Impact, efficiency, inequality, and injustice of urban air pollution: Variability by emission location

Abstract

Reducing exposure to air pollution is an important goal for many local and national governments. Disparities in air pollution exposure by race, ethnicity, and socioeconomic class are well documented; reducing these disparities is another important policy target. Meeting both goals requires tools to evaluate how emission reduction options affect average exposures and exposure disparities. Here, we consider the role of emission location in implementing control strategies, and investigate the effect of two practical, space-based approaches - low-emission zones and truck rerouting - on diesel particle levels in Southern California. We employ Eulerian grid modeling to explore the impact that emission location has on four outcomes important to policymakers: total pollution exposure, exposure efficiency (i.e. exposure impact per unit emission), exposure inequality (i.e. deviations from exposure being equally distributed across the population; unequal exposure among individuals), and exposure injustice (i.e. associations between exposure and demographic attributes such as race or ethnicity; unequal exposure among groups). Our results highlight potential trade-offs (e.g. an increase in equality but reduction in justice for interventions in some locations) as well as opportunities for 'win-win' solutions (locations for which emission reductions would reduce all four target outcomes). We find that a simple, straightforward approach - reducing emissions in neighborhoods with a high proportion of minority residents - may or may not yield the strongest benefits to environmental justice; the reason is that the straightforward approach fails to account for meteorology and where pollution travels after being emitted. In short, we demonstrate an approach that can be used to identify areas in which emissions reductions would have high efficiency and would also result in disproportionately large reductions to average exposure, exposure inequality, and exposure injustice. The approach presented here could be used to design and prioritize local or national emission reduction efforts.