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On the road to China's 2020 carbon intensity target from the perspective of “double control”

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  • Zhu, Bangzhu
  • Jiang, Minxing
  • Wang, Kefan
  • Chevallier, Julien
  • Wang, Ping
  • Wei, Yi-Ming

Abstract

This paper investigates the path choice of achieving China's 2020 carbon intensity target by using a multiple attribute decision model from the perspective of “double control”, i.e. quantity (energy consumption and CO2 emissions) and intensity (energy intensity and carbon intensity). Firstly, we propose a novel integrated model to predict the quantity and intensity. The cumulative effects of several drivers for CO2 emissions are examined by Logarithmic Mean Divisia Index method. Secondly, the quantity and intensity are normalized to identify the feasible pathway of “double control” in various scenarios by multiple attribute decision model, and robustness test is carried out by a case study. The results show that per capita GDP has a significantly positive cumulative effect on CO2 emissions, whereas energy intensity has significantly negative one on it. The targeted carbon intensity by 2020 can be differentially realized in all scenarios. Both slow economic growth speed and substantial energy structure adjustment facilitate “double control”. The results suggest that the best pathway of “double control” depends on the policy makers’ preferences on the quantity control and intensity control. The policy implications of the findings are discussed.

Suggested Citation

  • Zhu, Bangzhu & Jiang, Minxing & Wang, Kefan & Chevallier, Julien & Wang, Ping & Wei, Yi-Ming, 2018. "On the road to China's 2020 carbon intensity target from the perspective of “double control”," Energy Policy, Elsevier, vol. 119(C), pages 377-387.
    • Handle: RePEc:eee:enepol:v:119:y:2018:i:c:p:377-387
    DOI: 10.1016/j.enpol.2018.04.025
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    Cited by:

    1. Zhu, Bangzhu & Zhang, Mengfan & Huang, Liqing & Wang, Ping & Su, Bin & Wei, Yi-Ming, 2020. "Exploring the effect of carbon trading mechanism on China's green development efficiency: A novel integrated approach," Energy Economics, Elsevier, vol. 85(C).
    2. Yang, Zhenbing & Shi, Qingquan & Lv, Xiangqiu & Shi, Qi, 2022. "Heterogeneous low-carbon targets and energy structure optimization: Does stricter carbon regulation really matter?," Structural Change and Economic Dynamics, Elsevier, vol. 60(C), pages 329-343.
    3. Wu, C.B. & Guan, P.B. & Zhong, L.N. & Lv, J. & Hu, X.F. & Huang, G.H. & Li, C.C., 2020. "An optimized low-carbon production planning model for power industry in coal-dependent regions - A case study of Shandong, China," Energy, Elsevier, vol. 192(C).
    4. Wang, Juan & Hu, Mingming & Tukker, Arnold & Rodrigues, João F.D., 2019. "The impact of regional convergence in energy-intensive industries on China's CO2 emissions and emission goals," Energy Economics, Elsevier, vol. 80(C), pages 512-523.
    5. Zhu, Junpeng & Lin, Boqiang, 2020. "Convergence analysis of city-level energy intensity in China," Energy Policy, Elsevier, vol. 139(C).
    6. Yang, Xue & Su, Bin, 2019. "Impacts of international export on global and regional carbon intensity," Applied Energy, Elsevier, vol. 253(C), pages 1-1.
    7. Yuan, Yongna & Duan, Hongbo & Tsvetanov, Tsvetan G., 2020. "Synergizing China's energy and carbon mitigation goals: General equilibrium modeling and policy assessment," Energy Economics, Elsevier, vol. 89(C).
    8. Zhou, Xiaoyong & Zhou, Dequn & Wang, Qunwei & Su, Bin, 2020. "Who shapes China's carbon intensity and how? A demand-side decomposition analysis," Energy Economics, Elsevier, vol. 85(C).
    9. Ning, Yadong & Chen, Kunkun & Zhang, Boya & Ding, Tao & Guo, Fei & Zhang, Ming, 2020. "Energy conservation and emission reduction path selection in China: A simulation based on Bi-Level multi-objective optimization model," Energy Policy, Elsevier, vol. 137(C).
    10. Jin, Zhida & Li, Zheng & Yang, Mian, 2022. "Producer services development and manufacturing carbon intensity: Evidence from an international perspective," Energy Policy, Elsevier, vol. 170(C).

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