A novel framework for decomposing PM2.5 variation and demographic change effects on human exposure using satellite observations

Abstract

Human exposure to PM2.5, represented by population-weighted mean PM2.5 concentration (cρ), declines under three conditions: (1) mean PM2.5 concentration declines, (2) PM2.5 concentration within urban areas goes through more of a decrease than within rural areas, or (3) city planning relocates people into cleaner areas. Decomposing these effects on human exposure is essential to guide future environmental policies. The lack of ground PM2.5 observations limits the assessment of human exposure to PM2.5 over China. This study proposed a novel diagnostic framework using satellite observations to decompose the variation in cρ resulting from change in the mean PM2.5 concentration, spatial difference in PM2.5 change, and demographic change. In this framework, we decomposed cρ into mean PM2.5 concentration (c0) and pollution-population-coincidence induced PM2.5 exposure (PPCE). We then used this framework to decompose the variation in cρ over China within three recent Five-Year Plans (FYPs) (2001–2015). The results showed that the decline in c0 reduced cρ in most provinces within the eleventh and twelfth FYPs. The spatial difference in PM2.5 change reduced the PPCE and cρ in most provinces within the tenth and twelfth FYPs, with the most substantial reduction rate of −3.64 μg m−3·yr−1 in Tianjin within the twelfth FYP. Rural-to-urban migration resulting from rapid urbanization, however, increased the PPCE and cρ (by as much as 0.22 μg m−3·yr−1) in all provinces except Taiwan within all three FYPs. The demographic change reduced cρ in Taiwan because of the migration of population into less polluted areas. To better reduce human exposure, it is recommended that control efforts further target populous residential areas and urbanization planning relocates people into less polluted areas. Our decomposition framework paves a new way to decompose the human exposure to other air pollutants in China and other regions.