<p>Particulate matter (PM) plays a crucial role in atmospheric processes, significantly impacting air quality, climate, and human health across Africa. The present study identified five distinct regions: Western, Northern, Central, Eastern and Southern Africa, each exhibiting unique PM bin characteristics and sources. This study employed the multispectral data from Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) to characterize and apportion PM sources across the continent in five bins; Bin1 to Bin5. While, AERONET sun-photometry served as a validation tool at 440 nm, 500 nm and 675 nm, offering high-quality ground-based measurements. The validation of MERRA-2 model AOD data with ground-based AERONET measurements showed low<InlineEquation ID="IEq1"> <EquationSource Format="TEX">\(\:<0.5\)</EquationSource> </InlineEquation>, moderate <InlineEquation ID="IEq2"> <EquationSource Format="TEX">\(\:0.5<r<0.75\)</EquationSource> </InlineEquation> and strong <InlineEquation ID="IEq3"> <EquationSource Format="TEX">\(\:>0.75\:\)</EquationSource> </InlineEquation>correlation coefficients, indicating reliable data for regional PM analysis. Further, on source apportionment, analysis identifies major PM sources, including Sahara dust, biomass burning, and urban pollution (<InlineEquation ID="IEq4"> <EquationSource Format="TEX">\(\:>\)</EquationSource> </InlineEquation>0.0024<InlineEquation ID="IEq5"> <EquationSource Format="TEX">\(\:{\upmu\:}\text{g}{m}^{-2}{s}^{-1}\)</EquationSource> </InlineEquation>), highlighting the implications of air pollution on human health. Notably, the Bodele Depression in Chad emerged as a dominant dust emission hotspot, contributing significantly to transboundary dust transport. The contributions of each PM dust bin over the five African regions followed a similar pattern with <InlineEquation ID="IEq6"> <EquationSource Format="TEX">\(\:{\text{P}\text{M}}_{10}\:\)</EquationSource> </InlineEquation>posting approximately 50% over all regions. However, the PM matter was noted to be high over the Northern and Western regions of Africa attributed to Sahara desert where dust storms are dominant. Basing on the findings, there is urgent need to integrate advanced data technologies into future atmospheric and environmental studies by adopting high resolution multispectral and hyper spectral remote sensing and machine learning-driven source apportionment. An effective air quality management policies should focus on mitigating dust emissions in high-risk areas such as Northern Africa and the Sahel Also, there is need to strengthen observational networks across Africa especially in regions with complex aerosol interactions that are critical in refining air quality management strategies.</p> Graphical Abstract <p>Based on the graphical outline, this study was conducted over the five regions of Africa, segmented into five major regions: Northern, Western, Central, Eastern, and Southern Africa to determine the spatiotemporal variability and source Apportionment of PM matter. The abstract presents the analysis of dust across the study domain, utilizing MERRA-2 datasets to evaluate regional variability in PM distribution. This work captures complex spatiotemporal variability in PM matter. The total dust over various regions were evaluated based on sized bins starting with bin1, 2 3 4 and bin5 using linear regression at pixel wise to determine the spatial trends. The Northern Africa shows high PM source concentrations with color gradient scale ranging from 0 μgm^(-2) s^(-1) to 0.002μgm^(-2) s^(-1), particularly over Algeria and Libya, which is indicative of intense Saharan dust activity. In Western Africa, moderate to high values appear across the Sahel, pointing to dust transport and seasonal biomass burning. Further, Central Africa reveals significant PM hotspots, especially in the north, possibly due to widespread biomass burning or urban emissions. East Africa displays localized zones of elevated PM, likely linked to agricultural burning and urbanization. In Southern Africa, PM levels are generally lower, with slight increases in the northwest, suggesting minor regional sources or long-range transport. A concise summary of the principal results, presented in the abstract highlights the key takeaways while a clear call to action is encouraged to the readers to delve deeper into the full manuscript.</p>

Spatiotemporal Variability and Source Apportionment of Particulate Matter (PM) Emissions Using Binned Size Distributions: Insights from MERRA-2 Over Africa

期刊论文
发表日期：

2025年4月30日

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Geoffrey W. Khamala,
John W. Makokha

摘要

Particulate matter (PM) plays a crucial role in atmospheric processes, significantly impacting air quality, climate, and human health across Africa. The present study identified five distinct regions: Western, Northern, Central, Eastern and Southern Africa, each exhibiting unique PM bin characteristics and sources. This study employed the multispectral data from Modern-Era Retrospective analysis for Research and Applications, Version 2 (MERRA-2) to characterize and apportion PM sources across the continent in five bins; Bin1 to Bin5. While, AERONET sun-photometry served as a validation tool at 440 nm, 500 nm and 675 nm, offering high-quality ground-based measurements. The validation of MERRA-2 model AOD data with ground-based AERONET measurements showed low \(\:<0.5\) , moderate \(\:0.5<r<0.75\) and strong \(\:>0.75\:\) correlation coefficients, indicating reliable data for regional PM analysis. Further, on source apportionment, analysis identifies major PM sources, including Sahara dust, biomass burning, and urban pollution ( \(\:>\) 0.0024 \(\:{\upmu\:}\text{g}{m}^{-2}{s}^{-1}\) ), highlighting the implications of air pollution on human health. Notably, the Bodele Depression in Chad emerged as a dominant dust emission hotspot, contributing significantly to transboundary dust transport. The contributions of each PM dust bin over the five African regions followed a similar pattern with \(\:{\text{P}\text{M}}_{10}\:\) posting approximately 50% over all regions. However, the PM matter was noted to be high over the Northern and Western regions of Africa attributed to Sahara desert where dust storms are dominant. Basing on the findings, there is urgent need to integrate advanced data technologies into future atmospheric and environmental studies by adopting high resolution multispectral and hyper spectral remote sensing and machine learning-driven source apportionment. An effective air quality management policies should focus on mitigating dust emissions in high-risk areas such as Northern Africa and the Sahel Also, there is need to strengthen observational networks across Africa especially in regions with complex aerosol interactions that are critical in refining air quality management strategies.

Graphical Abstract

Based on the graphical outline, this study was conducted over the five regions of Africa, segmented into five major regions: Northern, Western, Central, Eastern, and Southern Africa to determine the spatiotemporal variability and source Apportionment of PM matter. The abstract presents the analysis of dust across the study domain, utilizing MERRA-2 datasets to evaluate regional variability in PM distribution. This work captures complex spatiotemporal variability in PM matter. The total dust over various regions were evaluated based on sized bins starting with bin1, 2 3 4 and bin5 using linear regression at pixel wise to determine the spatial trends. The Northern Africa shows high PM source concentrations with color gradient scale ranging from 0 μgm^(-2) s^(-1) to 0.002μgm^(-2) s^(-1), particularly over Algeria and Libya, which is indicative of intense Saharan dust activity. In Western Africa, moderate to high values appear across the Sahel, pointing to dust transport and seasonal biomass burning. Further, Central Africa reveals significant PM hotspots, especially in the north, possibly due to widespread biomass burning or urban emissions. East Africa displays localized zones of elevated PM, likely linked to agricultural burning and urbanization. In Southern Africa, PM levels are generally lower, with slight increases in the northwest, suggesting minor regional sources or long-range transport. A concise summary of the principal results, presented in the abstract highlights the key takeaways while a clear call to action is encouraged to the readers to delve deeper into the full manuscript.