Abstract
The transport sector in Germany causes one-quarter of energy-related greenhouse gas emissions. One potential solution to reduce these emissions is the use of battery electric vehicles. Although a number of life cycle assessments have been conducted for these vehicles, the influence of a transport system-wide transition has not been addressed sufficiently. Therefore, we developed a method which combines life cycle assessment with an agent-based transport simulation and synthetic electric-, diesel- and gasoline-powered vehicle models. We use a transport simulation to obtain the number of vehicles, their lifetime mileage and road-specific consumption. Subsequently, we analyze the product systems’ vehicle production, use phase and end-of-life. The results are scaled depending on the covered distance, the vehicle weight and the consumption for the whole life cycle. The results indicate that the sole transition of drive trains is insufficient to significantly lower the greenhouse gas emissions. However, sensitivity analyses demonstrate that there is a considerable potential to reduce greenhouse gas emissions with higher shares of renewable energies, a different vehicle distribution and a higher lifetime mileage. The method facilitates the assessment of the ecological impacts of complete car-based transportation in urban agglomerations and is able to analyze different transport sectors.
Highlights
Life cycle assessment (LCA) is a standardized method to assess environmental impacts [1]
We presented a method that combines agent-based transport simulation and LCAs
We established approaches to investigate the influence of lifetime mileage, vehicle distribution, energy supply and standstill
Summary
Life cycle assessment (LCA) is a standardized method to assess environmental impacts [1]. Many LCAs have focused on the comparison of battery electric and internal combustion engine vehicles (BEVs and ICEVs) [2,3,4,5,6]. A considerable number of LCAs have addressed transport system strategic-specific scopes: Dér et al investigated EVs in fleets [12]. They analyzed the influence of the grid mix, ambient temperatures and driving parameters. Jaeger et al developed an LCA method for strategic decision-making in urban transportation [17] Others focused on reviews and comparisons of the conducted studies [9,18,19]
Talk to us
Join us for a 30 min session where you can share your feedback and ask us any queries you have
Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.