Preprints
https://doi.org/10.5194/egusphere-2026-1685
https://doi.org/10.5194/egusphere-2026-1685
08 May 2026
 | 08 May 2026
Status: this preprint is open for discussion and under review for Geoscientific Model Development (GMD).

FluidUrban v1.0: Enhancing Urban Ventilation and Pollutant Dispersion Modelling with Three-dimensional Dynamic Adaptive Meshes Optimisation

Xiaofei Wu, Siyang Chen, Jinxi Li, Yu Zhang, Zifa Wang, Pu Gan, Jie Zheng, and Fangxin Fang

Abstract. Simulating urban airflow and pollutant dispersion requires resolving multiscale physical processes, from large-scale meteorological forcing to highly localized building-induced turbulence. To accurately capture these multiscale urban flow fields, this study introduces FluidUrban v1.0, an advanced modelling system built upon the Fluidity solver and centred on a three-dimensional Dynamic Adaptive Mesh Optimization (DAMO) framework. By dynamically adapting mesh resolution in response to the evolution of flow physics and scalar gradients, DAMO concentrates computational resources on critical high-gradient regions such as building wakes, shear layers and scalar sharp plume. The model's performance is systematically evaluated against high-fidelity “WOTAN” wind-tunnel experimental data under varying surface roughness conditions and inflow directions. The results demonstrate that the FluidUrban with DAMO framework consistently outperforms traditional non-uniform fixed meshes (FIXM) by accurately capturing complex urban wind fields and pollutant concentration. For normalized wind speed, FluidUrban with DAMO achieved a Mean Absolute Error (MAE) of 0.187, representing a notable reduction from the 0.214 simulated by FIXM. In terms of wind direction, the model reduced the MAE by up to 38.4 % in medium roughness and 36.1 % in high roughness conditions, respectively, during realistic oblique inflow scenarios. Furthermore, for pollutant dispersion, the model effectively suppresses numerical diffusion and maintained sharply plume gradients, achieving an 89 % compliance rate with established atmospheric model evaluation standards (FB, NMSE, and MG), compared to only 50 % for FIXM. While DAMO introduces runtime cost for mesh regeneration, this cost is strategically offset by the optimization of the accuracy-efficiency balance. Following the systematic evaluation, FluidUrban v1.0 was applied to a realistic urban scenario, demonstrating its robust capability to resolve the complex flow fields and spatial heterogeneity within real urban morphologies. Thus, FluidUrban v1.0 demonstrates to be a robust aerodynamic tool for resolving the transient, small-scale flow structures critical to pollutant transport, establishing a solid foundation for the future integration of comprehensive urban physical components, including radiation, vegetation, and full energy-balance physics.

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Xiaofei Wu, Siyang Chen, Jinxi Li, Yu Zhang, Zifa Wang, Pu Gan, Jie Zheng, and Fangxin Fang

Status: open (until 03 Jul 2026)

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Xiaofei Wu, Siyang Chen, Jinxi Li, Yu Zhang, Zifa Wang, Pu Gan, Jie Zheng, and Fangxin Fang
Xiaofei Wu, Siyang Chen, Jinxi Li, Yu Zhang, Zifa Wang, Pu Gan, Jie Zheng, and Fangxin Fang

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Short summary
Cities face a major challenge in tracking how wind and air pollution move through complex building clusters. Common numerical models often struggle to balance accuracy with calculating speed. We developed a new simulation system that automatically adjusts its focus to where the air is moving rapidly. By testing this against observations, it significantly improves predictions of wind and pollution. This tool helps urban planners design healthier cities by better identifying how pollutants travel.
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