TRAPSim: an agent-based model to estimate personal exposure to non-exhaust road emissions in central Seoul

Shin, H. and Bithell, M. (2023) TRAPSim: an agent-based model to estimate personal exposure to non-exhaust road emissions in central Seoul. Computers, Environment and Urban Systems, 99, 101894. (doi: 10.1016/j.compenvurbsys.2022.101894)

Abstract

Non-exhaust emissions (NEEs) from brake and tyre wear cause detrimental health effects, yet their relationship with mobility has not been examined rigorously. We constructed an agent-based traffic simulator to illustrate the coupled problems of emissions, behaviour, and the estimated exposure to PM10 for groups of drivers and subway commuters in Seoul CBD. Having calibrated the parameters, the results regarding the air quality revealed that roughly 25–30% of the roadside PM10 was significantly higher than the background PM10. Additionally, compared to intra-urban cars, pedestrians who commuted for longer periods of time and were exposed to more ambient particles suffered significant health losses; however, drivers only became aware of the health risk when PM10 levels were consistently high for a few days. Compared to the business-as-usual scenario of vehicle entry, a 90% vehicle restriction was able to reduce PM10 by 18–24% and cut the percentage of resident drivers who were at risk. However, it was not effective for subway commuters. Using an agent-based traffic simulator in a health context can provide insights into how exposure and health effects can vary depending on the time of exposure and the form of transportation.

• Item Type: Articles
• Status: Published
• Refereed: Yes
• Glasgow Author(s) Enlighten ID: Shin, Mr Hyesop
• Authors: Shin, H., and Bithell, M.
• College/School: College of Medical Veterinary and Life Sciences > School of Health & Wellbeing > MRC/CSO SPHSU
• Journal Name: Computers, Environment and Urban Systems
• Publisher: Elsevier
• ISSN: 0198-9715
• ISSN (Online): 1873-7587
• Published Online: 25 October 2022
• Copyright Holders: Copyright © 2022 Crown Copyright
• First Published: First published in Computers, Environment and Urban Systems 99: 101894
• Publisher Policy: Reproduced under a Creative Commons License
• Data DOI: 10.24433/CO.6287370.v1