Addressing Inequities in EV Infrastructure: Socio-Economic Disparities & Strategies for Equity

Abstract

Transportation accounts for the largest share of greenhouse gas emissions in the United States, with personal vehicles as primary contributors. Electric vehicles (EVs) are a critical pathway for emissions reduction. However, EV charging infrastructure deployment has been unevenly distributed and disproportionately concentrated in affluent urban areas, leaving low-income and minority communities underserved. 

These inequities have created "charging deserts," where limited access hinders EV adoption and worsens socio-economic disparities. This study uses an Ordinary Least Squares (OLS) regression model to examine the relationship between socio-economic, demographic, and transportation variables and EV charging infrastructure distribution across ZIP codes. Key predictors, including population size, household income, public transportation usage, and vehicle availability, were examined. Higher population size (β = 2.029e-05, p = 0.016) and household income above $100,000 (β = 0.0179, p < 0.001) significantly increase EV infrastructure availability. Conversely, higher vehicle ownership (β = -5.574e-05, p = 0.019) is negatively correlated. Public transportation usage (β = 0.0228, p = 0.004) emerges as a significant predictor, highlighting transit-oriented areas as critical locations for infrastructure expansion.

These findings emphasize systemic inequities in EV charging infrastructure distribution and underscore the need for targeted policy interventions. Addressing these disparities requires prioritizing underserved communities through financial incentives, public-private partnerships, and strategic integration of EV infrastructure into transportation and urban planning. This study contributes to the growing body of literature on sustainable transportation by providing empirical evidence to inform policies for equitable EV adoption and reduced transportation-related emissions.