The spatial and temporal variation of fine particulate matter pollution in Ethiopia: Data from the Atmospheric Composition Analysis Group (1998–2019)

Abstract

Background Evidence suggests ambient fine particulate matter (PM2.5) is a risk factor for cardiovascular diseases, lung cancer morbidity and mortality, and all-cause mortality. Countries that implement strong policies are able to reduce ambient PM2.5 concentration. In Ethiopia, however, PM2.5 monitoring stations, laboratory technicians, and equipment are staggeringly limited. In this study, the spatial and temporal variation of PM2.5 in Ethiopia was assessed. Methods Satellite-based PM2.5 estimates, from the year 1998 to 2019, by Atmospheric Composition Analysis Group (ACAG) at a spatial resolution of 0.01° X 0.01° was used. The annual mean PM2.5 concentration for all administrative regions and zones in Ethiopia was extracted. The average mean from the twenty-two years was also calculated. The trend of PM2.5 concentration was graphed and quantitatively calculated using the Mann-Kendall test. The slope of the change over time was estimated using the Theil-Sen slope. At the zonal administration level, for the average annual mean, spatial dependency using univariate Global Moran’s I and clustering and outlier tests using Anselin Local Moran’s were performed. Results The country’s average annual mean PM2.5 concentration was 17 μgm-3. The Afar region had the highest concentration, 27.9 μgm-3. The Mann-Kendall S was positive and significant at p<0.001. The spatial distribution of satellite-based ambient PM2.5 concentration was non-random. Significant highest value clustering of ambient total PM2.5 concentration exists in the Afar, Eastern Tigray, and Eastern and Southeastern Amhara while the significant lowest value dispersing was observed in the Southern Oromia and Somali region. Conclusion At the national and regional levels, the annual mean ambient PM2.5 concentration is beyond the World Health Organization (WHO)-recommended level. The ambient PM2.5 concentration distribution is spatially dependent and significantly clustered in space. Installation of additional ground-based PM2.5 monitoring devices, particularly in regions where PM2.5 concentration is higher, is recommended. Validating satellite-based PM2.5 data with ground-based measurements in the country is also advised.