Quantifying the effects of local determinants and geocomplexity on PM <scp>2.5</scp> spatial patterns

Fine particulate matter (PM2.5) across China exhibits significant spatial heterogeneity and highly complex spatial patterns. Existing studies have primarily focused on the global scale, with limited attention to local variations and the contribution of spatial patterns to PM2.5 variations. To address these limitations, this study integrates the local indicator of stratified power (LISP) model with geocomplexity to simultaneously identify locally varying determinants of PM2.5 and capture the spatial patterns shaping its regional distribution. The results show that LISP yields higher explanatory power than the optimal parameters-based geographical detector (OPGD). The mean determinant power increased by 0.362, and higher determinant power was observed for 17 of the 18 factors. Geocomplexity indicators constitute 50% of the top ten dominant factors and provide spatial structural information beyond conventional variable-based descriptions. The spatial stratified heterogeneity of PM2.5 determinants demonstrated significant regional disparities, with western China characterized by dispersion-related controls and other regions showing increasing importance of spatial-structural and anthropogenic regulation. PM2.5 regulation has shifted toward a regionally differentiated pattern dominated by dispersion processes, effectively captured by spatial structure indicators. These findings improve the understanding of the spatial determinants of PM2.5 across China and provide a basis for differentiated PM2.5 control strategies.