Martin Marietta Corporation

Abstract

The allocation of carbon emission quotas is crucial to the establishment of carbon emission trading scheme (ETS) in response to China's 2030 emission reduction target. Thus, based on equality and efficiency principles, we apply a methodology combining DEA models with entropy method to analyze China's carbon quota allocation from both provincial and regional perspectives. We integrate three indicators (total population, accumulated historical carbon emissions and emission efficiency) to construct a comprehensive indicator and use the integrated weighting approach to simulate the allocation of carbon emission quotas among China's 30 provinces. Different from previous studies, we use the non-radial directional distance function based on Kuosmanen technology to calculate emission efficiency. Also, we introduce an environmental Gini coefficient to evaluate the equality level of allocation results. Our main findings are as follows: (1) In 2030, provinces with large shares of carbon emission quotas are mainly located in China's southern region (e.g. Guangdong), while most northern provinces have small shares of carbon emission quotas (e.g. Xinjiang and Inner Mongolia). (2) Due to low emission efficiency, the emission quota shares of Hebei, Xinjiang, Shandong and Inner Mongolia decrease significantly during 2015–2030, indicating that these provinces will face greater pressure to reduce carbon emissions in the future. (3) The environmental Gini coefficient is 0.3177, which proves the equality of allocation results. (4) From the regional perspective, due to the low emission efficiency and large historical emissions, the carbon quota shares of the Middle Yellow River and Northern coastal regions decrease significantly during 2015–2030. This indicates that the two regions will need to purchase emission quotas from other regions in the future. Based on the results above, provinces and regions which undertake large emission reduction obligations need to further improve emission efficiency such that the 2030 emission reduction target can be realized.