Spatial-temporal evolution characteristics of PM and its driving mechanism: spatially explicit insights from Shanxi Province, China.

In China, despite the fact that the atmospheric environment quality has continued to improve in recent years, the PM pollution still had not been controlled fundamentally and its driving mechanism was complex which remained to be explored. Based on the 1-km ground-level PM datasets of China from 2000 to 2020, this study combined spatial autocorrelation, trend analysis, geographical detector, and multi-scale geographically weighted regression (MGWR) model to explore the spatial-temporal evolution of PM in Shanxi Province and revealed its complex driving mechanism behind this process. The results reflected that (1) there was a pronounced spatial clustering of PM concentration within Shanxi Province, with PM concentrations decreasing from southwest to northeast. From 2000 to 2020, the levels of PM pollution demonstrated a decline over time, with its concentrations decreasing by 9.15 µg/m overall. The Hurst exponent indicated a projected decrease in PM concentrations in the central and northern areas of Shanxi Province, contrasting with an anticipated increase in other regions. (2) The geographical detector indicated that all drivers had significant influences on PM concentrations, with meteorological factors exerting the greatest effects then followed by human activity and vegetation cover showing the least effects. (3) Both gross domestic product and population density exhibited positive correlations with PM concentration, while vegetation fractional cover, wind speed, precipitation, and elevation exerted negative influences on PM concentration all over the space. This study enriched the research content and ideas on the driving mechanism of PM and provided a reference for similar studies.