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Author:

Wang, X. (Wang, X..) | Dai, M. (Dai, M..) | Wang, W. (Wang, W..) | Gao, Y. (Gao, Y..) | Qi, T. (Qi, T..) | Dong, X. (Dong, X..) | Ren, P. (Ren, P..) | Ding, N. (Ding, N..)

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EI Scopus SCIE

Abstract:

Commercial vehicles are important within the context of global warming, since they exhibit greenhouse gas (GHG) emissions that are disproportionate to their quantity. The aim of this study was to create a bottom-up GHG emissions assessment model which considers GHG emissions of newly produced commercial vehicles and those in current use. Through this study, the number of future commercial vehicles were predicted, thereby facilitating a simulation of future GHG emissions. Our results show that the total GHG emissions of commercial vehicles in 2019 was 580 million t CO2-eq.. Among them, the GHG emissions stemming from the production of new commercial vehicles accounted for ∼0.3% of the emissions, whereas the use stage accounted for more than 99.0%. Moreover, the future ownership of commercial vehicles depends on GDP and the demand of freight and passenger transport. The ownership of commercial vehicles was predicted about 36.61 million in 2025, 45.44 million in 2030 and 55.85 million in 2035. The carbon peak of commercial vehicles varies across different scenarios, peaking around 2031–2034, at 680–780 million t CO2-eq.. This study systematically simulated the carbon peak of commercial vehicles, contributing toward a deeper understanding of commercial vehicles within the context of GHG emissions. These results can be applied toward creating quantitatively-driven pathways for carbon peak or neutrality targets in the commercial vehicle sector. © 2023 Elsevier Ltd

Keyword:

Ownership Automotive Commercial vehicles China GHG emissions Carbon peak

Author Community:

  • [ 1 ] [Wang X.]China Auto Information Technology (Tianjin) Co., Ltd., China Automotive Technology and Research Center Co., Ltd., Tianjin, 300300, China
  • [ 2 ] [Dai M.]China Auto Information Technology (Tianjin) Co., Ltd., China Automotive Technology and Research Center Co., Ltd., Tianjin, 300300, China
  • [ 3 ] [Wang W.]China Auto Information Technology (Tianjin) Co., Ltd., China Automotive Technology and Research Center Co., Ltd., Tianjin, 300300, China
  • [ 4 ] [Gao Y.]China Auto Information Technology (Tianjin) Co., Ltd., China Automotive Technology and Research Center Co., Ltd., Tianjin, 300300, China
  • [ 5 ] [Qi T.]China Auto Information Technology (Tianjin) Co., Ltd., China Automotive Technology and Research Center Co., Ltd., Tianjin, 300300, China
  • [ 6 ] [Dong X.]China Auto Information Technology (Tianjin) Co., Ltd., China Automotive Technology and Research Center Co., Ltd., Tianjin, 300300, China
  • [ 7 ] [Ren P.]Beijing University of Technology, National Engineering Laboratory for Industrial Big-Data Application Technology, Beijing, 100124, China
  • [ 8 ] [Ding N.]State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing, 100085, China

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Source :

Journal of Environmental Management

ISSN: 0301-4797

Year: 2023

Volume: 331

8 . 7 0 0

JCR@2022

ESI Discipline: ENVIRONMENT/ECOLOGY;

ESI HC Threshold:17

Cited Count:

WoS CC Cited Count: 0

SCOPUS Cited Count: 13

ESI Highly Cited Papers on the List: 0 Unfold All

WanFang Cited Count:

Chinese Cited Count:

30 Days PV: 4

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