Exploring Regional Reduction Pathways for Human Exposure to Fine Particulate Matter (PM_2.5) Using a Traffic Assignment Model

Abstract

An exposure-based traffic assignment (TA) model is used to quantify primary and secondary fine particulate matter (PM2.5) exposure from on-road vehicle flow on the Chicago Metropolitan Area regional network. PM2.5 exposure due to emissions from light-duty vehicles, heavy-duty trucks, public transportation, and electricity generation for electric vehicle charging and light-rail transportation is considered. The model uses travel demand data disaggregated by time-of-day period and vehicle user class to compare the exposure impacts of two TA optimization scenarios: a baseline user equilibrium with respect to travel time (UET) and a system optimal with respect to pollutant intake (SOI). Estimated baseline PM2.5 exposure damages are $3.7B–$8.3B/year. The SOI uses exposure-based vehicle rerouting to reduce total damages by 8.2%, with high-impacted populations benefiting from 10% to 20% reductions. However, the SOI’s rerouting principle leads to a 66% increase in travel time. The model is then used to quantify the mitigation potential of different exposure reduction strategies, including a bi-objective optimization formulation that minimizes travel time and PM2.5 exposure concurrently, adoption of a cleaner vehicle fleet, higher public transportation use, particle filtration, and exposure-based truck routing. Exposure reductions range between 1% and 40%, but collective adoption of all strategies would lead to reductions upward of 50%.

Environmental Justice and Systems Analysis for Air Quality Planning in the Port of Oakland in California

“…Overall, there are 1576 census tracts included in the exposure domain. We elected to use InMAP/the ISRM, which models the physical transport and chemical formation of pollutants using 2005 WRF-Chem based meteorological data, as our mechanistic air quality model because of its efficiency , and applications to exposure domains of similar scale. ,− InMAP has also been used outside of the United States, − making the methodological steps presented in this research adaptable for other locations. Despite some limitations in the InMAP/ISRM (e.g., based on 2005 meteorological data, use of annually averaged input data, parametrization of some chemical relationships, underestimation of particulate sulfate and overestimation of particulate ammonium formation), it has been shown to have similar performance to other reduced-complexity air quality models and is within published air quality model performance criteria used to quantify monetized health damages. ,− …”