Spatial Variation of the Relationship between PM(2.5) Concentrations and Meteorological Parameters in China

Epidemiological studies around the world have reported that fine particulate matter (PM(2.5)) is closely associated with human health. The distribution of PM(2.5) concentrations is influenced by multiple geographic and socioeconomic factors. Using a remote-sensing-derived PM(2.5) dataset, this paper explores the relationship between PM(2.5) concentrations and meteorological parameters and their spatial variance in China for the period 2001–2010. The spatial variations of the relationships between the annual average PM(2.5), the annual average precipitation (AAP), and the annual average temperature (AAT) were evaluated using the Geographically Weighted Regression (GWR) model. The results indicated that PM(2.5) had a strong and stable correlation with meteorological parameters. In particular, PM(2.5) had a negative correlation with precipitation and a positive correlation with temperature. In addition, the relationship between the variables changed over space, and the strong negative correlation between PM(2.5) and the AAP mainly appeared in the warm temperate semihumid region and northern subtropical humid region in 2001 and 2010, with some localized differences. The strong positive correlation between the PM(2.5) and the AAT mainly occurred in the mid-temperate semiarid region, the humid, semihumid, and semiarid warm temperate regions, and the northern subtropical humid region in 2001 and 2010.