Does A Battery-Electric Truck Make A Difference? – Life Cycle Emissions, Costs, And Externality Analysis Of Alternative Fuel-Powered Class 8 Heavy-Duty Trucks In The United States

Keywords

Air pollution externalities; Alternative fuel technology; Battery-electric trucks; Heavy-duty trucks; Life-cycle assessment; Regional electricity generation analysis

Abstract

Attempting to gain insights from how alternative fuel technologies employed in heavy-duty trucks (HDTs) differ with respect to their life-cycle emissions, costs, and externalities presents an important opportunity to develop a more holistic overall analysis of future HDTs. To this end, this study uses a hybrid life-cycle assessment method to analyze and compare alternative fuel-powered Class 8 HDTs. To account for the uncertainty in the data a Monte Carlo simulation is also applied. The HDTs considered in this analysis (biodiesel (B20), compressed natural gas (CNG), hybrid, and BE HDTs) are compared to the diesel HDT (conventional HDT). The results show that BE HDTs outperform all other types of trucks overall, despite their incremental costs and electricity generation-related emissions. Furthermore, if such a BE truck were to run on electricity generated in the Northeast Power Coordinating Council (NPCC) NERC region, fuel-consumption related GHGs emissions from BE HDTs could decrease by as much as 63 percent. It has also been found that, although there is a slight difference between the life-cycle costs (LCCs) of conventional HDTs and CNG-powered HDTs, the latter emits 33% more GHGs than the former. Moreover, this study concludes that CNG trucks yield no improvements in either HDT's life-cycle environmental impacts or LCCs compared to their conventional counterparts. Providing that electricity is generated from renewable energy sources, the use of BE trucks would significantly improve the life-cycle performance of a truck as well as ambient air quality.

Publication Date

1-10-2017

Publication Title

Journal of Cleaner Production

Volume

141

Number of Pages

110-121

Document Type

Article

Personal Identifier

scopus

DOI Link

https://doi.org/10.1016/j.jclepro.2016.09.046

Socpus ID

84994556231 (Scopus)

Source API URL

https://api.elsevier.com/content/abstract/scopus_id/84994556231

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