Design and validation of a wind tunnel for viral aerosol filtration testing

Abstract

Face masks were heavily used during the SARS-CoV-2 pandemic to reduce the transmission of the virus by aerosols. These facial barriers are tested in laboratory against particles and bacteria, but their efficiency is not tested for viruses. This study presents a wind tunnel designed to evaluate the filtration efficiency of different material use in face masks against particulates, total viral genomes and assess filtration impact on viral infectivity. The test bench was validated theoretically by mathematical modeling and experimentally by testing the performance of standardized masks against particles and MS2 viruses (Emesvirus zinderi). Results demonstrate that the data obtained for particle filtration was reliable and that filtration efficiency against viruses can be measured with the device.

Copyright © 2024 American Association for Aerosol Research

Editor:

• Andrea Ferro

Authors’ contributions

Vincent Brochu contributed to the redaction (leader), the experimental testing, and data analyses. Gabriel St-Onge contributed to the numerical modeling. Nathalie Turgeon contributed to the supervision and the revisions. Marc Veillette contributed to the supervision and the revisions. Mathieu Olivier contributed to the redaction, the funding, the numerical modeling, and the revisions. Caroline Duchaine contributed to the funding, the supervision, the revisions, and the research project direction.

Competing interests

We declare no competing interests.

Disclosure statement

No potential conflict of interest was reported by the author(s).

Additional information

Funding

Institut de Recherche Robert-Sauvé en Santé et en Sécurité du Travail; National Research Council Canada; This project was funded by the National Sciences and Engineering Research Council of Canada (NSERC-RGPIN-2019-04191 (CD) and NSERC-RGPIN-2019-04489 (MO)) and by the Institut de Recherche Robert-Sauvé en santé et sécurité du travail du Québec (IRSST-2017-0004 (CD)). Computational resources were provided by the Digital Research Alliance of Canada (RRG #4513 (MO)). We thank Matthieu Girard, Daniel Verreault, Cédric Morin, and Dan Zegan for the design and construction of the test bench.