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Regional-Level Carbon Allocation in China Based on Sectoral Emission Patterns under the Peak Commitment

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  • Qianting Zhu

    (School of Business Administration, China University of Petroleum at Beijing, Beijing 102249, China)

  • Wenwu Tang

    (Center for Applied GIScience, Department of Geography and Earth Sciences, University of North Carolina, Charlotte, NC 28223, USA)

Abstract

The Chinese government has committed to reaching its carbon emissions peak by 2030, which is a major undertaking. However, traditional carbon allocation processes may face a suite of difficulties, including the dynamics of the allocation principle, the independence of the allocation entities and data availability. Considering these difficulties, in this study, we developed a multi-level carbon allocation model that integrates five sectors and 30 provinces in China. Based on the clustering of the sectoral carbon emission of major countries (or regions), the model simulates and analyzes carbon allocation at the provincial level in China under the peak commitment. The results of this study are as follows: First, in contrast to allocating national carbon allocations (NCAs) to provinces, the grandfather principle is the only option for allocating NCAs to sectors. In the future, China’s carbon emissions pattern will be dominated by the contribution from electricity and heat production sectors. This carbon emission pattern can be further divided into three categories: Pattern M, where the manufacturing and construction sectors significantly contribute to total emissions; Pattern R, where the residential buildings and commercial and public services sectors have a significant contribution to total emissions; and Pattern T, where the contribution of the transport sector to total emissions is substantial. Second, emission patterns affect the allocation of sectoral carbon allocations at the national level (SCANs). Although the preferences vary from sector to sector, they are consistent between the national and provincial levels. Third, compared with sectoral preferences, provincial preferences are more complex. Sixteen provinces, including Hebei, Shanxi and Inner Mongolia, prefer Pattern T. There are nine provinces, for example, Guangdong, Shandong and Jiangsu, whose preferred pattern is M; and five provinces, represented by Beijing, Shanghai and Tianjin, have a preference for Pattern R. Last, but not least, to achieve China’s peak commitment, different provinces face alternative peak pressures. It is worth mentioning that, in patterns R and T, provinces with a high proportion of manufacturing and construction sector emissions, such as Guangdong, Shandong, Jiangsu and Zhejiang, may have to increase the share of carbon emissions from the transport sector or from residential buildings and commercial and public services sectors to postpone their peak year.

Suggested Citation

  • Qianting Zhu & Wenwu Tang, 2017. "Regional-Level Carbon Allocation in China Based on Sectoral Emission Patterns under the Peak Commitment," Sustainability, MDPI, vol. 9(4), pages 1-18, April.
  • Handle: RePEc:gam:jsusta:v:9:y:2017:i:4:p:552-:d:94959
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    References listed on IDEAS

    as
    1. Lozano, S. & Villa, G. & Brännlund, R., 2009. "Centralised reallocation of emission permits using DEA," European Journal of Operational Research, Elsevier, vol. 193(3), pages 752-760, March.
    2. Sonja Klinsky & Hadi Dowlatabadi, 2009. "Conceptualizations of justice in climate policy," Climate Policy, Taylor & Francis Journals, vol. 9(1), pages 88-108, January.
    3. Stern,Nicholas, 2007. "The Economics of Climate Change," Cambridge Books, Cambridge University Press, number 9780521700801, January.
    4. Lasse Ringius & Asbjørn Torvanger & Arild Underdal, 2002. "Burden Sharing and Fairness Principles in International Climate Policy," International Environmental Agreements: Politics, Law and Economics, Springer, vol. 2(1), pages 1-22, March.
    5. Michel Elzen & Marcel Berk & Paul Lucas & Patrick Criqui & Alban Kitous, 2006. "Multi-Stage: A Rule-Based Evolution of Future Commitments under the Climate Change Convention," International Environmental Agreements: Politics, Law and Economics, Springer, vol. 6(1), pages 1-28, March.
    6. Stephen Johnson, 1967. "Hierarchical clustering schemes," Psychometrika, Springer;The Psychometric Society, vol. 32(3), pages 241-254, September.
    7. 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.
    8. Benestad, Olav, 1994. "Energy needs and CO2 emissions Constructing a formula for just distributions," Energy Policy, Elsevier, vol. 22(9), pages 725-734, September.
    9. Cong, Rong-Gang & Wei, Yi-Ming, 2010. "Potential impact of (CET) carbon emissions trading on China’s power sector: A perspective from different allowance allocation options," Energy, Elsevier, vol. 35(9), pages 3921-3931.
    10. den Elzen, Michel & Höhne, Niklas & Moltmann, Sara, 2008. "The Triptych approach revisited: A staged sectoral approach for climate mitigation," Energy Policy, Elsevier, vol. 36(3), pages 1107-1124, March.
    11. 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.
    12. Qianting Zhu & Keran Duan & Jing Wu & Zheng Wang, 2016. "Agent-Based Modeling of Global Carbon Trading and Its Policy Implications for China in the Post-Kyoto Era," Emerging Markets Finance and Trade, Taylor & Francis Journals, vol. 52(6), pages 1348-1360, June.
    13. Park, Ji-Won & Kim, Chae Un & Isard, Walter, 2012. "Permit allocation in emissions trading using the Boltzmann distribution," Physica A: Statistical Mechanics and its Applications, Elsevier, vol. 391(20), pages 4883-4890.
    14. VAN STEENBERGHE, Vincent, 2004. "Core-stable and equitable allocations of greenhouse gas emission permits," LIDAM Discussion Papers CORE 2004075, Université catholique de Louvain, Center for Operations Research and Econometrics (CORE).
    15. Bohringer, Christoph & Lange, Andreas, 2005. "On the design of optimal grandfathering schemes for emission allowances," European Economic Review, Elsevier, vol. 49(8), pages 2041-2055, November.
    16. Yi, Wen-Jing & Zou, Le-Le & Guo, Jie & Wang, Kai & Wei, Yi-Ming, 2011. "How can China reach its CO2 intensity reduction targets by 2020? A regional allocation based on equity and development," Energy Policy, Elsevier, vol. 39(5), pages 2407-2415, May.
    17. Adam Rose & Brandt Stevens & Jae Edmonds & Marshall Wise, 1998. "International Equity and Differentiation in Global Warming Policy," Environmental & Resource Economics, Springer;European Association of Environmental and Resource Economists, vol. 12(1), pages 25-51, July.
    18. Wei, Yi-Ming & Wang, Lu & Liao, Hua & Wang, Ke & Murty, Tad & Yan, Jinyue, 2014. "Responsibility accounting in carbon allocation: A global perspective," Applied Energy, Elsevier, vol. 130(C), pages 122-133.
    19. Ji-Won Park & Chae Un Kim & Walter Isard, 2011. "Permit Allocation in Emissions Trading using the Boltzmann Distribution," Papers 1108.2305, arXiv.org, revised Mar 2012.
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