The University of Tokyo · Environmental Science
Professor Chao Lin's research lab specializes in urban air quality and atmospheric dispersion modeling, focusing on the complex interactions between traffic emissions, urban morphology, and atmospheric processes. The lab develops advanced computational models—such as the SSH-Aerosol box model—coupled with CFD tools like OpenFOAM and Code_Saturne to simulate the formation and dispersion of primary and secondary pollutants, including NO₂ and PM₁₀. Experimental validation is conducted through high-resolution wind tunnel studies using Particle Image Velocimetry (PIV), particularly examining the impact of building features like parapets and upwind structures on rooftop wind conditions for Urban-Air-Mobility (UAM) safety. The lab also advances turbulence modeling by proposing anisotropic diffusivity approaches to improve the accuracy of pollutant plume prediction in urban boundary layers.
Figures are computed from collected data and may differ slightly.
Abstract. In the urban environment, gas and particles impose adverse impacts on the health of pedestrians. The conventional computational fluid dynamics (CFD) methods that regard pollutants as passive scalars cannot reproduce the formation of secondary pollutants and lead to uncertain prediction. In this study, SSH-aerosol, a modular box model that simulates the evolution of gas, primary and secondary aerosols, is coupled with the CFD software, OpenFOAM and Code_Saturne. The transient dispersion
• PIV measurements are conducted to investigate parapet influence on rooftop airflow. • Parapets reduce near-roof wind-speed by more than 60%. • Parapets reduce near-roof wind-speed standard-deviation by 29%-50%. • Parapets reduce gust factor in the roof center but increase it near parapet regions. • Taller parapet is preferrable to provide low wind-speed and low wind-fluctuation region. This study investigates the parapet influence on rooftop wind conditions of an isolated building towards safe
This study proposes an anisotropic concentration diffusivity model in the Reynolds-averaged Navier-Stokes equations (RANS) and the Eulerian dispersion model. The proposed model combines models to consider the turbulent anisotropic and near-source limited diffusivity based on the generalized gradient-diffusion hypothesis and travel time. The proposed model and conventional isotropic models were applied to predict the pollutant dispersion in an atmospheric boundary layer from elevated and ground-l
Abstract. In the urban environment, gas such as nitrogen dioxide NO2, and particles impose adverse impacts on pedestrians’ health. The conventional computational fluid dynamics (CFD) methods that regard pollutant as passive scalar cannot reproduce the formation of secondary pollutants, such as NO2 and secondary inorganic and organic aerosols, leading to uncertain prediction. In this study, SSH-Aerosol, a modular box model that simulates the evolution of gas, primary and secondary aerosols, is co
• PIV measurements captured rooftop flow with varying upwind and parapet configurations. • Skimming flow due to an equal-height building increased rooftop wind speed. • Sheltering by a taller building reduced wind speed and increased the gust factor on the rooftop. • Parapets reduced wind speed and fluctuation at 1.05 times the building height. • Parapets increased gust factor and flow fluctuations at 1.15 times the building height. This study investigates the influence of the parapet on rooftop
In the urban environment, gas such as nitrogen dioxide NO2, and particles impose adverse impacts on pedestrians’ health. The conventional computational fluid dynamics (CFD) methods that regard pollutant as passive scalar cannot reproduce the formation of secondary pollutants, such as NO2 and secondary inorganic and organic aerosols, leading to uncertain prediction. In this study, SSH-Aerosol, a modular box model that simulates the evolution of gas, primary and secondary aerosols, is coupled with
In the urban environment, gas such as nitrogen dioxide NO2, and particles impose adverse impacts on pedestrians’ health. The conventional computational fluid dynamics (CFD) methods that regard pollutant as passive scalar cannot reproduce the formation of secondary pollutants, such as NO2 and secondary inorganic and organic aerosols, leading to uncertain prediction. In this study, SSH-Aerosol, a modular box model that simulates the evolution of gas, primary and secondary aerosols, is coupled with
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