Developing an evaluative framework for spatial equity and cost-effectiveness of emission reduction policies: A case...

Although numerous air quality and climate policies have recently been introduced, their effectiveness is assessed through regional-average pollutant concentration changes, with limited consideration of spatial variations in emissions, atmospheric chemistry, and population exposure. Here, battery electric vehicle (BEV) replacement is used as a counterfactual case to diagnose how large, spatially explicit reductions in on-road emissions, particularly NO_x, interact with atmospheric processes and population distribution to shape pollutant concentrations, exposure, and spatial equity. Using the Community Multiscale Air Quality (CMAQ) modeling system, we simulated an idealized scenario in which strong reductions in on-road diesel NO_x emissions are achieved through full replacement of diesel vehicles with BEVs. Population-weighted concentration (PWC) was used to evaluate responses across urban core (U.C.), urban periphery (U.P.), and rural regions. While NO_x emissions notably declined in the U.C. and U.P., annual averages of daily maximum 1-h O₃ concentrations increased owing to weakened NO titration, whereas ozone levels decreased in rural areas, leading to larger ozone PWC increases in urban areas despite modest concentration changes. Conversely, the largest reductions in fine particulate matter (PM_2.5) concentrations occurred in rural areas; however, lower population density limited corresponding exposure benefits. Consequently, relative mitigation cost required to achieve equivalent PM_2.5 exposure reductions was nearly nine times higher in the U.C. than in rural areas, indicating pronounced spatial disparities in mitigation efficiency. Importantly, within the diagnostic scenario and relative cost-effectiveness framework adopted in this study, complementary emission control conditions reduced the relative unit cost of PM_2.5 exposure mitigation in the U.C. by approximately 44% compared with the reference scenario. These results highlight the value of exposure-based diagnostic evaluations for interpreting the spatial equity implications of emission reduction policies and emphasize the role of nonlinear atmospheric responses, population distribution, and concurrent policy measures in shaping relative mitigation performance.