RESUMEN

Identification of spatio-temporal variation of PM2.5 related relationships under joint management zones is of great significance for scientifically conducting joint control of air pollution in China. Based on the PM2.5 concentration data of 334 prefecture-level cities in China from 2000 to 2016, from the perspective of air pollution regional linkage control and prevention, this paper systematically analyzes the spatio-temporal variation of PM2.5 related relationships in China using a spatial unit aggregation strategy and geographically and temporally weighted regression. The results show that:① With PM2.5 as the primary pollutant, ten air pollution joint management areas are obtained by considering the degree of pollution, geographical location, meteorology, topography, and economy. ② Geographically and temporally weighted regression can effectively reveal the spatio-temporal non-stationarity of the relationships between PM2.5 concentration and related factors. Meanwhile, population size, secondary industry gross domestic product, SO2 emissions, annual average temperature, annual precipitation, and annual relative humidity are identified as having a significant effect on changes in PM2.5 concentration. ③ The population impacts on PM2.5 concentration in the Beijing-Tianjin-Yunmeng region are the largest of all regions during the period. The influence of the secondary industry's gross domestic product on the PM2.5 concentration in the Sichuan-Yunnan District is the most variable. Apart from these values in the northeast of China, the regression coefficient values of SO2 emissions first decrease with time, then increase, and then decrease again. The time variability of the average annual temperature of each treatment area to PM2.5 is small. The influences of annual precipitation and annual average relative humidity on PM2.5 present different variability characteristics in each region.