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Abstract:As the world's largest carbon emitter, China considers carbon emissions trading to be an important measure in its national strategy for energy conservation and emissions reduction. The initial allocation of China's carbon emissions rights at the provincial level is a core issue of carbon emissions trading. A scientific and reasonable distinction between the carbon emission rights of provinces is crucial for China to achieve emissions reduction targets. Based on the idea of multi-objective decision-making, this paper uses the improved Technique for Order Preference by Similarity to an Ideal Solution (TOPSIS) method to allocate China's initial carbon emission rights to the provinces and uses the Gini coefficient sub-group decomposition method to evaluate the fairness of the allocation results. First, the results of a theoretical distribution show that in the initial allocation of carbon emission rights, a large proportion of China's provinces have large populations and high energy use, such as Shandong Province, Jiangsu Province, Hebei Province and Henan Province; the provinces with a small proportion of the initial allocation of carbon emissions consist of two municipalities, Beijing and Shanghai, as well as Hainan Province, which is dominated by tourism. Overall, the initial allocation of carbon emission rights in the northern and eastern regions constituted the largest proportion, with the south-central region and the northwest region being the second largest and the southwest region being the smallest. Second, the difference between the theoretical allocation and the actual allocation of carbon emission rights in China was clear. The energy consumption of large provinces and provinces dominated by industry generally had a negative difference (the theoretical allocation of carbon emissions was less than the actual value), while Qinghai, dominated by agriculture and animal husbandry, showed a positive balance (the theoretical allocation of carbon emissions was greater than the actual value). Third, the results based on the Gini coefficient showed that the carbon emission right allocation scheme proposed by the Topsis model in this paper has good fairness. Fourth, the economic development structure, technological innovation level, carbon emissions and other indicators have certain impacts on the fairness of the initial allocation of carbon emission rights. Finally, this paper offers some suggestions on energy conservation and emissions reduction in China, taking four aspects into account: regional disparities, technological innovation, industrial structure and the initial allocation of carbon emission rights. This paper could be helpful to provide a reference for the rational allocation of China's carbon emission right.

The calculation of marginal abatement costs of CO plays a vital role in meeting China's 2020 emission reduction targets by providing reference for determining carbon tax and carbon trading pricing. However, most existing researches only used one method to discuss regional and industrial marginal abatement costs, and almost no studies predicted future marginal abatement costs from the perspective of CO emission efficiency. To make up for the gaps, this paper first estimates marginal abatement costs of CO in three major industries of 30 provinces in China from 2005 to 2015 based on three assumptions. Second, based on the principle of fairness and efficiency, China's 2020 emission reduction targets are decomposed by province. Based on the ZSG-C-DDF model, the marginal abatement costs of CO in all provinces in China in 2020 are estimated and compared with the marginal abatement costs of 2005 to 2015. The results show that (1) from 2005 to 2015, marginal abatement costs of CO in all provinces show a fluctuating upward trend; (2) compared with the marginal abatement costs of primary industry or tertiary industry, most provinces have lower marginal abatement costs for secondary industry; and (3) the average marginal abatement costs of CO for China in 2020 are 2766.882 Yuan/tonne for the 40% carbon intensity reduction target and 3334.836 Yuan/tonne for the 45% target, showing that the higher the emission reduction target, the higher the marginal abatement costs of CO. (4) Overall, the average marginal abatement costs of CO in China by 2020 are higher than those in 2005-2015. The empirical analysis in this paper can provide multiple references for environmental policy makers.