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PM 2.5 Cooperative Control with Fuzzy Cost and Fuzzy Coalitions

Author

Listed:
  • Zhen Zhou

    (School of Management, Capital Normal University, Beijing 100089, China)

  • Meijia Zhang

    (School of Management, Capital Normal University, Beijing 100089, China)

  • Xiaohui Yu

    (School of Logistics, Beijing Wuzi University, Beijing 101149, China)

  • Xijun He

    (College of Economics and Management, Beijing University of Technology, Beijing 100124, China)

  • Kang Wang

    (School of Management, Capital Normal University, Beijing 100089, China)

  • Quan Shao

    (School of Economics and Management Engineering, Beijing University of Civil Engineering and Architecture, Beijing 100044, China)

  • Jie Wang

    (School of Management, Capital Normal University, Beijing 100089, China)

  • Hongxia Sun

    (School of Business, Beijing Industrial and Commercial University, Beijing 100084, China)

Abstract

Haze control cost is hard to value by a crisp number because it is often affected by various factors such as regional uncertain meteorological conditions and topographical features. Furthermore, regions may be involved in different coalitions for haze control with different levels of effort. In this paper, we propose a PM 2.5 cooperative control model with fuzzy cost and crisp coalitions or fuzzy coalitions based on the uncertain cross-border transmission factor. We focus on the Beijing–Tianjin–Hebei regions of China and obtain the following major findings. In the case of haze control in the Beijing–Tianjin–Hebei regions of China, local governments in the global crisp coalition can achieve their emission reduction targets with the lowest aggregated cost. However, Hebei fails to satisfy its individual rationality if there is no cost sharing. Therefore, the Hukuhara–Shapley value is used to allocate the aggregated cost among these regions so that the grand coalition is stable. However, the Beijing–Tianjin–Hebei regions cannot achieve their emission reduction targets in the global fuzzy coalition without government subsidies.

Suggested Citation

  • Zhen Zhou & Meijia Zhang & Xiaohui Yu & Xijun He & Kang Wang & Quan Shao & Jie Wang & Hongxia Sun, 2019. "PM 2.5 Cooperative Control with Fuzzy Cost and Fuzzy Coalitions," IJERPH, MDPI, vol. 16(7), pages 1-14, April.
    • Handle: RePEc:gam:jijerp:v:16:y:2019:i:7:p:1271-:d:221299
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    References listed on IDEAS

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    2. Armaghan Abed-Elmdoust & Reza Kerachian, 2012. "Water Resources Allocation Using a Cooperative Game with Fuzzy Payoffs and Fuzzy Coalitions," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 26(13), pages 3961-3976, October.
    3. Zhisong Chen & Huimin Wang & Xiangtong Qi, 2013. "Pricing and Water Resource Allocation Scheme for the South-to-North Water Diversion Project in China," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(5), pages 1457-1472, March.
    4. Armaghan Abed-Elmdoust & Reza Kerachian, 2013. "Incorporating Economic and Political Considerations in Inter-Basin Water Allocations: A Case Study," Water Resources Management: An International Journal, Published for the European Water Resources Association (EWRA), Springer;European Water Resources Association (EWRA), vol. 27(3), pages 859-870, February.
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