Ziyuan Kexue (Jun 2023)
Carbon quota allocation for club members from the perspective of difference analysis
Abstract
[Objective] To improve the carbon quota allocation method based on historical carbon emissions and advance the development of the carbon trading market in China, a two-level and double quota distribution system for carbon quota allocation was developed. [Methods] This study used Markov chain to divide 32 industrial sectors into three clubs (high, medium, and low-carbon clubs). It used carbon emissions and carbon intensity as indicators for primary and secondary allocation, respectively. The Dagum Gini decomposition method was used to measure the carbon emission differences of the clubs or sectors and determine the correction coefficients of the level of difference and the base-period of allocation. [Results] (1) The high, medium, and low-carbon clubs consisted of 6, 6, and 12 members respectively and their differentiation are remarkable. The high-carbon club included coal mining and washing, chemical raw material and manufacturing, non-metallic minerals manufacturing, ferrous metal smelting and rolling processing, non-ferrous metal smelting and rolling processing, and electricity and heat producing and supplying industries. The medium-carbon club included ferrous metal mining and dressing, non-ferrous metal mining and dressing, non-metal mining and dressing, agricultural and subsidiary foodstuff processing, paper making and paper product, and petroleum refining, coking, and nuclear fuel processing industries. (2) 2018 was the inflection point of differentiation, and using 2018 to 2020 as the base-period was more equitable. (3) Within the base-period, the change of carbon emission intensity varied greatly between clubs or sectors, and implementing secondary allocation first for the punished clubs, the punished high-carbon industries, and the rewarded medium-carbon industries helped to establish a clear reward and punishment system. (4) The ranges of primary allocation correction for the clubs and the high and medium-carbon industries were reasonable, which were from -0.36% to 2.41%, -4.41% to 9.60%, and -8.14% to 2.78%, respectively. (5) Compared to the one-level and one-time allocation system, this proposed system was better in stimulating industries to lower carbon emission intensity, and the carbon quota had been adjusted between -8.14% and 9.60% from the original system. [Conclusion] It is scientific and sound to use Markov chain to establish a two-level allocation system and use the Gini coefficient to determine the base-period and coefficients of the level of difference. The initial quota of the industries under this system not only can fully reflect the carbon emission level of each industry in the base-period, but also can reflect the magnitude of change of carbon emission intensity of the industries. Taking the trend of change of carbon emission differences as the theoretical basis for the selection of the base-period can provide a practical guidance for carbon quota allocation.
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