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Item Assessing groundwater quality in peri-urban Accra, Ghana: Implications for drinking and irrigation purposes(Groundwater for Sustainable Development, 2022) Hagan, G.B.; Minkah, R.; Yiran, G.A.B.; Dankyi, E.In many developing countries, cities are faced with rising water demand due to rapidly increasing population. inadequate municipal water supply and growing sanitation pressure. Consequently, groundwater resources are being heavily relied on to meet the demand. However, the long-term supply and quality of groundwater are threatened by multiple anthropogenic pressures. This study assessed the quality and suitability of groundwater available to more than 600,000 inhabitants in several peri-urban communities in Accra, the capital city of Ghana. Thirty-six (36) borehole samples were analysed for their suitability for domestic and irrigation purposes based on relevant physicochemical parameters. In addition, water quality index (WQI), sodium absorption ratio, and relevant statistical plots were employed to assess the groundwater’s quality and suitability for domestic and irrigation purposes. The results indicate that almost all parameters measured were within the WHO recommended limits for drinking water for most samples. This is reflected in the classification of 92% of water samples as good or excellent quality for domestic purposes using WQI. The abundance of ions in groundwater followed the trend: Na+ > Ca2+ > Mg2+ > K+ for cations, and Cl− > SO4 2 > HCO3 − > F > NO3 − for anions. By using principal component and hierarchical cluster analyses, the study identified mineral dissolution and anthropogenic activities as the main factors influencing groundwater chemistry in the study area. These factors resulted in mixed water types, viz., Na-Ca-Mg–Cl and Na-Ca-Mg–SO4, with Na-Cl as the dominant water type. Classifications based on the Wilcox and USSL diagrams, it appears that groundwater in the study area is generally suitable for irrigation. Given that these boreholes are new, the results from this study represent background levels and have important implications for groundwater development and management in the rapidly developing capital of Ghana.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 High frequency amplification of acoustic phonons in fluorine-doped single-walled carbon nanotubes(Diamond & Related Materials, 2024) Sekyi-Arthur, D.; Mensah, S.Y.; Amewode, .K.; Jebuni-Adanu, C.; Asare, J.Herein, we report on a strong high-frequency induced amplification of coherent acoustic phonons in a non degenerate fluorine-doped single-walled carbon nanotubes (FSWCNTs) by utilising a tractable analytical approach in the hypersound regime, ql≫1 (where q is the acoustic wavenumber and l is the carrier mean free path). The acoustoelectric gain obtained is highly nonlinear and is due to stimulated Cerenkov phonon emission by electrically driven carriers undergoing intraminiband transport and capable of performing Bloch oscillations. The transport process causes the carriers to undergo population inversion leading to intraminiband phonon assisted processes. The generation rate (phonon emission) is expansive and surpasses phonon losses. The threshold field (Eo), at which attenuation switches over to amplification (gain) depends on the FSWCNT pa rameters (Δs&Δz), carrier drift velocity (vd = μEo), sound velocity (vs) and the ratio ζs,z. This result has potential for intense sources of reasonable acoustic phonons in the sub-THz regime and is vital for the generation of SASER (sound amplification by stimulated emission of acoustic radiation). The amplified phonons also have THz fre quencies with wavelengths in the nanometer range, and depends on high spatial parameters which has potential applications for phonon filters and spectrometers.Item Prediction of gold mineralization zones using spatial techniques and geophysical data: A case study of the Josephine prospecting licence, NW Ghana(Heliyon, 2023) Forson, E.D.; Amponsah, P.O.In this study, predictive models that characterize gold potential zones within the Josephine Prospecting Licence (PL) Area of Northwestern Ghana have been created by data-driven methods comprising frequency ratio and information value. These predictive models were evaluated using known locations of gold (Au) occurrence datasets and compared to each other. The mineral prospectivity models (MPMs) of gold occurrence areas within the Josephine PL Area were con structed by determining the spatial correlation between known locations of Au occurrences and eight mineralization related factors. The locations of these known Au occurrences, which char acterize regions of anomalously high Au geochemical concentration and regions of previous or ongoing artisanal mining operations were identified by using geographic positioning systems (GPS). Eight mineralization related factors (geoscientific thematic layers) over the entire study area composed of analytic signal, lineament density, uranium-thorium ratio, uranium, potassium thorium ratio, potassium, reduction-to-equator and geology were used to generate the MPMs. The predictive capacity of each of the MPMs generated was determined by employing the area under the receiver operating characteristics curve (AUC). The AUC score obtained for the predictive models produced based on the information value and the frequency ratio approaches were respectively 0.794 and 0.815. The AUC scores generated indicate that the MPMs produced are good predictive models (with an AUC greater than 0.7) and can therefore assist in narrowing down the highly prospective zones of mineral occurrences within the study area. However, the overall predictive potential of the frequency ratio approach was better than the model produced by the information value approach.Item High frequency amplification of acoustic phonons in fluorine-doped single-walled carbon nanotubes(Diamond & Related Materials, 2024) Sekyi-Arthu, D.; Mensah, S.Y.; Jebuni-Adanu, C. .; Asare, J.Herein, we report on a strong high-frequency induced amplification of coherent acoustic phonons in a non degenerate fluorine-doped single-walled carbon nanotubes (FSWCNTs) by utilising a tractable analytical approach in the hypersound regime, ql≫1 (where q is the acoustic wavenumber and l is the carrier mean free path). The acoustoelectric gain obtained is highly nonlinear and is due to stimulated Cerenkov phonon emission by electrically driven carriers undergoing intraminiband transport and capable of performing Bloch oscillations. The transport process causes the carriers to undergo population inversion leading to intraminiband phonon assisted processes. The generation rate (phonon emission) is expansive and surpasses phonon losses. The threshold field (Eo), at which attenuation switches over to amplification (gain) depends on the FSWCNT pa rameters (Δs&Δz), carrier drift velocity (vd = μEo), sound velocity (vs) and the ratio ζs,z. This result has potential for intense sources of reasonable acoustic phonons in the sub-THz regime and is vital for the generation of SASER (sound amplification by stimulated emission of acoustic radiation). The amplified phonons also have THz fre quencies with wavelengths in the nanometer range, and depends on high spatial parameters which has potential applications for phonon filters and spectrometers.Item Bias-corrected NASA data for aridity index estimation over tropical climates in Ghana, West Africa(Journal of Hydrology:Regional Studies, 2024) Asilevi, P.J.; Klutse, N.A.B.; Amekudzi, L.K.; et al.Study region: Ghana, West Africa. Study focus: NASA’s Prediction of Worldwide Energy Resource (NASA POWER) satellite-based reanalysis products are used for estimating the aridity index (AI) in Ghana, West Africa. The NASA estimates are compared and bias-corrected with temperature-based potential evapotrans piration estimates and rainfall data from 22 synoptic climate stations. The cumulative distribution function (CDF) matching technique was used for bias correction New Hydrological Insights for the region: The results indicated a previous 36% over-estimation of arid conditions in dryland climates and an under-estimation of wetland climate regions by the NASA POWER data compared with the station-based estimation. Post bias-correction, the satellite-based estimates showed substantial improvements, as evidenced by a correlation coef ficient of R2 = 0.87. The rectified data suggests that with accurate interpretations and calibra tions, satellite-based metrics can play a pivotal role in advancing hydrological studies and water resource management in West Africa Sub-region. This insight underscores the potential of satellite data in augmenting regional hydrological research, establishing a foundation for similar studies in analogous global environments.Item Understanding The Role Of Hubbard Corrections In The Rhombohedral Phase Of Batio3(Physical Review B, 2023) Gebreyesus, G.; Bastonero, L.; Kotiuga, M.; et al.We present a first-principles study of the low-temperature rhombohedral phase of BaTiO3 using Hubbard-corrected density-functional theory. By employing density-functional perturbation theory, we compute the onsite HubbardU for Ti(3d) states and the intersite HubbardV between Ti(3d) and O(2p) states. We show that applying the onsite Hubbard U correction alone to Ti(3d) states proves detrimental, as it suppresses the Ti(3d)-O(2p) hybridization and drives the system towards a cubic phase. Conversely, when both onsite U and intersite V are considered, the localized character of the Ti(3d) states is maintained while also preserving the Ti(3d)-O(2p) hybridization, restoring the rhombohedral phase of BaTiO3. The generalized PBEsol+U+V functional yields good agreement with experimental results for the band gap and dielectric constant, while the optimized geometry is slightly less accurate compared to PBEsol. Zone-center phonon frequencies and Raman spectra are found to be significantly influenced by the underlying geometry. PBEsol and PBEsol+U+V provide satisfactory agreement with the experimental Raman spectrum when the PBEsol geometry is used, while PBEsol+U Raman spectrum diverges strongly from experimental data, highlighting the adverse impact of the U correction alone in BaTiO3. Our findings underscore the promise of the extended Hubbard PBEsol+U+V functional with first-principles U and V for the investigation of other ferroelectric perovskites with mixed ionic-covalent interactions.Item Beyond here and now: Evaluating pollution estimation across space and time from street view images with deep learning(Science of the Total Environment, 2023) Nathvani, R.; Nimo, J.; Baah, S.; et al.Advances in computer vision, driven by deep learning, allows for the inference of environmental pollution and its potential sources from images. The spatial and temporal generalisability of image-based pollution models is crucial in their real-world application, but is currently understudied, particularly in low-income countries where infrastructure for measuring the complex patterns of pollution is limited and modelling may therefore provide the most utility. We employed convolutional neural networks (CNNs) for two complementary classification models, in both an end-to-end approach and as an interpretable feature extractor (object detection), to estimate spatially and temporally resolved fine particulate matter (PM2.5) and noise levels in Accra, Ghana. Data used for training the models were from a unique dataset of over 1.6 million images collected over 15 months at 145 representative locations across the city, paired with air and noise measurements. Both end-to-end CNN and object-based approaches surpassed null model benchmarks for predicting PM2.5 and noise at single locations, but performance deteriorated when applied to other locations. Model accuracy diminished when tested on images from locations unseen during training, but improved by sampling a greater number of locations during model training, even if the total quantity of data was reduced. The end-to-end models used characteristics of images associated with atmospheric visibility for predicting PM2.5, and specific objects such as vehicles and people for noise. The results demonstrate the potential and challenges of image-based, spatiotemporal air pollution and noise estimation, and that robust, environmental modelling with images requires integration with traditional sensor networks.Item Beyond here and now: Evaluating pollution estimation across space and time from street view images with deep learning(Science of the Total Environment, 2023) Nathvani, R.; Nimo, J.; Agyei-Mensah, S.; et al.Advances in computer vision, driven by deep learning, allows for the inference of environmental pollution and its potential sources from images. The spatial and temporal generalisability of image-based pollution models is crucial in their real-world application, but is currently understudied, particularly in low-income countries where infrastructure for measuring the complex patterns of pollution is limited and modelling may therefore provide the most utility. We employed convolutional neural networks (CNNs) for two complementary classification models, in both an end-to-end approach and as an interpretable feature extractor (object detection), to estimate spatially and temporally resolved fine particulate matter (PM2.5) and noise levels in Accra, Ghana. Data used for training the models were from a unique dataset of over 1.6 million images collected over 15 months at 145 representative locations across the city, paired with air and noise measurements. Both end-to-end CNN and object-based approaches surpassed null model benchmarks for predicting PM2.5 and noise at single locations, but performance deteriorated when applied to other locations. Model accuracy diminished when tested on images from locations unseen during training, but improved by sampling a greater number of locations during model training, even if the total quantity of data was reduced. The end-to-end models used characteristics of images associated with atmospheric visibility for predicting PM2.5, and specific objects such as vehicles and people for noise. The results demonstrate the potential and challenges of image-based, spatiotemporal air pollution and noise estimation, and that robust, environmental modelling with images requires integration with traditional sensor networks.Item Depth-based correlation analysis between the density of lineaments in the crystalline basement’s weathered zones and groundwater occurrences within the Voltaian basin, Ghana(Geophysical Prospecting, 2023) Amponsah, T.Y.; Wemegah, D.D.; Danuor, S.K.; Forson, E.D.Geological structures have been shown by studies to have influence on the occurrence, storage and transportation of groundwater. Understanding the structural network of an area unearths a deep insight into the groundwater dynamics of the area. A geologi cal structural analysis was carried out to reveal the geological structural network of Ghana’s Voltaian basin. Using aeromagnetic data, structural density models were gen erated using the Center for Exploration Targeting grid analysis technique for two depth ranges (that is up to 100 m and 300 m) over the Voltaian basin. The total length of geo logical structures (lineaments) delineated at depths up to 100 m and 300 m were more than 5000 km and more than 8000 km, respectively. Given this, the study area was observed to be structurally dense at each of the aforementioned depths. The structural density models were discretized into five classes (very low, low, moderate, moderately high and very high regions), each of which was evaluated to determine their spatial asso ciation with known locations of groundwater occurrences within the study area using the frequency ratio technique. Frequency ratio results for both structural density models derived at 100 m and 300 m depths show the existence of a strong correlation between high structural density model classes and the known groundwater occurrences. The structural density models were further evaluated using the receiver operating character istics curve. The area under the receiver operating characteristics curve scores indicates that, although both structural density models showed very good performance (with receiver operating characteristics scores greater than 0.7), the 300-m depth structural density model performed better than the structural density model generated at a depth of 100 m (with their receiver operating characteristics scores being 0.721 and 0.715, respectively). The obtained results corroborate with literature assertion that groundwater occurrence within the Voltaian basin is mainly associated with structural features. It is expected that the outputs of this study would guide future groundwater exploration programmes within the study area.Item Evaluation of the impact of magnetic feld homogeneity on image quality in magnetic resonance imaging: a baseline quantitative study at 1.5 T(Egyptian Journal of Radiology and Nuclear Medicine, 2023) Manson, E.N.; Mumuni, A.N.; Inkoom, S.; Shirazu, I.Background Magnetic resonance images can be afected in a number of ways by magnetic feld inhomogeneity. The study aimed to optimize the main magnetic feld homogeneity (MFH) by assessing how magnetic feld inho mogeneity afects the signal-to-noise ratio (SNR) and geometric distortion of images acquired along the diameter of a spherical volume phantom from the isocenter of the MRI scanner. Results The MFH ranged between 0.10 and 0.60 ppm. The best MFH and the maximum SNR were determined in the isocenter at 400 mm feld of view with the application of shim. However, for all the phantom positions, geomet rical distortion in images acquired at 200 mm feld of view was generally better and worse at 400 mm feld of view. MFH could be optimized to reduce geometrical distortion and increase SNR by increasing the receiver bandwidth and the number of excitations whiles complementing it with shimming during image acquisition. According to Chi square independent test, there were no signifcant diferences (p>0.05) in the MFH, SNR, and geometrical distortion values. Compared to fndings at higher feld strengths, it was observed that MRI systems of higher feld strengths (greater than 1.5 T) could ofer superior magnetic feld homogeneity and SNR without causing observable geometri cal distortion. Conclusions The optimal feld of view for the fast feld echo (FFE) sequence required to maximize MFH, SNR, and reduce distortion during image acquisition may vary across MRI systems of diferent feld strengths. To determine the appropriate feld of view, the method and results of this study could serve as a guide for medical physicists as part of their routine quality assurance test proceduresItem Low-Cost Sensor Performance Intercomparison, Correction Factor Development, and 2+ Years of Ambient PM2.5 Monitoring in Accra, Ghana(Environmental Science and Technology, 2023) Raheja, G.; Nimo, J.; Quansah, R.; et al.Particulate matter air pollution is a leading cause of global mortality, particularly in Asia and Africa. Addressing the high and wide-ranging air pollution levels requires ambient monitoring, but many low- and middle-income countries (LMICs) remain scarcely monitored. To address these data gaps, recent studies have utilized low-cost sensors. These sensors have varied performance, and little literature exists about sensor intercomparison in Africa. By colocating 2 QuantAQ Modulair PM, 2 PurpleAir PA-II SD, and 16 Clarity Node-S Generation II monitors with a reference-grade Teledyne monitor in Accra, Ghana, we present the first intercomparisons of different brands of low-cost sensors in Africa, demonstrating that each type of low-cost sensor PM2.5 is strongly correlated with reference PM2.5, but biased high for ambient mixture of sources found in Accra. When compared to a reference monitor, the QuantAQ Modulair-PM has the lowest mean absolute error at 3.04 μg/m3 , followed by PurpleAir PA-II (4.54 μg/m3 ) and Clarity Node-S (13.68 μg/m3 ). We also compare the usage of 4 statistical or machine learning models (Multiple Linear Regression, Random Forest, Gaussian Mixture Regression, and XGBoost) to correct low-cost sensors data, and find that XGBoost performs the best in testing (R2 : 0.97, 0.94, 0.96; mean absolute error: 0.56, 0.80, and 0.68 μg/m3 for PurpleAir PA-II, Clarity Node-S, and Modulair-PM, respectively), but tree-based models do not perform well when correcting data outside the range of the colocation training. Therefore, we used Gaussian Mixture Regression to correct data from the network of 17 Clarity Node-S monitors deployed around Accra, Ghana, from 2018 to 2021. We find that the network daily average PM2.5 concentration in Accra is 23.4 μg/m3 , which is 1.6 times the World Health Organization Daily PM2.5 guideline of 15 μg/m3 . While this level is lower than those seen in some larger African cities (such as Kinshasa, Democratic Republic of the Congo), mitigation strategies should be developed soon to prevent further impairment to air quality as Accra, and Ghana as a whole, rapidly growItem Mineral prospectivity mapping over the Gomoa Area of Ghana’s southern Kibi-Winneba belt using support vector machine and naive bayes(Journal of African Earth Sciences, 2023) Forson, E.D.; Amponsah, P.O.Geospatial modeling of mineral prospective regions is essential, owing to its significant contribution towards the development and economic gains of many mineral-endowed countries including, Ghana. Thus, the primary objective of this study is to delineate mineral potential zones in the Gomoa Area of Ghana’s southern Kibi Winneba belt in order to supplement mineral resources in Ghana’s existing mineral prospective zones. To ach ieve the aforementioned objective, researchers generated predictive models characterising gold mineralisation prospects within the study area by employing machine learning techniques comprising support vector machines (SVM) and naive bayes (NB) classifiers on mineral-related conditioning factors. These mineral-related factors (geoscientific thematic layers) were sourced from geophysical, remote sensing, and geological datasets. The resulting mineral prospective models (MPM) produced based on SVM and NB classifiers were exhibited in binary classes (prospective and non-prospective zones). Regions delineated as prospective zones within the study area were, respectively estimated to cover an area extent of 181.62 km2 and 296.02 km2 for the SVM-derived MPM and NB-derived MPM and analogously characterise 22.07% and 35.97% of the study area. The ability of these two models to predict was determined using the area under the receiver operating characteristic curve (AUC). The AUC scores obtained for the SVM-derived MPM and the NB-derived MPM were, respectively, 0.90 and 0.83. Outputs of the AUC scores generally indicate that the two models produced have good accuracy, although the SVM-derived MPM performed better than that of the NB-derived MPM. Thus, the machine learning-based mineral prospectivity models produced in this study are worthy outputs to guide the planning of detailed mineral exploration surveys within the study area.Item The seasonal cycle of cloud radiative effects over Congo Basin based on CERES observation and comparison to CMIP6 models(Elsevier B.V., 2023) Klutse, N.A.B.; Dommo, A.; Fiedler, S.; et al.ABSTRACT This study investigates the seasonal variability of the cloud radiative effects (CREs) over Congo Basin (CB) using 15-year observations from Clouds and the Earth’s Radiant Energy System (CERES) Energy Budget and Filled (EBAF) Ed4.1 level 3b dataset involving CERES and Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on board Terra and Aqua satellites. The relationships between CREs and cloud properties such as total cloud fraction (TCF), cloud top height (CTH), cloud top temperature (CTT) and cloud optical thickness (COT) are checked. An evaluation of Coupled Model Intercomparison Project (CMIP) Phase 6 in capturing the seasonal cycle of CREs as well as the magnitudes of the CREs along the seasonal cycle is also performed. This study shows a net cloud cooling effect of − 8.4 W/m2 and − 43.9 W/m2 respectively at the top of the atmosphere (TOA) and at the surface, leading to a net warming effect of 35.67 W/m2 in the atmosphere. This value implies a large energy source over the Central Africa (CA) atmospheric column. The associated relationships between CREs and cloud properties show that the shortwave CRE is more sensitive to TCF and optical thickness whereas its longwave counterparts is more sensitive to CTH, CTT and COT at the TOA and in the atmosphere. All of the four CMIP6 models used in this study can capture the spatial pattern of CREs as well as their seasonal cycle but misrepresent intensity of CREs. Results also show that a better-simulated TCF considerably reduces the intensity of the annual mean underestimation in both longwave and shortwave CRE for some CMIP6 models, but not for models with overestimated shortwave CRE.Item Adapting to Changing Climate: Understanding Coastal Rural Residents’ Relocation Intention in Response to Sea Level Rise(MDPI, 2023-05) Klutse, A. B.; Adade, R.; Jaiye, D.; et alEx situ adaptation in the form of relocation has become inevitable in some low-lying coastal zones where other adaptation strategies become impractical or uneconomical. Although relocation of coastal low-lying communities is anticipated globally, little is still known about the factors that influence household-level adoption. This study draws on an extended version of Protection Motivation Theory (PMT) to assess the factors influencing the relocation intention of three highly vulnerable coastal rural communities in Ghana. A total of 359 household heads were randomly selected for a questionnaire survey. The study employed binary logistic regression to identify key factors that influence residents’ readiness to relocate. The results indicated that cognitive and compositional factors were more important than contextual factors in explaining the intention to relocate among coastal rural communities in Ghana. However, contextual factors mediated or attenuated the influence of cognitive and compositional factors on relocation intention. Based on the findings, this study advocates for intensive education on the effects of future sea-level rise impacts on communities as well as structural and non-structural measures to improve the socio-economic capacity of rural communities.Item Acoustoelectric direct current density in fluorine doped single-walled carbon nanotubes due to harmonic mixing of bichromatic fields with commensurate frequencies(Diamond & Related Materials, 2023) Sekyi-Arthur, D.; Mensah, S.Y.; Amewode, E.K.; Arthur, R.; Adams, R.R.Herein, we theoretically report on the acoustoelectric direct current (ADC) generation in a non-degenerate fluorine doped single-walled carbon nanotubes (FSWCNTs), due to mixing of waves with commensurate harmonics in the hypersound regime, qℓ≫1 (where q is the acoustic wavenumber and ℓ is the carrier mean free path). The only restriction of the theory on the sound intensity was that, the interaction energy between the carrier and the acoustic phonons must be small in comparison with the characteristic carrier energy. It was observed that in this situation, the higher harmonics of the effective field of the acoustic wave can be neglected; the origin of the nonlinearity was due to the distortion of the distribution function for carriers moving in phase with the phonons, as a result of interaction with the acoustic wave; the nonlinear effects can then be very important. The ADC generated was highly nonlinear and non-ohmic and depended on the amplitude of the bichromatic fields (i.e., pump and probe field), overlapping integral for jumps (Δs and Δz), carrier concentration (no), Bloch frequency (Ω), photon frequency (ω) and acoustic phonon frequency (ωq). The strong nonlinearity and non-ohmicity of the I-V characteristic of the FSWCNTs may be associated with a number of nonlinear phenomena including the non-parabolic band relation, carrier heating due to distortion in carrier distribution function, Stark component, and Bloch oscillations of intraminiband carriers. It was possible to alter the magnitude and direction of the rectified ADC by adjusting the phase of the fields, and the generation of ADC corresponded to even instability zones in the FSWCNTs. Thus, based on the high ADC obtained, we propose FSWCNTs for ADC generation under bichromatic fields with commensurate harmonics.Item Effect of band-gap tuning on absorption of phonons and acoustoelectric current in graphene nanoribbon(Physica E: Low-dimensional Systems and Nanostructures, 2023) Dompreh, K.A.; Sekyi-Arthur, D.; Mensah, S.Y.; Adu, K.W.; Edziah, R.; Amekpewu, M.We report the use of Boltzmann Transport Equation (BTE) in the hypersound regime for investigating the gen eration of acoustoelectric (AE) current in an armchair graphene nanoribbon (AGNR). The AE current obtained was deduced from the absorption due to the Landau damping of quantized sound waves (LD-QSW) energy. By stimulating the AGNR with a non-quantized electric field, the absorption and the AE current were analysed against the frequency, the wavenumber, the width of the bandgap and the drift velocity. The absorption was observed to switch to amplification as the drift velocity was varied. At high drift velocities, the amplitude of the AE current decreases as the band-gap (that depends on the applied electric field) was increased, suggesting a potential use of AGNR in the design of tunable acoustoelectric current devices.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 Potential impact of 1.5 °C and 2 °C global warming on consecutive dry and wet days over West Africa(Environmental Research Letters, 2018) Klutse, N.A.B.; Ajayi, V.O.; Gbobaniyi, E.O.; Egbebiyi, T.S.; Kouadio, K.; Nkrumah, F.; Quagraine, K.A.; Olusegu, C.; Diasso, U.; Abiodun, B.J.; Lawal, K.; Nikulin, G.; Lennard, C.; Dosio, A.We examine the impact of +1.5 ◦C and +2 ◦C global warming levels above pre-industrial levels on consecutive dry days (CDD) and consecutive wet days (CWD), two key indicators for extreme precipitation and seasonal drought. This is done using climate projections from a multi-model ensemble of 25 regional climate model (RCM) simulations. The RCMs take boundary conditions from ten global climate models (GCMs) under the RCP8.5 scenario. We define CDD as the maximum number of consecutive days with rainfall amount less than 1 mm and CWD as the maximum number of consecutive days with rainfall amount more than 1 mm. The differences in model representations of the change in CDD and CWD, at 1.5 ◦C and 2 ◦C global warming, and based on the control period 1971−2000 are reported. The models agree on a noticeable response to both 1.5 ◦C and 2 ◦C warming for each index. Enhanced warming results in a reduction in mean rainfall across the region. More than 80% of ensemble members agree that CDD will increase over the Guinea Coast, in tandem with a projected decrease in CWD at both 1.5 ◦C and 2 ◦C global warming levels. These projected changes may influence already fragile ecosystems and agriculture in the region, both of which are strongly affected by mean rainfall and the length of wet and dry periods.Item A predictive study of heat wave characteristics and their spatiotemporal trends in climatic zones of Nigeria(Modeling Earth Systems and Environment, 2018) Ragatoa, D.S.,; Ogunjobi, K.O.; Okhimamhe, A.A.; Klutse, N.A.B.; Lamptey, B.L.Heat waves (HWs) have always been the silent natural disaster but the most impactful, especially concerning health and agriculture. A crucial question is being asked after the evidence has shown increases in the climate extreme events especially the temperature: how will the future climate conditions be? The present investigation examines and analyzes the future occurrence and trend of HWs in the five climatic zones of Nigeria. WRF model output extracted from CORDEX-Africa for the period 2018–2100 was compiled using maximum and minimum temperatures under RCP4.5 and RCP8.5. Different HW characteristics were studied: the heat wave number, the duration, the frequency, the amplitude and the magnitude exploiting four different definitions, the temperature based 90th percentile thresholds (TN90 and TX90), the Excess Heat Factor (EHF) and the Heat Wave Magnitude Index daily (HWMId). The prediction under the two scenarios RCP4.5 and RCP8.5 has shown a spatial increase in the frequency and magnitude of HWs during different periods. In the 2050s, there will be a spatial increase and also an increase in the duration of HWs in the study area. The HWMId revealed Ultra extreme HWs when the Coastal zone will be having Super extreme HWs. The RCP8.5 revealed more dramatic and dreadful HWs from 2073. The trend showed significant increasing trends in the major parts of the country