To evaluate the direction, strength, and statistical significance of the relationship between emission density (exposure) and demographic factors such as the percentage of the population that is non-White and median household income, we develop ordinary least squares (OLS) regression models. These models are stratified by U.S. state/county, vehicle type (All, LDV, MDV, and HDV), and pollutant (NOX and PM2.5). We estimated 50,162 models for each county in the U.S., excluding several very rural counties with too few data points. The mean R 2 values were 0.028 (sd = 0.052) for NOX emission density and 0.029 (sd = 0.053) for PM2.5 emission density, indicating the variability explained by the models in predicting emission density based on demographic predictors across different geographic and pollutant-specific contexts.