The critical importance of mask seals on respirator performance: An analytical and simulation approach

PLoS One. 2021 Feb 17;16(2):e0246720. doi: 10.1371/journal.pone.0246720. eCollection 2021.

Abstract

Filtering facepiece respirators (FFRs) and medical masks are widely used to reduce the inhalation exposure of airborne particulates and biohazardous aerosols. Their protective capacity largely depends on the fraction of these that are filtered from the incoming air volume. While the performance and physics of different filter materials have been the topic of intensive study, less well understood are the effects of mask sealing. To address this, we introduce an approach to calculate the influence of face-seal leakage on filtration ratio and fit factor based on an analytical model and a finite element method (FEM) model, both of which take into account time-dependent human respiration velocities. Using these, we calculate the filtration ratio and fit factor for a range of ventilation resistance values relevant to filter materials, 500-2500 Pa∙s∙m-1, where the filtration ratio and fit factor are calculated as a function of the mask gap dimensions, with good agreement between analytical and numerical models. The results show that the filtration ratio and fit factor are decrease markedly with even small increases in gap area. We also calculate particle filtration rates for N95 FFRs with various ventilation resistances and two commercial FFRs exemplars. Taken together, this work underscores the critical importance of forming a tight seal around the face as a factor in mask performance, where our straightforward analytical model can be readily applied to obtain estimates of mask performance.

MeSH terms

  • Aerosols / analysis
  • Air Filters
  • Equipment Design
  • Filtration / methods*
  • Finite Element Analysis
  • Humans
  • Inhalation Exposure / analysis
  • Masks / statistics & numerical data
  • Masks / trends
  • Materials Testing / methods
  • Models, Theoretical
  • N95 Respirators / statistics & numerical data
  • Particle Size
  • Respiration
  • Respiratory Protective Devices / standards
  • Respiratory Protective Devices / statistics & numerical data*
  • Ventilators, Mechanical / statistics & numerical data
  • Ventilators, Mechanical / trends

Substances

  • Aerosols

Grants and funding

The author(s) received no specific funding for this work.