IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v13y2021i21p12272-d673707.html
   My bibliography  Save this article

Spatial and Seasonal Characteristics of Air Pollution Spillover in China

Author

Listed:
  • Baocheng Yu

    (School of Ocean Sciences, China University of Geosciences, Beijing 100083, China)

  • Wei Fang

    (School of Economics and Management, China University of Geosciences, Beijing 100083, China)

  • Shupei Huang

    (School of Economics and Management, China University of Geosciences, Beijing 100083, China)

  • Siyao Liu

    (School of Economics and Management, China University of Geosciences, Beijing 100083, China)

  • Yajie Qi

    (School of Economics and Management, China University of Geosciences, Beijing 100083, China)

  • Xiaodan Han

    (School of Economics and Management, China University of Geosciences, Beijing 100083, China)

Abstract

Air pollution spillover can cause air pollution to negatively affect neighboring regions. The structure of air pollution spillover varies with changes in season and space. Researching the spatial and seasonal characteristics of air pollution spillover is beneficial for determining air pollution prevention and control policies. First, this paper uses the GARCH-BEKK model to correlate the air pollution spillover among cities. Second, a complex network is constructed, and cities that have stronger spillover correlations are grouped into the same region. Finally, motifs are analyzed regarding the spillover relationships among regions. This paper also compares the structure of air pollution spillover during various seasons. This study determines that every season has a core region where the air pollution spillover exits the region. The core region in the spring is western East China, in the summer it is northern East China, in the autumn it is northern East China, and in the winter it is northern North China. These regions interact with most other regions. Furthermore, in spring and winter, the phenomena of air pollution spillover between regions are stronger than those in summer and autumn. We can weaken the air pollution spillover by controlling the air pollution in core regions.

Suggested Citation

  • Baocheng Yu & Wei Fang & Shupei Huang & Siyao Liu & Yajie Qi & Xiaodan Han, 2021. "Spatial and Seasonal Characteristics of Air Pollution Spillover in China," Sustainability, MDPI, vol. 13(21), pages 1-14, November.
    • Handle: RePEc:gam:jsusta:v:13:y:2021:i:21:p:12272-:d:673707
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/13/21/12272/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/13/21/12272/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Ruixue Jia & Hyejin Ku, 2019. "Is China's Pollution the Culprit for the Choking of South Korea? Evidence from the Asian Dust," The Economic Journal, Royal Economic Society, vol. 129(624), pages 3154-3188.
    2. Chen, Xiaoguang & Ye, Jingjing, 2017. "When the Wind Blows: Spatial Spillover Effects of Urban Air Pollution," 2017 Annual Meeting, July 30-August 1, Chicago, Illinois 258256, Agricultural and Applied Economics Association.
    3. Duncan J. Watts & Steven H. Strogatz, 1998. "Collective dynamics of ‘small-world’ networks," Nature, Nature, vol. 393(6684), pages 440-442, June.
    Full references (including those not matched with items on IDEAS)

    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. Samrachana Adhikari & Beau Dabbs, 2018. "Social Network Analysis in R: A Software Review," Journal of Educational and Behavioral Statistics, , vol. 43(2), pages 225-253, April.
    2. Wang, Xiaojie & Slamu, Wushour & Guo, Wenqiang & Wang, Sixiu & Ren, Yan, 2022. "A novel semi local measure of identifying influential nodes in complex networks," Chaos, Solitons & Fractals, Elsevier, vol. 158(C).
    3. Lin, Dan & Wu, Jiajing & Xuan, Qi & Tse, Chi K., 2022. "Ethereum transaction tracking: Inferring evolution of transaction networks via link prediction," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 600(C).
    4. Ferreira, D.S.R. & Ribeiro, J. & Oliveira, P.S.L. & Pimenta, A.R. & Freitas, R.P. & Dutra, R.S. & Papa, A.R.R. & Mendes, J.F.F., 2022. "Spatiotemporal analysis of earthquake occurrence in synthetic and worldwide data," Chaos, Solitons & Fractals, Elsevier, vol. 165(P2).
    5. Qinghu Liao & Wenwen Dong & Boxin Zhao, 2023. "A New Strategy to Solve “the Tragedy of the Commons” in Sustainable Grassland Ecological Compensation: Experience from Inner Mongolia, China," Sustainability, MDPI, vol. 15(12), pages 1-24, June.
    6. Jianhong Chen & Hongcai Ma & Shan Yang, 2023. "SEIOR Rumor Propagation Model Considering Hesitating Mechanism and Different Rumor-Refuting Ways in Complex Networks," Mathematics, MDPI, vol. 11(2), pages 1-22, January.
    7. Gregory Gutin & Tomohiro Hirano & Sung-Ha Hwang & Philip R. Neary & Alexis Akira Toda, 2021. "The effect of social distancing on the reach of an epidemic in social networks," Journal of Economic Interaction and Coordination, Springer;Society for Economic Science with Heterogeneous Interacting Agents, vol. 16(3), pages 629-647, July.
    8. Jie, Ke-Wei & Liu, San-Yang & Sun, Xiao-Jun & Xu, Yun-Cheng, 2023. "A dynamic ripple-spreading algorithm for solving mean–variance of shortest path model in uncertain random networks," Chaos, Solitons & Fractals, Elsevier, vol. 167(C).
    9. Divakaruni, Anantha & Zimmerman, Peter, 2023. "The Lightning Network: Turning Bitcoin into money," Finance Research Letters, Elsevier, vol. 52(C).
    10. Leto Peel & Tiago P. Peixoto & Manlio De Domenico, 2022. "Statistical inference links data and theory in network science," Nature Communications, Nature, vol. 13(1), pages 1-15, December.
    11. Abderrahim Zannou & Abdelhak Boulaalam & El Habib Nfaoui, 2020. "SIoT: A New Strategy to Improve the Network Lifetime with an Efficient Search Process," Future Internet, MDPI, vol. 13(1), pages 1-23, December.
    12. Jingsha He & Yue Li & Nafei Zhu, 2023. "A Game Theory-Based Model for the Dissemination of Privacy Information in Online Social Networks," Future Internet, MDPI, vol. 15(3), pages 1-17, February.
    13. Qian, Qian & Feng, Hairong & Gu, Jing, 2021. "The influence of risk attitude on credit risk contagion—Perspective of information dissemination," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 582(C).
    14. Fangyuan Tian & Hongxia Li & Shuicheng Tian & Chenning Tian & Jiang Shao, 2022. "Is There a Difference in Brain Functional Connectivity between Chinese Coal Mine Workers Who Have Engaged in Unsafe Behavior and Those Who Have Not?," IJERPH, MDPI, vol. 19(1), pages 1-21, January.
    15. Yelai Feng & Huaixi Wang & Chao Chang & Hongyi Lu, 2022. "Intrinsic Correlation with Betweenness Centrality and Distribution of Shortest Paths," Mathematics, MDPI, vol. 10(14), pages 1-18, July.
    16. Zhenpeng Li & Zhihua Yan & Xijin Tang, 2024. "Evolutionary Model of Signed Edges in Online Networks Based on Infinite One-Dimensional Uniform Lattice," Mathematics, MDPI, vol. 12(7), pages 1-9, March.
    17. Bachar Moussa & Nikos C. Varsakelis, 2022. "Causality Between International Trade and International Patenting: A Combination of Network Analysis and Granger Causality," Atlantic Economic Journal, Springer;International Atlantic Economic Society, vol. 50(1), pages 9-26, June.
    18. Peixin Dong & Dongyuan Li & Jianping Xing & Haohui Duan & Yong Wu, 2019. "A Method of Bus Network Optimization Based on Complex Network and Beidou Vehicle Location," Future Internet, MDPI, vol. 11(4), pages 1-12, April.
    19. Zhang, Wanli & Yang, Xinsong & Yang, Shiju & Alsaedi, Ahmed, 2021. "Finite-time and fixed-time bipartite synchronization of complex networks with signed graphs," Mathematics and Computers in Simulation (MATCOM), Elsevier, vol. 188(C), pages 319-329.
    20. Mario V. Tomasello & Mauro Napoletano & Antonios Garas & Frank Schweitzer, 2017. "The rise and fall of R&D networks," Industrial and Corporate Change, Oxford University Press and the Associazione ICC, vol. 26(4), pages 617-646.

    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:jsusta:v:13:y:2021:i:21:p:12272-:d:673707. 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.