Madiha Bencekri, Donggyun Ku, Doyun Lee, Yee Van Fan, Jiří Jaromír Klemeš, Petar Sabev Varbanov, Seungjae Lee
{"title":"交通运输碳减排策略的弹性和效率","authors":"Madiha Bencekri, Donggyun Ku, Doyun Lee, Yee Van Fan, Jiří Jaromír Klemeš, Petar Sabev Varbanov, Seungjae Lee","doi":"10.1080/15567036.2023.2276380","DOIUrl":null,"url":null,"abstract":"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.","PeriodicalId":11580,"journal":{"name":"Energy Sources, Part A: Recovery, Utilization, and Environmental Effects","volume":"89 1","pages":"0"},"PeriodicalIF":0.0000,"publicationDate":"2023-10-02","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"The elasticity and efficiency of carbon reduction strategies in transportation\",\"authors\":\"Madiha Bencekri, Donggyun Ku, Doyun Lee, Yee Van Fan, Jiří Jaromír Klemeš, Petar Sabev Varbanov, Seungjae Lee\",\"doi\":\"10.1080/15567036.2023.2276380\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"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. 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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.