IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v11y2019i3p914-d204848.html
   My bibliography  Save this article

How to Allocate Carbon Emission Permits Among China’s Industrial Sectors Under the Constraint of Carbon Intensity?

Author

Listed:
  • Jianguo Zhou

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China)

  • Yushuo Li

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China)

  • Xuejing Huo

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China)

  • Xiaolei Xu

    (Department of Economics and Management, North China Electric Power University, Baoding 071003, China)

Abstract

With the official launch of China’s national unified carbon trading system (ETS) in 2017, it has played an increasingly important role in controlling the growth of carbon dioxide emissions. One of the core issues in carbon trading is the allocation of initial carbon emissions permits. Since the industry emits the largest amount of carbon dioxide in China, a study on the allocation of carbon emission permits among China’s industrial sectors is necessary to promote industry carbon abatement efficiency. In this study, industrial carbon emissions permits are allocated to 37 sub-sectors of China to reach the emission reduction target of 2030 considering the carbon marginal abatement cost, carbon abatement responsibility, carbon abatement potential, and carbon abatement capacity. A hybrid approach that integrates data envelop analysis (DEA), the analytic hierarchy process (AHP), and principal component analysis (PCA) is proposed to allocate carbon emission permits. The results of this study are as follows: First, under the constraint of carbon intensity, the carbon emission permits of the total industry in 2030 will be 8792 Mt with an average growth rate of 3.27%, which is 1.57 times higher than that in 2016. Second, the results of the carbon marginal abatement costs show that light industrial sectors and high-tech industrial sectors have a higher abatement cost, while energy-intensive heavy chemical industries have a lower abatement cost. Third, based on the allocation results, there are six industrial sub-sectors that have obtained major carbon emission permits, including the smelting and pressing of ferrous metals (S24), manufacturing of raw chemical materials and chemical products (S18), manufacturing of non-metallic mineral products (S23), smelting and pressing of non-ferrous metals (S25), production and supply of electric power and heat power (S35), and the processing of petroleum, coking, and processing of nuclear fuel (S19), accounting for 69.23% of the total carbon emissions permits. Furthermore, the study also classifies 37 industrial sectors to explore the emission reduction paths, and proposes corresponding policy recommendations for different categories.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:3:p:914-:d:204848
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/11/3/914/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/11/3/914/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Rose, Adam, 1990. "Reducing conflict in global warming policy : The potential of equity as a unifying principle," Energy Policy, Elsevier, vol. 18(10), pages 927-935, December.
    2. Adam Rose & Zhong Zhang, 2004. "Interregional burden-sharing of greenhouse gas mitigation in the United States," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 9(4), pages 477-500, October.
    3. Cong, Ren & Lo, Alex Y., 2017. "Emission trading and carbon market performance in Shenzhen, China," Applied Energy, Elsevier, vol. 193(C), pages 414-425.
    4. 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.
    5. Huiqin Jiang & Xinxiao Shao & Xiao Zhang & Jianqiang Bao, 2017. "A Study of the Allocation of Carbon Emission Permits among the Provinces of China Based on Fairness and Efficiency," Sustainability, MDPI, vol. 9(11), pages 1-17, November.
    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. 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.
    8. Ringius, Lasse & Torvanger, Asbjorn & Holtsmark, Bjart, 1998. "Can multi-criteria rules fairly distribute climate burdens?: OECD results from three burden sharing rules," Energy Policy, Elsevier, vol. 26(10), pages 777-793, August.
    9. Siqin Xiong & Yushen Tian & Junping Ji & Xiaoming Ma, 2017. "Allocation of Energy Consumption among Provinces in China: A Weighted ZSG-DEA Model," Sustainability, MDPI, vol. 9(11), pages 1-12, November.
    10. Baochen Yang & Chuanze Liu & Yunpeng Su & Xin Jing, 2017. "The Allocation of Carbon Intensity Reduction Target by 2020 among Industrial Sectors in China," Sustainability, MDPI, vol. 9(1), pages 1-19, January.
    11. 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.
    12. Yong Wang & Han Zhao & Fumei Duan & Ying Wang, 2018. "Initial Provincial Allocation and Equity Evaluation of China’s Carbon Emission Rights—Based on the Improved TOPSIS Method," Sustainability, MDPI, vol. 10(4), pages 1-27, March.
    13. Zhou, P. & Ang, B.W. & Wang, H., 2012. "Energy and CO2 emission performance in electricity generation: A non-radial directional distance function approach," European Journal of Operational Research, Elsevier, vol. 221(3), pages 625-635.
    14. Yi, Wen-Jing & Zou, Le-Le & Guo, Jie & Wang, Kai & Wei, Yi-Ming, 2011. "How can China reach its CO2 intensity reduction targets by 2020? A regional allocation based on equity and development," Energy Policy, Elsevier, vol. 39(5), pages 2407-2415, May.
    15. 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.
    16. Wei, Yi-Ming & Wang, Lu & Liao, Hua & Wang, Ke & Murty, Tad & Yan, Jinyue, 2014. "Responsibility accounting in carbon allocation: A global perspective," Applied Energy, Elsevier, vol. 130(C), pages 122-133.
    17. 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.
    18. Feng Dong & Ruyin Long & Zhuolin Li & Yuanju Dai, 2016. "Analysis of carbon emission intensity, urbanization and energy mix: evidence from 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. 82(2), pages 1375-1391, June.
    19. 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.
    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. Haoran Zhang & Rongxia Zhang & Guomin Li & Wei Li & Yongrok Choi, 2020. "Has China’s Emission Trading System Achieved the Development of a Low-Carbon Economy in High-Emission Industrial Subsectors?," Sustainability, MDPI, vol. 12(13), pages 1-20, July.
    2. Shengxian Ge & Xianyu Yu & Dequn Zhou & Xiuzhi Sang, 2019. "The Integrated Effect of Carbon Emissions Trading and Pollution Rights Trading for Power Enterprises—A Case Study of Chongqing," Sustainability, MDPI, vol. 11(11), pages 1-17, June.
    3. Qiuyue Li & Hao Wang & Zhenshan Li & Shangwei Yuan, 2022. "A Comparative Study of the Effect of Different Carbon-Reduction Policies on Outsourcing Remanufacturing," IJERPH, MDPI, vol. 19(6), pages 1-22, 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. Zhou, P. & Wang, M., 2016. "Carbon dioxide emissions allocation: A review," Ecological Economics, Elsevier, vol. 125(C), pages 47-59.
    2. 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.
    3. 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.
    4. Zhu, Bangzhu & Jiang, Mingxing & He, Kaijian & Chevallier, Julien & Xie, Rui, 2018. "Allocating CO2 allowances to emitters in China: A multi-objective decision approach," Energy Policy, Elsevier, vol. 121(C), pages 441-451.
    5. 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).
    6. Baochen Yang & Chuanze Liu & Yunpeng Su & Xin Jing, 2017. "The Allocation of Carbon Intensity Reduction Target by 2020 among Industrial Sectors in China," Sustainability, MDPI, vol. 9(1), pages 1-19, January.
    7. 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.
    8. Jiekun Song & Rui Chen & Xiaoping Ma, 2021. "Collaborative Allocation of Energy Consumption, Air Pollutants and CO 2 Emissions in China," Sustainability, MDPI, vol. 13(16), pages 1-17, August.
    9. Ciardiello, F. & Genovese, A. & Simpson, A., 2019. "Pollution responsibility allocation in supply networks: A game-theoretic approach and a case study," International Journal of Production Economics, Elsevier, vol. 217(C), pages 211-217.
    10. Qianting Zhu & Wenwu Tang, 2017. "Regional-Level Carbon Allocation in China Based on Sectoral Emission Patterns under the Peak Commitment," Sustainability, MDPI, vol. 9(4), pages 1-18, April.
    11. Fei Ye & Lixu Li & Zhiqiang Wang & Yina Li, 2018. "An Asymmetric Nash Bargaining Model for Carbon Emission Quota Allocation among Industries: Evidence from Guangdong Province, China," Sustainability, MDPI, vol. 10(11), pages 1-18, November.
    12. 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.
    13. Yu, Anyu & Lee, Andy & Chen, Yao, 2021. "Carbon allocation targeting with abatement capability: A firm-level study," International Journal of Production Economics, Elsevier, vol. 235(C).
    14. 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.
    15. 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.
    16. Minxing Jiang & Bangzhu Zhu & Julien Chevallier & Rui Xie, 2018. "Allocating provincial CO2 quotas for the Chinese national carbon program," Australian Journal of Agricultural and Resource Economics, Australian Agricultural and Resource Economics Society, vol. 62(3), pages 457-479, July.
    17. Jiang, Jingjing & Xie, Dejun & Ye, Bin & Shen, Bo & Chen, Zhanming, 2016. "Research on China’s cap-and-trade carbon emission trading scheme: Overview and outlook," Applied Energy, Elsevier, vol. 178(C), pages 902-917.
    18. Laura Rodríguez-Fernández & Ana Belén Fernández Carvajal & María Bujidos-Casado, 2020. "Allocation of Greenhouse Gas Emissions Using the Fairness Principle: A Multi-Country Analysis," Sustainability, MDPI, vol. 12(14), pages 1-15, July.
    19. Weidong Chen & Qing He, 2016. "Intersectoral burden sharing of CO 2 mitigation in China in 2020," Mitigation and Adaptation Strategies for Global Change, Springer, vol. 21(1), pages 1-14, January.
    20. Qingyou Yan & Yaxian Wang & Tomas Baležentis & Yikai Sun & Dalia Streimikiene, 2018. "Energy-Related CO 2 Emission in China’s Provincial Thermal Electricity Generation: Driving Factors and Possibilities for Abatement," Energies, MDPI, vol. 11(5), pages 1-25, April.

    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:11:y:2019:i:3:p:914-:d:204848. 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.