Air Quality-Driven Traffic Management Using High-Resolution Urban Climate Modeling Coupled with a Large Traffic Simulation
This study presents a framework for integrating traffic simulation with high-resolution air pollution modeling to design adaptive traffic management policies aimed at reducing urban air pollution. Building on prior work that establishes the coupling of the MATSim traffic model with the PALM-4U urban...
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| Format: | Article |
| Language: | English |
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MDPI AG
2025-01-01
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| Series: | Atmosphere |
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| Online Access: | https://www.mdpi.com/2073-4433/16/2/128 |
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| author | Janek Laudan Sabine Banzhaf Basit Khan Kai Nagel |
| author_facet | Janek Laudan Sabine Banzhaf Basit Khan Kai Nagel |
| author_sort | Janek Laudan |
| collection | DOAJ |
| description | This study presents a framework for integrating traffic simulation with high-resolution air pollution modeling to design adaptive traffic management policies aimed at reducing urban air pollution. Building on prior work that establishes the coupling of the MATSim traffic model with the PALM-4U urban climate model, this second part focuses on implementing a feedback loop to inform traffic management decisions based on simulated air pollution concentration levels. The research explores how traffic volumes and atmospheric conditions, such as boundary layer dynamics, influence air quality throughout the day. In an artificial case study of Berlin, a time-based toll is introduced, aimed at mitigating concentration peaks in the morning hours. The toll scheme is tested in two simulation scenarios and evaluated regarding the effectiveness of reducing air pollution levels, particularly NO<sub>2</sub> during the morning hours. The case study results serve to illustrate the framework’s capabilities and highlight the potential of integrating traffic and environmental models for adaptive policy design. The presented approach provides a model for responsive urban traffic management, effectively aligning transportation policies with environmental goals to improve air quality in urban settings. |
| format | Article |
| id | doaj-art-29acedf0f5fa49cfaa5b366e80724cef |
| institution | DOAJ |
| issn | 2073-4433 |
| language | English |
| publishDate | 2025-01-01 |
| publisher | MDPI AG |
| record_format | Article |
| series | Atmosphere |
| spelling | doaj-art-29acedf0f5fa49cfaa5b366e80724cef2025-08-20T02:44:47ZengMDPI AGAtmosphere2073-44332025-01-0116212810.3390/atmos16020128Air Quality-Driven Traffic Management Using High-Resolution Urban Climate Modeling Coupled with a Large Traffic SimulationJanek Laudan0Sabine Banzhaf1Basit Khan2Kai Nagel3Institute of Land and Sea Transport Systems, Transport Systems Planning and Transport Telematics, Technische Universität Berlin, Kaiserin-Augusta-Allee 104-106, 10365 Berlin, GermanyInstitute of Meteorology, Tropospheric Environmental Research, Freie Universität Berlin, Carl-Heinrich Becker-Weg 6-10, 12165 Berlin, GermanyMubadala Arabian Center for Climate and Environmental Sciences (ACCESS), New York University Abu Dhabi, Abu Dhabi P.O. Box 129188, United Arab EmiratesInstitute of Land and Sea Transport Systems, Transport Systems Planning and Transport Telematics, Technische Universität Berlin, Kaiserin-Augusta-Allee 104-106, 10365 Berlin, GermanyThis study presents a framework for integrating traffic simulation with high-resolution air pollution modeling to design adaptive traffic management policies aimed at reducing urban air pollution. Building on prior work that establishes the coupling of the MATSim traffic model with the PALM-4U urban climate model, this second part focuses on implementing a feedback loop to inform traffic management decisions based on simulated air pollution concentration levels. The research explores how traffic volumes and atmospheric conditions, such as boundary layer dynamics, influence air quality throughout the day. In an artificial case study of Berlin, a time-based toll is introduced, aimed at mitigating concentration peaks in the morning hours. The toll scheme is tested in two simulation scenarios and evaluated regarding the effectiveness of reducing air pollution levels, particularly NO<sub>2</sub> during the morning hours. The case study results serve to illustrate the framework’s capabilities and highlight the potential of integrating traffic and environmental models for adaptive policy design. The presented approach provides a model for responsive urban traffic management, effectively aligning transportation policies with environmental goals to improve air quality in urban settings.https://www.mdpi.com/2073-4433/16/2/128emission modelingair pollutionpollution hotspotCFDtraffic simulation |
| spellingShingle | Janek Laudan Sabine Banzhaf Basit Khan Kai Nagel Air Quality-Driven Traffic Management Using High-Resolution Urban Climate Modeling Coupled with a Large Traffic Simulation Atmosphere emission modeling air pollution pollution hotspot CFD traffic simulation |
| title | Air Quality-Driven Traffic Management Using High-Resolution Urban Climate Modeling Coupled with a Large Traffic Simulation |
| title_full | Air Quality-Driven Traffic Management Using High-Resolution Urban Climate Modeling Coupled with a Large Traffic Simulation |
| title_fullStr | Air Quality-Driven Traffic Management Using High-Resolution Urban Climate Modeling Coupled with a Large Traffic Simulation |
| title_full_unstemmed | Air Quality-Driven Traffic Management Using High-Resolution Urban Climate Modeling Coupled with a Large Traffic Simulation |
| title_short | Air Quality-Driven Traffic Management Using High-Resolution Urban Climate Modeling Coupled with a Large Traffic Simulation |
| title_sort | air quality driven traffic management using high resolution urban climate modeling coupled with a large traffic simulation |
| topic | emission modeling air pollution pollution hotspot CFD traffic simulation |
| url | https://www.mdpi.com/2073-4433/16/2/128 |
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