Volume 29 Issue 2
Apr.  2019
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SUN Zhe, ZHAN Dongsheng, JIN Fengjun. Spatio-temporal Characteristics and Geographical Determinants of Air Quality in Cities at the Prefecture Level and Above in China[J]. Chinese Geographical Science, 2019, 20(2): 316-324. doi: 10.1007/s11769-019-1031-5
Citation: SUN Zhe, ZHAN Dongsheng, JIN Fengjun. Spatio-temporal Characteristics and Geographical Determinants of Air Quality in Cities at the Prefecture Level and Above in China[J]. Chinese Geographical Science, 2019, 20(2): 316-324. doi: 10.1007/s11769-019-1031-5

Spatio-temporal Characteristics and Geographical Determinants of Air Quality in Cities at the Prefecture Level and Above in China

doi: 10.1007/s11769-019-1031-5
More Information
  • Corresponding author: ZHAN Dongsheng
  • Received Date: 2018-02-02
  • Publish Date: 2019-04-01
  • In recent years, the large scale and frequency of severe air pollution in China has become an important consideration in the construction of livable cities and the physical and mental health of urban residents. Based on the 2016-year urban air quality index (AQI) data published by the Ministry of Environmental Protection of China, this study analyzed the spatial and temporal characteristics of air quality and its influencing factors in 338 urban units nationwide. The analysis provides an effective scientific basis for formulating national air pollution control measures. Four key results are shown. 1) Generally, air quality in the 338 cities is poor, and the average annual values for urban AQI and air pollution in 2016 were 79.58% and 21.22%, respectively. 2) The air quality index presents seasonal changes, with winter > spring > autumn > summer and a u-shaped trend. 3) The spatial distribution of the urban air quality index shows clear north-south characteristic differences and a spatial agglomeration effect; the high value area of air pollution is mainly concentrated in the North China Plain and Xinjiang Uygur Autonomous Region. 4) An evaluation of the spatial econometric model shows that differences in urban air quality are due to social, economic, and natural factors.
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Spatio-temporal Characteristics and Geographical Determinants of Air Quality in Cities at the Prefecture Level and Above in China

doi: 10.1007/s11769-019-1031-5
    Corresponding author: ZHAN Dongsheng

Abstract: In recent years, the large scale and frequency of severe air pollution in China has become an important consideration in the construction of livable cities and the physical and mental health of urban residents. Based on the 2016-year urban air quality index (AQI) data published by the Ministry of Environmental Protection of China, this study analyzed the spatial and temporal characteristics of air quality and its influencing factors in 338 urban units nationwide. The analysis provides an effective scientific basis for formulating national air pollution control measures. Four key results are shown. 1) Generally, air quality in the 338 cities is poor, and the average annual values for urban AQI and air pollution in 2016 were 79.58% and 21.22%, respectively. 2) The air quality index presents seasonal changes, with winter > spring > autumn > summer and a u-shaped trend. 3) The spatial distribution of the urban air quality index shows clear north-south characteristic differences and a spatial agglomeration effect; the high value area of air pollution is mainly concentrated in the North China Plain and Xinjiang Uygur Autonomous Region. 4) An evaluation of the spatial econometric model shows that differences in urban air quality are due to social, economic, and natural factors.

SUN Zhe, ZHAN Dongsheng, JIN Fengjun. Spatio-temporal Characteristics and Geographical Determinants of Air Quality in Cities at the Prefecture Level and Above in China[J]. Chinese Geographical Science, 2019, 20(2): 316-324. doi: 10.1007/s11769-019-1031-5
Citation: SUN Zhe, ZHAN Dongsheng, JIN Fengjun. Spatio-temporal Characteristics and Geographical Determinants of Air Quality in Cities at the Prefecture Level and Above in China[J]. Chinese Geographical Science, 2019, 20(2): 316-324. doi: 10.1007/s11769-019-1031-5
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