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城市尺度物流碳排放评价与预测对低碳发展策略的意义。

Evaluation and prediction of carbon emission from logistics at city scale for low-carbon development strategy.

机构信息

School of Business, Suzhou University of Science and Technology, Suzhou, Jiangsu Province, China.

College of Management and Economics, Tianjin University, Tianjin, China.

出版信息

PLoS One. 2024 Feb 29;19(2):e0298206. doi: 10.1371/journal.pone.0298206. eCollection 2024.

Abstract

Low-carbon is a part of China's efforts to pursue the national strategy of "carbon peaking and carbon neutrality." Meanwhile, the path of low-carbon transformation of logistics has become a topic of global concern. This study constructs a technical framework of logistics carbon emissions (LCE), which is composed of carbon emission evaluation, carbon emission prediction and low-carbon strategy. All 13 prefecture-level cities in Jiangsu, China, are the application objects in empirical research. Then, the influence analysis of the LCE efficiency based on the panel Tobit model and the evolution of LCE under different scenarios are explored. The results show that: (ⅰ) during the study period (2013-2020), the LCE in Jiangsu showed an overall upward trend, with Xuzhou, Suzhou and Nanjing being the cities with the highest carbon emissions; (ⅱ) the static efficiency of LCE in Jiangsu is at a medium level, with fluctuations in Suzhou, Changzhou, Zhenjiang, Nantong, and Suqian caused by the technical change index; (ⅲ) economic level, industrial structure, fixed asset utilization rate, and ecological environment in Jiangsu are significantly positively correlated with LCE efficiency, while education popularization and energy intensity are negative; (ⅳ) LCE in Jiangsu has been drastically reduced in the low-carbon scenario compared to the baseline scenario. On the above basis, this study proposes suggestions for the low-carbon development strategies of logistics in Jiangsu.

摘要

低碳是中国追求“碳达峰、碳中和”国家战略的一部分。同时,物流低碳转型的路径已成为全球关注的话题。本研究构建了物流碳排放(LCE)的技术框架,由碳排放评价、碳排放预测和低碳战略三部分组成。中国江苏省的 13 个地级市均为实证研究的应用对象。然后,利用面板 Tobit 模型分析了 LCE 效率的影响,并探讨了不同情景下 LCE 的演变。结果表明:(i)在研究期间(2013-2020 年),江苏的 LCE 呈总体上升趋势,徐州、苏州和南京的碳排放最高;(ii)江苏的 LCE 静态效率处于中等水平,苏州、常州、镇江、南通和宿迁的技术变化指数导致效率波动;(iii)江苏的经济水平、产业结构、固定资产利用率和生态环境与 LCE 效率显著正相关,而教育普及和能源强度则呈负相关;(iv)与基准情景相比,江苏在低碳情景下的 LCE 大幅减少。在此基础上,本研究提出了江苏省物流低碳发展策略的建议。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/0800/10903878/587dd096da6d/pone.0298206.g001.jpg

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