Abstract
The initial allocation of carbon emission quotas should be of primary concern when establishing China’s unified carbon emission trading market. Essentially, the issue of national carbon quota allocation is an allocation among China’s provinces. The novel bi-level allocation scheme that is based on weighted voting model is put forward, which divides allocation process into two levels, given that there are great regional differences in China. At the first level, k-means clustering is employed to cluster 29 provinces into four categories that are based on emission abatement responsibility, potential, capacity, pressure, and motivation. Subsequently, the national carbon quotas are allocated to the four classes. At the second level, carbon quotas of a class are allocated to each region in this class. The weighted voting models are constructed for the two levels, where each region selects their preferable scheme from three fundamental allocation schemes that are based on their voting rights. The comprehensive index method quantifies each region’s voting rights, which utilizes the information entropy method at the first level and the analytic hierarchy process (AHP) at the second level. The carbon trading market is simulated and welfare effects obtained from carbon trading market under different allocation schemes are measured to verify the rationality of the proposed model. The results indicate: (1) the emission abatement burdens are borne by all provinces in China, but the burden shares are different, which are related to their respective carbon emission characteristics. (2) The differences in carbon intensity among regions in 2030 have narrowed on the basis of the results of 2005, which means that the proposed scheme can balance corresponding differences. (3) When compared with three fundamental allocation schemes, the bi-level allocation scheme can obtain the most welfare effects, while the differences in the welfare effect among regions under this scheme are the smallest, which indicates that the proposed model is feasible for policy-maker.
Highlights
Global surface temperatures and sea levels are expected to increase by 4.8 ◦ C and 0.82 m by 2100, respectively, due to greenhouse effect [1]
The weighted voting models are constructed for the two levels, where each region selects their preferable scheme from three fundamental allocation schemes that are based on their voting rights
It is reasonable to explore their difference in carbon emission characteristics to allocate the emission quotas
Summary
Global surface temperatures and sea levels are expected to increase by 4.8 ◦ C and 0.82 m by 2100, respectively, due to greenhouse effect [1]. CO2 is one of the main greenhouse gases, and its excessive emissions have attracted massive attention with the rapid development of the world economy. China is faced with great pressure in reducing emission and addressing global warming, as the largest energy consumer and CO2 emitter in the world [2]. A series of emission mitigation targets have been put forward. At the Copenhagen conference, China’s government promised that. CO2 emissions per unit GDP, namely, carbon intensity, are reduced by 40–45% by 2020 based on the. 2005 level, which was listed in the 12th Five-Year Plan [3].
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