Spatial and seasonal analysis of aerosol optical depth distribution in selected cities of West Africa

A prominent factor used in evaluating aerosol content and air quality is the Aerosol Optical Depth. Cities in Africa remain vulnerable to environmental issues such as air pollution since there are few appropriate control mechanisms and infrequent routine monitoring due to social, technological, and financial issues. This paper analyzes the Aerosol Optical Depth (AOD) dataset of fifty-five locations in West Africa (2010–2020) using geographic information system software (QGIS). It is observed that the AOD values have a varying spatial pattern signifying that the source of high AOD diffused due to rainfall and wind dynamics. The spatial analysis shows that AOD over West Africa is consistently increasing over the years (2019–2020) showing four locations (south-south Nigeria, coastal Mauritania, northern Mali, and coastal Sierra Leone) with reasonably high AOD values. The AOD dispersion in these four locations is consistent with AOD values of > 0.4. These four cities with little fluctuations in their aerosol load are most likely having their sources of AOD from nature, which hardly changes on timescales of a year or season. The seasonal analysis shows higher mean values of AOD (0.30 ≤ AOD ≤ 0.80) occurring during the winter across all the cities studied with the highest numbers reported in Kanema City of Sierra Leone and the least mean values (0.20 ≤ AOD ≤ 0.40) during the summer occurring in Ngaoundere city of Cameroon and all the Liberian cities. Strong and positive correlations are observed between Portonovo/Kumasi, Lome/Kumasi, Bondouke/Bouake, and Praia/Santiago with R2 values ranging from 0.8 to 1.0. Weaker correlations are reported at Kandi/Fderik, Bonfara/Fderik, Soma/Accra, and Banjul/Accra, all with R2 values ranging from 0.0001 to 0.002. Determining the fundamental common causes of air pollution in West Africa can be greatly aided by the AOD correlations provided. This may help reduce the time required to address episodes of air pollution at the regional level because communities may utilize the data to create more targeted air pollution programs and provide citizens with better guidance on what to do in the event of major air pollution incidents or disasters.