Browsing by Author "Hughes, A.F."
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Item Air Pollution in Accra Neighborhoods: Spatial, Socioeconomic, and Temporal Patterns(Environmental Science and Technology, 2010-03) Dionisio, K.L.; Arku, R.E.; Hughes, A.F.; Jose Vallarin, O.; Carmichael, H.; Spengler, J.D.; Agyei-Mensah, S.; Ezzati, M.This study examined the spatial, socioeconomic status (SES), and temporal patterns of ambient air pollution in Accra, Ghana. Over 22 months, integrated and continuous rooftop particulate matter (PM) monitors were placed at a total of 11 residential or roadside monitoring sites in four neighborhoods of varying SES and biomass fuel use. PM concentrations were highest in late December and January, due to dust blown from the Sahara. Excluding this period, annual PM2.5 ranged from 39 to 53μg/m3 at roadside sites and 30 to 70 μg/m3 at residential sites; mean annual PM10 ranged from 80 to 108 μg/m3 at roadside sites and 57 to 106 μg/m3 at residential sites. The low-income and densely populated neighborhood of Jamestown/Ushertown had the single highest residential PM concentration. There was less difference across traffic sites. Daily PM increased at all sites at daybreak, followed by a mid-day peak at some sites, and a more spread-out evening peak at all sites. Average carbon monoxide concentrations at different sites and seasons ranged from 7 to 55 ppm, and were generally lower at residential sites than at traffic sites. The results show that PM in these four neighborhoods is substantially higher than the WHO Air Quality Guidelines and in some cases even higher than the WHO Interim Target 1, with the highest pollution in the poorest neighborhood. © 2010 American Chemical Society.Item Application of Gaussian Mixture Regression for the Correction of Low Cost PM2.5 Monitoring Data in Accra, Ghana(ACS Earth and Space Chemistry, 2021) McFarlane, C.; Raheja, G.; Malings, C.; Appoh, E.K.E.; Hughes, A.F.; Westervelt, D.M.ABSTRACT: Low-cost sensors (LCSs) for air quality monitoring have enormous potential to improve air quality data coverage in resource-limited parts of the world such as sub-Saharan Africa. LCSs, however, are affected by environment and source conditions. To establish high-quality data, LCSs must be collocated and calibrated with reference grade PM2.5 monitors. From March 2020, a low-cost PurpleAir PM2.5 monitor was collocated with a Met One Beta Attenuation Monitor 1020 in Accra, Ghana. While previous studies have shown that multiple linear regression (MLR) and random forest regression (RF) can improve accuracy and correlation between PurpleAir and reference data, MLR and RF yielded suboptimal improvement in the Accra collocation (R2 = 0.81 and R2 = 0.81, respectively). We present the first application of Gaussian mixture regression (GMR) to air quality data calibration and demonstrate improvement over traditional methods by increasing the collocated PM2.5 correlation and accuracy to R2 = 0.88 and MAE = 2.2 μg m−3. Gaussian mixture models (GMMs) are a probability density estimator and clustering method from which nonlinear regressions that tolerate missing inputs can be derived. We find that even when given missing inputs, GMR provides better correlation than MLR and RF performed with complete data. GMR also allows us to estimate calibration certainty. When evaluated, 95% confidence intervals agreed with reference PM2.5 data 96% of the time, suggesting that the model accurately assesses its own confidence. Additionally, clustering within the GMM is consistent with climate characteristics, providing confidence that the calibration approach can learn underlying relationships in data.Item Characterisation of urban environment and activity across space and time using street images and deep learning in Accra(Scientific reports, 2022) Nathvani, R.; Clark, S.N.; Muller, E.; Alli, A.S.; Bennett, J.E.; Nimo, J.; Moses, J.B.; Baah, S.; Metzler, A.B.; Brauer, M.; Suel, E.; Hughes, A.F.; Agyemang, E.; Owusu, G.; Agyei‑Mensah, S.The urban environment influences human health, safety and wellbeing. Cities in Africa are growing faster than other regions but have limited data to guide urban planning and policies. Our aim was to use smart sensing and analytics to characterise the spatial patterns and temporal dynamics of features of the urban environment relevant for health, liveability, safety and sustainability. We collected a novel dataset of 2.1 million time-lapsed day and night images at 145 representative locations throughout the Metropolis of Accra, Ghana. We manually labelled a subset of 1,250 images for 20 contextually relevant objects and used transfer learning with data augmentation to retrain a convolutional neural network to detect them in the remaining images. We identified 23.5 million instances of these objects including 9.66 million instances of persons (41% of all objects), followed by cars (4.19 million, 18%), umbrellas (3.00 million, 13%), and informally operated minibuses known as tro tros (2.94 million, 13%). People, large vehicles and market-related objects were most common in the commercial core and densely populated informal neighbourhoods, while refuse and animals were most observed in the peripheries. The daily variability of objects was smallest in densely populated settlements and largest in the commercial centre. Our novel data and methodology shows that smart sensing and analytics can inform planning and policy decisions for making cities more liveable, equitable, sustainable and healthy.Item Characterization and Source Apportionment of Airborne Particulate Matter in Some Urban Neighbourhoods of Accra, Ghana(University of Ghana, 2014-07) Hughes, A.F.; Kakane, V.C.K.; Amuzu, J.K.A; Agyei, E.K.; University of Ghana, College of Humanities , School of Arts , Department of Philosophy and ClassicsA year-long campaign which accounted for seasonal differences have been conducted to examine the levels, chemical composition and sources of ambient particulate matter in multiple neighbourhoods of varying socio-economic status in Accra, Ghana. Between September 2007 and August 2008, simultaneous measurements of PM2.5 and PM10 aerosols at five monitoring sites in four neighbourhoods (Asylum Down, East Legon, Nima and James Town/Ussher Town) were done for one 48-hour period every six days. Harvard Impactor with polytetrafluorethylene (PTFE) Teflon filter of 37 mm supported by a Whatman drain disc were used to sample air particles in the Accra neighbourhoods. Gravimetric analysis and energy dispersive X-ray fluorescence (EDXRF) were used to determine the chemical composition and concentration of the aerosol particles. The mean mass concentration values for PM2.5 obtained at the five sites during the study period varied from 45.9 μg m-3 to 74.8 μg m-3. The mean mass concentration for PM10 also varied from 93.9 μg m-3 to 134.8 μg m-3. These levels were all substantially higher than the EPA (Ghana) guidelines values and other international air quality standards from WHO, USEPA and EU. Weak relationships were obtained between PM and weather parameters. Crustal elements were most abundant during the seasonal Harmattan period between late December and early February when Saharan dust is transported across West Africa. Enrichment factor analysis was used to provide an initial indication of the species of anthropogenic origin in the measured elemental composition. Source contributions were analysed using positive matrix factorization (PMF) model separately for Harmattan and non-Harmattan periods because large changes to source profiles is expected during the Harmattan period. Anthropogenic sources resolved by PMF model (biomass burning, solid waste burning, resuspended dust and traffic/industry emissions) during both Harmattan and non-Harmattan periods had significant influence on the four neighbourhoods in Accra.Item Chemical characterization and source apportionment of household fine particulate matter in rural, peri-urban, and urban West Africa(Environmental Science and Technology, 2014) Zhou, Z.; Dionisio, K.L.; Verissimo, T.G.; Kerr, A.S.; Coull, B.; Howie, S.; Arku, R.E.; Koutrakis, P.; Renner, J.D.; Fornace, K.; Hughes, A.F.; Vallarino, J.; Agyei-Mensah, S.; Ezzati, M.Household air pollution in sub-Saharan Africa and other developing regions is an important cause of disease burden. Little is known about the chemical composition and sources of household air pollution in sub-Saharan Africa, and how they differ between rural and urban homes. We analyzed the chemical composition and sources of fine particles (PM2.5) in household cooking areas of multiple neighborhoods in Accra, Ghana, and in peri-urban (Banjul) and rural (Basse) areas in The Gambia. In Accra, biomass burning accounted for 39-62% of total PM2.5 mass in the cooking area in different neighborhoods; the absolute contributions were 10-45 μg/m 3. Road dust and vehicle emissions comprised 12-33% of PM 2.5 mass. Solid waste burning was also a significant contributor to household PM2.5 in a low-income neighborhood but not for those living in better-off areas. In Banjul and Basse, biomass burning was the single dominant source of cooking-area PM2.5, accounting for 74-87% of its total mass; the relative and absolute contributions of biomass smoke to PM 2.5 mass were larger in households that used firewood than in those using charcoal, reaching as high as 463 μg/m3 in Basse homes that used firewood for cooking. Our findings demonstrate the need for policies that enhance access to cleaner fuels in both rural and urban areas, and for controlling traffic emissions in cities in sub-Saharan Africa. © 2013 American Chemical Society.Item Chemical composition and sources of particle pollution in affluent and poor neighborhoods of Accra, Ghana(Environmental Research Letters, 2013-12) Zhou, Z.; Dionisio, K.L.; Verissimo, T.G.; Kerr, A.S.; Coull, B.; Arku, R.E.; Koutrakis, P.; Spengler, J.D.; Hughes, A.F.; Vallarino, J.; Agyei-Mensah, S.; Ezzati, M.The highest levels of air pollution in the world now occur in developing country cities, where air pollution sources differ from high-income countries. We analyzed particulate matter (PM) chemical composition and estimated the contributions of various sources to particle pollution in poor and affluent neighborhoods of Accra, Ghana. Elements from earth's crust were most abundant during the seasonal Harmattan period between late December and late January when Saharan dust is carried to coastal West Africa. During Harmattan, crustal particles accounted for 55 μg m-3 (37%) of fine particle (PM 2.5) mass and 128 μg m-3 (42%) of PM10 mass. Outside Harmattan, biomass combustion, which was associated with higher black carbon, potassium, and sulfur, accounted for between 10.6 and 21.3 μg m -3 of fine particle mass in different neighborhoods, with its contribution largest in the poorest neighborhood. Other sources were sea salt, vehicle emissions, tire and brake wear, road dust, and solid waste burning. Reducing air pollution in African cities requires policies related to energy, transportation and urban planning, and forestry and agriculture, with explicit attention to impacts of each strategy in poor communities. Such cross-sectoral integration requires emphasis on urban environment and urban poverty in the post-2015 Development Agenda. © 2013 IOP Publishing Ltd.Item Determination of the series resistance of a solar cell through its maximum power point(African Journal of Science, Technology, Innovation and Development, 2020-03-23) Koffi, A.H.; Yankson, A.A.; Hughes, A.F.; Ampomah-Benefo, K.; Amuzu, J.K.A.A simple analytical approach has been developed to determine the series resistance, Rs, of a solar cell. The method adopted here depends only on the knowledge of the open-circuit voltage, Voc, and the current and voltage at the maximum power point, Isc and Vmp respectively. This approach, based on a knowledge of these operating output parameters of the cell, provides a theoretical framework for an existing computer simulated approach which has been widely used in industries.Item Household and community poverty, biomass use, and air pollution in Accra, Ghana(Proceedings of the National Academy of the United States of America, 2011-07) Zhoua, Z.; Dionisio, K.L.; Arku, R.E.; Quaye, A.; Hughes, A.F.; Vallarino, J.; Spengler, J.D.; Hill, A.; Agyei-Mensah, S.; Ezzati, M.Many urban households in developing countries use biomass fuels for cooking. The proportion of household biomass use varies among neighborhoods, and is generally higher in low socioeconomic status (SES) communities. Little is known of how household air pollution varies by SES and how it is affected by biomass fuels and traffic sources in developing country cities. In four neighborhoods in Accra, Ghana, we collected and analyzed geo-referenced data on household and community particulate matter (PM) pollution, SES, fuel use for domestic and small-commercial cooking, housing characteristics, and distance to major roads. Cooking area PM was lowest in the high-SES neighborhood, with geometric means of 25 (95% confidence interval, 21–29) and 28 (23–33) μg/m3 for fine and coarse PM (PM2.5 and PM2.5–10), respectively; it was highest in two low-SES slums, with geometric means reaching 71 (62–80) and 131 (114–150) μg/m3 for fine and coarse PM. After adjustment for other factors, living in a community where all households use biomass fuels would be associated with 1.5- to 2.7-times PM levels in models with and without adjustment for ambient PM. Community biomass use had a stronger association with household PM than household’s own fuel choice in crude and adjusted estimates. Lack of regular physical access to clean fuels is an obstacle to fuel switching in low-income neighborhoods and should be addressed through equitable energy infrastructure.Item Household and community poverty, biomass use, and air pollution in Accra, Ghana(National Academy of Science of the Unites States of America, 2011-06) Zhoua, Z.; Dionisio, K.L.; Arku, R.E.; Quaye, A.; Hughes, A.F.; Vallarino, J.; Spengler, J.D.; Hill, A.; Agyei-Mensah, S.; Ezzati, M.Many urban households in developing countries use biomass fuels for cooking. The proportion of household biomass use varies among neighborhoods, and is generally higher in low socioeconomic status (SES) communities. Little is known of how household air pollution varies by SES and how it is affected by biomass fuels and traffic sources in developing country cities. In four neighborhoods in Accra, Ghana, we collected and analyzed geo-referenced data on household and community particulate matter (PM) pollution, SES, fuel use for domestic and small-commercial cooking, housing characteristics, and distance to major roads. Cooking area PM was lowest in the high-SES neighborhood, with geometric means of 25 (95% confidence interval, 21–29) and 28 (23–33) μg/m3 for fine and coarse PM (PM2.5 and PM2.5–10), respectively; it was highest in two low-SES slums, with geometric means reaching 71 (62–80) and 131 (114–150) μg/m3 for fine and coarse PM. After adjustment for other factors, living in a community where all households use biomass fuels would be associated with 1.5- to 2.7-times PM levels in models with and without adjustment for ambient PM. Community biomass use had a stronger association with household PM than household’s own fuel choice in crude and adjusted estimates. Lack of regular physical access to clean fuels is an obstacle to fuel switching in low-income neighborhoods and should be addressed through equitable energy infrastructure.Item Impact of material composition and food waste decomposition on characteristics of fuel briquettes(Resources, Conservation & Recycling Advances, 2022) Nikiema, J.; Akomea-Agyin, J.; Hughes, A.F.; et al.This study investigated the potential of using locally available municipal solid wastes (MSW) (such as food wastes from restaurants, charcoal dust, coconut husk and shell, and sawdust) as feedstock to produce non-carbonized fuel briquettes. A low-cost briquetting machine sourced from Alfaster Industries in Kenya served to demonstrate the concept. Using decomposed food waste resulted in briquettes with higher bulk density (+4%), greater net calorific value (+18%) and lower burning rate (-24%), compared to the use of regular food waste. There was no significant difference in ash content from the two briquette types. The results also indicate that decomposing food waste and mixing it with tree-based raw materials such as coconut waste, charcoal waste or sawdust improves the quality of briquettes and enhances the temperatures achieved during combustion. This recycling solution have the potential to serve multiple benefits in MSW management for sustainable cities while reducing rural land degradation and deforestation.Item Inequalities in urban air pollution in sub-Saharan Africa: an empirical modeling of ambient NO and NO2 concentrations in Accra, Ghana(Enviromental Research Letters, 2024) Wang, J.; Ezzati, M.; Hughes, A.F.; et al.Road traffic has become the leading source of air pollution in fast-growing sub-Saharan African cities. Yet, there is a dearth of robust city-wide data for understanding space-time variations and inequalities in combustion related emissions and exposures. We combined nitrogen dioxide (NO2) and nitric oxide (NO) measurement data from 134 locations in the Greater Accra Metropolitan Area (GAMA), with geographical, meteorological, and population factors in spatio-temporal mixed effects models to predict NO2 and NO concentrations at fine spatial (50 m) and temporal (weekly) resolution over the entire GAMA. Model performance was evaluated with 10-fold cross-validation (CV), and predictions were summarized as annual and seasonal (dusty [Harmattan] and rainy [non-Harmattan]) mean concentrations. The predictions were used to examine population distributions of, and socioeconomic inequalities in, exposure at the census enumeration area (EA) level. The models explained 88% and 79% of the spatiotemporal variability in NO2 and NO concentrations, respectively. The mean predicted annual, non-Harmattan and Harmattan NO2 levels were 37 (range: 1–189), 28 (range: 1–170) and 50 (range: 1–195) µg m−3 , respectively. Unlike NO2, NO concentrations were highest in the non-Harmattan season (41 [range: 31–521] µg m−3 ). Road traffic was the dominant factor for both pollutants, but NO2 had higher spatial heterogeneity than NO. For both pollutants, the levels were substantially higher in the city core, where the entire population (100%) was exposed to annual NO2 levels exceeding the World Health Organization (WHO) guideline of 10 µg m−3 . Significant disparities in NO2 concentrations existed across socioeconomic gradients, with residents in the poorest communities exposed to levels about 15 µg m−3 higher compared with the wealthiest (p < 0.001). The results showed the important role of road traffic emissions in air pollution concentrations in the GAMA, which has major implications for the health of the city’s poorest residents. These data could support climate and health impact assessments as well as policy evaluations in the city.Item Personal particulate matter exposures and locations of students in four neighborhoods in Accra, Ghana.(NCBI, 2015) Arku, R.E.; Dionisio, K.L.; Hughes, A.F.; Vallarino, J.; Spengler, J.D.; Castro, M.C.; Agyei-Mensah, S.; Ezzati, M.Air pollution exposure and places where the exposures occur may differ in cities in the developing world compared with high-income countries. Our aim was to measure personal fine particulate matter (PM2.5) exposure of students in neighborhoods of varying socioeconomic status in Accra, Ghana, and to quantify the main predictors of exposure. We measured 24-hour PM2.5 exposure of 56 students from eight schools in four neighborhoods. PM2.5 was measured both gravimetrically and continuously, with time-matched global positioning system coordinates. We collected data on determinants of exposure, such as distances of homes and schools from main roads and fuel used for cooking at their home or in the area of residence/school. The association of PM2.5 exposure with sources was estimated using linear mixed-effects models. Personal PM2.5 exposures ranged from less than 10 μg/m(3) to more than 150 μg/m(3) (mean 56 μg/m(3)). Girls had higher exposure than boys (67 vs 44 μg/m(3); P-value=0.001). Exposure was inversely associated with distance of home or school to main roads, but the associations were not statistically significant in the multivariate model. Use of biomass fuels in the area where the school was located was also associated with higher exposure, as was household's own biomass use. Paved schoolyard surface was associated with lower exposure. School locations in relation to major roads, materials of school ground surfaces, and biomass use in the area around schools may be important determinants of air pollution exposure.Item Personal particulate matter exposures and locations of students in four neighborhoods in Accra, Ghana.(Journal of Exposure Science and Environmental Epidemiology, 2015-11) Arku, R.E.; Dionisio, K.L.; Hughes, A.F.; Vallarino, J.; Spengler, J.D.; Castro, M.C.; Agyei-Mensah, S.; Ezzati, M.Air pollution exposure and places where the exposures occur may differ in cities in the developing world compared with high-income countries. Our aim was to measure personal fine particulate matter (PM2.5) exposure of students in neighborhoods of varying socioeconomic status in Accra, Ghana, and to quantify the main predictors of exposure. We measured 24-hour PM2.5 exposure of 56 students from eight schools in four neighborhoods. PM2.5 was measured both gravimetrically and continuously, with time-matched global positioning system coordinates. We collected data on determinants of exposure, such as distances of homes and schools from main roads and fuel used for cooking at their home or in the area of residence/school. The association of PM2.5 exposure with sources was estimated using linear mixed-effects models. Personal PM2.5 exposures ranged from less than 10 μg/m3 to more than 150 μg/m3 (mean 56 μg/m3). Girls had higher exposure than boys (67 vs 44 μg/m3; P-value=0.001). Exposure was inversely associated with distance of home or school to main roads, but the associations were not statistically significant in the multivariate model. Use of biomass fuels in the area where the school was located was also associated with higher exposure, as was household’s own biomass use. Paved schoolyard surface was associated with lower exposure. School locations in relation to major roads, materials of school ground surfaces, and biomass use in the area around schools may be important determinants of air pollution exposure.Item Seasonal variations in the operating temperature of silicon solar panels in southern Ghana(African Journal of Science, Technology, Innovation and Development, 2015-07) Koffi, H.A.; Kakane, V.C.K.; Kuditcher, A.; Hughes, A.F.; Adeleye, M.B.; Amuzu, J.K.A.This work deals with the seasonal daily variation of the operating temperature of silicon solar panels under tropical atmospheric conditions, including high turbidity (Harmattan dust particles). Data was collected from March 2010 to July 2012 at Legon (0°11’08″ W, 5°39’04″ N) using a Davis wireless Vantage Pro2 Plus weather station monitored with the software WeatherLink®. While the ‘common outdoor’ operating temperature is usually set at 45 °C, it has been observed that during the harmattan season, the operating temperature of a solar panel can rise beyond 70°C. © 2015 African Journal of Science, Technology, Innovation and Development.Item Spatial and temporal patterns of particulate matter sources and pollution in four communities in Accra, Ghana(Elsevier, 2012) Rooney, M.S.; Arku, R.E.; Dionisio, K.L.; Paciorek, C.; Friedman, A.B.; Carmichael, H.; Zhoua, Z.; Hughes, A.F.; Vallarino, J.; Agyei-Mensah, S.; Spengler, J.D.; Ezzati, M.Sources of air pollution in developing country cities include transportation and industrial pollution, biomass fuel use, and re-suspended dust from unpaved roads. We examined the spatial patterns of particulate matter (PM) and its sources in four neighborhoods of varying socioeconomic status (SES) in Accra. PM data were from 1 week of morning and afternoon mobile and stationary air pollution measurements in each of the study neighborhoods. PM2.5 and PM10 were measured continuously, with matched GPS coordinates. Data on biomass fuel use were from the Ghana 2000 population and housing census and from a census of wood and charcoal stoves along the mobile monitoring paths. We analyzed the associations of PM with sources using a mixed-effects regression model accounting for temporal and spatial autocorrelation. After adjusting for other factors, the density of wood stoves, fish smoking, and trash burning along the mobile monitoring path as well as road capacity and surface were associated with higher PM2.5. Road capacity and road surface variables were also associated with PM10, but the association with biomass sources was weak or absent. While wood stoves and fish smoking were significant sources of air pollution, addressing them would require financial and physical access to alternative fuels for low-income households and communities.