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美国道路运输部门能源相关碳排放的驱动因素:分解分析。

Driving Factors behind Energy-Related Carbon Emissions in the U.S. Road Transport Sector: A Decomposition Analysis.

机构信息

Shenzhen Institute of Advanced Technology, Chinese Academy of Sciences, Shenzhen 518055, China.

School of Design and the Built Environment, Curtin University, Perth 6102, Australia.

出版信息

Int J Environ Res Public Health. 2022 Feb 17;19(4):2321. doi: 10.3390/ijerph19042321.

DOI:10.3390/ijerph19042321
PMID:35206507
原文链接:https://pmc.ncbi.nlm.nih.gov/articles/PMC8871990/
Abstract

The U.S. is the second largest contributor to carbon emissions in the world, with its road transport sector being one of the most significant emission sources. However, few studies have been conducted on factors influencing the emissions changes for the U.S. from the perspective of passenger and freight transport. This study aimed to evaluate the carbon emissions from the U.S. road passenger and freight transport sectors, using a Logarithmic Mean Divisia Index approach. Emissions from 2008 to 2017 in the U.S. road transport sector were analysed and key findings include: (1) energy intensity and passenger transport intensity are critical for reducing emissions from road passenger transport, and transport structure change is causing a shift in emissions between different passenger transport modes; and (2) the most effective strategies to reduce carbon emissions in the road freight transport sector are to improve energy intensity and reduce freight transport intensity. Several policy recommendations regarding reducing energy and transport intensity are proposed. The results and policy recommendations are expected to provide useful references for policy makers to form carbon emissions reduction strategies for the road transport sector.

摘要

美国是世界上第二大碳排放国,其道路运输部门是最大的排放源之一。然而,从客运和货运的角度来看,关于影响美国排放变化的因素的研究甚少。本研究旨在使用对数平均迪氏指数法评估美国道路客运和货运部门的碳排放。分析了 2008 年至 2017 年美国道路运输部门的排放情况,主要结果包括:(1)能源强度和客运强度对于减少道路客运的排放至关重要,运输结构的变化导致不同客运方式之间的排放转移;(2)提高能源强度和降低货运强度是减少道路货运碳排放的最有效策略。提出了几项关于降低能源和运输强度的政策建议。预计结果和政策建议将为决策者制定道路运输部门的碳排放减排策略提供有益参考。

https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cc5/8871990/112717444c7b/ijerph-19-02321-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cc5/8871990/5d21f6872520/ijerph-19-02321-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cc5/8871990/b8c8f293847f/ijerph-19-02321-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cc5/8871990/f51015672365/ijerph-19-02321-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cc5/8871990/4d33cf5d9b26/ijerph-19-02321-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cc5/8871990/37d129004d1d/ijerph-19-02321-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cc5/8871990/5e9681916c2a/ijerph-19-02321-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cc5/8871990/59e41fbb4eef/ijerph-19-02321-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cc5/8871990/112717444c7b/ijerph-19-02321-g008.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cc5/8871990/5d21f6872520/ijerph-19-02321-g001.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cc5/8871990/b8c8f293847f/ijerph-19-02321-g002.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cc5/8871990/f51015672365/ijerph-19-02321-g003.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cc5/8871990/4d33cf5d9b26/ijerph-19-02321-g004.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cc5/8871990/37d129004d1d/ijerph-19-02321-g005.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cc5/8871990/5e9681916c2a/ijerph-19-02321-g006.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cc5/8871990/59e41fbb4eef/ijerph-19-02321-g007.jpg
https://cdn.ncbi.nlm.nih.gov/pmc/blobs/5cc5/8871990/112717444c7b/ijerph-19-02321-g008.jpg

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Statistics Notes: Percentage differences, symmetry, and natural logarithms.
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BMJ. 2017 Aug 16;358:j3683. doi: 10.1136/bmj.j3683.