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The allocation of carbon emission intensity reduction target by 2020 among provinces in China

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  • Yue-Jun Zhang
  • Jun-Fang Hao

Abstract

According to the combined principles of fairness and efficiency, a comprehensive allocating indicator system is developed, and the TOPSIS approach is applied to allocate China’s 40–45 % carbon emission intensity (carbon emission per unit of GDP) reduction target by 2020. The results indicate that, first of all, the unequally weighted indicator system outperforms the equally weighted one according to regional developing situation in China; and the most important indicator affecting the allowance allocation is carbon reduction responsibility, followed by future development right and emission reduction efficiency. Second, China’s carbon emission intensity should be cut, but its absolute carbon emission volume may inevitably increase in the future due to the continuous economic growth, and we confirm that the western provinces may take the highest shares to increase carbon emissions, followed by the central, northeast and eastern provinces. Finally, in order to achieve the national target of carbon emission intensity reduction, the northeast and eastern provinces require reducing carbon emission intensity significantly from 2013 to 2020, while the central and western provinces should be given more developing room. Copyright Springer Science+Business Media Dordrecht 2015

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  • Yue-Jun Zhang & Jun-Fang Hao, 2015. "The allocation of carbon emission intensity reduction target by 2020 among provinces 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. 79(2), pages 921-937, November.
    • Handle: RePEc:spr:nathaz:v:79:y:2015:i:2:p:921-937
    DOI: 10.1007/s11069-015-1883-7
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    5. Zhang, Cheng & Wang, Qunwei & Shi, Dan & Li, Pengfei & Cai, Wanhuan, 2016. "Scenario-based potential effects of carbon trading in China: An integrated approach," Applied Energy, Elsevier, vol. 182(C), pages 177-190.
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    7. 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.
    8. Wen, Wen & Feng, Cuiyang & Zhou, Hao & Zhang, Li & Wu, Xiaohui & Qi, Jianchuan & Yang, Xuechun & Liang, Yuhan, 2021. "Critical provincial transmission sectors for carbon dioxide emissions in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 149(C).
    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.
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    11. Tang, Ling & Shi, Jiarui & Bao, Qin, 2016. "Designing an emissions trading scheme for China with a dynamic computable general equilibrium model," Energy Policy, Elsevier, vol. 97(C), pages 507-520.
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    16. 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.
    17. Liyin Shen & Yingli Lou & Yali Huang & Jindao Chen, 2018. "A driving–driven perspective on the key carbon emission sectors 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. 93(1), pages 349-371, August.
    18. Zhang, Yue-Jun & Peng, Yu-Lu & Ma, Chao-Qun & Shen, Bo, 2017. "Can environmental innovation facilitate carbon emissions reduction? Evidence from China," Energy Policy, Elsevier, vol. 100(C), pages 18-28.
    19. Yang, Lin & Li, Fengyu & Zhang, Xian, 2016. "Chinese companies’ awareness and perceptions of the Emissions Trading Scheme (ETS): Evidence from a national survey in China," Energy Policy, Elsevier, vol. 98(C), pages 254-265.

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