Toward More Sustainable Transportation: Green Vehicle Metrics for 2023 and 2024 Model Years

Osama A. Marzouk

No 9d5by_v1, OSF Preprints from Center for Open Science

Abstract: This study provides a summary about various motor vehicle models tested at the National Vehicle and Fuel Emissions Laboratory of the US Environmental Protection Agency (EPA), or tested by vehicle manufacturers with EPA’s oversight. The dataset contained 46,147 records (as of April 27, 2023) for many vehicle models, corresponding to model years between 1984 and 2024. A subset of the most-recent records in the dataset was analyzed here. This subset has 1357 records for model years 2023 and 2024. These records were divided into 6 groups based on the energy source(s) as 993 conventional gasoline-only, 193 unplugged hybrid electric, 113 battery electric, 22 diesel-powered, 20 plug-in hybrid, and 16 dual-fuel ethanol-gasoline. Averages of multiple performance metrics for each group were computed. These vehicle performance metrics help in identifying green vehicles releasing no (or little) tailpipe emissions, or in identifying economic vehicles conserving (paid) energy. Ten green vehicle metrics are covered here. The most important of them is the released grams of tailpipe carbon dioxide per kilometer of driving (or per mile). The overall average of this metric for all analyzed records was 231.0 gCO2/km (corresponding to 371.7 gCO2/mi). With a standard combined driving mode (55% city, 45% highway), 1 L of liquid fuel (gasoline/petrol, diesel, or E85 ethanol-gasoline blend) or a standard equivalent electric energy of 8.90 kWh (32.0 MJ) is consumed by an average vehicle for traveling a distance of 12.4 km (corresponding to 29.3 miles per US gallon of gasoline-equivalent, or MPGe).

Date: 2024-04-07
References: Add references at CitEc
Citations:

Downloads: (external link)
https://osf.io/download/67dda799bbe8d968d5f32e8a/

Related works:
This item may be available elsewhere in EconPapers: Search for items with the same title.

Export reference: BibTeX RIS (EndNote, ProCite, RefMan) HTML/Text

Persistent link: https://EconPapers.repec.org/RePEc:osf:osfxxx:9d5by_v1

DOI: 10.31219/osf.io/9d5by_v1

Access Statistics for this paper

More papers in OSF Preprints from Center for Open Science
Bibliographic data for series maintained by OSF ().