Kenneth Neubauer

Although the public uses a wide range of face masks for the prevention of Covid-19 transmission, the most common is the 3-layer hygienic mask, which is manufactured and used globally. Since the rigorous quality standards required for certified medical masks, such as N-95 face masks, are not applicable to hygienic masks, it is important to assess the quality and safety of this mask category. Although consistent global standards do not exist for the determination of metal content in hygienic facemasks, 

 “Biocompatibility Evaluation of Breathing Gas Pathways in Healthcare Applications–Part 4: Leachables in Condensate” provides guidance for the analysis of metals in facemasks. This work describes the determination of metals in hygienic facemasks using ICP-OES, following the guidelines of 

, including sample preparation, analysis, and validation of the methodology.

The use of face masks for preventing the spread of Covid-19 is a required safety precaution in many public indoor areas across the globe. Face masks fall into two broad categories: surgical/medical and hygienic/disposable. The most common surgical/medical face mask is the N-95 respirator. Because these face masks are designed to minimize the spread of particles to protect both patients and medical staff, regulations have been established to ensure product quality and protect human health. Since regulations must be met, production cannot meet the demand of the general population, which therefore wears hygienic/disposable face masks to reduce the spread of airborne diseases. Even though these types of face masks do not have required standards that must be met in Europe and the United States, they have been recommended for limiting transmission of the Covid-19 virus and protecting people.

There are many types of hygienic face masks being used by the general public, with the most common being the three-layer disposable hygienic face mask, consisting of an innermost layer (closest to the wearer’s face), a middle layer, and an outer light blue layer, as shown in Figure 1. These types of face masks are being manufactured and worn globally.

FIGURE 1: Components of a common hygenic, disposable face mask.

As with any consumer product, it is important to validate that hygienic face masks do not pose any additional risk to their users. Two categories of analytes which must be evaluated are volatile organic compounds (VOCs) and metals. This work will discuss the determination of metals in hygienic face masks.

Globally, there are no consistent regulations or agreed-upon levels of metals in hygienic face masks, with different regions having different classifications, metals, and limits. However, 

 “Biocompatibility of Breathing Gas Pathways in Healthcare Applications–Part 4: Leachables in Condensate” (1) provides guidance that is relevant and may be applied, since it discusses the sample preparation, analytes, and methodologies used to evaluate data quality. This method states that the analytes and limits are defined by 

 (3). Because face masks cover the nose and mouth, 

states that the route of exposure is inhalation, assuming a maximum daily condensate intake of 1 mL. Analytes and their maximum daily exposure through inhalation (as defined in 

 defines the relevant concentrations as the 

with PDE equaling maximum permissible daily exposure (μg/g); Maximum Daily Dose equaling maximum amount of the medication consumed; and Dilution Factor equaling dilution used in sample preparation and the mass of sample or sample preparation volume. 

Disposable, non-medical face masks are challenging to analyze, due to the light weight of the inner layer, which results in lower analyte concentrations for method validation, a direct result of the 

To simulate exposure, sample preparation is vital, as 

 discusses in detail. It is important that analytes be leached at 37 °C (normal human body temperature) from the part of the face mask which the wearer is exposed to for a time representative of the duration the face mask is worn.

This work describes the sample preparation and analysis of metals in disposable, non-medical face masks with ICP-OES to meet the criteria defined in 

A variety of disposable, three-ply, non-medical-grade face masks were purchased, and the inner layer removed. Depending on the brand, the inner layers ranged in mass from 0.50–0.58 g, with most being ≈ 0.55 g. To minimize the creation of additional surface area and to better simulate a user’s exposure, the inner layer of each mask was not cut into smaller pieces, but rather leached whole.

For the leaching procedure, each inner layer was added to a 50 mL autosampler tube and pushed to the bottom, followed by the addition of 10 mL of 10% HCl + 1% HNO

 (v/v). Nitric acid was used to stabilize most elements, while the hydrochloric acid was required to stabilize the platinum group elements; 10% HCl was required to stabilize gold (Au) in solution over the leaching time. The tubes were capped and shaken before being heated in a sample preparation block at 37 °C for 4 h to simulate a common time a person may wear a face mask during a typical day. After 4 h, the acid was decanted into 15 mL autosampler tubes for analysis.

 requires several pre-sample preparation spikes to ensure that no analyte is lost during the sample preparation procedure. Sample spikes of 0.5

 were added to empty 50 mL autosampler tubes, followed by the mask inner layers. The inner layers were pushed to the bottom of the autosampler tubes to maximize contact with the spike solutions and allowed to sit for 30 min to absorb as much of the spike solutions as possible.

The acid mixture was then added so that the final volume of liquid added to each tube was 10 mL. The sample preparation is then continued as for the unspiked mask inner layers.

Calibrations were made against external calibration curves at 0.5

), and yttrium (Y) was added to all blanks, calibration standards, and samples as an internal standard.

All analyses were performed on a PerkinElmer Avio 550 Max ICP-OES using the analytes and wavelengths in Table I, along with the conditions and parameters in Table II. For maximum sensitivity, all analytes were measured with an axial plasma view, while high resolution was used to separate analytes from potential interferences. Multicomponent spectral fitting (MSF) was applied to Ir 208.882 nm to more easily resolve the peak from the baseline noise.

To assess the presence of analytes in the mask inner layers, samples were measured after 4 h of leaching. The concentrations of all analytes in all samples were less than 0.3

, a level more than three times lower than the inhalation PDE. These results indicate that the acids used for leaching do not extract excess analytes over time, as compared to normal respiration.

 states that methodology must be validated following 

1. Accuracy: Pre-preparation spike recoveries of 0.5

2. Repeatability: Relative standard deviations (RSDs) of six independent samples spiked at 

3. Ruggedness: Six solutions must be analyzed on different days, with different instruments, or with different analysts. The RSDs over the 12 measurements must be less than 25%.

4. System Suitability: The difference in the results of the high calibration standard (1.5

) measured at the beginning and end of a batch must be <20%.

Figure 2 shows that all the above criteria are met for all elements, with the exception of gold (Au) and palladium (Pd) in the accuracy study: both of these elements recovered just at or below the 70% minimum threshold.

FIGURE 2: Results of validation study: (a) system suitability, (b) accuracy, (c) repeatability, (d) ruggedness (

To investigate Au and Pd, another accuracy study was performed, but without the mask inner layers. The leach procedure was followed and spikes added, except the mask inner layers were not added to the sample tubes; only the acid mixture and spike solutions were added to the tubes. The recoveries from this accuracy study show that all elements recover within 10%, including Au and Pd, suggesting that Au and Pd stick to the mask inner layers and are not extracted during the leach process. The implication is that wearers will not inhale Au and Pd if they are present in face mask inner layers.

This work has demonstrated the ability of ICP-OES to effectively measure metals in non-medical, disposable mask inner layers, following 

, which references the analytes and validation procedures from 

. A four-hour leach simulates how long a person may wear a mask during a typical day. The results indicate that the methodology easily meets the criteria for 

 for all analytes, except Au and Pd, which stick to the mask inner layers and would not be inhaled. Although ICP-MS could also be used for this analysis, ICP-OES has proven to be a cost-effective alternative to ICP-MS capable of meeting the criteria in 

 “Biocompatibility Evaluation of Breathing Gas Pathways in Healthcare Applications – Part 4: Leachables in Condensate,' ISO 2017.

(2) General Chapter <232> “Elemental Impurities–Limits,” in 

2nd Supplement in United States Pharmacopeia 35-National Formulary 30

 (United States Pharmacopeial Convention, Rockville, Maryland, 2018).

(3) General Chapter <233> “Elemental Impurities–Procedures,” in 

 is a Principal Application Scientist at PerkinElmer, Inc. in Shelton, Connecticut. Direct correspondence to: 

Articles

The determination of metals in hygienic face masks is important for global heath
at this time. Following the guidelines of ISO 18562-4, an ICP-OES method is described including sample preparation, analysis, and validation of the methodology.

The Determination of Metals in Disposable, Non-Medical Face Masks by ICP-OES

Whenever concentrations are measured with atomic spectroscopy, they are calculated from a calibration curve. Therefore, attaining accurate quantitative results requires proper calibration, especially when measuring low-level concentrations near detection limits. This brief tutorial explains the effect of calibration on the accuracy and detection limits in atomic spectroscopy analyses. A thorough discussion of statistics in analytical chemistry is available in a series of 52 articles (1), with six articles (2–7) being the most relevant to this discussion.

Linearity must be considered when performing analyses by any atomic spectroscopy technique. In general, the linearity of atomic absorption (AA) is ≈3 orders of magnitude, inductively coupled plasma–optical emission spectrometry (ICP-OES) is ≈6 orders of magnitude, and inductively coupled plasma–mass spectrometry (ICP-MS) is ≈10–11 orders of magnitude. Although this is technically true, it does not mean that calibrating over wide ranges will produce accurate results. If a calibration curve in ICP-MS is constructed from calibration standards over 9 orders of magnitude (that is, 1 ppt to 1000 ppm) and has a correlation coefficient of 0.999992, this would be considered a linear calibration curve with an excellent correlation coefficient, implying that any concentration between 1 ppt and 1000 ppm would be read accurately against this curve, which is not true.

Consider a theoretical example of a calibration curve made from standards ranging from 0.1 to 100 ppb—four orders of magnitude. The only way to measure accurate concentrations over a wide range is if every measurement is perfect, which is not possible: every standard on the curve has an error associated with it. Consider that if each calibration standard in Figure 1 has a 2% error on the intensity, the mean intensity error increases as the concentration and intensity of each standard increases: a 2% error on the 0.1 ppb standard (100 counts per second [cps]) is only ±2 cps, but a 2% error on the 100 ppb standard (95,000 cps) is ±1,900 cps. If these data are plotted and a regression (or best-fit) line drawn through the standards (Figure 1), the error of the higher concentration standards dominates the curve. The best-fit line passes almost directly through the 100 ppb standard, but the lower standards are increasingly farther away from the line, demonstrating that the highest absolute error contributes most to the overall curve fit.

FIGURE 1: Calibration curve with 2% error bars for each standard.

Since the error of high concentration standards dominates the calibration curve, both accuracy at lower concentrations and detection limit calculations are affected. If accuracy at low concentrations is the most important criteria, then the calibration curve should be constructed without the use of high-concentration calibration standards: the calibration curve should only contain low-level standards. For example, if selenium (Se) is measured by ICP-MS and is expected to be below 10 ppb in most samples with a reporting limit of 0.1 ppb, a calibration curve consisting of a blank and three standards at 0.5, 2.0, and 10.0 ppb will provide much better accuracy at levels of 0.1 ppb than a calibration curve with standards at 0.1, 10, and 100 ppb. This same principle also applies to ICP-OES and AA, even though their linear ranges are narrower than ICP-MS.

Now consider an example from ICP-MS: a calibration curve for Zn constructed from 11 standards (0.01, 0.05. 0.1, 0.5, 1 5, 10 50, 100, 500, and 1000 ppb) over six orders of magnitude. Figure 2a shows the resulting calibration curve, which has a correlation coefficient (

) of 0.999905, indicating excellent linearity. However, when the 0.1 ppb standard was analyzed as a sample against this curve, it read 4.002 ppb – a huge error.

FIGURE 2: (a) ICP-MS calibration curve for Zn over six orders of magnitude with 11 standards; (b) same curve, with the lowest seven standards expanded.

The cause of this high readback is apparent in Figure 2b, which shows an expanded view of the low end of the curve (the 0.01–10 ppb standards): Zn contamination in the seven lowest standards which causes them to read higher than their nominal concentrations. However, this issue is not apparent from the correlation coefficient since the lowest standards contribute almost nothing statistically to the curve, compared to the four highest standards. This example clearly demonstrates the problem of calibrating at concentrations much higher than expected in samples.

The previous example demonstrates the problem with contamination in calibration standards, but another common issue is contamination in the calibration blank. Contamination can originate from a number of sources, including reagents (acid, water), deposition in the sample introduction system, or deposition in the instrument itself (interface cones, for example), to name a few. Since the blank is assumed to have analyte concentrations of zero, the measured signal from the blank is subtracted from all subsequent measurements. If the blank signal intensity is higher than that of a standard (or sample), the blank-subtracted concentrations will be negative, resulting in poor calibration curves. However, this may not be apparent with calibration curves which include high-concentration standards because the contamination will be small relative to the signal from the high standards. The result: the correlation coefficient will indicate a linear regression, implying that accurate results can be obtained at low concentrations.

In reality, there is no such thing as a true “blank”: contamination always exists at some level. The goal is to limit contamination so that it is much lower than the lowest calibration standard.

Calibrating for Low and High Concentrations Levels

As shown, accurate results for low-level samples can best be obtained by calibrating at concentrations close to the expected concentrations. But this leads to the question: will low-level calibrations produce accurate results for samples with high concentrations? The answer is yes, in most cases. The reason: the error at high concentrations dominates the curve. This means that errors at low concentrations will not have as large an impact on high-concentration samples. To confirm, it is good practice to perform a linear range study on any set of calibration standards: run successively higher standards against the calibration curve. The linear range is generally considered the highest concentration that recovers within 10% of its true value.

However, there are situations where high concentrations will be negatively affected by low level concentrations. Two common causes are large errors in the low calibration standards or when the analyte concentrations are so high that they cause matrix suppression. However, this latter case can usually be compensated for by proper selection of an internal standard.

The key to accurate measurements at low concentrations and to achieving meaningful detection limits is to establish calibration curves with low-level standards. Just about any calibration curve can produce correlation coefficients when using high-concentration standards, but these will not provide meaningful, accurate low-level results or detection limits.

. Parts 1–52, (2002–2013). https://www.americanlaboratory.com/841-Search/?search=Coleman%20Vanatta%20Part%201

. Part 40 (2010). https://www.americanlaboratory.com/914-Application-Notes/1114-Part-40-Blanks/

. Part 41 (2011). https://www.americanlaboratory.com/914-Application-Notes/981-Statistics-in-Analytical-Chemistry-Part-41-Blanks-Concluded/

. Part 44 (2011). https://www.americanlaboratory.com/913-Technical-Articles/35232-Part-44-R-sup-2-sup/

. Part 45 (2011). https://www.americanlaboratory.com/913-Technical-Articles/35860-Part-45-R-sup-2-sup-Continued/

. Part 46 (2012). https://www.americanlaboratory.com/913-Technical-Articles/38042-Part-46-R-Concluded/

. Part 47 (2012). https://www.americanlaboratory.com/913-Technical-Articles/39480-Part-47-Risky-Calibration-Practices/

 is a Principal Application Scientist with PerkinElmer in Shelton, Connecticut. Direct correspondence to: 

Attaining accurate quantitative results in atomic spectroscopy requires proper calibration, especially when measuring low-level concentrations near detection limits. This tutorial explains key concepts of calibration, illustrated with specific examples.

Kenneth Neubauer

Articles

The Determination of Metals in Disposable, Non-Medical Face Masks by ICP-OES

Calibration: Effects on Accuracy and Detection Limits in Atomic Spectroscopy