IDEAS home Printed from https://ideas.repec.org/a/gam/jeners/v12y2019i11p2118-d236723.html
   My bibliography  Save this article

Research on Optimization Allocation Scheme of Initial Carbon Emission Quota from the Perspective of Welfare Effect

Author

Listed:
  • Qunli Wu

    (Department of Economics and Management, North China Electric Power University, 689 Huadian Road, Baoding 071000, China
    Beijing Key Laboratory of New Energy and Low-Carbon Development, North China Electric Power University, Changping 102206, Beijing)

  • Hongjie Zhang

    (Department of Economics and Management, North China Electric Power University, 689 Huadian Road, Baoding 071000, China)

Abstract

The initial allocation of carbon emission quotas should be of primary concern when establishing China’s unified carbon emission trading market. Essentially, the issue of national carbon quota allocation is an allocation among China’s provinces. The novel bi-level allocation scheme that is based on weighted voting model is put forward, which divides allocation process into two levels, given that there are great regional differences in China. At the first level, k-means clustering is employed to cluster 29 provinces into four categories that are based on emission abatement responsibility, potential, capacity, pressure, and motivation. Subsequently, the national carbon quotas are allocated to the four classes. At the second level, carbon quotas of a class are allocated to each region in this class. The weighted voting models are constructed for the two levels, where each region selects their preferable scheme from three fundamental allocation schemes that are based on their voting rights. The comprehensive index method quantifies each region’s voting rights, which utilizes the information entropy method at the first level and the analytic hierarchy process (AHP) at the second level. The carbon trading market is simulated and welfare effects obtained from carbon trading market under different allocation schemes are measured to verify the rationality of the proposed model. The results indicate: (1) the emission abatement burdens are borne by all provinces in China, but the burden shares are different, which are related to their respective carbon emission characteristics. (2) The differences in carbon intensity among regions in 2030 have narrowed on the basis of the results of 2005, which means that the proposed scheme can balance corresponding differences. (3) When compared with three fundamental allocation schemes, the bi-level allocation scheme can obtain the most welfare effects, while the differences in the welfare effect among regions under this scheme are the smallest, which indicates that the proposed model is feasible for policy-maker.

Suggested Citation

  • Qunli Wu & Hongjie Zhang, 2019. "Research on Optimization Allocation Scheme of Initial Carbon Emission Quota from the Perspective of Welfare Effect," Energies, MDPI, vol. 12(11), pages 1-27, June.
    • Handle: RePEc:gam:jeners:v:12:y:2019:i:11:p:2118-:d:236723
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/1996-1073/12/11/2118/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/1996-1073/12/11/2118/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Eugenia Sanin, María & Violante, Francesco & Mansanet-Bataller, María, 2015. "Understanding volatility dynamics in the EU-ETS market," Energy Policy, Elsevier, vol. 82(C), pages 321-331.
    2. Shuai, Chenyang & Shen, Liyin & Jiao, Liudan & Wu, Ya & Tan, Yongtao, 2017. "Identifying key impact factors on carbon emission: Evidences from panel and time-series data of 125 countries from 1990 to 2011," Applied Energy, Elsevier, vol. 187(C), pages 310-325.
    3. Zhang, Yue-Jun & Wang, Ao-Dong & Da, Ya-Bin, 2014. "Regional allocation of carbon emission quotas in China: Evidence from the Shapley value method," Energy Policy, Elsevier, vol. 74(C), pages 454-464.
    4. 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.
    5. Huang, Hai & Roland-Holst, David & Springer, Cecilia & Lin, Jiang & Cai, Wenjia & Wang, Can, 2019. "Emissions trading systems and social equity: A CGE assessment for China," Applied Energy, Elsevier, vol. 235(C), pages 1254-1265.
    6. Ciscar, Juan-Carlos & Saveyn, Bert & Soria, Antonio & Szabo, Laszlo & Van Regemorter, Denise & Van Ierland, Tom, 2013. "A comparability analysis of global burden sharing GHG reduction scenarios," Energy Policy, Elsevier, vol. 55(C), pages 73-81.
    7. Chen, Jiandong & Cheng, Shulei & Song, Malin & Wu, Yinyin, 2016. "A carbon emissions reduction index: Integrating the volume and allocation of regional emissions," Applied Energy, Elsevier, vol. 184(C), pages 1154-1164.
    8. He Li & Kevin Lo & Mark Wang & Pingyu Zhang & Longyi Xue, 2016. "Industrial Energy Consumption in Northeast China under the Revitalisation Strategy: A Decomposition and Policy Analysis," Energies, MDPI, vol. 9(7), pages 1-13, July.
    9. Yue-Jun Zhang & Jun-Fang Hao, 2017. "Carbon emission quota allocation among China’s industrial sectors based on the equity and efficiency principles," Annals of Operations Research, Springer, vol. 255(1), pages 117-140, August.
    10. Chao Bi & Minna Jia & Jingjing Zeng, 2019. "Nonlinear Effect of Public Infrastructure on Energy Intensity in China: A Panel Smooth Transition Regression Approach," Sustainability, MDPI, vol. 11(3), pages 1-21, January.
    11. Li, Wei & Jia, Zhijie, 2016. "The impact of emission trading scheme and the ratio of free quota: A dynamic recursive CGE model in China," Applied Energy, Elsevier, vol. 174(C), pages 1-14.
    12. Edwards, T. Huw. & Hutton, John P., 2001. "Allocation of carbon permits within a country: a general equilibrium analysis of the United Kingdom," Energy Economics, Elsevier, vol. 23(4), pages 371-386, July.
    13. Voigt, Sebastian & De Cian, Enrica & Schymura, Michael & Verdolini, Elena, 2014. "Energy intensity developments in 40 major economies: Structural change or technology improvement?," Energy Economics, Elsevier, vol. 41(C), pages 47-62.
    14. Ji, Xiang & Li, Guo & Wang, Zhaohua, 2017. "Allocation of emission permits for China’s power plants: A systemic Pareto optimal method," Applied Energy, Elsevier, vol. 204(C), pages 607-619.
    15. Yu, Shiwei & Wei, Yi-Ming & Fan, Jingli & Zhang, Xian & Wang, Ke, 2012. "Exploring the regional characteristics of inter-provincial CO2 emissions in China: An improved fuzzy clustering analysis based on particle swarm optimization," Applied Energy, Elsevier, vol. 92(C), pages 552-562.
    16. Yilun Shang, 2018. "Resilient Multiscale Coordination Control against Adversarial Nodes," Energies, MDPI, vol. 11(7), pages 1-17, July.
    17. Pan, Xunzhang & Teng, Fei & Wang, Gehua, 2014. "A comparison of carbon allocation schemes: On the equity-efficiency tradeoff," Energy, Elsevier, vol. 74(C), pages 222-229.
    18. Zhou, P. & Zhang, L. & Zhou, D.Q. & Xia, W.J., 2013. "Modeling economic performance of interprovincial CO2 emission reduction quota trading in China," Applied Energy, Elsevier, vol. 112(C), pages 1518-1528.
    19. 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.
    20. William D. Nordhaus, 1991. "The Cost of Slowing Climate Change: a Survey," The Energy Journal, International Association for Energy Economics, vol. 0(Number 1), pages 37-66.
    21. Yue-Jun Zhang & Ya-Bin Da, 2013. "Decomposing the changes of energy-related carbon emissions in China: evidence from the PDA approach," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 69(1), pages 1109-1122, October.
    22. Pan, Xunzhang & Teng, Fei & Ha, Yuejiao & Wang, Gehua, 2014. "Equitable Access to Sustainable Development: Based on the comparative study of carbon emission rights allocation schemes," Applied Energy, Elsevier, vol. 130(C), pages 632-640.
    23. Tian, Xu & Dai, Hancheng & Geng, Yong & Huang, Zhen & Masui, Toshihiko & Fujita, Tsuyoshi, 2017. "The effects of carbon reduction on sectoral competitiveness in China: A case of Shanghai," Applied Energy, Elsevier, vol. 197(C), pages 270-278.
    24. 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.
    25. Xian, Yujiao & Wang, Ke & Wei, Yi-Ming & Huang, Zhimin, 2019. "Would China’s power industry benefit from nationwide carbon emission permit trading? An optimization model-based ex post analysis on abatement cost savings," Applied Energy, Elsevier, vol. 235(C), pages 978-986.
    26. 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.
    27. Dhakal, Shobhakar, 2009. "Urban energy use and carbon emissions from cities in China and policy implications," Energy Policy, Elsevier, vol. 37(11), pages 4208-4219, November.
    28. Hong, Taehoon & Koo, Choongwan & Lee, Sungug, 2014. "Benchmarks as a tool for free allocation through comparison with similar projects: Focused on multi-family housing complex," Applied Energy, Elsevier, vol. 114(C), pages 663-675.
    29. Tiago Sequeira & Marcelo Santos, 2018. "Education and Energy Intensity: Simple Economic Modelling and Preliminary Empirical Results," Sustainability, MDPI, vol. 10(8), pages 1-17, July.
    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. Hong, Zitao & Peng, Zhen & Zhang, Liumei, 2022. "Game analysis on the choice of emission trading among industrial enterprises driven by data," Energy, Elsevier, vol. 239(PE).

    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. 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.
    2. Zhou, P. & Wang, M., 2016. "Carbon dioxide emissions allocation: A review," Ecological Economics, Elsevier, vol. 125(C), pages 47-59.
    3. Yanbin Li & Zhen Li & Min Wu & Feng Zhang & Gejirifu De, 2018. "Regional-Level Allocation of CO 2 Emission Permits in China: Evidence from the Boltzmann Distribution Method," Sustainability, MDPI, vol. 10(8), pages 1-16, July.
    4. Min Yang & Qingxian An & Tao Ding & Pengzhen Yin & Liang Liang, 2019. "Carbon emission allocation in China based on gradually efficiency improvement and emission reduction planning principle," Annals of Operations Research, Springer, vol. 278(1), pages 123-139, July.
    5. Shaofu Du & Jun Qian & Tianzhuo Liu & Li Hu, 2020. "Emission allowance allocation mechanism design: a low-carbon operations perspective," Annals of Operations Research, Springer, vol. 291(1), pages 247-280, August.
    6. Zhang, Yue-Jun & Wang, Ao-Dong & Da, Ya-Bin, 2014. "Regional allocation of carbon emission quotas in China: Evidence from the Shapley value method," Energy Policy, Elsevier, vol. 74(C), pages 454-464.
    7. Fang, Kai & Zhang, Qifeng & Long, Yin & Yoshida, Yoshikuni & Sun, Lu & Zhang, Haoran & Dou, Yi & Li, Shuai, 2019. "How can China achieve its Intended Nationally Determined Contributions by 2030? A multi-criteria allocation of China’s carbon emission allowance," Applied Energy, Elsevier, vol. 241(C), pages 380-389.
    8. Xu, Zhongwen & Yao, Liming & Liu, Qiaoling & Long, Yin, 2019. "Policy implications for achieving the carbon emission reduction target by 2030 in Japan-Analysis based on a bilevel equilibrium model," Energy Policy, Elsevier, vol. 134(C).
    9. Chang, Kai & Zhang, Chao & Chang, Hao, 2016. "Emissions reduction allocation and economic welfare estimation through interregional emissions trading in China: Evidence from efficiency and equity," Energy, Elsevier, vol. 113(C), pages 1125-1135.
    10. Shihong Zeng & Yan Xu & Liming Wang & Jiuying Chen & Qirong Li, 2016. "Forecasting the Allocative Efficiency of Carbon Emission Allowance Financial Assets in China at the Provincial Level in 2020," Energies, MDPI, vol. 9(5), pages 1-18, May.
    11. Chiu-Ming Hsiao, 2022. "Economic Growth, CO 2 Emissions Quota and Optimal Allocation under Uncertainty," Sustainability, MDPI, vol. 14(14), pages 1-26, July.
    12. Amro M Elshurafa & Abdel Rahman Muhsen, 2019. "The Upper Limit of Distributed Solar PV Capacity in Riyadh: A GIS-Assisted Study," Sustainability, MDPI, vol. 11(16), pages 1-20, August.
    13. Zhang, Yue-Jun & Wang, Ao-Dong & Tan, Weiping, 2015. "The impact of China's carbon allowance allocation rules on the product prices and emission reduction behaviors of ETS-covered enterprises," Energy Policy, Elsevier, vol. 86(C), pages 176-185.
    14. Yali Zhang & Yihan Wang & Xiaoshu Hou, 2019. "Carbon Mitigation for Industrial Sectors in the Jing-Jin-Ji Urban Agglomeration, China," Sustainability, MDPI, vol. 11(22), pages 1-13, November.
    15. 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).
    16. Jianguo Zhou & Yushuo Li & Xuejing Huo & Xiaolei Xu, 2019. "How to Allocate Carbon Emission Permits Among China’s Industrial Sectors Under the Constraint of Carbon Intensity?," Sustainability, MDPI, vol. 11(3), pages 1-21, February.
    17. Yue-Jun Zhang & Zhao Liu & Huan Zhang & Tai-De Tan, 2014. "The impact of economic growth, industrial structure and urbanization on carbon emission intensity in China," Natural Hazards: Journal of the International Society for the Prevention and Mitigation of Natural Hazards, Springer;International Society for the Prevention and Mitigation of Natural Hazards, vol. 73(2), pages 579-595, September.
    18. Song, Xiangnan & Lu, Yujie & Shen, Liyin & Shi, Xunpeng, 2018. "Will China's building sector participate in emission trading system? Insights from modelling an owner's optimal carbon reduction strategies," Energy Policy, Elsevier, vol. 118(C), pages 232-244.
    19. Yang, Mian & Hou, Yaru & Fang, Chao & Duan, Hongbo, 2020. "Constructing energy-consuming right trading system for China's manufacturing industry in 2025," Energy Policy, Elsevier, vol. 144(C).
    20. Jiasen Sun & Guo Li, 2020. "Designing a double auction mechanism for the re-allocation of emission permits," Annals of Operations Research, Springer, vol. 291(1), pages 847-874, August.

    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:jeners:v:12:y:2019:i:11:p:2118-:d:236723. 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.