Electric vehicle fleet penetration helps address inequalities in air quality and improves environmental justice

Environmental justice (EJ) concerns highlight the disproportionate exposure of communities of color and low-income populations to environmental hazards, including air pollution. Traffic-related air pollutants (TRAPs), especially near major roads, contribute significantly to these disparities. While overall air pollution has decreased with emission control measures, inequalities persist. Vehicle electrification is a key strategy to reduce on-road emissions and improve air quality. Previous studies have demonstrated that EV penetration reduces on-road emissions, but fewer studies have specifically quantified the benefits for near-road EJ communities. This study addresses this gap by evaluating the impact of different EV penetration scenarios on air quality in Southern California communities adjacent to Interstate 710, a heavily trafficked roadway known for high levels of air pollution and disproportionate impacts on EJ communities. The study aims to determine if accelerated EV penetration leads to greater air quality improvements in these disadvantaged communities compared to the general population.

Existing literature demonstrates a strong correlation between race/ethnicity, socioeconomic status, and proximity to pollution sources like major roads. Communities with higher proportions of POC and lower incomes are often situated near highways, leading to disproportionately higher exposure to TRAPs. Although studies show that on-road emissions have decreased over time, disparities in air pollution exposure remain. Studies have shown that EV penetration effectively reduces on-road emissions, encompassing both light-duty and medium-heavy-duty vehicles. However, most prior research has focused on regional-scale air quality impacts, neglecting the localized effects near major roads where disparities are most pronounced. Existing work has explored the impact of EV adoption on regional air quality, finding that it generally leads to reductions in PM2.5, ozone (O3), and NOx concentrations. However, some studies indicate that in certain regions, reduced NOx emissions from EVs can paradoxically lead to localized increases in O3 due to changes in photochemical reactions. This study builds on previous work by focusing specifically on the near-road impacts of EV penetration on EJ communities and utilizing more spatially detailed modeling to capture these localized concentration hotspots.

Six 2040 EV penetration scenarios were modeled, including a reference case (no additional policies) and five alternative scenarios reflecting various policy interventions to accelerate EV adoption, including scenarios based on California Air Resources Board (CARB) policies and projections from the National Cooperative Highway Research Program (NCHRP). The California EMFAC model was used to estimate vehicle populations and emissions for each scenario, considering both light-duty vehicles (LDVs) and medium- and heavy-duty vehicles (MHDVs). The analysis focused on direct (primary) emissions of NOx, NO2, and PM2.5. The impacts of power generation emissions were not considered due to California's planned phase-out of fossil fuel-based electricity generation by 2045 and the primarily regional nature of power plant emissions. The U.S. EPA's Research LINE (R-LINE) model, a sophisticated Gaussian dispersion model, was used to estimate near-road pollutant concentrations. Regional background concentrations were estimated using inverse distance weighting based on monitored air quality data projected to 2040. The study area focused on Southern California communities adjacent to Interstate 710. The modeled pollutant concentrations were analyzed using CalEnviroScreen 3.0 parameters to identify and characterize communities with EJ concerns, including demographic factors like race, White population percentage, education level, and a composite EJ score. The study tested the hypothesis that accelerated EV penetration would lead to larger air quality improvements in EJ communities compared to others. Health impacts were assessed using the attributable fraction (AF) of mortality due to air pollution exposure. Statistical significance was evaluated using one-way analysis of variance (ANOVA) and post-hoc Tukey-Kramer tests.

Aggressive EV penetration (Scenario 5, 85% EV share) resulted in substantial reductions in NO2 and PM2.5 emissions compared to the reference case. In Scenario 5, NO2 concentrations decreased by an average of 1.75 ppb (-20.4%), and PM2.5 concentrations decreased by an average of 0.98 µg/m³ (-6.8%). The analysis showed that NO2 and PM2.5 concentration reductions were greater in communities with higher proportions of POC. For instance, in Scenario 5, NO2 reductions were 1.9 ppb in communities with more Latino residents and 1.6 ppb in communities with more White residents. Similarly, PM2.5 reductions were 1.1 µg/m³ in communities with more Asian residents and 0.94 µg/m³ in communities with more White residents. These differences were statistically significant (p<0.05). Aggressive EV penetration reduced the maximum disparity in NO2 concentrations by 30% and the maximum disparity in PM2.5 concentrations by 14%. The attributable fraction (AF) of avoided mortality was higher for NO2 and PM2.5 in POC communities compared to White communities, indicating greater health benefits from EV penetration in EJ communities. The study also found that policies targeting MHDVs, such as the CARB Advanced Clean Truck (ACT) and Advanced Clean Fleet (ACF) regulations, were especially effective in reducing NO2 emissions, while policies focused on LDVs were more impactful in reducing PM2.5 emissions.

The findings support the hypothesis that accelerated EV penetration provides greater air quality improvements in EJ communities near major roadways. This is because these communities experience higher initial concentrations of TRAPs due to their location. While the absolute concentration reductions were relatively modest on a regional scale, the disproportionately larger reductions in EJ communities demonstrate a significant impact on reducing existing inequalities. The study highlights the importance of early and aggressive EV adoption policies to maximize emission reductions and equity benefits. The larger impact of MHDV policies on NO2 reductions underscore the significance of addressing emissions from heavier vehicles in densely populated areas with significant truck traffic, commonly near ports or industrial areas. The disparity reductions observed in this study, though significant, do not fully eliminate existing inequalities. Further research is needed to understand the long-term health impacts of EV penetration and to explore additional strategies to address remaining air pollution disparities.

This study provides compelling evidence that accelerated EV penetration in Southern California offers significant air quality benefits, particularly for EJ communities. The findings demonstrate that policies aiming for aggressive EV penetration lead to larger reductions in NO2 and PM2.5 concentrations in communities with higher proportions of POC compared to communities with primarily White residents, thereby reducing existing air pollution exposure disparities. This highlights the importance of policy interventions that prioritize both emission reductions and equity. Future research should focus on improving the accuracy of emissions and exposure models, better understanding the role of non-exhaust emissions, and conducting comprehensive health impact assessments to more precisely quantify the health benefits of EV adoption.

The study relied on modeling outputs, which can have inherent uncertainties. While the models employed are state-of-the-art, factors such as changes in future background concentrations and the evolution of non-exhaust emissions from EVs were not fully accounted for. The health impact assessment was limited to a relative comparison of the attributable fraction of mortality, not a full health risk assessment. The focus on a single region in California limits the generalizability of the findings to other regions with different demographics, transportation patterns, and electricity generation mixes.