School of Statistics, Jiangxi University of Finance and Economics, No. 169, East Shuanggang Road, Changbei, Nanchang, 330013, China.
Environ Sci Pollut Res Int. 2021 Oct;28(38):52780-52797. doi: 10.1007/s11356-021-16190-6. Epub 2021 Sep 1.
Due to the lack of carbon dioxide (CO) emission data on China's logistics industry, this study uses the industry stripping method to calculate the embodied energy consumption CO emissions based on input-output tables for China's logistics industry from 1997 to 2017. And then the Log-Mean Divisia Index method is used to decompose the influencing factors of carbon emission from five aspects. The empirical study mainly focused on the application of carbon emission tools and approaches in China, and this resulted in four key findings. First, the use of transportation, warehousing, and postal industries as a proxy for the logistics is simply not in line with reality and could result in greatly underestimating the CO emissions of logistics. Second, the annual direct CO accounts for roughly 40% in the embodied CO emissions in the logistics industry. Third, construction industry makes a greater contribution to the embodied CO of the logistics industry, followed by manufacturing. Fourth, economic output, population size, industrial structure, and energy structure are factors that contributed to the increase of logistics CO emissions, while the restraining factors included energy intensity. There is immense scope for adjustment in the energy and industrial structures.
由于缺乏中国物流行业的二氧化碳（CO）排放数据，本研究使用行业剥离法，根据中国物流行业 1997 年至 2017 年的投入产出表，计算出隐含能源消费 CO 的排放量。然后使用对数平均迪氏指数法（Log-Mean Divisia Index method）从五个方面分解碳排放的影响因素。本实证研究主要集中于在中国应用碳排放工具和方法，得出了四个关键发现。首先，将运输、仓储和邮政行业作为物流的代表并不符合实际情况，可能会大大低估物流的 CO 排放量。其次，直接 CO 的排放量约占物流行业隐含 CO 排放量的 40%。第三，建筑行业对物流行业隐含 CO 的贡献最大，其次是制造业。第四，经济产出、人口规模、产业结构和能源结构是导致物流 CO 排放量增加的因素，而能源强度则是制约因素。能源和产业结构有很大的调整空间。
