Temporal and spatial distribution of PM _2.5 in the Xinjiang region based on AOD fusion data and the GTWR model

By integrating MODIS aerosol optical depth data and combining it with ground-based PM2.5 measurements and meteorological data, a geographically and temporally weighted regression (GTWR) model was used to estimate the spatiotemporal distribution of PM2.5 in Xinjiang in 2022. Findings include the following: (1) The GTWR model effectively represents PM2.5 distributions, with a correlation coefficient of 0.92, surpassing the geographically weighted regression model by 5.7% and the land use regression model by 9.5%. (2) Monthly PM2.5 levels in Xinjiang exhibit a pattern of initial decline followed by an increase. Elevated coal-fired heating in February and high air humidity in July contribute to higher atmospheric particulate concentrations. The peak monthly average concentration reaches 79.05 µg m−3 in February, and the lowest concentration drops to 33.86 µg m−3 in July. (3) Influenced by dust-prone conditions and atmospheric diffusion in the Taklimakan Desert region, PM2.5 levels in Xinjiang show a notable southwest-to-northeast gradient.