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<front>
<journal-meta>
<journal-id journal-id-type="publisher">EGUsphere</journal-id>
<journal-title-group>
<journal-title>EGUsphere</journal-title>
<abbrev-journal-title abbrev-type="publisher">EGUsphere</abbrev-journal-title>
<abbrev-journal-title abbrev-type="nlm-ta">EGUsphere</abbrev-journal-title>
</journal-title-group>
<issn pub-type="epub"></issn>
<publisher><publisher-name>Copernicus Publications</publisher-name>
<publisher-loc>Göttingen, Germany</publisher-loc>
</publisher>
</journal-meta>
<article-meta>
<article-id pub-id-type="doi">10.5194/egusphere-2026-1685</article-id>
<title-group>
<article-title>FluidUrban v1.0: Enhancing Urban Ventilation and Pollutant Dispersion Modelling with Three-dimensional Dynamic Adaptive Meshes Optimisation</article-title>
</title-group>
<contrib-group><contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Wu</surname>
<given-names>Xiaofei</given-names>
<ext-link>https://orcid.org/0000-0002-4797-1256</ext-link>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Chen</surname>
<given-names>Siyang</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Li</surname>
<given-names>Jinxi</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Zhang</surname>
<given-names>Yu</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Wang</surname>
<given-names>Zifa</given-names>
</name>
<xref ref-type="aff" rid="aff2">
<sup>2</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Gan</surname>
<given-names>Pu</given-names>
</name>
<xref ref-type="aff" rid="aff1">
<sup>1</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Zheng</surname>
<given-names>Jie</given-names>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
<contrib contrib-type="author" xlink:type="simple"><name name-style="western"><surname>Fang</surname>
<given-names>Fangxin</given-names>
<ext-link>https://orcid.org/0000-0002-3777-8428</ext-link>
</name>
<xref ref-type="aff" rid="aff3">
<sup>3</sup>
</xref>
</contrib>
</contrib-group><aff id="aff1">
<label>1</label>
<addr-line>Climate Change and Resource Utilization in Complex Terrain Regions Key Laboratory of Sichuan Province, Chengdu Plain   Urban Meteorology and Environment Observation and Research Station of Sichuan Province, School of Atmospheric Sciences, Chengdu University of Information Technology, Chengdu, 610225, China</addr-line>
</aff>
<aff id="aff2">
<label>2</label>
<addr-line>State Key Laboratory of Atmospheric Environment and Extreme Meteorology, Institute of Atmospheric Physics, Chinese Academy of Sciences, Beijing, 100029, China</addr-line>
</aff>
<aff id="aff3">
<label>3</label>
<addr-line>Applied Modelling and Computation Group, Department of Earth Science and Engineering, Imperial College London,  London, SW7 2AZ, United Kingdom</addr-line>
</aff>
<pub-date pub-type="epub">
<day>08</day>
<month>05</month>
<year>2026</year>
</pub-date>
<volume>2026</volume>
<fpage>1</fpage>
<lpage>31</lpage>
<permissions>
<copyright-statement>Copyright: &#x000a9; 2026 Xiaofei Wu et al.</copyright-statement>
<copyright-year>2026</copyright-year>
<license license-type="open-access">
<license-p>This work is licensed under the Creative Commons Attribution 4.0 International License. To view a copy of this licence, visit <ext-link ext-link-type="uri"  xlink:href="https://creativecommons.org/licenses/by/4.0/">https://creativecommons.org/licenses/by/4.0/</ext-link></license-p>
</license>
</permissions>
<self-uri xlink:href="https://egusphere.copernicus.org/preprints/2026/egusphere-2026-1685/">This article is available from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-1685/</self-uri>
<self-uri xlink:href="https://egusphere.copernicus.org/preprints/2026/egusphere-2026-1685/egusphere-2026-1685.pdf">The full text article is available as a PDF file from https://egusphere.copernicus.org/preprints/2026/egusphere-2026-1685/egusphere-2026-1685.pdf</self-uri>
<abstract>
<p>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&apos;s performance is systematically evaluated against high-fidelity &amp;ldquo;WOTAN&amp;rdquo; 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.</p>
</abstract>
<counts><page-count count="31"/></counts>
<funding-group>
<award-group id="gs1">
<funding-source>National Key Research and Development Program of China</funding-source>
<award-id>2023YFC3705702</award-id>
</award-group>
<award-group id="gs2">
<funding-source>Engineering and Physical Sciences Research Council</funding-source>
<award-id>EP/X029093/1</award-id>
</award-group>
</funding-group>
</article-meta>
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