Abstract
Rebates incentivize clean vehicle adoption but may raise equity concerns because upfront capital is required for vehicle acquisition, limiting access for low-income households. Since poorer communities typically experience worse air quality than their wealthier counterparts, rebates also may not incentivize clean vehicle acquisitions in more polluted areas where air quality benefits would be greater. We analyzed whether equity-promoting policy design elements changed the associations between rebate allocation rates and census tract characteristics including community disadvantage, household income, education, race and ethnicity, and ambient air pollution in two California rebate programs. We found that the Clean Vehicle Rebate Project issued more rebates per household to advantaged, higher-income, better-educated communities with more White residents and intermediate levels of ambient nitrogen dioxide (NO2). An income cap and income-tiered rebate amount introduced part way through the program improved distributional equity, but fewer rebates were still issued to lower income, less-educated census tracts with higher percentages of Hispanic and non-Hispanic Black residents. Furthermore, these policy design elements reduced the overall number of rebates that were distributed. In the Enhanced Fleet Modernization Program, which incorporates additional equity-related design elements, rebate allocation rates were positively associated with community disadvantage, lower income and education, and a higher proportion of Hispanics, and were the highest in areas with slightly higher NO2 levels. These findings indicate that design elements such as an income cap, income-tiered rebate amounts, expanded vehicle eligibility, and increased benefit eligibility in disadvantaged communities, can facilitate distribution of rebates to more socioeconomically diverse populations with higher air pollution burdens.
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This work was funded by the California Office of Environmental Health Hazard Assessment (https://oehha.ca.gov/; Contract #16-E0012-2).
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Geography, timeline, and spatial distribution of rebate programs (Fig. S1). Spearman rank correlations between CalEnviroScreen 3.0 scores and rebate allocation rates (Fig. S2). Data summary statistics (Tables S1 and S2). Regression model coefficients and 95% confidence intervals for the statewide CVRP model (Table S3). Regression model coefficients and 95% confidence intervals for the CVRP and EFMP in two air districts (Table S4). IRRs of population density (Table S5); (PDF 914 kb).
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Ju, Y., Cushing, L.J. & Morello-Frosch, R. An equity analysis of clean vehicle rebate programs in California. Climatic Change 162, 2087–2105 (2020). https://doi.org/10.1007/s10584-020-02836-w
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DOI: https://doi.org/10.1007/s10584-020-02836-w