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The Allocation of Carbon Intensity Reduction Target by 2030 among Cities in China

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  • Longyu Shi

    (Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China)

  • Fengmei Yang

    (Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China
    University of Chinese Academy of Sciences, Beijing 100049, China)

  • Lijie Gao

    (Key Laboratory of Urban Environment and Health, Institute of Urban Environment, Chinese Academy of Sciences, Xiamen 361021, China)

Abstract

The regional allocation of carbon emission quotas is of great significance to realize the carbon emission target. Basing on the combination of the multi-index method and the improved equal-proportion distribution method, and fully considering the differences in economic factors, population factors, energy factors, technological factors among cities, China’s 2030 carbon intensity reduction target was allocated. The results indicate that: (1) Under the target constraint of 60% reduction in CO 2 emissions per unit of Gross Domestic Product (GDP) (carbon intensity) in 2030 compared to 2005, the carbon intensity target reduction rate (CITRR) of 285 Chinese cities is between 17.65% and 141.14%, with an average reduction rate of 51.52%; (2) the CITRR of cities presents significant spatial positive correlation, and the Global Moran I correlation index is 0.38; and (3) the distribution trend of CITRR is the same as the general trend of economic development of China, showing a basic trend of gradual decline from south to north and from coastal to inland. The allocation method takes into account fairness and efficiency, and reflects the differences between cities, so that the allocation results are likely to be accepted by all parties. Meanwhile, this method breaks the limitation of the lack of city’s data and is likely to implement in actual operation. Cities should choose distinguished low-carbon economic development paths, in combination with their characteristics of economic and social development, and carry out inter-city cooperation to promote carbon emission reduction steadily.

Suggested Citation

  • Longyu Shi & Fengmei Yang & Lijie Gao, 2020. "The Allocation of Carbon Intensity Reduction Target by 2030 among Cities in China," Energies, MDPI, vol. 13(22), pages 1-14, November.
  • Handle: RePEc:gam:jeners:v:13:y:2020:i:22:p:6006-:d:446501
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    1. Zhu, Bangzhu & Ye, Shunxin & Jiang, Minxing & Wang, Ping & Wu, Zhanchi & Xie, Rui & Chevallier, Julien & Wei, Yi-Ming, 2019. "Achieving the carbon intensity target of China: A least squares support vector machine with mixture kernel function approach," Applied Energy, Elsevier, vol. 233, pages 196-207.
    2. Grossman, G.M & Krueger, A.B., 1991. "Environmental Impacts of a North American Free Trade Agreement," Papers 158, Princeton, Woodrow Wilson School - Public and International Affairs.
    3. World Bank & the People’s Republic of China Development Research Center of the State Council, 2013. "China 2030 : Building a Modern, Harmonious, and Creative Society," World Bank Publications - Books, The World Bank Group, number 12925.
    4. Frank Jotzo & John Pezzey, 2007. "Optimal intensity targets for greenhouse gas emissions trading under uncertainty," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 38(2), pages 259-284, October.
    5. Elzen, Michel den & Fekete, Hanna & Höhne, Niklas & Admiraal, Annemiek & Forsell, Nicklas & Hof, Andries F. & Olivier, Jos G.J. & Roelfsema, Mark & van Soest, Heleen, 2016. "Greenhouse gas emissions from current and enhanced policies of China until 2030: Can emissions peak before 2030?," Energy Policy, Elsevier, vol. 89(C), pages 224-236.
    6. Jaffe, Adam B. & Newell, Richard G. & Stavins, Robert N., 2005. "A tale of two market failures: Technology and environmental policy," Ecological Economics, Elsevier, vol. 54(2-3), pages 164-174, August.
    7. Feng Dong & Ruyin Long & Zhuolin Li & Yuanju Dai, 2016. "Analysis of carbon emission intensity, urbanization and energy mix: evidence from 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. 82(2), pages 1375-1391, June.
    8. Hao, Yu & Liao, Hua & Wei, Yi-Ming, 2015. "Is China’s carbon reduction target allocation reasonable? An analysis based on carbon intensity convergence," Applied Energy, Elsevier, vol. 142(C), pages 229-239.
    9. Wang, Shaojian & Liu, Xiaoping, 2017. "China’s city-level energy-related CO2 emissions: Spatiotemporal patterns and driving forces," Applied Energy, Elsevier, vol. 200(C), pages 204-214.
    10. Smith, L. Vanessa & Tarui, Nori & Yamagata, Takashi, 2021. "Assessing the impact of COVID-19 on global fossil fuel consumption and CO2 emissions," Energy Economics, Elsevier, vol. 97(C).
    11. Yao Qian & Lang Sun & Quanyi Qiu & Lina Tang & Xiaoqi Shang & Chengxiu Lu, 2020. "Analysis of CO 2 Drivers and Emissions Forecast in a Typical Industry-Oriented County: Changxing County, China," Energies, MDPI, vol. 13(5), pages 1-21, March.
    12. Vollebergh, Herman R.J. & Kemfert, Claudia, 2005. "The role of technological change for a sustainable development," Ecological Economics, Elsevier, vol. 54(2-3), pages 133-147, August.
    13. Wang, Zhaohua & Zhang, Bin & Liu, Tongfan, 2016. "Empirical analysis on the factors influencing national and regional carbon intensity in China," Renewable and Sustainable Energy Reviews, Elsevier, vol. 55(C), pages 34-42.
    14. Ang, B.W. & Liu, N., 2006. "A cross-country analysis of aggregate energy and carbon intensities," Energy Policy, Elsevier, vol. 34(15), pages 2398-2404, October.
    15. Zhang, Yue-Jun & Wang, Ao-Dong & Da, Ya-Bin, 2014. "Regional allocation of carbon emission quotas in China: Evidence from the Shapley value method," Energy Policy, Elsevier, vol. 74(C), pages 454-464.
    16. Chang, Kai & Chang, Hao, 2016. "Cutting CO2 intensity targets of interprovincial emissions trading in China," Applied Energy, Elsevier, vol. 163(C), pages 211-221.
    17. Feng, Zhiying & Tang, Wenhu & Niu, Zhewen & Wu, Qinghua, 2018. "Bi-level allocation of carbon emission permits based on clustering analysis and weighted voting: A case study in China," Applied Energy, Elsevier, vol. 228(C), pages 1122-1135.
    18. Zhao, Xueting & Burnett, J. Wesley & Fletcher, Jerald J., 2013. "Spatial Analysis of China Provincial-Level CO2 Emission Intensity," 2013 Annual Meeting, August 4-6, 2013, Washington, D.C. 149006, Agricultural and Applied Economics Association.
    19. Soimakallio, Sampo & Saikku, Laura, 2012. "CO2 emissions attributed to annual average electricity consumption in OECD (the Organisation for Economic Co-operation and Development) countries," Energy, Elsevier, vol. 38(1), pages 13-20.
    20. Apergis, Nicholas & Eleftheriou, Sofia & Payne, James E., 2013. "The relationship between international financial reporting standards, carbon emissions, and R&D expenditures: Evidence from European manufacturing firms," Ecological Economics, Elsevier, vol. 88(C), pages 57-66.
    21. Berkhout, Peter H. G. & Muskens, Jos C. & W. Velthuijsen, Jan, 2000. "Defining the rebound effect," Energy Policy, Elsevier, vol. 28(6-7), pages 425-432, June.
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