交通运输碳减排策略的弹性和效率

Madiha Bencekri, Donggyun Ku, Doyun Lee, Yee Van Fan, Jiří Jaromír Klemeš, Petar Sabev Varbanov, Seungjae Lee
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引用次数: 0

摘要

摘要交通运输是碳排放的重要来源,因此需要制定有效的减排政策。本研究解决了在评估运输碳政策有效性方面的知识差距,并提供了缺乏整体比较概述的问题。该研究使用了一个由混合效应元回归和碳弹性组成的模型来调查政策,如共享单车、交通枢纽、低排放区、拥堵收费、电动汽车和氢燃料汽车。该模型包括7个控制变量:年份、GDP、实施成本、地理规模、环境效益、能源消耗和碳排放的运输份额。交通枢纽和电动汽车是最有效的政策,其碳弹性分别为3.73和3.72,效应量分别为127.47和86.73,置信区间分别为[65.55,107.93]和[106.17,148.78]。其次是低排放区,碳弹性为16.3,证明了其成本效益,效应大小为10.16,置信区间为[−2.48,22.80]。尽管拥堵收费的效应值最高,为873.39,但其置信区间[- 354.01,2100.80]很宽,表明该效应具有不确定性。共享单车和氢燃料汽车排名最低,这表明需要更深入的基于生命周期的分析。尽管该模型显示出较高的准确性,但研究结果的解释应考虑到固有的数据局限性。本研究得到首尔大学基础研究与跨学科研发基金(2023)对Seungjae Lee的支持。这项工作得到了韩国教育部和韩国国家研究基金会(NRF-2019K1A4A7A03112460)对Madiha benekri的支持。本文的共同作者感谢SPIL的支持,项目编号为cz .02.1.01/0.0/0.0/15_003/0000456,由捷克共和国业务计划研究与发展,教育,优先事项1:加强高质量研究的能力”,并对已故的Jiří Jaromír klemesi教授表示感谢。他的贡献和坚定的支持对我们合作的成功是无价的。本研究由韩国国家研究基金会[NRF-2019K1A4A7A03112460]资助。madiha benekri,交通工程与智慧城市系博士候选人。摩洛哥卡萨布兰卡地区市政府前公职人员。Donggyun KuDonggyun Ku是韩国首尔大学交通工程系的一名博士。剑桥大学的前研究员。现任韩国京畿道研究所研究员。Doyun Lee,韩国首尔国立大学环境科学研究生院的硕士生。Yee Van Fan是捷克布尔诺理工大学设计与工艺工程系的博士。现任捷克布尔诺理工大学机械工程学院NETME中心可持续过程集成实验室研究员。Jiří Jaromír KlemešJiří Jaromír klemesi教授,VUT BRNO可持续过程集成实验室(SPIL)负责人;博士,博士,马里博尔大学,布加勒斯特POLITEHNICA,哈尔科夫国立技术大学,在捷克共和国。Petar Sabev Varbanov,博士,捷克布尔诺理工大学高级研究员。Seungjae Lee是首尔大学的一名教授。在过去的二十年里,他一直在首尔大学从事交通规划领域的教学、研究和咨询工作。他发表了100多篇研究论文。他曾担任International Journal of Transportation的主编,Journal of Advanced Transportation (scie索引期刊,John Wiley)的编辑,Transportmetrica Journal (ssci索引期刊,Taylor & Francis)的副主编等。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
The elasticity and efficiency of carbon reduction strategies in transportation
ABSTRACTTransportation significantly contributes to carbon emissions, prompting the need for effective mitigation policies. This study addresses the knowledge gaps in assessing the effectiveness of transport carbon policies and offers the lack of a holistic comparative overview. The study used a model composed of a mixed-effects meta-regression and carbon elasticity to investigate policies, like shared bikes, mobility hubs, low emission zones, congestion pricing, electric vehicles, and hydrogen vehicles. This model included seven control variables: year, GDP, implementation costs, geographic scale, environmental benefits, and transport share of energy consumption and carbon emissions. Mobility hubs and electric vehicles ranked are top effective policies with carbon elasticities of 3.73 and 3.72, effect sizes of 127.47 and 86.73, and confidence intervals of [65.55, 107.93] and [106.17, 148.78], respectively. Followed by the low emission zone of 16.3 carbon elasticity, proving its cost-effectiveness, effect size of 10.16, and a confidence interval of [−2.48, 22.80]. Congestion pricing, despite having the highest effect size of 873.39, its confidence interval [−354.01, 2100.80] is wide, indicating the uncertainty of this effect. Shared bikes and hydrogen vehicles ranked lowest, suggesting a need for deeper life cycle-based analysis. Although this model displayed high accuracy, the findings’ interpretation should consider the inherent data limitations.KEYWORDS: Carbon elasticitycarbon policymeta-analysispolicy efficiencytransport policy AcknowledgementsThis work was supported by the Basic Study and Interdisciplinary R&D Foundation Fund of the University of Seoul (2023) for Seungjae Lee. And, This work was supported by the Ministry of Education of the Republic of Korea and the National Research Foundation of Korea (NRF-2019K1A4A7A03112460) for Madiha Bencekri. The co-authors would like to acknowledge the support from SPIL, funded as project No.CZ.02.1.01/0.0/0.0/15_003/0000456, by Czech Republic Operational Programme Research and Development, Education, Priority 1: Strengthening capacity for quality research” and to express our gratitude to the late Prof Jiří Jaromír Klemeš. His contributions and unwavering support were invaluable to the success of our collaborationDisclosure statementNo potential conflict of interest was reported by the authors.Additional informationFundingThe work was supported by the National Research Foundation of Korea [NRF-2019K1A4A7A03112460].Notes on contributorsMadiha BencekriMadiha Bencekri, a Ph.D. candidate in the Department of Transportation Engineering and Smart Cities. Ex-public officer at the regional metropolitan government of Casablanca, Morocco.Donggyun KuDonggyun Ku is a doctor from the Department of Transportation Engineering at the University of Seoul in Korea. Ex-researcher at the University of Cambridge. Current researcher at the Gyeonggi Research Institute, Korea.Doyun LeeDoyun Lee, a master student in the Graduate School of Environmental Sciences at Seoul National University in Korea.Yee Van FanYee Van Fan is a doctor from the Department of Design and Process Engineering at the Brno University of Technology, in the Czech Republic. Current researcher at the Sustainable Process Integration Laboratory at the NETME center, faculty of mechanical engineering, Brno University of Technology, in the Czech Republic.Jiří Jaromír KlemešJiří Jaromír Klemeš is a Professor, Head of the Sustainable Process Integration Laboratory (SPIL), VUT BRNO; DS, Dr h c UTM, Univ of Maribor, POLITEHNICA Bucharest, National Tech Uni Kharkov, in the Czech Republic.Petar Sabev VarbanovPetar Sabev Varbanov is a doctor, Habil/PhD, senior researcher at Brno University of Technology, in the Czech Republic.Seungjae LeeSeungjae Lee is a professor at the University of Seoul. He has been involved in teaching, research, and consulting in the area of transportation planning for the past two decades at the University of Seoul. He has published more than 100 research papers. He has served International Journal of Transportation as an Editor-in-Chief, the Journal of Advanced Transportation (SCIE-indexed Journal, John Wiley) as an Editor and Transportmetrica Journal (SSCI-indexed journal, Taylor & Francis) as an Associate Editor, among others.
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