Effects of mask-wearing on the inhalability and deposition of airborne SARS-CoV-2 aerosols in human upper airway

Abstract

Even though face masks are well accepted as tools useful in reducing COVID-19 transmissions, their effectiveness in reducing viral loads in the respiratory tract is unclear. Wearing a mask will significantly alter the airflow and particle dynamics near the face, which can change the inhalability of ambient particles. The objective of this study is to investigate the effects of wearing a surgical mask on inspiratory airflow and dosimetry of airborne, virus-laden aerosols on the face and in the respiratory tract. A computational model was developed that comprised a pleated surgical mask, a face model, and an image-based upper airway geometry. The viral load in the nose was particularly examined with and without a mask. Results show that when breathing without a mask, air enters the mouth and nose through specific paths. When wearing a mask, however, air enters the mouth and nose through the entire surface of the mask at lower speeds, which favors the inhalation of ambient aerosols into the nose. With a 65% filtration efficiency (FE) typical for a three-layer surgical mask, wearing a mask reduces dosimetry for all micrometer particles except those of size 1 µm-3 µm, for which equivalent dosimetry with and without a mask in the upper airway was predicted. Wearing a mask reduces particle penetration into the lungs, regardless of the FE of the mask. The results also show that mask-wearing protects the upper airway (particularly the nose and larynx) best from particles larger than 10 µm while protecting the lungs best from particles smaller than 10 µm.

FIG. 1.

Mask–face-airway model: (a) model components: upper airway (nose, mouth, pharynx, and larynx), face with nostrils and mouth opening, and mask with inner and out layers; (b) the combined model with the upper airway being connected to the face and the mask fitted on the face with no leakage; and (c) the computational domain with spherical ambient airspace and a spherical aerosol profile. There are three fluid bodies: ambient air (fluid body 1), mask (fluid body 2 as porous media), and airway (fluid body 3). The face was divided into (1) face exposed and (2) face covered [yellow color in (b)], delineated by the mask–face interface (seal) and the nasal strip.

FIG. 2.

Computational mesh: (a) multi-scale, multi-domain mesh, with coarse mesh in the ambient airspace, fine mesh on the face and mask, and ultrafine mesh in the airway and (b) body-fitted mesh was used in the near-wall region of the airway, with four layers of prismatic cells and a height of 0.03 mm in the first layer, as displayed in the oropharyngeal carina and the glottis.

FIG. 3.

Comparison of inspiratory airflows at 30 l/min between two scenarios, (a) with a mask and (b) without a mask in terms of the mid-plane pressure contour (first panel), velocity contours and streamlines at large (second panel) and small (third panel) scales, vector field (fourth panel), and velocity of fluid particles passing the mask (fifth panel). Wearing a mask significantly distorted the airflow and pressure distributions.

FIG. 4.

Instantaneous snapshots of particle positions in M0 at different times after their release during (a) the first cycle and (b) the second cycle.

FIG. 5.

Particle deposition pattern and intensity on the mask at 30 l/min for particles of (a) 1 µm, (b) 5 µm, (c) 10 µm, and (d) 20 µm, with a top view, a side view, and a visualization of particle localizations in terms of the DEF (deposition enhancement factor).

FIG. 6.

Comparison of the particle deposition pattern and intensity on the face (a) with a mask and without a mask at an inhalation flow rate of 30 l/min for particles of 1 µm, 5 µm, 10 µm, and 20 µm. The deposition intensities were visualized using the DEF (deposition enhancement factor).

FIG. 7.

Comparison of the fate of inhaled aerosols at 30 l/min with (red lines) and without (black line) wearing a mask in terms of (a) face deposition, (b) airway deposition, and (c) penetration rate into the lungs. When wearing a mask, two scenarios were considered, with the filtration efficiency being 0% in the first scenario (i.e., before correction, hollow delta, representing the worst limit) and 65% in the second scenario (i.e., after correction, solid delta, representative of a typical three-layer surgical mask). A pass rate of 35% was applied for all particles that came in contact with the outer layer of the mask. For instance, the number of particles depositing on the face was counted as that of particles landing on the uncovered face plus the 35% of particles landing on the face covered by the mask.

FIG. 8.

Regional deposition fractions (DFs) at 30 l/min in different sections of the upper airway (i.e., the nose, mouth, pharynx, and larynx): (a) DFs without a mask vs DFs with a mask before correction (with 0% mask filtration efficiency), (b) DFs without a mask vs DFs with a mask after correction (with 65% mask filtration efficiency), (c) the nose DF without a mask vs with a mask after correction, (d) the larynx DF without a mask vs with a mask after correction, and (e) surface deposition in the upper airway for particles of sizes 1 µm, 5 µm, 10 µm, and 20 µm.

FIG. 9.

Effects of the flow rate on the fate of inhaled aerosols with (solid lines) and without (dashed lines) wearing a mask in terms of (a) face deposition, (b) airway deposition, and (c) penetration rate into the lungs. The upper panels show the scenario with 0% mask filtration (i.e., before correction), and the lower panel shows the modified rates with a mask filtration efficiency of 65% (i.e., after correction).

FIG. 10.

Effects of the mask resistance matrix on the fate of inhaled aerosols at 30 l in comparison to the scenario without a mask: (a) face deposition, (b) airway deposition, and (c) penetration rate into the lungs. The upper panels show the scenario with 0% mask filtration (i.e., before correction), and the lower panel shows that with 65% mask filtration (i.e., after correction).

FIG. 11.

Deposition variation on the mask under different inhalation flow rates for (a) 10-µm particles, (b) 20-µm particles, and (c) with different mask resistances (i.e., filter matrix in three directions: 1-1-1, 6-1-6, 10-1-10, and 10-10-10) for 5-µm particles at 30 l/min.

FIG. 12.

Deposition distribution in different sections of the upper airway (the nose, mouth, pharynx, and larynx) under varying breathing conditions: (a) 15 l/min, (b) 45 l/min, and (c) 60 l/min. The left panels compare the DFs without a mask vs DFs with a mask before correction (with 0% mask filtration efficiency), while the right panels compare the DFs without a mask vs DFs with a mask after correction (with 65% mask filtration efficiency). Zoomed inserts for particles of 1 µm–5 µm are shown in the three right panels.

FIG. 13.

Comparison of the regional airway dosimetry without vs with a mask (after correction) in the (a) nose and (b) larynx at different inhalation flow rates (15 l/min, 45 l/min, 60 l/min).

FIG. 14.

Comparison of the regional airway dosimetry among different mask resistance matrices in the (a) nose and (b) larynx for particles of 1 µm, 5 µm, 10 µm, and 20 µm.