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Allocation of SO2 emission rights in city agglomerations considering cross-border transmission of pollutants: A new network DEA model

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  • Zhao, Jiqiang
  • Wu, Xianhua
  • Guo, Ji
  • Gao, Chao

Abstract

Currently SO2 emission rights are allocated without considering the cross-border transmission characteristics of pollutants, and the allocation scheme cannot reflect the fact that air pollutant overflows in space. In this paper, the WRF (Weather Research and Forecasting Model)-CMAQ (Community Multiscale Air Quality) is combined with the data envelopment analysis (DEA) allocation model for the first time, and a two-stage (Stage-1: SO2 formation, Stage-2: SO2 treatment) network DEA allocation model is proposed with the SO2 spatial transmission taken as the intermediate output or input index between decision-making units. Based on the principles of efficiency, economic protection and fairness, the model is applied to the study of SO2 emission rights allocation in the Yangtze River Delta city agglomeration with high homogeneity in China. The results show that: (1) When the weight coefficient (α1) in stage-1 is 0.7, 0.8 or 0.9, the per capita relative deprivation coefficient (PRDC) of each decision-making unit (DMU) is less than 0.5 in the allocation scheme, indicating that our scheme can be used as a reference to allocate emission rights in the Yangtze River Delta city agglomeration. (2) With great robustness and universality, our allocation model allows decision-makers to adjust the GDP constraint coefficient and the weight coefficients in the two stages according to their preferences, so as to obtain the optimal allocation results. The model proposed in this paper can help decision-makers to formulate effective policies to reduce pollutant emission, and promote energy conservation & emission reduction and coordinate environmental governance in regions of city agglomerations.

Suggested Citation

  • Zhao, Jiqiang & Wu, Xianhua & Guo, Ji & Gao, Chao, 2022. "Allocation of SO2 emission rights in city agglomerations considering cross-border transmission of pollutants: A new network DEA model," Applied Energy, Elsevier, vol. 325(C).
    • Handle: RePEc:eee:appene:v:325:y:2022:i:c:s0306261922011849
    DOI: 10.1016/j.apenergy.2022.119927
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    as
    1. Fang, Guochang & Tian, Lixin & Yang, Zili, 2020. "The construction of a comprehensive multidimensional energy index," Energy Economics, Elsevier, vol. 90(C).
    2. Yu, Shiwei & Wei, Yi-Ming & Wang, Ke, 2014. "Provincial allocation of carbon emission reduction targets in China: An approach based on improved fuzzy cluster and Shapley value decomposition," Energy Policy, Elsevier, vol. 66(C), pages 630-644.
    3. Zhang, Jingxiao & Jin, Weixing & Yang, Guo-liang & Li, Hui & Ke, Yongjian & Philbin, Simon Patrick, 2021. "Optimizing regional allocation of CO2 emissions considering output under overall efficiency," Socio-Economic Planning Sciences, Elsevier, vol. 77(C).
    4. Fang, Guochang & Gao, Zhengye & Tian, Lixin & Fu, Min, 2022. "What drives urban carbon emission efficiency? – Spatial analysis based on nighttime light data," Applied Energy, Elsevier, vol. 312(C).
    5. Xiao, Huijuan & Wang, Daoping & Qi, Yu & Shao, Shuai & Zhou, Ya & Shan, Yuli, 2021. "The governance-production nexus of eco-efficiency in Chinese resource-based cities: A two-stage network DEA approach," Energy Economics, Elsevier, vol. 101(C).
    6. An, Qingxian & Wen, Yao & Ding, Tao & Li, Yongli, 2019. "Resource sharing and payoff allocation in a three-stage system: Integrating network DEA with the Shapley value method," Omega, Elsevier, vol. 85(C), pages 16-25.
    7. Antosiewicz, Marek & Fuentes, J. Rodrigo & Lewandowski, Piotr & Witajewski-Baltvilks, Jan, 2022. "Distributional effects of emission pricing in a carbon-intensive economy: The case of Poland," Energy Policy, Elsevier, vol. 160(C).
    8. S You & H Yan, 2011. "A new approach in modelling undesirable output in DEA model☆," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2146-2156, December.
    9. Li, Xiao-Bai & Reeves, Gary R., 1999. "A multiple criteria approach to data envelopment analysis," European Journal of Operational Research, Elsevier, vol. 115(3), pages 507-517, June.
    10. Zhou, P. & Wang, M., 2016. "Carbon dioxide emissions allocation: A review," Ecological Economics, Elsevier, vol. 125(C), pages 47-59.
    11. Zhou, P. & Sun, Z.R. & Zhou, D.Q., 2014. "Optimal path for controlling CO2 emissions in China: A perspective of efficiency analysis," Energy Economics, Elsevier, vol. 45(C), pages 99-110.
    12. Han, Rong & Li, Jianglong & Guo, Zhi, 2022. "Optimal quota in China's energy capping policy in 2030 with renewable targets and sectoral heterogeneity," Energy, Elsevier, vol. 239(PA).
    13. Huang, Qian & Xu, Jiuping, 2020. "Bi-level multi-objective programming approach for carbon emission quota allocation towards co-combustion of coal and sewage sludge," Energy, Elsevier, vol. 211(C).
    14. Wang, Enci & Su, Bin & Zhong, Sheng & Guo, Qinxin, 2022. "China's Embodied SO2 Emissions and Aggregate Embodied SO2 Intensities in Interprovincial and International Trade," Technological Forecasting and Social Change, Elsevier, vol. 177(C).
    15. Sebastián Lozano & Gabriel Villa, 2004. "Centralized Resource Allocation Using Data Envelopment Analysis," Journal of Productivity Analysis, Springer, vol. 22(1), pages 143-161, July.
    16. Glover, Fred & Sueyoshi, Toshiyuki, 2009. "Contributions of Professor William W. Cooper in Operations Research and Management Science," European Journal of Operational Research, Elsevier, vol. 197(1), pages 1-16, August.
    17. Sun, J. & Wen, W. & Wang, M. & Zhou, P., 2022. "Optimizing the provincial target allocation scheme of renewable portfolio standards in China," Energy, Elsevier, vol. 250(C).
    18. Feng, Chenpeng & Chu, Feng & Ding, Jingjing & Bi, Gongbing & Liang, Liang, 2015. "Carbon Emissions Abatement (CEA) allocation and compensation schemes based on DEA," Omega, Elsevier, vol. 53(C), pages 78-89.
    19. Guo, Ji & Zhao, Mengke & Wu, Xianhua & Shi, Beibei & Santibanez Gonzalez, Ernesto D.R., 2021. "Study on the distribution of PM emission rights in various provinces of China based on a new efficiency and equity two-objective DEA model," Ecological Economics, Elsevier, vol. 183(C).
    20. Chu, Junfei & Wu, Jie & Chu, Chengbin & Zhang, Tinglong, 2020. "DEA-based fixed cost allocation in two-stage systems: Leader-follower and satisfaction degree bargaining game approaches," Omega, Elsevier, vol. 94(C).
    21. S You & H Yan, 2011. "A new approach in modelling undesirable output in DEA model," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 62(12), pages 2146-2156, December.
    22. Jia, Zhijie & Wen, Shiyan & Sun, Zao, 2022. "Current relationship between coal consumption and the economic development and China's future carbon mitigation policies," Energy Policy, Elsevier, vol. 162(C).
    23. Wu, Jie & Zhu, Qingyuan & Liang, Liang, 2016. "CO2 emissions and energy intensity reduction allocation over provincial industrial sectors in China," Applied Energy, Elsevier, vol. 166(C), pages 282-291.
    24. Yitzhaki, Shlomo, 1994. "Economic distance and overlapping of distributions," Journal of Econometrics, Elsevier, vol. 61(1), pages 147-159, March.
    25. Feng, Zhiying & Tang, Wenhu & Niu, Zhewen & Wu, Qinghua, 2018. "Bi-level allocation of carbon emission permits based on clustering analysis and weighted voting: A case study in China," Applied Energy, Elsevier, vol. 228(C), pages 1122-1135.
    26. M P Estellita Lins & L Angulo-Meza & A C Moreira Da Silva, 2004. "A multi-objective approach to determine alternative targets in data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 55(10), pages 1090-1101, October.
    27. Yin, Pengzhen & Sun, Jiasen & Chu, Junfei & Liang, Liang, 2016. "Evaluating the environmental efficiency of a two-stage system with undesired outputs by a DEA approach: An interest preference perspectiveAuthor-Name: Wu, Jie," European Journal of Operational Research, Elsevier, vol. 254(3), pages 1047-1062.
    28. Pan, Xunzhang & Teng, Fei & Wang, Gehua, 2014. "Sharing emission space at an equitable basis: Allocation scheme based on the equal cumulative emission per capita principle," Applied Energy, Elsevier, vol. 113(C), pages 1810-1818.
    29. Sun, Tao & Zhang, Hongwei & Wang, Yuan, 2013. "The application of information entropy in basin level water waste permits allocation in China," Resources, Conservation & Recycling, Elsevier, vol. 70(C), pages 50-54.
    30. Pang, Rui-zhi & Deng, Zhong-qi & Chiu, Yung-ho, 2015. "Pareto improvement through a reallocation of carbon emission quotas," Renewable and Sustainable Energy Reviews, Elsevier, vol. 50(C), pages 419-430.
    31. Charnes, A. & Cooper, W. W. & Rhodes, E., 1979. "Measuring the efficiency of decision-making units," European Journal of Operational Research, Elsevier, vol. 3(4), pages 339-338, July.
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    1. Svetlana V. Ratner & Artem M. Shaposhnikov & Andrey V. Lychev, 2023. "Network DEA and Its Applications (2017–2022): A Systematic Literature Review," Mathematics, MDPI, vol. 11(9), pages 1-24, May.

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