Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China; School of Public Policy and Management, University of Chinese Academy of Sciences, Beijing 100049, China.
Institutes of Science and Development, Chinese Academy of Sciences, Beijing 100190, China.
Sci Total Environ. 2022 Sep 1;837:155798. doi: 10.1016/j.scitotenv.2022.155798. Epub 2022 May 11.
To balance China's socio-economic development and emission reduction goals, a fair and effective provincial carbon emission allowance (CEA) allocation is necessary. By considering the implied emissions of inter-provincial power transfer, this study designed a dynamic multi-criteria CEA allocation model based on four criteria-egalitarianism, historical responsibility, emission reduction capability, and emission efficiency-to calculate the provincial CEA year by year before 2030. The efficiency and fairness of the CEA scheme were evaluated through the Data envelopment analysis (DEA) model, the environmental Gini coefficient, and its grouped decomposition method. The national overall CEA, the results revealed, will peak during the 15th Five-Year Plan (FYP) period. Specifically, the CEA for eastern and central China is expected to peak first during the 14th FYP period, while the northeast region's CEA remains stable and that of the western region continues to grow. Provinces with high carbon emissions, high carbon emission intensity and high per capita carbon emissions and provinces with particularly high carbon emissions will face great pressure regarding emission reduction, and their CEA peaks are expected to arrive before 2025 and 2030 respectively. The CEA of the less-developed provinces will have a surplus. In terms of time, the high-emission provinces face greater emission reduction pressure during the 15th FYP period than during the 14th FYP period. In terms of scheme evaluation, the scheme achieved a double improvement in fairness and efficiency compared with the current actual emissions of various provinces. Reducing the differences in per capita CEA between the different regions and provinces in the western and eastern regions will help improve the scheme's fairness. This study overcomes the existing researches' shortcomings on the large differences in the distribution of emission reduction pressures in key provinces and is more feasible in practice.
为了平衡中国的社会经济发展和减排目标,公平有效的省级碳排放权(CEA)分配是必要的。考虑到省际电力转移的隐含排放,本研究设计了一个基于四个标准(平等主义、历史责任、减排能力和排放效率)的动态多准则 CEA 分配模型,以在 2030 年前逐年计算省级 CEA。通过数据包络分析(DEA)模型、环境基尼系数及其分组分解方法,评估了 CEA 方案的效率和公平性。研究结果表明,全国总体 CEA 将在“十五”规划期间达到峰值。具体而言,东部和中部地区的 CEA 预计将在“十四”规划期间率先达到峰值,而东北地区的 CEA 将保持稳定,西部地区的 CEA 将继续增长。碳排放高、碳排放强度高、人均碳排放高的省份以及碳排放特别高的省份,减排压力将很大,预计其 CEA 峰值将分别在 2025 年和 2030 年之前到来。欠发达省份的 CEA 将有盈余。就时间而言,高排放省份在“十五”规划期间比“十四”规划期间面临更大的减排压力。就方案评估而言,与各省目前的实际排放量相比,该方案在公平性和效率方面都有了双重提高。减少西部地区和东部地区不同省份之间人均 CEA 的差异将有助于提高方案的公平性。本研究克服了现有研究在重点省份减排压力分配差异较大的缺点,在实践中更具可行性。