Spatiotemporal Variation Characteristics of Near-Surface Pollutants and Their Meteorological Influencing Factors in Anhui Province from 2015 to 2024

Based on hourly observational data from 38 air quality monitoring stations in 9 cities and counties in Anhui Province from 2015 to 2024, along with concurrent meteorological data, this study systematically analyzed the spatiotemporal evolution characteristics of PM?.?, PM??, SO?, NO?, O?, CO, and AQI, as well as their meteorological influencing factors. The results show that over the past decade, air quality in Anhui Province has significantly improved, with annual average concentrations of AQI and most pollutants continuously declining, except for O?, which exhibited an upward trend. Further analysis revealed that O? displays a latitudinal distribution pattern of "higher in the south and lower in the north," with the magnitude of increase gradually growing as latitude decreases.In terms of seasonal variations, different pollutants exhibited distinct patterns. Specifically, particulate matter such as PM?.? and PM??, as well as gaseous pollutants like SO?, NO?, and CO, all showed higher concentrations in winter and lower concentrations in summer, primarily due to increased heating emissions and worsened atmospheric diffusion conditions in winter. In contrast, O? concentrations followed an opposite seasonal pattern, peaking in summer (82.3 μg/m3) and reaching their lowest levels in winter (43.2 μg/m3), reflecting the significant influence of photochemical reactions on O? formation. Regarding diurnal variations, particulate matter exhibited a typical "bimodal" distribution, closely linked to traffic peaks during morning and evening rush hours and boundary layer changes, whereas gaseous pollutants mostly displayed a "unimodal" pattern. Analysis of meteorological factors revealed significant correlations between pollutant concentrations and weather conditions. First, MDA8-O? showed significant negative correlations with CO (r = -0.256), PM?.? (r = -0.233), and NO? (r = -0.208) (p < 0.01). Second, all pollutants exhibited significant negative correlations with wind speed (p < 0.01), with NO? showing the strongest correlation (r = -0.338). This relationship was particularly pronounced in cities along the Yangtze River, such as Wuhu (r = -0.50), Tongling (r = -0.47), and Anqing (r = -0.41), likely due to the local terrain"s wind channel effect, where higher wind speeds significantly improved pollutant dispersion. Additionally, relative humidity (RH) also had a notable impact on pollutant concentrations. Most pollutants showed moderate negative correlations with RH (p < 0.01). Notably, when RH exceeded 75%, O? concentrations decreased rapidly with increasing humidity.