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

Saved in:
Bibliographic Details
Title: TRAPSim: An agent-based model to estimate personal exposure to non-exhaust road emissions in central Seoul.
Authors: Shin, Hyesop1 (AUTHOR) hyesop.shin@glasgow.ac.uk, Bithell, Mike1,2 (AUTHOR)
Source: Computers, Environment & Urban Systems. Jan2023, Vol. 99, pN.PAG-N.PAG. 1p.
Subjects: Vehicle models, Air quality, Roads, Subways, Cannabidiol, Roadside improvement
Geographic Terms: Seoul (Korea)
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 PM 10 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 PM 10 was significantly higher than the background PM 10. 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 PM 10 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 PM 10 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. • An agent-based model simulated the vehicles' NEEs and the adverse health effects. • Our model found that non-exhaust emissions contributed 25–30% of the roadside PM 10. • Banning 90% of vehicles to the study area led up to a 24% decrease in ambient PM 10. • 90% vehicle ban halved the at-risk drivers but negligible in subway commuters. • The estimates of health effects depend strongly on the parameterisation. [ABSTRACT FROM AUTHOR]
Copyright of Computers, Environment & Urban Systems is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)
Database: Engineering Source
FullText Text:
  Availability: 0
Header DbId: egs
DbLabel: Engineering Source
An: 160584911
AccessLevel: 6
PubType: Academic Journal
PubTypeId: academicJournal
PreciseRelevancyScore: 0
IllustrationInfo
Items – Name: Title
  Label: Title
  Group: Ti
  Data: TRAPSim: An agent-based model to estimate personal exposure to non-exhaust road emissions in central Seoul.
– Name: Author
  Label: Authors
  Group: Au
  Data: <searchLink fieldCode="AR" term="%22Shin%2C+Hyesop%22">Shin, Hyesop</searchLink><relatesTo>1</relatesTo> (AUTHOR)<i> hyesop.shin@glasgow.ac.uk</i><br /><searchLink fieldCode="AR" term="%22Bithell%2C+Mike%22">Bithell, Mike</searchLink><relatesTo>1,2</relatesTo> (AUTHOR)
– Name: TitleSource
  Label: Source
  Group: Src
  Data: <searchLink fieldCode="JN" term="%22Computers%2C+Environment+%26+Urban+Systems%22">Computers, Environment & Urban Systems</searchLink>. Jan2023, Vol. 99, pN.PAG-N.PAG. 1p.
– Name: Subject
  Label: Subjects
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Vehicle+models%22">Vehicle models</searchLink><br /><searchLink fieldCode="DE" term="%22Air+quality%22">Air quality</searchLink><br /><searchLink fieldCode="DE" term="%22Roads%22">Roads</searchLink><br /><searchLink fieldCode="DE" term="%22Subways%22">Subways</searchLink><br /><searchLink fieldCode="DE" term="%22Cannabidiol%22">Cannabidiol</searchLink><br /><searchLink fieldCode="DE" term="%22Roadside+improvement%22">Roadside improvement</searchLink>
– Name: SubjectGeographic
  Label: Geographic Terms
  Group: Su
  Data: <searchLink fieldCode="DE" term="%22Seoul+%28Korea%29%22">Seoul (Korea)</searchLink>
– Name: Abstract
  Label: Abstract
  Group: Ab
  Data: 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 PM 10 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 PM 10 was significantly higher than the background PM 10. 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 PM 10 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 PM 10 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. • An agent-based model simulated the vehicles' NEEs and the adverse health effects. • Our model found that non-exhaust emissions contributed 25–30% of the roadside PM 10. • Banning 90% of vehicles to the study area led up to a 24% decrease in ambient PM 10. • 90% vehicle ban halved the at-risk drivers but negligible in subway commuters. • The estimates of health effects depend strongly on the parameterisation. [ABSTRACT FROM AUTHOR]
– Name: AbstractSuppliedCopyright
  Label:
  Group: Ab
  Data: <i>Copyright of Computers, Environment & Urban Systems is the property of Pergamon Press - An Imprint of Elsevier Science and its content may not be copied or emailed to multiple sites without the copyright holder's express written permission. Additionally, content may not be used with any artificial intelligence tools or machine learning technologies. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract.</i> (Copyright applies to all Abstracts.)
PLink https://search.ebscohost.com/login.aspx?direct=true&site=eds-live&db=egs&AN=160584911
RecordInfo BibRecord:
  BibEntity:
    Identifiers:
      – Type: doi
        Value: 10.1016/j.compenvurbsys.2022.101894
    Languages:
      – Code: eng
        Text: English
    PhysicalDescription:
      Pagination:
        PageCount: 1
        StartPage: N.PAG
    Subjects:
      – SubjectFull: Vehicle models
        Type: general
      – SubjectFull: Air quality
        Type: general
      – SubjectFull: Roads
        Type: general
      – SubjectFull: Subways
        Type: general
      – SubjectFull: Cannabidiol
        Type: general
      – SubjectFull: Roadside improvement
        Type: general
      – SubjectFull: Seoul (Korea)
        Type: general
    Titles:
      – TitleFull: TRAPSim: An agent-based model to estimate personal exposure to non-exhaust road emissions in central Seoul.
        Type: main
  BibRelationships:
    HasContributorRelationships:
      – PersonEntity:
          Name:
            NameFull: Shin, Hyesop
      – PersonEntity:
          Name:
            NameFull: Bithell, Mike
    IsPartOfRelationships:
      – BibEntity:
          Dates:
            – D: 01
              M: 01
              Text: Jan2023
              Type: published
              Y: 2023
          Identifiers:
            – Type: issn-print
              Value: 01989715
          Numbering:
            – Type: volume
              Value: 99
          Titles:
            – TitleFull: Computers, Environment & Urban Systems
              Type: main
ResultId 1