PM2.5 Sink-Source Dichotomy in Urban Clusters: Land Cover Efficiency Gradients and Socio-Meteorological Interactions

Urban clusters face escalating atmospheric challenges, with elevated PM2.5 concentrations representing a critical environmental constraint. This study investigates spatiotemporal evolution mechanisms of PM2.5 within China’s Taiyuan-Yuci-Xinzhou (TYX) urban cluster. Daily PM2.5 concentrations (July–September 2000–2020) characterized spatiotemporal distributions. The Urban Forest Effects (UFORE) model integrated multisource data—remote sensing, leaf area index (LAI), wind speed, and precipitation—within a Geographically and Temporally Weighted Regression (GTWR) framework, quantifying PM2.5 dry deposition across land cover types and identifying drivers. Key findings reveal the following: (1) PM2.5 concentrations followed an initial-rise-then-decline trajectory, with pollution hotspots concentrated in Taiyuan City and neighboring industrial corridors; (2) Construction lands sprawl markedly elevated PM2.5 levels, whereas green areas and agricultural lands expansion promoted deposition; water areas exhibited no significant effect; (3) Wind speeds and precipitation positively modulated PM2.5 in green areas and agricultural lands, contrasting with NDVI’s negative influence; elevation showed null correlation, while agricultural lands deposition correlated positively with PM2.5; (4) GDP displayed an inverted U-curve association with PM2.5; positive correlations emerged with AVSI, TIOV, NOP, and EC indices, but negative linkage with TOC. This clarifies land cover impacts on urban atmospheric particulates, providing empirical foundations for pollution control.