双碳背景下典型汽车制造企业减碳表现评价研究
Research on the Evaluation of Carbon Reduction Performance of Typical Automobile Manufacturing Enterprises under the Background of Carbon Peaking and Carbon Neutrality
王宏1
作者信息
- 1. 上汽通用汽车有限公司 上海 201206
- 折叠
摘要
汽车行业作为碳排放的重要来源,影响着中国"双碳"目标能否顺利实现.基于数据可获取性和准确性,研究选取了 2022 年中国乘用车销量排名前列的汽车集团(以A～F表示),聚焦企业低碳规划、产品脱碳行动、碳减排效益及碳排放数据披露等维度,综合评价其低碳化转型表现,以期为汽车制造行业低碳化发展路径研究及减污降碳政策的制定提供参考借鉴.研究得出:1.企业低碳规划方面,F和E企业得分最高;2.产品脱碳行动方面,F企业得分最高为 18 分;3.碳减排效益方面,C企业表现尤为亮眼,F企业碳排放增量位居第一;4.碳排放数据披露方面,C、D和F企业表现较好.建议:1.汽车制造商加大汽车生产制造低零碳化转型力度;2.汽车制造商应制定具体的低碳规划;3.汽车制造商应加强其碳排放数据披露.
Abstract
As an important source of carbon emissions,the automotive industry affects whether China's"dual carbon"goal can be successfully achieved.Based on the availability and accuracy of data,this study selects the top automotive groups in China's passenger car sales in 2022(represented by A～F)to comprehensively evaluate their low-carbon transformation performance by focusing on the dimensions of corporate low-carbon planning,product decarbonization actions,carbon emission reduction benefits and carbon emission data disclosure,in order to provide reference for the research on the low-carbon development path of the automobile manufacturing industry and the formulation of pollution reduction and carbon reduction policies.The results show that:1.In terms of corporate low-carbon planning,F and E enterprises score the highest;2.In terms of product decarbonization actions,Company F scored the highest score of 18 points;3.In terms of carbon emission reduction benefits,Company C performed particularly well,and Company F ranked first in carbon emission increment;4.In terms of carbon emission data disclosure,companies C,D and F performed better.Suggestions:1.Automobile manufacturers should increase the transformation of low-zero carbon automobile manufacturing;2.automakers should develop specific low-carbon plans;3.Automakers should strengthen their carbon emissions data disclosure.
关键词
碳排放/低碳化/评价/碳中和Key words
Carbon Emissions/Decarbonization/Evaluation/Carbon Neutrality引用本文复制引用
出版年
2024
NETL
NSTL
万方数据