Allocation of provincial carbon emission allowances under China's 2030 carbon peak target: A dynamic multi-criteria decision analysis method | |
Cheng, Yonglong1; Gu, Baihe2![]() ![]() | |
Source Publication | SCIENCE OF THE TOTAL ENVIRONMENT
![]() |
Keyword | Carbon emission allowances (CEA) Dynamic multi-criteria decision analysis ZSG-DEA Entropy method Gini coef ficient |
Abstract | 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. |
2022 | |
Volume | 837 |
ISSN | 0048-9697 |
Subtype | Article |
DOI | 10.1016/j.scitotenv.2022.155798 |
WOS Keyword | REGIONAL ALLOCATION ; INITIAL ALLOCATION ; QUOTA ALLOCATION ; CO2 EMISSIONS ; EFFICIENCY ; PERFORMANCE ; ABATEMENT ; EQUITY ; LEVEL |
Language | 英语 |
WOS Research Area | Environmental Sciences & Ecology |
WOS Subject | Environmental Sciences |
WOS ID | WOS:000806053900011 |
Citation statistics | |
Document Type | 期刊论文 |
Identifier | http://ir.casisd.cn/handle/190111/12014 |
Collection | 可持续发展战略研究所 |
Affiliation | 1.Chinese Acad Sci, Inst Sci & Dev, Beijing 100190, Peoples R China 2.Univ Chinese Acad Sci, Sch Publ Policy & Management, Beijing 100049, Peoples R China 3.Chinese Acad Sci, Inst Sci & Dev, 15 ZhongGuanCun BeiYiTiao, Beijing 100190, Peoples R China |
Recommended Citation GB/T 7714 | Cheng, Yonglong,Gu, Baihe,Tan, Xianchun,et al. Allocation of provincial carbon emission allowances under China's 2030 carbon peak target: A dynamic multi-criteria decision analysis method[J]. SCIENCE OF THE TOTAL ENVIRONMENT,2022,837. |
APA | Cheng, Yonglong,Gu, Baihe,Tan, Xianchun,Yan, Hongshuo,&Sheng, Yuhui.(2022).Allocation of provincial carbon emission allowances under China's 2030 carbon peak target: A dynamic multi-criteria decision analysis method.SCIENCE OF THE TOTAL ENVIRONMENT,837. |
MLA | Cheng, Yonglong,et al."Allocation of provincial carbon emission allowances under China's 2030 carbon peak target: A dynamic multi-criteria decision analysis method".SCIENCE OF THE TOTAL ENVIRONMENT 837(2022). |
Files in This Item: | There are no files associated with this item. |
Items in the repository are protected by copyright, with all rights reserved, unless otherwise indicated.
Edit Comment