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Socioeconomic Drivers of PM 2.5 in the Accumulation Phase of Air Pollution Episodes in the Yangtze River Delta of China

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  • Cai-Rong Lou

    (Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210023, China
    College of Geographic Sciences, Nantong University, Nantong 226007, China
    State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, College of Geographical Science, Nanjing Normal University, Nanjing 210023, China)

  • Hong-Yu Liu

    (Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210023, China
    State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, College of Geographical Science, Nanjing Normal University, Nanjing 210023, China)

  • Yu-Feng Li

    (Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210023, China
    State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, College of Geographical Science, Nanjing Normal University, Nanjing 210023, China)

  • Yu-Ling Li

    (Key Laboratory of Virtual Geographic Environment, Nanjing Normal University, Ministry of Education, Nanjing 210023, China
    State Key Laboratory Cultivation Base of Geographical Environment Evolution (Jiangsu Province), Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, College of Geographical Science, Nanjing Normal University, Nanjing 210023, China)

Abstract

Recent studies in PM 2.5 sources show that anthropogenic emissions are the main contributors to haze pollution. Due to their essential roles in establishing policies for improving air quality, socioeconomic drivers of PM 2.5 levels have attracted increasing attention. Unlike previous studies focusing on the annual PM 2.5 concentration ( C year ), this paper focuses on the accumulation phase of PM 2.5 during the pollution episode (PMAE) in the Yangtze River Delta in China. This paper mainly explores the spatial variations of PMAE and its links to the socioeconomic factors using a geographical detector and simple linear regression. The results indicated that PM 2.5 was more likely to accumulate in more developed cities, such as Nanjing and Shanghai. Compared with C year , PMAE was more sensitive to socioeconomic impacts. Among the twelve indicators chosen for this study, population density was an especially critical factor that could affect the accumulation of PM 2.5 dramatically and accounted for the regional difference. A 1% increase in population density could cause a 0.167% rise in the maximal increment and a 0.214% rise in the daily increase rate of PM 2.5 . Additionally, industry, energy consumption, and vehicles were also significantly associated with PM 2.5 accumulation. These conclusions could serve to remediate the severe PM 2.5 pollution in China.

Suggested Citation

  • Cai-Rong Lou & Hong-Yu Liu & Yu-Feng Li & Yu-Ling Li, 2016. "Socioeconomic Drivers of PM 2.5 in the Accumulation Phase of Air Pollution Episodes in the Yangtze River Delta of China," IJERPH, MDPI, vol. 13(10), pages 1-19, September.
    • Handle: RePEc:gam:jijerp:v:13:y:2016:i:10:p:928-:d:78709
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    References listed on IDEAS

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    Cited by:

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    2. Qingyu Fan & Shan Yang & Shuaibin Liu, 2019. "Asymmetrically Spatial Effects of Urban Scale and Agglomeration on Haze Pollution in China," IJERPH, MDPI, vol. 16(24), pages 1-18, December.
    3. Yuan Shi & Alexis Kai-Hon Lau & Edward Ng & Hung-Chak Ho & Muhammad Bilal, 2021. "A Multiscale Land Use Regression Approach for Estimating Intraurban Spatial Variability of PM 2.5 Concentration by Integrating Multisource Datasets," IJERPH, MDPI, vol. 19(1), pages 1-16, December.
    4. Huilin Yang & Rui Yao & Peng Sun & Chenhao Ge & Zice Ma & Yaojin Bian & Ruilin Liu, 2023. "Spatiotemporal Evolution and Driving Forces of PM 2.5 in Urban Agglomerations in China," IJERPH, MDPI, vol. 20(3), pages 1-15, January.
    5. Weiguang Wang & Yangyang Wang, 2023. "Regional Differences, Dynamic Evolution and Driving Factors Analysis of PM 2.5 in the Yangtze River Economic Belt," Sustainability, MDPI, vol. 15(4), pages 1-24, February.
    6. Yafei Wu & Ke Hu & Yaofeng Han & Qilin Sheng & Ya Fang, 2020. "Spatial Characteristics of Life Expectancy and Geographical Detection of Its Influencing Factors in China," IJERPH, MDPI, vol. 17(3), pages 1-15, February.
    7. Tiansong Zhu & Kaiping Yu & Bo Wang, 2023. "Spatial Distribution Characteristics and Influencing Factors of Cultural and Tourism Resources in Xihu District of Hangzhou," Sustainability, MDPI, vol. 15(14), pages 1-20, July.
    8. Yazhu Wang & Xuejun Duan & Lei Wang, 2019. "Spatial-Temporal Evolution of PM 2.5 Concentration and its Socioeconomic Influence Factors in Chinese Cities in 2014–2017," IJERPH, MDPI, vol. 16(6), pages 1-18, March.
    9. Xiangxue Zhang & Changxiu Cheng, 2022. "Temporal and Spatial Heterogeneity of PM 2.5 Related to Meteorological and Socioeconomic Factors across China during 2000–2018," IJERPH, MDPI, vol. 19(2), pages 1-15, January.
    10. Lilin Xiong & Jie Li & Ting Xia & Xinyue Hu & Yan Wang & Maonan Sun & Meng Tang, 2018. "Risk Reduction Behaviors Regarding PM 2.5 Exposure among Outdoor Exercisers in the Nanjing Metropolitan Area, China," IJERPH, MDPI, vol. 15(8), pages 1-13, August.
    11. Hansol Mun & Mengying Li & Juchul Jung, 2022. "Spatial-Temporal Characteristics and Influencing Factors of Particulate Matter: Geodetector Approach," Land, MDPI, vol. 11(12), pages 1-26, December.
    12. Xiangxue Zhang & Yue Lin & Changxiu Cheng & Junming Li, 2021. "Determinant Powers of Socioeconomic Factors and Their Interactive Impacts on Particulate Matter Pollution in North China," IJERPH, MDPI, vol. 18(12), pages 1-15, June.
    13. Jin-Wei Yan & Fei Tao & Shuai-Qian Zhang & Shuang Lin & Tong Zhou, 2021. "Spatiotemporal Distribution Characteristics and Driving Forces of PM2.5 in Three Urban Agglomerations of the Yangtze River Economic Belt," IJERPH, MDPI, vol. 18(5), pages 1-25, February.
    14. Moon-Jung Kim & Yu-Sang Chang & Su-Min Kim, 2021. "Impact of Income, Density, and Population Size on PM 2.5 Pollutions: A Scaling Analysis of 254 Large Cities in Six Developed Countries," IJERPH, MDPI, vol. 18(17), pages 1-30, August.

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