Study on the initial carbon quota allocation and spatial balance compensation strategy at the provincial level in China

With the official national unified carbon market launch on July 16, 2021, the allocation and trading of initial carbon quotas between regions will become the focus of research in the future. Based on a reasonable regional initial carbon quota allocation, introducing the concept of carbon ecological compensation and formulating differentiated emission reduction strategies according to the characteristics of different provinces can better guarantee the realization of China's carbon emission reduction goals. Based on this, this paper first analyzes the distribution effects under different distribution principles from the perspective of fairness and efficiency. Secondly, the Pareto optimal multi-objective particle swarm optimization (Pareto-MOPSO) algorithm is used to build the initial carbon quota allocation optimization configuration model to optimize the allocation results. The optimal initial carbon quota allocation scheme is determined through the comparative analysis of the allocation results. Finally, we explore the combination of carbon quota allocation and the concept of carbon ecological compensation and formulate the corresponding carbon compensation scheme. This study not only reduces the relative sense of exploitation of carbon quota allocation in different provinces but also contributes to the realization of a carbon peak in 2030 and carbon neutrality in 2060 (the 30.60 double carbon target).

Automated summary

With the official launch of China's national unified carbon market on July 16, 2021, the allocation and trading of initial carbon quotas between regions will be a key focus. This paper proposes a reasonable allocation of regional carbon quotas and introduces the concept of carbon ecological compensation, which can better guarantee the achievement of China's carbon emission reduction goals. By analyzing the distribution effects under different principles and using the Pareto optimal multi-objective particle swarm optimization (Pareto-MOPSO) algorithm, an optimized configuration model for initial carbon quota allocation is built. The study also explores the combination of carbon quota allocation and carbon ecological compensation, contributing to the realization of China's carbon peak and carbon neutrality goals.