气候变化研究进展 ›› 2023, Vol. 19 ›› Issue (3): 347-356.doi: 10.12006/j.issn.1673-1719.2022.183

• 温室气体排放 • 上一篇    下一篇

我国交通运输行业及不同运输方式的碳排放水平和强度分析

田佩宁1,2(), 毛保华1,2(), 童瑞咏1,2, 张皓翔3, 周琪1,2   

  1. 1 北京交通大学中国综合交通研究中心,北京 100044
    2 北京交通大学综合交通运输大数据应用技术交通运输行业重点实验室,北京 100044
    3 北京城建设计发展集团股份有限公司,北京 100037
  • 收稿日期:2022-08-01 修回日期:2022-10-22 出版日期:2023-05-30 发布日期:2023-02-13
  • 通讯作者: 毛保华,男,教授,bhmao@bjtu.edu.cn
  • 作者简介:田佩宁,女,博士研究生,20120900@bjtu.edu.cn
  • 基金资助:
    国家自然科学基金资助项目(71971021);基本科研业务费科研学术活动资助项目(2019JBM334)

Analysis of carbon emission level and intensity of China’s transportation industry and different transportation modes

TIAN Pei-Ning1,2(), MAO Bao-Hua1,2(), TONG Rui-Yong1,2, ZHANG Hao-Xiang3, ZHOU Qi1,2   

  1. 1 Intergrated Transport Research Center of China, Beijing Jiaotong University, Beijing 100044, China
    2 Key Laboratory of Transport Industry of Big Data Application Technologics for Comprehensive Transport, Beijing 100044, China
    3 Beijing Urban Construction Design and Development Group Co., Ltd., Beijing 100037, China
  • Received:2022-08-01 Revised:2022-10-22 Online:2023-05-30 Published:2023-02-13

摘要:

针对中国交通运输行业碳排放量核算边界、范围、方法不清的问题,采用自上而下和自下而上相结合的方法,通过运输方式分解,建立统计口径清晰、可与国际对标的交通碳排放测算模型,测算2019年中国交通运输业和各运输方式的CO2排放量,分析中国交通运输业的碳排放结构和不同运输方式的碳排放强度,为中国交通运输业制定碳减排路径提供理论基础。结果表明,2019年中国交通运输业的CO2排放量为12.74亿t,仅次于美国(17.88亿t),占全国CO2排放总量的比重为12.42%,占世界交通运输CO2排放总量的比重为14.82%。中国交通碳排放结构较分散,作为碳排放主体的道路运输排放占比(79.15%)低于德国、法国等欧洲国家(85.19%~96.69%),而航空、水路、轨道交通的碳排放占比则高出许多,分别为9.13%、7.06%、4.39%。碳排放强度由大到小排序为航空、公路、铁路、水运。

关键词: 碳中和, 交通运输业, 碳排放测算, 碳排放结构, 碳排放强度, 自上而下, 自下而上

Abstract:

To address the problem of unclear boundary, scope and method of carbon emission accounting in China’s transport sector, a combination of top-down and bottom-up approaches was used, through the decomposition of transport modes, to establish a transportation carbon emission measurement model with clear statistical caliber and comparable with international. The CO2 emissions of China’s transport sector and transport modes in 2019 were measured, and the carbon emission structure and intensity of different modes of transport were analyzed, so as to provide a theoretical basis for the development of carbon emission reduction paths in China’s transport sector. The results show that CO2 emissions from China’s transport sector in 2019 is 1274 million t, second only to the United States (1788 million t), accounting for 12.42% of the country’s total CO2 emissions and 14.82% of the world’s total transport CO2 emissions. The structure of China’s transport carbon emissions is more fragmented, with the share of road transport emissions (79.15%), which is the mainstay of carbon emissions, being lower than that of European countries such as Germany and France and so on (85.19%-96.69%). While the shares of carbon emissions from aviation, waterways and rail transport are higher, at 9.13%, 7.06% and 4.39% respectively. The carbon emission intensity of each mode of transport ranks from the largest to the smallest: aviation, highway, railway and waterway, with the unit conversion turnover carbon emission factors being 899.48, 102.81, 11.33 and 8.65 g/(t∙km) respectively. The Chinese government should guide the transfer of passenger transport from aviation to railway, and insist on promoting the policy of “highway to railway” and “highway to waterway” for freight transport. The unit conversion turnover carbon emission factor does not accurately reflect the carbon intensity of passenger/cargo transport. There is a discrepancy between its value and the actual unit passenger/cargo turnover carbon emission factor value. Taking highways as an example, the value of the unit converted turnover carbon emission factor deviates from the value of the unit cargo turnover carbon emission factor (97.60 g/(t∙km)) and the unit passenger turnover carbon emission factor (45.36 g/(person∙km)) by 5.34% and 126.67% respectively.

Key words: Carbon neutrality, Transportation industry, Carbon emission measurement, Carbon emission structure, Carbon emission intensity, Top-down approach, Bottom-up approach

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