A Coupled Large-Eddy Simulation–Lagrangian Stochastic Modeling Framework with Applications to Urban Areas

Built terrains, with their complexity in morphology, high heterogeneity, and anthropogenic impact, impose substantial challenges in atmospheric boundary layer modeling. In this study, we developed a coupled large-eddy simulation (LES) –Lagrangian stochastic modeling (LSM) framework for urban terrains, with the built environment represented by street canyons. We used this modeling framework for two typical applications in this study, i.e. urban footprint estimates and simulations of effects of trees on pollutant dispersion. Running in a backward mode, the coupled LES–LSM is applied to evaluate the footprint over each urban facet. The proposed model is compared against an LSM based on Monin–Obukhov similarity theory (MOST) parameterization schemes. Predicted footprints using both models are similar when the sensor instrument is located at the upper part of the street canyon. However, the coupled model outperforms in depicting footprints when the sensor instrument is immersed into the lower part of the street canyon, owing to its capability of capturing canyon turbulent flow fields. We then apply the modeling framework in the forward mode to evaluate the effects of urban trees on the atmospheric dispersion of pollutants from vehicle emissions. A total of twenty-four scenarios were analyzed with various morphology of canyons and trees. The results show that trees taller than the mean building height lead to the strongest modification of the canyon flow and pollutant concentration. In addition, transport of scalar particles and the spatial distribution of the concentration over the leeward and windward walls are highly sensitive to the morphology of both street canyons and trees. The proposed modeling framework can be readily used for broader urban applications, providing solutions to urban environmental issues such as air quality monitoring, pollutant emission control, and pollution risk analysis.