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Carbon Mitigation Pathways of Urban Transportation under Cold Climatic Conditions

Climate heterogeneity has enormous impacts on CO(2) emissions of the transportation sector, especially in cold regions where the demand for in-car heating and anti-skid measures leads to high energy consumption, and the penetration rate of electric vehicles is low. It entails to propose targeted emi...

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Autores principales: Wang, Xianen, Qin, Baoyang, Wang, Hanning, Dong, Xize, Duan, Haiyan
Formato: Online Artículo Texto
Lenguaje:English
Publicado: MDPI 2022
Materias:
Acceso en línea:https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9026331/
https://www.ncbi.nlm.nih.gov/pubmed/35457437
http://dx.doi.org/10.3390/ijerph19084570
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author Wang, Xianen
Qin, Baoyang
Wang, Hanning
Dong, Xize
Duan, Haiyan
author_facet Wang, Xianen
Qin, Baoyang
Wang, Hanning
Dong, Xize
Duan, Haiyan
author_sort Wang, Xianen
collection PubMed
description Climate heterogeneity has enormous impacts on CO(2) emissions of the transportation sector, especially in cold regions where the demand for in-car heating and anti-skid measures leads to high energy consumption, and the penetration rate of electric vehicles is low. It entails to propose targeted emission reduction measures in cold regions for peaking CO(2) emissions as soon as possible. This paper constructs an integrated long-range energy alternatives planning system (LEAP) model that incorporates multi-transportation modes and multi-energy types to predict the CO(2) emission trend of the urban transportation sector in a typical cold province of China. Five scenarios are set based on distinct level emission control for simulating the future trends during 2017–2050. The results indicate that the peak value is 704.7–742.1 thousand metric tons (TMT), and the peak time is 2023–2035. Energy-saving–low-carbon scenario (ELS) is the optimal scenario with the peak value of 716.6 TMT in 2028. Energy intensity plays a dominant role in increasing CO(2) emissions of the urban transportation sector. Under ELS, CO(2) emissions can be reduced by 68.66%, 6.56% and 1.38% through decreasing energy intensity, increasing the proportion of public transportation and reducing the proportion of fossil fuels, respectively. Simultaneously, this study provides practical reference for other cold regions to formulate CO(2) reduction roadmaps.
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spelling pubmed-90263312022-04-23 Carbon Mitigation Pathways of Urban Transportation under Cold Climatic Conditions Wang, Xianen Qin, Baoyang Wang, Hanning Dong, Xize Duan, Haiyan Int J Environ Res Public Health Article Climate heterogeneity has enormous impacts on CO(2) emissions of the transportation sector, especially in cold regions where the demand for in-car heating and anti-skid measures leads to high energy consumption, and the penetration rate of electric vehicles is low. It entails to propose targeted emission reduction measures in cold regions for peaking CO(2) emissions as soon as possible. This paper constructs an integrated long-range energy alternatives planning system (LEAP) model that incorporates multi-transportation modes and multi-energy types to predict the CO(2) emission trend of the urban transportation sector in a typical cold province of China. Five scenarios are set based on distinct level emission control for simulating the future trends during 2017–2050. The results indicate that the peak value is 704.7–742.1 thousand metric tons (TMT), and the peak time is 2023–2035. Energy-saving–low-carbon scenario (ELS) is the optimal scenario with the peak value of 716.6 TMT in 2028. Energy intensity plays a dominant role in increasing CO(2) emissions of the urban transportation sector. Under ELS, CO(2) emissions can be reduced by 68.66%, 6.56% and 1.38% through decreasing energy intensity, increasing the proportion of public transportation and reducing the proportion of fossil fuels, respectively. Simultaneously, this study provides practical reference for other cold regions to formulate CO(2) reduction roadmaps. MDPI 2022-04-11 /pmc/articles/PMC9026331/ /pubmed/35457437 http://dx.doi.org/10.3390/ijerph19084570 Text en © 2022 by the authors. https://creativecommons.org/licenses/by/4.0/Licensee MDPI, Basel, Switzerland. This article is an open access article distributed under the terms and conditions of the Creative Commons Attribution (CC BY) license (https://creativecommons.org/licenses/by/4.0/).
spellingShingle Article
Wang, Xianen
Qin, Baoyang
Wang, Hanning
Dong, Xize
Duan, Haiyan
Carbon Mitigation Pathways of Urban Transportation under Cold Climatic Conditions
title Carbon Mitigation Pathways of Urban Transportation under Cold Climatic Conditions
title_full Carbon Mitigation Pathways of Urban Transportation under Cold Climatic Conditions
title_fullStr Carbon Mitigation Pathways of Urban Transportation under Cold Climatic Conditions
title_full_unstemmed Carbon Mitigation Pathways of Urban Transportation under Cold Climatic Conditions
title_short Carbon Mitigation Pathways of Urban Transportation under Cold Climatic Conditions
title_sort carbon mitigation pathways of urban transportation under cold climatic conditions
topic Article
url https://www.ncbi.nlm.nih.gov/pmc/articles/PMC9026331/
https://www.ncbi.nlm.nih.gov/pubmed/35457437
http://dx.doi.org/10.3390/ijerph19084570
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