Next Article in Journal
Investigation of the Flow Characteristics for Cylinder-in-Ball Valve Due to a Change in the Opening Rate
Previous Article in Journal
A Novel Method for Unexpected Obstacle Detection in the Traffic Environment Based on Computer Vision
 
 
Search for Articles:
Title / Keyword
Author / Affiliation / Email
Journal
Article Type
 
 
Advanced Search
 
Section
Special Issue
Volume
Issue
Number
Page
 
Journals
Applied Sciences
Volume 12
Issue 18
10.3390/app12188936
applsci-logo
Submit to this Journal Review for this Journal Propose a Special Issue
► Article Menu

Article Menu

share Share announcement Help format_quote Cite question_answer Discuss in SciProfiles thumb_up
...
Endorse textsms
...
Comment
first_page
settings
Order Article Reprints
Font Type:
Arial Georgia Verdana
Font Size:
Aa Aa Aa
Line Spacing:
Column Width:
Background:
Article

Performance Comparison among KN95-Certified Face Masks by Classical Techniques and Innovative Test

by
Stefano Alberti
1,
Antonio Comite
1,
Marcello Pagliero
1,
Emanuele Magi
1,*,
Giulia Codda
2,
Dimitri Sossai
3,
Valentina Caratto
1 and
Maurizio Ferretti
1
1
Department of Chemistry and Industrial Chemistry, University of Genoa, Via Dodecaneso 31, 16146 Genoa, Italy
2
Department of Surgical Sciences and Integrated Diagnostics (DISC), University of Genoa, Viale Benedetto XV 6, 16132 Genoa, Italy
3
Department of Prevention and Protection Health Care Workers IRCCS Ospedale Policlinico San Martino, Largo Rosanna Benzi 10, 16132 Genoa, Italy
*
Author to whom correspondence should be addressed.
Appl. Sci. 2022, 12(18), 8936; https://doi.org/10.3390/app12188936
Submission received: 27 July 2022 / Revised: 31 August 2022 / Accepted: 2 September 2022 / Published: 6 September 2022
(This article belongs to the Section Chemical and Molecular Sciences)
Browse Figures
Review Reports Versions Notes

Abstract

:

Featured Application

A potential application of the methodologies employed within the present work may be related to an easier and cheaper characterization of new materials developed for filtering purposes (specifically concerning the development of face masks for health issues). The possibility to employ a fast characterization technique as an official process to determine the filtering efficiency would both improve the solidity of the characterization method as well as lighten the bureaucratic burden which likely restricts the materials’ supply in shortage periods due to the long validation tests required for their trade.

Abstract

During the pandemic, the provision of Personal Protective Equipment (PPE) (e.g., face masks) to specialized personnel and general population represented a critical point to prevent virus spread; in addition, a huge variety of new manufacturers and products entered the market, widening the time required to test and validate the equipment’s performances according to the current regulations. In this study, we employ a simple method recently developed in our laboratory, to discriminate the filtering capability of a set of KN95-certified face masks from different producers. The method is based on a methylene blue (MB) solution which is sprayed towards a pneumatic lung simulator, connected to a dummy head dressed in different types of masks. The amounts of MB droplets passing through the tested devices are collected by a cotton pad and analyzed through UV-Vis Diffuse Reflectance. In the framework of interdisciplinary collaborations between the University and the Hospital, additional characterization techniques were performed including light optical and scanning electron microscopy morphological characterization, pressure decay, and bacterial filtration efficiency (BFE). All masks were compared to a reference one, considered the gold standard for filtering performances.

1. Introduction

Since December 2019, the world had to face a complicated threat due to the rise and spread from country to country of the coronavirus disease (COVID-19), which negatively affected people in all age ranges [1]. SARS-CoV-2 virus unavoidably crossed countries’ boundaries and has become a global pandemic following the modern travel routes, affecting international trade and movements in addition to personal health, lifestyle, and social behavior. [2,3]. Scientific and medical research made an unprecedented effort to understand and prevent the high mortality associated with the disease from the very beginning of the emergency; indeed, it was found that the virus transmission was mainly due to the emission of saliva droplets and water aerosol during sneezing and coughing events in infected people [4,5,6]. Nonetheless, also normal speech and breathing yield many particles serving as vehicles for respiratory pathogen transmission. Smaller particles (with the cut-off diameter set at 5 μm between droplets and aerosol) persist in the air for longer periods, are free to travel throughout the air carrying the viral content meters away, and have a larger probability of penetrating further into the respiratory tract [7,8,9,10]. It must be said that the understanding of relative infectiousness between smaller or larger particles is still limited [3,11,12,13]. In addition, some recent studies have also proven that the environmental particulate matter (PM) concentration is associated with the diffusion dynamics and the quick global spread of COVID-19 [14]. Aerosols from infected persons may therefore pose an inhalation threat even at considerable distances, therefore, all possible precautions against airborne transmission in indoor scenarios should be taken.
Probably the easiest and fastest strategy for preventing and fighting the spread of COVID-19 is the use of facial masks, especially in closed environments or when the density of people is high. The expression “face mask” usually indicates a wide range of personal protective equipment (PPE) with the central function of reducing the transmission of particles or droplets by removing suspended particles from the airstream entering or exiting the wearer’s respiratory system [15]. The most common application is to provide both protection to the wearer and to nearby persons from the wearer (patients with COVID-19 may be asymptomatic but still contagious). Facial masks reduce the number of disease-carrying particulates that infected people exhale but also play a significant role in preventing PM from entering the human respiratory system [16]. Recent studies suggest that wearing face masks blunts the growth of the epidemic curve [17,18], such that some experts claim that universal mask use in public (95% mask use) could be enough to amend the worst effects of epidemic reappearances in many states [19]. Wearing a face mask has become the new normal, many public service providers ask clients to wear masks for general services. Nowadays, specialized terms, such as FFP2, FFP3, N95, KN95, etc., have become part of the common language and have had a positive effect in the field of health and safety by increasing the culture of prevention [20].
The unprecedented extent of the COVID-19 outbreak paved the way for many concurrent problems, one of which is the lack of PPE. The global shortage affected not only the normal population (essential service companies, cleaners, workers in the food supply chain, security, transport, etc.) but also all the medical staff involved in the management of the emergency (the number of clinicians infected by SARS-CoV-2 is estimated to be around 15–20% of the total number of cases in several countries) [21,22]. The WHO itself estimates that approximately 89 million masks are required each month to respond to the virus [20] (assessed to be 3.4 billion masks for the whole duration of the pandemic so far [23]), and this highlighted that the demand for PPE dramatically surpassed the global production capacity of manufacturers, especially during the beginning of the pandemic.
In this frame, the use of facial masks and respirators increased in all countries but not all the masks used could be considered protective equipment. In general, high costs together with the low availability brought most people to direct towards cheaper and more accessible alternatives such as surgical masks and homemade ones (tissue, cotton, dusting cloth) but the majority of these homemade designs have not been tested yet, thus it is not easy to make any statement about their efficacy [17,24,25,26]. To face this unmet demand, a dramatic increase in PPE mass production capacity was established as well as new manufacturing, nevertheless the lack of certification on masks’ performances did not mitigate this issue [27].
Still, determining mask efficacy is a complex topic, made even more complicated because the infection pathways of SARS-CoV-2 are not yet thoroughly understood, and many factors, such as correct fit and usage of masks, and environmental variables further influence this issue [17].
Face masks must balance two main features: efficiency and breathability. Regarding the efficiency of the face masks, there are two main considerations: the performance of the material at filtering and the fitting of the design to the wearer’s face. Leakage must be assessed on an individual-by-individual basis while filtration efficacy can be measured using well-defined test methods. Filtration is achieved by forcing the air to pass through a layer that can retain the target particles or droplets. The efficiency depends on the type and the strength of the interaction between the mask’s materials and the particles to be retained in it (mechanical, electrostatic, chemical, biochemical, etc.) and on the factors that can enhance the possibility of this interaction. These factors depend on intrinsic pore properties such as the porosity, the pore size, the pore tortuosity, the internal surface area, and on other external factors such as the thickness of the membrane and the use of several layers. They also depend on the particles to be retained: size, shape, state (solid or fluid), concentration, electrostatic charge, etc. On the other hand, breathability can be defined as the degree to which a fabric permits air and water vapor to pass through it, proportionally to the ease with which an individual can normally breathe without a feeling of asphyxia. In some aspects, filtration efficiency and breathability can be the opposite [28]. Particle removal efficiency is mainly dependent on particle size and velocity, and the removal mechanism is related to impaction, diffusion, settling, and electrostatic attraction. Breathing resistance is associated with a pressure drop as the air passes through the mask, and can be affected by air velocity, particle loading, particle type (hygroscopic or non-hygroscopic), and relative humidity (RH) [16].
The characterization of mask efficacy represents a key point, as it brings the necessary knowledge to address different types of face masks to different types of risks and professions. Respirators, medical masks, and barrier face coverings all filter airborne particles using similar physical principles. However, they are tested for certification using a variety of standardized test methods, creating challenges for the comparison of differently certified products [15]. Disposable respirators are subjected to various regulatory standards all around the world, defining their physical properties and performance characteristics. In Europe, the European Committee for Standardization fixed the standards for respirators (type 1, 2, and 3, defined as FFP1, FFP2, and FFP3) with the EN 149-2001 regulation; in the US, the NIOSH defined with the 42CFR84 regulation the N95 and N99 standards; while in China, the GB2626-2006 regulation defined the KN95 standard. Properties and characteristics involve filter performance, test agent, flow rate, total inward leakage, inhalation resistance (max pressure drop) and exhalation resistance, and CO2 clearance requirement [29,30]. In addition, certified standards were developed to fit people with facial features common in a specific country or region. As a result, some individuals with different facial features may not be able to achieve a satisfactory fit and this should be considered when selecting and using a respirator approved by other countries and region standards.
In case of an emergency, such as a sudden manufacturing response, new, cheap, fast, and efficient tests that can give information on filtering performances are needed [28].
The main object of the present study is to apply a newly developed method [31], to evaluate the filtering efficacy of several disposable respirators, KN95-certified, available on the market during the first period of the pandemic. The method takes advantage of a fine nebulization of a methylene blue aqueous solution towards a head mannequin wearing a respirator. Within the developed technique, we preventively focused on the inhaled fraction which is the ability of masks to protect the individual from an unmasked subject. This procedure allowed us to obtain preliminary data on the filtration efficiency of each tested mask. Successively, results were compared with general physical–chemical characterization techniques such as scanning electron microscopy (SEM), light optical microscopy (LOM), contact angle measurements, bacterial filtration efficiency (BFE), and pressure decay.

2. Materials and Methods

2.1. Masks

Nine different face mask types available on the market during spring 2020 were considered for the present study (Table 1); all masks were KN95-certified, except for sample 0 (3M brand), which was FFP2-certified and was considered as the golden standard.
A picture of each mask sample is reported in Figure 1. All the examined masks belong to the flat-fold type and have a narrow modellable tab which can improve the quality of the adhesion of the mask over the nose. The mask 0 and 1 are horizontally folded while all the others are vertically folded.

2.2. Novel Methylene Blue Test Method

As reported in our previous work [31], the experimental setup of the new method developed for the evaluation of droplets and aerosol inhaled fraction can be described as follows: the emitter was simulated using a Hudson Micromist (Teleflex, Morrisville, NC, USA) small volume jet nebulizer operating at 7 L/m as driving flow. The nebulizer generates a distribution of nebulized drops with a median size of 5 µm and an asymmetric distribution [32], thus covering the range of both airborne and droplet transmission models. To identify the degree of filtering efficacy, an aqueous solution (deionized water by system ARIOSO Water Purification System, Human Corporation, Seoul, Korea) of 3.44 g/L of methylene blue (Merck, Darmstadt, Germany, 95%) was employed to be nebulized. The receiver was simulated using a pneumatic lung simulator (Dimar, Mirandola, Italy) connected to a Styrofoam head mannequin (acting the part of an exposed individual) protected with the different investigated masks. We simulated a normal breathing pattern with 550 mL tidal volume per breath and a respiratory rate of 14 breaths per min. The emitter was placed in front of the receiver at a 40 cm distance; between the receiver and the lung simulator, a custom-made filter with disposable cotton pads [33], was placed to intercept the nebulized methylene blue. The nebulizer was operated for 30 min loaded with 12 mL of methylene blue solution. Thanks to this arrangement, it is intrinsically possible to take into consideration how each mask fits the head mannequin according to its shape. Measurements were replicated on three different samples for each mask type.
The amount of methylene blue deposited on each cotton pad behind the facial mask was analyzed through UV-Vis spectrophotometry (Lambda 35, Perkin Elmer, Waltham, MA, USA), with the aid of an integrating sphere. The analysis was operated at a wavelength of 664 nm, corresponding to the maximum absorbance of MB [34], collecting diffuse reflectance values (R%). The development of the method started with the calibration of the instrument: a blank cotton pad (no MB nebulization) was considered as a 100 R% reference, equivalent to a 0% inhaled fraction. A saturated cotton pad (MB nebulization performed at 0 cm without a face mask) was instead considered as 0 R% reference, also corresponding to 100% inhaled fraction. The resulting filtering efficiency of all investigated masks was expressed as a percentage inhaled fraction: this was evaluated considering the different R% values obtained with the different samples and compared with the gold standard’s R% value. We assessed the minimum amount of detectable inhaled fraction (i.e., sensitivity) in a calibration experiment in which nebulization time was decreased in 1 s steps: the minimum nebulization time required to detect an R% signal was 22 s, which corresponds to 1.22% of the total nebulization time used in our current experimental runs (1800 s). We, therefore, assumed a sensitivity of 1.22%; when the measured inhaled fraction was below this threshold, we assumed an inhaled fraction of 1.22%.

2.3. Morphological Study

The masks investigated in this work using the University facilities were made of a multilayer structure, consisting of several layers of nonwoven tissues laid on top of each other. All the samples were made up of three layers except for samples 3, 4, and 5 consisting of four layers.
To verify the morphological features, a selected set of masks was chosen among our samples to be subjected to microscopy and BFE characterization. The selection was based on the outcomes of the MB test’s, focusing on samples with decreasing diffuse reflectance results, from the best (samples 1, 4) to an intermediate (sample 9) and the worst (sample 6). The selected set of samples was subjected to the microscope characterization techniques: a digital optical microscope (DinoLite Premiere, Dinolite, Almere, The Netherlands) was used to investigate the morphology of the external and intermediate layers, both on the face side and the external side of the mask.
The structure of the intermediate layers enclosed in the face masks was better studied by means of electron microscopy. The internal layers were observed using an FE-SEM (Supra 40 VP, Carl Zeiss, Oberkochen, Germany) at low magnifications. After being isolated, the intermediate layer was mounted on a stub using a conductive double-sided tape and then covered with a carbon nanolayer using a high vacuum evaporator (Polaron 6700, Bio-Rad, Hercules, CA, USA).
A digital tensiometer (Attension Theta, Biolin Scientific, Gothenburg, Sweden) was employed to measure the hydrophobicity of the external side of each mask. A small sample was cut, and the external surface was separated from the other layers and stuck on a flat glass. For each sample, 3 μL water drops were deposited in different spots on the surface of the mask. The instrument filmed the drop for 10 s at 15 fps which were subsequently analyzed.
The air permeability was assessed following a standard procedure developed for face masks UNI EN 14683:2019. A 4.9 cm2 round sample was mounted in a cell and equipped with a differential manometer and connected to a vacuum membrane pump. The airflow rate was set at 8 L/min and the transmembrane pressure drop was registered, according to the standard procedure.

2.4. Bacterial Filtration Efficiency

The Bacterial Filtration Efficiency (BFE) was performed according to the standard procedure developed for face masks UNI EN 14683:2019. Briefly, a specimen of the mask material is clamped between a 6-stage Andersen cascade impactor (IMP-6BIO XEarPro Srl, Cogliate, Italy) and an aerosol chamber. An aerosol of Staphylococcus aureus ATCC 6538 is introduced into the aerosol chamber and passed through the mask material and the impactor under vacuum. The bacterial filtration efficiency (BFE) of the mask is given by the number of colony-forming units (CFU) passing through the medical face mask material expressed as a percentage of the number of CFU present in the aerosol test. BFE test was also performed on a selected set of samples.

3. Results and Discussion

3.1. Percentage Inhaled Fraction and Breathability

Table 2 reports the experimental outcomes obtained during the present investigation for all tested samples by means of our newly developed MB method and the breathability test.
The percentage inhaled fraction is calculated as the difference between the mean R% values of investigated samples and the R% value of the golden standard. A bigger inhaled fraction value corresponds to a higher amount of MB droplets passing through the face mask during the 30 min MB nebulization test and reaching the cotton pad (mimicking the respiratory system in an individual). As general criterion, an inhaled fraction smaller than 10% can be considered as a positive result in terms of both MB droplet filtering capacity and an intrinsically good fit with the head mannequin for the duration of the experiment.
It is interesting to see how all tested masks have reached different filtration outcomes according to the MB method, thus showing differences despite being all KN95-certified. These results could indicate two possible scenarios: the KN95 certification is not able to discriminate the diffusion of such small droplets passing through the mask, thus potentially reaching the wearer’s respiratory system; otherwise, tested masks could be labeled but not validly certified. This is obviously a preliminary consideration, and further systematic tests should be performed.
For what concerns the masks’ breathability, the test consists in the pressure drop measurement between the internal and the external side of each mask, following the UNI EN 14683:2019 standard procedure; results are reported in Table 2. As the pressure drop increases, the air permeability lowers, making respiration more difficult [35]. The pressure drop per unit area (ΔP/A) ranged between 43 and 86 Pa/cm2, and the latter represents a quite high value which implies difficult breathability in the considered respirator. Sample 6 appeared to induce a higher pressure drop compared to the other masks together with sample 7, which reaches a comparable pressure drop with sample 6. Such a result could be related to the structure of the internal layer of this mask. As shown in Figure 2, the central part of the sample 6 was composed of a series of short, interconnected fibers that generated a denser film, compared to the other samples.

3.2. Morphology

The main characteristics of the face masks as well as the water contact angle measured on the external layer are summarized in Table 3.
Face masks should own a certain level of hydrophobicity, to avoid the wetting of the layers that could decrease the filtration efficiency after prolonged exposure [36,37], and transfer the aerosol to the face side of the mask.
All the tested masks showed a great hydrophobicity, confirmed by contact angles that ranged between 123° and 141°. Moreover, when leaving the water drop on the nonwoven sample for 10 min, no absorption was observed, confirming the adequate wetting resistance of the external layer of all the mask samples. The ability of the outer material not to be wet in a short time is important to avoid that the contagious droplet is then transferred to the inner layers of the mask up to the face.
Regarding the external mask layer, it is a spunbonded nonwoven film, which has the main objective of maintaining a smooth surface and stopping the largest droplets from entering inside the mask’s porous structure.
As mentioned in “Materials and Methods”, on the basis of experimental results discussed above, a select set of masks (i.e., samples 0, 1, 4, 6, 9) was chosen to be subjected to microscopy and BFE characterization.
Figure 2 shows the nonwoven tissue structure of the four chosen samples compared with the 3M mask (sample 0), considered as the gold standard for our investigation. The fiber diameter of this external layer is about 27 µm for sample 1 and approximately 20 µm for samples 4, 6, and 9. The denser structure in the images corresponds to the welding points of the fiber typical of spunbonded nonwoven materials. Unlike the other masks, the structure of the external nonwoven layer of sample 0 is composed of fibers with a slightly narrower diameter (15 µm) without welding points. A similar situation is on the face side of the mask. Sample 0 external layers show a thicker, porous structure than the other ones where the openings are more clearly visible.
Figure 3 shows the FESEM images of the intermediate nonwoven layer of the selected face masks at 150× (top) and 500× (bottom) magnifications.
The low magnification FESEM images (top in Figure 3) depict the uniform fibrous structure of the internal layer. At the lowest magnification level, no evident differences in the structure could be observed among the five samples. Higher magnifications (bottom in Figure 3) allowed us to better estimate the morphology of each sample.
The samples were formed by a random distribution of fibers, characterized by different sizes and orientations typical of a melt-blowing production process. While the most external and face side spunbonded layers (Figure 2) clearly showed some large passages between the fibrous structure, the intermediate layers exhibited a denser fiber arrangement. The intermediate nonwoven layer due also to its thickness (Table 3) imposes a more tortuous path to the small droplets and it can ensure a higher level of retention of the particles than the external layer during both the exhalation and inspiration.
Face masks’ filtration is assured by the combination of five different mechanisms [38,39]: (1) direct impact on the fibers; (2) inertial, the particles with high momentum cannot follow the path through the interconnected pores and are captured by the fibers; (3) free diffusion, when the movement of the particles is governed by pure diffusion they can be intercepted by the filter material; (4) electrostatic attraction; and (5) size exclusion.
All considered tissues present pores much larger than the normal coughing droplet size (0.5–16 µm) [40]; thus, the filtration efficiency could be assured mainly by the first four aforementioned mechanisms while size exclusion contribution could be neglected. Then, the interconnected structure of the different layers guarantees both a high separation factor and minor pressure drop, maintaining high breathability.

3.3. Bacterial Filtration Efficiency

BFE tests were performed on the same set of samples subject to microscopy investigation; the experimental procedure was performed according to the UNI EN 14683:2019 standard practice.
All the tested masks showed an excellent BFE% (100% for sample 0, 1, 4, and 9 while 99.9% for sample 6), confirming a high filtration efficiency given by the multilayer structure (3 or 4 layers, indifferently) of the bacterial droplets.
It is worthy to note that the BFE standard practice involves the use of S. aureus, the size of which is in the range of 0.5–1.5 µm. This also represents the minimum size at which the carrying droplet can be reduced during the measurement. Indeed, the effective cut off (ECD D50), corresponding to the aerodynamic diameter for which 50% of the particles are stopped by the last stage of impact and 50% are allowed to pass, is 0.65 µm [41]. The comparable filtration efficiency for all four analysed samples, could be due to the deposition and nature of the fibres forming the inner layer, which was similar in all four samples. Although several studies have shown that the droplet carrying SARS-CoV-2 is not smaller in size than S. aureus [42,43], and thus the BFE can be considered an important and recognized test, it is true that this test may be insufficient to discriminate the goodness of a face mask when the droplet size is strongly reduced, whereas the MB test seems to better discriminate the ability of different masks to protect the individuals.

4. Conclusions

The results discussed above allow us to state that the newly developed MB method can be considered a feasible way to discriminate the filtering efficiency of disposable facepiece respirators. It is clear how this procedure could sensitively determine the filtering efficiency of several masks which were reported to be KN95-certified but did not behave as expected from the certification itself. As estimated, the gold standard showed the highest performance among all the investigated masks. Apart from the different certification (FFP2), the excellent filtration efficiency of this mask could be imputed to its highest thickness and its very good fit. If we take into consideration exclusively KN95-certified masks, a large variability in the outcomes of the characterizing techniques was reported in the present work. Despite the same certification, general characteristics like bacterial filtration efficiency (99.9–100%), contact angle values (130–140°), and general morphology (10–30 μm fibers), resulted to be very similar among all masks while other features like grammage and overall thickness were shown to be irrelevant in determining the mask efficiency. The only parameter which can be likely imputed to the better filtration efficiency is the intermediate layer thickness, which somehow can be correlated to the inhaled fraction obtained with the MB method; when the intermediate layer thickness is bigger, the inhaled fraction decreases. In addition, the “shape” factor, which was intrinsically considered for the use of a head mannequin (thus expecting the mask to be worn) could be another significant feature that should be critically considered in the evaluation of the respirators’ performances.
The experimental outcome suggests that in such a shortage of PPE supply, even with proper certification or registration, the quality of masks should be further explored and tested. Hundreds of production lines have been set up since January 2020; while most manufacturers had good intent, successful mask production requires complicated systems, access to a specialty melt-blown fabric and high-quality metal strips and ear loops that can support an effective facial seal.
The proposed method could be employed to better select appropriate protective equipment in hectic times as the time required for its operation is very short and a large number of different products could be investigated in few days. This study shows how new selected characterizations, usually easily available in a university structure, can support the person in charge of PPE selection to take more scientific and quality-based decisions during a concomitant breathing contagious plague with shortage of clearly reliable masks.

Author Contributions

Conceptualization, S.A., A.C., E.M. and V.C.; methodology, S.A., V.C. and M.F.; validation, S.A., A.C., M.P. and E.M.; formal analysis, S.A., M.P. and G.C.; investigation, S.A., M.P. and G.C.; resources, A.C., E.M., D.S., V.C. and M.F.; writing—original draft preparation, S.A. and M.P.; writing—review and editing, S.A., A.C., M.P., E.M., G.C., D.S., V.C. and M.F.; visualization, S.A. and M.P.; supervision, S.A. and E.M.; project administration, S.A., A.C. and E.M.; funding acquisition, A.C., E.M., and M.F. All authors have read and agreed to the published version of the manuscript.

Funding

This research received no external funding.

Institutional Review Board Statement

Not applicable.

Conflicts of Interest

The authors declare no conflict of interest.

References

  1. Ren, L.-L.; Wang, Y.-M.; Wu, Z.-Q.; Xiang, Z.-C.; Guo, L.; Xu, T.; Jiang, Y.-Z.; Xiong, Y.; Li, Y.-J.; Li, X.-W.; et al. Identification of a Novel Coronavirus Causing Severe Pneumonia in Human: A Descriptive Study. Chin. Med. J. 2020, 133, 1015–1024. [Google Scholar] [CrossRef]
  2. Kaur, G.; Sinha, R.; Tiwari, P.K.; Yadav, S.K.; Pandey, P.; Raj, R.; Vashisth, A.; Rakhra, M. Face Mask Recognition System Using CNN Model. Neurosci. Inform. 2022, 2, 100035. [Google Scholar] [CrossRef]
  3. Morawska, L.; Cao, J. Airborne Transmission of SARS-CoV-2: The World Should Face the Reality. Environ. Int. 2020, 139, 105730. [Google Scholar] [CrossRef]
  4. Zhang, W.; Du, R.-H.; Li, B.; Zheng, X.-S.; Yang, X.-L.; Hu, B.; Wang, Y.-Y.; Xiao, G.-F.; Yan, B.; Shi, Z.-L.; et al. Molecular and Serological Investigation of 2019-NCoV Infected Patients: Implication of Multiple Shedding Routes. Emerg. Microbes Infect. 2020, 9, 386–389. [Google Scholar] [CrossRef]
  5. Anfinrud, P.; Stadnytskyi, V.; Bax, C.E.; Bax, A. Visualizing Speech-Generated Oral Fluid Droplets with Laser Light Scattering. N. Engl. J. Med. 2020, 382, 2061–2063. [Google Scholar] [CrossRef]
  6. Morawska, L.; Johnson, G.R.; Ristovski, Z.D.; Hargreaves, M.; Mengersen, K.; Corbett, S.; Chao, C.Y.H.; Li, Y.; Katoshevski, D. Size Distribution and Sites of Origin of Droplets Expelled from the Human Respiratory Tract during Expiratory Activities. J. Aerosol Sci. 2009, 40, 256–269. [Google Scholar] [CrossRef]
  7. Asadi, S.; Wexler, A.S.; Cappa, C.D.; Barreda, S.; Bouvier, N.M.; Ristenpart, W.D. Aerosol Emission and Superemission during Human Speech Increase with Voice Loudness. Sci. Rep. 2019, 9, 2348. [Google Scholar] [CrossRef]
  8. Brosseau, L. COVID-19 Transmission Messages Should Hinge on Science. Available online: http://www.cidrap.umn.edu/news-perspective/2020/03/commentary-covid-19-transmission-messages-should-hinge-science (accessed on 16 March 2020).
  9. van Doremalen, N.; Bushmaker, T.; Morris, D.H.; Holbrook, M.G.; Gamble, A.; Williamson, B.N.; Tamin, A.; Harcourt, J.L.; Thornburg, N.J.; Gerber, S.I.; et al. Aerosol and Surface Stability of SARS-CoV-2 as Compared with SARS-CoV-1. N. Engl. J. Med. 2020, 382, 1564–1567. [Google Scholar] [CrossRef]
  10. Stadnytskyi, V.; Bax, C.E.; Bax, A.; Anfinrud, P. The Airborne Lifetime of Small Speech Droplets and Their Potential Importance in SARS-CoV-2 Transmission. Proc. Natl. Acad. Sci. USA 2020, 117, 11875–11877. [Google Scholar] [CrossRef]
  11. Meselson, M. Droplets and Aerosols in the Transmission of SARS-CoV-2. N. Engl. J. Med. 2020, 382, 2063. [Google Scholar] [CrossRef]
  12. Fernstrom, A.; Goldblatt, M. Aerobiology and Its Role in the Transmission of Infectious Diseases. J. Pathog. 2013, 2013, 493960. [Google Scholar] [CrossRef] [PubMed]
  13. Bourouiba, L. Turbulent Gas Clouds and Respiratory Pathogen Emissions: Potential Implications for Reducing Transmission of COVID-19. JAMA 2020, 323, 1837–1838. [Google Scholar] [CrossRef] [PubMed]
  14. Jonsirivilai, B.; Torgbo, S.; Sukyai, P. Multifunctional Filter Membrane for Face Mask Using Bacterial Cellulose for Highly Efficient Particulate Matter Removal. Cellulose 2022, 29, 6205–6218. [Google Scholar] [CrossRef] [PubMed]
  15. Corbin, J.C.; Smallwood, G.J.; Leroux, I.D.; Norooz Oliaee, J.; Liu, F.; Sipkens, T.A.; Green, R.G.; Murnaghan, N.F.; Koukoulas, T.; Lobo, P. Systematic Experimental Comparison of Particle Filtration Efficiency Test Methods for Commercial Respirators and Face Masks. Sci. Rep. 2021, 11, 21979. [Google Scholar] [CrossRef] [PubMed]
  16. Lee, H.; Kim, S.; Joo, H.; Cho, H.; Park, K. A Study on Performance and Reusability of Certified and Uncertified Face Masks. Aerosol Air Qual. Res. 2022, 22, 210370. [Google Scholar] [CrossRef]
  17. Fischer, E.P.; Fischer, M.C.; Grass, D.; Henrion, I.; Warren, W.S.; Westman, E. Low-Cost Measurement of Face Mask Efficacy for Filtering Expelled Droplets during Speech. Sci. Adv. 2020, 6, eabd3083. [Google Scholar] [CrossRef]
  18. Gandhi, M.; Rutherford, G.W. Facial Masking for Covid-19—Potential for “Variolation” as We Await a Vaccine. N. Engl. J. Med. 2020, 383, e101. [Google Scholar] [CrossRef]
  19. Palcu, J.; Schreier, M.; Janiszewski, C. Facial Mask Personalization Encourages Facial Mask Wearing in Times of COVID-19. Sci. Rep. 2022, 12, 891. [Google Scholar] [CrossRef]
  20. Rubio-Romero, J.C.; del Carmen Pardo-Ferreira, M.; Torrecilla-García, J.A.; Calero-Castro, S. Disposable Masks: Disinfection and Sterilization for Reuse, and Non-Certified Manufacturing, in the Face of Shortages during the COVID-19 Pandemic. Saf. Sci. 2020, 129, 104830. [Google Scholar] [CrossRef]
  21. Santos-Rosales, V.; López-Iglesias, C.; Sampedro-Viana, A.; Alvarez-Lorenzo, C.; Ghazanfari, S.; Magariños, B.; García-González, C.A. Supercritical CO2 Sterilization: An Effective Treatment to Reprocess FFP3 Face Masks and to Reduce Waste during COVID-19 Pandemic. Sci. Total Environ. 2022, 826, 154089. [Google Scholar] [CrossRef]
  22. Bhaskar, M.E.; Arun, S. SARS-CoV-2 Infection Among Community Health Workers in India Before and After Use of Face Shields. JAMA 2020, 324, 1348–1349. [Google Scholar] [CrossRef] [PubMed]
  23. Whyte, H.E.; Joubert, A.; Leclerc, L.; Sarry, G.; Verhoeven, P.; Le Coq, L.; Pourchez, J. Reusability of Face Masks: Influence of Washing and Comparison of Performance between Medical Face Masks and Community Face Masks. Environ. Technol. Innov. 2022, 28, 102710. [Google Scholar] [CrossRef]
  24. Zhai, Z. Facial Mask: A Necessity to Beat COVID-19. Build. Environ. 2020, 175, 106827. [Google Scholar] [CrossRef] [PubMed]
  25. Feng, S.; Shen, C.; Xia, N.; Song, W.; Fan, M.; Cowling, B.J. Rational Use of Face Masks in the COVID-19 Pandemic. Lancet Respir. Med. 2020, 8, 434–436. [Google Scholar] [CrossRef]
  26. World Health Organization. Rational Use of Personal Protective Equipment for Coronavirus Disease (COVID-19) and Considerations during Severe Shortages: Interim Guidance; WHO: Geneva, Switzerland, 2020. [Google Scholar]
  27. Shukla, S.; Khan, R.; Saxena, A.; Sekar, S. Microplastics from Face Masks: A Potential Hazard Post COVID-19 Pandemic. Chemosphere 2022, 302, 134805. [Google Scholar] [CrossRef]
  28. Gómez Álvarez-Arenas, T.E.; Fariñas, M.D.; Ginel, A. Fast and Non-Destructive Ultrasonic Test for Face Masks. Ultrasonics 2021, 117, 106556. [Google Scholar] [CrossRef]
  29. Liang, M.; Gao, L.; Cheng, C.; Zhou, Q.; Uy, J.P.; Heiner, K.; Sun, C. Efficacy of Face Mask in Preventing Respiratory Virus Transmission: A Systematic Review and Meta-Analysis. Travel Med. Infect. Dis. 2020, 36, 101751. [Google Scholar] [CrossRef]
  30. Wadhwani, C.P.K.; Rosen, P.S.; Rosen, A.S.; Wadhwani, Y.H.; Chung, K.H. A Technique to Improve the Viral Protection of a Procedure Mask in Absence of an N95 Shield Respirator. Perio-Implant Advis. 2020. Available online: https://www.perioimplantadvisory.com/periodontics/oral-medicine-anesthetics-and-oral-systemic-connection/article/14173091/in-response-to-covid19-a-technique-to-improve-the-viral-protection-of-a-dental-procedure-mask-in-absence-of-an-n95-shield-respirator (accessed on 31 March 2020).
  31. Ball, L.; Alberti, S.; Belfortini, C.; Almondo, C.; Robba, C.; Battaglini, D.; Cravero, C.; Pelosi, P.; Caratto, V.; Ferretti, M. Effects of Distancing and Pattern of Breathing on the Filtering Capability of Commercial and Custom-Made Facial Masks: An in-Vitro Study. PLoS ONE 2021, 16, e0250432. [Google Scholar] [CrossRef]
  32. Hallberg, C.J.; Lysaught, M.; Zmudka, C.E.; Kopesky, W.K.; Olson, L.E. Characterization of a Human Powered Nebulizer Compressor for Resource Poor Settings. Biomed. Eng. OnLine 2014, 13, 77. [Google Scholar] [CrossRef] [PubMed]
  33. Ball, L.; Sutherasan, Y.; Caratto, V.; Sanguineti, E.; Marsili, M.; Raimondo, P.; Ferretti, M.; Kacmarek, R.M.; Pelosi, P. Effects of Nebulizer Position, Gas Flow, and CPAP on Aerosol Bronchodilator Delivery: An In Vitro Study. Respir. Care 2016, 61, 263–268. [Google Scholar] [CrossRef] [Green Version]
  34. Alberti, S.; Caratto, V.; Peddis, D.; Belviso, C.; Ferretti, M. Synthesis and Characterization of a New Photocatalyst Based on TiO2 Nanoparticles Supported on a Magnetic Zeolite Obtained from Iron and Steel Industrial Waste. J. Alloys Compd. 2019, 797, 820–825. [Google Scholar] [CrossRef]
  35. Nguyên, N.N.; Van Loon, J.; Du Bois, E.; Verlinden, J.; Verwulgen, S.; Watts, R. Experimental Comparison of CWA 17553:2020 Community Face Coverings to Surgical Masks and Filtering Facepiece Respirators. In Advances in Safety Management and Human Performance; Arezes, P.M., Boring, R.L., Eds.; Lecture Notes in Networks and Systems; Springer International Publishing: Cham, Switzerland, 2021; Volume 262, pp. 169–177. ISBN 978-3-030-80287-5. [Google Scholar]
  36. Pavon, C.; Aldas, M.; Rayón, E.; Arrieta, M.P.; López-Martínez, J. Deposition of Gum Rosin Microspheres on Polypropylene Microfibres Used in Face Masks to Enhance Their Hydrophobic Behaviour. Environ. Technol. Innov. 2021, 24, 101812. [Google Scholar] [CrossRef]
  37. Li, Y.; Wong, T.; Chung, J.; Guo, Y.P.; Hu, J.Y.; Guan, Y.T.; Yao, L.; Song, Q.W.; Newton, E. In Vivo Protective Performance of N95 Respirator and Surgical Facemask. Am. J. Ind. Med. 2006, 49, 1056–1065. [Google Scholar] [CrossRef] [PubMed]
  38. Gopal, R.; Kaur, S.; Feng, C.Y.; Chan, C.; Ramakrishna, S.; Tabe, S.; Matsuura, T. Electrospun Nanofibrous Polysulfone Membranes as Pre-Filters: Particulate Removal. J. Membr. Sci. 2007, 289, 210–219. [Google Scholar] [CrossRef]
  39. Van Goethem, C.; Op de Beeck, D.; Ilyas, A.; Thijs, M.; Koeckelberghs, G.; Aerts, P.E.M.; Vankelecom, I.F.J. Ultra-Thin and Highly Porous PVDF-Filters Prepared via Phase Inversion for Potential Medical (COVID-19) and Industrial Use. J. Membr. Sci. 2021, 639, 119710. [Google Scholar] [CrossRef]
  40. Yang, S.; Lee, G.W.M.; Chen, C.-M.; Wu, C.-C.; Yu, K.-P. The Size and Concentration of Droplets Generated by Coughing in Human Subjects. J. Aerosol Med. 2007, 20, 484–494. [Google Scholar] [CrossRef]
  41. Lindsley, W.; Green, B.; Blachere, F.; Martin, S.; Law, B.; Jensen, P.; Schafer, M. Sampling and Characterization of Bioaerosols; National Institute for Occupational Safety and Health: Washington, DC, USA, 2017; p. BA36-64. [Google Scholar]
  42. Lee, B. Minimum Sizes of Respiratory Particles Carrying SARS-CoV-2 and the Possibility of Aerosol Generation. Int. J. Environ. Res. Public Health 2020, 17, 6960. [Google Scholar] [CrossRef]
  43. Chia, P.Y.; Coleman, K.K.; Tan, Y.K.; Ong, S.W.X.; Gum, M.; Lau, S.K.; Lim, X.F.; Lim, A.S.; Sutjipto, S.; Lee, P.H.; et al. Detection of Air and Surface Contamination by SARS-CoV-2 in Hospital Rooms of Infected Patients. Nat. Commun. 2020, 11, 2800. [Google Scholar] [CrossRef]
Applsci 12 08936 g001 550
Figure 1. Tested KN95 devices plus FFP2 golden standard mask (0); the sequential numbers are related to Table 1.
Figure 1. Tested KN95 devices plus FFP2 golden standard mask (0); the sequential numbers are related to Table 1.
Applsci 12 08936 g001
Applsci 12 08936 g002 550
Figure 2. Optical microscope images of gold standard (sample 0) and samples 1, 4, 6, and 9 external layers (A–E) and face side layers (F–L), respectively.
Figure 2. Optical microscope images of gold standard (sample 0) and samples 1, 4, 6, and 9 external layers (A–E) and face side layers (F–L), respectively.
Applsci 12 08936 g002
Applsci 12 08936 g003 550
Figure 3. FESEM images of the selective layer of the gold standard (sample 0) and the 1, 4, 6, and 9 face mask samples at 150× (A–E) and 500× (F–L) magnifications.
Figure 3. FESEM images of the selective layer of the gold standard (sample 0) and the 1, 4, 6, and 9 face mask samples at 150× (A–E) and 500× (F–L) magnifications.
Applsci 12 08936 g003
Table
Table 1. Name, sequential sample number, and certification type of each tested device.
Table 1. Name, sequential sample number, and certification type of each tested device.
SampleNameCertification
0GOLDEN STANDARD 3MFFP2 1
1KN 95 WN GUANGZHOU WEINI TECHNOLOGY DEVELOPMENT CINAKN95 2
2BYD KN95 PARTICULATE RESPIRATORKN95 2
3KN95 POWECOM CINAKN95 2
4KN 95 1981 IVAISIAN CINAKN95 2
5KN 95 (no brand)KN95 2
6KN95 BYD ELECTRONICS GB2626-2006KN95 2
7TEDA TECLANDA KN 95KN95 2
8MEDICAL MASK EN 14683:2014 KN95 SINLILAISI CINAKN95 2
9KN95 GB2626-2006 QINGHAI ZHONG DAO CINAKN95 2
1 FFP stands for Filtering Factor Protection of types 1,2 and 3, according to Europe EN 149/2001 regulations standards, as depicted in the Introduction paragraph. 2 KN95 stands for the performance standard GB2626-2006 of China.
Table
Table 2. Diffuse reflectance values measured after 30 min of MB nebulization; calculated percentage inhaled fraction, and breathability values for the set of investigated face masks.
Table 2. Diffuse reflectance values measured after 30 min of MB nebulization; calculated percentage inhaled fraction, and breathability values for the set of investigated face masks.
Samplea Diffuse Reflectance R%Inhaled Fraction (%)b ∆P/A (Pa/cm2)
099.5 ± 0.90 (ref)62
198.7 ± 1.40.854
289.2 ± 1.410.369
381.3 ± 1.518.243
493.1 ± 2.76.461
584.5 ± 3.915.051
675.6 ± 3.623.986
788.9 ± 1.010.681
878.2 ± 7.321.358
986.8 ± 1.212.763
a Standard deviation calculated on n = 3. b (8 L/min, 4.9 cm2—according to UNI EN 14683:2019).
Table
Table 3. Morphological characteristics of the face masks and water contact angle of the external layers.
Table 3. Morphological characteristics of the face masks and water contact angle of the external layers.
SampleGrammage (g/m2)Intermediate Layer Thickness (µm)Total Thickness
(mm)		Contact Angle (°)
0378304 ± 181.04130 ± 5
1180207 ± 170.57128 ± 3
2242190 ± 120.64134 ± 1
3179117 ± 110.71141 ± 2
4279181 ± 230.78127 ± 2
5220165 ± 110.63137 ± 7
6216169 ± 130.59136 ± 5
7258241 ± 210.75129 ± 3
8232320 ± 200.75123 ± 1
9195216 ± 130.57132 ± 3
Publisher’s Note: MDPI stays neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Share and Cite

MDPI and ACS Style

Alberti, S.; Comite, A.; Pagliero, M.; Magi, E.; Codda, G.; Sossai, D.; Caratto, V.; Ferretti, M. Performance Comparison among KN95-Certified Face Masks by Classical Techniques and Innovative Test. Appl. Sci. 2022, 12, 8936. https://doi.org/10.3390/app12188936

AMA Style

Alberti S, Comite A, Pagliero M, Magi E, Codda G, Sossai D, Caratto V, Ferretti M. Performance Comparison among KN95-Certified Face Masks by Classical Techniques and Innovative Test. Applied Sciences. 2022; 12(18):8936. https://doi.org/10.3390/app12188936

Chicago/Turabian Style

Alberti, Stefano, Antonio Comite, Marcello Pagliero, Emanuele Magi, Giulia Codda, Dimitri Sossai, Valentina Caratto, and Maurizio Ferretti. 2022. "Performance Comparison among KN95-Certified Face Masks by Classical Techniques and Innovative Test" Applied Sciences 12, no. 18: 8936. https://doi.org/10.3390/app12188936

APA Style

Alberti, S., Comite, A., Pagliero, M., Magi, E., Codda, G., Sossai, D., Caratto, V., & Ferretti, M. (2022). Performance Comparison among KN95-Certified Face Masks by Classical Techniques and Innovative Test. Applied Sciences, 12(18), 8936. https://doi.org/10.3390/app12188936

Note that from the first issue of 2016, this journal uses article numbers instead of page numbers. See further details here.

Article Metrics

Back to TopTop