Comprehensive Evaluation of Carbon Emission Permits Allocation: Evidence From 30 Provinces in China

Hong CHEN

Abstract


The initial allocation of inter-provincial carbon allowances based on total control is a realistic way to achieve carbon emission reduction in China. In order to evaluate different distribution methods, the most important thing is to weigh the fairness and efficiency. This paper focuses on the common carbon allowance allocation methods in the centralized, and then measures from the four dimensions of cost, DEA efficiency, personal will, and fairness. Finally, TOPSIS is used to construct a comprehensive evaluation system to sort the various distribution schemes. The comprehensive evaluation results show that the comprehensive evaluation of the Nash negotiation method is the highest, and the comprehensive evaluation based on the GDP allocation method is the worst.


Keywords


Carbon emission quota allocation; Abatement cost; DEA efficiency; Individual willing; Carbon Gini coefficient; Topsis

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References


An, Q.X., We, Y, X., Yang, M., & Chen, X. H. (2017). Allocation of carbon dioxide emission permits with the minimum cost for Chinese provinces in big data environment. J. Clean. Prod, 142, 886-893.

Bian, Y. W., He, P., & Xu, H. (2013). Estimation of potential energy saving and carbon dioxide emission reduction in China based on an extended non-radial DEA approach. Energy. Policy, 63, 962-971.

Dinda, S. (2004). Environmental Kuznets Curve hypothesis: A survey. Ecological Economics,49(4),431-455

Fan, Y., Mo, J. L., & Zhu, L. (2016). China carbon market: Policy design and socio-economic impact. Science Press (in Chinese).

International Environmental Agreements-Politics Law and Economics, 17(5),709-729.

IPCC [Intergovernmental Panel on Climate Change]. (2014). Climate change 2014: mitigation of climate change, contribution of working group III to the fifth assessment report of the intergovernmental panel on climate change. Cambridge: United Kingdom and New York, NY, USA: Cambridge

Jiang, H.Q.,Shao, X.X.,Zhang, X., Bao, J. Q. (2017). A study of the allocation of carbon emission permits among the provinces of China based on fairness and efficiency. Sustainability, 9(11).

Jiang. J. J., Ye, B., Xie, D. J., & Tang, .J. (2017). Provincial-level carbon emission drivers and emission reduction strategies in China: Combining multi-layer LMDI decomposition with hierarchical clustering. J. Clean. Prod, 169, 178-190.

Lee, H. C., & Chang, C. T. (2018). Comparative analysis of MCDM methods for ranking renewable energy sources in Taiwan. Renewable and Sustainable Energy Reviews, 92, 883-896

Lewis, C. D. (1982). Industrial and business forecasting methods: A practical guide to exponential smoothing and curve fitting; Butterworth Scientific. Heinemann: London, UK

Li L.X., Li Y.N., Ye F., & Li Z. (2018). Carbon dioxide emissions quotas allocation in the Pearl River Delta region: Evidence from the maximum deviation method. J. Clean. Prod., 177,207-217

Li, T., Wang, Y., & Zhao, D., (2016). Environmental Kuznets Curve in China: new evidence from dynamic panel analysis. Energy Pol., 91(2), 138-147.

Liao, Z. L., Zhu, X. L, & Shi, J. R. (2015). Case study on initial allocation of Shanghai carbon emission trading based on Shapley value. Journal of Cleaner Production, 103, 338-344

Lin, T., & Ning, J. F. (2011). Study on allocation efficiency of carbon emission permit in EU ETS based on ZSG-DEA model. The Journal of Quantitative & Technical Economics, 3, 36-50.

Liu, H. X. , & Lin, B. Q. (2017). Cost-based modelling of optimal emission quota allocation. J. Clean. Prod., 149, 472-484.

Pan, X. Z., Teng, F., & Wang, G. H. (2014). Sharing emission space at equitable basis: Allocation scheme based on the equal cumulative emission per capital principle. Applied Energy, 113, 1810–1818

Ren, F., Gu, L. H. (2016). Study on Transition of Primary Energy Structure and Carbon Emission Reduction Targets in China Based on Markov Chain Model and GM (1, 1). Mathematical Problems in Engineering, 2016.

Schuur, EAG , McGuire, A. D., & Schadel, C. (2015). Climate change and the permafrost carbon feedback. Nature, 520, 171-179.

Shan, Y. L., Guan, D. B., & Zheng, H. R. (2018). Data descriptor: China CO2 emission accounts 1997–2015. Science Data, 5.

The State Council. (2016). 13th five year plan for controlling greenhouse gas emissions. (Accessed 4 November 2016)

Vartiainen H. (2007). Nash implementation and the bargaining problem. Social Choice and Welfare, 29(2), 333-351.

Ye, F., Xie, X. X., Zhang, Li., & Hu, X. L. (2018). An improved grey model and scenario analysis for carbon intensity forecasting in the Pearl River delta region of China. Energies, 11(1), 91

Yu, S., van Ierland, E.C, Weikard, H. P., & Zhu, X. (2017). Nash bargaining solutions for international climate agreements under different sets of bargaining weights. International Environmental Agreements-Politics, 17(5), 709-929.

Zhang, J., Wu, G. Y., Zhang, J. P. (2004). China’s inter-provincial physical capital stock estimate: 1952-2000. Economic Research, 10, 35-44.

Zhang, X. D. (1995). The pure bargaining problem among coalitions. Asia-Pacific Journal of Operational Research, 12(1), 1-15.

Zhang, Y. J., Wang, A. D., & Da, Y. B. (2014). Regional allocation of carbon quotas in China: Evidence from the Shapley value method. Energy Policy, 74, 454–464

Zhou, P., & Wang, M. (2016). Carbon dioxide emissions allocation: A review. Ecol. Econ., 125, 47-59.

Zhou, X., Zhang, M., Zhou, M. H., & Zhou, M. (2017). A comparative study on decoupling relationship and influence factors between China’s regional economic development and industrial energy-related carbon emissions. J. Clean. Prod., 142, 783-800.




DOI: http://dx.doi.org/10.3968/11020

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