Addressing Environmental Justice: Importance Of Spatially-Targeted Emission-Reductions

Abstract

Introduction: Concentrations of fine particulate matter (PM2.5) in the U.S. have improved over time, but improvements in air quality have not always coincided with improvements in exposure disparity by race, ethnicity, and socioeconomic classes. The lack of quantifiable tools and methods to evaluate the justice and equality effects of emission-reduction options has limited the advancement and implementation of environmental justice policies. Methods: We employ CAMx, a state-of-the-science air dispersion model, to estimate air quality impacts of various spatial emission-reduction strategies of diesel PM2.5 in Southern California. We evaluate the emission-reductions scenarios based on four distinct goals: impact (total inhalation intake), efficiency (intake fraction), equality (Dissimilarity Index), and justice (exposure differences between socioeconomic groups). Results: Our results show that spatially-targeted emission-reductions can improve all four goals. Spatially-targeted reductions, such as a hypothetical low emission zone in downtown Los Angeles, could potentially yield large benefits at only modest changes in emissions' locations: for example, a 2.6% emission-reduction would yield 5%, 6%, and 18% reductions in health impact, exposure inequality, and exposure injustice, respectively. As another example, rerouting trucks to avoid hot spots of exposure disparity could improve exposure justice up to 67% and reduce the potential exposure of the truck emissions by 17%. Discussion: Spatially-targeted emission-reductions can highlight ways to meet environmental goals (environmental justice, total health impact, etc.) while reflecting and responding to factors such as demographics, meteorology, and emission-locations. The spatial patterns we identify uncover Pareto-optimal opportunities (“win-win's”) among those goals.