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Optimization and Spatiotemporal Differentiation of Carbon Emission Rights Allocation in the Power Industry in the Yangtze River Economic Belt

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  • Dalai Ma

    (School of Management, Chongqing University of Technology, Chongqing 400054, China)

  • Yaping Xiao

    (School of Management, Chongqing University of Technology, Chongqing 400054, China)

  • Na Zhao

    (School of Management, Chongqing University of Technology, Chongqing 400054, China)

Abstract

Reasonable allocation of carbon emission rights aids in the realization of the goal of carbon emission reduction. The purpose of this paper is to examine how carbon emission rights in the power sector in the Yangtze River Economic Belt (the YREB) are distributed. The YREB spans China’s eastern, central, and western areas. The levels of development and resource endowment differ significantly across regions, resulting in great heterogeneity in the YREB provinces’ carbon emission rights distribution in the power sector. The ZSG–DEA model is used in this paper to re-adjust the power sector’s carbon emission quotas in each province to achieve optimal efficiency under the country’s overall carbon emission reduction target. The results show that: (1) In most provinces, the power sector’s initial distribution efficiency is inefficient. Only Zhejiang and Yunnan have reached the production frontier, with Jiangxi and Chongqing having the lowest distribution efficiency. In the future, we should concentrate our efforts on them for conserving energy and lowering emissions; (2) The initial distribution efficiency of the power sector in the YREB’s upstream, midstream, and downstream regions is considerably different. Most upstream and downstream provinces have higher carbon emission quotas, while most midstream provinces have less, implying that the power sector in the midstream provinces faces greater emission reduction challenges; (3) The carbon emission quotas of the power industry varies greatly between provinces and shows different spatial features over time. In the early stage (2021–2027), the carbon emission quota varies substantially, while for the later stage (2027–2030), it is rather balanced. Zhejiang, Jiangsu, Sichuan, and Yunnan are more likely to turn into sellers in the market for carbon emission trading with larger carbon emission quotas. While Jiangxi and Chongqing are more likely to turn into buyers in the market for carbon emission trading with fewer carbon emission quotas. Other provinces’ carbon emission quotas are more evenly distributed. To successfully achieve China’s emission reduction target by 2030, the YREB should promote regional collaboration, optimize industrial structure, accelerate technical innovation, establish emission reduction regulations, and provide financial support based on local conditions.

Suggested Citation

  • 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.
    • Handle: RePEc:gam:jsusta:v:14:y:2022:i:9:p:5201-:d:802103
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    1. Oliver Sartor & Clement Palli�re & Stephen Lecourt, 2014. "Benchmark-based allocations in EU ETS Phase 3: an early assessment," Climate Policy, Taylor & Francis Journals, vol. 14(4), pages 507-524, July.
    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. E G Gomes & M P E Lins, 2008. "Modelling undesirable outputs with zero sum gains data envelopment analysis models," Journal of the Operational Research Society, Palgrave Macmillan;The OR Society, vol. 59(5), pages 616-623, May.
    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. & Sun, Z.R. & Zhou, D.Q., 2014. "Optimal path for controlling CO2 emissions in China: A perspective of efficiency analysis," Energy Economics, Elsevier, vol. 45(C), pages 99-110.
    6. 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).
    7. Zhang, Yue-Jun & Wang, Ao-Dong & Tan, Weiping, 2015. "The impact of China's carbon allowance allocation rules on the product prices and emission reduction behaviors of ETS-covered enterprises," Energy Policy, Elsevier, vol. 86(C), pages 176-185.
    8. Robert E. Hall & Charles I. Jones, 1999. "Why do Some Countries Produce So Much More Output Per Worker than Others?," The Quarterly Journal of Economics, President and Fellows of Harvard College, vol. 114(1), pages 83-116.
    9. Guo, Ji & Zhao, Mengke & Wu, Xianhua & Shi, Beibei & Santibanez Gonzalez, Ernesto D.R., 2021. "Study on the distribution of PM emission rights in various provinces of China based on a new efficiency and equity two-objective DEA model," Ecological Economics, Elsevier, vol. 183(C).
    10. Yu, Anyu & You, Jianxin & Rudkin, Simon & Zhang, Hao, 2019. "Industrial carbon abatement allocations and regional collaboration: Re-evaluating China through a modified data envelopment analysis," Applied Energy, Elsevier, vol. 233, pages 232-243.
    11. Schmidt, Robert C. & Heitzig, Jobst, 2014. "Carbon leakage: Grandfathering as an incentive device to avert firm relocation," Journal of Environmental Economics and Management, Elsevier, vol. 67(2), pages 209-223.
    12. Yang, Mian & Hou, Yaru & Ji, Qiang & Zhang, Dayong, 2020. "Assessment and optimization of provincial CO2 emission reduction scheme in China: An improved ZSG-DEA approach," Energy Economics, Elsevier, vol. 91(C).
    13. Burtraw, Dallas & McCormack, Kristen, 2017. "Consignment auctions of free emissions allowances," Energy Policy, Elsevier, vol. 107(C), pages 337-344.
    14. Pan, Xunzhang & Teng, Fei & Wang, Gehua, 2014. "Sharing emission space at an equitable basis: Allocation scheme based on the equal cumulative emission per capita principle," Applied Energy, Elsevier, vol. 113(C), pages 1810-1818.
    15. 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.
    16. 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.
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