Ruth Marfil-Vega

In 1991, the United States Environmental Protection Agency (EPA) published the Lead and Copper Rule (also known as LCR) with the aim to reduce exposure to lead and copper in drinking water. Two decades later, it promulgated the Lead and Copper Rule Revisions (LCRR) to provide communities with the tools for preventing lead exposure. This article details the use of current inductively coupled plasma–mass spectrometry (ICP–MS) instrumentation in accordance with EPA Method 200.8 and the new requirements of the LCRR.

Lead and copper are elements that can enter drinking water through plumbing systems and cause a wide range of health problems (1–5). The lead crisis in Flint, Michigan, introduced a public health crisis of life-long impact to the children and families affected; it also triggered greater concerns about overall water quality. In early 2021, two decades after the publication of the Lead and Copper Rule (LCR), the U.S. Environmental Protection Agency (EPA) promulgated the Lead and Copper Rule Revisions (LCRR), although the effective date for the new regulation is not yet established. The changes in LCRR focus on identifying areas most impacted by lead contamination, increasing sampling and analysis in facilities serving vulnerable populations (like schools and childcare facilities), and strengthening treatment requirements with the introduction of a new trigger level of 10 μg/L for lead, lower than the action level of 15 μg/L that will remain in the revised rule.

EPA Method 200.8 is one method approved to determine trace metals in water, including lead and copper by using the inductively coupled plasma–mass spectrometry (ICP–MS) technique (6–8). The EPA method was published more than 25 years ago. Since then, new features have been introduced in the design of ICP–MS instrumentation to simplify operation and improve performance. An example of new technology developed since EPA Method 200.8 was published is the implementation of collision cell technology. Because it was not available at the time of releasing EPA Method 200.8, collision cell technology is not currently permitted to remove polyatomic interferences. Alternatively, correction equations can be used to minimize the effect of this type of interferences. In addition, a correction equation is specifically required for determining lead in water. Various isotopes of lead are the final products of the radioactive decay of heavier elements (uranium, for example) and the ratio between lead isotopes is dependent on the source of origin (9,10). Hence, the sum of the signals for all lead isotopes is used for analyzing lead, according to EPA Method 200.8.

In this study, we demonstrate that elemental analysis of drinking water samples can be performed with current ICP–MS technology to meet all the EPA quality assurance (QA) criteria established in EPA Method 200.8, while supporting the LCRR with the newly proposed trigger level for lead (10 μg/L).

Deionized (DI) water with resistivity higher than 18.2 MΩ∙cm and trace metal grade nitric acid (67–70%, w/w VWR Chemicals) were used as primary reagents for standards preparation. The EPA 200.8 package of multielement standards (Inorganic Ventures) was used to prepare calibration standards and internal standard solutions. All drinking water samples from different sources were acidified with nitric acid to a concentration of 2% v/v.

An ICP–MS Model 2030 equipped with a AS-10 Autosampler (Shimadzu Scientific Instruments) was used for all analyses. Inline addition of internal standards to calibration and unknown samples was accomplished using a Glass Expansion inline internal standard addition kit. Operational parameters of the ICP–MS are listed in Table I.

The instrument was tuned to optimize system parameters prior to analysis using an ICP–MS tuning solution to ensure correct torch position, lens voltages, and mass resolution. Following tuning, the status of the instrument was evaluated using the EPA Method 200.8 tuning solution. The mass resolution at low and high masses was evaluated by measuring magnesium isotopes (

Pb) respectively to ensure an acceptable resolution (approximately 0.75 amu) could be achieved. The stability of the instrument was also evaluated by measuring five replicates of the tuning solution; relative standard deviation (RSD) of recorded signals for beryllium, cobalt, indium, magnesium, and lead below 5% demonstrated acceptable stability.

After successful tuning and performance evaluation, the instrument was calibrated for the elements of interest (included in Table II). Appropriate calibration standards were selected for each analyte to cover the required analysis range; the specific concentrations for each analyte are shown in Table II. An internal standard solution containing yttrium, scandium, indium, and bismuth was added to all samples using an inline internal standard addition kit, with dilution factor of 1:10. The final concentration of the internal standards was 50 μg/L.

Although modern ICP–MS instruments, including the one used in this study, are equipped with a collision cell to effectively remove polyatomic interferences, the collision cell technology is not currently accepted by EPA Method 200.8. Therefore, correction equations were used as an alternative method to compensate for potential interferences. In the case of lead measurement, the sum of the signals from all three lead isotopes (

Pb) are measured by applying appropriate correction equation to negate naturally occurring variations in the isotopic ratios between calibration standards and samples. All correction equations used in this study are shown in Table III.

Calibration of the instrument for quantification of lead and other analytes of interest was performed by the creation of calibration curves using external standards. EPA Method 200.8 does not include specific quality assurance criteria for determining the suitability of the calibration curve. However, for this work, calibration curves were accepted when linear regression values (

) of ≥0.995 were achieved. As shown in Table IV, all calibration curves show excellent linearity across the respective calibration range with 

The linear dynamic range (LDR), instrument detection limits (IDL), and method detection limits (MDL) were established to validate instrument performance according to EPA QA criteria included in EPA Method 200.8 before the samples were analyzed. The LDR is determined by analyzing a series of samples at concentrations higher than calibration range to determine at which concentrations they fall out of ±10% of their expected concentration. LDR results are listed in Table IV. The values for lead and copper are 20 and 40 mg/L, respectively.

The IDLs are calculated as three times the standard deviation of 10 replicate measurements of a calibration blank. According to EPA Method 200.8, MDL is defined as the minimum concentration of an analyte that can be measured and reported with 99% confidence level. The MDLs are calculated by the equation 1 below:

-distribution value for a confidence level of 99% that is 3.14 for a sample size of 7 and 

 is the standard deviation of 7 replicate analyses. Each analyte was spiked into 2% nitric acid solution at a concentration from two to five times the IDL.

For calculating the IDLs and MDLs, each replicate was measured as an unknown or calibration sample; three measurements were carried out for each replicate. IDL and MDL for all analytes are shown in Table IV. IDL and MDL for lead are 0.014 μg/L and 0.03 μg/L, respectively. For copper, the IDL is 0.003 μg/L and the MDL is 0.008 μg/L. IDL provides an estimation of the sensitivity of an instrument based on its condition at the time of acquiring the data; results are heavily impacted by numerous factors, such as instrument age, maintenance record, and system cleanliness. For the practical purpose of reporting data in support of the requirements of LCRR, MDL is a more relevant parameter than IDL, because impact of sample matrix is considered in the calculation. The LCRR introduces a new trigger value for lead of 10 μg/L. Water utilities will have to modify water treatment if lead exceeds the trigger level. Therefore, laboratories will have to provide reliable results of lead concentrations several orders of magnitude lower than 10 μg/L for utilities to be able to plan and respond to the level of lead in drinking water. As seen in Table IV, the MDL calculated for lead in this work easily meets this requirement.

Samples Analysis and Post-Analysis Validation

Table V shows concentrations of elements in the original samples and spiked samples for a blank and three different water samples. The spike and recovery method are used to validate the results and en- sure reliable instrument performance. The spiked concentration was 100 μg/L for selenium and 20 μg/L for all other analytes. The recovery is calculated by the following equation 2:

 are concentration of sample and fortified (spiked) samples respectively, and s is the concentration equivalent of added analyte to the fortify sample.

The spike and recovery tests for all analytes fell within the acceptable range of 90–110% of the spiked values. All relative standard deviations (RSD) were also below 5%, further demonstrating the validity of the methodology and the high level of precision for the routine analysis of lead and other metals in water samples.

The stability of the instrument was evaluated by analyzing a series of known samples repeatedly for 10 h to demonstrate deviation of signal intensities. A total of 120 samples were analyzed during this period of time. Stable operation of an ICP–MS instrument is critical once the LCRR is implemented because additional monitoring of schools, childcare facilities, and other sectors, will be required. As shown in Figure 1, the recoveries for all analytes are extremely stable and within ±10% recovery threshold over a 10-h period, demonstrating the capability of the instrument to provide precise results over typical operational times in environmental laboratories.

FIGURE 1: Recovery of analytes over a 10-hour period. The dashed lines represent 100 ±10% recovery.

Drinking water samples were successfully analyzed by ICP–MS according to current technology. The detection limit (IDL and MDL) were calculated for all analytes and three water samples were analyzed to demonstrate method performance. The spiked-recovery tests showed all values were in the acceptable range of 90–110% with all RSDs below 5%. The MDL for lead was >300 times lower than the newly introduced trigger level of 10 μg/L; this provides laboratories and water utilities a large concentration range for anticipating and responding to high levels of lead in drink- ing water. Stable responses were also obtained for all analytes over a 10-h period, demonstrating the stability of instrument over a typical operation conditions in environmental laboratories. Consequently, laboratories will be able to accommodate increasing sample loads without additional downtime for instrument maintenance.

The sensitivity, precision, durability, and accuracy obtained for determining lead in drinking water according to EPA Method 200.8 validates the suitability of the current ICP–MS instrumentation used in this study to successfully support the new demands and challenges the implementation of LCRR will pose to water utilities and the laboratories working with them.

(1) A. Kumar, A. Kumar, C.-P. M.M.S., A.K. Chaturvedi, A.A. Shabnam, G. Subrahmanyam, R. Mondal, D.K. Gupta, S.K. Malyan, S.S. Kumar, S. A. Khan, and K.K. Yadav, 

(3) A.L. Wani, A. Ara, and J.A. Usmani, Interdiscip Toxicol. 8(2), 55–64 (2015).

(4) N.C. Papanikolaou, E.G. Hatzidaki, S. Belivanis, G.N. Tzanakakis, and A.M. Tsatsakis, 

(5) H. Gurer-Orhan, H.U. Sabır, and H. Özgüneş, 

EPA Method 200.8: Determination of Trace Elements in Waters and Wastes by Inductively Coupled Plasma Mass Spectrometry, Revision 5.4

(7) “Analysis of Trace Elements in Water by EPA Method 200.8 using the Shimadzu ICPMS- 2030,” Shimadzu Application News, No. ICP-005.

(8) “Analysis of River Water by ICPMS-2030”, Shimadzu Application News, No. J118.

(9) E. Schnyder, M. Štrok, Z. Kosonen, M. Skudnik, D. Mazej, Z. Jeran, and L. Thöni, 

 is a Product Specialist–Elemental Spectroscopy, at Shimadzu Scientific Instruments, in Columbia, Maryland. 

 is the Market Manager- Energy & Chemicals at Shimadzu Scientific Instruments, in Columbia, Maryland. 

 is the Product Manager–Elemental Spectroscopy at Shimadzu Scientific Instruments, in Columbia, Maryland. 

 is the Senior Market Manager–Environmental at Shimadzu Scientific Instruments, in Columbia, Maryland. Direct correspondence to: rmmarfilvega@shimadzu.com.

 is the principal of Scientific Solutions, an educational consulting company that serves the training and writing needs of the trace element user community. He has worked in the field of atomic and mass spectroscopy for more than 45 years. ●

Articles

EPA Method 200.8 and the Lead and Copper Rule Revisions don’t allow use of modern ICP-MS technology with a collision cell. Instead, correction equations can be used to compensate for polyatomic interferences.

Analyzing Water Samples Using EPA Method 200.8 to Support the Lead and Copper Rule Revisions

Micro- and nanoplastics enter the environment as manufactured products in cosmetics and other industrial products, and as breakdown products of plastics of larger size (macroplastics). Recent estimates suggest that the mass of microplastics in aquatic habitats will surpass that of fish by 2050; therefore, plastic pollution is a major environmental issue faced at global scale. Marine scientists have been working in this field for over a decade, and more recently the study of microplastics has captured the attention of other scientists in the environmental field. Despite efforts focused on identifying, quantifying, and assessing the size of microplastics in the environment, standardized methods are lacking. As a result, studies cannot be compared or reproduced. Infrared (IR) microscopy has become an essential technique in the toolbox for the analysis of microplastics in environmental samples. In this work, we conducted a methodical evaluation of significant operational parameters of IR microscopy for accurately determining the size of microplastics, with the overarching goal of outlining performance parameters that will help in the standardization of microplastics analysis.

Plastic pollution is a major environmental issue faced at global scale. Micro- and nanoplastics enter the environment as manufactured products in cosmetics and other industrial products, and as breakdown products of plastics of larger size (macroplastics). According to a recent perspective paper (1), the most pessimistic estimates suggest that the mass of microplastics in aquatic habitats will surpass that of fish by 2050. Interest in the scientific community and public has exponentially increased in the past few years, resulting in a significant increase in the number of publications focused on this topic (2). Marine scientists have been working on this field for a decade, and more recently the study of microplastics has captured the attention of other scientists in the environmental field. Despite efforts focused on identifying, quantifying, and assessing the size of microplastics in the environment, standardized methods and agreement of reporting parameters are lacking (3). As a result, studies cannot be compared or reproduced. Common requests from scientists engaged in the field include the need for reference materials, proficiency tests and interlaboratory studies, and detailed descriptions of instrumental and spectral treatment parameters (2). Multiple international groups (2,3), scientific organizations (such as the Society of Environmental Toxicology and Chemistry), and standardization agencies (such as the American Society for Testing and Materials [ASTM] and the International Organization for Standardization [ISO]) are currently engaging in efforts to fulfill these requests.

 (4) provides an excellent summary of various techniques suitable of the identification of microplastics and their scope. Infrared (IR) microscopy has become an essential technique in the toolbox for the analysis of microplastics in environmental samples. IR microscopy is often used for two purposes: the identification and sizing of microplastics present in the sample. While lack of appropriate standard spectra in the libraries could cause challenges in proper identification, especially for weathered plastics, this problem can be overcome with custom-created libraries and analyzing specific regions of the spectra (unique peaks, valleys, and intensity ratios, to name a few). Therefore, the real challenge is to understand the capability of IR microscopy for microplastics analysis, mainly in terms of smallest measurable microplastic particle size.

The objective of the work presented here was to collect data to support current standardization efforts for the analysis of microplastics in environmental samples by IR microscopy. For this purpose, we conducted a methodical evaluation of significant operational parameters of IR microscopy for accurately determining the size of microplastics, including optical mode, number of scans, and background contribution from filters.

Microplastic standards were purchased from Sigma-Aldrich. They were polymer based micro particles with various diameters: 100 µm polystyrene (P/N 59336), 50 µm polymethacrylate (P/N 74161), 50 µm polystyrene (P/N 74491) and 10 µm polystyrene (P/N 72986).

Three types of filters commonly used to hold the microplastics samples for Fourier transform infrared (FT-IR) spectroscopy studies were evaluated: a stainless-steel mesh filter (Utah Biodiesel Supply, 5 μm pore size), a cellulose ester filter (Whatman, 0.6 μm pore size) and a glass fiber filter (Whatman, 934-AH grade, 1.5 μm pore size).

The measurements were carried out with a Shimadzu AIM-9000 FT-IR microscope in combination with an IRTracer-100 FT-IR spectrophotometer. Instrumental control and data acquisition were done automatically by the AIMSolution software. Data were collected in reflection mode and attenuated total reflectance (ATR) mode. When measuring in the reflection mode, background was acquired using a silver mirror. Experiments conducted in ATR mode were conducted with the Shimadzu ATR attachment with a Ge objective on the FT-IR microscope. The only post-processing steps performed were baseline correction of the data whose signal to noise ratio were calculated, and Kubelka-Munk transformation of the spectrum of the cellulose ester filter. The instrumental parameters are listed in Table I.

All samples were diluted first to 1 mL of Deionized water, except for the 100 μm polystyrene based microplastics sample. For reflection mode measurements, the samples were dispensed onto the filters and dried under ambient conditions. For ATR mode studies, 1–2 drops of the diluted samples or the 100 μm polystyrene-based stock sample were dispensed on a low-E microscope slide, and dried under ambient conditions.

To get a better understanding of types and distribution of the particles on the filters, infrared mapping measurements were carried out using the reflection mode on the FT-IR microscope. The information obtained from mapping is often qualitative; however, some quantitative information can also be obtained with further data analysis. In-depth measurements using more sensitive setup and parameters were carried out on areas of interest determined by mapping.

Samples containing microplastics of decreasing particle size (described in the section 

) were analyzed in reflection mode with the conditions listed in Table I. These experiments were repeated using three filter types (stainless-steel mesh filter, cellulose ester filter, and glass fiber filter) to assess the impact of the background spectra on the detection threshold of the particle sizes.

The reflection mode measurement of the samples was obtained as-is in the filter, and although this measurement mode allows for faster data acquisition with the ability to analyze multiple particles or an entire area automatically, it is susceptible to background noise from the filter element, surrounding particles, and matrix. Therefore, once the particles were identified using the reflection method, a more targeted measurement with better signal-to-noise ratio (S/N) using the ATR attachment on single particles was carried out. Samples containing microplastics of decreasing particle size were analyzed in ATR mode with the conditions listed in Table I. Because ATR is a contact-based measurement for surface measurement (no more than 2–5 µm into the surface), only particles pressed against the ATR crystal are measured, ensuring
higher accuracy.

Evaluation of S/N and Threshold of Detection Based on Sample Size

An experiment was conducted for IR spectral acquisition (reflection mode) on the 100 μm polystyrene-based sample with varying aperture sizes. The aperture sizes started from 5x5 μm, then increased to 10x10 μm. The aperture sizes were gradually increased from 10x10 μm to 100x100 μm, with an interval of 10 μm (Figure 1). This change in aperture size can be directly correlated to the difference in sample size. In addition, and more importantly, using the same particle but with different aperture sizes also ensured that any other experimental variations (inter-sample variation and instrument conditions) were eliminated. In a second experiment, the impact of the number of scans in the S/N of the measurement at each aperture size was evaluated.

Spectral Search Using the FT-IR Polymer Library

Spectral searches for all spectra were performed using polymer libraries provided by the microscope software. The Shimadzu AIM-9000 FT-IR microscope adopts a score system from 0 to 1000 to report search results. In this study, the differential derivative algorithm was used, which calculates the primary differential of each data and compares the differential factor at each point with fitting of whole curves.

Reflection Mode Mapping Measurement Results

Microplastics samples dispensed on filters were scanned automatically using the mapping function of the AIMSolution Software. Aperture sizes were adjusted according to the dimension of the microplastics particles. The ratio of the signature peak intensity over the baseline intensity could be mapped to reflect the specific microplastics abundance at the locale. Figure 2 shows the mapping area settings and the resulting chemical mapping of microplastics samples of four different sizes on a stainless-steel mesh filter.

In Figure 2, it can be observed that mapping measurement in the reflection mode can provide relatively quick qualitative analysis of the microplastics samples in a potentially large area. When measuring particles with a size of 10x10 μm, it became challenging to capture focused images of the samples because the unevenness and the structure of the filters made it almost impossible for the microplastics particles to lie within the focal plane. As a result, the FT-IR spectra acquired for the 10 μm samples tended to reflect signals contributed by a subset of particles rather than that of an exact individual particle.

Similar reflection mapping measurements were obtained for microplastics samples held on a cellulose ester filter and a glass fiber filter. These filters were selected because they are commonly used in environmental laboratories for sample filtration. When those filters were used, signal interferences from the filters were evident (Figure 3). The cellulose ester filter showed IR peaks across the whole measured region (Figure 3e), whereas the glass fiber had IR absorption mainly in the low wavenumber region (Figure 3j). The stainless-steel mesh filter is highly reflective in the IR and can be considered to share similar features to that of the metal mirror used for background measurement; therefore, the spectra were not included in Figure 3. Figure 3 also demonstrates qualitatively how the background spectra negatively affects the detection threshold of the particle size. Overall, using the stainless-steel filter had the advantage of suppressing the signal contributions of the filters.

When measuring in the reflection mode, IR signals from the microplastics samples may be unable to be determined because of unwanted interference, like neighboring contaminants or substance attaching to the samples. It is desirable to measure in the ATR mode because it greatly assists in getting signal only from the targeted area. With a tip diameter of only 12.5 μm, the Shimadzu ATR attachment for AIM-9000 can acquire IR spectra from particles with high specificity. Figure 4 illustrates the microplastic samples and the FT-IR spectra acquired using ATR mode. However, samples were analyzed in triplicates; only one spectrum per particle size is included in the figure. The pictures on the left side are visible images captured for each of the samples analyzed. The FT-IR spectra are shown on the right side, and they illustrate the characteristic absorption bands of the microplastics. Spectral search was performed using polymer libraries provided by the microscope software; search results showed ≥75% match for the four samples analyzed, independently from the size of the particle. Qualitatively, the results demonstrate that FT-IR spectra of microplastics as small as 10 µm can be detected in ATR mode.

Evaluation of S/N and Detection Threshold

Measurements made in reflection mode are known to be more affected by the presence of interferences and background than ATR measurements; therefore, it can be assumed that the threshold of detection for determining the size of microplastics will be higher in reflection mode than ATR mode. To quantitatively determine the threshold of detection under the most challenging conditions, a series of experiments was conducted in reflection mode. FT-IR spectra were acquired on a 100 μm polystyrene particle, with variable aperture sizes gradually increasing from 5x5 μm to 100x100 μm (Figure 1); four replicate measurements at each aperture were performed. This change in aperture size can be directly correlated to the difference in sample size (See the Experimental Approach section for more details). Peak-to-peak S/N values at each aperture setting were evaluated; results are shown in Figure 4. Threshold of detection was determined based on measurements that presented a S/N > 3 (5). According to the results included in Figure 5, it can be concluded that when using the typical operational conditions of FT-IR microscopy (included in Table I), the smallest particle size that can reliably measured is 10x10 μm. From Figure 5, it was clear that the greatest increase in S/N took place when the sample (aperture) size was increased from 5x5 μm to 10x10 μm. After the sample (aperture) size was increased to 40x40 μm and higher, the rate of increase of S/N remained constant.

To further confirm the threshold of detection in terms of particle size, another study was carried out with sample sizes of 5x5 μm and 10x10 μm. In this study, the number of scans averaged to obtain a spectrum were gradually increased. The number of scans was set at 32, 64, 128, and 256 scans for the two sample sizes mentioned above. Measurements were replicated five times. Peak-to-peak S/N was evaluated at each measurement. As can be concluded from Figure 6, S/N in the 5x5 μm sample size did not show any substantial improvement with the increased number of scans. The averaged S/N values stayed close to 0.5, suggesting that only noise was observed. When the sample size was changed to 10x10 μm, S/N showed a noticeable increase as the number of scans increased. S/N should increase as more scans are averaged when a real signal is detected, this result further verifies that the signal from the 10x10 μm was real and that from the 5x5 μm sample was primarily noise; thereby, this confirms the threshold of 10x10 μm.

This work demonstrates a series of method and experimental conditions in FT-IR microscopy in both reflectance and ATR mode for identification and accurate determination of the size of microplastics. The results presented in this paper are a subset of data being prepared for standardizing the analysis of microplastics in environmental samples. We have demonstrated that, by using typical operating conditions of FT-IR microscopy, it is possible to identify and distinguish between microplastic particles as small as 10x10 μm in dimension. This threshold value held true for both the reflection measurement method (which is faster, but can experience signal interference from neighboring particles and matrix) and the ATR method, which is specific to a particle to get “cleaner” measurements but is slower because of the setup involved. In the reflection measurement itself, this threshold value was determined and verified by two separate analysis methods, further verifying the capability of the technique.

J.M. Andrade, B. Ferreiro, P. López-Mahía, and S. Muniategui-Lorenzo, 

W. Cowger, A. Booth, B. Hamilton, S. Primpke, et al., 

is a Product Specialist in the Molecular Spectroscopy group at Shimadzu Scientific Instruments in Columbia, Maryland. 

is the Product Manager of the Molecular Spectroscopy group at Shimadzu Scientific instruments in Columbia, Maryland. 

 is the Environmental Market Manager at Shimadzu Scientific Instruments, in Columbia, Maryland. Direct correspondence to: 

Here we conduct an evaluation of significant operational parameters of IR microscopy for accurately determining the size of microplastics, with the overarching goal of outlining performance parameters that will help in the standardization of microplastics analysis.

Insights Toward Standardization of the Analysis of Microplastics by Infrared Microscopy

Environmental scientists have documented a dramatic increase in the public interest about the occurrence of per- and polyfluoralkyl substances (PFAS) in water. Liquid chromatography mass spectrometry-based PFAS detection (LC–MS) has been established as the most suitable technology for monitoring these substances. Implementing robust methodologies for targeted monitoring, identification, and emergency response to emerging PFAS is challenging. Despite a vast PFAS-related scientific knowledge base, a lack of access and training for LC–MS instruments is a primary hurdle for expanded monitoring and identification. This paper presents data acquired according to draft method EPA 8327. This method requires minimal sample preparation and adequately assesses PFAS in various environmental samples, including groundwater, surface water, and wastewater.

	
	Per- and polyfluoralkyl substances (PFAS) are a class of more than 5,000 man-made and commercially available chemicals (1). PFAS are stable, and have water, oil, grease, and heat-resistant properties. These substances have been extensively used in the manufacturing of industrial (such as firefighting foams) and household (such as carpets, clothing, cookware, and food packages) products since the 1940s. The properties of PFAS that assist manufacturers in producing durable products are also responsible for their persistence in the environment and human body. Therefore, PFAS are resistant to biodegradation and other conventional remediation technologies. Possible health effects in humans and animals from exposure to PFAS have been reported, including increased risk of cancer, endocrine, and development disruption (2,3).

	Known PFAS are currently divided into ten subclasses (4). Perfluorooctanoic acid (PFOA) and perfluorooctanesulfonic acid (PFOS) have been historically the most studied chemicals. PFOA and PFOS belong to perfluoroalkyl carboxylic acids (PFCAs; base structure: C

COOH) and perfluoroalkane sulfonic acids (PFSAs: C

H) classes, respectively. Hexafluoropropylene oxide (HFPO), from the perfluoroether carboxylic acids class (PFECAs; base structure: CnF

-COOH), also known as GenX, has received focused attention since its recent discovery in the environment (5). GenX was introduced in the market as a replacement of PFOA and PFOS, together with other shorter chained PFAS, as a result of the PFOA Stewardship Program. This program involved eight major PFAS manufacturers in the United States that voluntarily phased out PFOA and PFOS-related compounds by 2015 (6). The shift in PFAS manufacturing processes towards the shorter chain compounds has been confirmed by the changes of PFAS fingerprint in wastewaters (7).

	The occurrence and fate of PFAS in the environment has been studied by the scientific community for two decades. Analytical methods have been developed and normally validated for specific studies, including variable lists of target compounds. Liquid chromatography mass spectrometry (LC–MS) detection (either triple quadrupole or high-resolution instruments) is required for the extremely low detection limits required for quantification of known PFAS and the identification of new ones in environmental samples. In the United States, LC–MS-based PFAS methods have had a limited reach in the environmental field outside of research laboratories. However, the recent emergence of public concern regarding the presence of PFAS in the environment, especially in water, have required laboratories to provide rapid and accurate results to relevant stakeholders. Figure 1 describes various workflows that laboratories may need to implement, depending on the end-goal for PFAS analysis. Nakayama and associates published an extensive review of the latest global trends for quantitation of PFAS and screening of new compounds in 2019 (8). In this review, research methods allow for more flexibility, especially as it applies to samples that can be analyzed using a single method and pre-treatment step.

	Over the past year, the US Environmental Protection Agency (EPA) published several standardized methods to partially address the current needs of environmental labs and other relevant stakeholders. Namely, standardized methods that allow for faster turn-around-times. In November 2018, EPA method 537.1 (Determination of selected per- and polyfluorinated alkyl substances in drinking water by solid phase extraction and liquid chromatography–tandem mass spectrometry [LC–MS/MS]) (9) was published. EPA 537.1 was an update of EPA 537 (determination of selected perfluorinated alkyl acids in drinking water by solid phase extraction and liquid chromatography–tandem mass spectrometry [LC–MS/MS]) (10) to include four additional compounds: HFPO-DA (GenX), ADONA, 11Cl-PF3OUdS and 9Cl-PF3ONS. These two methods were only validated for the analysis of drinking water; hence, their performance was not demonstrated in non-potable waters. In December 2019, the EPA published a new method for the analysis of PFAS in drinking water, EPA method 533 (Determination of per- and polyfluoroalkyl substances in drinking water by isotope dilution anion exchange solid phase extraction and liquid chromatography–tandem mass spectrometry) (11). This method expanded the target compounds to focus on the shorted chain substances. Table I lists the target compounds included in each of the methods published by EPA for analysis of PFAS in drinking water. The Department of Defense (DOD) is also invested in the standardization of analytical methods for the assessment of PFAS in drinking water. While the DOD requires laboratories to use method EPA 537 or EPA 537.1 for drinking water analysis, the DOD allows in-house developed methods for the analysis of other environmental samples. These methods are acceptable provided that the laboratories demonstrate adherence and compliance with the quality criteria established in the current version of DOD’s Quality Systems Manual (Version 5.3) (12).

	Draft method EPA 8327 (Per-and polyfluoroalkyl substances [PFAS] using external standard calibration and multiple reaction monitoring [MRM] liquid chromatography–tandem mass spectrometry [LC–MS/MS]) was published in the summer of 2019 (13). Draft method EPA 8327 is similar to ASTM 7979 (Standard test method for determination of per- and polyfluoroalkyl substances in water, sludge, influent, effluent, and wastewater by liquid chromatography–tandem mass spectrometry [LC–MS/MS]), originally published in 2016 (14). This method expands the list of target compounds as well as sample types available for analysis, including non-potable waters. The scope draft method EPA 8327 is the quantification of 28 selected PFAS with minimal sample preparation (similar to “dilute and shoot” approaches) in non-potable waters (ground water, surface water, and wastewater). The elimination of solid phase extraction in this method reduces analysis times and  experimental bias, and minimizes PFAS contamination during sample pre-treatment. This paper presents the results from assessing PFAS in non-potable waters (groundwater, surface water, and wastewater) according to draft method EPA 8327, and aims to demonstrate the reliable and robust performance of the method.

	A commercial mixture of PFAS, including targets and isotopically labeled compounds, from Wellington Laboratories were used (Catalog no. PFCA-24PAR and MPFCA-24ES). These standards were diluted to working standards with 95:5 (

) acetonitrile:water, in accordance to EPA Method 8327.

	The LC–MS/MS analysis of 43 PFAS (24 targets and 19 surrogates, listed in Table I) was performed using a Shimadzu Nexera UHPLC system coupled with LCMS-8050 triple quadrupole mass spectrometer. A detailed description of the LC–MS/MS parameters is included in Table II. A Shim-pack GIST Phenyl-Hexyl, 2.1 mm × 100 mm and 3.0-μm particle size (Shimadzu P/N: 227-30713-03) analytical column was used to conduct the analysis, along with a Shimadzu Shim-pack XR-ODS 50 mm × 3.0 mm x 2.2-μm (Shimadzu P/N: 228-41606-92) as delay column. The delay column was installed for minimizing possible PFAS contamination from the solvents being used. Mobile Phases A and B were the same as those listed in EPA method 8327 for a binary gradient: 20 mM ammonium acetate in 95:5 water:acetonitrile and 10 mM ammonium acetate in 95:5 acetonitrile:water for A and B, respectively. A 0.3 mL/min flow rate was used in the 21 min gradient, an allowed modification of the gradient listed in EPA method 8327. The total run time of 21 min included re-equilibration for both the delay and the analytical column. This gradient (described in Table II) was developed to ensure maximum resolution between peaks in the shortest time possible with minimum co-elution of isomers.

	All compound specific parameters, including precursor ion, product ion, and collision energies were optimized using flow injection analysis (FIA), bypassing the analytical column using Lab Solutions software. The lower ESI heater temperature selected reduces HF loss and minimizes false identification of fluorotelomer acids. The MRM transitions are listed in Table III. A total of 66 MRMs was monitored. The targets monitored in this work are anionic, hence, analyzed by electrospray ionization in negative mode. However, new research suggests cationic and zwitterionic PFAS might ionize better in positive mode (15). The ultra-fast acquisition rate of 555 MRM/sec of the LCMS-8050 used in this work allows for the inclusion of more targets (to be analyzed in positive and negative mode), without compromising the sensitivity in a single run. Additional details about the method and configuration can be found elsewhere (16).

	The working standards were used to create a calibration curve ranging from 5 to 200 ng/L, with the injection solvent consisting of 50:50 water:methanol, with 0.1% acetic acid in order to match the injection solvent for the extracted samples. Filtration was not performed on the calibration standards. Quality control samples (QCs) were prepared as the calibration standards.

	Replicated samples, including reagent water, groundwater, surface water, and wastewater were analyzed during this study. Each sample was diluted 50:50 with methanol and 0.1% acetic acid, spiked with isotopically labeled surrogates, and vortexed for 2 min. The samples were then filtered through 0.2 μm syringe filters, and analyzed by LC–MS/MS.

	Data presented in this paper were acquired in two batches, and analyzed in consecutive dates. Each batch included the analysis of 39 injections (9 calibration standards, 4 blanks [reagent, method, and travel blanks], 6 QCs [LLOQ, LCS, and CCV] injected along the sequence according to EPA requirements, and 20 samples [reagent water, ground water, surface water and wastewater]).

	Calibration curves were performed for all PFAS targets, using a nine-point calibration curve, ranging from 5 to 200 ng/L. Figure 2 shows a total ion chromatogram and MRMs from a 5 ng/L standard; this figure demonstrates the separation and peak shape of targets at the lowest concentration included in the calibration curve.

	The linearity of the curve was determined using a 1/x weighting factor, and not forcing through zero. Excellent linearity was obtained with correlation coefficients (

) greater than 0.99 for all analytes or transitions in the two batches analyzed for collecting the data presented in this paper. Residuals of each standards were within ±30% difference from its true concentration. More detailed information about the calibration curve results can be found elsewhere (16).

	A total of eight continuing calibration verification standards (QCs) were injected in the two batches consecutively analyzed for this study. Surrogates and targets were spiked at 80 ng/L (in sample equivalent). Figure 3 summarizes the concentrations of all surrogates, grouped by PFAS class, from EPA 8327 in the eight QCs samples; the red solid line represents the true concentration (80 ng/L), and the dotted red lines set the limits of the acceptable concentration range according to EPA guidelines (±30% of the expected value, equivalent to 56 and 104 ng/L). For the PFCAs class, the concentration range increases with carbon chain length; no clear trends were observed for the other classes of PFAS. All results, except for one injection of d3-NMeFOSAA, were within ±30% of the expected value, and, moreover, most to the results were within ±20% of the expected value. Figure 4 summarizes the concentrations of the eleven PFCAs included in the method. Similar trend to that observed for the PFCAs surrogates was observed for the targets. For the targets, including the other classes not shown in Figure 4, results were well within EPA’s acceptable range (±30% of the expected value) and even the stricter bracket of ±20%. The percent relative standard deviation was <20% for all compounds (results not included here) in the two batches analyzed. The results summarized in Figures 3 and 4 demonstrate the robustness and reproducibility of the method validated in this work. It is also noteworthy that maintenance was not required for maintaining the performance of the instrument after the analysis of at least 40 environmental samples (approximately 28 h of operation).

	Forty environmental samples were analyzed in two consecutive batches. Figure 5 summarizes the surrogate (spiked at 160 ng/L) recoveries from 16 representative samples collected from various sources (reagent water, groundwater, surface water, and wastewater), and prepared as described in the Materials and Methods section, in accordance to EPA method 8327. Samples were analyzed in a random order in the two batches. Surrogates %recovery ranged between 82% and 92% in reagent water, groundwater, surface water, and wastewater; these values are well within the acceptable ranges (70-130%). The percent recoveries in the groundwater samples were consistently higher than in the other sample types; however, they were still within limits accepted by EPA, and ranged between 95% and 123%, except for M2PFTreA (138%). As samples were analyzed randomly, the difference could be attributed to matrix enhancement in the groundwater samples. EPA method 8327 utilizes an external calibration; the matrix enhancement could be minimized by using an internal calibration or isotopic dilution for calculating the PFAS concentrations. The %RSDs were less than 10% (half of the acceptable criteria listed in EPA method 8327), and no major differences were observed across samples types. The reproducibility in the results from the surrogate recoveries corroborates the robustness of the system inferred from the results of the QCs.

	Multiple analytical methods for the monitoring of PFAS have been developed and validated over the past two decades. However, one of the challenges environmental stakeholders face for understanding the global occurrence of PFAS and the effectiveness of mitigation strategies is the lack of standardized methods. Secondly, the recent increase in PFAS by the public requires laboratories to provide results quickly. This paper demonstrates the reliable and robust quantification of PFAS, according to latest EPA method for the analysis of environmental samples different from drinking water, with minimal sample preparation; hence, it allows laboratories to increase the sample throughput, and ensure stakeholders receive information in a timely manner.

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		Centers for Disease Control and Prevention, 

Per- and Polyfluorinated Substances (PFAS) Factsheet

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Method 537: Determination of selected perfluorinated alkyl acids in drinking water by solid phase extraction and liquid chromatography/ tandem mass spectrometry (LC/MS/MS)

. (US EPA, Office of Research and Development, Washington, D.C., Version 1.1, September 2009).

Method 537.1: Determination of selected perfluorinated alkyl acids in drinking water by solid phase extraction and liquid chromatography/ tandem mass spectrometry (LC/MS/MS).

 (US EPA, Office of Research and Development, Washington, D.C., Version 1.0, November 2018).

Method 533: Determination of Per- And Polyfluoroalkyl Substances in Drinking Water by Isotope Dilution Anion Exchange Solid Phase Extraction and Liquid Chromatography/Tandem Mass Spectrometry

. (US EPA, Office of Research and Development, Washington, D.C., Version 1.0, December 2019).

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Available at https://www.denix.osd.mil/edqw/documents/manuals/qsm-version-5-3-final/. Accessed January 2nd, 2020.

Method 8327 Per- and polyfluoroalkyl substances (PFAS) using external standard calibration and multiple reaction monitoring (MRM) liquid chromatography/ tandem mass spectrometry (LC/MS/MS).

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		G. Munoz, P. Ray, S. Mejia-Avendaño, S.V. Duy, D.T. Do, J. Liu, and S. Sauvé, 

Analysis of Per- and Polyfluoroalkyl Substances (PFAS) Specified in EPA M8327 using the LCMS-8050 Triple Quadrupole Mass Spectrometer, 

Shimadzu Scientific Instruments Application Note.

 is the Environmental Marketing Manager at Shimazdu Scientific Instruments, in Columbia, Maryland. 

 is a Strategic Scientist at Shimazdu Scientific Instruments, in Columbia, Maryland. Direct correspondence to: 

The presence of per- and polyfluoralkyl substances (PFAS) in water is an important health and environmental concern. Liquid chromatography–mass spectrometry (LC–MS) has been established as the most suitable technology for monitoring these substances. A method is described, using EPA 8327, for PFAS analysis in groundwater, surface water, and wastewater.

Ruth Marfil-Vega

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