Spatial and Temporal Heterogeneity of Air Pollution in East Africa

East Africa's air pollution levels are deteriorating due to biomass burning and unfavorable weather conditions. This study investigates spatiotemporal changes in air pollution and quantitatively explores relative contributions of potential influencing factors and their interactions with air pollution dynamics in East Africa from 2001 to 2021. The result revealed that  air pollution effect experienced an increasing (decreasing) trend in PHS (PCS) with values of -5.415E-4 (3.157E-4) from 2001-2021. The major pollution seasons (HPL1 and HPL2) were correlated with wildfire seasons (DJF and JJA). At an annual scale, spatial OLS analysis between air pollution and 14 response factors found that percentage increase in BA, BCS, OCS, SOS, and DSC would worsen air pollution. In contrast, negative spatial OLS coefficients of SS, P, RH, WS, SLP, NDVI, PD, and ELV suggest that air pollution would decrease with increase of these variables. The variance presented in ascending order based on their influence is given by DSC(R2=68.93) > SLP(R2=36.59) > RH(R2=24.12) > T(R2=23.78) > SOS(R2=23.16) > BA(R2=20.30) > ELV(R2=7.80) > OCS(R2=4.48) > NDVI(R2=3.21) > BCS(R2=3.04) > WS(R2=2.89) > PD(R2=0.66) > SS(R2=0.55) > P(R2=0.50). The factor interaction detector analysis revealed that DSC (q = 0.681), SOS (q = 0.389), TMP (q = 0.324), and SLP (q = 0.472) showed significant high response power at an annual scale, among all factors that have significant influences on air pollution in the study area. NDVI (q = 0.096), PD (q = 0.012), BCS (q = 0.054), SS (q = 0.078), P (0.093), and OCS (q=0.086) had the least influence on air pollution, which is consistent with the results of the correlation analysis. In conclusion, the study covered the dynamics of air pollution and their influencing factors, spatiotemporal heterogeneity, and interaction between influencing factors. All this put together can help in providing timely management strategies to combat air pollution.