IDEAS home Printed from https://ideas.repec.org/a/gam/jsusta/v15y2023i21p15306-d1267679.html
   My bibliography  Save this article

Carbon Emission Projection and Carbon Quota Allocation in the Beijing–Tianjin–Hebei Region of China under Carbon Neutrality Vision

Author

Listed:
  • Shuohua Zhang

    (School of Economics and Management, North China Electric Power University, Hui Long Guan, Chang Ping District, Beijing 102206, China)

  • Hanning Dong

    (Faculty of Arts and Social Sciences, University of Singapore, 21 Lower Kent Ridge Rd, Singapore 119077, Singapore)

  • Can Lu

    (School of Economics and Management, North China Electric Power University, No. 689 Hua Dian Road, Baoding 071003, China
    Energy and Economic Development & Philosophy and Social Science Research Base of Hebei Province (North China Electric Power University), No. 689 Hua Dian Road, Baoding 071003, China)

  • Wei Li

    (School of Economics and Management, North China Electric Power University, No. 689 Hua Dian Road, Baoding 071003, China
    Energy and Economic Development & Philosophy and Social Science Research Base of Hebei Province (North China Electric Power University), No. 689 Hua Dian Road, Baoding 071003, China)

Abstract

Supported by the coordinated development strategy, the Beijing–Tianjin–Hebei (BTH) region has achieved rapid development but also faces severe energy consumption and environmental pollution problems. As the main responsibility of emission reduction, the coordinated and orderly implementation of carbon emission reduction in Beijing, Tianjin, and Hebei is of great significance to the realization of the carbon neutrality target. Based on this, this study comprehensively uses the expanded STIRPAT model, optimized extreme learning machine (ELM) network, entropy method, and zero-sum gains DEA (ZSG-DEA) model to explore the carbon emission drivers, long-term emission reduction pathway, and carbon quota allocation in the BTH region. The results of the driving factor analysis indicate that the proportion of non-fossil energy consumption is a significant driving factor for Beijing’s carbon emissions, and the improvement of the electrification level can inhibit the carbon emissions. The total energy consumption has the greatest impact on the carbon emissions of Tianjin and Hebei. The simulation results reveal that under the constraint of the carbon neutrality target, Beijing, Tianjin, and Hebei should formulate more stringent emission reduction measures to ensure that the overall carbon emission will reach its peak in 2030. The cumulative emission reduction rate should exceed 60% in 2060, and negative carbon technology should be used to offset carbon emissions of not less than 360 million tons (Mt) per year by 2060. Furthermore, the allocation results show that Beijing will receive a greater carbon quota than Hebei. The final allocation scheme will greatly promote and encourage carbon emission reduction in Hebei Province, which is conducive to achieving the goal of carbon neutrality.

Suggested Citation

  • Shuohua Zhang & Hanning Dong & Can Lu & Wei Li, 2023. "Carbon Emission Projection and Carbon Quota Allocation in the Beijing–Tianjin–Hebei Region of China under Carbon Neutrality Vision," Sustainability, MDPI, vol. 15(21), pages 1-29, October.
    • Handle: RePEc:gam:jsusta:v:15:y:2023:i:21:p:15306-:d:1267679
    as

    Download full text from publisher

    File URL: https://www.mdpi.com/2071-1050/15/21/15306/pdf
    Download Restriction: no
    File URL: https://www.mdpi.com/2071-1050/15/21/15306/
    Download Restriction: no
    ---><---

    References listed on IDEAS

    as
    1. Xin Yang & Yifei Sima & Yabo Lv & Mingwei Li, 2023. "Research on Influencing Factors of Residential Building Carbon Emissions and Carbon Peak: A Case of Henan Province in China," Sustainability, MDPI, vol. 15(13), pages 1-18, June.
    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. Yuhong Zhao & Ruirui Liu & Zhansheng Liu & Liang Liu & Jingjing Wang & Wenxiang Liu, 2023. "A Review of Macroscopic Carbon Emission Prediction Model Based on Machine Learning," Sustainability, MDPI, vol. 15(8), pages 1-28, April.
    4. Lins, Marcos P. Estellita & Gomes, Eliane G. & Soares de Mello, Joao Carlos C. B. & Soares de Mello, Adelino Jose R., 2003. "Olympic ranking based on a zero sum gains DEA model," European Journal of Operational Research, Elsevier, vol. 148(2), pages 312-322, July.
    5. Zhou, P. & Wang, M., 2016. "Carbon dioxide emissions allocation: A review," Ecological Economics, Elsevier, vol. 125(C), pages 47-59.
    6. Wang, Xiaojun & Chen, Yiping & Chen, Jingjing & Mao, Bingjing & Peng, Lihong & Yu, Ang, 2022. "China's CO2 regional synergistic emission reduction: Killing two birds with one stone?," Energy Policy, Elsevier, vol. 168(C).
    7. Qin, Quande & Liu, Yuan & Huang, Jia-Ping, 2020. "A cooperative game analysis for the allocation of carbon emissions reduction responsibility in China's power industry," Energy Economics, Elsevier, vol. 92(C).
    8. Shan, Yuli & Liu, Jianghua & Liu, Zhu & Xu, Xinwanghao & Shao, Shuai & Wang, Peng & Guan, Dabo, 2016. "New provincial CO2 emission inventories in China based on apparent energy consumption data and updated emission factors," Applied Energy, Elsevier, vol. 184(C), pages 742-750.
    9. Yuan Zeng & Wengang Zhang & Jingwen Sun & Li’ao Sun & Jun Wu, 2023. "Research on Regional Carbon Emission Reduction in the Beijing–Tianjin–Hebei Urban Agglomeration Based on System Dynamics: Key Factors and Policy Analysis," Energies, MDPI, vol. 16(18), pages 1-20, September.
    10. Huang, Ren & Zhang, Sufang & Wang, Peng, 2022. "Key areas and pathways for carbon emissions reduction in Beijing for the “Dual Carbon” targets," Energy Policy, Elsevier, vol. 164(C).
    11. Huo, Tengfei & Xu, Linbo & Liu, Bingsheng & Cai, Weiguang & Feng, Wei, 2022. "China’s commercial building carbon emissions toward 2060: An integrated dynamic emission assessment model," Applied Energy, Elsevier, vol. 325(C).
    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. Fanmin Liu & Xianchao Zhao & Mengjie Wang, 2025. "Spatial Network Heterogeneity of Land Use Carbon Emissions and Ecosystem Services in Chang-Zhu-Tan Urban Agglomeration," Land, MDPI, vol. 14(11), pages 1-29, October.
    2. Changjiang Mao & Jian Luo & Shengyang Jiao & Bin Zhao, 2025. "Logarithmic Mean Divisia Index Analysis and Dynamic Back Propagation Neural Network Prediction of Transport Carbon Emissions in Henan Province," Energies, MDPI, vol. 18(7), pages 1-18, 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. 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.
    2. Mei, Tianhua & Liu, Jie & Guo, Jianming & Siano, Pierluigi & Jin, Xuanxuan, 2022. "Allocation of emission allowances considering strategic voting," Energy Economics, Elsevier, vol. 114(C).
    3. 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.
    4. Qinliang Tan & Jin Zheng & Yihong Ding & Yimei Zhang, 2020. "Provincial Carbon Emission Quota Allocation Study in China from the Perspective of Abatement Cost and Regional Cooperation," Sustainability, MDPI, vol. 12(20), pages 1-20, October.
    5. 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).
    6. Guoyu Wang & Jinsheng Zhou, 2022. "Multiobjective Optimization of Carbon Emission Reduction Responsibility Allocation in the Open-Pit Mine Production Process against the Background of Peak Carbon Dioxide Emissions," Sustainability, MDPI, vol. 14(15), pages 1-21, August.
    7. Dalai Ma & Yaping Xiao & Na Zhao, 2022. "Optimization and Spatiotemporal Differentiation of Carbon Emission Rights Allocation in the Power Industry in the Yangtze River Economic Belt," Sustainability, MDPI, vol. 14(9), pages 1-15, April.
    8. Jiancheng Qin & Lei Gao & Weihu Tu & Jing He & Jingzhe Tang & Shuying Ma & Xiaoyang Zhao & Xingzhe Zhu & Karthikeyan Brindha & Hui Tao, 2022. "Decomposition and Decoupling Analysis of Carbon Emissions in Xinjiang Energy Base, China," Energies, MDPI, vol. 15(15), pages 1-18, July.
    9. 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).
    10. Yanyan Ke & Lu Zhou & Minglei Zhu & Yan Yang & Rui Fan & Xianrui Ma, 2023. "Scenario Prediction of Carbon Emission Peak of Urban Residential Buildings in China’s Coastal Region: A Case of Fujian Province," Sustainability, MDPI, vol. 15(3), pages 1-17, January.
    11. Yuxue Zhang & Rui Wang & Xingyuan Yang & He Zhang, 2023. "Can China Achieve Its Carbon Emission Peak Target? Empirical Evidence from City-Scale Driving Factors and Emission Reduction Strategies," Land, MDPI, vol. 12(6), pages 1-21, May.
    12. Jiale He, 2025. "The impact of energy transition policies on urban green innovation: evidence from the new energy demonstration cities in China," Economic Change and Restructuring, Springer, vol. 58(3), pages 1-24, June.
    13. Hongyang Qiao & Sanmang Wu, 2025. "Decoupling Factor Analysis for Sustainable Development in China’s Four Municipalities Using the Tapio Model," Sustainability, MDPI, vol. 17(6), pages 1-26, March.
    14. Teng, Meixuan & Burke, Paul J. & Liao, Hua, 2019. "The demand for coal among China's rural households: Estimates of price and income elasticities," Energy Economics, Elsevier, vol. 80(C), pages 928-936.
    15. Kangyin Dong & Yalin Han & Yue Dou & Muhammad Shahbaz, 2022. "Moving toward carbon neutrality: Assessing natural gas import security and its impact on CO2 emissions," Sustainable Development, John Wiley & Sons, Ltd., vol. 30(4), pages 751-770, August.
    16. Alireza Amirteimoori & Sohrab Kordrostami, 2012. "A distance-based measure of super efficiency in data envelopment analysis: an application to gas companies," Journal of Global Optimization, Springer, vol. 54(1), pages 117-128, September.
    17. Du, Minzhe & Wu, Fenger & Luo, Lichun & Wang, Qiya & Liao, Liping, 2025. "Spatial effects of the market-based energy allocation on energy efficiency: A quasi-natural experiment of energy quota trading," Energy, Elsevier, vol. 318(C).
    18. J-L Hu & C-Y Fang, 2010. "Do market share and efficiency matter for each other? An application of the zero-sum gains data envelopment analysis," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 61(4), pages 647-657, April.
    19. Yu, Shasha & Lei, Ming & Deng, Honghui, 2023. "Evaluation to fixed-sum-outputs DMUs by non-oriented equilibrium efficient frontier DEA approach with Nash bargaining-based selection," Omega, Elsevier, vol. 115(C).
    20. Khalil Nimer & Muath Abdelqader & Cemil Kuzey & Ali Uyar, 2024. "Emission targeting and carbon emissions: The moderating effect of female directors," Business Strategy and the Environment, Wiley Blackwell, vol. 33(4), pages 3480-3504, May.

    More about this item

    Keywords

    ;
    ;
    ;
    ;

    Statistics

    Access and download statistics

    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:15:y:2023:i:21:p:15306-:d:1267679. 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.