基于LMDI与国际类比组合法的我国交通运输行业碳排放驱动因素及减排潜力  

Driving Factors and Carbon Emission Reduction Potention of China′s Transportation Industry Based on the Combination of LMDI and International Analogies

作　　者：李艳红[1] 王安宇 杨东 LI Yan-hong;WANG An-yu;YANG Dong(China Academy of Transportation Sciences,Beijing 100029,China)

机构地区：[1]交通运输部科学研究院,北京100029

出　　处：《交通运输研究》2022年第4期36-45,共10页Transport Research

基　　金：中央级公益性科研院所基本科研业务费项目(20216105)。

摘　　要：为了给“双碳”目标下我国交通运输行业发展路径及政策制定提供学术参考,基于对数平均迪氏指数法(Logarithmic Mean Divisia Index, LMDI),选取交通运输碳排放系数、运输方式结构、客货运结构和换算周转量4个因素定量分析了2010—2020年间我国交通运输行业碳排放变化的主要机理,并结合与美国、日本、德国等已达峰国家相应驱动因素的类比分析,提出我国交通运输行业面向“双碳”目标的路径建议与实现措施。研究结果表明:交通运输碳排放系数、运输方式结构、换算周转量是驱动我国交通运输行业碳排放的关键因素,2010—2020年的贡献率均值分别为24.8%, 27.2%和42.0%,故需要从这3个因素入手,制定针对性的政策来实现交通运输行业“双碳”目标;客货运结构对我国交通运输行业“双碳”目标的影响较弱,2010—2020年的贡献率均值为6.0%,即总周转量中客运和货运占比对我国交通运输行业碳排放的影响不大,但2020年由于新冠疫情的影响,客货运结构对我国交通运输行业碳排放的贡献率升高至43.3%,需要重点关注疫情时期的这一新变化。In order to provide academic reference for the formulation of pathways and policies of China’s transportation industry with carbon peaking and carbon neutrality goals, four influencing factors such as carbon emission coefficient, transport mode structure, passenger and freight transport structure and conversion turnover were selected to decompose the carbon emission changes in China quantitatively from2010 to 2020 based on LMDI(Logarithmic Mean Divisia Index) algorithm. By comparing with the corresponding influencing factors in some developed countries such as the United States, Japan and Germany which have reached carbon peaking, some suggestions and measures for carbon peaking and carbon neutrality in China′s transportation industry were proposed. The results showed that the intensity of transport carbon emission coefficient, transport mode structure and conversion turnover were the key factors affecting carbon emissions in China′s transport industry and the average contribution rates were 24.8%, 27.2% and 42.0% individually from 2010 to 2020. So it is necessary to formulate targeted policies starting from these three factors to achieve carbon peaking in China′s transport industry. While the influence of passenger and freight transport structure on carbon peaking in China′s transportation industry was weak and the average contribution rate was only 6.0% from 2010 to 2020. However, due to COVID-19 pandemic, the contribution rate of passenger and freight transport structure on carbon peaking rose to 43.3% from 2019 to 2020, so it should be given more attention in the future while COVID-19 pandemic continues.

关 键 词：碳达峰和碳中和 交通运输碳排放 LMDI算法 国际类比法 驱动因素 减排潜力 

分 类 号：U115[交通运输工程]