The Impact of Local Environment and Neighboring Pollution on the Spatial Variation of Particulate Matter in Chinese Mainland

Abstract

Particulate matter (PM) pollution has caused several environmental problems and damaged human health. To understand the different driving forces of PM2.5 and PM10, we investigated the spatial distribution of PM2.5, PM10, and the ratio of PM2.5 to PM10 (PM2.5/PM10), and simulated how they respond to socioeconomic, natural conditions and pollutant transmission in 336 cities across Chinese mainland in 2017. The results indicated that 35.4% and 49.7% of cities in Chinese mainland satisfied the national level II standard for PM2.5 (35 μg/m3) and PM10 (70 μg/m3), respectively. The average PM2.5/PM10 was 57.5 ± 9.4%, which is a relatively high value across the world. Global spatial regression results revealed that the transport of pollutants emitted from neighboring regions was the most important factor for local PM concentrations, while population density was the dominant local variable. The influence of socioeconomic factors and the neighboring pollution level on PM2.5 was greater than that on PM10, while the effect of precipitation was greater on PM10. Cluster analysis revealed that 336 Chinese cities could be classified into three groups. The regions with a high PM concentration and a high level of social economy were included in Group 1 (G1). Group 2 (G2) was predominantly observed in southern China, while Group 3 (G3) was seen in western China. Furthermore, population density significantly affected the PM in G2 and PM2.5 in G3, and PM levels in G1 and G3 had a sensitive response to the variation in precipitation, especially PM10.