mean surface air temperature (GSAT) Global average of transnational, regional and local levels, thus bypassing the state level near-surface air temperatures over land and oceans. Changes in GSAT are (Peters and Pierre, 2001) often used as a measure of global temperature change in climate models Participatory governance but are not observed directly. See also Global mean surface temperature A governance system that enables direct public engagement in decision- (GMST) and Land surface air temperature. making using a variety of techniques for example, referenda, community Global warming The estimated increase in global mean surface deliberation, citizen juries or participatory budgeting. The approach can be temperature (GMST) averaged over a 30-year period, or the 30-year applied in formal and informal institutional contexts from national to local, period centered on a particular year or decade, expressed relative to but is usually associated with devolved decision-making. This definition pre-industrial levels unless otherwise specified. For 30-year periods that builds from Fung and Wright (2003) and Sarmiento and Tilly (2018). span past and future years, the current multi-decadal warming trend is Governance capacity See Governance. assumed to continue. See also Climate change and Climate variability. Green infrastructure The interconnected set of natural and Governance A comprehensive and inclusive concept of the full range constructed ecological systems, green spaces and other landscape of means for deciding, managing, implementing and monitoring policies features. It includes planted and indigenous trees, wetlands, parks, and measures. Whereas government is defined strictly in terms of the green open spaces and original grassland and woodlands, as well as nation-state, the more inclusive concept of governance recognizes the possible building and street-level design interventions that incorporate contributions of various levels of government (global, international, vegetation. Green infrastructure provides services and functions in the regional, sub-national and local) and the contributing roles of the private same way as conventional infrastructure. This definition builds from sector, of nongovernmental actors, and of civil society to addressing the Culwick and Bobbins (2016). many types of issues facing the global community. Greenhouse gas (GHG) Greenhouse gases are those gaseous Adaptive governance constituents of the atmosphere, both natural and anthropogenic, that An emerging term in the literature for the evolution of formal and absorb and emit radiation at specific wavelengths within the spectrum of informal institutions of governance that prioritize social learning in terrestrial radiation emitted by the Earth’s surface, the atmosphere itself planning, implementation and evaluation of policy through iterative and by clouds. This property causes the greenhouse effect. Water vapour social learning to steer the use and protection of natural resources, (H2O), carbon dioxide (CO2), nitrous oxide (N2O), methane (CH4) and 1 Past IPCC reports, reflecting the literature, have used a variety of approximately equivalent metrics of GMST change. 550 Glossary Annex I ozone (O3) are the primary GHGs in the Earth’s atmosphere. Moreover, Mitigation behaviour there are a number of entirely human-made GHGs in the atmosphere, Human actions that directly or indirectly influence mitigation. such as the halocarbons and other chlorine- and bromine-containing Human behavioural change A transformation or modification of substances, dealt with under the Montreal Protocol. Beside CO2, N2O and human actions. Behaviour change efforts can be planned in ways that CH4, the Kyoto Protocol deals with the GHGs sulphur hexafluoride (SF6), mitigate climate change and/or reduce negative consequences of climate hydrofluorocarbons (HFCs) and perfluorocarbons (PFCs). See also Carbon change impacts. dioxide (CO2), Methane (CH4), Nitrous oxide (N2O) and Ozone (O3). Human rights Rights that are inherent to all human beings, universal, AI Greenhouse gas removal (GGR) Withdrawal of a GHG and/or inalienable, and indivisible, typically expressed and guaranteed by law. a precursor from the atmosphere by a sink. See also Carbon dioxide They include the right to life; economic, social, and cultural rights; removal (CDR) and Negative emissions. and the right to development and self-determination. Based upon the Gross domestic product (GDP) The sum of gross value added, definition by the UN Office of the High Commissioner for Human Rights at purchasers’ prices, by all resident and non-resident producers in the (UNOHCHR, 2018). economy, plus any taxes and minus any subsidies not included in the Procedural rights value of the products in a country or a geographic region for a given Rights to a legal procedure to enforce substantive rights. period, normally one year. GDP is calculated without deducting for depreciation of fabricated assets or depletion and degradation of natural Substantive rights resources. Basic human rights, including the right to the substance of being human such as life itself, liberty and happiness. Gross fixed capital formation (GFCF) One component of the GDP that corresponds to the total value of acquisitions, minus disposals of Human security A condition that is met when the vital core of human fixed assets during one year by the business sector, governments and lives is protected, and when people have the freedom and capacity to live households, plus certain additions to the value of non-produced assets with dignity. In the context of climate change, the vital core of human (such as subsoil assets or major improvements in the quantity, quality or lives includes the universal and culturally specific, material and non- productivity of land). material elements necessary for people to act on behalf of their interests and to live with dignity. Halocarbons A collective term for the group of partially halogenated organic species, which includes the chlorofluorocarbons (CFCs), Human system Any system in which human organizations and hydrochlorofluorocarbons (HCFCs), hydrofluorocarbons (HFCs), halons, institutions play a major role. Often, but not always, the term is methyl chloride and methyl bromide. Many of the halocarbons have synonymous with society or social system. Systems such as agricultural large global warming potentials. The chlorine and bromine-containing systems, urban systems, political systems, technological systems and halocarbons are also involved in the depletion of the ozone layer. economic systems are all human systems in the sense applied in this report. Hazard The potential occurrence of a natural or human-induced physical event or trend that may cause loss of life, injury, or other Hydrological cycle The cycle in which water evaporates from the health impacts, as well as damage and loss to property, infrastructure, oceans and the land surface, is carried over the earth in atmospheric livelihoods, service provision, ecosystems and environmental resources. circulation as water vapour, condenses to form clouds, precipitates as See also Disaster, Exposure, Risk, and Vulnerability. rain or snow, which on land can be intercepted by trees and vegetation, potentially accumulates as snow or ice, provides runoff on the land Heatwave A period of abnormally hot weather. Heatwaves and warm surface, infiltrates into soils, recharges groundwater, discharges into spells have various and in some cases overlapping definitions. See also streams, flows out into the oceans, and ultimately evaporates again Extreme weather event. from the ocean or land surface. The various systems involved in the Heating, ventilation, and air conditioning (HVAC) Heating, hydrological cycle are usually referred to as hydrological systems. ventilation and air conditioning technology is used to control temperature Ice sheet A mass of land ice of continental size that is sufficiently and humidity in an indoor environment, be it in buildings or in vehicles, thick to cover most of the underlying bed, so that its shape is mainly providing thermal comfort and healthy air quality to the occupants. HVAC determined by its dynamics (the flow of the ice as it deforms internally systems can be designed for an isolated space, an individual building or and/or slides at its base). An ice sheet flows outward from a high central a distributed heating and cooling network within a building structure or ice plateau with a small average surface slope. The margins usually slope a district heating system. The latter provides economies of scale and also more steeply, and most ice is discharged through fast flowing ice streams scope for integration with solar heat, natural seasonal cooling/heating etc. or outlet glaciers, in some cases into the sea or into ice shelves floating Holocene The Holocene is the current interglacial geological epoch, on the sea. There are only two ice sheets in the modern world, one on the second of two epochs within the Quaternary period, the preceding Greenland and one on Antarctica. During glacial periods there were being the Pleistocene. The International Commission on Stratigraphy others. See also Glacier. defines the start of the Holocene at 11,650 years before 1950. See also (climate change) Impact assessment The practice of identifying Anthropocene. and evaluating, in monetary and/or non-monetary terms, the effects of Human behaviour The way in which a person acts in response to a climate change on natural and human systems. particular situation or stimulus. Human actions are relevant at different Impacts (consequences, outcomes) The consequences of levels, from international, national, and sub-national actors, to NGO, firm- realized risks on natural and human systems, where risks result from level actors, and communities, households, and individual actions. the interactions of climate-related hazards (including extreme weather Adaptation behaviour and climate events), exposure, and vulnerability. Impacts generally Human actions that directly or indirectly affect the risks of climate refer to effects on lives; livelihoods; health and well-being; ecosystems change impacts. and species; economic, social and cultural assets; services (including 551 Annex I Glossary ecosystem services); and infrastructure. Impacts may be referred to and management training to support integrated planning and decision- as consequences or outcomes, and can be adverse or beneficial. See making processes between organizations and people, as well as also Adaptation, Exposure, Hazard, Loss and Damage, and losses and empowerment, social capital, and an enabling environment, including damages, and Vulnerability. the culture, values and power relations (Willems and Baumert, 2003). Incremental adaptation See Adaptation. Integrated assessment A method of analysis that combines results and models from the physical, biological, economic and social sciences Indigenous knowledge Indigenous knowledge refers to the and the interactions among these components in a consistent framework AI understandings, skills and philosophies developed by societies with to evaluate the status and the consequences of environmental change long histories of interaction with their natural surroundings. For many and the policy responses to it. See also Integrated assessment model Indigenous peoples, Indigenous knowledge informs decision-making (IAM). about fundamental aspects of life, from day-to-day activities to longer term actions. This knowledge is integral to cultural complexes, which also Integrated assessment model (IAM) Integrated assessment encompass language, systems of classification, resource use practices, models (IAMs) integrate knowledge from two or more domains into social interactions, values, ritual and spirituality. These distinctive ways a single framework. They are one of the main tools for undertaking of knowing are important facets of the world’s cultural diversity. This integrated assessments. definition builds on UNESCO (2018). One class of IAM used in respect of climate change mitigation may Indirect land-use change (iLUC) See Land-use change (LUC). include representations of: multiple sectors of the economy, such as energy, land use and land-use change; interactions between sectors; the Industrial revolution A period of rapid industrial growth with far- economy as a whole; associated GHG emissions and sinks; and reduced reaching social and economic consequences, beginning in Britain during representations of the climate system. This class of model is used to assess the second half of the 18th century and spreading to Europe and later to linkages between economic, social and technological development and other countries, including the United States. The invention of the steam the evolution of the climate system. engine was an important trigger of this development. The industrial revolution marks the beginning of a strong increase in the use of fossil Another class of IAM additionally includes representations of the costs fuels, initially coal, and hence emission of carbon dioxide (CO2). See also associated with climate change impacts, but includes less detailed Pre-industrial. representations of economic systems. These can be used to assess impacts and mitigation in a cost–benefit framework and have been used Industrialized/developed/developing countries There are a to estimate the social cost of carbon. diversity of approaches for categorizing countries on the basis of their level of development, and for defining terms such as industrialized, Integrated water resources management (IWRM) A process developed, or developing. Several categorizations are used in this report. which promotes the coordinated development and management of (1) In the United Nations system, there is no established convention for water, land and related resources in order to maximize economic and designation of developed and developing countries or areas. (2) The social welfare in an equitable manner without compromising the United Nations Statistics Division specifies developed and developing sustainability of vital ecosystems. regions based on common practice. In addition, specific countries are Inter-generational equity See Equity. designated as Least Developed Countries (LDC), landlocked developing countries, small island developing states, and transition economies. Many Inter-generational justice See Justice. countries appear in more than one of these categories. (3) The World Internal variability See Climate variability. Bank uses income as the main criterion for classifying countries as low, lower middle, upper middle and high income. (4) The UNDP aggregates Internet of Things (IoT) The network of computing devices indicators for life expectancy, educational attainment, and income into a embedded in everyday objects such as cars, phones and computers, single composite Human Development Index (HDI) to classify countries connected via the internet, enabling them to send and receive data. as low, medium, high or very high human development. Iron fertilization See Ocean fertilization. Inequality See Equality. Irreversibility A perturbed state of a dynamical system is defined as Information and communication technology (ICT) An umbrella irreversible on a given timescale, if the recovery time scale from this state term that includes any information and communication device or due to natural processes is substantially longer than the time it takes for application, encompassing: computer systems, network hardware and the system to reach this perturbed state. See also Tipping point. software, cell phones, etc. Justice Justice is concerned with ensuring that people get what is due Infrastructure commitment See Climate change commitment. to them, setting out the moral or legal principles of fairness and equity in the way people are treated, often based on the ethics and values of society. Institution Institutions are rules and norms held in common by social actors that guide, constrain and shape human interaction. Institutions Climate justice can be formal, such as laws and policies, or informal, such as norms and Justice that links development and human rights to achieve a human- conventions. Organizations – such as parliaments, regulatory agencies, centred approach to addressing climate change, safeguarding the rights private firms and community bodies – develop and act in response to of the most vulnerable people and sharing the burdens and benefits of institutional frameworks and the incentives they frame. Institutions can climate change and its impacts equitably and fairly. This definition builds guide, constrain and shape human interaction through direct control, upon the one used by the Mary Robinson Foundation – Climate Justice through incentives, and through processes of socialization. See also (MRFCJ, 2018). Institutional capacity. Distributive justice Institutional capacity Institutional capacity comprises building Justice in the allocation of economic and non-economic costs and and strengthening individual organizations and providing technical benefits across society. 552 Glossary Annex I Inter-generational justice production, ecological or social functions’. Since managed land may Justice in the distribution of economic and non-economic costs and include CO2 removals not considered as ‘anthropogenic’ in some of the benefits across generations. scientific literature assessed in this report (e.g., removals associated with CO2 fertilization and N deposition), the land-related net GHG emission Procedural justice estimates included in this report are not necessarily directly comparable Justice in the way outcomes are brought about including who participates with LULUCF estimates in National GHG Inventories. and is heard in the processes of decision-making. See also Afforestation, Deforestation, Reforestation, and the IPCC Special Social justice AI Report on Land Use, Land-Use Change, and Forestry (IPCC, 2000). Just or fair relations within society that seek to address the distribution of wealth, access to resources, opportunity, and support according to Land use, land-use change and forestry (LULUCF) See Land-use principles of justice and fairness. change (LUC). See also Equity, Ethics, Fairness, and Human rights. Life cycle assessment (LCA) Compilation and evaluation of the inputs, outputs and the potential environmental impacts of a product or Kyoto Protocol The Kyoto Protocol to the United Nations Framework service throughout its life cycle. This definition builds from ISO (2018). Convention on Climate Change (UNFCCC) is an international treaty adopted in December 1997 in Kyoto, Japan, at the Third Session of the Likelihood The chance of a specific outcome occurring, where this Conference of the Parties (COP3) to the UNFCCC. It contains legally might be estimated probabilistically. Likelihood is expressed in this report binding commitments, in addition to those included in the UNFCCC. using a standard terminology (Mastrandrea et al., 2010). See Section 1.6 Countries included in Annex B of the Protocol (mostly OECD countries for the list of likelihood qualifiers used. See also Agreement, Evidence, and countries with economies in transition) agreed to reduce their Confidence and Uncertainty. anthropogenic greenhouse gas (GHG) emissions (carbon dioxide Livelihood The resources used and the activities undertaken in order (CO2), methane (CH4), nitrous oxide (N2O), hydrofluorocarbons (HFCs), to live. Livelihoods are usually determined by the entitlements and assets perfluorocarbons (PFCs), and sulphur hexafluoride (SF6)) by at least 5% to which people have access. Such assets can be categorised as human, below 1990 levels in the first commitment period (2008–2012). The social, natural, physical or financial. Kyoto Protocol entered into force on 16 February 2005 and as of May 2018 had 192 Parties (191 States and the European Union). A second Local knowledge Local knowledge refers to the understandings commitment period was agreed in December 2012 at COP18, known as and skills developed by individuals and populations, specific to the the Doha Amendment to the Kyoto Protocol, in which a new set of Parties places where they live. Local knowledge informs decision-making about committed to reduce GHG emissions by at least 18% below 1990 levels fundamental aspects of life, from day-to-day activities to longer-term in the period from 2013 to 2020. However, as of May 2018, the Doha actions. This knowledge is a key element of the social and cultural systems Amendment had not received sufficient ratifications to enter into force. which influence observations of, and responses to climate change; it also See also United Nations Framework Convention on Climate Change informs governance decisions. This definition builds on UNESCO (2018). (UNFCCC) and Paris Agreement. Lock-in A situation in which the future development of a system, Land surface air temperature The near-surface air temperature including infrastructure, technologies, investments, institutions, and over land, typically measured at 1.25–2 m above the ground using behavioural norms, is determined or constrained (‘locked in’) by historic standard meteorological equipment. developments. Land use Land use refers to the total of arrangements, activities and Long-lived climate forcers (LLCF) Long-lived climate forcers refer inputs undertaken in a certain land cover type (a set of human actions). to a set of well-mixed greenhouse gases with long atmospheric lifetimes. The term land use is also used in the sense of the social and economic This set of compounds includes carbon dioxide (CO2) and nitrous oxide purposes for which land is managed (e.g., grazing, timber extraction, (N2O), together with some fluorinated gases. They have a warming effect conservation and city dwelling). In national greenhouse gas inventories, on climate. These compounds accumulate in the atmosphere at decadal land use is classified according to the IPCC land use categories of forest to centennial time scales, and their effect on climate hence persists for land, cropland, grassland, wetland, settlements, other. See also Land-use decades to centuries after their emission. On time scales of decades to change (LUC). a century, already emitted emissions of long-lived climate forcers can only be abated by greenhouse gas removal (GGR). See also Short-lived Land-use change (LUC) Land-use change involves a change from climate forcers (SLCF). one land use category to another. Loss and Damage, and losses and damages Research has taken Indirect land-use change (iLUC) Loss and Damage (capitalized letters) to refer to political debate under Refers to market-mediated or policy-driven shifts in land use that cannot the UNFCCC following the establishment of the Warsaw Mechanism be directly attributed to land-use management decisions of individuals on Loss and Damage in 2013, which is to ‘address loss and damage or groups. For example, if agricultural land is diverted to fuel production, associated with impacts of climate change, including extreme events forest clearance may occur elsewhere to replace the former agricultural and slow onset events, in developing countries that are particularly production. vulnerable to the adverse effects of climate change.’ Lowercase letters Land use, land-use change and forestry (LULUCF) (losses and damages) have been taken to refer broadly to harm from In the context of national greenhouse gas (GHG) inventories under the (observed) impacts and (projected) risks (see Mechler et al., in press). UNFCCC, LULUCF is a GHG inventory sector that covers anthropogenic Maladaptive actions (Maladaptation) Actions that may lead emissions and removals of GHG from carbon pools in managed lands, to increased risk of adverse climate-related outcomes, including via excluding non-CO2 agricultural emissions. Following the 2006 IPCC increased GHG emissions, increased vulnerability to climate change, or Guidelines for National GHG Inventories, ‘anthropogenic’ land-related diminished welfare, now or in the future. Maladaptation is usually an GHG fluxes are defined as all those occurring on ‘managed land’, i.e., unintended consequence. ‘where human interventions and practices have been applied to perform 553 Annex I Glossary Market exchange rate (MER) The rate at which a currency of illiteracy, discrimination against women and environmental degradation. one country can be exchanged with the currency of another country. In These goals were agreed at the UN Millennium Summit in 2000 together most economies such rates evolve daily while in others there are official with an action plan to reach the goals by 2015. conversion rates that are adjusted periodically. See also Purchasing Mitigation (of climate change) A human intervention to reduce power parity (PPP). emissions or enhance the sinks of greenhouse gases. Market failure When private decisions are based on market prices Mitigation behaviour See Human behaviour. that do not reflect the real scarcity of goods and services but rather AI reflect market distortions, they do not generate an efficient allocation Mitigation measures In climate policy, mitigation measures are of resources but cause welfare losses. A market distortion is any event technologies, processes or practices that contribute to mitigation, for in which a market reaches a market clearing price that is substantially example, renewable energy (RE) technologies, waste minimization different from the price that a market would achieve while operating processes and public transport commuting practices. See also Mitigation under conditions of perfect competition and state enforcement of legal option, and Policies (for climate change mitigation and adaptation). contracts and the ownership of private property. Examples of factors Mitigation option A technology or practice that reduces GHG causing market prices to deviate from real economic scarcity are emissions or enhances sinks. environmental externalities, public goods, monopoly power, information asymmetry, transaction costs and non-rational behaviour. Mitigation pathways See Pathways. Measurement, Reporting and Verification (MRV) Mitigation scenario A plausible description of the future that describes how the (studied) system responds to the implementation of Measurement mitigation policies and measures. See also Emission scenario, Pathways, ‘Processes of data collection over time, providing basic datasets, including Socio-economic scenario and Stabilization (of GHG or CO -equivalent associated accuracy and precision, for the range of relevant variables. 2 concentration). Possible data sources are field measurements, field observations, detection through remote sensing and interviews.’ (UN-REDD, 2009). Monitoring and evaluation (M&E) Monitoring and evaluation refers to mechanisms put in place at national to local scales to respectively Reporting monitor and evaluate efforts to reduce greenhouse gas emissions and/ ‘The process of formal reporting of assessment results to the UNFCCC, or adapt to the impacts of climate change with the aim of systematically according to predetermined formats and according to established identifying, characterizing and assessing progress over time. standards, especially the IPCC [Intergovernmental Panel on Climate Change] Guidelines and GPG [Good Practice Guidance].’ (UN-REDD, Motivation (of an individual) An individual’s reason or reasons for 2009) acting in a particular way; individuals may consider various consequences of actions, including financial, social, affective and environmental Verification consequences. Motivation can come from outside (extrinsic) or from ‘The process of formal verification of reports, for example the established inside (intrinsic) the individual. approach to verify national communications and national inventory reports to the UNFCCC.’ (UN-REDD, 2009) Multilevel governance See Governance. Megadrought See Drought. Narratives Qualitative descriptions of plausible future world evolutions, describing the characteristics, general logic and developments Methane (CH4) One of the six greenhouse gases (GHGs) to be underlying a particular quantitative set of scenarios. Narratives are also mitigated under the Kyoto Protocol and is the major component of referred to in the literature as ‘storylines’. See also Scenario, Scenario natural gas and associated with all hydrocarbon fuels. Significant storyline and Pathways. emissions occur as a result of animal husbandry and agriculture, and their management represents a major mitigation option. Nationally Determined Contributions (NDCs) A term used under the United Nations Framework Convention on Climate Change (UNFCCC) Migrant See Migration. whereby a country that has joined the Paris Agreement outlines its plans Migration The International Organization for Migration (IOM) for reducing its emissions. Some countries’ NDCs also address how defines migration as ‘The movement of a person or a group of persons, they will adapt to climate change impacts, and what support they need either across an international border, or within a State. It is a population from, or will provide to, other countries to adopt low-carbon pathways movement, encompassing any kind of movement of people, whatever and to build climate resilience. According to Article 4 paragraph 2 its length, composition and causes; it includes migration of refugees, of the Paris Agreement, each Party shall prepare, communicate and displaced persons, economic migrants, and persons moving for other maintain successive NDCs that it intends to achieve. In the lead up to purposes, including family reunification.’ (IOM, 2018). 21st Conference of the Parties in Paris in 2015, countries submitted Intended Nationally Determined Contributions (INDCs). As countries join Migrant the Paris Agreement, unless they decide otherwise, this INDC becomes The International Organization for Migration (IOM) defines a migrant their first Nationally Determined Contribution (NDC). See also United as ‘any person who is moving or has moved across an international Nations Framework Convention on Climate Change (UNFCCC) and Paris border or within a State away from his/her habitual place of residence, Agreement. regardless of (1) the person’s legal status; (2) whether the movement is voluntary or involuntary; (3) what the causes for the movement are; or Negative emissions Removal of greenhouse gases (GHGs) from (4) what the length of the stay is.’ (IOM, 2018). the atmosphere by deliberate human activities, i.e., in addition to the removal that would occur via natural carbon cycle processes. See also See also (Internal) Displacement. Net negative emissions, Net zero emissions, Carbon dioxide removal Millennium Development Goals (MDGs) A set of eight time- (CDR) and Greenhouse gas removal (GGR). bound and measurable goals for combating poverty, hunger, disease, 554 Glossary Annex I Net negative emissions A situation of net negative emissions is stratosphere, it is created by the interaction between solar ultraviolet achieved when, as result of human activities, more greenhouse gases radiation and molecular oxygen (O2). Stratospheric ozone plays a are removed from the atmosphere than are emitted into it. Where dominant role in the stratospheric radiative balance. Its concentration is multiple greenhouse gases are involved, the quantification of negative highest in the ozone layer. emissions depends on the climate metric chosen to compare emissions Paris Agreement The Paris Agreement under the United Nations of different gases (such as global warming potential, global temperature Framework Convention on Climate Change (UNFCCC) was adopted on change potential, and others, as well as the chosen time horizon). See December 2015 in Paris, France, at the 21st session of the Conference also Negative emissions, Net zero emissions and Net zero CO2 emissions. AIof the Parties (COP) to the UNFCCC. The agreement, adopted by 196 Net zero CO2 emissions Net zero carbon dioxide (CO2) emissions Parties to the UNFCCC, entered into force on 4 November 2016 and as are achieved when anthropogenic CO2 emissions are balanced globally of May 2018 had 195 Signatories and was ratified by 177 Parties. One by anthropogenic CO2 removals over a specified period. Net zero CO2 of the goals of the Paris Agreement is ‘Holding the increase in the global emissions are also referred to as carbon neutrality. See also Net zero average temperature to well below 2°C above pre-industrial levels emissions and Net negative emissions. and pursuing efforts to limit the temperature increase to 1.5°C above pre-industrial levels’, recognising that this would significantly reduce Net zero emissions Net zero emissions are achieved when the risks and impacts of climate change. Additionally, the Agreement anthropogenic emissions of greenhouse gases to the atmosphere are aims to strengthen the ability of countries to deal with the impacts balanced by anthropogenic removals over a specified period. Where of climate change. The Paris Agreement is intended to become fully multiple greenhouse gases are involved, the quantification of net zero effective in 2020. See also United Nations Framework Convention on emissions depends on the climate metric chosen to compare emissions Climate Change (UNFCCC), Kyoto Protocol and Nationally Determined of different gases (such as global warming potential, global temperature Contributions (NDCs). change potential, and others, as well as the chosen time horizon). See also Net zero CO2 emissions, Negative emissions and Net negative Participatory governance See Governance. emissions. Pathways The temporal evolution of natural and/or human systems Nitrous oxide (N2O) One of the six greenhouse gases (GHGs) to be towards a future state. Pathway concepts range from sets of quantitative mitigated under the Kyoto Protocol. The main anthropogenic source of and qualitative scenarios or narratives of potential futures to solution- N2O is agriculture (soil and animal manure management), but important oriented decision-making processes to achieve desirable societal goals. contributions also come from sewage treatment, fossil fuel combustion, Pathway approaches typically focus on biophysical, techno-economic, and chemical industrial processes. N2O is also produced naturally from a and/or socio-behavioural trajectories and involve various dynamics, goals wide variety of biological sources in soil and water, particularly microbial and actors across different scales. action in wet tropical forests. 1.5°C pathway Non-CO2 emissions and radiative forcing Non-CO2 emissions A pathway of emissions of greenhouse gases and other climate forcers included in this report are all anthropogenic emissions other than CO2 that provides an approximately one-in-two to two-in-three chance, given that result in radiative forcing. These include short-lived climate forcers, current knowledge of the climate response, of global warming either such as methane (CH4), some fluorinated gases, ozone (O3) precursors, remaining below 1.5°C or returning to 1.5°C by around 2100 following aerosols or aerosol precursors, such as black carbon and sulphur dioxide, an overshoot. See also Temperature overshoot. respectively, as well as long-lived greenhouse gases, such as nitrous Adaptation pathways oxide (N2O) or other fluorinated gases. The radiative forcing associated A series of adaptation choices involving trade-offs between short-term with non-CO2 emissions and changes in surface albedo is referred to as and long-term goals and values. These are processes of deliberation to non-CO2 radiative forcing. identify solutions that are meaningful to people in the context of their Non-overshoot pathways See Pathways. daily lives and to avoid potential maladaptation. Ocean acidification (OA) Ocean acidification refers to a reduction Development pathways in the pH of the ocean over an extended period, typically decades or Development pathways are trajectories based on an array of social, longer, which is caused primarily by uptake of carbon dioxide (CO2) from economic, cultural, technological, institutional and biophysical features the atmosphere, but can also be caused by other chemical additions or that characterise the interactions between human and natural systems subtractions from the ocean. Anthropogenic ocean acidification refers to and outline visions for the future, at a particular scale. the component of pH reduction that is caused by human activity (IPCC, Emission pathways 2011, p. 37). Modelled trajectories of global anthropogenic emissions over the 21st Ocean fertilization Deliberate increase of nutrient supply to century are termed emission pathways. the near-surface ocean in order to enhance biological production Mitigation pathways through which additional carbon dioxide (CO2) from the atmosphere is A mitigation pathway is a temporal evolution of a set of mitigation sequestered. This can be achieved by the addition of micro-nutrients or scenario features, such as greenhouse gas emissions and socio-economic macro-nutrients. Ocean fertilization is regulated by the London Protocol. development. Overshoot See Temperature overshoot. Overshoot pathways Overshoot pathways See Pathways. Pathways that exceed the stabilization level (concentration, forcing, or temperature) before the end of a time horizon of interest (e.g., before Ozone (O3) Ozone, the triatomic form of oxygen (O3), is a gaseous 2100) and then decline towards that level by that time. Once the target atmospheric constituent. In the troposphere, it is created both naturally level is exceeded, removal by sinks of greenhouse gases is required. See and by photochemical reactions involving gases resulting from human also Temperature overshoot. activities (smog). Tropospheric ozone acts as a greenhouse gas. In the 555 Annex I Glossary Non-overshoot pathways Plug-in hybrid electric vehicle (PHEV) See Electric vehicle (EV). Pathways that stay below the stabilization level (concentration, forcing, Policies (for climate change mitigation and adaptation) or temperature) during the time horizon of interest (e.g., until 2100). Policies are taken and/or mandated by a government – often in conjunction Representative Concentration Pathways (RCPs) with business and industry within a single country, or collectively with other Scenarios that include time series of emissions and concentrations of countries – to accelerate mitigation and adaptation measures. Examples of the full suite of greenhouse gases (GHGs) and aerosols and chemically policies are support mechanisms for renewable energy supplies, carbon or active gases, as well as land use/land cover (Moss et al., 2008). The AI energy taxes, fuel efficiency standards for automobiles, etc. word representative signifies that each RCP provides only one of many possible scenarios that would lead to the specific radiative forcing Political economy The set of interlinked relationships between characteristics. The term pathway emphasizes the fact that not only the people, the state, society and markets as defined by law, politics, long-term concentration levels but also the trajectory taken over time to economics, customs and power that determine the outcome of trade and reach that outcome are of interest (Moss et al., 2010). RCPs were used to transactions and the distribution of wealth in a country or economy. develop climate projections in CMIP5. Poverty Poverty is a complex concept with several definitions • RCP2.6: One pathway where radiative forcing peaks at stemming from different schools of thought. It can refer to material approximately 3 W m-2 and then declines to be limited at 2.6 W m-2 circumstances (such as need, pattern of deprivation or limited resources), in 2100 (the corresponding Extended Concentration Pathway, or economic conditions (such as standard of living, inequality or economic ECP, has constant emissions after 2100). position) and/or social relationships (such as social class, dependency, • RCP4.5 and RCP6.0: Two intermediate stabilization pathways exclusion, lack of basic security or lack of entitlement). See also Poverty in which radiative forcing is limited at approximately 4.5 W m-2 eradication. and 6.0 W m-2 in 2100 (the corresponding ECPs have constant concentrations after 2150). Poverty eradication A set of measures to end poverty in all its • RCP8.5: One high pathway which leads to >8.5 W m-2 in 2100 forms everywhere. See also Sustainable Development Goals (SDGs). (the corresponding ECP has constant emissions after 2100 until Precursors Atmospheric compounds that are not greenhouse 2150 and constant concentrations after 2250). gases (GHGs) or aerosols, but that have an effect on GHG or aerosol See also Coupled Model Intercomparison Project (CMIP) and Shared concentrations by taking part in physical or chemical processes regulating Socio-economic Pathways (SSPs). their production or destruction rates. See also Aerosol and Greenhouse Shared Socio-economic Pathways (SSPs) gas (GHG). Shared Socio-economic Pathways (SSPs) were developed to complement Pre-industrial The multi-century period prior to the onset of large- the RCPs with varying socio-economic challenges to adaptation and scale industrial activity around 1750. The reference period 1850–1900 mitigation (O’Neill et al., 2014). Based on five narratives, the SSPs is used to approximate pre-industrial global mean surface temperature describe alternative socio-economic futures in the absence of climate (GMST). See also Industrial revolution. policy intervention, comprising sustainable development (SSP1), regional rivalry (SSP3), inequality (SSP4), fossil–fuelled development (SSP5) and Procedural equity See Equity. middle-of-the-road development (SSP2) (O’Neill, 2000; O’Neill et al., Procedural justice See Justice. 2017; Riahi et al., 2017). The combination of SSP-based socio-economic scenarios and Representative Concentration Pathway (RCP)-based Procedural rights See Human rights. climate projections provides an integrative frame for climate impact and Projection A projection is a potential future evolution of a quantity policy analysis. or set of quantities, often computed with the aid of a model. Unlike Transformation pathways predictions, projections are conditional on assumptions concerning, for Trajectories describing consistent sets of possible futures of greenhouse example, future socio-economic and technological developments that gas (GHG) emissions, atmospheric concentrations, or global mean may or may not be realized. See also Climate projection, Scenario and surface temperatures implied from mitigation and adaptation actions Pathways. associated with a set of broad and irreversible economic, technological, Purchasing power parity (PPP) The purchasing power of a currency societal and behavioural changes. This can encompass changes in the is expressed using a basket of goods and services that can be bought way energy and infrastructure are used and produced, natural resources with a given amount in the home country. International comparison of, are managed and institutions are set up and in the pace and direction of for example, gross domestic products (GDPs) of countries can be based technological change. on the purchasing power of currencies rather than on current exchange See also Scenario, Scenario storyline, Emission scenario, Mitigation rates. PPP estimates tend to lower the gap between the per capita GDP in scenario, Baseline scenario, Stabilization (of GHG or CO2-equivalent industrialized and developing countries. See also Market exchange rate concentration) and Narratives. (MER). Peri-urban areas Peri-urban areas are those parts of a city that Radiative forcing Radiative forcing is the change in the net, appear to be quite rural but are in reality strongly linked functionally to downward minus upward, radiative flux (expressed in W m-2) at the the city in its daily activities. tropopause or top of atmosphere due to a change in a driver of climate Permafrost Ground (soil or rock and included ice and organic change, such as a change in the concentration of carbon dioxide (CO2) material) that remains at or below 0°C for at least two consecutive years. or the output of the Sun. The traditional radiative forcing is computed with all tropospheric properties held fixed at their unperturbed values, pH pH is a dimensionless measure of the acidity of a solution given by and after allowing for stratospheric temperatures, if perturbed, to its concentration of hydrogen ions ([H+]). pH is measured on a logarithmic readjust to radiative-dynamical equilibrium. Radiative forcing is called scale where pH = -log +10[H ]. Thus, a pH decrease of 1 unit corresponds to instantaneous if no change in stratospheric temperature is accounted for. a 10-fold increase in the concentration of H+, or acidity. The radiative forcing once rapid adjustments are accounted for is termed 556 Glossary Annex I the effective radiative forcing. Radiative forcing is not to be confused identity and structure while also maintaining the capacity for adaptation, with cloud radiative forcing, which describes an unrelated measure of learning and transformation. This definition builds from the definition the impact of clouds on the radiative flux at the top of the atmosphere. used by Arctic Council (2013). See also Hazard, Risk and Vulnerability. Reasons for Concern (RFCs) Elements of a classification Risk The potential for adverse consequences where something of framework, first developed in the IPCC Third Assessment Report, which value is at stake and where the occurrence and degree of an outcome aims to facilitate judgments about what level of climate change may be is uncertain. In the context of the assessment of climate impacts, the dangerous (in the language of Article 2 of the UNFCCC) by aggregating term risk is often used to refer to the potential for adverse consequences AI risks from various sectors, considering hazards, exposures, vulnerabilities, of a climate-related hazard, or of adaptation or mitigation responses to capacities to adapt, and the resulting impacts. such a hazard, on lives, livelihoods, health and well-being, ecosystems and species, economic, social and cultural assets, services (including Reducing Emissions from Deforestation and Forest Degradation ecosystem services), and infrastructure. Risk results from the interaction (REDD+) An effort to create financial value for the carbon stored in of vulnerability (of the affected system), its exposure over time (to the forests, offering incentives for developing countries to reduce emissions hazard), as well as the (climate-related) hazard and the likelihood of its from forested lands and invest in low-carbon paths to sustainable occurrence. development (SD). It is therefore a mechanism for mitigation that results from avoiding deforestation. REDD+ goes beyond deforestation and Risk assessment The qualitative and/or quantitative scientific forest degradation, and includes the role of conservation, sustainable estimation of risks. See also Risk, Risk management and Risk perception. management of forests and enhancement of forest carbon stocks. Risk management Plans, actions, strategies or policies to reduce the The concept was first introduced in 2005 in the 11th Session of the likelihood and/or consequences of risks or to respond to consequences. Conference of the Parties (COP) in Montreal and later given greater See also Risk, Risk assessment and Risk perception. recognition in the 13th Session of the COP in 2007 at Bali and inclusion in the Bali Action Plan, which called for ‘policy approaches and positive Risk perception The subjective judgment that people make about incentives on issues relating to reducing emissions from deforestation the characteristics and severity of a risk. See also Risk, Risk assessment and forest degradation in developing countries (REDD) and the role of and Risk management. conservation, sustainable management of forests and enhancement Runoff The flow of water over the surface or through the subsurface, of forest carbon stock in developing countries.’ Since then, support for which typically originates from the part of liquid precipitation and/or REDD has increased and has slowly become a framework for action snow/ice melt that does not evaporate or refreeze, and is not transpired. supported by a number of countries. See also Hydrological cycle. Reference period The period relative to which anomalies are Scenario A plausible description of how the future may develop computed. See also Anomaly. based on a coherent and internally consistent set of assumptions Reference scenario See Baseline scenario. about key driving forces (e.g., rate of technological change, prices) and relationships. Note that scenarios are neither predictions nor forecasts, Reforestation Planting of forests on lands that have previously but are used to provide a view of the implications of developments contained forests but that have been converted to some other use. For and actions. See also Baseline scenario, Emission scenario, Mitigation a discussion of the term forest and related terms such as afforestation, scenario and Pathways. reforestation and deforestation, see the IPCC Special Report on Land Use, Land-Use Change, and Forestry (IPCC, 2000), information provided by Scenario storyline A narrative description of a scenario (or family of the United Nations Framework Convention on Climate Change (UNFCCC, scenarios), highlighting the main scenario characteristics, relationships 2013), the report on Definitions and Methodological Options to between key driving forces and the dynamics of their evolution. Also Inventory Emissions from Direct Human-induced Degradation of Forests referred to as ‘narratives’ in the scenario literature. See also Narratives. and Devegetation of Other Vegetation Types (IPCC, 2003). See also SDG-interaction score A seven-point scale (Nilsson et al., 2016) Deforestation, Afforestation and Reducing Emissions from Deforestation used to rate interactions between mitigation options and the SDGs. and Forest Degradation (REDD+). Scores range from +3 (indivisible) to −3 (cancelling), with a zero score Region A region is a relatively large-scale land or ocean area indicating ‘consistent’ but with neither a positive or negative interaction. characterized by specific geographical and climatological features. The The scale, as applied in this report, also includes direction (whether the climate of a land-based region is affected by regional and local scale interaction is uni- or bi-directional) and confidence as assessed per IPCC features like topography, land use characteristics and large water guidelines. bodies, as well as remote influences from other regions, in addition to Sea ice Ice found at the sea surface that has originated from the freezing global climate conditions. The IPCC defines a set of standard regions for of seawater. Sea ice may be discontinuous pieces (ice floes) moved on the analyses of observed climate trends and climate model projections (see ocean surface by wind and currents (pack ice), or a motionless sheet Figure 3.2; AR5, SREX). attached to the coast (land-fast ice). Sea ice concentration is the fraction Remaining carbon budget Estimated cumulative net global of the ocean covered by ice. Sea ice less than one year old is called first- anthropogenic CO2 emissions from the start of 2018 to the time that year ice. Perennial ice is sea ice that survives at least one summer. It may anthropogenic CO2 emissions reach net zero that would result, at some be subdivided into second-year ice and multi-year ice, where multi-year probability, in limiting global warming to a given level, accounting for the ice has survived at least two summers. impact of other anthropogenic emissions. Sea level change (sea level rise/sea level fall) Sea level can Representative Concentration Pathways (RCPs) See Pathways. change, both globally and locally (relative sea level change) due to (1) a change in ocean volume as a result of a change in the mass of water in Resilience The capacity of social, economic and environmental the ocean, (2) changes in ocean volume as a result of changes in ocean systems to cope with a hazardous event or trend or disturbance, water density, (3) changes in the shape of the ocean basins and changes responding or reorganizing in ways that maintain their essential function, 557 Annex I Glossary in the Earth’s gravitational and rotational fields, and (4) local subsidence as a special case both for their environment and development at the or uplift of the land. Global mean sea level change resulting from change Rio Earth Summit in Brazil in 1992. Fifty-eight countries and territories in the mass of the ocean is called barystatic. The amount of barystatic are presently classified as SIDS by the UN OHRLLS, with 38 being UN sea level change due to the addition or removal of a mass of water is member states and 20 being Non-UN Members or Associate Members of called its sea level equivalent (SLE). Sea level changes, both globally and the Regional Commissions (UN-OHRLLS, 2018). locally, resulting from changes in water density are called steric. Density Social cost of carbon (SCC) The net present value of aggregate changes induced by temperature changes only are called thermosteric, climate damages (with overall harmful damages expressed as a number AI while density changes induced by salinity changes are called halosteric. with positive sign) from one more tonne of carbon in the form of carbon Barystatic and steric sea level changes do not include the effect of dioxide (CO ), conditional on a global emissions trajectory over time. changes in the shape of ocean basins induced by the change in the ocean 2 mass and its distribution. Social costs The full costs of an action in terms of social welfare losses, including external costs associated with the impacts of this action Sea surface temperature (SST) The sea surface temperature is on the environment, the economy (GDP, employment) and on the society the subsurface bulk temperature in the top few meters of the ocean, as a whole. measured by ships, buoys, and drifters. From ships, measurements of water samples in buckets were mostly switched in the 1940s to samples Social-ecological systems An integrated system that includes from engine intake water. Satellite measurements of skin temperature human societies and ecosystems, in which humans are part of nature. (uppermost layer; a fraction of a millimeter thick) in the infrared or The functions of such a system arise from the interactions and the top centimeter or so in the microwave are also used, but must be interdependence of the social and ecological subsystems. The system’s adjusted to be compatible with the bulk temperature. structure is characterized by reciprocal feedbacks, emphasising that humans must be seen as a part of, not apart from, nature. This definition Sendai Framework for Disaster Risk Reduction The Sendai builds from Arctic Council (2016) and Berkes and Folke (1998). Framework for Disaster Risk Reduction 2015–2030 outlines seven clear targets and four priorities for action to prevent new, and to reduce Social inclusion A process of improving the terms of participation existing, disaster risks. The voluntary, non-binding agreement recognizes in society, particularly for people who are disadvantaged, through that the State has the primary role to reduce disaster risk but that enhancing opportunities, access to resources, and respect for rights (UN responsibility should be shared with other stakeholders, including local DESA, 2016). government and the private sector. Its aim is to achieve ‘substantial Social justice See Justice. reduction of disaster risk and losses in lives, livelihoods and health and in the economic, physical, social, cultural and environmental assets of Social learning A process of social interaction through which people persons, businesses, communities and countries.’ learn new behaviours, capacities, values and attitudes. Sequestration See Uptake. Social value of mitigation activities (SVMA) Social, economic and environmental value of mitigation activities that include, in addition Shared Socio-economic Pathways (SSPs) See Pathways. to their climate benefits, their co-benefits to adaptation and sustainable Short-lived climate forcers (SLCF) Short-lived climate forcers development objectives. refers to a set of compounds that are primarily composed of those with Societal (social) transformation See Transformation. short lifetimes in the atmosphere compared to well-mixed greenhouse gases, and are also referred to as near-term climate forcers. This set Socio-economic scenario A scenario that describes a possible of compounds includes methane (CH4), which is also a well-mixed future in terms of population, gross domestic product (GDP), and other greenhouse gas, as well as ozone (O3) and aerosols, or their precursors, socio-economic factors relevant to understanding the implications of and some halogenated species that are not well-mixed greenhouse gases. climate change. See also Baseline scenario, Emission scenario, Mitigation These compounds do not accumulate in the atmosphere at decadal to scenario and Pathways. centennial time scales, and so their effect on climate is predominantly Socio-technical transitions Socio-technical transitions are where in the first decade after their emission, although their changes can still technological change is associated with social systems and the two are induce long-term climate effects such as sea level change. Their effect inextricably linked. can be cooling or warming. A subset of exclusively warming short-lived climate forcers is referred to as short-lived climate pollutants. See also Soil carbon sequestration (SCS) Land management changes Long-lived climate forcers (LLCF). which increase the soil organic carbon content, resulting in a net removal of CO from the atmosphere. Short-lived climate pollutants (SLCP) See Short-lived climate 2 forcers (SLCF). Soil moisture Water stored in the soil in liquid or frozen form. Root- zone soil moisture is of most relevance for plant activity. Sink A reservoir (natural or human, in soil, ocean, and plants) where a greenhouse gas, an aerosol or a precursor of a greenhouse gas is stored. Solar radiation management See Solar radiation modification (SRM). Note that UNFCCC Article 1.8 refers to a sink as any process, activity or Solar radiation modification (SRM) Solar radiation modification mechanism which removes a greenhouse gas, an aerosol or a precursor refers to the intentional modification of the Earth’s shortwave radiative of a greenhouse gas from the atmosphere. See also Uptake. budget with the aim of reducing warming. Artificial injection of Small island developing states (SIDS) Small island developing stratospheric aerosols, marine cloud brightening and land surface albedo states (SIDS), as recognised by the United Nations OHRLLS (Office of modification are examples of proposed SRM methods. SRM does not the High Representative for the Least Developed Countries, Landlocked fall within the definitions of mitigation and adaptation (IPCC, 2012b, p. Developing Countries and Small Island Developing States), are a distinct 2). Note that in the literature SRM is also referred to as solar radiation group of developing countries facing specific social, economic and management or albedo enhancement. environmental vulnerabilities (UN-OHRLLS, 2011). They were recognized 558 Glossary Annex I Stabilization (of GHG or CO2-equivalent concentration) A Societal (social) transformation state in which the atmospheric concentrations of one greenhouse gas A profound and often deliberate shift initiated by communities toward (GHG) (e.g., carbon dioxide) or of a CO2-equivalent basket of GHGs (or a sustainability, facilitated by changes in individual and collective values combination of GHGs and aerosols) remains constant over time. and behaviours, and a fairer balance of political, cultural, and institutional power in society. Stranded assets Assets exposed to devaluations or conversion to ‘liabilities’ because of unanticipated changes in their initially expected Transformation pathways See Pathways. revenues due to innovations and/or evolutions of the business context, Transformational adaptation See Adaptation. AI including changes in public regulations at the domestic and international levels. Transformative change A system-wide change that requires more than technological change through consideration of social and economic Stratosphere The highly stratified region of the atmosphere above factors that, with technology, can bring about rapid change at scale. the troposphere extending from about 10 km (ranging from 9 km at high latitudes to 16 km in the tropics on average) to about 50 km altitude. See Transient climate response See Climate sensitivity. also Atmosphere, and Troposphere. Transient climate response to cumulative CO2 emissions Sub-national actor Sub-national actors include state/provincial, (TCRE) The transient global average surface temperature change per regional, metropolitan and local/municipal governments as well as non- unit cumulative CO2 emissions, usually 1000 GtC. TCRE combines both party stakeholders, such as civil society, the private sector, cities and other information on the airborne fraction of cumulative CO2 emissions (the sub-national authorities, local communities and indigenous peoples. fraction of the total CO2 emitted that remains in the atmosphere, which is determined by carbon cycle processes) and on the transient climate Substantive rights See Human rights. response (TCR). See also Transient climate response (under Climate Supply-side measures See Demand- and supply-side measures. sensitivity). Surface temperature See Global mean surface temperature (GMST), Transit-oriented development (TOD) An approach to urban Land surface air temperature, Global mean surface air temperature development that maximizes the amount of residential, business and (GSAT) and Sea surface temperature (SST). leisure space within walking distance of efficient public transport, so as to enhance mobility of citizens, the viability of public transport and the Sustainability A dynamic process that guarantees the persistence of value of urban land in mutually supporting ways. natural and human systems in an equitable manner. Transition The process of changing from one state or condition Sustainable development (SD) Development that meets the needs to another in a given period of time. Transition can be in individuals, of the present without compromising the ability of future generations to firms, cities, regions and nations, and can be based on incremental or meet their own needs (WCED, 1987) and balances social, economic and transformative change. environmental concerns. See also Sustainable Development Goals (SDGs) and Development pathways (under Pathways). Tropical cyclone The general term for a strong, cyclonic-scale disturbance that originates over tropical oceans. Distinguished from Sustainable Development Goals (SDGs) The 17 global goals weaker systems (often named tropical disturbances or depressions) by for development for all countries established by the United Nations exceeding a threshold wind speed. A tropical storm is a tropical cyclone through a participatory process and elaborated in the 2030 Agenda for with one-minute average surface winds between 18 and 32 m s-1. Beyond Sustainable Development, including ending poverty and hunger; ensuring 32 m s-1, a tropical cyclone is called a hurricane, typhoon, or cyclone, health and well-being, education, gender equality, clean water and depending on geographic location. See also Extratropical cyclone. energy, and decent work; building and ensuring resilient and sustainable infrastructure, cities and consumption; reducing inequalities; protecting Troposphere The lowest part of the atmosphere, from the surface land and water ecosystems; promoting peace, justice and partnerships; to about 10 km in altitude at mid-latitudes (ranging from 9 km at high and taking urgent action on climate change. See also Sustainable latitudes to 16 km in the tropics on average), where clouds and weather development (SD). phenomena occur. In the troposphere, temperatures generally decrease with height. See also Atmosphere and Stratosphere. Technology transfer The exchange of knowledge, hardware and associated software, money and goods among stakeholders, which Uncertainty A state of incomplete knowledge that can result from leads to the spread of technology for adaptation or mitigation. The a lack of information or from disagreement about what is known or term encompasses both diffusion of technologies and technological even knowable. It may have many types of sources, from imprecision in cooperation across and within countries. the data to ambiguously defined concepts or terminology, incomplete understanding of critical processes, or uncertain projections of human Temperature overshoot The temporary exceedance of a specified behaviour. Uncertainty can therefore be represented by quantitative level of global warming, such as 1.5°C. Overshoot implies a peak followed measures (e.g., a probability density function) or by qualitative by a decline in global warming, achieved through anthropogenic removal statements (e.g., reflecting the judgment of a team of experts) (see Moss of CO2 exceeding remaining CO2 emissions globally. See also Overshoot and Schneider, 2000; IPCC, 2004; Mastrandrea et al., 2010). See also pathways and Non-overshoot pathways (both under Pathways). Confidence and Likelihood. Tipping point A level of change in system properties beyond which United Nations Framework Convention on Climate Change a system reorganizes, often abruptly, and does not return to the initial (UNFCCC) The UNFCCC was adopted in May 1992 and opened for state even if the drivers of the change are abated. For the climate system, signature at the 1992 Earth Summit in Rio de Janeiro. It entered into force it refers to a critical threshold when global or regional climate changes in March 1994 and as of May 2018 had 197 Parties (196 States and the from one stable state to another stable state. See also Irreversibility. European Union). The Convention’s ultimate objective is the ‘stabilisation Transformation A change in the fundamental attributes of natural of greenhouse gas concentrations in the atmosphere at a level that and human systems. would prevent dangerous anthropogenic interference with the climate 559 Annex I Glossary system.’ The provisions of the Convention are pursued and implemented by two treaties: the Kyoto Protocol and the Paris Agreement. See also Kyoto Protocol and Paris Agreement. Uptake The addition of a substance of concern to a reservoir. See also Carbon sequestration and Sink. Vulnerability The propensity or predisposition to be adversely AI affected. 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In Press. 563 Annex II Acronyms μatm Microatmospheres BET Basic Energy systems, Economy, Environment, and End-use Technology Model 1.5DS 1.5 Degree Scenario BEV Battery Electric Vehicle 2DS 2 Degree Scenario BNEF Bloomberg New Energy Finance ACCESS Australian Community Climate and Earth-System Simulator BNU Beijing Normal University ACCMIP Atmospheric Chemistry and BRT Bus Rapid Transit Climate Model Intercomparison Project cm Centimetres ACCRN The Asian Cities Climate C Carbon Change Resilience Network CA Conservation Agriculture ACOLA Australian Council of Learned Academies CAF Corporacion Andina de Fomento ACs Air Conditioners (Development Bank of Latin America) ADB Asian Development Bank AII CAM Central America/Mexico AII ADVANCE Advanced Model Development and Validation or Community Atmosphere Model for the Improved Analysis of Costs and Impacts CAMx Comprehensive Air Quality Model with Extensions of Mitigation Policies CanESM Canadian Earth System Model AEZ Agro-Ecological Zone CanRCM Canadian Regional Climate Model AfDB African Development Bank CAR Small Islands Regions Caribbean AFOLU Agriculture, Forestry and Other Land-Use CAS Central Asia AGCM Atmospheric General Circulation Model Cat-HM Catchment-scale Hydrological Models AI Artificial Intelligence CbA Community-based Adaptation AIM Asia-Pacific Integrated Model CBA Cost-Benefit Analysis ALA Alaska/Northwest Canada CBD Convention on Biological Diversity AMAP Arctic Monitoring and Assessment Programme CBDR-RC Common But Differentiated Responsibilities AMOC Atlantic Meridional Overturning Circulation and Respective Capabilities AMP Adjusting Mitigation Pathway CBS & GNH Centre for Bhutan Studies AMZ Amazon and Gross National Happiness Research ANT Antarctica CC Carbon Capture APEX Air Pollutants Exposure Model CCAM Conformal Cubic Atmospheric Model AR Afforestation and Reforestation CCC Constant Composition Commitment AR4 IPCC Fourth Assessment Report CCCma Canadian Centre for Climate Modelling and Analysis AR5 IPCC Fifth Assessment Report CCRIF Caribbean Catastrophe Risk Insurance Facility AR6 IPCC Sixth Assessment Report CCS Carbon dioxide Capture and Storage ARC Arctic CCSM Community Climate System Model ASEAN Association of Southeast Asian Nations CCT Cirrus Cloud Thinning ASIA Non-OECD Asia CCU Carbon dioxide Capture and Utilisation AUD Australian Dollar CCUS Carbon dioxide Capture, Utilisation and Storage B2DS Beyond 2 Degrees Scenario CDD Consecutive Dry Days BASIC Brazil, South Africa, India, China CD-LINKS Linking Climate and Development Policies BC Black Carbon – Leveraging International BCC-CSM Beijing Climate Center Climate System Model Networks and Knowledge Sharing BCM Bergen Climate Model CDM Clean Development Mechanism BECCS Bioenergy with Carbon CDP Carbon Disclosure Project dioxide Capture and Storage CDR Carbon Dioxide Removal 564 Acronyms Annex II CEA Cost-Effectiveness Analysis CRISPR Clustered Regularly Interspaced Short Palindromic Repeats CEC Clean Energy Council C-ROADS Climate Rapid Overview And Decision-support CEDS Community Emissions Data System Simulator CEMICS Contextualizing Climate Engineering and Mitigation: CRU Climatic Research Unit Illusion, Complement or Substitute? CSA Climate-Smart Agriculture CES Constant Elasticity of Substitution CSC Climate Service Center Germany CESM Community Earth System Model CSDI Cold Spell Duration Index CEU Central Europe CSIRO Commonwealth Scientific and Industrial CFCs Chlorofluorocarbons Research Organisation CGCM Coupled Global Climate Model CSP Concentrated Solar Power CGE Computable General Equilibrium CSR Corporate Social Responsibility AII CGI Canada/Greenland/Iceland AIICTC Covenant Territorial Coordinator CGIAR Consultative Group on International Agricultural CWD Consecutive Wet Days Research DACCS Direct Air Carbon dioxide Capture and Storage CH4 Methane DACS Direct Air Capture and Storage CHP Combined Heat and Power DALY Disability Adjusted Life Year CI Confidence Interval DICE Dynamic Integrated Climate-Economy model CIRED Centre International de Recherche sur l’Environnement et le Développement DJF December, January, February CISL Cambridge Institute for Sustainability Leadership DM8H Daily Maximum 8-Hour exposure CLM Climate Limited-area Modelling DNE21+ Dynamic New Earth 21 model CMAQ Community Multiscale Air Quality Modeling System DOE Department of Energy (USA) CMIP3 Coupled Model Intercomparison Project Phase 3 DRI Direct Reduced Iron CMIP5 Coupled Model Intercomparison Project Phase 5 DRM Disaster Risk Management CMIP6 Coupled Model Intercomparison Project Phase 6 DTU Technical University of Denmark CNA Central North America E Equilibrium, Evaporation or Evapotranspiration CNRM Centre National de Recherches Météorologiques EAF East Africa CO Carbon monoxide EAIS East Antarctic Ice Sheet CO2 Carbon dioxide EAS East Asia CO2e Carbon dioxide equivalent EbA Ecosystems-based Adaptation CO2eq Carbon dioxide equivalent EC European Commission CoM Covenant of Mayors ECF European Climate Foundation COP Conference of the Parties ECMWF European Centre for Medium-Range Weather Forecasts COPPE-COFFEE Programa de Planejamento Energético – COmputable Framework For Energy and ECS Equilibrium Climate Sensitivity the Environment EDGAR Emission Database for Global Atmospheric CORDEX Coordinated Regional Research Climate Downscaling Experiment EEA European Environment Agency COSMO Consortium for Small-scale Modeling EGMAM ECHO-G Middle Atmosphere Model CRCM Canadian Regional Climate Model E-HYPE European Hydrological Predictions CRDPs Climate-Resilient Development Pathways for the Environment CRIEPI Institut Central de Recherche des Industries EJ Exajoules Électriques EMEP European Monitoring and Evaluation Programme 565 Annex II Acronyms EMF Energy Modeling Forum F-gas Fluorinated gases EMIC Earth-system Model of Intermediate Complexity FGOALS Flexible Global Ocean-Atmosphere-Land System model ENA East North America FIO First Institute of Oceanography ENSO El Niño-Southern Oscillation FMNR Farmer Managed Natural Regeneration EOR Enhanced Oil Recovery FUND Climate Framework for Uncertainty, EPA Environmental Protection Agency (USA) Negotiation, and Distribution model EPIs Energy-Intensive Processing Industries FUSSR Former Union of Soviet Socialist Republics ERA ECMWF ReAnalysis g Grams ERF Effective Radiative Forcing GAMS General Algebraic Modeling System ERFaci Effective Radiative Forcing from aerosol-cloud GBAM Ground-Based Albedo Modification interactions AII GCAM Global Change Assessment Model ERFari Effective Radiative Forcing from aerosol-radiation AII interactions GCC Gulf Cooperative Council ESCOs Energy Service Companies GCEC Global Commission on the Economy and Climate ESL Extreme Sea Level GCM General Circulation Model or Global Climate Model ESM Earth System Model GCP Global Carbon Project ESR Empirical Scaling Relationship GDP Gross Domestic Product ESRB ASC European Systemic Risk Board Advisory GE General Equilibrium Scientific Committee GEA Global Energy Assessment ESRL NOAA Earth System Research Laboratory GEM-E3 General Equilibrium Model for Economy - Eta-CPTEC Eta Centro de Previsão do Tempo e Energy - Environment Estudos Climáticos GENeSYS-MOD Global Energy System Model ETP Pacific Islands region [3] or Energy Technology GeSI Global e-Sustainability Initiative Perspectives model GFCF Gross Fixed Capital Formation ETS Emission Trading Scheme GFDL Geophysical Fluid Dynamic Laboratory EU European Union GFR Grid Flexibility Resources EU-FP6 European Union Sixth Framework Programme Gha Gigahectares EUG4 France, Germany, Italy, United Kingdom GHCNDEX Global Historical Climatology Network – EURO-CORDEX European branch of the Coordinated Regional Daily climate Extremes Climate Downscaling Experiment GHGs Greenhouse Gases EV Electric Vehicle GHM Global Hydrological Models EW Enhanced Weathering GIS Greenland Ice Sheet FAIR Finite Amplitude Impulse Response model GISS Goddard Institute for Space Studies FAO Food and Agriculture Organization of the United Nations GISTEMP Goddard Institute for Space Studies Surface Temperature Analysis FAOSTAT Database Collection of the Food and Agriculture Organization of the United Nations GJ Gigajoules FAQ Frequently Asked Questions GLEAM Global Livestock Environmental Assessment Model FARM Future Agricultural Resources Model Glob-HM Global Hydrological Model Fe Iron GLOBIOM GLObal BIOsphere Management model FE Final Energy GLOFs Glacial Lake Outburst Floods FEMA Federal Emergency Management Agency (USA) GM Genetically Modified FF Fossil Fuel GMO Genetically Modified Organism FF&I Fossil-Fuel combustion and Industrial processes GMSL Global Mean Sea Level 566 Acronyms Annex II GMST Global Mean Surface Temperature ICSU International Council for Science GMT Global Mean Temperature ICT Information and Communication Technology GNHI Gross National Happiness Index IEA International Energy Agency GPP Gross Primary Productivity IEAGHG IEA Greenhouse Gas R&D Programme GPT General Purpose Technologies IFAD International Fund for Agricultural Development GRAPE Global Relationship Assessment to Protect IFPRI International Food Policy Research Institute the Environment model IGCC Integrated Gasification Combined Cycle GSAT Global mean Surface Air Temperature IIASA International Institute for Applied Systems Analysis Gt Gigatonne IIF Institute of International Finance GTP Global Temperature-change Potential iLUC Indirect Land-Use Change GWA Government of Western Australia IMACLIM-NLU IMpact Assessment of CLIMate policies model – AII GWP Global Warming Potential or Gross World Product Nexus Land-Use model AII ha Hectares IMAGE Integrated Model to Assess the Global Environment H2 Hydrogen IMF International Monetary Fund HadCM Hadley Centre Coupled Model IMO International Maritime Organization HadCRUT Hadley Centre Climatic Research Unit Gridded IMPACT2C Quantifying Projected Impacts under 2°C Warming Surface Temperature Data Set INDCs Intended Nationally Determined Contributions HadEX Hadley Centre Global Climate Extremes index INM Russian Institute for Numerical Mathematics HadGEM Hadley Centre Global Environmental Model IOM International Organization for Migration HadRM Hadley Centre Regional Model IoT Internet of Things HAPPI Half a degree Additional warming, IPCC Intergovernmental Panel on Climate Change Prognosis and Projected Impacts IPSL Institute Pierre Simon Laplace HDV Heavy-Duty Vehicle IRENA International Renewable Energy Agency HEV Hybrid Electric Vehicle ISIMIP Inter-Sectoral Impact Model Intercomparison HFCs Hydrofluorocarbons Project HLCCP High-Level Commission on Carbon Prices ISO International Standards Organisation HLPE High Level Panel of Experts on Food Security ISSC International Social Science Council and Nutrition ITF International Transport Forum HSRTF Hurricane Sandy Rebuilding Task Force IUCN International Union for Conservation of Nature HTM Holocene Thermal Maximum IWG Interagency Working Group on Social Cost HYMOD HYdrological MODel of Greenhouse Gases IAEA International Atomic Energy Agency IWRM Integrated Water Resources Management IAMC Integrated Assessment Modelling Consortium JeDi Jena Diversity-Dynamic Global Vegetation Model IAMs Integrated Assessment Models JJA June, July, August IBA International Bar Association JMA Japan Meteorological Agency IBI International Biochar Initiative JRA-55 Japanese 55-year Reanalysis ICAMS Integrated Climate and Air Quality JRC European Commission – Joint Research Centre Modeling System JULES Joint United Kingdom Land Environment Simulator ICEM International Centre for Environmental Management kcal cap-1 day-1 Kilocalories per capita per day ICLEI International Council for Local Environmental km Kilometres Initiatives kt Kilotonnes ICPDR International Commission for the Protection of the Danube River kWh Kilowatt hours 567 Annex II Acronyms KNMI Koninklijk Nederlands Meteorologisch Instituut MER Market Exchange Rates (Royal Netherlands Meteorological Institute) MERET Managing Environmental Resources to L Litres Enable Transitions L&D Loss and Damage MERGE-ETL Model for Evaluating Regional and Global Effects of greenhouse gas reduction policies – LAM Latin America and Caribbean Endogenous Technology Learning LDCs Least Developed Countries MESSAGE Model for Energy Supply Systems And their LDMz-INCA Laboratoire de Météorologie Dynamique General Environmental impact – INteractions between Chemistry and Aerosols Mha Megahectare LDV Light-Duty Vehicle MIROC Model for Interdisciplinary Research on Climate LE Limited Evidence MISI Marine Ice Sheet Instability LED Low Energy Demand or Light Emitting Diode MIT IGSM Massachusetts Institute of Technology Integrated AII LGM Last Glacial Maximum Global System Model AII LIG Last Interglacial MJ Megajoules LLCFs Long-Lived Climate Forcers MoCC Ministry of Climate Change and Adaptation (Government of Vanuatu) LNG Liquefied Natural Gas MOHC Met Office Hadley Centre LPG Liquefied Petroleum Gas MOPEX Model Parameter Estimation Experiment LPJmL Lund-Potsdam-Jena managed Land model MPAs Marine Protected Areas LTA Land Transport Authority of Singapore MPI Max-Planck-Institut für Meteorologie LTGG Long-Term Global Goal (Max Planck Institute for Meteorology) LUC Land-Use Change MPWP Mid Pliocene Warm Period LULUCF Land Use, Land-Use Change, and Forestry MRFCJ Mary Robinson Foundation – Climate Justice m Metres MRI Meteorological Research Institute of m3 cap-1 yr-1 Cubic metres per capita per year Japan Meteorological Agency mg Milligrams MRV Measurement, Reporting and Verification mL Millilitres MSR Multi-Sector Risk score mm Millimetres Mt Megatonnes M&E Monitoring and Evaluation N Nitrogen Ma Million years ago N2O Nitrous oxide MAC Marginal Abatement Cost NAP National Adaptation Plan MacPDM Macro-scale – Probability-Distributed Moisture NAS North Asia Model NASA National Aeronautics and Space Administration MAGICC Model for the Assessment of Greenhouse Gas NASEM National Academies of Sciences, Engineering, Induced Climate Change and Medicine MAgPIE Model of Agricultural Production and its Impact NAU North Australia on the Environment NCAR National Center for Atmospheric Research MAM March, April, May NCCARF National Climate Change Adaptation Research MCB Marine Cloud Brightening Facility MCCA Mercado Común Centroamericano NCE New Climate Economy MDB Group of Multilateral Development Banks NDCs Nationally Determined Contributions MDGs Millennium Development Goals NEA Nuclear Energy Agency MEA Millennium Ecosystem Assessment NEB North-East Brazil MED South Europe/Mediterranean NEC National Environment Commission MEPS Minimum Energy Performance Standards (Royal Government of Bhutan) 568 Acronyms Annex II NETL National Energy Technology Laboratory PDSI Palmer Drought Severity Index (US Department of Energy) PE Primary Energy or Partial Equilibrium NEU North Europe PET Physiologically Equivalent Temperature or NF3 Nitrogen trifluoride Potential Evapo-Transpiration NGO Non-Governmental Organization PFCs Perfluorocarbons NH3 Ammonia Pg Petagrams NHD Number of Hot Days PHEV Plug-in Hybrid Electric Vehicle NITI Aayog National Institution for Transforming India PIK Potsdam-Institut für Klimafolgenforschung (Potsdam Institute for Climate Impact Research) NMVOC Non-Methane Volatile Organic Compounds PM10 Particulate Matter with Aerodynamic NOAA National Oceanic and Atmospheric Administration Diameter <10 μm NorESM Norwegian Earth System Model PM2.5 Particulate Matter with Aerodynamic AII NOx Nitrogen oxides Diameter <2.5 μm AII NPCC New York City Panel on Climate Change POLES Prospective Outlook on Long-term Energy Systems model NPP Net Primary Productivity PPP Purchasing Power Parity NPV Net Present Value PR Probability Ratio NRC National Research Council PV Photovoltaics NSR Northern Sea Route R&D Research and Development NTP Pacific Islands region [2] RCA Rossby Centre Regional Atmospheric Model NYC New York City RCI Rotterdam Climate Initiative NZAGRC New Zealand Agricultural Greenhouse Gas Research Center RCM Regional Climate Model O2 Oxygen RCPs Representative Concentration Pathways O3 Ozone REDD+ Reducing Emissions from Deforestation and forest Degradation; and the role of conservation, OA Ocean Acidification or Ocean Alkalinization sustainable management of forests and OC Organic Carbon enhancement of forest carbon stocks in developing countries OECD Organisation for Economic Co-operation and Development ReEDS-IPM Regional Electricity Deployment System model – Integrated Planning Model OGCC Optimal Gasification Combined Cycle RegCM Regional Climate Model system OHCHR Office of the United Nations High Commissioner for Human Rights REMIND REgional Model of INvestments and Development OIF Ocean Iron Fertilisation REN21 Renewable Energy Policy Network for the 21st Century ORCHIDEE ORganising Carbon and Hydrology In Dynamic EcosystEms model RF Radiative Forcing ORR NYC Mayor’s Office of Recovery & Resiliency RFC Reason for Concern OS Overshoot RGoB Royal Government of Bhutan pp People RMI Rocky Mountain Institute ppb Parts per billion RNCFC Reference Non-CO2 Forcing Contribution ppm Parts per million RNCTC Reference Non-CO2 Temperature Contribution ppt Parts per thousand Rx1day Annual maximum 1-day precipitation P Precipitation or Phosphorous Rx5day Annual maximum 5-day precipitation PAGE Policy Analysis of the Greenhouse Effect model SAF Southern Africa PAHO Pan American Health Organization SAH Sahara PCM Parallel Climate Model SAI Stratospheric Aerosol Injection 569 Annex II Acronyms SAMS South American Monsoon System SREX IPCC Special Report on Managing the Risks of Extreme Events and Disasters to Advance Climate SAR IPCC Second Assessment Report Change Adaptation SAS South Asia SRM Solar Radiation Modification SAT Surface Air Temperature SROCC IPCC Special Report on the Ocean and Cryosphere SAU South Australia/New Zealand in a Changing Climate SBSTA Subsidiary Body for Scientific and Technological SSA Southeastern South America Advice (UNFCCC) SSPs Shared Socioeconomic Pathways SCC Social Cost of Carbon SST Sea Surface Temperature SCS Soil Carbon Sequestration STP Southern Tropical Pacific SD Sustainable Development SWAT Soil & Water Assessment Tool SDGs Sustainable Development Goals SWF Social Welfare Function AII SDGVM Sheffield Dynamic Global Vegetation Model AIISYR IPCC Synthesis Report SDII Simple Daily Intensity Index t Tonnes SDSN Sustainable Development Solutions Network tDM Tonnes Dry Matter SEA Southeast Asia tril$ Trillion dollars SEAPs Sustainable Energy Action Plans T Temperature or Transient SED Structured Expert Dialogue T&D Transmission and Distribution SEM Semi-Empirical Model TCR Transient Climate Response SF6 Sulphur hexafluoride TCRE Transient Climate Response to cumulative SFM Sustainable Forest Management CO2 Emissions SIDS Small Island Developing States TEAP Technology and Economic Assessment Panel SIFMA Securities Industry and Financial Markets TFE Thematic Focus Element Association TFP Total Factor Productivity SLCFs Short-Lived Climate Forcers Tg Teragrams SLCPs Short-Lived Climate Pollutants TIB Tibetan Plateau SLR Sea Level Rise TNn Coldest night-time temperature of the year SM Supplementary Material TOD Transit Oriented Development SMA Soil Moisture Anomalies TS Technical Summary SMHI Swedish Meteorological and Hydrological Institute Tt Teratonnes SO2 Sulphur dioxide TTs Transition Towns SOLARIS HEPPA SOLARIS High Energy Particle Precipitation TXx Hottest daytime temperature of the year in the Atmosphere UCCRN Urban Climate Change Research Network SON September, October, November UHI Urban Heat Islands SOx Sulphur oxides UITP Union Internationale des Transports Publics SPAs Shared climate Policy Assumptions (International Association of Public Transport) SPC Secretariat of the Pacific Community UKCP United Kingdom Climate Projections SPEI Standardized Precipitation Evapotranspiration UN United Nations Index UN DESA United Nations Department of Economic SPI Standardised Precipitation Index and Social Affairs SPM Summary for Policymakers UNCBD United Nations Convention on Biological Diversity SR1.5 IPCC Special Report on Global Warming of 1.5°C UNDP United Nations Development Programme SRCCL IPCC Special Report on Climate Change and Land UNEP UN Environment SRES IPCC Special Report on Emissions Scenarios 570 Acronyms Annex II UNEP-WCMC UNEP World Conservation Monitoring Centre WGII IPCC Working Group II UNESCO United Nations Educational, Scientific and Cultura WGIII IPCC Working Group III Organization WHO World Health Organization UNFCCC United Nations Framework Convention on Climate WIM Warsaw International Mechanism for Loss Change and Damage UNGA United Nations General Assembly WIO West Indian Ocean UNICEF United Nations International Children’s WITCH World Induced Technical Change Hybrid Model Emergency Fund WMGHGs Well-Mixed Greenhouse Gases UNISDR United Nations Office for Disaster Risk Reduction WMO World Meteorological Organization UN-OHRLLS Office of the High Representative for the Least Developed Countries, Landlocked Developing WNA West North America Countries and Small Island Developing States WRF Weather Research and Forecasting AII UNRISD United Nations Research Institute for AII Social Development WSA West Coast South America UNSCEAR United Nations Scientific Committee on the WSDI Warm Spell Duration Index Effects of Atomic Radiation WTO World Trade Organization UNU United Nations University yr Year UNU-EHS United Nations University – Institute for ZEC Zero Emissions Commitment Environment and Human Security USD United States Dollars UV Ultraviolet VISIT Vegetation Integrative Simulator for Trace Gases VKT Vehicle Kilometres of Travel VOCs Volatile Organic Compounds w/ With w/o Without w.r.t. With respect to W Watts WAF West Africa WAIS West Antarctic Ice Sheet WAS West Asia WBCSD World Business Council for Sustainable Development WBGU Wissenschaftlicher Beirat der Bundesregierung Globale Umweltveränderungen (German Advisory Council on Global Change) WBM Water Balance Model WCED World Commission on Environment and Development WCRP World Climate Research Programme WEC World Energy Council WEF Water-Energy-Food or World Economic Forum WEM World Energy Model WEO World Energy Outlook WFP World Food Programme WGI IPCC Working Group I 571 Annex III: Contributors AIII to the IPCC Special Report on Global Warming of 1.5°C This annex should be cited as: IPCC, 2018: Annex III: Contributors to the IPCC Special Report on Global Warming of 1.5°C. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)]. In Press. 573 Annex III Contributors to the IPCC Special Report on Global Warming of 1.5°C ABDUL HALIM, Sharina BERRY, Peter CHEN, Yang Institute for Environment and Climate Change and Innovation Bureau IPCC WGI Technical Support Unit Development-LESTARI Health Canada Chinese Academy of Meteorological Sciences Malaysia Canada China ABDULLA, Amjad BERTOLDI, Paolo CHEUNG, William Climate Change Department European Commission University of British Columbia Ministry of Environment and Energy Italy Canada Maldives BHASKAR CHOUDHARY, Bishwa CONNORS, Sarah ACHLATIS, Michelle National Institute of Agricultural IPCC WGI Technical Support Unit University of Queensland Economics and Policy Research Université Paris-Saclay Australia/ Greece India France/UK ALEXANDER, Lisa BINDI, Marco CORREIA DE OLIVEIRA DE University of New South Wales University of Florence PORTUGAL PEREIRA, Joana Australia Italy IPCC WGIII Technical Support Unit Imperial College London’s Centre ALLEN, Myles R. BOER, Rizaldi for Environmental Policy University of Oxford Center for Climate Risk and UK/Portugal UK Opportunity Management Indonesia CRAIG, Marlies ANTWI-AGYEI, Philip IPCC WGII Technical Support Unit Kwame Nkrumah University of BOYER, Christopher School of Life Sciences Science and Technology University of Washington University of KwaZulu-Natal AIII Ghana USA South Africa ARAGÓN-DURAND, Fernando BRILLI, Lorenzo CRAMER, Wolfgang Institute for Environmental Studies University of Florence CNRS Program on Sustainable Development IBIMET-CNR Mediterranean Institute for El Colegio de México Italy Biodiversity and Ecology Mexico Aix-Marseille University BROWN, Sally France/Germany ARAOS, Malcolm University of Southampton Ministry of Environment and Energy UK DASGUPTA, Dipak Canada The Energy and Resources Institute (TERI) BUCKERIDGE, Marcos India BABIKER, Mustafa University of São Paulo Saudi Aramco Biosciences Institute DASGUPTA, Purnamita Sudan Brazil Institute of Economic Growth India BAKKER, Stefan BYERS, Edward Netherlands International Institute for DE CONINCK, Heleen Applied Systems Analysis Radboud University BANGALORE, Mook Austria/Brazil Netherlands/EU London School of Economics USA CALVIN, Katherine DE KLEIJNE, Kiane Pacific Northwest National Laboratory Radboud University BAZAZ, Amir USA Netherlands/EU Indian Institute for Human Settlements India CAMILLONI, Ines DEL MAR ZAMORA DOMINGUEZ, Maria Centro de Investigaciones del Mercator Research Institute on Global BELFER, Ella Mar y la Atmósfera Commons and Climate Change McGill University University of Buenos Aires Mexico USA Argentina DEN ELZEN, Michel BENTON, Tim CARTWRIGHT, Anton PBL Netherlands Environmental University of Leeds African Centre for Cities Assessment Agency UK South Africa Netherlands 574 Contributors to the IPCC Special Report on Global Warming of 1.5°C Annex III DIEDHIOU, Arona FIGUEROA, Maria GHERSI, Frédéric Institut de Recherche pour le Développement Copenhagen Business School Centre International de Recherches sur Ivory Coast/Senegal Danmark/Venezuela l’Environnement et le Développement (CIRED) CNRS DJALANTE, Riyanti FINON, Dominique France United Nations University Centre International de Recherches sur Institute for the Advanced Study l’Environnement et le Développement GILLETT, Nathan of Sustainability (UNU-IAS) France Environment and Climate Change Canada Japan/Indonesia Canada FISCHER, Hubertus Universität Bern GINZBURG, Veronika DONG, Wenjie Switzerland Institute of Global Climate and Sun Yat-sen University Ecology Roshydromet China FISCHLIN, Andreas Russian Federation Swiss Federal Institute of Technology DUBE, Opha Pauline Switzerland GRANDIS, Adriana University of Botswana University of São Paulo Botswana FLATO, Greg Biosciences Institute Environment and Climate Change Canada Brazil EAKIN, Hallie Canada Julie Ann Wrigley Global GREVE, Peter Institute of Sustainability FORD, James International Institute for USA University of Leeds Applied Systems Analysis UK/ Canada Austria/Germany EBI, Kristie L. University of Washington FORSTER, Piers GUILLEN BOLAÑOS, Tania AIII USA University of Leeds Climate Service Center (GERICS) UK Helmholtz-Zentrum Geesthacht Germany/Nicaragua EDELENBOSCH, Oreane Politecnico di Milano FRAEDRICH, Klaus Italy/Netherlands Universität Hamburg GUIOT, Joel Germany CNRS Aix-Marseille University ELGIZOULI IDRIS, Ismail FUGLESTVEDT, Jan FrancePrivate Consultancy Sudan CICERO Center for International Climate Research GUPTA, Mukesh Norway Asian University for Women of BangladeshELLIS, Neville India University of Western Australia Australia FUSS, Sabine Mercator Research Institute on Global HANASAKI, Naota Commons and Climate Change National Institute for Environmental Studies EMMERLING, Johannes Germany Japan Fondazione Eni Enrico Mattei Italy/Germany GANASE, Anjani HANDA, Collins University of Queensland Technical University of Kenya ENGELBRECHT, Francois Australia/Trinidad and Tobago Kenya Council for Scientific and Industrial Research South Africa GAO, Xuejie HAROLD, Jordan Institute of Atmospheric Physics University of East Anglia EVANS, Jason China UK University of New South Wales Australia GASSER, Thomas HASEGAWA, Tomoko International Institute for National Institute for Environmental Studies FERRAT, Marion Applied Systems Analysis Japan IPCC WGIII Technical Support Unit Austria/France Imperial College London’s Centre HAUGHEY, Eamon for Environmental Policy GATTUSO, Jean-Pierre School of Natural Sciences UK/France Institut du développement durable et Trinity College Dublin des relations internationales (IDDRI) Ireland FIFITA, Solomone CNRS Pacific Community Sorbonne Université HAYES, Katie Fiji/Tonga France University of Toronto Canada 575 Annex III Contributors to the IPCC Special Report on Global Warming of 1.5°C HAYWARD, Bronwyn JACOB, Daniela KRINNER, Gerhard University of Canterbury Climate Service Center Germany (GERICS) Institut de Géosciences de l’Environnement New Zealand Helmholtz-Zentrum Geesthacht (HZG) France Germany HE, Chenmin LAWRENCE, David Peking University JAMES, Rachel National Center for Athmospheric Research China Environmental Change Institute USA University of Oxford HERTWICH, Edgar UK LENTON, Tim Yale University University of Exeter USA/Austria JIANG, Kejun UK Energy Research Institute HIJIOKA, Yasuaki China LEY, Debora National Institute for Environmental Studies Latinoamérica Renovable Japan JOHANSEN, Tom Gabriel Guatemala/Mexico Infodesign Lab HINGE SALILI, Diana Norway LIVERMAN, Diana University of the South Pacific Laucala Campus University of Arizona Vanuatu JONES, Chris USA Met Office Hadley Centre HIRSCH, Annette UK LUDERER, Gunnar ETH Zurich Potsdam Institute for Climate Impact Research University of New South Wales JUNG, Thomas Germany Switzerland/Australia Alfred Wegener Institute Helmholtz Centre for Polar MAHOWALD, Natalie AIII HOEGH-GULDBERG, Ove and Marine Research Cornell University Global Change Institute Germany USA University of Queensland Australia KAINUMA, Mikiko MARCOTULLIO, Peter Institute for Global Environmental Strategies CUNY Institute for Sustainable Cities HÖGLUND-ISAKSSON, Lena Japan USA International Institute for Applied Systems Analysis KALA, Jatin MARENGO, Jose Antonio Austria/Sweden Murdoch University National Centre for Monitoring and Australia Warning of Natural Disasters HOURCADE, Jean-Charles Brazil/Peru Centre International de Recherches sur KANNINEN, Markku l’Environnement et le Développement (CIRED) University of Helsinki MARKANDYA, Anil CNRS Finland Basque Centre for Climate Change France Spain/UK KHESHGI, Haroon HOWDEN, Mark ExxonMobil Research and MASSERA, Omar Climate Change Institute Engineering Company Instituto de Investigaciones en Australian National University USA Ecosistemas y Sustentabilidad Australia Universidad Nacional Autonoma de México KLEIN, Richard Mexico HUMPHREYS, Stephen Stockholm Environment Institute London School of Economics Netherlands/Germany MASSON-DELMOTTE, Valérie and Political Science Co-Chair IPCC WGI UK/Ireland KOBAYASHI, Shigeki France Transport Institute of Central Japan HUPPMANN, Daniel Japan MATTHEWS, J. B. Robin International Institute for IPCC WGI Technical Support Unit Applied Systems Analysis KRAKOVSKA, Svitlana Université Paris-Saclay Austria Ukrainian Hydrometeorological Institute France/UK Ukraine MCCOLLUM, David KRIEGLER, Elmar International Institute for HUQ, Saleemul Potsdam Institute for Climate Impact Research Applied Systems Analysis International Centre for Climate Germany Austria/USA Change & Development UK/Bengladesh 576 Contributors to the IPCC Special Report on Global Warming of 1.5°C Annex III MCINNES, Kathleen MUNDACA, Luis PAZ, Shlomit Commonwealth Scientific and Lund University University of Haifa Industrial Research Organisation Sweden/Chile Israel Australia NEWMAN, Peter PEREIRA, Joy MECHLER, Reinhard Curtin University Institute for Environment and Development International Institute for Australia Malaysia Applied Systems Analysis Germany NICOLAI, Maike PEREZ, Rosa IPCC WGII Technical Support Unit Manila Observatory MEDHIN, Haileselassie Amaha Alfred-Wegener-Institut Bremen Philippines Ethiopian Development Research Institute Germany Ethiopia PETERSEN, Juliane NOTZ, Dirk Climate Service Center Germany (GERICS) MEHROTRA, Shagun Max-Planck-Institut für Meteorologie Helmholtz-Zentrum Geesthacht The World Bank Germany Germany The New School USA, India NURSE, Leonard PETZOLD, Jan The University of West Indies IPCC WGII Technical Support Unit MEINSHAUSEN, Malte Barbados Alfred-Wegener-Institut Bremen The University of Melbourne Germany Australia/Germany OKEM, Andrew IPCC WGII Technical Support Unit PICHS-MADRUGA, Ramon MEISSNER, Katrin J. School of Life Sciences Centre for World Economy Studies University of New South Wales Sydney University of KwaZulu Natal Cuba Australia South Africa/Nigeria AIII PIDCOCK, Roz MILLAR, Richard OKEREKE Chukwumerije IPCC WGI Technical Support Unit University of Oxford University of Reading Université Paris-Saclay UK UK, Nigeria France/UK MINTENBECK, Katja OLSSON, Lennart PINHO, Patricia Fernanda IPCC WGII Technical Support Unit Uppsala University University of Sao Paulo Alfred-Wegener-Institut Bremen Sweden Brazil Germany OPIO, Carolyn PIRANI, Anna MITCHELL, Dann Food and Agriculture Organization IPCC WGI Technical Support Unit University of Bristol Uganda Université Paris-Saclay UK The Abdus Salam International OPPENHEIMER, Michael Centre for Theoretical Physics MIX, Alan C Princeton University Italy/UK Oregon State University USA USA PLAZZOTTA, Maxime PAIVA HENRIQUE, Karen Météo-France University of Western Australia MORELLI, Angela Centre Naional de Recherches Brazil Infodesign Lab Météorologiques Norway FrancePARKINSON, Simon International Institute for MOUFOUMA-OKIA, Wilfran POLOCZANSKA, ElviraApplied Systems Analysis IPCC WGI Technical Support Unit IPCC WGII Technical Support Unit Canada Université Paris-Saclay Alfred-Wegener-Institut Bremen France/Congo Germany, UKPATHAK, Minal IPCC WGIII Technical Support Unit MRABET, Rachid POPP, AlexanderAhmedabad University National Institute of Agricultural Potsdam Institute for Climate Impact ResearchIndia Research (INRA) Germany Morocco PAYNE, Antony University of Bristol PÖRTNER, Hans-Otto MULUGETTA, Yacob UK Co-Chair IPCC WGII University College London Germany UK/Ethiopia 577 Annex III Contributors to the IPCC Special Report on Global Warming of 1.5°C PREUSCHMANN, Swantje ROGELJ, Joeri SENEVIRATNE, Sonia I. Climate Service Center Germany (GERICS) International Institute for Swiss Federal Institute of Technology Helmholtz-Zentrum Geesthacht Applied Systems Analysis Switzerland Germany Belgium/Austria SHERSTYUKOV, Boris PUROHIT, Pallay ROJAS, Maisa Russian Research Institute of International Institute for University of Chile Hydrometeorological Information Applied Systems Analysis Chile World Data Centre Austria/India Russian Federation ROY, Joyashree RAGA, Graciela Jadavpur University SHINDELL, Drew Universidad Nacional Autonoma de Mexico Asian Institute of Technology Duke University Mexico/Argentina Thailand/India USA RAHMAN, Mohammad Feisal SANCHEZ, Roberto SHUKLA, Priyadarshi R. International Centre for Climate El Colegio de la Frontera Norte Co-Chair IPCC WGIII Change and Development Mexico India Bengladesh SAUNDERS, Harry SILLMANN, Jana REISINGER, Andy Independent Center for International Climate Research New Zealand Agricultural Greenhouse Canada/USA Germany/Norway Gas Research Centre New Zealand SCHÄDEL, Christina SINGH, Chandni Northern Arizona University Indian Institute for Human Settlements REVI, Aromar USA/Switzerland India AIII Indian Institute for Human Settlements India SCHAEFFER, Roberto SKEA, Jim Universidade Federal do Rio de Janeiro Co-Chair IPCC WGIII REVOKATOVA, Anastasia Brazil UK Hydrometeorological Research Centre of Russian Federation SCHEUFFELE, Hanna SLADE, Raphael Russian Federation IPCC WGII Technical Support Unit IPCC WGIII Technical Support Unit Alfred-Wegener-Institut Bremen Imperial College London’s Centre RHINEY, Kevon Germany for Environmental Policy Rutgers University UK Jamaica SCHIPPER, Lisa Environmental Change Institute SMITH, Chris RIAHI, Keywan University of Oxford University of Leeds International Institute for UK/Sweden UK Applied Systems Analysis Austria SCHLEUSSNER, Carl-Friedrich SMITH, Christopher Potsdam Institute for Climate Impact Research UK RIBES, Aurélien Humboldt University Centre National de Recherches Germany SMITH, Pete Météorologiques University of Aberdeen France SCHMIDT, Jörn UK Christian-Albrechts-Universität zu Kiel RICHARDSON, Mark Germany SOLECKI, William USA/UK City University of New York SCHULTZ, Seth USA RICKELS, Wilfried C40 Cities Climate Leadership Group Kiel Institute for the World Economy USA SOME, Shreya Germany Jadavpur University SCOTT, Daniel India ROBERTS, Debra University of Waterloo Co-Chair IPCC WGII Canada SPAROVEK, Gerd South Africa Universidade de São Paulo SÉFÉRIAN, Roland Escola Superior de Agricultura Luiz de Queiroz ROBERTS, Timmons Centre National de Recherches Brazil Brown University Météorologiques USA France 578 Contributors to the IPCC Special Report on Global Warming of 1.5°C Annex III STEFFEN, Will ÜRGE-VORSATZ, Diana WEYER, Nora M The Australian National University Department of Environmental IPCC WGII Technical Support Unit Australia Sciences and Policy Alfred-Wegener-Institut Bremen Central European University Germany STEG, Linda Hungary University of Groningen WHYTE, Felicia Netherlands URQUHART, Penny The University of the West Indies Freelance climate resilient Jamaica STEPHENSON, Kimberly development specialist The University of the West Indies South Africa WOLLENBERG, Eva Jamaica University of Vermont and the CGIAR VAN DIEMEN, Renee Research Program on Climate Change STEPHENSON, Tannecia IPCC WGIII Technical Support Unit Agriculture and Food Security The University of the West Indies Imperial College London’s Centre USA Jamaica for Environmental Policy UK/Netherlands XIU, Yang SUAREZ RODRIGUEZ, Avelino G. National Center for Climate Change Research Center for the World Economy VAN ROOIJ, Arjan Strategy and International Cooperation Cuba Netherlands China SUAREZ, Pablo VAN VALKENGOED, Anne YOHE, Gary Red Cross Climate Centre University of Groningen Wesleyan University Argentina Netherlands USA SUGIYAMA, Taishi VAUTARD, Robert ZHAI, Panmao The Canon Institute for Global Studies Laboratory for Sciences of Co-Chair IPCC WGI AIII Japan Climate and Environment China France SYLLA, Mouhamadou B ZHANG, Xuebin West African Science Service Center on VILARIÑO, Maria Virginia Environment and Climate Change Canada Climate Change and Adapted Land Use Argentinean Business Council for Canada Senegal Sustainable Development Argentina ZHOU, Guangsheng TAYLOR, Michael Chinese Academy of Meteorological Sciences The University of the West Indies WAIRIU, Morgan China Jamaica University of the South Pacific Solomon Islands ZHOU, Wenji TEARIKI-RUATU, Nenenteiti International Institute for University of the South Pacific Laucala Campus WAISMAN, Henri Applied Systems Analysis Kiribati Institut du développement durable et Austria/China des relations internationales (IDDRI) TEBBOTH, Mark France ZICKFELD, Kirsten University of East Anglia Simon Fraser University UK WARREN, Rachel Canada/Germany Tyndall Centre and School of THOMAS, Adelle Environmental Sciences ZOUGMORÉ, Robert B University of The Bahamas UK Consultative Group for International Bahamas Agricultural Research WARTENBURGER, Richard International Crops Research Institute THORNE, Peter ETH Zürich for the Semi-Arid Tropics Maynooth University Switzerland/Germany Burkina Faso/Mali Ireland/UK WEHNER, Michael TRUTNEVYTE, Evelina Lawrence Berkeley National Laboratory University of Geneva USA Switzerland/Lithuania WEWERINKE-SINGH, Margaretha TSCHAKERT, Petra University of Leiden University of Western Australia Netherlands Australia/Austria 579 Annex IV: Expert Reviewers AIV of the IPCC Special Report on Global Warming of 1.5°C This annex should be cited as: IPCC, 2018: Annex IV: Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)]. In Press. 581 Annex IV Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C AAMAAS, Borgar ALBEROLA, Emilie ARIKAN, Yunus Center for International Climate Research Eco-Act ICLEI - Local Governments for Sustainability Norway France Germany ABABNEH, Linah ALCARAZ, Olga ARIMA, Jun Swedish University of Agriculture Universitat Politècnica de Catalunya University of Tokyo and Cornell University Spain Japan USA ALDRICH, Elizabeth ARTINANO, Begoña ABANADES Carlos, USA Centro de Investigaciones Energéticas Consejo Superior de Investigaciones Medioambientales y Tecnológicas Científicas ALEXEEVA, Victoria Spain Spain International Atomic Energy Agency Austria AYEB-KARLSSON, Sonja ACOSTA NAVARRO, Juan Camilo University of Sussex Barcelona Supercomputing Center ALFIERI, Lorenzo UNU-EHS Spain European Commission UK Italy ADU-BOATENG, Afua AZEITEIRO, Ulisses Training and Research Network ALI, Shaukat Departamento de Biologia & CESAM UK Global Change Impact Studies Centre University of Aveiro Ministry of climate change Portugal ADVANI, Nikhil Pakistan World Wildlife Fund BABAEIAN, Iman USA ALLEN, Myles Climatological Research Institute University of Oxford Iran AGUILAR-AMUCHASTEGUI, Naikoa Environmental Change Institute World Wildlife Fund UK BABIKER, Mustafa USA Saudi Aramco ALLWRIGHT, Gavin Sudan AHMAD, Ijaz International Windship Association Applied Systems Analysis Division UK BAHAMONDES DOMINGUEZ, Pakistan Atomic Energy Commission Angela Andrea Pakistan ALPERT, Alice University of Southampton AIV United States Department of State UK/Chile AHMADI, Mohammad USA Regional Meteorological MetOffice BAKHTIARI, Fatemeh Iran AN, Nazan Researcher at UNEP DTU partnership Bogazici University Center for Climate Denmark AHN, Young-Hwan Change and Policy Studies Korea Energy Economics Institute Turkey BALA, Govindasamy Republic of Korea Indian Institute of Science ANDERSON, Cheryl India AKHTAR, Farhan LeA International Consultants Ltd U.S. Department of State New Zealand BARAU, Aliyu Office of Global Change Faculty of Earth and Environmental Sciences USA ANDERSSON, Peter Bayero University Kano Uppsala University Nigeria AKIMOTO, Keigo Sweden Research Institute of Innovative BARBOSA ARAUJO SOARES Technology for the Earth ANDREWS, Nadine SNIEHOTTA, Vera Japan IPCC WGII Technical Support Unit Newcastle University Alfred-Wegener-Institut Bremen UK AKPAN, Archibong Germany/UK University of Ibadan BARDHAN, Suchandra Nigeria ANORUO, Chukwuma Jadavpur University Imo State University Owerri India ALAM, Lubna Nigeria Institute for Environment and BARKER, Timothy Development (LESTARI) AQUINO, Sergio DIYNGO.org Bangladesh University of British Columbia UK Canada 582 Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C Annex IV BARRETT, Ko BLUM, Mareike BREYER, Christian National Oceanographic and University of Freiburg Lappeenranta University of Technology Atmospheric Administration Germany Finland USA BOBIN, Jean Louis BRICEÑO-ELIZONDO, Elemer BASTOS, Ana Université Pierre et Marie Curie Instituto Tecnológico de Costa Rica Laboratoire des sciences du climat France Costa Rica et de l’environnement France BODMAN, Roger BROWN, Louis The University of Melbourne Manchester Business School BATAILLE, Christopher Australia UK Institute for Sustainable Development and International Relations BONDUELLE, Antoine BROWN, Sally Simon Fraser University E&E Consultant University of Southampton Canada France UK BAUER, Nico BOONEEADY, Prithiviraj BRUCKNER, Thomas Potsdam Institut for Climate Impact Research Mauritius Meteorological Services University of Leipzig Germany Mauritius Germany BAYAS, Dilipsing BOOTH, Mary BRUNNER, Beat International Consultant (Roster) Partnership for Policy Integrity Lightning MultiCom SA UN Global Pulse Lab USA Switzerland India BORGES LANDAEZ, Pedro Alfredo BUDINIS, Sara BELLAMY, Rob Venezuelan Institute for Scientific Research Imperial College London University of Oxford UNFCCC Technology Executive Committee Sustainable Gas Institute UK Venezuela UK BENNACEUR, Kamel BORGFORD-PARNELL, Nathan BULLOCK, Simon Abu Dhabi National Oil Company Climate and Clean Air Coalition Friends of the Earth, England, United Arab Emirates Switzerland Wales and Northern Ireland UK BENNETT, Simon BOSETTI, Valentina AIV International Energy Agency Bocconi University BUZÁSI, Attila France Fondazione Eni Enrico Mattei Budapest University of Italy Technology and Economics BENTO, Nuno Hungary ISCTE-Instituto Universitário de Lisboa BOUCHER, Olivier Portugal Institut Pierre Simon Laplace BYERS, Edward France International Institute for BENVENISTE, Hélène Applied Systems Analysis Woodrow Wilson School of Public BOYER-VILLEMAIRE, Ursule Austria and International Affairs Université du Québec à Montréal Princeton University Canada BUTT, Nathalie USA The University of Queensland BRANDÃO, Miguel Australia BERDALET, Elisa Royal Institute of Technology (KTH) Consejo Superior de Investigaciones Científicas Sweden CAESAR, John Spain Met Office Hadley Centre BRANDER, Keith UK BERTOLDI, Paolo DTU Aqua European Commission Denmark CAI, Rongshuo Italy Third Institute of Oceanography BREGMAN, Bram State Oceanic Administration of China BISHOP, Justin Radboud University China University of Cambridge The Netherlands UK CALLEN, Jessica BREON, Francois-Marie International Institute for BLOK, Kornelis Laboratoire des sciences du climat Applied Systems Analysis Delft University of Technology et de l’environnement Austria The Netherlands France 583 Annex IV Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C CAMES, Martin CASTANEDA, Fátima CHOI, Woonsup Öko-Institut Konrad Adenauer S. University of Wisconsin-Milwaukee Germany Guatemala USA CAMPBELL, Donovan CAZZOLA, Pierpaolo CHOW, Winston Jamaica International Energy Agency National University of Singapore France Singapore CAMPBELL, Kristin Institute for Governance and CEARRETA, Alejandro CHRISTOPHER, Barrington-Leigh Sustainable Development Universidad del Pais Vasco/EHU McGill University USA Spain Canada CAMPBELL-DURUFLÉ, Christopher CENTELLA, Abel CHUST, Guillem Center for International Sustainable Instituto de Meteorologia AZTI Marine Research Division Development Law Cuba Spain Canada CERDÁ, Emilio CIOT, Marco CANEILL, Jean-Yves University Complutense of Madrid Italian Peace Civil Corps FOCSIV IETA non-profit business organisation Spain Italy France CHACÓN, Noemi CLARK, Christopher CANEY, Simon Instituto Venezolano de US Government University of Warwick Investigaciones Científicas USA UK Venezuela CLARKE, David CAPSTICK, Stuart CHADBURN, Sarah Canada Cardiff University University of Leeds UK UK CLARKE, Jamie Climate Outreach CARAZO ORTIZ, Maria Pia CHAN, Yi-Chieh UK University for Peace Delta Electronics Foundation Germany China CLAYTON, Susan The College of Wooster CARNICER, Jofre CHARPENTIER LJUNGQVIST, Fredrik USA AIV University of Barcelona Stockholm University Spain Sweden CLEMMER, Steve Union of Concerned Scientists CARPENTER, Mike CHEN, Wenting USA Gassnova Norwegian Institute for Water Research Norway Norway COLLINS, Mat University of Exeter CARRASCO, Jorge CHEN, Wenying UK Universidad de Magallanes Tsinghua University Chile China COLLINS, William University of Reading CARTER, Peter CHEN, Ying UK Climate Emergency Institute Chinese Academy of Social Sciences Canada China CONNORS, Sarah IPCC WGI Technical Support Unit CARTER, Timothy CHERKAOUI, Ayman Bel Hassan Université Paris-Saclay Finnish Environment Institute (SYKE) Center for International Sustainable France/UK Finland Development Law Morocco CONVERSI, Alessandra CARTWRIGHT, Anton Consiglio Nazionale delle Ricerche African Centre for Cities CHERNOKULSKY, Alexander Italy University of Cape Town A.M. Obukhov Institute of Atmospheric Physics South Africa Russian Academy of Sciences COOK, Lindsey Russian Federation Friends World Committee for Consultation CASSOTTA, Sandra Germany Denmark CHINWEZE, Chizoba Chemtek Associates Limited Nigeria 584 Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C Annex IV COOPER, David DAIOGLOU, Vassilis DENG, Xiangzheng Convention on Biological Diversity PBL Netherlands Environmental Institute of Geographic Sciences Canada Assessment Agency and Natural Resources Research Netherlands Chinese Academy of Sciences CORFEE-MORLOT, Jan China New Climate Economy DALIAKOPOULOS, Ioannis France Technical University of Crete DENIS-RYAN, Amandine Greece Monash University CORNELIUS, Stephen Australia World Wildlife Fund DAMASSA, Thomas UK Oxfam America DESCONSI, Cristiano USA Federal University of Goiás COROBOV, Roman Brazil Eco-Tiras International Association DAÑO, Elenita of River Keepers Action Group on Erosion DI BELLA, Jose Republic of Moldova Technology and Concentration ParlAmericas Philippines Canada COULTER, Liese Griffith University DAVIES, Elizabeth Penelope DIAZ, Julio Australia Ford Foundation National School of Public Health USA Carlos III Institute of Health COURAULT, Romain Spain Sorbonne-Universités Paris IV DE BEAUVILLE-SCOTT, Susanna France Sustainable Development Department DIOP, Cherif Government of Saint Lucia Agence nationale de l’aviation CREMADES, Roger Saint Lucia civile et de la météorologie Climate Service Center Germany (GERICS) Senegal DE CONINCK, Heleen Germany Radboud University DIOSEY RAMON, Lugo-Morin Netherlands CREUTZIG, Felix Universidad Intercultural del Estado de Puebla Mercator Research Institute on Global MexicoDE FRENNE, Pieter Commons and Climate Change Ghent University Technical University Berlin Belgium DIXON, Tim Germany IEA Greenhouse Gas DE OLIVEIRA, Gabriel UK AIV CURRIE-ALDER, Bruce University of Kansas International Development Research Centre Brazil DOCQUIER, David Canada Université catholique de Louvain DEISSENBERG, Christophe Belgium CUSACK, Geraldine Ann Aix-Marseille University Siemens Ltd Groupement de recherche en DOELLE, Meinhard Ireland économie quantitative Dalhousie University Luxembourg Canada CUTTING, Hunter Cimate Nexus/Climate Signals DELUSCA, Kenel DONEV, Jason USA Institut des sciences, des technologies University of Calgary et des études avancées d’Haïti Canada CZERNICHOWSKI-LAURIOL, Isabelle University of Montreal Bureau de recherches géologiques et minières Haiti DONNELLY, Chantal France Bureau of Meteorology DEMKINE, Volodymyr Australia DAALDER, Henk Kenya Pak de Wind DOOLEY, Kate Netherlands DEN ELZEN, Michel University of Melbourne PBL Netherlands Environmental Australia DAGNET, Yamide Assessment Agency World Resources Institute Netherlands DOYLE, Paul USA BC Rivers Consulting Ltd Canada DAI, Zhen Harvard University USA/China 585 Annex IV Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C DRIOUECH, Fatima ELBEHIRY, Fathy FINNVEDEN, Göran Direction de la météorologie nationale Central laboratory for Environmental Studies Royal Institute of Technology (KTH) Morocco Kafrelsheikh University Fortum Värme Egypt Sweden DROEGE, Susanne German Institute for International ELBEHRI, Aziz FISCHLIN, Andreas and Security Affairs (SWP) Italy ETH Zurich Germany Switzerland ELSHAROUNY, Mohamed DUBE, Lokesh Chandra Cairo University FLATO, Greg Ministry of Environment, Forest Egypt Canadian Centre for Climate and Climate Change Modelling and Analysis India EMORI, Seita Environment Canada National Institute for Environmental Studies Canada DUNPHY, Brendon Japan The University of Auckland FLEMING, John New Zealand ENOMOTO, Hiroyuki Center for Biological Diversity Japan USA DURAND, Frédéric Toulouse II University ERB, Karlheinz FLEMING, Sean France Austria University of British Columbia USA DYKEMA, John ERIKSSON, Flintull Annica Paulson School Statistics Denmark FODA, Rabiz Harvard University Sweden Hydro One Networks Inc. USA Canada ERLANIA, Erlania EASTHAM, Sebastian Center for Fisheries Research FOLTESCU, Valentin Massachusetts Institute of Technology Indonesia United Nations Environment USA/UK France ESPARTA, Adelino Ricardo Jacintho EGBENDEWE, Aklesso Universidade de São Paulo FORD, James University of Lome Brazil Department of Geography Togo McGill University AIV FÆHN, Taran Canada EHARA, Makoto Statistics Norway Research Department Forestry and Forest Products Research Institute Norway FORSTER, Piers Japan University of Leeds FANG, Kai UK EHSANI, Nima Zhejiang University Saint Louis University China FREI, Thomas USA Research and Consulting FARAGO, Tibor Switzerland EISEN, Olaf Eötvös L. University (ELTE) Alfred-Wegener-Institut Hungary FUGLESTVEDT, Jan Helmholtz-Zentrum für Polar- Center for International Climate Research und Meeresforschung FARIA, Sergio Henrique Norway Germany Basque Centre for Climate Change (BC3) Spain FUHR, Lili EKHOLM, Tommi Heinrich Böll Foundation Aalto University FAST, Stewart Germany Finland Institute for Science, Society and Policy University of Ottawa FUJIMORI, Shinichiro EL ZEREY, Wael Canada National Institute for Environmental Studies Djillali Liabes University Japan Algeria FAUSET, Sophie University of Leeds FUSS, Sabine ELBASIOUNY, Heba UK Mercator Research Institute on Global Al-Azhar University Commons and Climate Change Egypt FICHERA, Alberto Germany University of Catania Italy 586 Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C Annex IV GADIAN, Alan GLENN, Aaron GUPTA, Himangana National Centre for Atmospheric Sciences Agriculture and Agri-Food Canada NATCOM Cell University of Leeds Canada Ministry of Environment, Forest UK and Climate Change GOLSTON, Levi India GAILL, Françoise Princeton University Plateforme océan climat USA HABERL, Helmut France Institute of Social Ecology GÓMEZ CANTERO, Jonathan University of Natural Resources GAJJAR, Sumetee Pahwa Universidad de Alicante and Life Sciences (BOKU) Indian Institute for Human Settlements Castilla-La Mancha Media Austria India Spain HAFEZ, Marwa GALOS, Borbala GONZALEZ, Miguel Institute for Graduate Studies & Research University of Sopron Global Education and Alexandria Governor office Hungary Infrastructure Services Ltd Egypt Nigeria GALYNA, Trypolska HAGEN, Achim Institute for Economics and Forecasting, UNAS GONZALEZ, Patrick Resource Economics Group Ukraine University of California Humboldt-Universität USA Germany GAN, Thian University of Alberta GONZÁLEZ-EGUINO, Mikel HAITES, Erik Canada Basque Centre for Climate Change Margaree Consultants Inc. Spain Canada GARCI SOTO, Carlos Spanish Institute of Ocenography GOODWIN, Philip HALLAM, Samantha Spain University of Southampton University of Southampton UK UK GECK, Angela Institute of Political Science GORNER, Marine HALSNAES, Kirsten University of Freiburg Organisation for Economic Co-operation and The Danish Technical University Germany Development, International Energy Agency Denmark France GEDEN, Oliver HAMDI, Rafiq AIV German Institute for International and Security GRANT, Jonathan Royal Meteorological Institute of Belgium Affairs (Stiftung Wissenschaft und Politik) PwC Belgium Germany UK HANN, Veryan GEORGIADIS, Teodoro GRASSI, Giacomo University of Tasmania Italian national Research Council Italy Australia Instituto of Biometeorology (CNR-IBIMET) Italy GRAU, Marion HARA, Masayuki MF Norwegian School of Theology Center for Environmental Science in Saitama GIARDINO, Alessio Norway Japan Deltares Netherlands GRILLAKIS, Manolis HARE, Bill Technical University of Crete Climate Analytics GIAROLA, Sara Greece Germany Imperial College London UK GROVER, Samantha HARMELING, Sven La Trobe University CARE International GILLE, Sarah Australia Germany Scripps Institution of Oceanography University of California San Diego GUIVARCH, Céline HAROLD, Jordan USA Centre international de recherche sur University of East Anglia l’environnement et le développement, UK GILLETT, Nathan Ecole des Ponts ParisTech Environment and Climate Change Canada France HARPER, Anna Canada University of Exeter UK 587 Annex IV Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C HARRISON, Jonathan HIRVONEN, Janne HUEBENER, Heike University of Southampton Aalto University Hessian Agency for Nature Conservation, UK Finland Environment and Geology Germany HASEGAWA, Tomoko HITE, Kristen National Institute for Environmental Studies American University HURTADO ALBIR, Francisco Javier Japan School of International Service European Patent Office USA Germany HASHIMOTO, Shoji Forestry and Forest Products Research Institute HOF, Andries HUSSEIN, Amal Japan PBL Netherlands Environmental National Research Centre Assessment Agency Egypt HAYMAN, Garry Netherlands NERC IGLESIAS BRIONES, Maria Jesus Centre for Ecology & Hydrology HOLZ, Christian Universidad de Vigo UK Climate Equity Reference Project Spain Canada HAYWOOD, Jim IIZUMI, Toshichika University of Exeter HONDA, Yasushi Institute for Agro-Environmental Sciences UK Faculty of Health and Sport Sciences National Agriculture and Food University of Tsukuba Research Organization HEAD, Erica Japan Japan Fisheries and Oceans Canada Canada HONEGGER, Matthias INFIELD, David Research Scientist at Institute for Advanced University of Strathclyde HEBBINGHAUS, Heike Sustainability Studies Potsdam UK Landesamt für Natur, Umwelt und Germany Verbraucherschutz Nordrhein- INSAROV, Gregory Westfalen (LANUV) HONG, Jinkyu Institute of Geography Germany Department of Atmospheric Sciences Russian Academy of Sciences Yonsei University Russian Federation HENSON, Stephanie Republic of Korea National Oceanography Centre INYANG, Hilary UK HONGO, Takashi Global Education and AIV Mitsui Global Strategic Studies Institute Infrastructure Services LLC HERBERT, Annika Japan Nigeria University of Sydney Australia HOREN GREENFORD, Daniel IQBAL, Muhammad Mohsin Concordia University Global Change Impact Studies Centre HERRALA, Risto Canada Pakistan International Monetary Fund USA HORTON, Joshua IRVINE, Peter Harvard University School of Engineering and Applied Sciences HERTWICH, Edgar Havard Kennedy School Harvard University Yale University USA USA USA HOSSEN, Mohammad Anwar ISHIMOTO, Yuki HEYD, Thomas University of Dhaka The Institute of Applied Energy University of Victoria Bangladesh Norway Canada HOWDEN, Mark ISLAM, Akm Saiful HIDALGO, Julia Australian National University Bangladesh University of National Center of Scientific Research Australia Engineering and Technology France Bangladesh HUANG, Yuanyuan HILDÉN, Mikael Laboratoire des sciences du climat ISLAM, Md. Sirajul Finnish Environment Institute et de l’environnement North South University Bangladesh Finland France ITO, Akihiko HILMI, Nathalie National Institute for Environmental Studies France Japan 588 Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C Annex IV IZZET, Ari JOUZEL, Jean KAY, Robert Head of Department of Sustainable Centre d’énergie atomique de Saclay ICF Development and Environment France USA Turkey KABIDI, Khadija KEENAN, Jesse JACOBSON, Mark Direction de la météorologie nationale Harvard University Stanford University Morocco USA USA KACHI, Aki KEITH, David JAEGER-WALDAU, Arnulf Carbon Market Watch Harvard University European Commission Germany USA/Canada/UK Italy KADITI, Eleni KEMPER, Jasmin JAKOB, Grandin Organization of the Petroleum IEA Greenhouse Gas R&D Programme University of Bergen Exporting Countries UK Norway Austria KERKHOVEN, John JAMES, Rachel KAINUMA, Mikiko Partner Quintel Intelligence University of Oxford Institute for Global Environmental Strategies Netherlands UK Japan KERSTING, Diego Kurt JEREZ, Sonia KALLBEKKEN, Steffen Freie Universität Berlin University of Murcia Center for International Climate Research Germany Spain Norway KHAZAEI, Mahnaz JERSTAD, Heid KALLIOKOSKI, Tuomo Iran Meteorological Organization University of Edinburgh University of Helsinki Iran UK Finland KHAZANEDARI, Leili JIA, Gensuo KALUGIN, Andrey Climate Research Institute China Water Problems Institute of Iran Russian Academy of Sciences JIM ILHAM, Jasmin Irisha Russian Federation KHENNAS, Smail Jeffrey Sachs Center on Independent energy and climate change expert Sustainable Development KANAKO, Morita UK AIV Malaysia Forestry and Forest Products Research Institute Japan KHESHGI, Haroon JINNAH, Sikina ExxonMobil Research and UC Santa Cruz KARIMIAN, Maryam Engineering Company USA Climatology Research Institute USA National Center of Climatology JOHANSEN, Tom Gabriel Iran KIENDLER-SCHARR, Astrid InfoDesignLab IEK-8: Troposphere, Forschungszentrum Norway KARMALKAR, Ambarish Jülich GmbH University of Massachusetts Amherst Germany JOHNSTON, Eleanor USA Climate Interactive KILKIS, Siir USA KARTADIKARIA, Aditya The Scientific and Technological Research Bandung Institute of Technology Council of Turkey (TUBITAK) JONES, Ian Indonesia International Centre for Sustainable University of Sydney Development of Energy, Water and Australia KATBEHBADER, Nedal Environment Systems (SDEWES Centre) Environment Quality Authority Turkey JONES, Lindsey State of Palestine Switzerland KIM, Hyung JuLondon School of Economics Green Technology Center Korea Overseas Development Institute KAWAMIYA, Michio Republic of KoreaUK Japan Agency for Marine-Earth KINN, Moshe JOSEY, Simon Science and Technology The University of Salford National Oceanography Centre Japan UK UK 589 Annex IV Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C KJELLSTRÖM, Erik KUHNHENN, Kai LEE, Arthur Swedish Meteorological and Konzeptwerk Neue Ökonomie Chevron Energy Technology Company Hydrological Institute Germany USA Sweden KUSCH, Sigrid LEE, Sai Ming KNOPF, Brigitte University of Padua Hong Kong Observatory Mercator Research Institute on Global Germany China Commons and Climate Change Germany KUYLENSTIERNA, Johan Carl Ivar LEFALE, Penehuro Fatu Stockholm Environment Institute LeA International KOBAYAHI, Shigeki UK Joint Centre for Disaster Research Transport Institute of Central Japan Massey University Japan LABRIET, Maryse New Zealand Eneris Environment Energy Consultants KOCHTITZKY, William Spain LEFFERTSTRA, Harold University of Maine Climate Consultant USA LAHA, Priyanka Norway Indian Institute of the Technology Kharagur KOLL, Roxy Mathew India LEHOCZKY, Annamaria India Centre for Climate Change LAHIRI, Souparna Universitat Rovira i Virgili KONDO, Hiroaki Global Forest Coalition Spain National Institute of Advanced India Industrial Science and Technology LESLIE, Michelle Japan LAHN, Bård Canadian Nuclear Association Center for International Climate Research Canada KOPPU, Robert Norway Rutgers University LEVIHN, Fabian USA Royal Institute of Technology (KTH)LATIF, Muhammad Fortum Värme Applied Systems Analysis Division KOUTROULIS, Aristeidis Pakistan Atomic Energy Commission Sweden Technical University of Crete Pakistan School of Environmental Engineering LEVINA, Ellina Greece LAW, Matt International Energy Agency AIV Bath Spa University France KRAVITZ, Ben UK Pacific Northwest National Laboratory LEY, Debora USA LAWRENCE, Mark Latinoamérica Renovable Institute for Advanced Sustainability Studies Guatemala/Mexico KREUTER, Judith Germany Technische Universität LICKER, Rachel Germany LE BRIS, Nadine Union of Concerned Scientists Sorbonne University USA KREY, Volker France International Institute for LIJUAN, Ma Applied Systems Analysis LE QUÉRÉ, Corinne National Climate Center Austria Tyndall Centre China University of East Anglia KRIEGLER, Elmar UK LINARES, Cristina Potsdam Institute for Climate Impact Research Carlos III Institute of Health Germany LEAHY, Paul National School of Public Health University College Cork Spain KRINNER, Gerhard Ireland Centre national de la recherche scientifique LITTLE, Conor France LEAL, Walter University of Limerick Hamburg University of Applied Sciences Ireland KRISHNASWAMY, Jagdish Germany India LLASAT, Maria-Carmen LECOCQ, Noé University of Barcelona KÜHNE, Kjell Inter-Environnement Wallonie Spain Leave it in the Ground Initiative Belgium Mexico 590 Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C Annex IV LLOYD, Philip LUPO, Anthony MARX, Andreas Cape Peninsula University of Technology University of Missouri Helmholtz Centre for Environmental Beijing Agricultural University USA Research GmbH (UFZ) South Africa Germany LYNN, Jonathan LOBELLE, Delphine IPCC Secretariat MASOOD, Amjad University of Southampton World Meteorological Organization Global Change Impact Studies Centre UK Switzerland Pakistan LOCKIE, Stewart LYONS, Lorcan MASSON-DELMOTTE, Valérie James Cook University France IPCC Co-Chair WGI Australia France MAAS, Wilfried LOCKLEY, Andrew Royal Dutch Shell MATA, Érika UK Netherlands IVL Swedish Environmental Research Institute Sweden LOMBROSO, Luca MACCRACKEN, Michael University of Modena and Reggio Emilia Climate Institute MATSUMOTO, Katsumi Italy USA University of Minnesota USA LONGDEN, Thomas MACDOUGALL, Andrew Centre for Health Economics St. Francis Xavier University MATSUMOTO, Ken’ichi Research and Evaluation Canada Nagasaki University University of Technology Sydney Japan Australia MACMARTIN, Douglas Cornell University MATTHEWS, J. B. Robin LOPEZ-BUSTINS, Joan A. USA IPCC WGI Technical Support Unit University of Barcelona Université Paris-Saclay Spain MAHAL, Snaliah France/UK Department of Sustainable Development LOUGHMAN, Joshua Saint Lucia MAY, Wilhelm Arizona State University Lund University USA MAHOWALD, Natalie Denmark Cornell University LOUREIRO, Carlos USA MAZAUD, Alain AIV Ulster University Laboratoire des sciences du climat University of KwaZulu-Natal MANTYKA-PRINGLE, Chrystal et de l’environnement UK/South Africa School of Environment and Sustainability France University of Saskatchewan LOVERA-BILDERBEEK, Simone Canada MAZZOTTI, Marco Global Forest Coalition ETH Zurich University of Amsterdam MARBAIX, Philippe Switzerland Paraguay Université catholique de Louvain Belgium MBEVA, Kennedy LOVINS, Amory African Centre for Technology Studies Rocky Mountain Institute MARCOTULLIO, Peter Australia USA Hunter College City University of New York MCCAFFREY, Mark LUCERO, Lisa USA National University for Public Service University of Illinois at Urbana-Champaign Hungary USA MARTIN, Eric Irstea MCKINNON, Catriona LUDERER, Gunnar France University of Reading Potsdam Institute for Climate Impact Research UK Germany MARTINI, Catherine Yale Program on Climate MECHLER, Reinhard LUENING, Sebastian Change Communication International Institute for Institute for Hydrography, Geoecology USA Applied Systems Analysis and Climate Sciences Austria/Germany Portugal MARTYR-KOLLER, Rosanne University of California Berkeley Germany 591 Annex IV Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C MEFTAH, Mustapha MOHAMED ABULEIF, Khalid MORTON, John Centre national de la recherche scientifique Sustainability Advisor to the Minister Ministry Natural Resources Institute France of Petroleum and Mineral Resources University of Greenwich Saudi Arabia UK MELAMED, Megan International Global Atmospheric Chemistry MOLERO, Francisco MORTON, Oliver University of Colorado Centro de Investigaciones Energéticas, University College London Cooperative Institute for Research Medioambientales y Tecnológicas UK in Environmental Sciences Spain USA MOUFOUMA OKIA, Wilfran MÖLLER, Ina IPCC WGI Technical Support Unit MELIA, Nathanael Lund University Université Paris-Saclay Scion Sweden France/Congo New Zealand MÖLLERSTEN, Kenneth MOUSSADEK, Rachid METZ, Bert Swedish Energy Agency National Agricultural Research Institute European Climate Foundation Sweden Morocco Netherlands MONFORTI-FERRARIO, Fabio MOVAGHARI, Alireza MEYA, Jasper Joint Research Centre Urmia University Humboldt-Universtiät European Commission Iran Germany Italy MUÑOZ SOBRINO, Castor MICHAELIS, Laurence MONTT, Guillermo Universidade de Vigo Living Witness (Quakers) International Labour Organization Spain UK Switzerland MURI, Helene MICHAELOWA, Axel MOORE, Robert Daniel University of Oslo University of Zurich University of British Columbia Norway Switzerland Canada MUSOLIN, Dmitry L. MIDGLEY, Pauline MORALES, Manuel Saint Petersburg State Forest Independent Consultant Université Clermont Auvergne Technical University Germany France Russian Federation AIV MIN, Seung-Ki MORECROFT, Mike MYCOO, Michelle Pohang University of Science and Technology Natural England The University of the West Indies Republic of Korea UK Trinidad and Tobago MINDENBECK, Katja MORELLI, Angela NALAU, Johanna IPCC WGII Technical Support Unit InfoDesignLab Griffith University Alfred-Wegener-Institut Bremen Norway Australia Germany MORENO, Meimalin NANGOMBE, Shingirai Shepard MITCHELL, Dann Venezuelan Institute for Scientific Research University of Chinese Academy of Science University of Bristol Venezuela Zimbabwe UK MORGAN, Jennifer NATALINI, Davide MIZUNO, Yuji Greenpeace Global Sustainability Institute Institute for Global Environmental Strategies The Netherlands Anglia Ruskin University Japan UK MORIN, Samuel MKWAMBISI, David France NAUELS, Alexander Lilongwe University of Agriculture University of Melbourne and Natural Resources MORROW, David Australia Malawi American University George Mason University NDIONE, Jacques-André MODIRIAN, Rahele USA Centre de Suivi Ecologique Climatological Research Institute Senegal Iran NEDJRAOUI, Dalila Algeria 592 Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C Annex IV NERILIE, Abram OLA, Kalen PAREDES, Franklin Australian National University Swedish Meteorological and Institute of Atmospheric Sciences (ICAT) Australia Hydrological Institute Federal University of Alagoas Sweden Brazil NEU, Urs ProClim OLHOFF, Anne PARK, Go Eun Swiss Academy of Sciences UNEP DTU Partnership National Institute of Forest Science Switzerland Denmark Republic of Korea NICHOLLS, Neville OLSEN, Karen PARKER, Andrew Monash University UNEP DTU Partnership University of Bristol Australia Denmark UK NICOLAU, Mariana O’MAHONY, Tadhg PASTOR, Amandine Collaborating Centre on Sustainable Finland Futures Research Centre Institut de recherche pour le développement Consumption and Production Finland France Germany ONGOMA, Victor PATERSON, Matthew NIEVES, Barros South Eastern Kenya University University of Manchester University of Santiago de Compostela Kenya UK Spain ONUOHA, Mgbeodichinma Eucharia PATT, Anthony NIFENECKER, Herve TU Bergakademie Freiberg Saxony ETH Zurich Global Initiative to Save Our Climate (GISOC) Germany Switzerland France OOGJES, Justin PATWARDHAN, Anand NISHIOKA, Shuzo University of Melbourne University of Maryland Institute for Global Environmental Strategies USAAustralia Japan PAUL ANTONY, Anish NOGUEIRA DA SILVA, Milton OPPENHEIMER, Michael Massachusetts Institute of Technology Climate Change & Technology Consultant Princeton University USA Brazil USA PAUW, Willem Pieter NOH, Dong-Woon OSCHLIES, Andreas German Development Institute Korea Energy Economics Institute GEOMAR Germany AIV Germany Republic of Korea OTTO, Friederike PEARSON, Pamela NORMAN, Barbara University of Oxford International Cryosphere Climate Initiative University of Canberra UK USA Australia OURBAK, Timothée PEBAYLE, Antoine NUGRAHA, Adi Agence française de développement Plateforme océan et climat Pacific Northwest National Laboratory France France USA PAGNIEZ, Capucine PEDACE, Alberto NUNES, Ana Raquel Plateforme océan et climat Climate Action Network LatinoAmerica University of Warwick France Argentina UK PAJARES, Erick PERDINAN NUNEZ-RIBONI, Ismael The Biosphere Group Bogor Agricultural University Thünen Institute of Sea Fisheries Peru Indonesia Germany PALTER, Jaime PERLMAN, Kelsey OGDEN, Nicholas University of Rhode Island Carbon Market Watch Public Health Agency of Canada Graduate School of Oceanography France Canada USA PERRIER, Quentin OKPALA, Denise PÁNTANO, Vanesa Centre international de recherche sur The Institution of Environmental Sciences Department of Atmosphere l’environnement et le développement Nigeria and Ocean Sciences France University of Buenos Aires Argentina 593 Annex IV Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C PETERS, Glen POLOCZANSKA, Elvira RAHIMI, Mohammad Center for International Climate Research IPCC WGII Technical Support Unit Faculty of Desert Studies Norway Alfred-Wegener-Institut Bremen Semnan University Germany Iran PETRASEK MACDONALD, Joanna Inuit Circumpolar Council POMPEU PAVANELLI, João Arthur RASUL, Golam Canada Instituto Nacional de Pesquisas Espaciais International Centre for Integrated Brazil Mountain Development PETZOLD, Jan Nepal IPCC WGII Technical Support Unit POOT-DELGADO, Carlos Alfred-Wegener-Institut Bremen Instituto Tecnologico Superior de Champotón RAU, Greg Germany Mexico University of California, Santa Cruz USA PHILIBERT, Cedric POPKOSTOVA, Yana International Energy Agency European Centre for Energy RAWE, Tonya France and Geopolitical Analysis CARE France USA PIACENTINI, Rubén Institute of Physics Rosario PÖRTNER, Hans-Otto RAYMOND, Colin Consejo Nacional de Investigaciones IPCC Co-Chair WGII Columbia University Científicas y Técnicas Germany USA National University of Rosario Argentina PRAG, Andrew REAY, David International Energy Agency University of Edinburgh PIANA, Valentino France UK Economics Web Institute Italy PRAJAL, Pradhan REES, Morien The International Council of Museums Potsdam Institute for Climate Impact Research Norway PIGUET, Etienne Germany University of Neuchâtel REINECKE, Sabine Switzerland PRICE, Lynn University of Freiburg Lawrence Berkeley National Laboratory Forest and Environmental Policy PIRLO, Giacomo USA Germany Consiglio per la ricerca in agricotura AIV e l’analisi dell’economia agraria PUIG, Daniel REISINGER, Andy Italy Technical University of Denmark New Zealand Agricultural Denmark GHG Research Centre PISANI, Bruno New Zealand Civil Engineering School PUIG ARNAVAT, Maria University of A Coruña Technical University of Denmark RETUERTO, Rubén Spain Denmark Universidade de Santiago de Compostela Spain PISKOZUB, Jacek PULIDO-VELAZQUEZ, David Institute of Oceanology Polish Instituto Geológico y Minero REYER, Christopher Academy of Sciences Spanish Geological Survey Potsdam Institute for Climate Impact Reserach Poland Spain Germany PITARI, Giovanni PUPPIM DE OLIVEIRA, Jose Antonio REYNOLDS, Jesse Department of Physical and Chemical Sciences Fondation Getúlio Vargas Utrecht University Università L’Aquila Brazil The Netherlands Italy QIAN, Budong RINKEVITCH, Baruch PLANTON, Serge Agriculture and Agri-Food Canada Israel Météo-France Canada France RIXEN, Tim RABITZ, Florian Leibniz Zentrum für Marine Tropenforschung POITOU, Jean Kaunas University of Technology Germany Sauvons Le Climat Lithuania France ROBERTS, Debra RADUNSKY, Klaus IPCC Co-Chair WGII Umweltbundesamt South Africa Austria 594 Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C Annex IV ROBERTS, Erin ROY, Shouraseni SANDER, Sylvia King’s College London University of Miami Section of Marine Environmental UK USA Studies Laboratory Monaco ROBIOU DU PONT, Yann ROYER, Marie-Jeanne S. University of Melbourne Universite de Montreal SANTOSH KUMAR, Mishra France Canada S. N. D. T. Women’s University India ROBLEDO ABAD, Carmenza RUTH, Urs USYS-TdLab Robert Bosch GmbH SANZ SANCHEZ, Maria Jose ETH Zurich Germany Basque Centre for Climate Change Switzerland Spain SAGNI, Regasa ROBOCK, Alan Malole consults SARGENT, Philip Rutgers University Ethiopia Cambridge Energy Forum USA UK SAHEB, Yamina ROCKMAN, Marcy OpenExp SAUNDERS, Harry National Park Service Ecole des Mines of Paris Decision Processes Inc USA France USA RODRÍGUEZ AÑÓN, José Antonio SALA, Hernan Edgardo SAVARESE, Stephan University of Santiago de Compostela Argentine Antarctic Institute ForCES SAS Spain National Antarctic Directorate France Argentina ROEHM, Charlotte SAVÉ, Robert Terralimno LLC SALANAVE, Jean-Luc Institut de Recerca i Tecnologia USA Ecole CENTRALE SUPELEC Agroalimentaries Spain ROGELJ, Joeri France International Institute for Applied Systems Analysis SALAT, Jordi SAVOLAINEN, Ilkka Austria/Belgium Instituto de Ciencias del mar Technical Research Centre of Finland Consell Superior d’Investigacions Científiques Finland ROMERI, Mario Valentino Spain Italy SAYGIN, Deger AIV SALAWITCH, Ross Turkey ROSE, Steven University of Maryland Electric Power Research Institute USA SCHAEFFER, Michiel USA Climate Analytics SALTER, Stephen University of Wageningen ROSEN, Richard University of Edinburgh The Netherlands Germany UK SCHEWE, Jacob ROSENZWEIG, Cynthia SALVADOR, Pedro Potsdam Institute for Climate Impact Research National Aeronautics and Centro de Investigaciones Energéticas, Germany Space Administration Medioambientales y Tecnológicas Goddard Institute for Space Studies Spain SCHIPPER, Lisa USA Stockholm Environment Institute SAMSET, Bjørn Overseas Development Institute ROTLLANT, Guiomar Center for International Climate Research Vietnam Instituto de Ciencias del mar Norway Consell Superior d’Investigacions Científiques SCHISMENOS, Spyros Spain SANCHEZ, Jose Luis National Yunlin University of University of Leon Science and Technology ROUDIER, Philippe Spain Eastern Macedonia and Thrace Institute French Development Agency China France SÁNCHEZ-MOREIRAS, Adela M University of Vigo SCHLEUSSNER, Carl-Friedrich ROY, Joyashree Spain Climate Analytics Jadavpur University Germany Institute of Technology, Bangkok Thailand/India 595 Annex IV Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C SCHNEIDER, Linda SHAPIRO, Robert SINGER, Stephan Heinrich Boell Foundation Climate Mobilization Outer Cape Climate Action Network International Germany USA Belgium SCHOEMAN, David SHAWOO, Zoha SINGH, Chandni University of the Sunshine Coast University of Oxford Indian Institute for Human Settlements Australia UK Myanmar/India SCHULZ, Astrid SHEPARD, Isaac SINGH, Neelam Wissenschaftliche Beirat der Bundesregierung University of Maine World Resources Institute Globale Umweltveränderungen USA USA Germany SHINDELL, Drew SKEA Jim SCOWCROFT, John Duke University IPCC Co-Chair WGIII Global Carbon Capture and Storage Institute USA UK Belgium SHINE, Keith SKEIE, Ragnhild SEHATKASHANI, Saviz Department of Meteorology Center for International Climate Research Academic member of Atmospheric Science University of Reading Norway and Meteorological Research Center UK Iran SMEDLEY, Andrew SHINE, Tara University of Manchester SEILER, Jean Marie Mary Robinson Foundation UK Retired from Commissariat à l’énergie Climate Justice atomique et aux énergies alternatives) Ireland SMITH, Alison France University of Oxford SHIOGAMA, Hideo UK SEITZINGER, Sybil National Institute for Environmental Studies University Victoria Japan SMITH, Sharon Pacific Institute for Climate Solutions Geological Survey of Canada Canada SHOAI-TEHRANI, Bianka Natural Resources Canada Research Institute of Innovative Canada SEMENOV, Sergey Technology for the Earth Institute of Global Climate and Ecology Japan SMITHERS, Richard J. AIV Russian Federation Ricardo Energy & Environment SHUE, Henry UK SEMENOVA, Inna University of Oxford Odessa State Environmental University UK SMOLKER, Rachel Ukraine Biofuelwatch SIETZ, Diana USA SENEVIRATNE, Sonia I. Wageningen University ETH Zurich Netherlands Switzerland SOLAYMANI OSBOOEI, Hamidreza SIHI, Debjani Forest, Range and Watershed SENSOY, Serhat University of Maryland Center for Management Org. Turkish State Meteorological Service Environmental Science Appalachian Laboratory Iran Turkey USA SOLERA UREÑA, Miriam SERRAO-NEUMANN, Silvia SIKAND, Monika Universidad Nacional de Educación Cities Research Institute Bronx Community College a Distancia (Spain) Griffith University City University of New York Germany Australia USA SOORA, Naresh Kumar SETTELE, Josef SIMMONS, Adrian Indian Agricultural Research Institute Helmholtz Centre for Environmental European Centre for Medium- India Research (UFZ) Range Weather Forecasts Germany UK SÖRENAAON, Anna Centro de Investigaciones del SHAH, Shipra SIMS, Ralph Mar y la Atmósfera Fiji National University Massey University Argentina Fiji New Zealand 596 Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C Annex IV SREENIVAS, Ashok SUN, Junying TAKANO, Kohei Prayas (Energy Group) Chinese Academy of Meteorological Sciences Nagano Environmental Conservation India China Research Institute Japan STABINSKY, Doreen SUN, Yongping College of the Atlantic Center of Hubei Cooperative Innovation TAKAYABU, Izuru USA for Emissions Trading System Japan Meteorological Agency China Meteorological Research Institute STANGELAND, Aage Japan The Research Council of Norway SUSANTO, Raden Dwi Norway USA TAKEMURA, Toshihiko Kyushu University STANLEY, Janet SUSATYA, Agus Japan University of Melbourne UNIB Australia Indonesia TAM, Chi Keung Newcastle University STEFANO, Caserini SUTHERLAND, Michael Singapore Politecnico di Milano, Dipartimento di Trinidad and Tobago Ingegneria Civile ed Ambientale TAMAKI, Tetsuya Italy SUTTER, Daniel Kyushu University ETH Zurich Japan STENMARK, Aurora Switzerland Norwegian Environment Agency TAMURA, Makoot Norway SWART, Rob Ibaraki University Wageningen Environmental Research Japan STOCKER, Thomas The Netherlands University of Bern TANAKA, Katsumasa Switzerland SWEENEY, John National Institute for Environmental Studies Maynooth University Japan STONE, Kelly Ireland ActionAid USA TESKE, Sven USA SYRI, Sanna University of Technology Sydney Aalto University Australia STOTT, Peter Finland University of Exeter and Met Office TEXTOR, Christiane AIV UK TABARA, J. David German Aerospace Centre Autonomous University of Barcelona Germany STRANDBERG, Gustav Spain Swedish Meteorological and THALER, Thomas Hydrological Institute TABATABAEI, Seyed Muhammadreza Institute of Mountain Risk Engineering Sweden University of Tehran University of Natural Resources Iran and Life Sciences Austria STRAPASSON, Alexandre TACHIIRI, Kaoru Harvard University Japan Agency for Marine THIERY, Wim Brazil Earth Science and Technology ETH Zurich Japan Switzerland SU, Mingshah National Center for Climate Change TAKAGI, Hiroshi THOBER, Stephan Strategy and International Cooperation Tokyo Institute of Technology Helmholtz Centre for Environmental China Japan Research (UFZ) Germany SUGIYAMA, Masahiro TAKAGI, Masato The University of Tokyo Research Institute of Innovative THOMPSON, Michael Japan Technology for the Earth Forum for Climate Engineering Assessment Japan USA SULISTYAWATI, Linda Yanti Universitas Ahmad Dahlan TAKAHASHI, Kiyoshi THORNE, Peter Indonesia National Institute for Environmental Studies Maynooth University Japan Ireland 597 Annex IV Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C THORNTON, Thomas TYLER, Emily VENEMA, Henry David Environmental Change Institute University of Cape Town International Institute for University of Oxford South Africa Sustainable Development UK Prairie Climate Centre UDDIN, Noim Canada THWAITES, Joe CPMA International World Resources Institute Australia VERA, Carolina USA Centro de Investigaciones del UDO, Keiko Mar y la Atmosfera TIBIG, Lourdes Tohoku University University of Buenos Aires Climate Change Commission Japan Comision Nacional de Investigaciones Philippines Cientifico Tecnologicas URQUHART, Penny Argentina TILCHE, Andrea Independent climate resilient European Union development specialist VERHOEF, Leendert Belgium South Africa University of Technology Delft Netherlands TINDALL, David VAILLES, Charlotte Department of Sociology Institute for Climate Economics VICTOR, David University of British Columbia France University of California San Diego Canada USA VALDES, Luis TOKARSKA, Katarzyna B Instituto Español de Oceanografía VIDALENC, Eric University of Victoria Spain Agence de l’environnement et UK de la maîtrise de l’énergie VAN DE WAL, Roderik France TORVANGER, Asbjørn Netherlands Center for International Climate Research VINCENT, Ceri Norway VAN DEN HURK, Bart British Geological Survey TREBER, Manfred Koninklijk Nederlands Meteorologisch UK Germanwatch Instituut Germany Netherlands VINER, David Mott MacDonald TREGUER, Paul VAN MUNSTER, Birgit UK AIV Université de Bretagne Occidentale Homo Sapiens Foundation France UK VIVIAN, Scott University of Edinburgh TSCHAKERT, Petra VAN RUIJVEN, Bastiaan UK University of Western Australia International Institute for Australia/Austria Applied Systems Analysis VLADU, Iulain Florin Austria United Nations Framework TSUTSUI, Junichi Convention on Climate Change Central Research Institute of VAN VELTHOVEN, Peter Germany Electric Power Industry Koninklijk Nederlands Meteorologisch Japan Instituut VON SCHUCKMANN, Karina Netherlands France TUITT, Cate Honourable society of Inner Temple VAN YPERSELE, Jean-Pascal WACHSMUTH, Jakob UK Université catholique de Louvain Fraunhofer Institute for Systems Earth and Life Institute and Innovation Research TULKKI, Ville Belgium Germany VTT Technical Research Centre of Finland Ltd Finland VAUTARD, Robert WACKERNAGEL, Mathis Institut Pierre Simon Laplace Global Footprint Network TURCO, Marco France USA University of Barcelona Spain VELDORE, Vidyunmala WADLEIGH, Michael DNV-GL Closed Mass TURP, Mustafa Tufan Norway USA Bogazici University Center for Climate Change and Policy Studies Turkey 598 Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C Annex IV WAGNER, Gernot WEST, Thales A. P. WOLF, Shaye Harvard John A. Paulson School of University of Florida Center for Biological Diversity Engineering and Applied Sciences Brazil USA Harvard Kennedy School USA WESTPHAL, Michael WOOLLACOTT, Jared World Resources Institute RTI International WANG, Bin USA USA University of Virginia USA WESTRA, Seth WRATT, David University of Adelaide National Institute of Water & WANG, Junye Australia Atmospheric Research Athabasca University New Zealand Canada WHITEFORD, Ross University of Southampton WRIGHT, Helena WANG, Xiaojun UK E3G Research Center for Climate Change, UK Ministry of Water Resources WHITLEY, Shelagh China Overseas Development Institute WU, Jianguo UK Chinese Research Academy of WANG, Zhen-Yi Environmental Sciences Delta Electronics Foundation WICHMANN, Janine China China University of Pretoria South Africa WURZLER, Sabine WARNER, Koko North Rhine Westphalian State Agency for United Nations Framework WIEL, Stephen Nature, Environment, and Consumer Protection Convention on Climate Change CLASP Germany Germany USA XENIAS, Dimitrios WARRILOW, David WILDENBORG, Ton Cardiff University Royal Meteorological Society Netherlands Organisation for Applied UK UK Scientific Research (TNO) Netherlands XU, Yangyang WASHBOURNE, Carla-Leanne Texas A&M University University College London WILLIAMS, Jonny USA UK The National Institute of Water AIV and Atmospheric Research XU, Yinlong WASKOW, David New Zealand China World Resources Institute USA WILLIAMS, Richard YAMAGUCHI, Mitsutsune Liverpool University Research Institute of Innovative WEBB, Jeremy UK Technology for the Earth Department of Science, Technology Japan Engineering and Public Policy WINIGER, Patrik University College London Netherlands YANG, Hong UK Swiss Federal Institute of Aquatic WINKLER, Harald Science and Technology WEBER, Christopher University of Cape Town Switzerland 1982 Energy Research Centre USA South Africa YANG, Tao Jiangxi Normal University WEHNER, Michael WINROTH, Mats China Lawrence Berkeley National Laboratory Chalmers University of Technology USA Sweden YANG, Xiu National Center for Climate Change WEI, Taoyuan WISSENBURG, Marcel Strategy and International Cooperation Center for International Climate Research Radboud University China Norway Netherlands YOON, Soonuk WEISENSTEIN, Debra WITHANACHCHI, Sisira S. Green Technology Center School of Engineering and Applied University of Kassel Republic of Korea Science, Harvard University Germany USA 599 Annex IV Expert Reviewers of the IPCC Special Report on Global Warming of 1.5°C YOSEPH-PAULUS, Rahayu ZICKFELD, Kirsten Local Government of Buton Regency Simon Fraser University Indonesia Canada/Germany YU, Rita Man Sze ZIELINSKI, Tymon CSR Asia Institute of Oceanology China Polish Academy of Sciences Poland YU, Yau Hing Sovran Environment & Energy Corp. ZINKE, Jens China Freie Universitaet Berlin Germany ZABOL ABBASI, Fatemeh Climatological Research Institute ZOBAA, Ahmed Iran Brunel University London UK ZAELKE, Durwood Institute for Governance and ZRINKA, Mendas Sustainable Development University of Bolton USA UK ZAFAR, Qudsia Global Change Impact Studies Centre Pakistan ZARIN, Daniel Climate and Land Use Alliance USA ZAVIALOV, Petr Shirshov Institute of Oceanology Russian Federation ZEREFOS, Christos AIV Academy of Athens Greece ZHANG, Jingyong Institute of Atmospheric Physics Chinese Academy of Sciences China ZHANG, Wei IIHR Hydroscience and Engineering University of Iowa USA ZHANG, Xiaolin Florida State University China ZHAO, Zong-Ci National Climate Center China Meteorological Administration China ZHOU, Tianjun Institute of Atmospheric Physics Chinese Academy of Sciences China 600 Index This index should be cited as: IPCC, 2018: Index. In: Global Warming of 1.5°C. An IPCC Special Report on the impacts of global warming of 1.5°C above pre-industrial levels and related global greenhouse gas emission pathways, in the context of strengthening the global response to the threat of climate change, sustainable development, and efforts to eradicate poverty [Masson-Delmotte, V., P. Zhai, H.-O. Pörtner, D. Roberts, J. Skea, P.R. Shukla, A. Pirani, W. Moufouma-Okia, C. Péan, R. Pidcock, S. Connors, J.B.R. Matthews, Y. Chen, X. Zhou, M.I. Gomis, E. Lonnoy, T. Maycock, M. Tignor, and T. Waterfield (eds.)]. In Press. 601 Index 1.5°C warmer worlds*, 4–6, 274–281 4.SM.4.5.1, 4.SM.5.2 Note: [*] indicates the term also appears in the commonalities in, 277 transformational, 5, 315, 322–323, 384, 397, Glossary. Italicized page numbers denote tables, definition, 53 456–457 figures and boxed material. Bold page numbers energy supply and demand in (FAQ), 161, 162 Adaptation behaviour*, See Human behaviour indicate main discussion of topics. Supplementary equity and, 54–55, 451–453 Adaptation limits*, 10, 70, 454–456 Material is listed by section number, for example, impacts in, 7–10, 177–179, 319 examples of, 455 1.SM.3, 2.SM.1.3.4. importance of adaptation in (FAQ), 396–397, 397 hard limits, 70, 455 key questions, 274–277 residual risks and, 454–455 knowledge base for, 52, 53–56 for Small Island Developing States, 235 1.5°C pathways*, 12–17, 51, 59–64, 93–174, poverty, equality, and equity implications, 451–453 soft limits, 70, 455 265–271, 278, 320, 1.SM.4, 1.SM.6 projected climatic changes, 7–10, 186–188, 188, 189 Adaptation options*, 10, 19, 316–317, 319, assumptions, 95, 98, 109–112 projected risks and impacts, 7–10, 11, 51, 336–337 carbon dioxide removal (CDR)* in, 17, 21, 95, 96, 175–311 in agriculture, 70, 315, 457 118–125, 180, 277, 316 risks, vs. 2°C worlds, 5, 7–9, 11, 177–181, 277 cost-effectiveness, 316 classification of, 99–100, 100, 113–114 storyline of this report, 77–78, 78 education and learning, 337, 456 CO2 emissions, 1.SM.6 storylines of, 277 enabling conditions*, 4.SM.2 definition, 51, 53, 59–61 sustainable development and, 18–23, 55–56, 447 energy system transitions, 4.SM.4.3.1 demand-side mitigation and, 97, 460–461 temperature in, 283 feasibility, 381, 384–386, 385, emissions and, 5, 6, 12, 13, 14–15, 18, 51, 95–96, time frame for mitigation, 277, 278 4.SM.4.3.1-4.SM.4.3.5 112, 1.SM.6 variation in, 177, 277, 278 industrial system transitions, 4.SM.4.3.4 emissions, benchmark indicators for watershed management in, 356 land and ecosystem transitions, 4.SM.4.3.2 sectoral changes in, 4.SM.1 See also Global warming of 1.5°C overarching, 336–337, 338, 385, 389, 4.SM.4.3.5 emissions evolution in, 115–118, 117, 119 2030 supporting transitions, 336–337, 338 feasibility*, 18–19, 52, 56, 71–72, 380–386 emissions gap, 358 sustainable development and, 457–458 four categories of, 59–61, 62, 63 emissions levels in, 18, 95, 114 synergies, 18, 19 future emissions in, 96, 104–107 2030 Agenda for Sustainable Development*, urban, 10, 70, 263, 340–341, 384–386, 385 impediments to, 93, 95, 110 56, 73, 469, 477 urban and infrastructure transitions, 4.SM.4.3.3 implications of, 265–271 See also Sustainable Development Goals Adaptation pathways*, 64, 70, 396, 458–459 investments and economics, 16, 95–96, 150–151, place-specific, 458 152–155, 264–265 A Adaptive capacity*, key characteristics, 112–114, 129 enhancing, 316, 319, 456–457 knowledge gaps, 388–390 Acceptability of policy or system change*, factors affecting, 69 mitigation and adaptation options*, 110–112, 22, 368–369 limits to, 10 316–317 Adaptability. See Adaptive capacity sustainable development and, 447 mitigation measures, 14–15, 19–21, 51–52, 110–112 Adaptation*, 5, 10 Adaptive governance. See Governance model pathways, 12, 14–15, 278 bottom-up approaches, 317, 368 Aerosols*, 12, 65, 118, 120, 267–268 multiple strategies for, 157, 469 community-based, 315, 330, 384, 458 aerosol cooling, 96, 267–268 near-term action, implications of, 126–129, 128 definition, 51, 70, 396 knowledge gaps, 157 one-in-two to two-in-three chance (of reaching ecosystem-based, 386, 457–458 precursors, 98, 102–103, 118, 157 limit) in, 60, 63, 113 FAQ on, 396–397, 397 radiative forcing, 102–103 overview of, 108–129, 129 feasibility, 380, 381, 385 See also Black carbon pathway archetypes, 99–100, 100, 112–113, 113 finance, 21–22, 379, 456 Afforestation*, 17, 21, 96, 121, 266, 270, 316, 343 pathways remaining below 1.5°C, 100, implementing, 51, 315, 383–386 co-benefits, 316 113–114, 160 importance of, 396–397, 397 constraints, 316 pathways temporarily exceeding 1.5°C, 100, infrastructure investments, 21 FAQ, 394, 395 113–114, 160 integration with mitigation and sustainable incentivization of, 147 policies, 112, 148–150 development, 75–76, 448, 467 land requirements, 125, 126, 265, 266, 269, remaining carbon budget*, 12, 96, 104–107, 108 knowledge gaps, 388–391 270, 316 scenarios, 98–100, 100 levels of, 51 trade-offs, 269 strengthening the global response, 18–23, 70–75, local participation, 456 AFOLU. See Agriculture, forestry and other land-use 313–443 maladaptation, 19, 386, 396 Africa sustainable development and, 19–23, 20–21, 98, in Mekong River basin, 239–240 Fybnos and succulent Karoo biomes, 260, 261 156–157, 156, 448–449, 463–472, 465 place-specific, 447, 458 Limpopo Watercourse Commission, 356 sustainable development pathways, 64, 448–449, potential for, 247–250 Sahel, 180, 236, 259, 261, 262–263 466–472, 469, 479–480 rate of temperature change and, 178 Southern Africa, 260, 261 synergies and trade-offs, 18–21, 20–21, 316, 391 risk reduction and, 5, 10 tipping points*, 262–263, 264 system/sector transitions, 14–15, 15–16, sea level rise and, 10, 457 West Africa and the Sahel, 259, 261, 264 323–349 socio-economic challenges to, 110 West African monsoon, 262–263, 264 time frame for mitigation, 95–96 specific sectors, 10 Agreement*. See Confidence; Evidence; Likelihood transformations, 129–148, 322–323, 466 sustainable development and, 19, 447, 456–459 Agriculture transitions, speed and scale of, 320, 320, 322–323 synergies, 18–19, 391, 447, 475 adaptation options*, 70, 315, 457 See also Pathways synergies with mitigation, 386–387, 475, agroforestry, 328, 384 602 Index Index climate-smart agriculture*, 457, 467 warming in, 4 342–343, 394, 395 conservation agriculture*, 267, 327, 384, 459 See also Arctic sea ice in IAMs, 124 crop yields/productivity, 9, 11, 145, 145, 147, Arctic sea ice, 8, 205–206, 209, 254 land requirements, 125, 126, 180, 265–266 179, 236–237, 252, 259, 263, 264, 267, 316, 327, beyond end of century, 270 net zero emissions and, 135 452, 3.SM.3.3.5 fisheries and, 224–225 pathways with, 14–15, 17, 96, 180 emissions, 12, 14, 95, 96, 116–118, 147, 147, 157, as hotspot and tipping point, 258, 261, 262, 270 risks, 125, 268–270 265, 315–316 projected changes, 205, 212, 254 uncertainties, 158 energy crops, 16, 97 sea-ice free summers, 8, 178, 205, 206, 254 Bioethanol, 371 intensification of, 266–267, 327 temperature overshoot and, 8, 178, 206 Biofuel*, 269, 324–325 irrigation, 201, 215, 267, 267, 315, 328, 384, 466 Asian monsoon, 262, 264 Biomass*, 131, 132–133, 138, 269, 324 land for, 16, 97, 112, 146, 327–329 Assessment frameworks, 75–76 Biome shifts, 216, 217, 247, 250, 256–257 livelihoods, 55, 315, 447 climate models and simulations, 76 Fybnos and succulent Karoo biomes, 260, 261 mitigation potential, 316 confidence, uncertainty, and risk, 77 Bivalve molluscs, 180, 227, 228, 237, 238, 248, peri-urban, 316 cost-benefit analysis*, 76 3.SM.3.2.5, 3.SM.3.2.11 risk reduction, 456 detection and attribution, 76 Black carbon (BC)*, 12, 13, 96, 118, 120, 316, technological innovation and, 329, 370 knowledge sources and evidence, 75–76 341–342 tipping points*, 263, 264 methodologies, 76 main characteristics of, 342 transformational adaptation in, 384 risk assessment*, 183–186 reducing emissions of, 341–342 transitions, 315–316 Atlantic Meridional Overturning Circulation warming impact, 66 water-energy-food (WEF) nexus, 386–387 (AMOC), 205, 223, 257 Blue carbon*, 330, 462 Agriculture, forestry and other land-use (AFOLU), Atlantic Multi-Decadal Oscillation (AMO), 201 Bolivian Altiplano, 458 144–148, 463 Atmosphere-ocean general circulation model Boreal forests, 8, 263, 264 CDR and, 17, 121, 144–145 (AOGCM). See Climate models Bottom-up approaches, 317, 368 drivers of changes in, 145–146 Attribution. See Detection and attribution Brazil emissions, 14–15, 114, 118, 268 Avoided impacts, 18, 68, 183, 253–265, 447 bioethanol in, 371 mitigation options*, 462–463 aggregated avoided impacts, 253–258 National Adaptation Plan, 340 policy assumptions, 145–146 hotspots, 258–260, 261 Buen Vivir, 480 projections for, 17 poverty and inequality implications, 452–453, 453 Buildings, 15–16, 139, 140–142, 316 Agroforestry, 328, 384 Reasons for Concern, 253–259 building codes, 332, 339, 377 Air pollution/quality*, 157, 241, 250, 267, 316, 464 reduced risks, 452–453, 453, 455 decarbonization of energy supply, 316 Albedo*, 70, 267 regional tipping points, 262–263, 264 decarbonization of investments, 378 Algae, as bioenergy source, 111–112 sustainable development electrification, 141 Alpine regions, 259, 261 implications, 452–453, 453 energy efficiency and, 332, 339, 377, 460 Amazon, 340 energy supply/use in, 139, 140–142, 141, 331 tropical forest, 221, 263, 340 B heating and cooling demand, 141–142, 331 Ammonia (NH3) emissions, 96 long-lived infrastructure, 142 Anomalies* Baseline period. See Reference period low-emission, 317, 460 global mean surface temperature, 183, 210 Batteries, 325 technological innovations, 370 soil moisture*, 198, 199, 200 Behavioural change. See Human behaviour transitions, speed and scale of, 320 Antarctic ice sheet, 7, 178, 208–209, 257, 258, 271, Beijing, peak car use, 376 Burden sharing*, 380, 470 282 Bhutan, national goals, 387 Antarctic sea ice, 206, 225 Bio-based feedstocks, 315, 335–336, 335 C Anthropocene*, 52, 53, 54, 75 Bio-technologies, 319 as boundary concept for 1.5°C warmer worlds, 54 Biochar*, 121, 268, 270, 345 Cancun Agreement, 79, 353 geological dimension of, 54 Biodiversity*, 8, 256–257 Car use Anthropogenic emissions*, 5, 95 adaptation limits*, 455 peak car use, 376 recent trends, 1.SM.7 Aichi targets, 266 pricing policies and use reductions, 366 Appliances, energy-efficient, 316, 331, 460, 461 CDR and, 265, 266, 269 Carbon budget*, 12, 96, 104–107 Aquaculture, 8, 9, 237–238 impacts and risks at 1.5°C vs. 2°C, 8, 179, 256–257 in 1.5°C pathways, 113–114 hypoxia and, 224 management, 10 remaining carbon budget*, 12, 24, 96, 104–107, 108 production, 237–238 Bioenergy*, 12, 17, 97, 111–112, 124, 131, 324–325 remaining carbon budget*, assessment methods, risks for, 228 carbon intensity of, 324–325 104–107, 2.SM.1.1.2 AR5. See IPCC Fifth Assessment Report (AR5) crops, 147 total, 24 Arctic region, 258–259, 338–339, 452, 3.SM.3.3.5 emissions increase with, 96 uncertainties, 12, 96, 106, 108 adaptation in, 339 IAMs/modelling, 124, 2.SM.1.2.4 Carbon cycle*, 96, 103, 157 economic effects of climate change, 339 land use for, 19, 146, 147, 265, 269, 343 inertia, 107 ecosystems, 9, 11, 53, 220 risks of implementing, 125 oceans and, 257–258 as hotspot, 258, 261, 262, 270, 338 sugarcane for bioethanol in Brazil, 371 terrestrial, 219, 220 indigenous peoples, 9, 339 trade-offs, 97 uncertainties, 347 land regions, 259, 261 water use and, 464–466 Carbon dioxide (CO2)* risks for, 9, 53, 251, 252, 253, 452 Bioenergy with carbon dioxide capture and cumulative emissions, 6, 12, 62, 67, 96, 105, 114, tipping points*, 262, 264 storage (BECCS)*, 17, 121, 268–270, 316, 123, 126–127, 127 603 Index Index emissions reductions, 18, 95, 96 of electricity, 97, 130 Coupled Model Intercomparison Project (CMIP)*, net emissions, 12–17, 13, 14–15, 114, 116, 119 of final energy sectors, 129–130, 130, 137–138, 139 62, 76 net zero emissions, 5, 12, 24, 95, 107, 116 of residual fuel mix, 130 downscaling*, 76, 186, 194 permafrost release of, 104 Carbon leakage, 149, 375 FAIR, 99, 101, 102, 103, 103, 158 sector-specific emissions, 119 Carbon neutrality*, 14, 96 HAPPI, 76 time scales of warming due to, 64 timing of, 12, 96 integrated multimodel studies, 99 Carbon dioxide capture and storage (CCS)*, 14, 15, Carbon price*, 95, 152–153, 153, 375–377 knowledge gaps, 272 97, 134–136, 136, 268, 277, 315 necessity and constraints, 375–377 MAGICC, 99, 101, 102, 103, 103, 127, 127, 158 deployment in 1.5°C and 2°C pathways, 134–136, policies on, 95, 317, 375–377, 460 reduced-complexity, 2.SM.1.1.1 136 uniform world carbon price, 375 regional (RCM), 185 direct air carbon dioxide capture and storage Carbon sequestration*, 67, 95, 112, 114, 121–124, Climate monitoring, 317 (DACCS)*, 17, 125 147, 266 Climate projections* fossil fuels with CCS, 97, 135 marine, 17, 121, 125, 178, 227, 228, 229, climate models and simulations, 76, 183–184 in industry sector, 335, 336 3.SM.3.2.8 definition of, 184 in power sector, 326–327 in peatlands, 221 Climate-resilient development pathways uncertainties, 136 permanence of, 125 (CRDPs)*, 22, 52, 73, 448–449, 450–451, 451, See also Bioenergy with carbon dioxide capture soil carbon sequestration (SCS)*, 17, 121, 219, 468–472, 475–476 and storage (BECCS) 268, 269, 270, 345 country and community strategies, 470–471 Carbon dioxide capture and utilisation (CCU)*, terrestrial, 112, 121, 125, 146–147, 219, 265, 316 definition, 24, 64 15, 335, 336 tracking progress toward, 67 development trajectories and equity, 469–470 Carbon dioxide capture, utilisation and storage See also Blue carbon; Carbon dioxide capture FAQ on, 479–480, 480 (CCUS). See Carbon dioxide capture and utilisation and storage low-carbon development pathways, 471–472 (CCU) Carbon sink. See Carbon sequestration regional and national factors, 22 Carbon dioxide removal (CDR)*, 17, 70, 118–125, Carbonate chemistry, 178, 222, 223 sustainable development and, 22, 448–449 268–270, 342–346, 4.SM.4.2.5 Caribbean region, 260, 339–340 trajectories and decision-making in, 451, 480 in 1.5°C pathways*, 17, 21, 95, 96, 111, 114, small island developing states and territories, transformations, equity, and well-being in, 118–125, 122, 180, 265, 277, 316 339–340 468–469, 472, 472–474 AFOLU sector, 17, 121 China urban transformations* in, 472–473 co-benefits, 121, 266 peak car use in Beijing, 376 in Vanuatu, 471 comparison of removal options, 270 technology and renewables pathways, 471 Climate-resilient pathways*, 64 costs, 344, 4.SM.3 Circular economy, 335–336 Climate sensitivity* cross-cutting issues, 347 Cities, 330–334 equilibrium climate sensitivity*, 103, 104 definition, 24, 70 impacts and risks, 180, 182 transient climate response*, 96, 184–185 deployment at scale, 17, 70, 96, 114, 121–124, sea level rise, impacts, 231–232 uncertainties, 12 122, 180, 265–266, 269–270, 343, 4.SM.3 transformation* in, 472–474 See also Transient climate response to cumulative deployment potential, 344 See also Urban areas; and specific cities CO2 emissions design and implementation of, 21, 448 Civil society, 23, 317 Climate services*, 337, 338, 385 ethical aspects, 347 Clean Development Mechanism (CDM)*, 474 Climate system*, 5, 208 FAQ on, 394, 395 Climate change commitment* as a global commons, 353 feasibility, 17, 121, 269, 316, 343, 383, 4.SM.4.2.5 constant composition commitment, 64 assessment of changes in, 183, 186 governance and, 17, 347 geophysical warming commitment, 64–66, 65 observed changes in, 177 key messages, 270 warming commitment from past emissions, tipping points in, 262–263, 270 knowledge gaps, 158, 390 64–66, 65, 1.SM.5 Climate target*, 98–99, 151 land-based, 268–270 zero emissions commitment, 64–65, 65 policy assumptions and, 149 land footprint of, 125, 126, 180, 265–266, 269, Climate education, 22, 317, 456 stringent, 112, 126 270, 343 Climate extreme (extreme weather or climate Climate variability*, 279–281 limitations of, 96 event)*, 4, 182 Coal, 96–97, 132, 132–133, 138, 461 in model pathways, 12, 14–15 in 1.5°C warmer worlds*, 7 Coastal communities, 9, 181, 182, 222, 453, net negative emissions, 96, 114, 118 human health and, 240–241 Table 3.SM.4 ramp-up rates for, 119, 123 impacts, 7, 177–178, 182, 240 adaptation, 226, 233, 457 reducing dependence on, 19, 149, 180, 277 observed changes in, 4, 7, 177, 210, 223, 1.SM.1 adaptation limits*, 455 risks of, 96, 114, 125, 265–266, 344 precipitation extremes, 7, 178, 189, 190–192, 197 coastal protection, 225, 226, 227–228, role of, 17, 21, 96, 111, 114, 122–123 projected changes, 7, 177–178, 189, 190–191, 192 3.SM.3.2.9 side effects, 344, 4.SM.3 risks from, 11, 181 flooding, 11, 181, 231, 235, 249, 252, 252, sustainability and, 21, 96, 114, 124–125 temperature extremes, 7, 177, 187, 189, 190–191, 3.SM.3.3.3 Sustainable Development Goals and, 448, 462 192, 210, 255 groundwater, 181 trade-offs, 21, 96, 462 Climate feedbacks*, 5, 103 infrastructure risks, 181, 226, 231, 235, 249 types of measures employed, 17, 70, 96, 121, biophysical feedbacks, 266–267 livelihoods, 9, 222, 226, 249, 447, 452 125, 265, 268, 270, 316, 342–346, 394 Earth system feedbacks, 65, 103–104 relocation of, 457 uncertainties, 96, 158, 343, 347 land processes and, 268 sea level rise and, 207, 225, 231–234, 243, 249, Carbon intensity*, 97 Climate forcers. See Radiative forcing 252, 457 of bioenergy*, 324–325 Climate models*, 7, 76, 177, 183–184, 274, 3.SM.1.1 tourism, 229, 253 604 Index Index Coastal ecosystems, 8, 181, 182, 226, 249, 330, 259, 263, 267, 327, 452, 3.SM.3.3.5 reduction, technological innovations and, 370 Table 3.SM.4 Cuba, risk management in, 339 Sendai Framework for Disaster blue carbon*, 330, 462 Cultural practices and resilience, 360 Risk Reduction*, 70 framework organisms in, 225–226, 248 See also Hazard integrated coastal zone management, 226 D Discounting*, 152 protection services, 227–228, 228, 248 Disease, 9, 452 restoration of, 330 Danube River Protection Convention, 356 dengue fever, 9, 180, 241 saltwater intrusion, 8 Decarbonization* diarrhoea, 452 sea level rise and, 207, 225, 249 of electricity, 95 geographic range shifts of vectors, 9, 180, 241 storms/storm surge, 223, 249 of energy sector, 95, 148, 277, 316, 461 malaria, 9, 180, 241 stress management in, 330 of industry sector, 140 vector-borne, 9, 180 Co-benefits*, 2, 67, 157, 268, 316, 319, 323 of investments, 378 See also Human health of sustainable development*, 447 macro-level indicators, 129–130 Displacement*. See Migration Common but Differentiated Responsibilities rate of, 12, 468 Disruptive innovation*, 22, 111, 319, 323 and Respective Capabilities (CBDR-RC)*, 318 transport sector, 333, 461 Double dividend*, 376 Community-based adaptation, 315, 330, 360, Decision-making, 321, 360, 365, 456, 462, 469 Downscaling*, 76, 186, 194, 204 384, 458 adaptation, 459 Droughts*, 182, 196–201, 211, 215, 247, 250, 255, Conference of the Parties (COP)* information provision and, 367 3.SM.3.1.1.2 COP 15, 378 participatory, 386, 459 hotspots, 199, 200, 260 COP 16 (Cancun), 353 problem-solving, 448–449 management responses/examples, 356 COP 21, 66, 79, 372 sustainable development goals and, 451, 480 in Mediterranean Basin and the Middle East, Confidence*, 77, 182 Decoupling*, 56, 372, 376, 461 200–201 See also Evidence; Likelihood; Uncertainty Definitions, 24 observed changes, 196, 211 Conflict, 245 See also Glossary Palmer Drought Severity Index, 199, 215 Conservation agriculture*, 267, 327, 384, 459 Deforestation*, 263, 264 precipitation minus evapotranspiration, 198–199, Consumption, 53, 56 emissions from, 146 198, 255 resource-intensive, 95 of mangroves, 226, 251 projected, for 1.5°C warming, compared with 2°C, responsible, 460 rates of, 146 7, 178, 196–201, 199, 211, 215, 247, 250, 255, Cook stoves, 460 reducing emissions from (REDD+), 329–330 3.SM.3.1.1.2 Cooperation, 23, 461 tipping points*, 263 regional changes, 198–200, 198, 199, 200–201 international, 22, 23, 95, 240 Deltas and estuaries, 232–233 Drylands, 459 regional, 353–354 Demand and supply-side measures*, 97, 111, Copenhagen Accord, 353 161, 317 E Coral reefs, 8, 11, 179, 229–230, 3.SM.3.2.3, demand-side measures*, 97, 460–461 3.SM.3.2.10, 3.SM.3.3.9 investments, 153–154 Early warning systems (EWS)*, 338, 339, 370 adaptation limits*, 455 mitigation and, 97 Earth system bleaching and mortality, 70, 228, 229, 254 supply-side measures*, 111 feedbacks, 65, 96, 103–104 Great Barrier Reef (Australia), 228, 251 See also Energy supply and demand inertia of, 64 heat stress, 226, 229 Dengue fever, 9, 180, 241 Economic factors, 9, 150–151, 152–155, 264–265 impacts, 221 Detection and attribution*, 76, 183, 210–212 access to finance, 21, 23, 155 observed loss of, 8, 228–229 attribution methods, 3.SM.1.2 circular economy, 335–336, 335 projected losses, 8, 179 human influences on climate, 4, 51, 59, 81,82, co-benefits (‘double dividend’), 376 projected risks, 53, 225–226, 228, 228–229, 248, 186–187, 210–212, 282, 1.SM.2, 1.SM.6, 3.SM.2.1 depreciation of assets, 375 251, 252, 254 of impacts, 69, 213 ‘depression economics’, 319 protection for coastal areas, 228 regional precipitation on land, 3.SM.2.2.1 economic damages from climate change, 243, storm damage, 222 regional temperature on land, 3.SM.2.2.1 264–265 Cost-benefit analysis*, 76, 150–151 sea level rise, 252 green economy, 470–471 Cost-effectiveness*, 150–151, 152–153, 316 Developing countries incentives, 317, 366, 377 Costs, 76 adaptation finance, 21 marginal abatement costs, 16, 95, 150, 375 adaptation, 21–22, 316 development trajectories, 469–470 pricing instruments, 317 economic damages from climate change, 243, international cooperation and, 23 redistributive policies, 21 264–265 Development pathways. See Climate-resilient regional economic benefits, 258 energy sector transition, 374–375 development pathways; Pathways See also Finance; Investments marginal abatement costs, 16, 95, 150 Diet, human, 19, 180, 316, 462, Table 3.SM.12 Economic growth, 53, 180–181, 182, 319 mitigation, 16, 22, 258, 264, 316 Direct air carbon dioxide capture and storage decoupling from emissions, 56, 372, 376, 461 regional economic benefits, 258 (DACCS)*, 17, 125, 316, 346, 394 impacts on, 180–181, 182 social cost of carbon (SCC)*, 150–151, 265, 375 Disaster risk management (DRM)*, 10, 316, 336, mitigation costs and, 258 See also Carbon price 338, 385 regional economic benefits, 258 Coupled Model Intercomparison Project (CMIP)*, in Jamaica, 339–340 risks at 1.5°C, vs. 2°C, 9, 180–181, 182 62, 76 Disaster* in SSPs, 110, 149 Covenant of Mayors initiative, 354, 355 early warning systems*, 338, 339, 370 Economic indicators/variables Crop yields, 9, 11, 145, 145, 147, 179, 236–237, 252, preparedness, 339–340 discounting*, 152 605 Index Index economic diversification, 21, 71, 448 evolution of supply over time, 134, 135 enabling technological innovations, 369–372, 370 gross domestic product (GDP)*, 158, 243, 256, investments, 154 FAQ, 392–393 258, 265, 373 from renewables, 15, 96, 134, 324 international cooperation, 22, 23 gross fixed capital formation (GFCF)*, 317, 373 technological innovations, 370 knowledge gaps, 390–391 Economic sectors, 242–244, 256, 3.SM.3.5 Electrification, 15, 95, 97, 111, 134, 315, 316, 326 Manizales, Colombia: enabling environment in, 361 energy systems, 243–244 in industry sector, 335, 336 for mitigation implementation, 381–383 global economic impacts, 256 in transport sector, 332–333, 333, 460 Energy efficiency*, 15, 96, 137, 140, 315, 316, impacts and risks, 180–181, 242–244, 250, 256 Emission pathways*, 12–17, 13, 14–15, 137, 184, 460–461 tourism, 242–243 274–276 appliances, 316, 331, 460, 461 transportation, 244 in a prospective scenario, 276 behavioural responses and, 460–461 Ecosystem(s)*, 179, 182, 216–230, 250 definition and categories, 24, 59–61, 62 building codes, 332, 339, 377 adaptation options*, 384, 385, 4.SM.4.3.2 See also Pathways efficiency standards, 377, 378 Arctic, 9, 11, 53, 220 Emissions food production systems, 315–316 coastal, 8, 181, 182, 226, 249, 330 1.5°C pathways*, 6, 12–17, 13, 14–15, 95, 112, improving, 377–378 drylands, 459 113–118, 113, 117, 463 in industry sector, 315, 335, 335 feasibility of mitigation options, 382 aggregate, 67–68, 115 mitigation options, 460–461 freshwater, 213–216, 221, 247 anthropogenic, recent trends, 1.SM.7 policies, 149, 153, 377–378 impacts and risks at 1.5°C, vs. 2°C, 5, 8–9, in archetype pathways, 112–113, 113 sustainable development goals (SDGs) and, 448 11, 179, 182, 250, 453 benchmark values, 115, 4.SM.1 Energy sector, 15, 129–144, 243–244, 315, 324–327 impacts of temperature overshoot, 277 calculating, 66–68 adaptation options*, 384, 385 knowledge gaps, 388 carbon budget* and, 96 carbon dioxide capture and storage in, 326–327 large-scale shifts in, 69 CO2 equivalent emission*, 67, 127 carbon intensity, 129–130, 130, 137–138, 138, 139 mitigation and, 315, 4.SM.4.2.2 cumulative CO2, 6, 12, 62, 67, 96, 113, 123, 1.SM.6 decarbonization, 95, 148, 277, 316, 461 observed impacts, 253 cumulative CO2 and temperature, 96, 104, 105, decarbonization, macro-level indicators, 129–130 ocean, 8–9, 179, 221–230, 248 126–127, 127 diversification of, 21, 448 resilience, 70 cumulative emissions*, 6, 12, 62, 67, 123 electrification, 15, 95, 97, 111, 134, 315, 316, 326 restoration of, 329–330, 459 at current rate, consequences of, 5 emissions, 96, 137, 138 risks of severe impacts, 53 decoupling economic growth from, 56, 372, 376, 461 end-use sectors, 136–144 risks, regional and ecosystem-specific, 219–221 emissions gap, 126, 358 energy security, 387 succession in, 69 future emissions, commitment to, 66 feasibility of mitigation options, 382 terrestrial, 8, 11, 179, 216–221, 247, 251, global, in 2030, 6, 12, 13, 95 final energy, 137, 138 3.SM.3.3.7 long-lived climate forcers, 66–68, 116–118, 117 fuel switch, 460–461 trade-offs, 19 measuring progress to net-zero emissions, 66–68 hybrid systems, 326 transformations, 8 Nationally Determined Contributions (NDCs)*, infrastructure, 326, 384, 385 transitions, 315, 4.SM.4.2.2, 4.SM.4.3.2 56, 95, 126–129, 127, 128, 149 investments, 16, 22, 95–96, 153, 155, 372, 373–374 Ecosystem-based adaptation, 386, 457–458 negative emissions*, 17, 51, 70, 96, 114, 118 knowledge gaps, 388 Ecosystem restoration, 16, 70, 329–330, 384 net-zero emissions, 12, 51, 95, 107, 116 low-carbon pathways, 462, 464–466 Ecosystem services*, 17, 19, 179, 247 net-zero, timing of, 95, 119 low-carbon technologies, 15, 16, 96 carbon sinks, 69, 220, 221 non-CO2, 12, 13, 96, 105–107, 115–116, 147, 1.SM.6 mitigation options, 12, 14, 460–461, 4.SM.4.2.1 impacts and risks at 1.5°C, vs. 2°C, 8, 9, 179, past emissions, global warming and, 51, 64–65, 65 renewable energy, 14, 15, 96, 111, 131, 132–133, 247, 256–257 peak, 95, 115, 129 316, 324 irreversible impacts, 8 peak, timing of, 115, 126–127, 129 solar energy, 96 marine, 179, 221–230, 248 reductions, 13, 15, 18, 95, 463 synergies with Sustainable Development Goals, 19 mitigation and, 315 reductions, behaviour change and, 317, 363 transformation, 129–144, 316, 463 observed changes, 5 reductions, near-term, 17, 96, 124, 126–129, 128 transitions in 1.5°C pathways*, 15, 96–97, 130, terrestrial, 221 reductions, rate of, 51 315, 316, 324–327, 374–375, 4.SM.4.2.1, Education (climate education), 22, 317, 385, 456 reductions, remaining carbon budget and, 96 4.SM.4.3.1 Effective climate sensitivity. See Climate sensitivity reductions, technologies and, 369–370 transitions, speed and scale of, 320, 320 Effective radiative forcing. See Radiative forcing reductions, timing of, 5, 6, 18, 61, 95, 96, 107, water and, 326, 384, 464–466 El Niño-Southern Oscillation (ENSO)*, 58, 201, 257 114, 116–118 water-energy-food (WEF) nexus, 386–387 deforestation and, 263 sectoral pathways, 137 Energy supply and demand, 15, 17, 96–97, La Niña events, 235 short-lived climate forcers, 64, 66–68, 118, 120, 316 129–136, 316, 460–461, 466 response in Guatemala, 356 timescales and, 5, 61, 64–66 in 1.5°C warmer worlds, 161, 162, 316 Electric vehicle (EV)*, 316, 332–333, 333 timing of, 95, 117, 119 access to energy, 464 costs of, 325 warming commitment from past emissions, 64–66, air conditioning, 243 Electricity generation/use, 15, 97, 133–134, 135, 65, 1.SM.5 batteries, 325 138, 243–244, 326 zero emissions commitment, 64–65, 65 bioenergy*, 12, 17, 96, 111–112, 124, 324–325 carbon intensity* of, 97 Enabling conditions*, 18–19, 52, 148–150, 317–318, carbon intensity of, 129–130, 130, 461 decarbonization, 95 338, 352, 386, 474–475, 4.SM.2 demand reductions, 95, 137 disruptions of, 326 adaptation options*, 4.SM.2 disruptions and vulnerabilities, 326 enabling conditions, 387 enabling behavioural and lifestyle changes, emissions pathways, 12, 14, 15, 95 energy storage, 325–326 362–369 energy storage, 316, 325–326 606 Index Index evolution of primary energy contributions, 130–132, heavy precipitation, 255 Floods*, 11, 182, 201–203, 211, 214–215, 131, 132–134 See also Climate extreme 3.SM.3.1.1.2 final energy demand, 137, 138 Extremes. See Climate extreme; and specific topics, coastal, 181, 231, 235, 249, 252, 252, 3.SM.3.3.3 fossil fuels, 96–97 e.g., precipitation damage from, 214, 215 grid flexibility resources (GFR), 325 Danube River Protection Convention, 356 low-demand scenarios, 110, 111, 448 F fluvial, 201–203, 214, 247, 251–252, 252, mitigation options, 460–461 3.SM.3.3.4 primary energy supply, 96–97, 130–132, 131, Fairness*, 449, 469, 479 management in Rotterdam, The Netherlands, 342 132–133 nation-level fair shares, 470 numbers of people at risk, 452 smart grids, 316 FAQs. See Frequently Asked Questions observed changes, 201, 211 in SSPs, 109–110, 110 Farmer managed natural regeneration (FMNR), 459 Philippines, flood measures, 368 sustainable development goals Feasibility*, 18–19, 52, 56, 71–72, 380–386, 381, projected changes, 179, 201–203, 202, 211, 214, (SDGs) and, 447–448 392–393, 393 3.SM.3.1.1.2 synergies and trade-offs, 19, 20–21, 448 adaptation options*, 381, 384–386, 385, risks, with 1.5°C warming, compared with 2°C, 7, transformations in, 129–136, 130–135 4.SM.4.3.1-4.SM.4.3.5 178, 179, 181, 201–203, 202, 214–215, 247, urban, 331 assessment of, 71–72, 380, 381, 382–383, 4.SM.4.1 251–252, 252 See also Electricity generation/use definition, 52 sea level rise and, 8 Enhanced weathering*, 17, 112, 268, 269, 270, dimensions of, 71–72, 380, 381, 392 Fluorinated gases, 118, 120 345–346, 462–463 enabling conditions*, 18–19, 52, 56 Food, Table 3.SM.12 costs, 316, 345 mitigation options*, 381, 381, 382–383, GHG-intensive foods, 97, 147 side effects, 345–346 4.SM.4.2.1-4.SM.4.2.5 healthy diets and choices, 19, 97, 147, 180, 462 Equality*, 448–449, 451–453 Feedback. See Climate feedbacks land use for, 97, 145 in 1.5°C warmer worlds*, 451–453 Fiji, freshwater resources, 368 plant-based proteins, 112 inequality, 456 Finance, 21–22, 23, 148–149, 317, 361–362, 372–380, prices, 447, 462, 464 inequality, reducing, 18–23, 445–538 474 quality/nutrition, 327, Table 3.SM.12 Equilibrium climate sensitivity. access to, 21, 23, 155, 317, 456 water-energy-food (WEF) nexus, 386–387 See Climate sensitivity adaptation financing, 21–22, 379, 456 Food demand Equity*, 18, 23, 51, 54–55, 448–449, 456, 469–470, challenges of, 372–375, 373–374, 379 reducing, 464, 466 479 climate-friendly products, 378 in SSPs, 110, 110, 111 in 1.5°C warmer worlds*, 451–453 de-risking, 317, 378–379 Food production systems, 178, 236–240, 250, 252, burden sharing*, 380, 470 global and national systems for, 317–318, 380 327–329, 453, 464, Table 3.SM.5 climate-resilient development Green Climate Fund, 74, 379 climate-smart food production, 239 pathways*, 22, 448–449, 469–470 green instruments, 378, 474 efficiency of, 315–316, 464 conditions for achieving, 474–475 innovative, 315, 380 genome modification, 329 disproportionate impacts and, 51 knowledge gaps, 391 land use and, 327–329 fairness* and, 449, 469, 479 low-emission assets, 317 mixed crop-livestock production, 315, 328 gender equity*, 23 mobilization of, 19, 456 projected impacts, 179–180, 236–240, 250 intergenerational equity*, 55 multilateral and national development banks, 317 technological innovations, 316, 329 international equity, 55 new forms of, 374, 380, 474 tipping points*, 263, 264 justice and, 22, 55, 456, 470 policy instruments and, 317, 372–380 See also Agriculture; Crop yields mitigation efforts and, 18, 55 private sector, 21, 22 Food security*, 180, 182, 237, 238–240, 250 national equity, 55, 470 public-private partnerships, 317, 474 decline in, 53 policies and, 22, 456 public sector, 21, 317 enhancing, 315–316 procedural equity*, 55, 73 redirection of, 317, 374, 378 food insecurity, 447 research gaps, 475–476 See also Investments mitigation pathways and, 464 responsibility–capacity–need assessment, 470 Financial institutions*, 361–362 projected impacts, 179–180, 239, 250, Table 3.SM.5 in social-ecological systems*, 338–341 Fires, 244, 259 risks to, 238–239 trade-offs, 19 forest fires, 8, 247 strategies for improving, 239–240 Ethics*, 51, 52 tundra, 262 Food shortages, 9 European Union, Covenant of Mayors, 354, 355 Fisheries, 8, 9, 11, 237–238, 248, 452 Food wastage*, 316, 328–329, 462 Evidence*, 451 adaptation measures, 238 Forcing. See Radiative forcing Exposure* fin fish, 180, 226–227, 237–238, 3.SM.3.2.7, Forest fires, 8, 247 factors influencing, 53 3.SM.3.3.10, 3.SM.3.2.12, 3.SM.3.2.13 Forests*, 220, 316, 329–330 numbers of people exposed, 178, 246, 453 foodwebs and, 226–227, 248 agroforestry, 328, 384 See also Hazard; Risk; Vulnerability hypoxia and, 224 Amazon tropical forest, 221, 263, 340 Extinction, 8, 179, 218, 256–257 livelihoods, 452 Australian rainforest, 254 commitment to, 218 management, 227 boreal, 8, 263, 264 Extratropical cyclone*, 203–204, 211 productivity change, 225, 249, 258 as carbon sinks, 340 See also Tropical cyclone projected impacts, 8, 9, 11, 178, 222, 228, 248, 257 CDR options and, 316 Extreme weather events*, 182, 255 range shifts, 222, 248 ecosystem restoration, 329–330 floods and droughts, 214–215, 255 restoration of, 330 emissions, 14 frequency of, 223 risks, 180, 228, 237–238, 251, 252, 257 impacts, 220 607 Index Index land area for, 16, 97 G 1.SM.5 land-use change, 146 current level of, 4, 51, 53, 76, 106, 177, 1.SM.1 rainforests, 254, 263, 264 Gender equity*, 23, 452 definition, 24, 51, 56 REDD+, 329–330 General circulation model (GCM). See Climate models with emissions continuing at present rate, 4 responsible sourcing of products, 462 Genome modification techniques, 329 geophysical warming commitment, 64–66, 65 risks, 8, 220–221 Geophysical relationships, 101–107 human experience of present-day, 53, 1.SM.1 tipping points*, 263, 264 climate and Earth-system feedbacks, 103–104 human-induced, 4–5, 51, 53, 53, 54, 59, 81, 82, See also Afforestation; Deforestation; Reforestation geophysical uncertainties, 96, 101–104 186–187, 282, 1.SM.2, 1.SM.6 Fossil fuels* knowledge gaps, 157–158 level in 2017, 51, 59, 81 in 1.5°C pathways*, 14–15, 15, 96–97 non-CO climate forcers, 101–103, 103 maximum temperature reached, 52 combined with CCS, 97, 135 Geophysical warming commitment, 64–66, 65 observed, 4, 51, 53, 53, 58–59, 189–190, countries/economies dependent on, 448, Glaciers*, 206 1.SM.1, 1.SM.2, 1.SM.3, 1.SM.6 461, 462 Global climate model (GCM). See Climate models past emissions and, 51, 64–65, 65, 72 energy sector use, 15, 96–97, 131, 131, Global financial systems, 317–318 peak in, 5, 65, 96, 101, 177, 277, 278 132–133, 138 Globalisation, 319 pre-industrial* reference period, greenhouse gas emissions, 53, 114 Global mean surface temperature (GMST)*, 51, 56, 57–59, 184 market preference, shifting, 317 56–57, 57, 177, 186, 274 projections, 4, 81, 82, 95, 187–188, 188 reducing investments in, 378 1.5°C rise, factors in, 4, 274 reference periods, 56–59, 184 Framing and context, 49–92 anomalies*, 183, 210 regional/seasonal variations in, 4, 59, 60, 81 assessment and methodologies, 75–76 definition, 24 temperatures used for definition, 51, 106 confidence, uncertainty and risk, 77 measurement of, 12 timescales and persistence, 5 feasibility, 71–72 observed, 4, 6, 186 total warming, 59, 61 framing asymmetries, 55 past emissions and, 51 See also Global mean surface temperature; global response, 70–75 Global mean surface air temperature (GSAT)*, Temperature impacts, 69–70 12, 56 Global warming of 1.5°C, 4–6, 56–64, 187, 274 knowledge base, 53–56, 75–76 Global response, strengthening, 18–23, 70–75, 1.5°C pathways*, 12–17, 51, 93–174 sustainable development, 73–75 313–443 already experienced in some regions transformation and transitions, 73 1.5°C-consistent pathways, implications of, and seasons, 4, 51, 59, 68, 81, 452 understanding 1.5°C, 56–64 320–321, 320, 448 closeness to (FAQ), 81, 82 Frequently Asked Questions (FAQs) accelerating the response, 319–320 context of sustainable development How Close are we to 1.5°C?, 81, 82 adaptation options, 321, 336–337, 338 and poverty eradication, 18–23 What are Carbon Dioxide Removal and Negative change, far-reaching and rapid, 352–380, 392 framing and context, 4–6, 49–92 Emissions?, 394, 395 change, historical rates of, 322 future emissions and, 6, 13 What are the Connections between Sustainable cooperation, 22, 23 impacts and risks, compared with 2°C, Development and Limiting Global Warming to enabling change, 21–22, 315–318 5, 7–10, 11, 51, 175–311, 261 1.5°C above Pre-Industrial Levels?, feasibility assessments, 380–386, 381, 382–383, not considered ‘safe’, 447, 455 477–478, 478 385 projected climatic changes, 7–10, 186–188 What are the Impacts of 1.5°C and 2°C of finance and investments, 317, 321, 361–362, projected timeline for reaching, Warming?, 282–283, 283 372–380 4, 95–96, Table 3.SM.7 What are the Pathways to Achieving Poverty governance and policies, 23, 71, 315, 316, 317, Reasons for concern (RFCs)*, 10, 11, 181 Reduction and Reducing Inequalities while 321, 352–355 reference period, 56–59, 184 Reaching a 1.5°C World?, 479–480, 480 implementation, 23, 70, 71, 315, 317, 319, returning to, after overshoot, 5, 17, 61, 96 What do Energy Supply and Demand have to 320–323, 352–380 stabilization responses/scenarios, 147, 158, 182, do with Limiting Warming to 1.5°C?, 161, 162 implementing adaptation, 383–386, 385 184–185 What Kind of Pathways Limit Warming to 1.5°C implementing mitigation, 381–383 strengthening the global response, 18–23, 70–75, and are we on Track?, 159, 160 integration and enabling transformation, 380–387 313–443 What Transitions Could Enable Limiting Global knowledge gaps, 318, 387, 388–391 synergies and trade-offs, 19 Warming to 1.5°C?, 392–393, 393 levels of ambition, raising, 315 temperature range for, 51, 187, 188, 275 Why are we Talking about 1.5°C?, 78, 80 monitoring and evaluation (M&E)*, 386 See also 1.5°C warmer worlds* Why is Adaptation Important in a 1.5°C-Warmer policy instruments and finance, 372–380 Global warming of 2°C, 100 World?, 396–397, 397 response options, 19–21, 70–71, 316–317 emissions and, 116 Freshwater systems, 182, 213–216, 221, 247 sustainable development and, 18, 22, 316, 321 impacts and risks, compared with 1.5°C, 5, 7–10, adaptation initiatives, 368 synergies and trade-offs, 316, 386–387 11, 175–311, 261 extreme events, 214–215 system transitions, and rates of change, 322–323 OECD scenario for, 373 freshwater stress, 181 systemic changes, 323–349 Reasons for concern (RFCs)*, 10, 11 knowledge gaps, 272 transformation and transitions, 70, 73, 315, regions with high risks, 247–250 water temperature, 214 380–387 runoff and floods, 178, 211 See also Water resources transitions, speed and scale of, 317, 320, 320 Global warming of 3°C, 18, 261 Fuel switch, 460–461, 481–506 Global Temperature-change Potential (GTP), rainforests and, 263 Fybnos and succulent Karoo biomes, 260, 261 66–68 Global Warming Potentials (GWPs), 66–68 Global warming*, 4–6 Governance*, 19, 71, 316, 317, 352–355 commitment to continued warming, 64–66, 65, adaptive governance*, 315 608 Index Index challenges in 1.5°C pathways, 95 coral reefs, 226, 229 Hydrofluorocarbons (HFCs), 12, 96, 118, 341–342, Covenant of Mayors initiative, 354, 355 Heatwaves*, 9, 263, 264 342 governance capacity*, 71 in cities, 242 radiative forcing from, 342 governance framework, 317, 359 deadly, 263, 264 Hydrogen, 15, 315, 335, 336 inclusive, 475 extreme, 177 Hydrological cycle*, 191–196 international, 352–354, 474 marine, 177 Hydropower, 201, 214, 243, 466 knowledge gaps, 390 numbers of people exposed, 178 linkages across sectors, 71 observed changes, 177 I local and regional, 316, 354, 355 projected changes, 177–178 multilevel governance*, 19, 23, 317, 352–355, tipping points*, 263, 264 Ice sheets* 355, 356, 384, 386, 474–475 Holocene*, 53 albedo and, 257 national, 316, 353, 361 Holocene Thermal Maximum (HTM), 208 Antarctic ice sheet, 7, 178, 208–209, 257, 258, partnerships among actors, 23 Hotspots, 182, 258–260, 261 271, 282 sub-national, 354 drought*, 199, 200 Greenland ice sheet, 7, 178, 206, 208–209, 257, water-energy-food (WEF) nexus, 386–387 precipitation, 193, 194 271, 282 See also Policies temperature, 190–191, 193 marine ice sheet instability (MISI), 257, 258 Green bonds, 378 Human behaviour*, 362–369 sea level rise and, 7, 178, 206, 208, 257, 271 Green Climate Fund, 74, 379 adaptation behaviour*, 363 thresholds, 257 Green economy, 470–471 adaptation options*, 457 time frame for loss of, 257 Green infrastructure*, 10, 316, 334, 334, 384, 385 behavioural change*, 19, 21, 22, 97, 315, 317, 461 tipping points, 282 investment in, 316 behavioural change, enabling, 362–369 (Climate change) Impact assessment*, 76, 185–186 Greenhouse gas(es) (GHGs)*, behavioural change, knowledge gaps, 390–391 Impacts*, 7–10, 68–70, 175–311 long-lived, 64–66, 66–68, 116–118 dietary choices, 19, 97, 147, 180, 316, 462 in 1.5°C and 2°C warmer worlds*, 7–10, short-lived, 64, 66–68, 316 energy efficiency* and, 460–461 177–179, 182, 319 See also Carbon dioxide; Methane; Nitrous oxide; factors affecting, 364–365 in 1.5°C pathways, vs. overshoot pathways, 51, Ozone habits, heuristics, and biases, 365, 461 61, 62 Greenhouse gas emissions, 14–15, 18 knowledge and, 364 attribution for, 69, 213 aggregate, 115 mitigation behaviour*, 362, 363 avoided, 18, 68, 183, 253–265, 447, 452–453, benchmark values, 115 motivation and, 364–365 453, 475 cumulative emissions*, 6, 12, 62 rebound effect, 460 climate extremes and, 7, 177–178, 182 drivers of, 53 See also Values coastal and low-lying areas, 231–234, Table 3.SM.4 global, in 2030, 12, 13 Human health, 9, 178, 182, 240–241, 250, 385 definitions, 24, 68 reductions in, 6, 12, 13, 14–15, 95 adaptation limits*, 455 direct vs. indirect, 69 reporting of, 66 air quality and, 241, 250, 464, Table 3.SM.9 disproportionate, 11, 51, 447, 452 timing of reductions, 6, 13, 95 benefits of emissions reductions, 12 distribution of, 10, 11, 18, 181, 255–256 See also Emissions co-benefits, 157 drivers of, 69 Greenhouse gas removal*. See Carbon dioxide cold-related mortality, 241 economic sectors and services, 180–181, 182, removal (CDR) heat-related morbidity and mortality, 9, 11, 180, 242–244, 250, 256 Greenland ice sheet, 7, 178, 206, 208–209, 257, 240–241, 250, 252, 252, 263, 264, 3.SM.3.3.1 ecosystems, 178, 179, 182 271, 282 impacts and risks at 1.5°C, vs. 2°C, 9, 180, 182, emission pathways* and, 51, 282 Gross domestic product (GDP)*, 158, 243, 256, 240–241, 250, 252, 453 FAQ on, 282–283, 283 258, 265, 373 occupational health, 241, 250 food systems, 179–180, 182, 236–240, 250, Gross fixed capital formation (GFCF)*, 317, 373 population health, 337, 338, 385, 457 Table 3.SM.5 Gross world product (GWP), 256 risks, 180, 240–241, 252 global aggregate, 10, 11, 181, 182, 256–257 Groundwater, 15, 3.SM.3.1.1.3 temperature-related risks, Table 3.SM.8 global and regional climate changes, 186–212, coastal, 181 tipping points*, 263, 264 210–212 Guatemala trade-offs, 19 human health, 9, 180, 182, 240–241, 250, Indigenous Table for Climate Change, 360 urban areas, 180 252, 453 Maya watershed meteorological forecasts, 360 vector-borne diseases, 9, 180, 241, Table 3.SM.10 impact assessment*, 76, 185–186 response to drought and El-Niño, 356 Human-induced warming, 4, 51, 59, 81, 82, impact cascades, 69, 245, 452 Gulf Cooperative Council (GCC) countries, 462 186–187, 188, 282, 1.SM.2, 1.SM.6 irreversible, 5, 61, 177, 251, 252, 254 equal to observed warming, 51, 59 knowledge gaps, 272–273 H rate of, 66 land use, 179–180 Human population, 51, 319 livelihoods, poverty, and migration, 244–245, 447 Happiness index (Bhutan), 387 current, 319 marine ecosystems, 8–9, 179, 221–230 Hazard*, 68, 186–212, 210–212 displacement/migrations of, 180, 181, 244–245, non-linearity, 69–70 collocated and/or concomitant, 188 337, 338, 385 observed, 5, 53, 212–253 See also Disaster; Risk; Vulnerability growth of, 95, 319 ocean, 5, 8–9, 178, 179, 180, 182, 221–230, 228, Health. See Human health in regions where 1.5°C already exceeded, 51 248–249, 3.SM.3.2.1-3.SM.3.2.13 Heat-related morbidity and mortality, 9, 11, in SSPs, 109, 110 projected risks, 7–10, 212–253 180, 240–241, 250, 252, 252, 263, 264, 3.SM.3.3.1 Human rights*, 55, 450, 460, 469–470, 475 regional, 9, 68, 180–181, 182, 189–196 Heat stress, 452 Human security*, 9 sea level rise, 7–8, 181, 182, 206–207, 212 609 Index Index small islands and coastal areas, 181, 182 Infrastructure Investments, 21, 95–96, 149, 153–155, 316, summary of, 182–183, 182, 247–250, 251–253 adaptation options*, 384–386, 385, 4.SM.4.3.3 372–380 terrestrial ecosystems, 8, 11, 179, 216–221, 252, climate-resilient, 386 decarbonization*, 378 Table 3.SM.2 coastal, 181, 226, 231, 235, 249 energy-related, 16, 95–96, 153, 155 time-integrated, 61, 62 decommissioning of existing, 374 green investment, 474 timescales of, 61, 62 feasibility of mitigation options, 382 incentives, 317 uncertainties*, 69 floods and, 181 investment needs, 373–374 uncertainty propagation, 3.SM.1.3 green infrastructure*, 10, 316, 334, 334, 384, 385 knowledge gaps, 158 urban areas, 241–242 investments in, 21, 333, 373–374, 374 low-emission, 154, 317, 378 water resources, 179, 3.SM.3.1.1.2-3.SM.3.1.1.4 knowledge gaps, 388–389 mitigation, 21, 95–96, 466 Implementation. See Global response, strengthening lock-in of carbon-emitting, 18, 126 policy instruments and, 317 Inclusion/inclusive processes, 331, 333, 353, 381, low-emission, 317, 374 speed and scale of change, 321 449, 475 mitigation options*, 4.SM.4.2.3 upscaling of, 15, 317 cultural considerations, 384 sea level rise and, 8, 231, 249 world investment, 317, 373 decision-making, 456 transitions in, 15–16, 4.SM.4.3.3 See also Finance Incremental adaptation. See Adaptation urban, 331, 333 IPCC Fifth Assessment Report (AR5), 51, 81 India, technology and renewables pathways, 471 Insects, 254–255 IPCC Special Report on 1.5°C (SR1.5), 4, 74, 79 Indigenous knowledge*, 22, 315, 337, 338, 339, phenology, 216, 218 storyline, 77–78, 78 385, 456, 480 pollination by, 216, 218, 255 timeline of, 80 community adaptation and, 360 range loss, 254–255, 256–257 Iron fertilization. See Ocean fertilization in Guatemala, 360 species loss, 179, 218 Irreversibility*, 5, 61, 177, 251, 252, 254, 262, 277 Indigenous Table for Climate Change (Guatemala), Institutional capacity*, 19, 71, 359–362 temperature overshoot and, 8, 61, 179 360 cooperative institutions and social safety nets, 362 See also Tipping points in Pacific Islands and small island developing enhancing, 359–362, 384 Italy, Province of Foggia, multilevel governance states, 360 monitoring, reporting, and review, 361 in, 355 in Tanzania, 360 policy design and implementation, 359–360 Indigenous peoples, 23, 447 Institutions*, 359–362, 474–475 J in Arctic, 9, 339 financial, 361–362 cultural beliefs, 364 institutional capacities, 359–362 Jamaica, 339–340 land tenure, 462 knowledge gaps, 390 Justice*, 448–449, 456, 469 Maya (in Guatemala), 360 monitoring, reporting, and review, 361 distributive justice*, 55 risks and impacts, 9 reform: Manizales, Colombia, 361 justice-centered pathways, 470 Industry sector, 334–336, 4.SM.4.3.4 Integrated assessment*, 95 procedural justice*, 55 adaptation options*, 385, 386 Integrated assessment models (IAMs)*, 99, social justice*, 22, 448–449 bio-based feedstocks, 335–336, 335 100–101, 108–109, 136–137 See also Equity; Ethics; Fairness; Human rights carbon capture and storage (CCS), 335, 336 assumptions, 2.SM.1.2.2, 2.SM.1.2.3 changes in structure of, 375 bioenergy and BECCS deployment in, 124, 268 K decarbonization, 140 CDR and, 268–269 electrification and hydrogen, 335, 336, 460 global economic impacts, 256 Kampala, Uganda, Climate Change Action emissions, 15, 114, 140, 334 knowledge gaps, 158 Strategy, 340 energy efficiency, 315, 335, 335, 460 land use and bioenergy modelling, 2.SM.1.2.4 Kigali Amendment, 118 energy-intensive industry, 334 multiple IAMs, 463–464 Kiribati, adaptation in, 368, 471 feasibility of mitigation options, 383 scope, use and limitations, 2.SM.1.2.1 Knowledge gaps, 157–158, 388–391 final energy demand and use, 138–140, 139 Integrated assessment model (IAM) scenario impacts and risks, 272–273 knowledge gaps, 389 database See also specific topics mitigation options*, 335, 4.SM.4.2.4 configuration, 2.SM.1.3.1 Knowledge sources, 52, 53–56, 75–76 substitution and circularity, 335, 335, 460 data collected, 2.SM.1.3.4 grey literature, 76, 451 technological innovations, 370, 460 modelling Framework Reference Cards, 2.SM.2 indigenous knowledge*, 22, 315, 337, 338, 339, transitions in, 15, 334–336, 460, 4.SM.4.3.4 Part 2 385, 456, 480 transitions, speed and scale of, 320, 320 overview of mitigation measures, 2.SM.1.2.6 local knowledge*, 22, 339, 457 Inequality overview of scenarios, 2.SM.1.3.2 scientific literature, 75, 451 in 1.5°C warmer world*, 447 overview of studies, 2.SM.1.3.3 Krill, 227, 228, 3.SM.3.2.6 adaptation pathways* and, 458–459 scenario classification, 2.SM.1.4 Kyoto Protocol*, 80, 353 increased, 53, 319 summary of models, Table 2.SM.7 Kyoto GHG-emissions, 14, 115–116, 117, 119, 126 persistent, 471 Interconnectivity, 52, 54, 319 reducing, 18–23, 72, 445–538, 456, 475 International agreements, 70, 317 L research gaps, 475–476 International cooperation, 22, 23, 95 See also Equality Mekong River Commission, 240 Land management, 17, 19, 180 Information and communication technology International governance, 352–354, 474 carbon dioxide removal and, 121, 180 (ICT)*, 316, 319 Internet of Things (IoT)*, 331 Land surface air temperature*, 56 Information flow and sharing, 377–378, 456, 457 Invasive species, 8, 9, 223 Land use*, 144–148, 180, 327–329 adaptation options*, 384, 385, 4.SM.4.3.2 610 Index Index for agriculture and food, 16, 97, 112, 146, 327–329 Lock-in*, 18, 126, 129 socio-economic challenges to, 110 carbon dioxide removal (CDR)* and, 125, 126, London, U.K. sustainable development and, 12, 19–21, 97, 265–266, 268–270, 343 adaptation and disaster risk management, 458 156–157, 447–448, 459–466, 465, 481–509 climate-resilient, 333 car use/policies, 366 synergies and trade-offs, 18–21, 20–21, 72, 97, feasibility of mitigation options, 382 Long-lived climate forcers (LLCF)*, 66–68, 157, 316, 386–387, 391, 459–463, 465, governance and, 17 116–118, 117 4.SM.4.5.1 intensification of, 16 time scales, 64–66 synergies with adaptation, 386–387, 475, knowledge gaps, 388 Loss and Damage*, 454–456 4.SM.4.5.1, 4.SM.5.2 mitigation options, 148, 265–266, 382, 462–463, Low-carbon pathways, 471–472 time frames for, 277, 278, 279–281 4.SM.4.2.2 See also 1.5°C pathways; Pathways mitigation potential, 315 M Mitigation behaviour. See Human behaviour modelling, 2.SM.1.2.4 Mitigation options*, 19–21, 316–317, 319, 323, planning: Manizales, Columbia example, 361 Maharashtra, India, water resources, 368 324–347, 463, 481–509 risks of carbon release, 221 Maladaptive actions (Maladaptation)*, 19, 1.5°C pathways*, 100, 110–112, 316–317, 465 sustainability of, 16, 97 386, 396 CDR, 4.SM.4.2.5 synergies and trade-offs, 19, 20–21 Malaria, 9, 180, 241, 452 emissions reduction with, 12, 13, 14–15 transitions in, 16, 17, 96, 97, 144–148, 315, Mangroves, 225, 226, 228, 228, 248, 252, 462, enabling conditions, 381–383 327–329, 4.SM.4.3.2 3.SM.3.2.1, 3.SM.3.3.8 energy supply and demand, 460–462, 4.SM.4.2.1 urban, 316, 333 replanting, 330, 457 feasibility assessment, 381, 381, 382–383, Land-use change (LUC)*, 112, 126, 144–148, Manizales, Colombia, 361 4.SM.4.2.1-4.SM.4.2.5 179, 180 Marginal abatement costs, 16, 95, 150, 375 industrial system, 4.SM.4.2.4 in agricultural sector, 98, 144–148 Marine ecosystems. See Ocean ecosystems land-based, 16, 462–463, 4.SM.4.2.2 bioenergy production and, 69 Mayan K’iché population in Guatemala, 360 mitigation–SDG table, 481–509 biophysical feedbacks, 266–267 Mediterranean region, 259, 261 overview, 2.SM.1.2.6 CDR and, 268–269 droughts, 200–201 SDGs and, 19–21, 20–21, 448 overview of, 145 threatened systems, 254 synergies and trade-offs, 459–463, 463, 465, pace of, 145, 146 Mekong River basin, 239–240 4.SM.4.5.1 risks in mitigation pathways, 69, 97, 265–266 Methane (CH4)*, 268, 316, 341, 342 urban and infrastructure, 4.SM.4.2.3 in SSPs, 145 AFOLU sector, 118, 147, 147 Mitigation pathways*, 93–174, 265–271 Large scale singular events, 10, 11, 181, 254, agricultural, 96 1.5°C pathways*, 12–17, 13, 14–15, 60–61, 98, 257–258 emissions, 13, 118, 120 101, 102, 108–129, 110, 2.SM.1.5 Last Glacial Maximum (LGM), 208 emissions, evolution of, 96 2°C pathways, 96, 100, 101, 102 Lifestyles, 315 emissions reduction, 12, 95, 102, 157, 268, 316 adaptive mitigation pathway, 60–61 choices, 97, 180 mitigation potential, 118 carbon dioxide removal (CDR) in, 118–125, 180 consumption and, 53, 56, 95, 97 release from permafrost*, 12, 104 challenges, opportunities, and emissions reduction through, 317 release from wetlands, 12 co-impacts, 147–157 lifestyle change, enabling, 362–369 zero emissions commitment (ZEC), 65 emissions and, 12, 14–15 lifestyle change, knowledge gaps, 390–391 Migration*, 180, 181, 232, 244–245, 337, 338, 385 four model pathways, 12, 14–15, 61, 62 low energy demand, 97 as adaptation, 457 geophysical characteristics, 101–104 low resource use, 97 (internal) displacement*, 245 groups/classification, 61, 62, 113–114, 113 mitigation and adaptation behaviour, 362–363 sea level change* and, 232 land-use change, 265–266 in SSPs, 110 Millennium Development Goals (MDGs)*, 74, overview, 108–129, 129 sustainable, 276 450, 477 prospective, 60, 63 See also Food; Human behaviour Mitigation*, 19–21, 70, 93–174 scenarios in, 98–100, 100, 277, 279–281 Likelihood*, 77, 182 in 1.5°C pathways*, 12–17, 51–52, 93–174, 465 sustainable development and, 463–472, 465, Limpopo Watercourse Commission, 356 adaptation and, 19, 386–387, 4.SM.4.5.1 2.SM.1.5 Livelihoods*, 73, 182, 244 classification of, 99–100, 100 synergies and trade-offs, 465 agricultural, 55, 315, 447 costs, 16, 22, 258, 264, 316 transformations, 129–157, 466 coastal, 9, 222, 226, 249, 447, 452, 455 decisions after 2030, 56 See also 1.5°C pathways; Pathways impacts and risks of 1.5°C warmer worlds*, 452 definition, 70 Mitigation potential, 118, 315, 363 poverty and, 244 demand-side measures*, 97 Mitigation scenarios*. See Mitigation pathways security, promoting, 456–457 equity considerations, 55 Models. See Climate models; Integrated assessment Livestock, 9, 180, 264, 327–328 feasibility, 15, 380, 381 models (IAMs) animal feed, 112 global response, strengthening, 19–21, 70–75, Monitoring and evaluation (M&E)*, 386 emissions, 147, 327 313–443 Monitoring, reporting, and review institutions, land use, 97 implementing, 381–383 361 mixed crop-livestock production, 315, 328 integrated mitigation studies, 95 Monsoon, 194, 262–263, 264 production, 237 investments, 21, 95–96, 466 Montreal Protocol, 118, 353 in the tropics and subtropics, 263, 264 knowledge gaps, 388–391 Mosquitoes, 241 Local communities, 23 non-CO2 mitigation, 95, 96, 105–106, 108, Motivation*, 364–365 Local knowledge*, 22, 339, 457 115–116, 120, 265, 268 Mountain ecosystems, 254 Local participation, 456 risks and risk reduction, 5, 179, 448 611 Index Index N heatwaves*, 177 aim and context, 54–55, 66, 74, 77, 79, 359 hypoxia and dead zones, 179, 210, 224, 248 equity principle, 51, 54, 479 Narratives*, 52, 109 impacts and risks at 1.5°C, vs. 2°C, 5, 8–9, 178, goal of adaptation, 359 Nationally Determined Contributions (NDCs)*, 179, 180, 182, 221–230, 228, 248–249, goal of limiting warming, 51 56, 95, 126–129, 127, 128, 149, 159, 357–359 3.SM.3.2.1-3.SM.3.2.13 time horizon for, 74 adaptation and, 359 irreversible impacts, 8 transparency framework, 361 consistency of, 357–359 knowledge gaps, 272–273 Pathway archetypes, 99–100, 100, 112–113, 113, 147 remaining carbon budget and, 113–114 productivity/fisheries, 8, 179, 249 cumulative CO2 emissions, 123 uncertainties and, 358 projected changes, 8–9 electricity generation, 135 Natural gas, 97 pteropods, 224, 226–227, 3.SM.3.2.4 land-use change (LUC)*, 126, 145 NDCs. See Nationally Determined Contributions Reasons for Concern, 3.SM.3., Table 3.SM.6 land use/footprint, 147 (NDCs) salinity, 209 primary energy contributions, 130–131, 131 Negative emissions*, 17, 51, 70, 118–121, 394, 395 Southern Ocean, 257–258 Pathways, 12–17, 49–64, 62–64, 93–174 474 storms, 222–223, 249 1.5°C pathways*, 12–17, 14–15, 52, 59–64, CDR, role in, 70, 114, 118 stratification, 222, 224, 248 93–174, 100, 160, 265–271, 274–276, 320, FAQ on, 394, 395 temperature, 8, 177, 204–205, 212, 222, 223–224, 1.SM.4, 1.SM.6 See also Net-zero emissions; 248 2°C pathways, 96, 100, 101, 102 Net-zero CO emissions thermal inertia/expansion of, 64–65, 107, 282 adaptation pathways*, 64, 70, 396, 458–4592 Net negative emissions*, 51, 96, 114, 116, 474 warming over, 4, 51 assumptions, 95, 109–112 Net-zero emissions*, 5, 24 See also Coastal communities; Coral reefs; bioenergy with carbon dioxide capture Net-zero CO emissions*, 12, 51, 95, 116 Fisheries; Sea level change and storage (BECCS)*, 17, 962 definition, 24 Ocean acidification (OA)*, 8, 209–210, 212, carbon dioxide removal (CDR)* in, 17, 21, 95, 96, measuring progress to, 66–68 223–224, 248, 282 111, 118–125, 180, 265–266 necessary to stabilize GMST, 116, 161 pH*, 212, 222, 223 classification of, 61, 62, 99–100, 100, 113–114, 113 timing of, 5, 12, 13, 61, 95, 107, 116, 119 reversal of, 5, 67 climate-resilient development pathways, 22, 52, New York, United States, adaptation initiatives, 340 risks from, 180, 223–224, 227 64, 73, 448–449, 450–451, 451, 468–472, Nitrogen fertilizer, 116 Ocean alkalinization, 17, 121, 345–346 475–476, 479–480, 480 Nitrous oxide (N O)*, 13, 66 Ocean chemistry, 209–210, 223–224 definitions of, 59–61, 63–642 agricultural, 96, 116–118, 147 carbonate chemistry, 178, 222, 223 emissions in, 12–17, 13, 14–15, 24, 95, 96 bioenergy and, 12 Ocean ecosystems, 8–9, 179, 221–230, 248 four categories/model pathways, 12, 14–15, emission increases, 96 blue carbon*, 330, 462 59–61, 62, 63, 265–271 emission reductions, 116–1118 critical thresholds, 179 geophysical characteristics, 101–104 Non-CO climate forcers, 96, 120, 341–342 ecosystem services, 227–229, 228 implications beyond end of century, 270–271, 2782 geographical variation in, 103 foodwebs, 226–227, 228, 248 net-zero CO2 emissions*, 12, 61, 66–68, 116 reductions in, 95 framework organisms, 225–226, 248 nexus approaches, 467 uncertainties, 101–103, 103, 106, 108 impacts, 8, 9, 178, 179, 221–230, 228, 248 no or limited overshoot, 12–17, 13, 14–15, 60–61, Non-CO emissions*, 12, 13, 96, 106, 115–116, ocean circulation and, 223, 248 62, 1002 265, 1.SM.6 species range shifts, 222, 248 non-CO2 mitigation, 265, 268 agricultural, 147, 147 Ocean fertilization*, 346, 462–463 overshoot pathways, 12, 14–15, 18, 24, 51, 60–61, reducing, 341 Organization for Economic Co-operation and 62, 100, 277 remaining carbon budget* and, 105–107, 108 Development (OECD), 373 overview, 108–129 Non-governmental organizations, 22 Overshoot*, 12, 14–15, 18, 51, 100, 179, 265 portfolio of measures, 12, 15 Non-overshoot pathways. See Overshoot; Pathways CDR and, 17, 95 prospective mitigation pathways, 60, 63 Nuclear energy, 14, 15, 325, 461 definition, 24 Representative Concentration Pathways (RCPs)*, 62 costs of, 325 emission reductions and, 13, 14–15, 18, 95, 116 scenarios used, 98–100, 100 role in primary energy supply, 130–131, 132, impacts of, 60 sector and system transitions, 14–15, 15–16 132–133 irreversible impacts, 61, 179 Shared Socio-economic Pathways (SSPs)*, 62–63, safety of, 325 low-OS vs. high-OS, 100 109–110, 110, 111, 448, 467–468 water use and, 466 magnitude and duration of, 179, 265 sustainable development and, 18–23, 98–101 no or limited overshoot, 12–17, 13, 14–15, 156–157, 156, 463–466, 465 O 60–61, 62 Sustainable Development Pathways, 64, 448–449, returning to 1.5°C after overshoot, 5, 17, 61, 96 466–472, 469, 479–480 Ocean(s), 8–9, 178, 182, 221–230, 248–249, risks of, 5, 177, 179, 277 temperature pathways, 59–61, 62, 63 3.SM.3.2, Table 3.SM.3 Ozone (O3)*, 268 time frame for, 95–96 adaptation options, 225 ozone-related mortality, 9, 180, 250 transformation pathways*, 70, 148–157 biodiversity, 8 precursors, 98, 118, 241 transformations, whole-system, 129–148 carbon sequestration, 17, 121, 178, 222, 227, 228, tropospheric, 236 transitions, speed and scale of, 15, 320, 320, 392 248, 257–258 uncertainty, 60, 98 carbon uptake, 17, 121, 178, 227, 228, 229, P used in this report, 59–61, 62, 63 3.SM.3.2.8 See also 1.5°C pathways; Climate-resilient circulation, 204–205, 212, 223, 248 Pacific decadal variability (PDV), 201 development pathways; Pathway archetypes; foodwebs, 226–227, 228, 248 Paris Agreement*, 4, 18, 77, 79, 353 Scenarios 612 Index Index Peatlands, 221 extremes, projected, 189, 197, 214–215 warming of >1.5°C already experienced, 4, 51, Permafrost*, 182, 262, 271 extremes, Sub-Saharan Africa, 197 68, 81, 452 beyond end of century, 271 heavy precipitation, 7, 177, 178, 194–196, 195, See also specific regions and countries feedbacks, 103–104, 262 211, 255 Regional climate change, 68, 177, 188–191 irreversible loss of carbon from, 262, 264 hotspots, 193, 194 drought*, 198–200, 198, 199, 200–201, 260 remaining carbon budget and, 12 monsoon, 194, 262–263, 264 runoff*, 201–202, 202, 211 thawing, 8, 12, 104, 220, 259, 262 observed changes, 177, 191–194, 211 temperatures on land, 188–191, 189, 192, 193, tipping points*, 262, 264 projected changes, 7, 178, 187–188, 188, 211 196, 197 pH*. See Ocean acidification regional, 191–196, 196, 3.SM.2.3.1, 3.SM.2.3.2 See also Regional impacts; Regional precipitation; Phenology, 216–218 runoff*, 201–203, 211 Regional temperatures Philippines, flood measures, 368 See also Droughts; Floods Regional impacts, 9, 68, 177–178, 182 Phytoplankton, 224, 226 Precursors*, 64, 65, 98, 102–103, 118 crop production, 9, 259, 263 Policies*, 19, 21–22, 71, 148–150, 317, 372–380 Pre-industrial*, 24 economic growth, 9, 180–181 acceptability* of, 22, 368–369 reference period, 51, 56, 57–59, 81, 184 variation in, 450 assumptions in 1.5° pathways, 112, 149 Procedural equity. See Equity Regional precipitation, 191–196, 196 car/transport pricing policies, 366 Pteropods, 224, 226–227, 3.SM.3.2.4 observed changes, 191–194, 3.SM.2.3.1 carbon pricing, 95, 317, 375–377, 460 Public acceptability, 22, 317, 368–369 projected changes, 193, 194–196, 195, 196 coordination and monitoring of, 449 3.SM.2.3.2 design and implementation, R Sub-Saharan Africa, 197 71, 321, 359–360, 460 Regional temperatures, 59, 60, 189–191, 196, 283 enabling climate finance, 372–380 Radiative forcing*, 59, 66–67, 188 observed changes, 189–190, 197, 1.SM.1, 1.SM.3, equity in, 22 aerosols*, 102–103 3.SM.2.2.1 innovation, 22 long-lived climate forcers (LLCF)*, 64–66, 66–68, projected changes, 189, 190–191, 192, 193, 196, integrated policy packages, 379–380, 383 116–118 197, 283, 3.SM.2.2 international agreements, 70, 317 natural forcings, 59, 66–67 Regulatory measures, 377–378 internationally cooperative, 22, 23, 95 non-CO2 forcers, 5, 6, 95, 96, 101–103, 103 Remaining carbon budget*, 12, 96, 104–107, investment, 22 recent trends, 1.SM.7 2.SM.1.1.2 knowledge gaps, 391 short-lived climate forcers (SLCF)*, 64, 66–68, 118, 1.5°C pathways*, 113–114 for low-emission transition, 372–375 120, 316 agricultural emissions and, 147 mobilization and integration of, 150, 317 uncertainties in, 96, 101–104, 103 assessment of, 104–107, 108 national, 316 Rainfall. See Precipitation CO2 and non-CO2 contributions, 105–107, 108 promoting climate action, 366–368 Reasons for concern (RFCs)*, 10, 11, 181, 182, definition, 24, 96 redistributive, 21, 448 251–258, 3.SM.3.3.1-3.SM.3.3.7 overshoot minimization and, 177 regulatory measures, 377–378 RFC1 (Unique and threatened systems), 10, 11, permafrost thawing and, 105, 107 for residual risk and loss and damage, 456 181, 251, 253–255, 254 uncertainties, 12, 96, 108 Sustainable Development Goals and, 448 RFC2 (Extreme weather events), 10, 11, 181, Remedial measures, 70–71 technology, 95, 148, 370–371 251–252, 254, 255 Renewable energy, 14, 15, 96, 111, 131, 132–133, See also Governance RFC3 (Distribution of impacts), 10, 11, 181, 316, 324 Population. See Human population 251–253, 254, 255–256 acceptability of, 368–369 Poverty*, 9, 53, 180, 182, 244 RFC4 (Global aggregate impacts), 10, 11, 181, deployment and scaling up, 461, 464–466 in 1.5°C warmer worlds*, 447, 451–453 251–254, 254, 256–257 feasibility of, 324 adaptation limits*, 455 RFC5 (Large scale singular events), 10, 11, 181, hybrid systems, 326 avoided impacts of 1.5°C vs. 2°C, 452–453 254, 257–258 water demands for, 464 climate change influence on, 55, 282, 447, 450, 452 Recycling, 335, 335, 460 Representative Concentration Pathways (RCPs)*, disproportionate impacts, 9, 51 Reducing Emissions from Deforestation and 62 energy poverty, 464 Forest Degradation (REDD+)*, 329–330 Resilience*, 316, 456 increase in, 180 Reference period*, 56–59, 81, 184 climate-resilient land use, 333 livelihoods* and, 244 periods shorter than 30 years, 51 cultural practices and, 360 multidimensional, 55, 450, 457 pre-industrial* temperatures, 51, 56, 57–59 See also Climate-resilient development pathways Multidimensional Poverty Index, 55 30-year period used, 51, 56 (CRDPs); Vulnerability numbers of people at risk, 447, 452 Reforestation*, 17, 70, 121, 265, 266, 270, 316, Risk(s)*, 5, 7–10, 177–181, 186–253, 210–212, ‘poverty scenario’ (SSP4), 452 343, 394, 395 247–250 projections for, 9, 10, 180 constraints, 316 confidence and likelihood qualifiers, 77, 182 Poverty eradication*, 18–23, 55, 72, 445–538 incentivization of, 147 de-risking policies and investments, 317, 378–379 conditions for achieving, 474–475 trade-offs, 269 definition, 24, 68 mitigation pathways and, 22 Region(s)*, 187 ecosystems*, 8–9, 11 research gaps, 475–476 climate differences in, 177–178 factors influencing, 5, 277 sustainable development and, 450 cooperation and governance, 353–354 with global warming of 1.5°C, compared with Power asymmetries, 449, 459, 462, 471, 475 with high risks at 2°C, 247–250 2°C, 5, 7–10, 11, 177–181, 186–253, 210–212, Prairie pothole ecosystems, 221, 254 hotspots, 258–260, 261 247–250, 453 Precipitation, 182, 191–196 regions used in this report, 187 human health, 180, 182, 250 extremes, observed, 191–192, 197 tipping points, 262–263, 264 interacting and cascading, 245, 452 613 Index Index key elements of, 251–253, 252 detection and attribution, 252 tourism, 229 multi-sector, 246 emissions and, 5, 7, 51 Vanuatu, planning for climate-resilient multiple and compound, 10, 178, 181 glaciers and, 206 development, 449, 471 to natural and human systems, 178, 179–181, global mean sea level rise, 178, 206–207, 212 Snow, 182 212–253, 247–250 ice sheets* and, 7, 178, 206, 208, 257, 271 Social cost of carbon (SCC)*, 150–151, 265, 375 Reasons for concern (RFCs)*, 10, 11, 181 impacts, 178, 181, 182 Social costs*, 67, 265, 317, 365, 375 residual, 454–456 migration due to, 232 Social-ecological systems*, 338–341 social-ecological systems, 338–341 multi-metre rise, 7, 178, 271 Social learning*, 449, 475 summary of, 247–250, 251–253 numbers of people at risk, 178, 231, 232, 234, 256 Social safety nets, 362, 385 of temperature overshoot, 5, 177, 179 past climate episodes and, 208 Societal choices, 98, 99 of unavoidable impacts, 455 projected, for 1.5°C, vs. 2°C, 7–8, 178, 206–207, Societal (social) transformation. uncertainty, 77 207, 212, 231–234, 234 See Transformation urban areas, 183 regional, 178, 207, 234 Socio-economic drivers, 109–110, 110 to vulnerable populations, 53 sea level rise, 7–8, 67, 178, 206–207, 225, Socio-economic scenario*, 62–63 Risk assessment*, 55, 183–186 231–234, 248, 249, 252 Soil carbon sequestration (SCS)*. See Carbon Risk management*, 336 small islands and, 7, 8, 232 sequestration adaptation* and, 5, 10 time-integrated impacts, 61, 62 Soil erosion, 216 Sendai Framework*, 70 UNESCO World Heritage sites at risk, 243 Soil moisture*, 190, 191, 196 See also Disaster risk management Sea surface temperature (SST)*, 204, 223–224, anomalies, 198, 199, 200 Risk sharing, 316, 336–337, 338, 385 248 Solar energy, 96, 131, 131, 132–133 Rotterdam, The Netherlands, adaptation strategy, in definition of 1.5°C, 51 water use and, 464–466 341 Seagrasses, 225–226, 228, 248, 3.SM.3.2.1 Solar radiation modification (SRM)*, 12–13, 70–71, Runoff*, 178, 201–203, 211 Seasonal warming, 4, 51, 59, 60, 68 347–349, 349–352 observed changes, 201, 211 Sendai Framework for Disaster Risk Reduction*, 70 carbon budget and, 351 projected changes, 201–203, 202, 211 Sequestration. See Carbon sequestration in context of 1.5°C pathways*, 349–352 Shared Socio-economic Pathways (SSPs)*, 62–63, feasibility, 347–349, 351–352 S 109–110, 110, 111, 448, 467–468 governance, 347–348 land-use change and, 145 impacts and ethical issues, 71, 317, 349, 351 Sahel, Africa, projected risks and impacts in, 180, policy assumptions, 149 knowledge gaps, 390 236, 259, 261, 262–263 SDGs and, 321, 448, 467–468 overview/main characteristics, 348 Scenarios*, 52, 62–64, 98–100, 276, 277, 279–281 Shipping, 333 risks of, 13, 347 1.5°C- and 2°C scenarios, 98–100, 100, 184 Short-lived climate forcers (SLCF)*, 64, 66–68, social acceptability of, 349 comparison of, 279–281 118, 120, 316, 341–342 sustainable development and, 351 database of, 99 co-benefits of reducing, 342, 342 timing and magnitude, 349–351 definition of, 63 emission reductions, 67, 316, 341–342 uncertainties and limitations, 12–13, 316–317 emission scenarios*, 184, 276 knowledge gaps, 389 Southeast Asia, vulnerability and risks in, 259, 261 faster transition scenario, 131, 135 main characteristics of, 342 Southern Ocean, role in global carbon cycle, inclusion of CDR in, 277 mitigation options*, 341 257–258 OECD scenario for 2°C, 373 projected emissions, 96, 157 Special Report on 1.5°C. See IPCC Special Report primary energy supply in, 132–133 SDGs and, 157 on 1.5°C (SR1.5) socio-economic scenario*, 62–63 Singapore, road pricing and car use, 366 Species SRES, 62 Sink*. See Carbon sequestration interactions, phenology and, 216–218 used in this report, 63 Small Island Developing States (SIDS)*, 9, invasive, 8, 9, 223 See also Narratives; Pathways 234–235, 255, 260, 261 loss and extinction, 8, 179, 218 Scientific evidence, 52 adaptation approaches, 339–340 range loss/shifts, 8, 179, 218, 222, 247, 248, Scientific institutions, 23, 317, 451 adaptation limits, 235, 455 256–257 Sea ice*, 182, 205–206, 212, 224–225, 249, 270 in Caribbean, 339–340 SSPs. See Shared Socio-economic Pathways (SSPs) Antarctic, 206, 225 climate hazards for, 234–235, 471 Stabilisation (of GHG or CO2-equivalent Arctic, 8, 178, 205–206, 209, 212, 224, 254, 258, climate-resilient development pathways* in, concentration)*, 116, 122, 147, 158, 184–185 261, 262 471, 471 Stockholm, congestion charge and car use, 366 beyond end of century, 270 disproportionate impacts/risks, 9, 53, 447 Storms, 181, 222–223, 249 irreversible changes, 257, 262 flooding, 235 extratropical, 203–204 temperature overshoot and, 8 freshwater resources, 9, 213, 234, 235 storm surge, 223 as tipping point, 261, 262, 270 Kiribati, adaptation in, 368, 471 tropical cyclones, 203–204, 211 Sea level change*, 7–8, 182, 206–207, 212, 225, livelihoods, 232, 235 Stranded assets*, 18 231–234, 248, 249 migration and, 181 Structured Expert Dialogue (SED), 79 adaptation and, 10 multiple, compounded risks, 10, 178, 181, Sub-national actors*, 23 beyond end of century, 271 260, 261 Sub-Saharan Africa, changes in climate extremes, coastal areas and, 207, 231–234, 243, 248, 249, 252 Pacific Islands, indigenous knowledge in, 360 197 commitment to continued rise, 7, 51, 67, 207, 257, risks, 9, 181, 232, 255 Sulphur dioxide (SO2), 96, 118, 120 271, 282 sea level rise and, 7, 8, 232, 234–235 Supply-side measures. See Demand and supply-side deltas and estuaries, 232–233 storm damage, 235 measures 614 Index Index Surface air temperature (SAT) mitigation and SDGs, 19–21, 20–21, 157, 459–463, and human health, 263, 264 in definition of 1.5°C, 51, 56 463, 465 observed, 210 global average temperature and, 56–57 mitigation and sustainable development, 459–463, probability ratio of, 192 Sustainable development (SD)*, 18–23, 72, 73–75, 463, 475 projected, 7, 177, 189, 190–191, 192, 210, 255 445–538 uneven distribution of, 466 Sub-Saharan Africa, 197 and 1.5°C pathways*, 93, 97, 98, 156–157, 253, Synfuels, 333 Temperature overshoot*. See Overshoot 450–451, 463–466, 465 Systemic changes/transitions, 14–15, 15–16, 21–22, Temperature threshold, 65, 66 and 1.5°C warmer worlds*, 55–56, 447, 451–453 315, 323–349, 449, 476 Terrestrial ecosystems, 8, 179, 216–221, 247, 252, adaptation and, 19, 447, 456–459 enabling, 315–318 3.SM.3.3.7 avoided impacts and, 452–453, 453, 475 rates of change, 322–323 biomass and carbon stocks, 219, 220 climate-resilient development pathways (CRDPs)* See also Transitions biome shifts, 216, 217, 247, 250 and, 22, 52, 64, 448–449, 450–451, 451, 468–472, ecosystem function, 219 475–476, 479–480 T impacts and risks at 1.5°C, vs. 2°C, 8, 11, 179, co-benefits, 447 216–221, 247, 251, 252, 3.SM.3.3.7, Table 3.SM.2 conditions for achieving, 474–475 Tanzania, indigenous knowledge used in, 360 knowledge gaps, 272 definition, 73 Technology, 22 phenology, 216–218 equity and, 55–56, 448–449 access to, 23 productivity, 220 integration with adaptation and mitigation, 75–76, biotechnology/genome modification, 319, 329 regional and ecosystem-specific risks, 219–221 448, 467 deployment of, 72 respiration, 219 mitigation and, 12, 18, 19–21, 97, 156–157, 156, disruptive, 22, 111, 319, 323 severe ecosystem changes, 217 447–448, 459–466, 481–509 general purpose technologies (GPT)*, 369–370, 383 Thermohaline circulation. See Atlantic Meridional mitigation pathways and, 463–466, 465 information and communication Overturning Circulation (AMOC) overview, 450, 475–476 technology (ICT)*, 316, 319 Tipping points*, 182, 262–263, 264, 270, 282 pathways to 1.5°C, 466–472, 469, 479–480 innovation in, 19, 21, 22, 316, 369–370 identifying, 458 research gaps, 475–476 innovation, enabling, 369–372 See also Irreversibility risks to, 253 innovation, examples of, 370 Tourism, 11, 178, 181, 242–243, 253, 3.SM.3.3.2 in social-ecological systems*, 338–341 innovation, knowledge gaps, 391 coastal areas, 229, 253 synergies and trade-offs, 457–458, 459–463, 463, low-carbon, 15, 16, 96, 153, 331 observed impacts, 181 475 new, 15, 22, 319 projected impacts, 181, 242–243, 253 trajectories, 451, 469–470, 480 policies, 95, 148, 370–371 risks, 181, 253 transformation* and, 22, 56, 73, 448, 456, 466 Power-2-X, 111 seasonal, 181, 243 Sustainable Development Goals (SDGs)*, 18, smart technology/IoT, 331 Trade-offs, 18–19, 72, 73, 269, 4.SM.4.5.1, 4.SM.5.2 19–21, 73–75, 156–157, 156 standards, 332, 378 example of, 477 adaptation options* and, 457–458 Technology transfer*, 19, 23, 371–372, 371, 449, 474 knowledge gaps, 391 avoided impacts and, 18, 68, 183, 253–265, 447, Temperature, 182 mitigation options and sustainable development, 453, 475 carbon budget, emissions, and, 96 459–463, 465 CDR and, 448, 462 datasets, 53, 56, 57, 58, 59, 1.SM.1 reconciling, 467 climate change and, 73, 74, 75, 157, 158, 252 fluctuations in, natural, 56, 59 with SDGs, 19, 73 energy efficiency and, 448 global average, defined, 56–57, 81 specific mitigation options, 97 equity and, 51 global mean surface temperature (GMST)*, 56–57, uneven distribution of, 466 food security and nutrition, 238 57, 177, 186 Transformation*, 22, 52, 70, 73, 112, 129–157, 315, mitigation options and, 19–21, 20–21, 448, heat-related morbidity and mortality, 9, 11, 180, 468–469 459–463 240–241, 250, 252, 252, 263, 264, 3.SM.3.3.1 1.5°C pathways*, 95, 112–113, 129–148, 448, 472 mitigation pathways, interactions with, 2.SM.1.5 heatwaves*, 9, 177–178, 263, 264 1.5°C warmer worlds*, 73 mitigation-SDG table, 481–509 land-sea contrast in warming, 8, 51, 59, 187, 190, 205 challenges, opportunities, and overview, 450 land surface air temperature*, 56 co-impacts, 148–157 policy instruments and, 448 number of hot days, 190, 193, 210 cities/urban areas, 472–474 prioritizing, 447 observed warming, 6, 51, 53, 53, 58, 106, 189–191, in climate-resilient development pathways, 468–469 risks from 1.5°C, vs. 2°C, 453 1.SM.1, 1.SM.2, 1.SM.3, 1.SM.6 context-specific, 469 SDG Global Index Scores, 53 peak in, 5, 96, 101, 104, 177, 277 energy system, 129–144, 463 SDG-interaction scores*, 481–509 peak, reducing after, 17, 18, 278 FAQ on, 392–393, 393 Shared Socio-economic Pathways* and, 321, 448, projections, 4, 7, 177, 187–188, 188, 190–191, feasibility of, 52, 72 467–468 192, 193 fundamental elements of, 73 synergies and trade-offs, 19–21, 21–22, 319, 447, rate of change, 54, 177, 178 implementing, 276 463, 475 regional variation in, 177, 283 societal (social) transformation*, system transitions and, 317 sea surface temperature (SST)*, 51, 204, 223–224, 22, 52, 73, 448–449, 466 Sustainable Development Pathways, 64, 448–449, 248 sustainable development and, 22, 448, 456 466–472, 469, 479–480 temperatures used in definition of 1.5°C, 51, 187, trade-offs, 73 Synergies, 18–19, 20–21, 72, 269, 316, 477, 188 upscaling and accelerating, 314 4.SM.4.5.1, 4.SM.5.2 See also Global warming whole systems approach, 392 adaptation and SDGs, 447 Temperature extremes, 255, 263 See also Transitions knowledge gaps, 391 hotspots (key risks), 190–191, 193 Transformation pathways*. See Pathways 615 Index Index Transformational adaptation. See Adaptation propagation of, 3.SM.1.3 redistributive policies and, 21 Transient climate response*, 184–185 Unique and threatened systems, 10, 11, 181, 251, reducing, 19, 447, 457 See also Climate sensitivity 253–255, 254 risks and, 53, 452 Transient climate response to cumulative CO2 United Kingdom Overseas Territories (UKOT), 339 sustainable development and, 447 emissions (TCRE)*, 96, 104, 106 United Nations Framework Convention on systemic, 22, 447, 457 Transition Movement, 480 Climate Change (UNFCCC)*, 79, 80, 353 Transition Towns (TTs), 473–474 adaptation financing, 21 W Transitions*, 14–15, 15–16, 21–22, 73, 315–318, Conference of the Parties (COP)*, 79 323–349, 4.SM.4.2.1-4.SM.4.2.5, Green Climate Fund, 74, 379 Warm Spell Duration Index (WSDI), 190 4.SM.4.3.1-4.SM.4.3.5 Uptake*. See Carbon sequestration Water availability, 178, 213–214 adaptation options* supporting, 321, 336–337, 338 Urban areas, 180, 241–242, 330–334 Water cycle. See Hydrological cycle enabling, 19, 21–22, 315–318 adaptation examples, 340–341 Water management, 10 in energy sector, 15, 96–97, 315, 324–327, adaptation options*, 10, 70, 263, 384–386, 385, Water resources, 179, 182, 213–216, 464–466 374–375, 4.SM.4.2.1, 4.SM.4.3.1 4.SM.4.3.3 bottom-up initiatives, 368 equity* in, 22 agriculture in, 316 demand for, 464–466 FAQ on, 392–393, 393 demotorization, 316, 366, 376 groundwater, 181, 215, 3.SM.3.1.1.3 in land use, 16, 17, 96, 97, 315, 327–329, energy systems, 331 impacts and risks, 213–216, 247 4.SM.4.3.2 feasibility of adaptation options, 384–386, 385 irrigation, 201, 215, 267, 267, 315, 328, 384, 466 policies supporting, 22 feasibility of mitigation options, 382 projections, 179 risks and ethics, 319 global urbanization, 472 regional, 179, 247 speed and scale of, 15, 314, 317, 320, 320, governance, 473 in urban areas, 316, 334 322–323, 392, 394 green infrastructure*, 10, 334, 334, 385 water-energy-food (WEF) nexus, 386–387 sustainable development and, 22 heat island effect, 9, 180, 242 water quality, 215–216, 3.SM.3.1.1.4 synergies, 316, 4.SM.5.2 heat-related extreme events, 241–242 water temperature, 214 system/sector transitions, 14–15, 15–16, 21–22, impacts and risks, 180, 182, 183, 241–242 watershed management, 356 96–97, 315–318, 323–349 informal urban settlements, 473 See also Precipitation See also specific sectors infrastructure, 331, 333 Water scarcity, 179, 213, 452, 453, 466 Transnational emission reduction initiatives knowledge gaps, 388–389 Water security, 464–466 (TERIs), 149 land use, 316, 333 Water stress, 9, 181, 247, 452, 466 Transport sector, 244, 316, 332–333 low-carbon cities, 331 Well-being*, 18, 180 biofuels, 325 mitigation options*, 4.SM.4.2.3 Bhutan’s happiness index, 387 car/transport pricing policies, 366 numbers of people in, 330, 340 place-specific adaptation and, 447 decarbonization* of, 316, 461 peri-urban agriculture, 316 well-being for all, 469 demotorization, 316, 366, 376 poverty and, 242 Wetlands, 179, 225, 254, 330, Table 3.SM.2 electric vehicle (EV)*, 316, 332–333, 333 risks and risk reduction, 331, 456 management, 330 electrification of, 332–333, 333, 460 sea level rise and, 231–232, 241 methane release from, 12 emissions, 96, 114, 142–144, 143 transformation* in, 472–474 salinization of, 233 emissions reduction, 366 transformational adaptation, 386 sea level rise and, 233 final energy demand and use, 139, 142–144, 143, Transition Towns (TTs), 473–474 Wind energy, 96, 131, 131, 132–133 332 transitions, 15–16, 316, 330–334, 4.SM.4.2.3, impacts of weather and climate on, 244 4.SM.4.3.3 Z international transport, 333 transport, 316, 331, 332–333 investments in, 373–374 urban planning, 148 Zero emissions commitment (ZEC), 64–65, 65 road safety for pedestrians, 461 water services, 316, 334 road transport, 142–143, 461 See also specific cities strategies to reduce energy consumption, 142 Urban heat islands, 9, 180, 242 sustainable transport, 332 technological innovations, 370 V transitions, 15–16, 316 transitions, speed and scale of, 320, 320 Values, 22, 71, 317, 364–365 urban environments, 316, 332 re-examination of, 449, 469, 475 Tropical cyclone*, 203–204, 211 societal, 448, 476 Cyclone Pam, 471 value judgements, 55 Tundra, 8, 179, 216, 220 Vanuatu, planning for climate-resilience, 449, 471 tipping points*, 262, 264 Vector-borne disease, 9, 180, 241 Aedes mosquitoes, 241 U Vulnerability*, 69, 447 disproportionate impacts and, 9, 51, 447 Uncertainty*, 69, 77 factors influencing, 53 of climate response to mitigation, 60, 63 international cooperation and, 23 geophysical, 96, 101–104 multiple, interrelated climate risks, 10 in mitigation pathways, 60, 63 new vulnerabilities, 10 616 Index