IDEAS home Printed from https://ideas.repec.org/a/eee/tefoso/v159y2020ics0040162520310246.html
   My bibliography  Save this article

Analysis of the carbon emission reduction potential of China's key industries under the IPCC 2 °C and 1.5 °C limits

Author

Listed:
  • Wu, Feng
  • Huang, Ningyu
  • Zhang, Fan
  • Niu, Lulu
  • Zhang, Yali

Abstract

Carbon emission from human activities is one of the main factors inducing the on-going global warming. It is, therefore, essential to establish a shared responsibility in industry for carbon emissions reduction. In this study, we examined the allocation of carbon emission rights in China's six high-energy-consuming industries from the perspective of allocation efficiency. The initial carbon emission quota was iteratively optimized using the zero-sum gains data envelopment analysis (ZSG-DEA) model. Furthermore, a scenario-based method was used to predict the future of various industries under a 1.5 °C warming target. According to our analysis, the largest carbon emission quota was in the transport industry, at 19.61 Gt CO2 under a 2 °C target and 16.27 Gt CO2 under a 1.5 °C target. The electric power industry and the iron and steel industry show the greatest potential for emissions reduction, and significant effort is now needed to achieve the allocation efficiency target. A “high economic growth and low energy consumption” scenario was more conducive to the sustainable growth of industry. Emissions reduction should focus on the electric power industry and the transport industry. In addition, the use of energy-saving and emissions-reducing technologies in high-energy-consuming industries should be increased.

Suggested Citation

  • Wu, Feng & Huang, Ningyu & Zhang, Fan & Niu, Lulu & Zhang, Yali, 2020. "Analysis of the carbon emission reduction potential of China's key industries under the IPCC 2 °C and 1.5 °C limits," Technological Forecasting and Social Change, Elsevier, vol. 159(C).
  • Handle: RePEc:eee:tefoso:v:159:y:2020:i:c:s0040162520310246
    DOI: 10.1016/j.techfore.2020.120198
    as

    Download full text from publisher

    File URL: http://www.sciencedirect.com/science/article/pii/S0040162520310246
    Download Restriction: Full text for ScienceDirect subscribers only

    File URL: https://libkey.io/10.1016/j.techfore.2020.120198?utm_source=ideas
    LibKey link: if access is restricted and if your library uses this service, LibKey will redirect you to where you can use your library subscription to access this item
    ---><---

    As the access to this document is restricted, you may want to search for a different version of it.

    References listed on IDEAS

    as
    1. Zhang, Fan & Deng, Xiangzheng & Phillips, Fred & Fang, Chuanglin & Wang, Chao, 2020. "Impacts of industrial structure and technical progress on carbon emission intensity: Evidence from 281 cities in China," Technological Forecasting and Social Change, Elsevier, vol. 154(C).
    2. Charnes, A. & Cooper, W. W. & Rhodes, E., 1978. "Measuring the efficiency of decision making units," European Journal of Operational Research, Elsevier, vol. 2(6), pages 429-444, November.
    3. 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.
    4. Wang, Guofeng & Deng, Xiangzheng & Wang, Jingyu & Zhang, Fan & Liang, Shiqi, 2019. "Carbon emission efficiency in China: A spatial panel data analysis," China Economic Review, Elsevier, vol. 56(C), pages 1-1.
    5. 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.
    6. Lee, Cheng F. & Lin, Sue J. & Lewis, Charles, 2008. "Analysis of the impacts of combining carbon taxation and emission trading on different industry sectors," Energy Policy, Elsevier, vol. 36(2), pages 722-729, February.
    7. 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.
    8. Yang, Lisha & Li, Zhi, 2017. "Technology advance and the carbon dioxide emission in China – Empirical research based on the rebound effect," Energy Policy, Elsevier, vol. 101(C), pages 150-161.
    9. 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.
    10. Wang, Q.W. & Zhou, P. & Shen, N. & Wang, S.S., 2013. "Measuring carbon dioxide emission performance in Chinese provinces: A parametric approach," Renewable and Sustainable Energy Reviews, Elsevier, vol. 21(C), pages 324-330.
    11. 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.
    12. R. D. Banker & A. Charnes & W. W. Cooper, 1984. "Some Models for Estimating Technical and Scale Inefficiencies in Data Envelopment Analysis," Management Science, INFORMS, vol. 30(9), pages 1078-1092, September.
    13. 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.
    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. Tan, Xiujie & Liu, Yishuang & Dong, Hanmin & Zhang, Zhan, 2022. "The effect of carbon emission trading scheme on energy efficiency: Evidence from China," Economic Analysis and Policy, Elsevier, vol. 75(C), pages 506-517.
    2. Bagchi, Prantik & Sahu, Santosh Kumar & Kumar, Ajay & Tan, Kim Hua, 2022. "Analysis of carbon productivity for firms in the manufacturing sector of India," Technological Forecasting and Social Change, Elsevier, vol. 178(C).
    3. Wang, Fengjuan & Lv, Chengwei & Xu, Jiuping, 2023. "Carbon awareness oriented data center location and configuration: An integrated optimization method," Energy, Elsevier, vol. 278(C).
    4. Wang, Xiaoling & Zhang, Tianyue & Nathwani, Jatin & Yang, Fangming & Shao, Qinglong, 2022. "Environmental regulation, technology innovation, and low carbon development: Revisiting the EKC Hypothesis, Porter Hypothesis, and Jevons’ Paradox in China's iron & steel industry," Technological Forecasting and Social Change, Elsevier, vol. 176(C).
    5. Liu, S. & Xiao, Q., 2021. "An empirical analysis on spatial correlation investigation of industrial carbon emissions using SNA-ICE model," Energy, Elsevier, vol. 224(C).
    6. Yang, Fan & Lee, Hyoungsuk, 2022. "An innovative provincial CO2 emission quota allocation scheme for Chinese low-carbon transition," Technological Forecasting and Social Change, Elsevier, vol. 182(C).

    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. Xin Zheng & Shenya Mao & Siqi Lv & Sheng Wang, 2022. "An Optimization Study of Provincial Carbon Emission Allowance Allocation in China Based on an Improved Dynamic Zero-Sum-Gains Slacks-Based-Measure Model," Sustainability, MDPI, vol. 14(12), pages 1-22, June.
    2. 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).
    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. Chu, Junfei & Hou, Tianteng & Li, Feng & Yuan, Zhe, 2024. "Dynamic bargaining game DEA carbon emissions abatement allocation and the Nash equilibrium," Energy Economics, Elsevier, vol. 134(C).
    5. Yongjun Li & Wenhui Hou & Weiwei Zhu & Feng Li & Liang Liang, 2021. "Provincial carbon emission performance analysis in China based on a Malmquist data envelopment analysis approach with fixed-sum undesirable outputs," Annals of Operations Research, Springer, vol. 304(1), pages 233-261, September.
    6. Du, Xiaoyun & Meng, Conghui & Guo, Zhenhua & Yan, Hang, 2023. "An improved approach for measuring the efficiency of low carbon city practice in China," Energy, Elsevier, vol. 268(C).
    7. Alexandre Marinho & Simone de Souza Cardoso & Vivian Vicente de Almeida, 2009. "Avaliação da Eficiência Técnica dos Países nos Jogos Olímpicos de Pequim – 2008," Discussion Papers 1394, Instituto de Pesquisa Econômica Aplicada - IPEA.
    8. Kangjuan Lv & Yu Cheng & Yousen Wang, 2021. "Does regional innovation system efficiency facilitate energy-related carbon dioxide intensity reduction in China?," Environment, Development and Sustainability: A Multidisciplinary Approach to the Theory and Practice of Sustainable Development, Springer, vol. 23(1), pages 789-813, January.
    9. Ding, Tao & Zhang, Yun & Zhang, Danlu & Li, Feng, 2023. "Performance evaluation of Chinese research universities: A parallel interactive network DEA approach with shared and fixed sum inputs," Socio-Economic Planning Sciences, Elsevier, vol. 87(PA).
    10. Zhang, Ning & Zhao, Yu & Wang, Na, 2022. "Is China's energy policy effective for power plants? Evidence from the 12th Five-Year Plan energy saving targets," Energy Economics, Elsevier, vol. 112(C).
    11. Yang, Min & Li, Yong Jun & Liang, Liang, 2015. "A generalized equilibrium efficient frontier data envelopment analysis approach for evaluating DMUs with fixed-sum outputs," European Journal of Operational Research, Elsevier, vol. 246(1), pages 209-217.
    12. Li, Feng & Zhang, Danlu & Zhang, Jinyu & Kou, Gang, 2022. "Measuring the energy production and utilization efficiency of Chinese thermal power industry with the fixed-sum carbon emission constraint," International Journal of Production Economics, Elsevier, vol. 252(C).
    13. 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.
    14. 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.
    15. Bougnol, M.-L. & Dulá, J.H. & Estellita Lins, M.P. & Moreira da Silva, A.C., 2010. "Enhancing standard performance practices with DEA," Omega, Elsevier, vol. 38(1-2), pages 33-45, February.
    16. Alexandre de Cássio Rodrigues & Carlos Alberto Gonçalves & Tiago Silveira Gontijo, 2019. "A two-stage DEA model to evaluate the efficiency of countries at the Rio 2016 Olympic Games," Economics Bulletin, AccessEcon, vol. 39(2), pages 1538-1545.
    17. 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).
    18. Zeng, Shihong & Jiang, Xue & Su, Bin & Nan, Xin, 2018. "China's SO2 shadow prices and environmental technical efficiency at the province level," International Review of Economics & Finance, Elsevier, vol. 57(C), pages 86-102.
    19. 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.
    20. 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.

    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:eee:tefoso:v:159:y:2020:i:c:s0040162520310246. 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: Catherine Liu (email available below). General contact details of provider: http://www.sciencedirect.com/science/journal/00401625 .

    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.