捐赠
碳纤维
中国
环境经济学
温室气体
城市绿地
业务
自然资源经济学
空格(标点符号)
环境工程
环境科学
经济
地理
政治学
计算机科学
生态学
考古
算法
复合数
法学
生物
操作系统
作者
Wanying Li,Fugui Dong,Zhengsen Ji
标识
DOI:10.1016/j.jclepro.2023.139372
摘要
Increasing carbon emissions efficiency (CEE) is essential for Chinese cities to achieve their dual carbon goals. For cities with higher CEE, it is crucial to comprehensively evaluate their carbon emissions reduction potential (CERP) and develop targeted carbon reduction paths. This study first determined the input, expected output, and non-expected output indicators and used the super-efficiency Slack Based Measure model to calculate the CEE of 336 cities. Secondly, we evaluated the urban development level, structural optimization space, and natural resource endowment using the BWM-CRITIC-TOPSIS method and combined them with CEE to evaluate the CERP. Finally, we used K-means clustering to group cities according to the carbon emissions level and CERP and proposed targeted emission reduction recommendations. The results showed that cities in the northern part of China had lower CEE, while the coastal areas had higher CEE. In the primary indicators of CERP, structural optimization space was the most important, followed by efficiency improvement space. The eastern region has a greater potential for carbon reduction, with an average score of 63.71 points (out of 100 evaluation points) for the 336 cities. The cities could be classified into nine types, with the ninth category being the key focus cities for achieving the 2030 carbon peak goal with high carbon emissions and CERP.
科研通智能强力驱动
Strongly Powered by AbleSci AI