Determinants of electric vehicle emissions savings and costs across locations and individuals

Unofficial AI-generated summary based on the public title and abstract. Not an official translation.

🔬研究者:Provides a comprehensive, location- and individual-specific analysis of EV emissions and costs, advancing understanding of heterogeneity in clean vehicle transitions.

🏢実務担当者:Fleet managers can use the findings to optimize EV adoption rates based on local electricity grid, mileage, and driving patterns to maximize emission reductions cost-effectively.

🏛政策担当者:Offers evidence for designing EV incentives and infrastructure policies that account for regional and behavioral variability, improving cost-benefit analysis.

Abstract Electric vehicles (EVs) such as plug-in hybrid and battery EVs (PHEVs and BEVs) promise to lower greenhouse gas emissions compared to internal combustion engine vehicles (ICEVs). However, these emission reductions depend on regional and individual factors, which have been considered largely in isolation from one another and separately from costs. Here, we evaluate how current electricity mixes, driving behaviors, climatic conditions, prices, and fees affect lifecycle emissions and ownership costs of BEVs compared to ICEVs and PHEVs across locations and different individual vehicles within those locations. We conduct this analysis for the United States, which offers a wide range of background conditions and driving patterns. In most locations, BEVs save 40%–60% of emissions compared to ICEVs, though these values can vary substantially at the extremes (0–4700 kgCO 2 eq yr −1 or 0%–82%). The electricity mix is the most important contributor to these regional variations, leading to more uniform and greater emissions reductions if the electricity supply decarbonizes. Regional driving patterns mean that PHEVs achieve 80%–90% of the emissions savings of BEVs in urban areas and 60% in rural areas, assuming regular charging. Individual driving patterns can, however, lead to as much variability in emission savings and costs of EVs as all regional factors combined. Collectively, these effects mean that a company or community prioritizing clean electricity and vehicles with high annual mileage and frequent urban driving may need to adopt only 9% BEVs to achieve 10% emissions reductions across their fleet, whereas a fleet with low annual miles and infrequent urban driving may need to adopt 42% BEVs to reach the same emissions reductions. Local climate has a more moderate effect on these results than is sometimes assumed. We also find that electricity costs are a key determinant of EV costs relative to ICEVs, along with gasoline prices and fees. In many locations and for many people, however, the costs of EVs—especially BEVs—are competitive with those of ICEVs. These results can inform efforts to decarbonize vehicle fleets and to develop platforms that provide personalized information to consumers.

• crossref https://doi.org/10.1088/1748-9326/ae0c23first seen 2026-05-16 04:40:24 · last seen 2026-05-16 04:40:33