Investigating the impact of high-altitude on vehicle carbon emissions: A comprehensive on-road driving study

This study addresses the literature gap concerning accurately identifying vehicle carbon emission characteristics in high-altitude areas. Utilizing a portable emission measurement system (PEMS) for real-world testing, the authors quantified the influence of altitude on carbon emissions from light-duty gasoline (LDGV) and diesel vehicles (LDDV). The Random Forest (RF) algorithm was employed to analyze the complex nonlinear relationships between altitude, meteorological conditions, driving patterns, and carbon dioxide (CO₂) emissions, enabling predictions across different altitudes. The results showed that CO₂ emissions progressively increase with elevation. Furthermore, as altitude increases, combustion efficiency declines, and the overall impact of driving conditions on emission rates diminishes. Altitude and meteorological factors significantly contributed to CO₂ emissions, whereas driving conditions and road grades contributed less. Compared with the COPERT model, the RF model demonstrates strong accuracy in predicting carbon emissions at different altitudes. Specifically, the CO₂ emission rate nearly triples as altitude increases from 2.0 km to 4.5 km. This research bridges a critical gap in the understanding carbon emissions from high-altitude vehicles, offering insights into policy development for emission reduction strategies in such regions. Future studies should integrate diverse testing methodologies and comprehensive surveys to validate and extend the findings.

• Record URL:
  • https://doi.org/10.1016/j.scitotenv.2024.170671
• Record URL:
  • http://www.sciencedirect.com/science/article/pii/S0048969724008106
• Availability:
  • Find a library where document is available. Order URL: http://worldcat.org/issn/00489697
• Supplemental Notes:
  • © 2024 Published by Elsevier B.V. Abstract reprinted with permission of Elsevier.
• Authors:
  • Jiang, Zhiwen
  • Wu, Lin
  • Niu, Haomiao
  • Jia, Zhenyu
  • Qi, Zhaoyu
  • Liu, Yan
  • Zhang, Qijun
  • Wang, Ting
  • Peng, Jianfei
  • Mao, Hongjun
• Publication Date: 2024-3-25

Language

• English

Media Info

• Media Type: Web
• Features: References;
• Pagination: 170671
• Serial:
  • Science of the Total Environment
  • Volume: 918
  • Issue Number: 0
  • Publisher: Elsevier
  • ISSN: 0048-9697
  • Serial URL: http://www.sciencedirect.com/science/journal/00489697

Subject/Index Terms

• TRT Terms: Altitude; Carbon dioxide; Diesel engines; Exhaust gases; Gasoline engines; Light vehicles
• Identifier Terms: Portable Emissions Measurement System
• Subject Areas: Environment; Highways; Vehicles and Equipment;

Filing Info

• Accession Number: 01914055
• Record Type: Publication
• Files: TRIS
• Created Date: Apr 8 2024 9:16AM