Visualizing face mask data.
How good are common materials?
How good are common materials?
The primary function of any mask is to filter particles out of the air that passes through the mask, which is relevant to preventing the spread of the COVID-19 and other respiratory diseases. Filtration occurs as a result of several mechanisms, including impaction, interception, diffusion, and electrostatic attraction.
Impaction tends to dominate for larger particles, while diffusion is most significant for smaller particles. Electrostatic charges in the mask, as are typically present in N95-compliant masks, tend to enhance particle filtration but also tend to hold up rather poorly when the mask is sanitized. For example, washing most N95-compliant masks with soap and water will significantly reduce their filtration properties.
This web app seeks to visualize the overall filtration measured for a range of common materials, using data from Rogak et al. (2021). In accordance with that paper, we consider relatively large particles in the typical aerosol range, roughly from half to several micron. This compliments other studies that consider smaller particles. Limited information is also provided in terms of sanitization treatments (e.g., laundering) and their effect on material properties.
Before continuing, we make several general notes:
This is a key question!
We note that the focus of this data is on the materials themselves. As such, these curves do not consider leakage around the mask. This is another very important feature in constructing an effective masks but requires different kinds of tests that are wearer-specific. There are studies by other aerosol researchers and health professionals considering this aspect of mask construction.
Konda et al. (2020), for example, present the difference in filtration between candidate materials with and without leakage. This research found a gap representing only 0.5-2% of the surface area reduced the performance of an N95-compliant mask from 99% to less than 15% filtration. It is worth noting that those meausurements correspond to where a majority of the particles are near the lower end of the particle size range considered here. The largest human-generated particles (that is, the particles you can see, which are above the size range even considered here) will travel ballistically (that is, more of less on straight trajectories), such that leakage should trend downwards, even if some of the particles from the deflected spray will still escape the masks in practice.
Regardless, the mask will function better if one reduces the impact of gaps. We recommend maximizing the surface area of air exchange to improve effective ventilation. A cup-shape or duck bill design may be preferred. Other solutions to reduce gaps include external braces, sponge nose pads, or reinforced nose wires.
Overall, any mask is still better than no mask as (1) the remaining filtration efficiency (~15% for the N95-compliant masks in the Konda et al. (2020) study) will filter some of the smaller particles and (2) the mask should significantly reduce the fraction of larger droplets released into the air.
We used a flow rate of 1 LPM, yielding a face velocity of 4.9 cm/s, below that used in the NIOSH N95 standard (8-9 cm/s).
There are multiple kinds of particle diameters that aerosol scientists use when making these kinds of measurements, which may differ a bit from the physical diameter.
We phrase things in terms of the aerodynamic diameter, which is related to the drag force on the particles. This is more relevant for the impaction and interception mechanisms, which are dominant for the size range considered here.
We occasionally characterize the materials by their physical colour. This is done as there is often limited information available about the specific material properties (e.g., thread count). In this regard, the colour is simply used to denote different materials within a similar material class. Accordingly, this data should be interpretted as indicating the potential variability of filtration and pressure drop that could be associated with a given type of material.
A pertinent example is the knit cottons, which have variable quality despite being a similar material to the consumer.
Simply put, these are codes we assign to each material, composed of characters identifying a material, its structure, number of layers used during measurement, and sanitization treatment applied (e.g., laundered), if any. While we provide these codes for reference back to the associated paper, in most instances the reader can ignore these codes.
For those more interested:
1. The first letter or pair of letters generally denotes the material structure, using W for woven materials, K for knit materials, CP for cut pile materials (e.g., corduroy), and nW for non-woven materials. Composite masks, such as the N95-compliant materials tested, have different codes (e.g., ASTM for surgical masks that adhere to the ASTM standard). The different material structures can be added or removed from the plot using the checkboxes in the controls above the first plot.
2. The second component is a number used to identify the different materials within a given material structure. As the number is only used to identify the material, it does not contain any information about the material makeup or structure.
3. Next, some codes append x* to denote if multiple layers were used during the test. For example K4x2 is four layers of the K4 material (Double-knit jersey, yellow). If the x* component is missing, a single layer of the material was used.
4. Finally, some codes append a space followed by a code denoting if a sanitization treatment was applied to the material. Examples include, HS for heat treatment, IPA for isopropyl alcohol treatments, WD for laundering, and SW for washing with soap and water. If no such code is appended, the material is in its original condition. If santization was repeatedly applied, this latter part of the code will also be appended with x* (e.g., WDx10 denotes materials laundered ten times).
For example, a code denoting a knit material that has been laundered multiple times is K4x4 WDx4. A list of the codes is included in the table at the bottom of this page.