Explicit consideration of human exposure to minimize freight routing impacts

Abstract

As freight demand grows, so do its negative externalities, such as health and environmental impacts. This study integrates a reduced-complexity air quality model (RCM) with a multimodal traffic assignment model to analyze the scenario in which trucks minimize their public health costs. The study compares the least health-cost path (LHCP) with the shortest, fastest, and least-emissions paths. Two LHCP scenarios with geofences around sensitive populations differed in travel time (TT), health costs, and community impacts. LHCP had 10.9% higher TT and 29% lower costs than the next lowest scenarios. Under the LHCP, within-scenario burdens increased for some communities (e.g., PM_2.5 burden) but decreased for others (e.g., ozone burden). The other routing scenarios similarly produced differential effects across communities, highlighting tradeoffs. Geofences increased TT and health costs relative to the LHCP and produced different community impacts. This study provides new, actionable insights into methods to mitigate transportation externalities, particularly in communities.