News4.2.2022

Research on the risks of airborne viral transmission in indoor spaces was published in the scientific journal Physics of Fluids

Researchers at the Finnish Meteorological Institute studied the principal mechanisms of airborne transmission by means of supercomputer modelling. The researchers used experimental measurements to validate the accuracy of their modelling results.
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The modelling work and its validation have now been thoroughly documented, peer-reviewed, and published in the prestigious scientific journal Physics of Fluids.

The study advanced our understanding of the working mechanisms behind measures that can help reduce the likelihood of viral transmission indoors. The research underlined the importance of enhancing the mixing of indoor air, fully utilizing the existing ventilation capacity and potentially augmenting it with effective air purifiers. The significance of limiting the exposure time to the airborne virus is also demonstrated.

The study exposed significant inadequacies in the simplified methods that are currently used in assessing infection risks and their reduction strategies indoors. Furthermore, the reported high-accuracy modelling work provides evidence that the methods that improve air hygiene are more effective than previously thought.

The study has been conducted in the multidisciplinary TUPA and E3 projects which are funded by Business Finland. The work has also received special funding for COVID-19 research from the Academy of Finland.

Further information:

Mikko Auvinen, Senior Scientist, Finnish Meteorological Institute, mikko.auvinen@fmi.fi, tel. +358 50 475 0157

Antti Hellsten, Senior Scientist, Finnish Meteorological Institute, antti.hellsten@fmi.fi, tel. +358 50 409 0477

Scientific article is available on Physics of Fluids.

Mikko Auvinen, Joel Kuula, Tiia Grönholm, Matthias Sühring, and Antti Hellsten, "High-resolution large-eddy simulation of indoor turbulence and its effect on airborne transmission of respiratory pathogens—Model validation and infection probability analysis", Physics of Fluids 34, 015124 (2022) https://doi.org/10.1063/5.0076495

Read the AIP Scilight article about the research: Using computer modeling to test virus mitigation strategies