A modelling-mapping approach for fine-scale assessment of pedestrian-level wind in high-density cities

This study develops an approach to model the pedestrian-level wind speed at high spatial resolution within urban areas. The aerodynamic properties of urban areas are a necessary component in the current urban planning and design. However current numerical modelling methods, such as Computational Fluid Dynamics (CFD), cannot balance modelling cost with result accuracy to satisfy the requirements of exploratory urban design at the neighborhood scale. Alternatively, current morphological models, algorithms that correlate urban geometries with aerodynamic properties, are inexpensive but can only provide results with low spatial resolution. This study describes the balance between the momentum transfer and drag force in both an averaged sense over an area and a moving air particle to extend conventional frontal area density (λf) to a point-specific index (λf_point). Through correlation with data from wind tunnel experiments, λf_point was determined to be a good index to assess the pedestrian-level wind speed at a test point with multiple input wind directions. Regression equations were developed to map the pedestrian-level wind environment at 1 m × 1 m resolution. This modelling-mapping approach requires less computational time and support technology than CFD simulations. Meanwhile, from a practical point of view, the modelling method provides accurate results at high resolution. Therefore, the modelling results of the urban wind environment can be well integrated into the neighborhood-scale design. Using this approach, urban planners and architects can estimate the neighborhood-scale pedestrian-level wind speed and optimize proposed planning and design at the onset of the procedure.