Traffic Simulation-Based Approach for A Cradle-to-Grave Greenhouse Gases Emission Model
Sergio Maria Patella,
Flavio Scrucca,
Francesco Asdrubali and
Stefano Carrese
Additional contact information
Sergio Maria Patella: Department of Engineering, Roma Tre University, Via Vito Volterra 62, 00146 Rome, Italy
Flavio Scrucca: CIRIAF, University of Perugia, Via G. Duranti 67, 06125 Perugia, Italy
Francesco Asdrubali: Department of Engineering, Roma Tre University, Via Vito Volterra 62, 00146 Rome, Italy
Stefano Carrese: Department of Engineering, Roma Tre University, Via Vito Volterra 62, 00146 Rome, Italy
Sustainability, 2019, vol. 11, issue 16, 1-14
Abstract:
This paper presents a model to evaluate the life cycle greenhouse gases (GHG) emissions, expressed in terms of carbon dioxide equivalent (CO 2 eq), of a generic fleet composition as a function of the traffic simulation results. First we evaluated the complete life cycle of each category of the vehicles currently circulating; next, by defining a general linear equation, the traffic environmental performances of a real road network (city of Rome) were evaluated using a traffic simulation approach. Finally, the proposed methodology was applied to evaluate the GHG emission of a 100% penetration of battery electric vehicles (BEVs) and various electric and conventional vehicles composition scenarios. In terms of life cycle impacts, BEVs are the vehicles with the highest GHG emissions at the vehicle level (construction + maintenance + end-of-life processes) that are, on average, 20% higher than internal combustion engine vehicles, and 6.5% higher than hybrid electric vehicles (HEVs). Nevertheless, a 100% BEVs penetration scenario generates a reduction of the environmental impact at the mobility system level of about 65%.
Keywords: traffic emissions; traffic simulation; electric vehicles; greenhouse gases emissions; life cycle assessment (search for similar items in EconPapers)
JEL-codes: O13 Q Q0 Q2 Q3 Q5 Q56 (search for similar items in EconPapers)
Date: 2019
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Citations: View citations in EconPapers (2)
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Persistent link: https://EconPapers.repec.org/RePEc:gam:jsusta:v:11:y:2019:i:16:p:4328-:d:256489
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