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Analysis of the Spatial Association Network of PM 2.5 and Its Influencing Factors in China

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  • Huiping Wang

    (Western Collaborative Innovation Research Center for Energy Economy and Regional Development, Xi’an University of Finance and Economics, Xi’an 710100, China)

  • Qi Ge

    (Western Collaborative Innovation Research Center for Energy Economy and Regional Development, Xi’an University of Finance and Economics, Xi’an 710100, China)

Abstract

The spatial association network of PM 2.5 is constructed using a modified gravity model, with the data of 31 provinces in China from 2009–2020. On this basis, the spatial correlation structure of PM 2.5 and its influencing factors were investigated through social network analysis (SNA). The results showed that, first, the PM 2.5 has a typical and complex spatial correlation, and the correlation degree tends to decrease with the implementation of collaborative management. Second, they show that there is a clear “core-edge” distribution pattern in the network. Some areas with serious PM 2.5 pollution have experienced different degrees of decline in centrality due to policy pressure. Third, the network is divided into “net benefits”, “net spillovers”, “two-way spillovers” and “brokers”. The linkage effect among the four blocks is obvious. Fourth, the government intervention and the industrial structure differentiation promote the formation of the network, but environmental regulation and car ownership differentiation have the opposite effect on the network.

Suggested Citation

  • Huiping Wang & Qi Ge, 2022. "Analysis of the Spatial Association Network of PM 2.5 and Its Influencing Factors in China," IJERPH, MDPI, vol. 19(19), pages 1-15, October.
    • Handle: RePEc:gam:jijerp:v:19:y:2022:i:19:p:12753-:d:934234
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    References listed on IDEAS

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    Cited by:

    1. Huiping Wang & Peiling Liu, 2023. "Spatial Correlation Network of Energy Consumption and Its Influencing Factors in the Yangtze River Delta Urban Agglomeration," Sustainability, MDPI, vol. 15(4), pages 1-20, February.
    2. Peiqi Hu & Kai Zhou & Haoxi Zhang & Zhong Ma & Jingyuan Li, 2023. "The Cause and Correlation Network of Air Pollution from a Spatial Perspective: Evidence from the Beijing–Tianjin–Hebei Region," Sustainability, MDPI, vol. 15(4), pages 1-21, February.
    3. Meixia Wang & Qingyun Zheng & Yunxia Wang, 2023. "Spatial Correlation Network and Driving Factors of Urban Energy Eco-Efficiency from the Perspective of Human Well-Being: A Case Study of Shaanxi Province, China," IJERPH, MDPI, vol. 20(6), pages 1-20, March.

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