EGU24-12397, updated on 09 Mar 2024
https://doi.org/10.5194/egusphere-egu24-12397
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Cross-Ventilation Strategies for Efficient Indoor Radon Reduction: Experimental Data and CFD Simulations

Diana Altendorf1, Henning Wienkenjohann1, Florian Berger1, Jörg Dehnert2, Michal Duzynski3, Hannes Grünewald4, Dmitri Naumov5, Ralf Trabitzsch1, and Holger Weiß1
Diana Altendorf et al.
  • 1Helmholtz-Zentrum für Umweltforschung - UFZ Leipzig, ENVINF, Leipzig, Germany (diana.altendorf@ufz.de)
  • 2Landesamt für Umwelt, Landwirtschaft und Geologie (LfULG), Dresden, Germany
  • 3Sarad GmbH, Dresden, Germany
  • 4inVENTer GmbH, Germany
  • 5Technische Universität Bergakademie Freiberg, TUBAF-UFZ Centre for Environmental Geosciences Freiberg, Freiberg, Germany

Naturally occurring radon-222 (Rn) is a widespread indoor air pollutant, posing a potential health risk for humans, particularly elevating the risk of lung cancer in indoor living and working spaces. One highly promising solution for existing buildings, requiring relatively minimal technical effort to reduce indoor radon, is the installation of a ventilation system.

As a proof of concept, a series of different ventilation experiments, utilising a decentralised ventilation system with heat recovery (inVENTer GmbH, Germany) were performed in an unoccupied ground-floor flat in Bad Schlema (Germany).

The flat was divided into three individually controllable ventilation zones using strategically positioned ventilation devices, controlled by a novel real-time measurement system for indoor radon activity concentration [Rn] (Smart Radon Sensors by SARAD GmbH, Germany) in each room. This innovative approach to eliminate indoor radon by employing [Rn] as a control parameter enabled automated switching between different ventilation modes or the option to deactivate the system entirely.

Over three years, the different ventilation experiments successfully reduced elevated indoor radon levels from up to 7000 Bq/m³ to 300 Bq/m³ and below. The effectiveness varied based on factors such as the initial room-specific radon levels before each experiment, the performance level of the fans and meteorological parameters.

Furthermore, we developed a true-to-scale three-dimensional Computational Fluid Dynamics (CFD) model based on the actual flat, enabling the quantitative interpretation of various ventilation experiments within a CFD environment. The CFD model utilised a stationary k-ε turbulent flow model to simulate ventilation-induced airflow inside the flat and was coupled with a transient transport model for radon simulation.

For the development of the CFD model, the "Cross-Ventilation" experiment was chosen. This experiment successfully achieved a room-specific reduction of indoor radon levels from approximately 3,000 Bq/m³ to about 300 Bq/m³. To precisely capture the impact of ventilation on indoor radon, the initial radon values for each room were utilised as initial conditions for the transient radon transport model.

Base case results showed an overestimation by the model in radon level reduction due to ventilation. Parameter adjustments of the inflowing radon and the airflow velocity at the inlet resulted in good agreement between experimental values and the CFD model's outcome.

In summary, this study highlights CFD modeling as a versatile tool for evaluating and optimising ventilation systems, offering valuable insights into the mechanism of managing the air quality in complex real-world indoor environments with elevated radon levels.

How to cite: Altendorf, D., Wienkenjohann, H., Berger, F., Dehnert, J., Duzynski, M., Grünewald, H., Naumov, D., Trabitzsch, R., and Weiß, H.: Cross-Ventilation Strategies for Efficient Indoor Radon Reduction: Experimental Data and CFD Simulations, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-12397, https://doi.org/10.5194/egusphere-egu24-12397, 2024.