Progressive optimization allocation model for carbon emission quotas: An empirical study of Jiangsu cities

Abstract

The rational allocation of carbon emission quotas is crucial for improving the orderly operation of carbon markets. As a major energy-consuming province in China, Jiangsu's cities must allocate allowable carbon emissions effectively to meet China's 2030 peaking target. This study aims to achieve an optimal allocation of carbon emission quotas by considering principles such as responsibility, efficiency, and equity. To accomplish this goal, we developed a three-stage progressive optimization allocation process. This process incorporates the entropy weight TOPSIS allocation model, zero-sum game-DEA model, and Gini coefficient. The initial allocation scheme revealed that cities in southern Jiangsu, which have higher economic development levels, also received higher carbon emission quotas, compromising efficiency and equity. In response, the second stage involves adjusting the allocation to optimize efficiency for each city, aligning the quotas more closely with historical levels. Finally, the third stage uses the Gini coefficient to further refine the allocation scheme, achieving a more balanced distribution that aligns responsibility, efficiency, and fairness. This research highlights the importance of a structured approach to carbon quota allocation, ensuring a balance that supports both environmental goals and equitable development.

Keywords

• Carbon emission quota
• Carbon allocation
• Progressive optimization
• Zero-sum game
• Data envelopment analysis