Characteristic and Driving Factors of Aerosol Optical Depth over Mainland China during 1980-2017

Since the reform and opening up of China, the increasing aerosol emissions have posted great challenges to the country’s climate change and human health. The aerosol optical depth (AOD) is one of the main physical indicators quantifying the atmospheric turbidity and air pollution. In this study, 38-years (1980–2017) of spatial and temporal variations of AOD in China were analyzed using AOD records derived from MODIS atmosphere products and the MERRA-2 dataset. The results showed that the annual mean AOD values throughout China have gone through an increasing, but fluctuating, trend, especially in 1982 and in 1992 due to two volcano eruptions; the AOD values experienced a dramatically increasing period during 2000–2007 with the rapid economic development and “population explosions” in China/after 2008, the AOD values gradually decreased from 0.297 (2008) to 0.257 (2017). The AOD values in China were generally higher in spring than that in other seasons. The Sichuan Basin has always been an area with high AOD values owing to the strong human activity and the basin topography (hindering aerosol diffusions in the air). In contrast, the Qinghai Tibet Plateau has always been an area with low AOD values due to low aerosol emissions and clear sky conditions there. The trend analysis of AOD values during 1980–2017 in China indicated that the significant increasing trend was mainly observed in Southeastern China. By contrast, the AOD values in the northernmost of China showed a significant decreasing trend. Then, the contributions (AODP) of the AOD for black carbon aerosol (BCAOD), dust aerosol (DUAOD), organic carbon aerosol (OCAOD), sea salt aerosol (SSAOD), and SO4 aerosol (SO4AOD) to the total AOD values were calculated. The results showed that DUAOD (25.43%) and SO4AOD (49.51%) were found to be the main driving factors for the spatial and temporal variations of AOD values. Finally, the effects of anthropogenic aerosol emissions, socioeconomic factors, and land-use and land coverage changes on AOD were analyzed. The GDP, population density, and passenger traffic volume were found to be the main socioeconomic drivers for AOD distributions. Relatively larger AOD values were mainly found in urban land and land covered by water, while lower AOD values were found in grassland and permanent glacier areas.