Spatio-temporal variation and impact factors analysis of satellite-based aerosol optical depth over China from 2002 to 2015

- We identify spatio-temporal trends of AOD in China and over five typical regions.
- We quantify the relationship between AOD variation and plausible impact factors.
- Transition from upward to downward beginning 2008 dominates the overall AOD trend.
- YRD and April were respectively the most severely polluted, spatially and temporally.
- Terrain and population show strong relationships with AOD but NDVI fails.

Air quality in China, especially the concentration of particles suspended in the atmosphere, is increasingly affecting the country's climate, the health of communities and even policy-makers. Satellite-derived aerosol optical depth (AOD) data provide an alternative means of analysing fine-scale aerosol variations over the entire of China, thus overcoming the limitations of the sparse network of ground-level measurements. This study used moderate resolution imaging spectrometer data at 550 nm to investigate the variation in and factors affecting AOD over a 3-km grid for the entire of China, and five typical regions in particular. Spatial and temporal data from 2002 onwards were used. The high aerosol loadings were usually located in the economically and industrially developed areas of eastern and southern China, especially over the five typical regions, whereas the low aerosol loadings were located in the rural and less developed areas of western and northeastern China. A notable transition dominated the long-term overall trend in the AOD: an upward tendency (+0.0003) pre-2008 followed by a downward tendency (−0.0005) post-2008. The seasonally averaged AOD reached its maximum in spring (AOD of about 0.41), followed by summer (0.37), winter (0.34) and autumn (0.26). AOD was negatively associated with terrain and positively associated with socio-economic activities over the entire country, consistent with the regional correlations. However, the effect of vegetation on AOD exhibited large spatial and temporal heterogeneity, as indicated by the weak relationship between AOD and the Normalized Difference Vegetation Index. The multiple linear regression results indicated that of the 10 indices, elevation and population were the main factors influencing aerosol variation.