<p>Air pollution has become a significant environmental issue affecting ecological security and human health. However, air pollution in urban areas is complex and investigations at small scales are still lacking. To reveal the spatial and temporal evolution patterns and driving mechanisms of air pollution in urban areas, in this study, the characteristics of spatial and temporal dynamics of six major air pollutants (SO₂, NO₂, CO, O₃, PM_2.5, and PM₁₀) were characterized using statistical analysis and Moran’s index based on the 2018–2023 monitoring station data with Tianshui City as the study area, and the driving relationships between each pollutant and natural and anthropogenic factors were explored using the Geodetector model. The results showed that, the main pollutants in Tianshui City during the study period were PM_2.5 and PM₁₀, with multi-year average concentrations of 30.52&#xa0;µg/m³ and 66.63&#xa0;µg/m³. Except for O₃, all pollutants exhibited a decreasing trend. Pollutant concentrations generally pronounced significant seasonal variations (high in winter and low in summer) and clear spatial heterogeneity. GDP had the greatest influence on the concentration of air pollutants in Tianshui City, showing high explanatory power for PM_2.5 (q = 0.0762), PM₁₀ (q = 0.1517), NO₂ (q = 0.5237), SO₂ (q = 0.5202) and CO (q = 0.3505), and POP had the strongest explanatory power for O₃ concentration (q = 0.3583). And GDP together with other factors showed significant enhancement effects. In addition, precipitation, wind speed, and relative humidity also had a greater impact on air pollutants in Tianshui City. Overall, economic development and meteorological conditions jointly drived the spatiotemporal variation of air pollution in Tianshui City. This study can provide a theoretical basis for regional air pollution management and a reference for sustainable urban development and environmental policy formulation.</p>