Articles | Volume 23, issue 2
https://doi.org/10.5194/acp-23-1421-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
https://doi.org/10.5194/acp-23-1421-2023
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
Modeling of street-scale pollutant dispersion by coupled simulation of chemical reaction, aerosol dynamics, and CFD
Chao Lin
CORRESPONDING AUTHOR
Graduate School of Engineering, The University of Tokyo, 4-6-1
Komaba, Meguro-ku, Tokyo 153-8505, Japan
Yunyi Wang
CEREA, École des Ponts ParisTech, EdF R&D, 77 455 Marne la
Vallée, France
Ryozo Ooka
Institute of Industrial Science, The University of Tokyo, 4-6-1
Komaba, Meguro-ku, Tokyo 153-8505, Japan
Cédric Flageul
Curiosity Group, Prime Institute, Université de Poitiers, CNRS,
ISAE-ENSMA, Chasseneuil, France
Youngseob Kim
CEREA, École des Ponts ParisTech, EdF R&D, 77 455 Marne la
Vallée, France
Hideki Kikumoto
Institute of Industrial Science, The University of Tokyo, 4-6-1
Komaba, Meguro-ku, Tokyo 153-8505, Japan
Zhizhao Wang
CEREA, École des Ponts ParisTech, EdF R&D, 77 455 Marne la
Vallée, France
Karine Sartelet
CEREA, École des Ponts ParisTech, EdF R&D, 77 455 Marne la
Vallée, France
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Cited
12 citations as recorded by crossref.
- Large-eddy simulations on pollutant reduction effects of road-center hedge and solid barriers in an idealized street canyon C. Lin et al. 10.1016/j.buildenv.2023.110464
- Spatial Distribution of PM2.5 Mass and Number Concentrations in Paris (France) from the Pollutrack Network of Mobile Sensors during 2018–2022 J. Renard et al. 10.3390/s23208560
- Impact of solid road barriers on reactive pollutant dispersion in an idealized urban canyon: A large-eddy simulation coupled with chemistry C. Lin et al. 10.1016/j.uclim.2024.101989
- Machine learning and deep learning approaches for PM2.5 prediction: a study on urban air quality in Jaipur, India S. Singh & G. Suthar 10.1007/s12145-024-01648-1
- To what extent is the description of streets important in estimating local air quality: a case study over Paris A. Squarcioni et al. 10.5194/acp-25-93-2025
- Use of Computational Fluid Dynamics to Study Ammonia Concentrations at Pedestrian Height in Smart Broiler Chamber Clusters M. Li et al. 10.3390/agriculture13030656
- Modelling concentration heterogeneities in streets using the street-network model MUNICH T. Sarica et al. 10.5194/gmd-16-5281-2023
- Impact of gas dry deposition parameterization on secondary particle formation in an urban canyon C. Lin et al. 10.1016/j.atmosenv.2024.120633
- Data extension of high-resolution wind speed database by fusing meteorological observation and local objective analysis data with POD–LSE X. Wang et al. 10.1016/j.jweia.2024.105812
- On the suitability of dispersion models of varying degree of complexity for air quality assessment and urban planning W. Patiño et al. 10.1016/j.buildenv.2024.111892
- Using computational fluid dynamics to minimize droplet dispersion in intraoral suction devices with a dental triple syringe T. Phonsahwat et al. 10.1016/j.buildenv.2025.112699
- Population exposure to outdoor NO2, black carbon, and ultrafine and fine particles over Paris with multi-scale modelling down to the street scale S. Park et al. 10.5194/acp-25-3363-2025
12 citations as recorded by crossref.
- Large-eddy simulations on pollutant reduction effects of road-center hedge and solid barriers in an idealized street canyon C. Lin et al. 10.1016/j.buildenv.2023.110464
- Spatial Distribution of PM2.5 Mass and Number Concentrations in Paris (France) from the Pollutrack Network of Mobile Sensors during 2018–2022 J. Renard et al. 10.3390/s23208560
- Impact of solid road barriers on reactive pollutant dispersion in an idealized urban canyon: A large-eddy simulation coupled with chemistry C. Lin et al. 10.1016/j.uclim.2024.101989
- Machine learning and deep learning approaches for PM2.5 prediction: a study on urban air quality in Jaipur, India S. Singh & G. Suthar 10.1007/s12145-024-01648-1
- To what extent is the description of streets important in estimating local air quality: a case study over Paris A. Squarcioni et al. 10.5194/acp-25-93-2025
- Use of Computational Fluid Dynamics to Study Ammonia Concentrations at Pedestrian Height in Smart Broiler Chamber Clusters M. Li et al. 10.3390/agriculture13030656
- Modelling concentration heterogeneities in streets using the street-network model MUNICH T. Sarica et al. 10.5194/gmd-16-5281-2023
- Impact of gas dry deposition parameterization on secondary particle formation in an urban canyon C. Lin et al. 10.1016/j.atmosenv.2024.120633
- Data extension of high-resolution wind speed database by fusing meteorological observation and local objective analysis data with POD–LSE X. Wang et al. 10.1016/j.jweia.2024.105812
- On the suitability of dispersion models of varying degree of complexity for air quality assessment and urban planning W. Patiño et al. 10.1016/j.buildenv.2024.111892
- Using computational fluid dynamics to minimize droplet dispersion in intraoral suction devices with a dental triple syringe T. Phonsahwat et al. 10.1016/j.buildenv.2025.112699
- Population exposure to outdoor NO2, black carbon, and ultrafine and fine particles over Paris with multi-scale modelling down to the street scale S. Park et al. 10.5194/acp-25-3363-2025
Latest update: 01 Apr 2025
Short summary
In this study, SSH-aerosol, a modular box model that simulates the evolution of gas, primary, and secondary aerosols, is coupled with the computational fluid dynamics (CFD) software, OpenFOAM and Code_Saturne. The transient dispersion of pollutants emitted from traffic in a street canyon of Greater Paris is simulated. The coupled model achieved better agreement in NO2 and PM10 with measurement data than the conventional CFD simulation which regards pollutants as passive scalars.
In this study, SSH-aerosol, a modular box model that simulates the evolution of gas, primary,...
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