It is of great significance for joint prevention and control of air pollution to understand the spatial and temporal differentiation characteristics and regional driving factors of PM2.5 in China. In this study, from a multi-scale perspective, the spatial pattern analysis and geographical detectors are used to explore the spatial and temporal distribution pattern and causes of PM2.5 pollution in China mainland from 2011 to 2017. The results show that:① the annual average PM2.5 concentration is relatively stable from 2011 to 2017, and there is no obvious trend. The change characteristics of regional PM2.5 are similar to those of national PM2.5, showing a "W" shaped fluctuation. Overall, the order of pollution degree from high to low is:central, eastern, western, and northeastern. ② From the spatial pattern analysis results, we can see that the high-value cluster mainly appears in east China, middle China, and southwest of Xinjiang, while the low-value cluster appears in Qinghai-Tibet, Yunnan, Guizhou, Plateau, and Daxinganling regions. ③ The results of geographic detector analysis show that the population factor is the leading factor nationally; meanwhile, the industrial, energy consumption, and traffic factors all contribute to the distribution pattern of PM2.5 in varying degrees. Regionally, besides the population factor, the proportion of secondary production and urban green space rate have the greatest impact on the northeast, the industrial smoke and dust and road area in the east, and the total industrial electricity and buses in the central area. The impact of social and economic factors does not significantly affect the PM2.5 in the western region.
Keywords: PM2.5; air pollutant; geographical detector; local autocorrelation; spatial-temporal differentiation.