Li Wei, Ma Hongqing, Lu Can
School of Economics and Management, North China Electric Power University, No.619 Yonghua Street, Baoding, 071003, Hebei, China.
Energy and Economic Development & Philosophy and Social Science Research Base of Hebei Province, North China Electric Power University), No.689 Hua Dian Road, Baoding, 071003, Hebei, China.
Environ Sci Pollut Res Int. 2023 Jan;30(3):7956-7972. doi: 10.1007/s11356-022-22641-5. Epub 2022 Sep 1.
China needs to achieve its carbon peaking target with minimal economic costs. This paper proposes a framework for achieving the carbon peaking target that emphasizes economic effects. Based on the prediction, the parametric directional distance function (DDF) is adopted to calculate the total factor carbon emission efficiency and marginal carbon abatement cost in each region of China before 2030, and the allocation scheme of the abatement tasks necessary for carbon peaking is optimized from the perspective of least cost. The empirical results show the following: (1) The predicted rapid growth of China's economy from 2020 to 2030 will lead to a rapid increase in marginal abatement costs, with the average marginal carbon abatement cost increasing from 8,833 yuan/ton to 15,077 yuan/ton. The cost of carbon emission reduction in the future is very expensive. (2) The measured marginal abatement costs in China are positively correlated with carbon emission efficiency. In order to ensure economic development, developed regions should try to maintain the development trend, while the central and western regions take on more emission reduction tasks. (3) The emission efficiency is improved by optimizing the allocation scheme of the abatement tasks required to reach the peak, and the scientific and orderly path to reach the peak of each province and the corresponding lowest economic cost are obtained. This paper are of great theoretical and practical significance for the initial quota allocation in carbon trading market and ensuring the achievement of carbon peaking target under economic effect.
中国需要以最小的经济成本实现碳达峰目标。本文提出了一个强调经济效应的实现碳达峰目标的框架。基于预测，采用参数化方向距离函数（DDF）来计算2030年前中国各地区的全要素碳排放效率和边际碳减排成本，并从成本最小化的角度优化碳达峰所需减排任务的分配方案。实证结果表明：（1）预测显示2020年至2030年中国经济的快速增长将导致边际减排成本迅速上升，平均边际碳减排成本从8833元/吨增加到15077元/吨。未来碳排放减少的成本非常高昂。（2）中国测算的边际减排成本与碳排放效率呈正相关。为了确保经济发展，发达地区应尽量保持发展态势，而中西部地区承担更多的减排任务。（3）通过优化达峰所需减排任务的分配方案提高了排放效率，得出了各省达峰的科学有序路径及相应的最低经济成本。本文对于碳交易市场初始配额分配以及确保在经济效应下实现碳达峰目标具有重要的理论和现实意义。
