Regional variation of urban air quality in China and its dominant factors

Research on the spatiotemporal evolution of urban air pollution and its driving forces has great theoretical and practical significance because it helps to deeply understand the mutual feedback mechanism between urban environment and socio-economic system and improve the efficiency of environmental governance. This paper illustrated the regional evolution characteristics of six urban ambient air pollutants, namely, CO, NO2, O3_8h, PM10, PM2.5, and SO2, in 286 sample cities at the prefecture level in China from 2014 to 2019, starting from the year when the "Air Pollution Prevention and Control Action Plan" was fully implemented in China. The interactions between the concentrations of each pollutant were then analyzed on the basis of panel regression models. Furthermore, random forest model was employed to explore the correlations between concentrations of these six pollutants and thirteen natural and socio-economic impact factors so as to sort out crucial ones. The results are shown in three aspects. First, the average annual concentration of O3_8h increased while that of the other urban ambient air pollutants decreased year by year, among which SO2 concentration decreased the most. Although the typical heavy pollution areas had shrunk, cities in the Beijing-Tianjin-Hebei region, Shandong Peninsula region, Shanxi Province, and Henan Province still have witnessed relatively high concentrations of air pollutants. Second, there was a significant interaction between concentrations of these six pollutants, indicating that comprehensive measures for urban air pollution prevention are necessary. Third, the impact of natural factors and socio-economic factors on urban air quality varied greatly towards different air pollutants, together with a nonlinear response relationship with the pollutant concentrations. Within the selected five natural factors of temperature, precipitation, wind speed, humidity and NDVI, the urban annual average temperature had the strongest correlation with air pollutant concentrations, followed by NDVI. Among the eight selected socio-economic factors, the level of land urbanization and the proportion of secondary production were the two leading drivers of the urban air pollution, followed by the total power consumption and traffic factors. Besides, partial dependence model was used to further analyze the response threshold of different pollutant concentrations to the dominant influencing factors. In consideration of the limited ability of human to control the physical environment and meteorological conditions, it is recommended that urban air quality should be further effectively improved by means of the optimization of urban density, the control of man-made emission sources, and the implementation of strict air pollution prevention and control measures. © 2021, Science Press. All right reserved.