The seasonal characteristics and spatial distribution of PM2.5 in China

In this paper, Geographic Information System (GIS) technology combined with spatial statistics analysis was used for research on the distribution of fine particulate matter (PM_2.5) in different seasons. The surface of PM_2.5 was obtained by using Inverse distance weighting (IDW). Mean center, Standard deviational ellipse, and G index were used to describe discrete tendency and central tendency and spatial autocorrelations from macro and micro perspectives. The results showed seasonal change influences the change of mean center location in Henan province. East and most northeast regions in China have always had severe pollution. The distribution of PM_2.5 is high cluster pattern on the whole. Local areas show low clusters in spring and summer. From the view of spatial autocorrelation, we should take regional cooperation to treat and control PM_2.5 pollution.