| 2 | Regional variation of urban air quality in China and its dominant factors显示文摘It is of great theoretical and practical importance to carry out research on the spatio-temporal evolution of urban air pollution and its driving forces,which helps to facilitate a deeper understanding of the mutual feedback mechanisms between the urban environment and socio-economic systems.Comprehension of these mechanisms will contribute to the design and implementation of efficient environmental policies that ultimately will improve the quality of urbanization development.This paper illustrates the spatio-temporal evolutionary characteristics of six urban ambient air pollutant concentrations,namely,CO,NO_(2),O_(3),PM_(10),PM_(2.5),SO_(2),in 286 sample cities above the prefecture level in China from 2014 to 2019.The interactions between the pollutant concentrations are analyzed based on panel regression models.A random forest model is then employed to explore the correlations between the concentrations of these six pollutants and 13 natural and socio-economic impact factors to isolate the most crucial ones.The results reveal three aspects.First,within the research period,the average annual concentration of O_(3)increased while that of other pollutants decreased year by year.Second,there were significant interactions between concentrations of the six pollutants,leading to obvious compound air pollution in urban areas.Third,the impact of natural and socio-economic factors on urban air quality varied greatly among different air pollutants,with air temperature,vegetation coverage,urbanization level and traffic factors ranking high and the different response thresholds to the dominant influencing factors.In light of the limited ability of humans to control the natural environment and meteorological conditions,it is recommended that urban air quality be further improved by optimizing urban density,controlling anthropogenic emission sources,and implementing strict air pollution prevention and control measures. | ZHAO Yanyan ZHANG Xiaoping CHEN Mingxing GAO Shanshan LI Runkui | 2022 | Journal of Geographical Sciences2022，32，5： | 0 |
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