ValUr: A High-Fidelity Dataset for Validation of Urban Pollution Dispersion Models – Project Overview and Geometry Preparation
Paper in proceeding, 2025

Computational fluid dynamics (CFD) models, used independently or integrated into city digital twins, can predict air pollution dispersion and support informed decision-making in urban planning. While modelling complexity and capabilities have increased, systematic validation and uncertainty quantification remain crucial, yet are among the least understood and applied aspects of the analysis process. To address this issue, the ValUr project, supported by the ERIES programme, aims to establish a best-practice protocol for urban CFD validation and to generate a high-quality, open-access pollution dispersion dataset. This work introduces the project scope, motivation, and goals, detailing early project activities, including the identification of the study area - part of the city centre of Sofia, Bulgaria, where air quality is a pressing concern, and the creation of a scaled geometry suitable for physical model-making, wind tunnel testing, and CFD simulations. The geometry goes beyond the basic level of detail (LoD) 1, typically used in validation databases and reaches LoD 2.2, capturing the complex building morphologies and realistic urban conditions of the area. By sharing protocols and data openly, ValUr seeks to promote the importance of model reliability and to encourage validation consistency within the computational wind engineering community.

Wind tunnel testing

Urban pollution dispersion modelling

Model validation

Geometry preparation

Author

Mariya Pantusheva

Sofia University

Radostin Mitkov

Sofia University

Petar O. Hristov

Sofia University

Evgeny Shirinyan

Sofia University

Vasilis Alexandros Naserentin

University of Gothenburg

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

A. K.R. Jayakumari

Eindhoven University of Technology

Stefanie Gillmeier

Eindhoven University of Technology

Anders Logg

Chalmers, Mathematical Sciences, Applied Mathematics and Statistics

University of Gothenburg

Lecture Notes in Civil Engineering

23662557 (ISSN) 23662565 (eISSN)

Vol. 718 LNCE 83-94
9783031988929 (ISBN)

International Workshop in Engineering Research Infrastructures for European Synergies, ERIES-IW 2025
Lisbon, Portugal,

Big data for smart society (GATE)

European Commission (EC) (EC/H2020/857155), 2019-09-01 -- 2026-08-31.

Subject Categories (SSIF 2025)

Computer Sciences

DOI

10.1007/978-3-031-98893-6_9

More information

Latest update

9/3/2025 5