PM2.5 pollution is an environmental issue caused by multiple natural and socioeconomic factors, presenting with significant spatial disparities across mainland China. However, the determinant power of natural and socioeconomic factors and their interactive impact on PM2.5 pollution is still unclear. In the study, the GeogDetector method was used to quantify nonlinear associations between PM2.5 and potential factors. This study found that natural factors, including ecological environments and climate, were more influential than socioeconomic factors, and climate was the predominant factor (q = 0.56) in influencing PM2.5 pollution. Among all interactions of the six influencing factors, the interaction of industry and climate had the largest influence (q = 0.66). Two recognized major contaminated areas were the Tarim Basin in the northwest region and the eastern plain region; the former was mainly influenced by the warm temperate arid climate and desert, and the latter was mainly influenced by the warm temperate semi-humid climate and multiple socioeconomic factors. The findings provided an interpretation of the influencing mechanisms of PM2.5 pollution, which can contribute to more specific policies aimed at successful PM2.5 pollution control and abatement.
Keywords: GeogDetector; Interaction effect; Natural and socioeconomic factors; PM(2.5).
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