Abstract: Based on hourly observational data from 48 air quality monitoring stations in nine 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_2.5, PM₁₀, SO₂, NO₂, O₃, CO, and the Air Quality Index (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 a continuous decline in AQI and the annual average concentrations of most pollutants, except for O₃, which exhibited an upward trend. Further analysis revealed that O₃ exhibited a latitudinal distribution pattern with higher concentrations in the south and lower concentrations in the north, with the rise gradually increasing toward lower latitudes. In terms of seasonal variations, different pollutants exhibited distinct patterns. Specifically, particulate matter such as PM₂.₅ and PM₁₀, as well as gaseous pollutants such as SO₂, NO₂, and CO, showed higher concentrations in winter and lower concentrations in summer. This was primarily due to increased heating emissions and worsened atmospheric diffusion conditions in winter. In contrast, O₃ concentrations followed an opposite seasonal pattern, peaking in summer (82.3 μg m⁻³) and reaching their lowest levels in winter (43.2 μg m⁻³), reflecting the significant influence of photochemical reactions on O₃ formation. In terms of 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 followed a unimodal pattern. Analysis of meteorological factors revealed significant correlations between pollutant concentrations and weather conditions. First, the maximum daily 8-h average ozone (MDA8-O₃) showed significant negative correlations with CO (r = −0.251), PM_2.5 (r = −0.230), and NO₂ (r = −0.166) (p<0.01). Second, all pollutants exhibited significant negative correlations with wind speed (p<0.01), with NO₂ showing the strongest correlation (r = −0.361). This relationship was markedly 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 wind channel effect of the local terrain, where higher wind speeds significantly improved pollutant dispersion. Additionally, Relative Humidity (RH) had a notable impact on pollutant concentrations. Most pollutants showed moderate negative correlations with RH (p<0.01). Notably, when RH exceeded 75%, the O₃ concentrations decreased rapidly with increasing humidity.