Spatio-temporal trends and influencing factors of PM2.5 concentrations in urban agglomerations in China between 2000 and 2016.

An urban agglomeration (UA), similar to a megalopolis or a metropolitan area, is a region where cities and people are concentrated, and where air pollution has adversely impacted on sustainable and high quality development. Studies on the spatio-temporal trends and the factors which influence PM2.5 concentrations may be used as a reference to support air pollution control policy for major UAs throughout the world. Nineteen UAs in China covering the years 2000-2016 were chosen as the research object, the PM2.5 concentrations being used to reflect air pollution and being estimated from analysis of remote sensing images. The Exploratory Spatial Data Analysis method was used to study the spatio-temporal trends for PM2.5 concentrations, and the Geodetector method was used to examine the factors influencing the PM2.5 concentrations. The results revealed that (i) the temporal trend for the average values of the PM2.5 concentrations in the UAs followed an inverted U-shaped curve and the inflection points of the curve occurred in 2007. (ii) The PM2.5 concentrations in the UAs exhibited significant global spatial autocorrelation with the high-high type and the low-low type being the main categories. (iii) The rate of land urbanization and the structure of energy consumption were the main factors which influenced the PM2.5 concentrations in the UAs.