Unequal air quality benefits from EV adoption in California, the world’s EV leader

• Connects transport electrification to environmental justice using California ZIP code–level panel data (2015–2023). • Lower-income and less-educated communities consistently face higher PM 2.5 exposure. • EV adoption reduces PM 2.5 on average, but larger gains occur in wealthier, better-educated areas. • Develops a fixed-effects moderation framework (with elasticity analysis) to quantify unequal air-quality benefits of EVs. • Identifies income-based incentives, targeted charging, and public fleet electrification to prevent wider exposure gaps. Transport electrification is central to global decarbonization, yet its equity consequences remain contested. Within this broader transition, adoption of electric vehicles (EVs) has become a key pathway for reducing transport emissions. While EVs reduce emissions from internal combustion engines, the extent to which their benefits reach disadvantaged communities is uncertain. Using ZIP code-level panel data for California from 2015 to 2023, we combine fixed effects and moderation analysis to examine how EV adoption interacts with socioeconomic characteristics to shape PM 2.5 exposure. Our results confirm that disadvantaged communities with lower incomes and lower educational attainment face higher pollution burdens. EV adoption is associated with significant reductions in PM 2.5 concentrations (–0.034 to –0.060 µg/m 3 per thousand EVs; p < 0.05). However, the moderating effects show that these reductions are larger in wealthier and more educated areas, where adoption is already highest. This pattern suggests that EV adoption may unintentionally exacerbate existing inequalities by concentrating environmental benefits in advantaged communities. To ensure that the clean mobility transition delivers inclusive health gains, equity-centered policies, such as income-based incentives, targeted charging infrastructure, and public fleet electrification, are needed. Our framework provides a transferable approach for evaluating the distributional impacts of low-carbon transitions in diverse contexts.