IDEAS home Printed from https://ideas.repec.org/a/gam/jijerp/v19y2022i19p12753-d934234.html
   My bibliography  Save this article

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

Author

Listed:
  • 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
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1660-4601/19/19/12753/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1660-4601/19/19/12753/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Gohar Feroz Khan & Sungjoon Lee & Ji Young Park & Han Woo Park, 2016. "Theories in communication science: a structural analysis using webometrics and social network approach," Scientometrics, Springer;Akadémiai Kiadó, vol. 108(2), pages 531-557, August.
    2. Yifeng Wang & Ken Sun & Li Li & Yalin Lei & Sanmang Wu & Yong Jiang & Yanling Xi & Fang Wang & Yanfang Cui, 2022. "Assessing the Public Health Economic Loss from PM 2.5 Pollution in ‘2 + 26’ Cities," IJERPH, MDPI, vol. 19(17), pages 1-16, August.
    3. Hang Zhang & Yong Liu & Dongyang Yang & Guanpeng Dong, 2022. "PM 2.5 Concentrations Variability in North China Explored with a Multi-Scale Spatial Random Effect Model," IJERPH, MDPI, vol. 19(17), pages 1-14, August.
    4. Shengling Zhang & Yao Wang & Zhiwei Liu & Yu Hao, 2021. "The spatial dynamic relationship between haze pollution and economic growth: new evidence from 285 prefecture-level cities in China," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 64(11), pages 1985-2020, July.
    5. Yongpei Wang & Zhenyu Xu, 2022. "The scale boundary of urbanized population with peaking PM2.5 concentration: a spatial panel econometric analysis of China’s prefecture-level and above cities," Journal of Environmental Planning and Management, Taylor & Francis Journals, vol. 65(1), pages 126-149, January.
    6. Leng, Zhihui & Sun, Han & Cheng, Jinhua & Wang, Hai & Yao, Zhen, 2021. "China's rare earth industry technological innovation structure and driving factors: A social network analysis based on patents," Resources Policy, Elsevier, vol. 73(C).
    7. Ji, Xi & Yao, Yixin & Long, Xianling, 2018. "What causes PM2.5 pollution? Cross-economy empirical analysis from socioeconomic perspective," Energy Policy, Elsevier, vol. 119(C), pages 458-472.
    Full references (including those not matched with items on IDEAS)

    Citations

    Citations are extracted by the CitEc Project, subscribe to its RSS feed for this item.
    as


    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. Feng Zhou & Chunhui Wen, 2024. "Research on the Evolution of the Spatial Association Network Structure and Driving Factors of China’s Agricultural Green Development," Agriculture, MDPI, vol. 14(5), pages 1-27, April.
    4. 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.

    Most related items

    These are the items that most often cite the same works as this one and are cited by the same works as this one.
    1. Wenqin Gong & Yu Kong, 2022. "Nonlinear Influence of Chinese Real Estate Development on Environmental Pollution: New Evidence from Spatial Econometric Model," IJERPH, MDPI, vol. 19(1), pages 1-22, January.
    2. Barbara McGillivray & Gard B. Jenset & Khalid Salama & Donna Schut, 2022. "Investigating patterns of change, stability, and interaction among scientific disciplines using embeddings," Palgrave Communications, Palgrave Macmillan, vol. 9(1), pages 1-15, December.
    3. Jun Bai & Shixiang Li & Nan Wang & Jianru Shi & Xianmin Li, 2020. "Spatial Spillover Effect of New Energy Development on Economic Growth in Developing Areas of China—An Empirical Test Based on the Spatial Dubin Model," Sustainability, MDPI, vol. 12(8), pages 1-17, April.
    4. Wang, Xiaomin & Tian, Guanghui & Yang, Dongyang & Zhang, Wenxin & Lu, Debin & Liu, Zhongmei, 2018. "Responses of PM2.5 pollution to urbanization in China," Energy Policy, Elsevier, vol. 123(C), pages 602-610.
    5. 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.
    6. Feng Wang & Jing Ren & Juan Liu & Mingru Dong & Bin Yan & Hui Zhao, 2021. "Spatial correlation network and population mobility effect of regional haze pollution: empirical evidence from Pearl River Delta urban agglomeration in China," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(11), pages 15881-15896, November.
    7. Liudan Jiao & Dongrong Li & Yu Zhang & Yinghan Zhu & Xiaosen Huo & Ya Wu, 2021. "Identification of the Key Influencing Factors of Urban Rail Transit Station Resilience against Disasters Caused by Rainstorms," Land, MDPI, vol. 10(12), pages 1-21, November.
    8. Zeng, Jingjing & Liu, Ting & Feiock, Richard & Li, Fei, 2019. "The impacts of China's provincial energy policies on major air pollutants: A spatial econometric analysis," Energy Policy, Elsevier, vol. 132(C), pages 392-403.
    9. Feipeng Guo & Linji Zhang & Zifan Wang & Shaobo Ji, 2022. "Research on Determining the Critical Influencing Factors of Carbon Emission Integrating GRA with an Improved STIRPAT Model: Taking the Yangtze River Delta as an Example," IJERPH, MDPI, vol. 19(14), pages 1-20, July.
    10. Enkhjargal Enkhbat & Yong Geng & Xi Zhang & Huijuan Jiang & Jingyu Liu & Dong Wu, 2020. "Driving Forces of Air Pollution in Ulaanbaatar City Between 2005 and 2015: An Index Decomposition Analysis," Sustainability, MDPI, vol. 12(8), pages 1-17, April.
    11. Weiwei Xie & Hongbing Deng & Zhaohui Chong, 2019. "The Spatial and Heterogeneity Impacts of Population Urbanization on Fine Particulate (PM 2.5 ) in the Yangtze River Economic Belt, China," IJERPH, MDPI, vol. 16(6), pages 1-17, March.
    12. Lan, Jing & Wei, Yiming & Guo, Jie & Li, Qiuming & Liu, Zhen, 2023. "The effect of green finance on industrial pollution emissions: Evidence from China," Resources Policy, Elsevier, vol. 80(C).
    13. Liu, Yang & Du, Junying & Wang, Kun, 2024. "Towards common prosperity: The role of mitigating energy inequality," Energy Policy, Elsevier, vol. 195(C).
    14. Hao, Yu & Guo, Yunxia & Li, Suixin & Luo, Shiyue & Jiang, Xueting & Shen, Zhiyang & Wu, Haitao, 2022. "Towards achieving the sustainable development goal of industry: How does industrial agglomeration affect air pollution?," Innovation and Green Development, Elsevier, vol. 1(1).
    15. Asrah Heintzelman & Gabriel M. Filippelli & Max J. Moreno-Madriñan & Jeffrey S. Wilson & Lixin Wang & Gregory K. Druschel & Vijay O. Lulla, 2023. "Efficacy of Low-Cost Sensor Networks at Detecting Fine-Scale Variations in Particulate Matter in Urban Environments," IJERPH, MDPI, vol. 20(3), pages 1-18, January.
    16. Yue Wang & Yang Wen & Yingying Xu & Lei Shi & Xuan Yang, 2022. "Health Benefits Quantification for New-Energy Vehicles Promotion: A Case Study of Beijing," IJERPH, MDPI, vol. 19(21), pages 1-12, October.
    17. Vélez-Henao, Johan-Andrés & Font Vivanco, David & Hernández-Riveros, Jesús-Antonio, 2019. "Technological change and the rebound effect in the STIRPAT model: A critical view," Energy Policy, Elsevier, vol. 129(C), pages 1372-1381.
    18. Pengcheng Lv & Haoyu Zhang & Xiaodong Li, 2023. "Spatio-Temporal Distribution Characteristics and Drivers of PM 2.5 Pollution in Henan Province, Central China, before and during the COVID-19 Epidemic," IJERPH, MDPI, vol. 20(6), pages 1-14, March.
    19. Di, Jinghan & Wen, Zongguo & Jiang, Meihui & Miatto, Alessio, 2022. "Patterns and features of embodied environmental flow networks in the international trade of metal resources: A study of aluminum," Resources Policy, Elsevier, vol. 77(C).
    20. Lingyan Xu & Dandan Wang & Jianguo Du, 2021. "The Heterogeneous Influence of Infrastructure Construction on China’s Urban Green and Smart Development—The Threshold Effect of Urban Scale," Land, MDPI, vol. 10(10), pages 1-17, September.

    Corrections

    All material on this site has been provided by the respective publishers and authors. You can help correct errors and omissions. When requesting a correction, please mention this item's handle: RePEc:gam:jijerp:v:19:y:2022:i:19:p:12753-:d:934234. See general information about how to correct material in RePEc.

    If you have authored this item and are not yet registered with RePEc, we encourage you to do it here. This allows to link your profile to this item. It also allows you to accept potential citations to this item that we are uncertain about.

    If CitEc recognized a bibliographic reference but did not link an item in RePEc to it, you can help with this form .

    If you know of missing items citing this one, you can help us creating those links by adding the relevant references in the same way as above, for each refering item. If you are a registered author of this item, you may also want to check the "citations" tab in your RePEc Author Service profile, as there may be some citations waiting for confirmation.

    For technical questions regarding this item, or to correct its authors, title, abstract, bibliographic or download information, contact: MDPI Indexing Manager (email available below). General contact details of provider: https://www.mdpi.com .

    Please note that corrections may take a couple of weeks to filter through the various RePEc services.

    IDEAS is a RePEc service. RePEc uses bibliographic data supplied by the respective publishers.