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Exploring Regional Reduction Pathways for Human Exposure to Fine Particulate Matter (PM2.5) Using a Traffic Assignment Model
- Source :
- Environmental Science & Technology; December 2023, Vol. 57 Issue: 48 p19649-19662, 14p
- Publication Year :
- 2023
-
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. PM2.5exposure 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 PM2.5exposure 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 PM2.5exposure 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%.
Details
- Language :
- English
- ISSN :
- 0013936X and 15205851
- Volume :
- 57
- Issue :
- 48
- Database :
- Supplemental Index
- Journal :
- Environmental Science & Technology
- Publication Type :
- Periodical
- Accession number :
- ejs64476895
- Full Text :
- https://doi.org/10.1021/acs.est.3c05594