Public Health and Climate Benefits and Trade-Offs of U.S. Vehicle Electrification

Abstract

Vehicle electrification is a common climate change mitigation strategy, with policymakers invoking co-beneficial reductions in carbon dioxide (CO₂) and air pollutant emissions. However, while previous studies of U.S. electric vehicle (EV) adoption consistently predict CO₂ mitigation benefits, air quality outcomes are equivocal and depend on policies assessed and experimental parameters. We analyze climate and health co-benefits and trade-offs of six U.S. EV adoption scenarios: 25% or 75% replacement of conventional internal combustion engine vehicles, each under three different EV-charging energy generation scenarios. We transfer emissions from tailpipe to power generation plant, simulate interactions of atmospheric chemistry and meteorology using the GFDL-AM4 chemistry climate model, and assess health consequences and uncertainties using the U.S. Environmental Protection Agency Benefits Mapping Analysis Program Community Edition (BenMAP-CE). We find that 25% U.S. EV adoption, with added energy demand sourced from the present-day electric grid, annually results in a ~242 M ton reduction in CO₂ emissions, 437 deaths avoided due to PM_2.5 reductions (95% CI: 295, 578), and 98 deaths avoided due to lesser ozone formation (95% CI: 33, 162). Despite some regions experiencing adverse health outcomes, ~$16.8B in damages avoided are predicted. Peak CO₂ reductions and health benefits occur with 75% EV adoption and increased emission-free energy sources (~$70B in damages avoided). When charging-electricity from aggressive EV adoption is combustion-only, adverse health outcomes increase substantially, highlighting the importance of low-to-zero emission power generation for greater realization of health co-benefits. Our results provide a more nuanced understanding of the transportation sector's climate change mitigation-health impact relationship.

Keywords: air quality; climate change; co‐benefits; electric vehicles; health impact analysis.

Figure 1

Air pollutant changes. Simulated annual average changes from the baseline scenario for (a–f) O₃ (MD8A: maximum daily 8‐hr average) and (g–l) PM_2.5 (24‐hr mean) for each EV adoption‐energy generation scenario.

Figure 2

National, regional, and state co‐benefits. Avoided premature mortality and CO₂ reduction co‐benefits under six vehicle electrification scenarios. (a) National aggregate benefits of CO₂, O₃, and PM_2.5 reductions. Metrics provided include premature deaths avoided, value of statistical life (Anenberg et al., 2019), tonnage of CO₂ emissions avoided, and the U.S. social cost of carbon ($48 ton⁻¹; Ricke et al., 2018). Error bars show the 95% CI for health impact results. Circles indicate premature death avoided from changes in O₃, as calculated using the Bell et al. (2004) HIF. Triangles indicate PM_2.5 premature deaths avoided annually, using Krewski et al. (2009). (b–g) Climate and PM_2.5 health co‐benefits and trade‐offs (Krewski et al., 2009) for individual states (smaller circles) and regional averages (larger circles). For population normalized data see Figure S3.

Figure 3

Annual premature deaths avoided. EV adoption scenario‐driven changes in air pollutants (a–f) O₃ (Bell et al., 2004) and (g–l) PM_2.5 (Krewski et al., 2009) drive changes in annual premature mortality incidence. Negative numbers signify increases in premature mortality. Panels (a) and (g) are subdivided into U.S. Census regions: Midwest, West, northeast, and south (U.S. Census Bureau, 2018). For population normalized state and grid cell level data see Figures S1 and S2.

Figure 4

Regional health outcome uncertainties. Regional premature mortality changes under different EV adoption scenarios and different HIFs. Error bars reflect 95% CI of HIFs. See Figure 3 for regional U.S. Census demarcations.