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Spatiotemporal Variations and Driving Factors of Air Pollution in China

Author

Listed:
  • Dongsheng Zhan

    (Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Mei-Po Kwan

    (Department of Geography and Geographic Information Science, University of Illinois at Urbana-Champaign, Urbana, IL 61801, USA
    Department of Human Geography and Spatial Planning, Utrecht University, P.O. Box 80125, 3508 TC Utrecht, The Netherlands)

  • Wenzhong Zhang

    (Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Shaojian Wang

    (Guangdong Provincial Key Laboratory of Urbanization and Geo-simulation, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China)

  • Jianhui Yu

    (Key Laboratory of Regional Sustainable Development Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

In recent years, severe and persistent air pollution episodes in China have drawn wide public concern. Based on ground monitoring air quality data collected in 2015 in Chinese cities above the prefectural level, this study identifies the spatiotemporal variations of air pollution and its associated driving factors in China using descriptive statistics and geographical detector methods. The results show that the average air pollution ratio and continuous air pollution ratio across Chinese cities in 2015 were 23.1 ± 16.9% and 16.2 ± 14.8%. The highest levels of air pollution ratio and continuous air pollution ratio were observed in northern China, especially in the Bohai Rim region and Xinjiang province, and the lowest levels were found in southern China. The average and maximum levels of continuous air pollution show distinct spatial variations when compared with those of the continuous air pollution ratio. Monthly changes in both air pollution ratio and continuous air pollution ratio have a U-shaped variation, indicating that the highest levels of air pollution occurred in winter and the lowest levels happened in summer. The results of the geographical detector model further reveal that the effect intensity of natural factors on the spatial disparity of the air pollution ratio is greater than that of human-related factors. Specifically, among natural factors, the annual average temperature, land relief, and relative humidity have the greatest and most significant negative effects on the air pollution ratio, whereas human factors such as population density, the number of vehicles, and Gross Domestic Product (GDP) witness the strongest and most significant positive effects on air pollution ratio.

Suggested Citation

  • Dongsheng Zhan & Mei-Po Kwan & Wenzhong Zhang & Shaojian Wang & Jianhui Yu, 2017. "Spatiotemporal Variations and Driving Factors of Air Pollution in China," IJERPH, MDPI, vol. 14(12), pages 1-18, December.
    • Handle: RePEc:gam:jijerp:v:14:y:2017:i:12:p:1538-:d:122236
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    References listed on IDEAS

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    Cited by:

    1. Dongyang Nie & Mindong Chen & Yun Wu & Xinlei Ge & Jianlin Hu & Kai Zhang & Pengxiang Ge, 2018. "Characterization of Fine Particulate Matter and Associated Health Burden in Nanjing," IJERPH, MDPI, vol. 15(4), pages 1-12, March.
    2. Hua Wang & Changwei Tian & Wenming Wang & Xiaoming Luo, 2019. "Temporal Cross-Correlations between Ambient Air Pollutants and Seasonality of Tuberculosis: A Time-Series Analysis," IJERPH, MDPI, vol. 16(9), pages 1-11, May.
    3. Dongsheng Zhan & Qianyun Zhang & Xiaoren Xu & Chunshui Zeng, 2022. "Spatiotemporal Distribution of Continuous Air Pollution and Its Relationship with Socioeconomic and Natural Factors in China," IJERPH, MDPI, vol. 19(11), pages 1-17, May.
    4. Feng Han & Xingcheng Lu & Cuicui Xiao & Miao Chang & Ke Huang, 2019. "Estimation of Health Effects and Economic Losses from Ambient Air Pollution in Undeveloped Areas: Evidence from Guangxi, China," IJERPH, MDPI, vol. 16(15), pages 1-16, July.
    5. Yu Song & Bingrui Liu & Xiaohong Chen & Jia Liu, 2020. "Atmospheric Pollution Mapping of the Yangtze River Basin: An AQI-Based Weighted Co-Word Analysis," IJERPH, MDPI, vol. 17(3), pages 1-16, January.
    6. Li Yue & Dan Xue & Muhammad Umar Draz & Fayyaz Ahmad & Jiaojiao Li & Farrukh Shahzad & Shahid Ali, 2020. "The Double-Edged Sword of Urbanization and Its Nexus with Eco-Efficiency in China," IJERPH, MDPI, vol. 17(2), pages 1-20, January.
    7. Qingbin Wei & Lianjun Zhang & Wenbiao Duan & Zhen Zhen, 2019. "Global and Geographically and Temporally Weighted Regression Models for Modeling PM 2.5 in Heilongjiang, China from 2015 to 2018," IJERPH, MDPI, vol. 16(24), pages 1-20, December.

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