ฃ%	United States

Environmental Protectio
^1 M^k. Agency

Office of Water

www.epa.gov	January 2024

Multi-laboratory Validation Study
Report for Method 1621:

Determination of Adsorbable Organic
Fluorine (AOF) in Aqueous Matrices by
Combustion Ion Chromatography (CIC)


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U.S. Environmental Protection Agency
Office of Water (4303T)

Office of Science and Technology
Engineering and Analysis Division
1200 Pennsylvania Avenue, NW
Washington, DC 20460

EPA 821-R-24-003


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Acknowledgements

This report was prepared by S. Bekah Burket and Adrian Hanley of the Engineering and Analysis
Division within The EPA's Office of Water, with assistance from Mirna Alpizar and Harry McCarty of
General Dynamics Information Technology (GDIT).

The EPA acknowledges the support of the several organizations and individuals in the development and
validation of the draft method for the detection of adsorbable organic fluorine in aqueous samples,
including the members of the EPA's workgroup, the developers of the original procedure, the
organizations that provided the bulk samples of wastewater, and the EPA's support contractor staff who
oversaw the day-to-day operations during the study and assisted the EPA in the preparation of this report.
At a minimum, that includes the following:

S. Bekah Burket
Adrian Hanley
Jenifer Jones
Jody Shoemaker
Brian Pike
Nick Nigro
Joel Kelly
Tom Patten

Ron MacGillivray
Craig Forbes
Blaine Hoffman

EPA OW/OST/EAD	Mike Martin

EPA OW/OST/EAD	Louis Logan

EPA ORD/CESER	Steve Rhode

EPA ORD/CESER	Mahesh Pujari

Pace Analytical Services, LLC	Mirna Alpizar

Pace Analytical Services, LLC	Harry McCarty

Pace Analytical Services, LLC	Kenneth Miller

Pace Analytical Services, LLC,	William Lipps
and member of ASTM D19

Delaware River Basin Commission	Takuro Kato

Hampton Roads Sanitation District	Jayesh Gandhi
Hampton Roads Sanitation District

Hampton Roads Sanitation District
Massachusetts Water Resources Authority
Massachusetts Water Resources Authority
Los Angeles City Sanitation
General Dynamics Information Technology
General Dynamics Information Technology
General Dynamics Information Technology
Shimadzu Scientific Instrument, Inc., and member
of ASTM D19

Mitsubishi Chemical, and member of ASTM D19
Metrohm USA, Inc., and member of ASTM D19

The EPA also thanks the staff at the 11 laboratories in Table 2-1 that participated in the validation study.

Disclaimer

Mention of company names, trade names, or commercial products in this report does not constitute
endorsement or recommendation for use.

Contact

Questions or comments regarding this report should be addressed to:

CWA Methods Team, Engineering and Analysis Division (4303T)

Office of Science and Technology

U.S. Environmental Protection Agency

1200 Pennsylvania Avenue Washington, DC 20460

https ://www.epa.gov/cwa-methods

https://www.epa.gov/cwa-methods/forms/contact-us-about-cwa-analytical-methods

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Executive Summary

The goal of this project was to complete a multi-laboratory validation study of a method for determination
of adsorbable organic fluorine (AOF) in aqueous samples. AOF is a "method-defined parameter" (MDP)
meaning that the measurement result is defined solely by the method used to determine the analyte. In the
case of AOF, Method 1621, estimates an aggregate concentration of any organofluorine compounds in the
sample that are retained on the granular activated carbon (GAC) sorbent and subsequently measured by
combustion ion chromatography (CIC).

Because there are no methods for the detection of AOF in aqueous samples that are approved for use in
Clean Water Act compliance monitoring, in 2020 the US Environmental Protection Agency (EPA)
convened a workgroup of the EPA, laboratory, and utility staff, supported by contractors. The workgroup
selected a draft ASTM International standard with the primary intended use for the analysis of wastewater
for compliance monitoring. The method was validated in a single-laboratory method validation (SLV)
study. Based on the results of the SLV, EPA Method 1621 was published, a multi-laboratory method
validation (MLV) study was performed in 2023. The results of the MLV study are discussed in this
report.

The MLV study of Method 1621 met all of the EPA's goals. The study generated precision and recovery
data for aqueous matrices. Out of the 429 matrix spike results gathered during this study, 96% of the
results had recoveries between 50 and 150 percent. Only 3% of the spiked samples had recoveries below
50% and 1% were above 150%. This level of performance is suitable for an aggregate method.

However, because organofluorines are ubiquitous, the method is prone to contamination from the various
transfer lines and valves in the adsorption unit, air contamination, and background contamination from the
capping material on the granular activated carbon (GAC) columns or from the carbon itself. Additionally,
results may be biased based on the composition of organofluorines within a sample. This method is
useful to broadly assess organofluorine contamination in aqueous matrices. The method detection limit
studies demonstrated that the method can be sensitive down to 1.5 (.ig F /L when using stringent
instrument cleaning protocols and GAC columns containing low fluoride background. These points are
emphasized in the method.

There also is a need for testing for organofluorines in biosolids, soils, sediments, and fish tissue, and
portions of this method may form the basis for future studies, as technology advances and sample
preparation techniques evolve.

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Table of Contents

Acknowledgements	i

Disclaimer	i

Contact	i

Executive Summary	ii

1.	Introduction	1

2.	Identification and Selection of Laboratories	4

3.	Study Samples Selection	5

4.	Calibration and Calibration Verification	8

5.	Method Detection Limit	11

6.	Precision and Recovery	13

7.	Method Blanks	15

8.	Matrix Spike Re suits	16

9.	Calibration with an Organofluorine Standard	21

10.	Column Breakthrough	23

11.	Data Review and Validation	24

12.	Conclusions	26

13.	References	27

Appendix A - Study Plan	A-l

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List of Tables

Table 2-1. List of Participating Laboratories	4

Table 3-1. Study Sample Matrix Sources	5

Table 3-2. Water Quality Characteristics of the Study Samples	6

Table 3-3. Results for TOC, pH, Inorganic Fluoride, and Chloride	6

Table 3-4. AOF Reconnaissance Results, (ig FYL	7

Table 4-1. Initial Calibration Standards, (ig FYL	8

Table 4-2. Initial Calibration % Relative Standard Error	9

Table 4-4. Observed Calibration Verification Recovery Failures for Two Potential Acceptance

Criteria per Concentration Level	10

Table 5-1.	Pooled MDL Results (|ig F/L)	12

Table 6-1.	Calculated IPR and OPR QC Acceptance Criteria, (%)	13

Table 6-2.	Observed OPR Recovery Failures for Four Potential Acceptance Criteria	14

Table 7-1.	Method Blank Summary (fig F /L)	15

Table 8-1.	Extended Calibration Standards (|ig F /L)	16

Table 8-2.	Initial Calibration % Relative Standard Error Summary	17

Table 8-3.	Unspiked Study Sample Results, (ig F /L	17

Table 8-4.	Percent Recoveries for All Sample Spiked with PFHxS	18

Table 8-5.	Calculated MS/MSD QC Acceptance Criteria, (%)	18

Table 8-6.	Observed Matrix Spike Recovery Failures for Two Potential Acceptance Criteria	19

Table 8-7.	Recoveries for Different Standards Spiked into Sample #7	19

Table 8-8.	Relative Percent Difference (RPD) for Duplicate Spikes per Laboratory	19

Table 8-9.	Observed Recovery Failures for Two Potential Acceptance Criteria per Spiked Standard.... 20

Table 9-1.	Comparison of Inorganic vs. Organic Standard Calibrations	21

Table 9-2.	Combustion Efficiencies of Standards by Direct Combustion	22

Table 9-3.	Recoveries of Mixed PFAS Standard, Inorganic vs. Organic Calibrations	22

Table 10-1.	Observed Failure Rates for Three Potential % Breakthrough Acceptance Criteria	23

List of Figures

Figure 4-1. Comparison of % Relative Standard Error Across Calibration Models	9

Figure 4-2. Example of linear 1/x2 fit vs. quadratic 1/x2 fit	10

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1. Introduction

The goal of this proj ect was to complete a multi-laboratory validation (MLV) study of EPA Method 1621,
which is a procedure for the measurement of adsorbable organic fluorine (AOF). The method is designed
to estimate the concentration of organic fluorine in aqueous environmental samples arising from per- and
polyfluoroalkyl substances (PFAS), as well as from non-PFAS compounds such as pesticides and
pharmaceuticals.

Background

Fluorine is the thirteenth most abundant element in the earth's crust; however, it is mostly found in
inorganic forms such as fluoride salts. Only a handful of the over 3,000 naturally occurring
organohalogens contain one or more fluorine atoms covalently bonded to a carbon atom. Most
organofluorine chemicals found in the environment are man-made. Of the man-made organofluorines,
PFAS, fluorinated pharmaceuticals, and fluorinated pesticides are the most widespread. PFAS are of
particular concern due to their persistence in the environment.

PFAS include thousands of man-made chemicals that have been in production since the 1940s and are
found in a variety of consumer products such as cookware, food packaging, and water-repellent fabrics.
Some of the most common legacy sources of PFAS were from the manufacture of non-stick materials and
largely consisted of perfluorinated compounds such as perfluorooctanesulfonic acid (PFOS) and
perfluorooctanoic acid (PFOA). Even though voluntary efforts to phase out those compounds began in
2008, they are persistent in the environment and resistant to typical environmental degradation processes.
Since the phase out of PFOS and PFOA, a large variety of other polyfluorinated alkyl substances are now
in common use as alternatives to PFOS and PFOA.

Many PFAS are soluble in water, and as a result, are highly mobile in the environment. PFAS are
extensively distributed across all trophic levels and are found in soil, air, and groundwater at sites across
the globe. Most PFAS do not readily breakdown in the environment, and many are known to
bioaccumulate in aquatic and terrestrial biota, with some compounds bioaccumulating more than others.

EPA Workgroup

Various organizations and regulatory authorities at state, federal, and international levels are taking action
to address the release of PFAS to the environment. However, developing analytical methods for each
individual PFAS compound is impractical, if not impossible. Therefore, this project pursued validation of
a procedure to determine an aggregate measure of organofluorine substances in aqueous matrices as a
proxy for PFAS and other fluorinated pesticides and pharmaceuticals, known as AOF. The EPA
assembled a workgroup in 2020 led by the Engineering and Analysis Division, which is part of the Office
of Science and Technology within the Office of Water (OW/OST/EAD), to spearhead efforts for the
single-laboratory validation (SLV) and multi-laboratory validation (MLV) studies.

Method Selection

For the SLV study, the workgroup identified a draft standard from ASTM International (Reference 1)
which uses combustion ion chromatography (CIC) as the best starting point for the development of an
EPA method. EAD, in conjunction with members of the ASTM D19 Committee, prepared a hybrid study
plan/quality assurance project plan to develop and validate an EPA procedure in a single laboratory that
would be based on the original ASTM draft standard.

The SLV study took place during 2022 and tested many different PFAS and non-PFAS compounds. The
SLV study produced consistent data and many of the procedures from the draft ASTM standard were

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incorporated into the draft of Method 1621. In 2023, a new hybrid study plan/quality assurance project
plan was prepared for an MLV study of the draft method that focused mainly on PFHxS as the spike
compound for the quality control samples and the real-world matrices. In addition, a secondary smaller
study was done using one of the nine study samples spiked with PFBA, PFOS, and a mixed PFAS
standard.

Summary of the Results of the Single-laboratory Studies

Two SLV studies were performed: one by Pace Analyticalฎ Services, LLC, in their IDEA Laboratory,
and a second SLV study at EPA ORD in Cincinnati, using a CIC instrument from a different vendor. As
noted in the report on those two studies (EPA 2022), the SLV studies of the draft method met the
following EPA criteria.

1.	The method provides an aggregate response for adsorbable organofluorine from single compounds
with chain lengths between C4 and Cs as well as non-PFASfluorinated compounds using combustion
ion chromatography.

The studies generated initial precision and recovery data for aqueous matrices. IPR recoveries between
80 - 120% were achieved in most of the 30 reagent water IPR samples analyzed during this study (25 out
of 30 results, or 83%). The single-laboratory validation matrix spike results demonstrated that the method
was capable of quantifying AOF from various environmental aqueous sources with recoveries between 50
and 150%. However, the SLV report indicated potential bias for certain organofluorines.

2.	The method is sensitive enough to be used as a screening method.

Due to the ubiquitous occurrence of PFAS, almost all method blanks contained some organofluorine.
Blank results suggested AOF baseline contamination originated from the capping material used in the
adsorption columns and that it could not be removed with a nitrate pre-wash. High blank levels were
observed in certain cases. Thus, the SLV data demonstrated that the method was sensitive; however,
unless strict cleaning protocols are followed, the method can be subject to significant blank
contamination. Nonetheless, the method can reliably estimate the concentrations of organofluorines at
low part-per-billion levels.

3.	Can be implemented at a typical mid-sized full-service environmental laboratory.

Not all laboratories own an adsorption unit or a combustion ion chromatography unit; therefore, the ease
of implementation is unknown, but there is little doubt that a typical full-service laboratory could
implement this procedure. The procedure has many similarities to other EPA organohalogen methods
(e.g., Methods 1650 and 9020B). All the standards for the method are commercially available from one
or more vendors. Also, two laboratories performed similar single-laboratory validation studies, the Pace
IDEA laboratory, as detailed in the SLV report, and EPA's ORD Laboratory in Cincinnati, OH, as
summarized in Appendix C of the SLV report. Both laboratories achieved similar method performance
and results. This indicates that the method can likely be implemented in a typical mid-sized, full-service
environmental laboratory.

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Study Objectives

The main objective of the MLV study was to develop data to characterize the performance of a new
method for adsorbable organofluorine compounds. As such, EPA's goals were to:

•	Obtain data from matrices that are representative of the method's intended use

•	Obtain data from laboratories that are representative of those likely to use the approved method, but
that were not directly involved in the method development

•	Obtain feedback from laboratory users on the specifics of the draft method

•	Use study data to characterize performance of the method

•	Develop statistically derived quality control (QC) acceptance criteria that will reflect method
performance capabilities in real-world situations

The design of the MLV study is described in a formal study plan that is included as Appendix B to this
report. The design is based on the specifications in the EPA's Protocol for Review and Validation of New
Methods for Regulated Organic and Inorganic Analytes in Wastewater Under EPA's Alternate Test
Procedure Program (USEPA 2018). Briefly, the design involved:

•	Eleven laboratories, with a goal of complete wastewater data from at least six laboratories

•	Nine wastewater samples from a variety of sources

•	Determination of retention times for fluoride and separation from chloride peak

•	Multi-point calibration of the target analyte

•	Initial demonstration of capability (IDC) by each laboratory

•	Determination of method detection limits (MDLs) by each laboratory

•	Analyses of matrix spike and matrix spike duplicate (MS/MSD) samples prepared from each of the
nine wastewater samples

Results Contained in this Report

The data tables contained in the body of this report are summaries of the data.

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2. Identification and Selection of Laboratories

After completing the single-laboratory studies at the beginning of 2022, the EPA and GDIT identified
potential participants in the multi-laboratory study. By May 2022, through a combination of established
relationships, review of an EPA database of laboratory capabilities, internet searches, and telephone calls,
16 potential participants were identified, including commercial environmental laboratories, state
laboratories, and utility laboratories. The EPA identified potential Regional and emergency response
laboratories within the Agency as well.

Between April and June 2022, through emails and telephone calls, the EPA put together a list of potential
participants and ultimately targeted 15 laboratories, including those who would be contracted and those
who could volunteer. GDIT developed a contractual statement of work (SOW) covering all aspects of the
study, sent a formal solicitation to nine commercial/research laboratories, and received bids from six of
the labs. Some of the potential participants were not able to participate because of time and/or staff
constraints. The selected paid laboratories comprised five commercial laboratories and one research
laboratory, each of whom received a purchase order for participation. The EPA arranged for five
volunteer participants and used the GDIT SOW as the basis for a memorandum of understanding with
each of the volunteer laboratories. The list of the original eleven participants is provided in Table 2-1.

Table 2-1. List of Participating Laboratories

Bureau Veritas, Canada

Pace Analytical Services, Massachusetts

Enthalpy Analytical

SGS AXYS, Canada

Eurofins, Lancaster, PA

Thermo Fisher, IC Applications Lab

EPA ORD, Cincinnati, OH

Trace Elemental Instruments

EPA Robert S. Kerr Environmental Research Laboratory,
Ada, OK

University of North Carolina at Charlotte

Mandel Scientific Inc.



On November 18, 2022, immediately prior to the start of the study, the EPA held a kick-off call with all
the participating laboratories to discuss the specifics of the study. A summary of the call, including
answers to any questions raised by the participants, was circulated to all the laboratories after the call.
The EPA subsequently held conference calls from February 2023 through October 2023. Because not all
participants were able to attend every call, the discussion and any critical points were summarized and
circulated by email after each call.

Unfortunately, despite the EPA's best efforts, not all eleven laboratories were able to complete the study.
Two laboratories dropped out during the initial phase of the study due to instrument issues. Where
practical, the data from these laboratories were considered for use in the study. In the end, nine
laboratories provided full data sets for all aspects of the study. Having data from nine laboratories met
the EPA's study design goals of acquiring data from at least six laboratories for the wastewater matrices.

Other than the list of laboratories in Table 2-1 above, the remainder of this report does not associate
specific results with a named laboratory. Rather, each laboratory that completed any portion of the study
was randomly assigned an identifying number between 1 and 11.

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3. Study Samples Selection

The wastewater samples used in the study were selected to meet the specifications in the EPA's New
Method Protocol (USEPA 2018), namely, that at least one of the wastewater matrix types should have
one of the characteristics below:

•	Total suspended solids (TSS) greater than 40 mg/L

•	Total dissolved solids (TDS) greater than 100 mg/L

•	Oil and grease (O&G) greater than 20 mg/L

•	Conductivity as NaCl, greater than 120 mg/L

•	Hardness as CaCC>3, greater than 140 mg/L

GDIT obtained large volumes of nine real-world wastewaters from three major wastewater treatment
operations: Hampton Roads Sanitation District (HRSD), Los Angeles Sanitation and Environment
(LASAN), and Massachusetts Water Resources Authority (MWRA), including samples of wastewater
effluents and influents, as well as samples of aqueous matrices from indirect dischargers to those systems.
Table 3-1 lists the samples provided.

Table 3-1. Study Sample Matrix Sources

Sample Identification

Industry Type

Sample Identification

Industry Type

Sample #1

POTW-1

Sample #6

Bus Washing Station

Sample #2

Dairy Effluent

Sample #7

Pharmaceutical Effluent

Sample #3

Hospital Effluent

Sample #8

Industrial Effluent

Sample #4

Metal Finisher

Sample #9

POTW-3

Sample #5

POTW-2



Due to the total sample volume required for this project, each of the samples used for the study was
collected in bulk in multiple 10-L LDPE cubitainers. After collection, the bulk samples were shipped in
coolers with ice to GDIT's sample repository at Microbac Laboratories in Baltimore, MD, and stored in a
walk-in refrigerator at 0 - 6 ฐC.

Study Samples Characterization

Following collection of the 10-L bulk samples that were shipped to GDIT's repository, smaller aliquots of
the wastewater sources were collected and preserved following the requirements in 40 CFR Part 136,
Table II. Samples for AOF were collected in 125-mL HDPE, wide-mouth bottles, and were left
unpreserved. Aliquots of each of the nine wastewater samples were shipped on ice directly to Eurofins
Lancaster Laboratories Environment Testing (ELLE) and tested for the five water quality characteristics
listed above, as well as for Total Organic Carbon (TOC), anions, pH, and AOF.

I. Water Quality Parameters

At least two of the sample characteristics criteria were met by each of the study samples, and the EPA
deemed the samples suitable for use in the study. A summary of the sample characteristics is provided in
Table 3-2. The values in bold font indicate that the sample met the requirements for that parameter.

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Table 3-2. Water Quality Characteristics of the Study Samples



TSS

TDS

O&G

Conductivity

Hardness

Sample #

(mg/L)

(mg/L)

(mg/L)

(|jmhos/cm)

(mg/L)

1

9.4

410

ND

930

140

2

210

300

115

630

42

3

160

480

19.6

910

ND

4

30

670

ND

980

30

5

5.1

1600

2.2

3000

200

6

790

1700

27.9

3200

110

7

4.1

300

1.5

400

13

8

4.5

930

ND

1800

130

9

13

940

1.8

1800

300

ND = Not detected

II. MethodInterferent Compounds Levels

The pH and TOC levels were determined for each of the study samples. At low pH levels, inorganic
fluoride in the sample can cause high bias for AOF results, while high levels of organic carbon can lead to
negative interferences by inhibiting quantitative adsorption of halogen bound organic substances to the
activated carbon. Note that TOC was measured in these samples, instead of dissolved organic carbon,
because filtering the samples in the field was considered impractical, especially given that the samples
were collected by volunteers.

The nitrate wash employed in EPA Method 1621 has been shown to remove levels of inorganic fluoride
up to 8 mg/L; therefore, the concentration of inorganic fluoride was also determined for each of the study
samples, as well as the concentration of chloride, which can interfere with the fluoride peak in ion
chromatography when found at concentrations above 500 mg/L. With the exceptions of Sample #5 and
Sample #6, which had concentrations of chloride above 500 mg/L and required dilution prior to analysis,
the other known interferents in the bulk samples were within the method-specified limits. Results for
these parameters are summarized in Table 3-3 below.

Table 3-3. Results for TOC, pH, Inorganic Fluoride, and Chloride

Sample #

TOC (mg/L)

pH (SU)

Inorganic F (mg/L)

Chloride (mg/L)

1

10

7.5

0.62

130

2

140

5.9

0.72

46

3

110

7.1

1.1

84

4

13

9.5

2.6

47

5

10

7.5

0.57

840

6

80

6.9

1.1

970

7

32

7.2

0.55

58

8

26

8.2

5.3

350

9

18

7.0

1.1

290

Chlorine was not detected in any of the study samples; therefore, none of the bulk samples needed to be
dechlorinated.

III. AOF Reconnaissance Results

As noted in Section 1, the study design called for analyses of MS/MSD pairs for each study sample. In
order to provide information to each participating laboratory about the concentrations at which to spike
those MS/MSD pairs of each sample, the EPA sent single aliquots of each study sample to ELLE for
determination of the background AOF levels. The "reconnaissance" results from those analyses were

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used by the EPA and GDIT to develop spiking concentrations for the MS/MSD aliquots of each of the
study samples. Reconnaissance results for each study sample are summarized in Table 3-4 below. ELLE
diluted all the study samples by a factor of 2 to prevent any possible damage to their instrument;
therefore, all the detection limits for the reconnaissance results are 2.0 (.ig F /L.

Table 3-4. AOF Reconnaissance Results, |jg F /L

Sample #

Result

Sample #

Result

1

4.4

6

ND

2

ND

7

ND

3

10

8

ND

4

6.9

9

2.8

5

2.4





ND = Not detected

Preparation and Shipping of Study Samples Aliquots

The sample aliquoting and shipping activities took place during the week of June 12, 2023. GDIT
personnel retrieved the 10-L LDPE cubitainers from the sample repository and homogenized each study
sample by placing the bulk volume in a large open container and thoroughly mixing it for 10 minutes.
The samples were aliquoted as 100-mL volumes using HDPE pipettes, into 125-mL HDPE, wide-mouth
containers of the same type and lot number as the ones used for the reconnaissance analysis, and the
samples were stored at 0 - 6 ฐC until they were shipped to the participating laboratories (within at most
two days of preparation).

Due to their high levels of chloride, Sample #5 and Sample #6 were diluted 2x during the homogenization
process using PFAS-free reagent water obtained from one of the participating laboratories. For these two
samples, one of the 10-L cubitainers for each sample was homogenized with equal amounts of PFAS-free
water, and the study samples aliquoted from the diluted bulk sample.

GDIT shipped the study samples to the participating laboratories in coolers containing enough ice to
maintain the samples at a temperature < 6 ฐC for several days. Once received by the laboratories, the
samples were stored at 0 - 6 ฐC until the time of analysis. In a few situations where a laboratory did not
have enough refrigerator space, the laboratory was allowed to store the samples in a freezer at < -20 ฐC.
In those cases, the samples were allowed to fully thaw before any spiking solution was added to the
sample for analysis.

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4. Calibration and Calibration Verification

In EPA Method 1621, the ion chromatograph (IC) is calibrated using a sodium fluoride standard that is
combusted, instead of directly injected, in order to normalize the results for any possible loss of analyte
that may be caused by sample combustion. However, the calibration standards do not go through the
carbon adsorption process. The calibration curve is based on the concentration of fluoride ion in the
standard (i.e., |ag F"/L), rather than the mass or concentration of a specific fluorine-containing compound.

Two brands of IC instruments, Dionex Integrion HPIC and Metrohm 930 IC Compact Flex, were used
during this study to encompass the instruments that most laboratories would be using during typical
sample analyses. To minimize potential variability in the results that might be caused by differences in IC
column types, the laboratories were required to use an IC column model from the same vendor as their
instrument. Therefore, laboratories that used the Dionex IC, were required to use a Dionex IonPac AS24,
2x250 mm IC column, while laboratories that used the Metrohm IC were required to use a MetroSep A,
Supp 5, 4x150 mm IC column. GDIT provided the appropriate IC columns to those laboratories that were
using a different IC column from the ones required for the study.

Initial Calibration

The IC instruments were initially calibrated using a series of six standards designated as CS-1 to CS-6,
with a concentration range from 1.0 to 50.0 (.ig FYL. Table 4-1 lists the concentrations of those
calibration standards.

Table 4-1. Initial Calibration Standards, |jg FVL

Analyte

CS-1

CS-2

CS-3

CS-4

CS-5

CS-6

Fluoride

1.0

2.0

5.0

10.0

25.0

50.0

All eleven laboratories completed the calibration portion of the MLV study. Each of their calibrations
was evaluated using four different model fits to see which would be the best approach to calibration. The
four models were:

•	Linear fit with 1/x concentration weighting,

•	Linear fit with 1/x2 concentration weighting,

•	Quadratic fit with 1/x concentration weighting, and

•	Quadratic fit with 1/x2 concentration weighting.

The calibration models were not forced through zero. Each laboratory was asked to calculate the percent
relative standard error (%RSE) to assess the fit of their calibration curve for each model, using the
equation below. The software for some of the instruments could not calculate the %RSE based on the
equation used by the EPA. In those instances, the laboratories calculated the %RSE using a spreadsheet
provided by GDIT with the correct equation.

I

' -i2

X;

n — p

i=i

%RSE = 100 X

M

where:

x, = Nominal concentration (true value) of each calibration standard
x'i = Measured concentration of each calibration standard
n = Number of standard levels in the curve
p = Type of curve (2 = linear, 3 = quadratic)

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Table 4-2 summarizes the %RSEs of the initial calibrations performed by the participating laboratories.
Laboratory 7 added one extra calibration point and extended their initial calibration up to 100 juig F"/L.
The extended calibration for Laboratory 7 gave them slightly lower %RSEs for all four fits when
compared to the %RSEs calculated when their curve was cut off at 50 i.ig F /L. Their lower %RSEs were
comparable to the %RSEs from the remaining 10 laboratories.

Table 4-2. Initial Calibration % Relative Standard Error

Calibration Fit

%RSE

Mean (n=11)

Min

Max

Linear with 1/x weighting

10.3

2.5

22.8

Linear with 1/x2 weighting

7.1

2.1

12.8

Quadratic with 1/x weighting

5.3

0.07

15.1

Quadratic with 1/x2 weighting

4.1

0.22

11.8

Figure 4-1 shows the %RSE for each of the laboratories for each of the calibration fits. The highest
%RSEs for the linear fits were observed for Laboratories 1, 3, 4, 7, and 8. Laboratories 4 and 7 had a
%RSE > 10% for the quadratic with 1/x weighting calibration fit, while the rest of the laboratories had a
%RSE well below 10% for the same fit. As the fit was moved to quadratic with 1/x2 weighting, only
Laboratory 4's %RSE remained above 10%. With the exception of Laboratory 4, most calibrations
showed better model fit (e.g., lower %RSE) when using a quadratic with 1 /x3 weighting fit.

Comparison of Calibration Curve Fits

25

r 20

ro
"D

c

O)
>

01
0ฃ

15

10

Linear 1/x

Linear l/x2	Quadratic 1/x

Calibration Curve Fit

Quadratic l/x2

Lab

1

Lab

2

Lab

3

Lab

4

Lab

5

Lab

6

Lab

7

Lab

8

Lab

9

Lab

10

Lab

11

Figure 4-1. Comparison of % Relative Standard Error Across Calibration Models

Although %RSEs for the linear fit with 1/x concentration weighting were < 20% for 10 of the 11
laboratories, visual examination showed that the highest point of the calibration curve did not fall along
the curve, whereas that point did fall along the curve for the quadratic fit with 1/x2 concentration
weighting, as shown in the example in Figure 4-2 below. Based on the %RSE results and visual
inspection of the curves, GDIT and the EPA chose a quadratic with 1/x2 weighting fit for the analysis of
samples for this study and relayed that requirement to each of the laboratories in the study.

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Figure 4-2. Example of linear 1/x2 fit vs. quadratic 1/x2 fit

In addition to requiring the quadratic calibration fit, prior to analyzing study samples, EPA required the
laboratories to extend their calibration range to 100 (.ig F /L. The discussion for the extended calibration
results is included with Section 8 of this report.

Calibration Verification

A calibration verification (CV) standard was analyzed at the beginning and at the end of each analytical
batch. As with the ICAL, the CV standards were combusted, but not adsorbed onto the carbon columns.
Verification was performed at two concentrations, 2 (.ig F /L and 25 (.ig F /L (200 ng and 2,500 ng). A
total of 118 calibration verification standards were analyzed during the study. The recoveries ranged
from 80.2% to 135.6%, with an average recovery of 101.3%. Table 4-3 summarizes the recoveries
observed for both concentrations. The highest recovery for the low-level CV was observed for
Laboratory #8, while the highest recovery for the mid-level CV was observed for Laboratory #1.

Table 4-3. Observed Recoveries for Calibration Verifications per
Concentration Level

Calibration
Verification

Cone.
(M9 F /L)

# Results

Recovery (%)

Mean

Min

Max

Low-level

2

59

100.98

85.5

135.6

Mid-level

25

59

101.58

80.2

122.1

GDIT performed a /'-test that confirmed that the mean recoveries for the two spiking levels were not
significantly different, while an /' -test indicated that the variance in the mid-level recoveries was half that
seen for the low-level recoveries. Table 4-4 summarizes the observed failures for the calibration
verification using two recovery ranges for each concentration level. For the recovery range of 90 - 110%,
four recoveries for the low-level and two recoveries for the mid-level failed the lower limit (LL), while
seven recoveries for the low-level and three recoveries for the mid-level failed the upper limit (UL). The
observed failures are equivalent to an 18.6% failure rate for the low-level CV and 8.5% failure rate for the
mid-level CV. When the recovery range is increased to 80 - 120%, only one recovery for each
concentration level falls outside the upper limits, which is equivalent to a 1.7% failure rate. The two
failing CV results are from Laboratories #1 and #8. Based on these failure rates, the interim recovery of
80 - 120% in the draft method will be retained and will apply to both CV concentrations.

Table 4-4. Observed Calibration Verification Recovery Failures for Two
	Potential Acceptance Criteria per Concentration Level	

Calibration

Cone.

Criteria 1

Criteria 2

Verification

(M9 F /L)

LL 90%

UL 110%

LL 80%

UL 120%

Low-level

2

4

7

0

1

Mid-level

25

2

3

0

1

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5. Method Detection Limit

As part of the MLV study, the EPA required that the laboratories determine their method detection limit
(MDL) for AOF. For the purpose of the study, the MDL was determined using the revised MDL
procedure Definition and Procedure for the Determination of the Method Detection Limit, Revision 2,
December 2016, EPA 821-R-16-006, and also included at 40 CFR Part 136, Appendix B.

The revised procedure defines the MDL as:

"... the minimum measured concentration of a substance that can be reported with 99%
confidence that the measured concentration is distinguishable from method blank results. "

The procedure consists of two parts: determination of the MDL based on method blanks (MDLb), and
determination of the MDL based on spiked samples (MDLS). Both MDLb and MDLS are determined in a
reference matrix, using at least seven replicates prepared and analyzed on three non-consecutive days.

The MDLb is calculated as:

MDLb — X + t(n-l,l-cc=0.99)Sb

where:

X = Mean of the method blank results (use zero in place of the mean if the mean is
negative)

t(n l j a = 0 99) = Student's lvalue appropriate for the single-tailed 99th percentile t statistic and a
standard deviation estimate with n-1 degrees of freedom.

Sb = Sample standard deviation of the replicate method blank sample analyses.

Note: The equation above is used when all the method blanks for an individual analyte give numerical
results. If some (but not all) of the method blank results give numerical results, then the MDLb is
set to be equal to the highest method blank result.

The MDLS is calculated as:

MDLS — t(n_i7 l-oc=0.99)^s

where:

^(n-l, 1-a = 0.99)

t(n-i i-a = 0 99) = Student's /-value appropriate for a single-tailed 99th percentile t statistic and a standard

deviation estimate with n-1 degrees of freedom.

Ss = Sample standard deviation of the replicate spiked sample analyses.

For MDL determinations in this study, the reference matrix used was PFAS-free reagent water. After
both an MDLb and MDLS were calculated, each laboratory set their initial MDL to the greater of the
MDLb and MDLS values.

AOF MDL Determination

Method 1621 tests for the aggregate concentration of organic fluorine compounds which has been
adsorbed onto the granular activated carbon. Because there are numerous PFAS and non-PFAS
organofluorine compounds found in the environment, it would be impossible to determine an MDL that
would include every compound. During the SLV study, the EPA ORD investigated the recoveries of
various individual PFAS analytes and found that PFHxS showed consistent recoveries ranging from 99%

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to 106%. Therefore, GDIT and the EPA specified PFHxS as the compound to be used by all of the MLV
laboratories for their MDL studies.

One of the first steps in the EPA MDL procedure is for the laboratory to make an estimate of the MDL.
The laboratories were directed to consider the limitations of the instrument, more specifically the
limitation presented by the observed GAC background, when estimating their initial MDL. GDIT and the
EPA directed the laboratories to set the estimated initial MDL as three times the standard deviation of the
initial background observed for the GAC columns. The spike levels were then established to be
approximately between 2 and 10 times the estimated MDL, at 5.0 (.ig FYL.

Due to a lack of reproducibility of their calibration verifications and after several attempts at instrument
troubleshooting, Laboratory 4 had to drop out from the study after the initial calibration. The remaining
10 laboratories proceeded with the MDL study by preparing and analyzing at least seven replicate method
blanks and seven replicate spiked samples. Laboratory 6 analyzed nine method blanks and nine spiked
sample replicates while Laboratory 8 analyzed eight method blanks and eight spiked sample replicates.
This approach yielded 73 results for blanks and 73 results for spiked samples.

Laboratory 1 was the only laboratory that did not have a numerical value for each of the seven blank
replicates, and therefore the highest blank value was used by that laboratory for their MDLb. The initial
MDL estimates for six of the laboratories were established from the MDLb, due to the high background
levels present in the GAC columns. GDIT determined the pooled MDL by using the average blank
concentration of all the labs plus the left-tailed inverse of the Student's t distribution times the pooled
highest standard deviation of each laboratory from either the blanks or the spiked samples. The results
are summarized in Table 5-1 below.

Table 5-1. Pooled MDL Results (|jg F /L)

# Labs

Pooled MDLs

Max. MDLs

# MDLb

Max. MDLb

10

1.5

2.9

6

3.2

Because many organofluorine compounds are prone to surface adsorption, analytical results between
different manufacturer's adsorption apparatus may not be comparable due to differences in the numbers
and areas of surfaces (e.g., tubing, syringes, etc.) with which the sample comes in contact during sample
loading onto the GAC. For that reason, GDIT and the EPA compared the MDL study results for the two
adsorption instruments used in the study, Analytik-Jena APU sim and the Mitsubishi TXA-04 units, to
determine if there was a consistent difference that could be attributed to the instrument configuration. A
Student's /-test and an Analysis of Variance (ANOVA) were used to compare the MDLS and MDLb for
each system and both tests showed no statistical difference between the adsorption units.

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6. Precision and Recovery

As part of the method validation effort, the EPA required that each laboratory perform an initial precision
and recovery (IPR) study. Each IPR study consisted of a set of four reagent water aliquots, spiked at
approximately 25 (.ig F /L with PFHxS. The laboratories calculated and reported the mean concentration,
mean recovery, the standard deviations of the recoveries, and the relative standard deviations (RSDs) of
the recoveries for each set of four IPR aliquots.

Each laboratory also included one ongoing precision and recovery (OPR) sample with each batch of study
samples prepared and analyzed. The OPR aliquots were spiked at the same concentration as the IPR
aliquots. Each laboratory calculated and reported the recovery of the spiked analytes in each OPR
aliquot.

One of the EPA's objectives in conducting the multi-laboratory validation study was to generate data
from which to derive multi-laboratory QC acceptance criteria for the various performance tests in the
method, or to evaluate the ability of the method to meet commonly applied acceptance criteria for some
performance tests. In this study, GDIT calculated QC acceptance criteria for IPR and OPR tests based on
the procedures and equations in Appendix G of the Protocol for Review and Validation of New Methods
for Regulated Organic and Inorganic Analytes in Wastewater Under EPA's Alternate Test Procedure
Program (USEPA 2018), with modifications to account for the actual number of laboratories, samples,
and replicates in the study. In order to yield a more complete dataset, the IPR and OPR data were
combined when calculating the criteria, using different formulae to generate IPR- and OPR-specific
criteria that account for how they would be evaluated in practice (i.e., mean recovery and RSD of four
IPR replicates, and OPR recovery evaluated on an individual basis). Briefly:

•	The QC acceptance criterion for recovery in the IPR test was calculated by constructing a prediction
interval around the mean percent recovery, using the Student's t value, with the degrees of freedom
determined using the Satterthwaite estimation procedure (Satterthwaite, 1946), using the calculated
between- and within-laboratory variance components, weighted based on future IPR usage (assuming
means of four replicates per laboratory).

•	The maximum acceptable RSD for the four IPR aliquots was calculated as an upper confidence limit
around the observed RSD of the results from all the laboratories. The RSDipr (computed as s„
divided by X) is multiplied by the square root of a 95th percentile F value with 3 degrees of freedom
in the numerator and nj-m degrees of freedom in the denominator, where m = the number of
laboratories, and nT is the number of data points across all laboratories.

•	The QC acceptance criterion for recovery in the OPR test was calculated by constructing a prediction
interval around the mean percent recovery, using the Student's t value, with the degrees of freedom
determined using the Satterthwaite estimation procedure, using the calculated between- and within-
laboratory variance components, weighted based on future OPR usage (assuming a single replicate
per laboratory).

The calculated IPR and OPR QC acceptance criteria for AOF are presented in Table 6-1. The statistically
determined recovery ranges for the IPR and OPR reflect the variability within each laboratory, as well as
the variability across the laboratories that completed that portion of the study. Ten laboratories finished
the IPR part of the study; however, only nine laboratories finished the study sample analysis portion and
provided OPR results. The recovery ranges combined the results for both the IPR and the OPR results.

Table 6-1. Calculated IPR and OPR QC Acceptance Criteria, (%)

# Labs

# Results

IPR

OPR Range

Range for Mean

Max RSD

10

97

79.7-114.3

14.7

74.7-119.4

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The IPR is assessed based on the mean of the four IPR replicates; therefore, results for individual IPR
aliquots may fall outside the established range. All mean recoveries fell within the calculated IPR mean
range with the exception of Laboratory 7, which had a mean recovery of 117.1 %. The calculated
maximum RSD was well below the method interim requirement of 20%. Three OPR recoveries fell
outside the calculated OPR range, two recoveries for Laboratory 1 and one recovery for Laboratory 10.

Table 6-2 summarizes the observed failure rates for the OPR using four possible recovery ranges based on
rounding up the calculated range above to multiples of 5% or 10%.

Table 6-2. Observed OPR Recovery Failures for Four Potential Acceptance Criteria



Observed Failures



Criteria 1

Criteria 2

Criteria 3

Criteria 4

Total # Results

LL 85%

UL 115%

LL 80%

UL 120%

LL 75%

UL 125%

LL 70%

UL 130%

57

5

4

2

3

0

3

0

2

The criteria in Table 6-2 are arranged with the tightest criteria on the left, and increasingly wider criteria
to the right. For an acceptance criterion of 85 - 115%, nine recoveries from six different laboratories, or
15.8% of the results, fell outside the limits. For an acceptance criterion of 80 - 120%, five recoveries
from three laboratories, or 8.8% of the results, fell outside the limits.

For an acceptance criterion of 75 - 125%, only the three recoveries from Laboratories 1 and 10 fell
outside the range, reducing the failure rate to 5.3%. For an acceptance criterion of 70 - 130%, two
recoveries, one from Laboratory 1 and one from Laboratory 10, or 3.5% of the results, fell outside the
range.

Based on the results, the EPA established an acceptance limit of 80 - 120% for the mean IPR recovery,
with an RSD < 20%, and retained the interim limit of 70 - 130% for the OPR.

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7. Method Blanks

Each laboratory analyzed two method blanks with each analytical batch of study samples (one at the
beginning of the analytical sequence and one at the end). The result from one closing method blank from
Laboratory 11 had to be dropped because the bottom GAC column was lost during instrumental analysis,
yielding a total of 114 blank results from nine laboratories. The descriptive statistics for those 114 blanks
are summarized in Table 7-1 below and do not include any method blanks associated with the IPR and
MDL studies.

The draft of EPA Method 1621 that was used for the method validation study stated that the method
blanks should not exceed 5 (.ig F-/L, and preferably, should be less than 3 (.ig F-/L. For that reason, GDIT
evaluated the method blanks using both criteria. The results showed that 107 of 114 method blanks were
< 3 jj.g F/L, five results were between 3 and 5 (.ig FYL, and two method blanks were > 5 (.ig FYL limit.
Two of the blanks that were between 3 and 5 (.ig F /L were from Laboratory 2, two from Laboratory 8,
and one was from Laboratory 10. The two blanks with results above 5 (.ig F /L were from Laboratory 2.
The contamination in the blanks from Laboratory 2 may be due to the fact that the laboratory did not store
the GAC columns segregated from possible fluoride sources at the start of the project. A new lot of GAC
columns was provided to the laboratory for the remainder of the study. The two high method blanks
affected the results for all the unspiked samples for Laboratory 2, with the exception of Sample #3, which
was prepared and analyzed in a different batch. Because the affected sample results were all < 5x the
associated blank values, there are no means by which to ascertain whether the presence of the analyte may
be attributed to contamination only. However, because the unspiked sample results were comparable to
the results of the unspiked samples for the other laboratories, none of the results were excluded from the
study due to contamination. Higher blank values were consistently seen from Laboratories 2, 8, and 9 for
different GAC column lot numbers, compared to the other six laboratories.

Table 7-1. Method Blank Summary (|jg F /L

# Blanks







Std



# Below

# Between

# Above

Analyzed

Minimum

Maximum

Mean

Dev

Median

3 M9 F /L

3 and 5 |jg F /L

5 |jg f-/l

114

0.0

10.45

1.37

1.34

0.97

107

5

2

GDIT calculated a QC acceptance criterion for the method blanks of < 4.0 (ig F /L using the mean plus
two standard deviations of the blank measurements. Of the 114 method blank results in the study, 97%
fell below the calculated limit.

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8. Matrix Spike Results

Generating the most useful matrix spike data requires knowledge of the background levels of analytes in
the unspiked samples. Spiking levels should not be unrealistically high, nor should they be so low that the
spiked amount is difficult to discern from the background concentration in the original sample. Rather
than waiting for each participating laboratory to analyze all the unspiked samples, and then develop a
customized spiking scheme based on those results, the EPA and GDIT used the reconnaissance analysis
results discussed in Section 3 to develop sample-specific spiking levels for all the samples in the study.
The EPA determined that the low spike level should be between 2x and lOx the background AOF level of
each of the study samples, and the high spike level should be at least double the concentration of the low
spike level. This spiking scheme design gave the possibility of collecting up to 154 data points at the low
end of the calibration range, up to 264 data points around the mid-point of the calibration, and up to 110
data points at the high end of the calibration range.

The results discussed in this report include 124 data points at the low end of the calibration range, 215
data points around the mid-point, and 90 data points at the high end of the calibration, for a total of 429
spike recoveries.

GDIT directed the laboratories to analyze the full sample volume that was provided and were instructed
not to dilute the samples prior to analysis. The laboratories calculated all results based on a nominal 100-
mL sample volume and not the individual volumes in each sample bottle.

Three study samples, #2, #3, and #6, had TSS levels above 100 mg/L and required the use of quartz wool
plugs as pre-filters for both the unspiked and spiked analyses. The quartz wool plugs were combusted
separately from the top and bottom GAC columns. Results for the quartz wool were added to results from
the top and bottom GAC columns and are reported in the summary tables below. The laboratories also
were required to combust quartz wool blanks with each analytical batch that contained the samples
requiring quartz wool pre-filters. The quartz wool blank consisted of a small plug of quartz wool placed
inside an empty GAC glass column (to make the amount of glass wool for the blank as close as possible
to the amount used for the samples), rinsed with 25 mL of 0.01M sodium nitrate followed by 20 mL of
reagent water. The quartz wool blank columns were not connected in tandem to the blank GAC columns
to prevent the transfer of any possible contamination from the quartz wool to the blank GAC columns and
cause a possible bias when subtracting the method blank from samples on the same preparation batch that
did not require the use of quartz wool. The quartz wool blank result was added to the result of the first
method blank (top and bottom GAC columns) from the preparation batch and the summed result was
subtracted from the total result for those three samples to compensate for any background fluorine that
may have been present in the quartz wool.

Extended Calibration Results

Some of the samples had background AOF concentrations high enough that the high spike level would
exceed the calibration range set at the beginning of the study; therefore, the laboratories were required to
perform an extended calibration, as shown in Table 8-1.

Table 8-1. Extended Calibration Standards

Analyte

CS-1

CS-2

CS-3

CS-4

CS-5

CS-6

CS-7*

CS-8*

Fluorine

1.0

2.0

5.0

10.0

25.0

50.0

75.0

100.0

H9 F /L)

*New standards added to the curve

The individual %RSEs were all below 20% with the exception of Laboratory 8. This laboratory's
extended curve had a %RSE of 20.7%. Because their lowest point was consistently biased high, the
laboratory was allowed to drop the lowest point of their curve (CS-1) after several failed attempts at

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achieving a %RSE < 20%. This change allowed their %RSE to decrease to 6.1% making the maximum
observed %RSE of the quadratic 1/x2 fit for the extended calibration in any of the laboratories below
10%. A summary of the %RSE results is presented in Table 8-2.

Table 8-2. Initial Calibration % Relative Standard Error Summary

Calibration Fit

Mean %RSE

Min %RSE

Max %RSE

Quadratic 1/x2

4.5

1.1

9.5

Unspiked Sample Results

GDIT directed the laboratories to analyze the study samples unspiked, and to use those results to calculate
their spiked sample recoveries. The results for the unspiked sample analyses for the nine laboratories,
plus the original reconnaissance results, are summarized in Table 8-3.

Table 8-3. Unspiked Study Sample Results, |jg F7L

Sample #

Lab 1

Lab 2

Lab 3

Lab 5

Lab 7

Lab 8

Lab 9

Lab 10

Lab 11

Recon

1

11.6

13.8

5.8

3.6

9.8

2.8

2.1

4.1

4.1

4.4

2

10.1

ND

4.1

ND

ND

ND

ND

ND

ND

ND

3

16.6

14.2

13.1

9.5

12.4

8.7

8.5

8.7

11.9

10.0

4

15.1

12.8

19.6

7.4

8.4

9.9

6.1

7.3

3.8

6.9

5

2.4

ND

ND

ND

ND

ND

ND

3.4

ND

2.4

6

9.8

16.1

11.8

4.2

5.0

5.5

ND

4.9

ND

ND

7

8.6

ND

ND

ND

ND

ND

ND

ND

ND

ND

8

7.2

ND

2.4

ND

ND

ND

ND

ND

ND

ND

9

4.7

ND

3.2

2.3

2.8

ND

ND

6.9

ND

2.8

ND = Not detected at the laboratory's MDL

Results for the unspiked samples from most of the laboratories were similar to those found during the
reconnaissance analysis. In general, Laboratory 1 had the highest results for the samples. Laboratories 1,
2, and 3 had the highest results for Samples #4 and #6.

Matrix Spike Results

GDIT directed the laboratories to analyze matrix spike aliquots for each of the nine real-world wastewater
matrices. The matrix spike analyses were done in two parts. For Part 1, the laboratories were asked to
spike separate aliquots of each of the nine study samples at two levels using linear PFHxS, and each spike
level was prepared and analyzed in duplicate, i.e., a matrix spike (MS) and matrix spike duplicate (MSD).
For Part 2, the EPA selected Sample #7 and GDIT directed the laboratories to prepare three sets of
MS/MSD aliquots spiked at two levels, using PFBA, PFOS, and a mixed PFAS standard. The mixed
PFAS solution contained 30 PFAS compounds with carbon chains ranging from C4 to C14 and had
eleven perfluoroalkyl carboxylic acids, seven perfluoroalkyl sulfonates (linear and branched), three
fluorotelomer sulfonates, two ether sulfonic acids, two perfluorooctane sulfonamidoacetic acids (linear
and branched), two per- and polyfluoroether carboxylic acids, and three perfluoroalkane sulfonamides.
The results from both parts are discussed in detail below.

Part 1 Study Samples Spiked with PFHxS

GDIT calculated the mean recovery of each spiked sample across nine laboratories, along with the
minimum and maximum observed values. The values are presented in Table 8-4.

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Table 8-4. Percent Recoveries for All Sam

jle Spiked with PFHxS

Sample #

# of Results

Nominal Spike
Cone (|jg FVL)

% Recovery

RSD

(%)

Mean

Min

Max

1

18

30

92.4

74.9

108.0

12.4

18

60

96.9

89.1

110.8

5.8

2

18

10

102.8

45.2

181.5

35.8

18

30

95.7

70.0

113.7

11.2

3

18

30

85.7

72.8

99.8

9.5

18

60

83.8

56.3

101.2

14.7

4

18

30

95.7

55.4

139.5

21.5

18

60

93.0

78.0

103.5

7.1

5

18

30

98.1

70.6

113.8

10.3

18

60

99.5

92.3

109.1

5.6

6

16

10

101.6

46.1

175.4

32.6

18

30

94.4

63.2

112.3

15.3

7

18

10

101.3

71.9

146.5

15.8

18

30

97.7

85.6

107.5

7.5

8

18

10

99.1

82.4

123.6

9.3

17

30

99.7

91.2

114.2

5.7

9

18

30

97.0

79.9

122.5

10.7

18

60

98.4

85.4

117.2

8.2

For Samples #6 and #8, GDIT dropped three results, either due to sample loss during instrumental
analysis or known contamination. All the mean recoveries in Table 8-4 fall within the range of 60 to
120%. Of the 321 individual recoveries, seven were below 60%, and 13 were over 120%, which is
equivalent to 6.2% failure rate.

The within-sample RSDs were < 20% for most of the samples, with the exception of Samples #2, #4, and
#6, at the lowest level spike. The variability was driven mainly by results from Laboratories 1 and 8. The
overall RSD for the entire set of spikes was 16.4%.

GDIT performed an ANOVA test which showed that there was a statistical difference between the spike-
level groups. To determine which of the groups was different, GDIT performed a Tukey HSD test at the
5% significance level. The Tukey HSD test confirmed that the recoveries at the lower end of the
calibration curve (10 (ig F7L) were statistically different from the recoveries at the higher end of the
curve.

GDIT used the results of the MS/MSD analyses performed in this part of the study to calculate the
MS/MSD QC acceptance criteria presented in Table 8-5. One point from the MS/MSD results was
dropped from the calculation of the acceptance criteria because the corresponding aliquot from that pair
was lost due to instrument failure; therefore, there were 320 data points used in this calculation. Of the
320 total points used in the statistics, nine results failed the lower recovery limit, and seven results failed
the higher recovery limit of the calculated range, which is equivalent to 5% of the data.

Table 8-5. Calculated MS/MSD QC Acceptance Criteria, (%)	

# labs

Total # of Points

Recovery Range

Maximum RPD

9

320

65.0- 127.5

34.5

Table 8-6 summarizes the observed failures for the matrix spikes using two acceptance criteria. For the
recovery range of 60 - 120%, seven recoveries failed the lower limit (LL), and 13 recoveries failed the
upper limit (UL). When the recovery range is increased to 50 - 150%, two of the recoveries fall below
50% and four recoveries, from Laboratories 7 and 11, are above 150%, which corresponds to 1.9% of the
data.

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Table 8-6. Observed Matrix Spike Recovery Failures for Two
	Potential Acceptance Criteria	

# Results

Criteria 1

Criteria 2

LL 60%

UL 120%

LL 50%

UL 150%

320

7

13

2

4

Based on the failure rates for the two potential recovery ranges, the EPA established a recovery range for
MS/MSD of 50 - 150% and a Relative Percent Difference (RPD) limit of <30% for EPA Method 1621.

Part 2 Sample #7 Spiked with Various PFAS Compounds

Six sets of MS/MSD aliquots were prepared from Sample #7 using three different spiking solutions and
two spiking levels that matched those used with PFHxS in Part 1 of the study for this sample. Results for
nine laboratories are presented in Table 8-7 below.

Table 8-7. Recoveries for Different Standards Spiked into Sample #7

Spiking
Standard

# of
Results

Nominal Spike
Cone. (|jg FVL)

% Recovery

RSD

(%)

Mean

Min

Max

PFBA

18

10

64.1

41.0

86.9

23.9

18

30

63.6

22.8

107.8

27.5

PFOS

18

10

93.6

41.1

145.0

23.6

18

30

84.5

33.3

102.3

23.8

Mixed PFAS

18

10

83.1

36.9

107.7

22.6

18

30

83.1

53.7

95.2

11.7

The within-sample RSDs were > 20% for PFBA and PFOS and for the low-level mixed PFAS spike,
indicating higher variability among the laboratories. The variability was mainly driven by recoveries
from Laboratories 1, 2, 7 and 9.

The variability within each laboratory's spiked duplicates is presented in Table 8-8. Some laboratories
had better control of their replicates, while others had wildly different results between their duplicates.
Laboratories 1, 7 and 9 had the highest variability in their MS/MSD results, regardless of the spike level
or standard used. This may be due to a lack of familiarity of these laboratories with the method and/or
instrumentation. Additionally, percent breakthrough was above 50% for PFBA for Laboratory 1.
Laboratory 2 had variability in the low-level aliquots spiked with PFOS, with 76% and 121% recoveries
for the MS/MSD pair, resulting in an RPD of 45.9% for that pair.

Table 8-8. Relative Percent Difference (RPD) for Duplicate Spikes per Laboratory

Standard

Nominal
Cone.
(H9 F /L)

RPD (%)

Lab 1

Lab 2

Lab 3

Lab 5

Lab 7

Lab 8

Lab 9

Lab 10

Lab 11

PFBA

10

53.9

7.4

8.4

10.5

1.5

10.9

5.4

2.4

11.8

30

6.9

13.4

3.8

3.7

48.4

1.3

79.4

3.7

0.7

PFOS

10

48.7

45.9

4.9

2.1

12.2

2.3

42.4

9.2

15.7

30

76.3

2.8

3.0

3.4

95.7

20.7

4.9

1.8

18.9

Mixed PFAS

10

35.8

4.4

14.5

1.3

21.8

4.7

5.6

0.3

12.4

30

5.3

3.3

1.8

0.3

2.8

1.9

34.7

0.0

9.2

Table 8-9 summarizes the observed failures for the Phase 2 matrix spikes using two different acceptance
criteria for each individual spiked standard. For the recovery range of 60 - 120%, 21 recoveries failed the
lower limit (LL), and two failed the upper limit (UL). When the recovery range is widened to 50 - 150%,
11 recoveries fall below 50% and none are above 150%.

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Table 8-9. Observed Recovery Failures for Two Potential Acceptance
	Criteria per Spiked Standard	

Standard

# Results

Criteria 1

Criteria 2

LL 60%

UL 120%

LL 50%

UL 150%

PFBA

36

15

0

7

0

PFOS

36

3

2

3

0

Mixed PFAS

36

3

0

1

0

GDIT performed an ANOVA test which showed that there were differences between the recoveries for
the three different spiking standards. Further, GDIT performed a Tukey HSD test which confirmed the
recoveries for PFBA were different from the recoveries for the other two standards. The low recoveries
observed for PFBA may be due to the fact that short-chain PFAS (four carbons or less) tend to be poorly
retained on GAC. Low recoveries for PFBA also were observed during the single-laboratory method
validation study. The percent breakthrough for this compound was consistently above 50%, confirming
its low adsorption on GAC. There were three recoveries < 50% for PFOS, for Laboratories 1, 7, and 9.
For Laboratory 7, the low recovery may be due to the lab accidentally spiking that sample at the low-
spike level, based on the other results observed for PFOS from this lab.

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9. Calibration with an Organofluorine Standard

Different fluorine-containing compounds have different combustion efficiencies. Thus, there was a
concern that using inorganic standards such as sodium fluoride for instrument calibration may under- or
overestimate the concentrations of organofluorine compounds because those compounds have a wide
range of combustion efficiencies. To determine if the type of standard, inorganic vs. organic, used in the
calibration may cause such an estimation bias for AOF, Laboratory 3 was directed to perform a special
study to compare if AOF results may be biased based on the type of fluoride standard used for instrument
calibration.

Note that the use of inorganic fluoride allows for wider calibration ranges to be prepared using a
combustion volume of 0.2 mL (lower combustion volumes may be used if the working calibration
standards have higher concentrations). In contrast, because the organic fluoride standards have a
concentration of 50 (ig/mL (approximately 28 (.ig F"/mL), the analyst must combust 0.35 mL of the
standard for the 100 (.ig F7L calibration point. Using such higher volumes of liquid in a combustion boat
designed to combust solids can lead to splattering within the instrument, which can cause internal
contamination. Also, being a simple fluoride salt, sodium fluoride is less costly and thus a more
economical option for instrument calibration than a PFAS standard.

Comparison of Calibrations Using Organofluorine Standards

In the special study, Laboratory 3 calibrated their IC instrument with PFHxS, using a series of six
calibration standards designated as CS-1 to CS-6. For ease of comparison with the calibration performed
using sodium fluoride, the PFHxS standards were prepared with as close to the same fluoride
concentrations as were used in that initial calibration. The PFHxS standards were combusted directly
without carbon adsorption, as was done with the sodium fluoride standard. Because the inorganic
fluoride calibration showed a quadratic model was a better fit, the organofluorine calibration used a
quadratic fit, with 1/x2 weighing, not forced through zero. The %RSE was calculated to assess the model
fit, as was done with the inorganic initial calibration (Section 4.0). Table 9-1 compares the recoveries and
%RSE of both calibrations from Laboratory 3.

Table 9-1. Comparison of Inorganic vs. Organic
Standard Calibrations

Calibration Std

Concentration
(M9 F /L)

Recovery (%)

NaF

PFHxS

CS-1

1.0

99.0

97.8

CS-2

2.0

102.7

105.0

CS-3

5.0

98.9

99.9

CS-4

10.0

98.8

98.5

CS-5

25.0

100.7

96.7

CS-6

50.0

99.9

102.6

%RSE

2.0

4.1

The model fit of both calibrations was well within the %RSE requirement of < 20% and no systematic
differences were observed between the two calibrations.

Combustion Efficiencies of Organofluorine Standards

During the single-laboratory validation study, the combustion efficiencies of several organofluorine
standards were tested against an inorganic fluoride calibration. For the multi-laboratory validation,
Laboratory 3 was asked to perform direct combustion, without carbon adsorption, of four of the standards

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used in the study, tested against an organofluorine calibration curve, to see if there was any difference in
the combustion efficiencies.

Table 9-2. Combustion Efficiencies of Standards by Direct Combustion

Standard

Inorganic Calibration

Organic Calibration

Mass (ng F )

% Recovery

Mass (ng F )

% Recovery

NaF

1000

99.5

1000

95.9

PFBA

302

48.6

304

98.3

PFOS

653

108.8

667

93.4

Mixed PFAS

742

94.6

745

99.2

Based on the % Recovery data in Table 9.2 for the organofluorine calibration, direct combustion of PFBA
had an efficiency two-fold higher than with an inorganic fluoride calibration (i.e., 98.3% versus 48.6%).

Results for Matrix Spikes

Sample #7 was selected by the EPA to be used for this special study. Aliquots of the sample were spiked
with the mixed PFAS standard at the same two spiking levels used in Section 8. One pair of MS and
MSD aliquots was analyzed for each spike level. The mean recovery and RPD of the MS/MSD for each
spike level are provided in Table 9-3. The table also compares the recoveries for this sample between
both types of calibration standards. (The result for the inorganic calibration is the average of the
MS/MSD from Laboratory 3 only and not the average across all the participating laboratories.)

Table 9-3. Recoveries of Mixed PFAS Standard, Inorganic vs. Organic Calibrations

Nominal Spike
Cone (|jg F/L)

Inorganic Calibration

Organic Calibration

Mean Recovery (%)

RPD (%)

Mean Recovery (%)

RPD (%)

10

100.5

14.5

93.0

3.2

30

91.6

1.8

91.5

3.1

GDIT performed statistical analyses using a /-test and an ANOVA that demonstrated that there was no
statistical difference in the recoveries when the instrument is calibrated using an inorganic vs. an organic
fluoride standard when analyzing samples composed of a mixture of PFAS compounds. But given the
different affinities of the GAC for short-chain and long-chain PFAS during the adsorption process, the
loss of some short-chain PFAS from the mixed standard might not be immediately apparent in the
MS/MSD recovery data. Therefore the Method 1621 requirement to use sodium fluoride for the
instrument calibration will not be changed. However, further evaluation of a calibration with
organofluorine standards may be warranted and may be included in a future revision of Method 1621.

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10. Column Breakthrough

Breakthrough occurs when the sorbate leaves the top column due to either low adsorption of the
compound to the adsorbent bed, or by exceeding the capacity of the adsorbent bed, and is captured to
some extent on the bottom column. Because GAC columns can adsorb other compounds besides
organofluorines, high levels of co-adsorbed non-fluorine-containing contaminants can cause breakthrough
of organofluorine analytes on the GAC by overloading the bed. Also, short-chain PFAS, like PFBA, are
prone to lower recoveries, due to poor retention on the carbon. Therefore, GDIT asked the laboratories to
calculate the percent breakthrough between the top and bottom columns for each of the replicate analyses
using the equation below.

(.M2~B2) x 100
% Breakthrough = [(Ml _Bl) +

where,

Mi = Mass measured for the first column, (.ig F
M2 = Mass measured for the second column, (.ig F
Bi = Mass measured for first column of the initial method blank, (.ig F
B2 = Mass measured for second column of the initial method blank, (.ig F

Percent breakthroughs above 50% were observed in 18 of the 81 unspiked sample results and in 23 of the
36 results for Sample #7 spiked with PFBA. Of the 18 results showing high column breakthrough for the
unspiked sample results, six were for unspiked samples above the laboratory's MDL, while the remaining
12 results were for unspiked samples with results below the laboratory's MDL. Because sample results
below the laboratory's MDL are considered non-detects, having the % breakthrough above the limit is not
considered an issue for these samples. The average column breakthrough was 19.5%, with a maximum
breakthrough of 125.2%, which was seen in Sample #6 unspiked for Laboratory 1.

Table 10-1 summarizes the observed percent breakthrough failure rate for the 475 spiked and unspiked
samples with detectable AOF, using three potential acceptance criteria. When the criterion was set at
< 20%, 165 results failed the limit. When the criterion was widened to < 30%, 86 results failed the limit,
and when the criterion was set at < 50%, 29 results failed the limit, with 23 of those results being the
spikes for PFBA.

Table 10-1. Observed Failure Rates for Three Potential
% Breakthrough Acceptance Criteria

Criterion

# Results

# Failures

Failure Rate (%)

< 20%

475

165

34.7

< 30%

475

86

18.1

< 50%

475

29

4.2

The percent breakthrough observed in the study was < 50% for 94% of the 475 detected results across the
nine wastewater samples tested, which could lead some to suggest that column breakthrough issues may
not warrant combusting the top and bottom GAC columns separately. However, separate combustion of
the top and bottom GAC may still be necessary for certain types of wastewater samples, especially when
the sample source is unfamiliar to the laboratory. In situations where the laboratory consistently analyzes
the same sample sources for the same client, and the percent breakthroughs for those samples are
consistently below 50%, separate combustion of the top and bottom GAC columns may not be necessary,
but may require periodic checks. Based on the results from this study, EPA Method 1621 will include
recommendations for column breakthrough for samples with concentrations below the laboratory's
quantitation limit and for samples with baseline historical data.

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11. Data Review and Validation

The laboratories submitted the results for all analyses in this study as electronic data deliverables (EDDs)
in Excel format and supported by raw data and reporting forms provided in PDF format that were
equivalent to a hardcopy data package. Separate data submissions were provided for each technical
directive (e.g., each task) in the study. GDIT reviewed both the EDDs and the supporting raw data for
completeness and data quality and evaluated the data based on the preliminary method performance
criteria described in the draft method. The EPA will establish formal method performance criteria based
on the statistical analyses of the data from this multi-laboratory validation study. The data review process
was patterned after that used by GDIT for various other Office of Water studies.

As part of the review process, GDIT added data qualifiers and comments to the EDD when applicable,
and the file was saved with a new file name that indicated the data had been reviewed. This approach
preserves the original laboratory submission. While some data were qualified as part of this review
process, the results were not rejected based on the preliminary acceptance criteria in the method, and the
qualifiers applied by GDIT are intended to make the data user aware of potential data quality issues. The
exception to this is in cases where the result did not meet qualitative identification criteria (e.g., retention
time outside the window).

GDIT evaluated the MDL, IPR, reconnaissance (unspiked real-world samples), MS/MSD, OPR, and
method blank results in both the EDD and PDF raw data, while initial calibration and calibration
verification results were not provided in the EDD and therefore only the PDF raw data were evaluated.
GDIT independently calculated all of the results to ensure that they were within 1% of the reported
values. This 1% allowance accounts for rounding differences between the data available on the
instrument and the values with fewer decimal places that are typically reported in the hard copy. The data
review steps taken by GDIT are briefly described in the sections below.

Completeness check - The data report narratives in the data package were reviewed and any quality
control or performance related issues were noted. The data were verified to be consistent with the
narrative and appropriate validation qualifiers were applied. EDD elements and results were checked for
completeness and consistency with the raw data. Elements checked included the EPA sample identifier,
analysis date and time, laboratory qualifiers, found concentrations, sample sizes (volume), dilution
factors, spiked amounts, percent recoveries, percent breakthrough, preparation date, and concentration
units. Hardcopy and EDD data for all samples and blanks were checked to ensure that no data were
missing or inconsistent. Hardcopy data were checked to ensure that all chromatograms and quantitation
reports were available for all analyses and that all samples were reported in the sample pretreatment and
sample preparation worksheet records.

Initial Calibration - The initial calibrations were checked to ensure that at least 5 calibration standards
were analyzed and that they covered the concentration range of 100 - 5,000 ng F" (1.0- 50 (.ig F /L). The
model fit (%RSE) for the initial calibration standards was checked to ensure that it was < 20%. The
%RSE calculations were independently performed by GDIT to ensure that they were within 1% of the
reported values. For the matrix sample analyses, the calibration was extended to 100 - 10,000 ng F
(1.0 - 100 (ig F /L) and that extended calibration also was reviewed and validated.

Calibration Verification (CV) - All samples and blanks were checked to ensure they were bracketed by
a CV every 10 samples. The observed recoveries for the CV were within 80 - 120%. The reported
concentration calculations were independently performed by GDIT to ensure they were within 1% of the
reported values.

Instrument Sensitivity - Results between the MDL and the laboratory's quantitation or nominal
reporting limit were checked to confirm they were flagged by the laboratory. Any flagged results were

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checked to confirm the concentration warranted the qualifier (e.g., was between the MDL and the
quantitation limit). All reported non-detects were checked to confirm no signal was present, or that they
were detects below the MDL value.

Blank Contamination - Analyte concentrations reported in the method blank were compared to the
results for the associated samples. If the concentration in a sample was greater than 10 times the
concentration in the method blank, then the sample result was considered to be unaffected and the
validation flag "B, RNAF" was applied to indicate that the blank contamination was at a low enough level
to not significantly affect sample results.

OPR Recovery - The percent recoveries for the OPR were checked to ensure they were within
preliminary control limits of 70 - 130%. Independent calculations of the percent recovery were
performed to ensure they were within 1% of the reported values.

Matrix Spike Recovery - Real-world matrices were used to prepare matrix spike samples and recoveries
were checked to ensure they were within the preliminary control limits of 50 - 150%. Percent recoveries
for a few samples were recalculated to ensure they were within 1% of the reported values. High MS
recoveries indicated a positive interference or a high bias. Isolated instances of high recovery are not
uncommon, and patterns across multiple MS samples are more of a concern.

Quantification Check - The reported results in each sample were independently calculated by GDIT,
using equations provided in the draft method to ensure they were within 1% percent of the reported
values.

Column Breakthrough Check - The percent column breakthrough was checked for each analysis to
ensure it was below the preliminary control limit of 50%. Independent calculations were performed to
ensure they were within 1% of the reported values.

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12. Conclusions

The Office of Water's Engineering and Analysis Division completed the multi-laboratory validation study
of EPA Method 1621 for adsorbable organic fluorine in aqueous samples. The multi-laboratory
validation study achieved all its intended goals, as outlined below.

1.	Obtain data from matrices that are representative of the method's intended use

As described in Section 3, the wastewater matrices were a diverse selection of wastewaters from multiple
parts of the country with different physical parameters, as demonstrated in Table 3-2. The aqueous
matrices chosen are typical of what might be analyzed by a laboratory performing NPDES compliance
monitoring and included some pretreatment samples that would be more challenging than a typical
NPDES compliance final effluent.

2.	Obtain data from laboratories that are representative of those likely to use the approved method,
but that were not directly involved in its development

The majority of the laboratories that participated in this method validation study were commercial
laboratories that routinely perform NPDES compliance monitoring analyses. University, EPA, and in-
house vendor laboratories also participated. Because commercial laboratories are those most likely to use
this method for NPDES compliance monitoring, the use of those laboratories in this study meets this goal.

3.	Obtain feedback from laboratory users on the specifics of the draft method

Participant laboratories were encouraged to provide feedback on the method, and most did. Where
appropriate, the EPA has revised the method in response to such feedback.

4.	Use study data to characterize performance of the method

All the data collected during this study were reviewed and evaluated to characterize the performance of
this method, as summarized in detail in Sections 4 through 9. This includes data on calibration, initial
precision and recovery, method detection limits, and performance in real-world matrices.

5.	Develop statistically derived QC acceptance criteria that will reflect method performance
capabilities in real-world situations

Sections 6 through 8 contain statistically derived QC limits that were calculated from the data collected
during this study. The laboratories that participated are representative of the real-world laboratories that
would potentially run this method, and the matrices are typical of matrices that a laboratory using this
method would analyze.

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13. References

ASTM, WK68866, New Test Method for Determination ofAdsorbable Organic Fluorine in Waters and
Wastewaters by Adsorption on Activated Carbon Followed by Combustion Ion Chromatography, (no
date), www.astm.org

Jones, J., S. Burket, A. Hanley, and J. Shoemaker, 2022, Development of a Standardized Adsorbable
Organqfluorine Screening Method for Wastewaters with Detection by Combustion Ion Chromatography.
RSC Publishing, Cambridge, UK, 14(36):3501-3511.

Satterthwaite, F. E., 1946, An Approximate Distribution of Estimates of Variance Components,

Biometrics Bulletin, 2: 110-114.

USEPA, 2018, Protocol for Review and Validation of New Methods for Regulated Organic and Inorganic
Analytes in Wastewater Under EPA 's Alternate Test Procedure Program, EPA 821-B-16-001, Office of
Water, Office of Science and Technology, Engineering and Analysis, Washington, DC, February 2018.

USEPA, 2022, Draft Method 1621, Screening Method for the Determination of Adsorbable Organic
Fluorine (AOF) in Aqueous Matrices by Combustion Ion Chromatography (CIC), EPA 821-D-22-002,
Office of Water, Office of Science and Technology, Engineering and Analysis, Washington, DC, April
2022.

USEPA, 2022, Report on the Single-lab orator}' Validation of Clean Water Act Method 1621 for
Adsorbable Organic Fluoride (AOF), EPA 820-R-22-003, Office of Water, Office of Science and
Technology, Engineering and Analysis, Washington, DC, April 2022.

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Appendix A
Study Plan

(This appendix attempts to preserve the pagination and numbering of the original document)

Appendix A

A-l

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Study Plan/QAPP for the Multi-Laboratory Validation Study for
Draft EPA Method 1621 - Adsorbable Organic Fluorine

Prepared for

S. Bekah Burket
U.S. Environmental Protection Agency
Office of Water
Office of Science and Technology
Engineering and Analysis Division (4303T)
1200 Pennsylvania Avenue, NW
Washington, DC 20460

Prepared by

General Dynamics Information Technology, Inc.
3170 Fairview Park Dr.

Falls Church, VA 22042

Prepared under

EPA Scientific and Technical Support Contract EP-C-17-024
September 7, 2022

Approvals

Brian D'Amico, EPA, EAD TASB Chief	Adrian Hanley, EPA, WACOR

S. Bekah Burket, EPA, Alt WACOR/Project Manager	Lemuel Walker, EPA, QA Coordinator

Lynn Walters, GDIT, Program Manager	Harry McCarty, GDIT, Work Assignment Manager

Mirna Alpizar, GDIT, Study Manager

Marguerite Jones, GDIT QA Manager


-------
Acknowledgments

This study plan was prepared under the direction of S. Bekah Burket of the Engineering and Analysis
Division (EAD) within the U.S. Environmental Protection Agency (EPA) Office of Water by General
Dynamics Information Technology, Inc. (GDIT) under contract to the EPA Office of Water EAD. We
thank the ASTM International working group members for their comments during development of this
plan and the ASTM D19 Committee for providing the draft standard.

Disclaimer

This document has been reviewed and approved by the Engineering and Analytical Support Branch of
EAD. Mention of company names, trade names, or commercial products does not constitute endorsement
or recommendation for use.

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Table of Contents

Page

Acknowledgments	i

Disclaimer	i

Distribution List	n

Section 1 Background	1

Section 2 Study Objectives	1

Section 3 Study Management	3

Section 4 Technical Approach	4

4.1	Phase 1 - Solicitation of Laboratories	5

4.2	Phase 2 - Procurement of Standards, Select Supplies, and Study Samples	5

4.3	Phase 3 - Initial Calibration and Demonstration of Capability	6

4.4	Phase 4 - Analyses of Study Samples	8

4.5	Phase 5 - Special Study for Calibration with Organic Fluoride Standard	10

4.6	Phase 6 - Data Verification and Validation	10

4.7	Phase 7 - Development of QC Acceptance Criteria	10

Section 5 Quality Assurance and Quality Control Procedures	10

Section 6 Data Reporting and Management	12

6.1	Laboratory Reporting Requirements	12

6.2	GDIT Data Management and Reporting	13

Section 7 Evaluation of Method Performance	14

Section 8 References	14

Appendix A: Procedures for Derivation of QC Acceptance Criteria from the Validation Study Results
Appendix B: Draft EPA Method 1621 (weblink)

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Distribution List

Brian D'Amico, EPA EAD
Adrian Hanley, EPA EAD
S. Bekah Burket, EPA EAD
Lemuel Walker, EPA EAD
Lynn Walters, GDIT
Harry McCarty, GDIT
Mirna Alpizar, GDIT
Marguerite Jones, GDIT
Emily Surpin, GDIT
ASTM D19 workgroup members
EPA AOF workgroup members

GDIT Technical Staff (Study Coordinator, Data Reviewer, Statistician)

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Study Plan/QAPP for the Multi-Laboratory Validation Study for
Draft Method 1621 - Adsorbable Organic Fluorine

Section 1 Background

Various organizations and regulatory authorities at state, federal, and international levels are taking action
to address the release of per- and polyfluoroalkyl substances (PFAS) to the environment. Some of the
most common legacy sources of PFAS were from the manufacture of non-stick materials and largely
consisted of perfluorinated compounds such as perfluorooctane sulfonate (PFOS) and perfluorooctanoic
acid (PFOA). Voluntary efforts to phase out those compounds began in 2008, but a large variety of other
PFAS are now in common use as alternatives to PFOS and PFOA. There are other significant sources of
PFAS, including aqueous film-forming foams (AFFF) used in firefighting, that contain many more
fluorine-containing compounds. In addition to PFAS, fluorine is broadly used in the pharmaceutical and
pesticide industries because of the stability of the carbon-fluorine bond. The combination of PFAS and
non-PFAS fluorinated compounds are referred to hereafter as organofluorines.

From September 2021 through March 2022, the EPA Office of Water conducted a single-laboratory
validation (SLV) study of a screening method for the aggregate measurement of organofluorines based on
draft ASTM standard WK68866. Briefly, the organofluorines from aqueous environmental samples are
adsorbed on granular activated carbon (GAC) and analyzed by combustion ion chromatography (CIC).
EPA posted the procedure that resulted from the SLV as Draft Method 1621 (Ref 8.1).

This document is a hybrid study plan and quality assurance project plan (QAPP) for the multi-laboratory
validation of Draft Method 1621. The format and content of the document are consistent with the EPA
Office of Water's Hybrid Quality Assurance/Study Plan Format for Method Development and Method
Validation Studies, Revision 1, July 2020. As such, it should be considered a "living document" that is
intended to be updated as decisions are made by EAD and the study progresses.

The study will be conducted in the following seven phases, as described in Sections 4.1 through 4.7
below.

Phase

1

Phase

2

Phase

3

Phase

4

Phase

5

Phase

6

Phase

7

Solicitation of Laboratories

Procurement of Standards, Supplies, and Study Samples
Initial Calibration and Demonstration of Capability
Analysis of Study Samples

Special Study for Calibration with Organic Fluoride Standard
Data Verification and Validation
Development of QC Acceptance Criteria

Section 2 Study Objectives and Schedule

The goals of the multi-laboratory validation study are to:

•	Obtain data from matrices that are representative of the method's intended use

•	Obtain data from laboratories that are representative of those likely to use the method

•	Obtain feedback from laboratory users on the specifics of the draft method

•	Use the study data to characterize performance of the method

•	Develop statistically derived quality control (QC) acceptance criteria that will reflect method
performance capabilities in real-world situations

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In addition to the overall objective described above, EAD has two general quality objectives for this
study:

1.	Except where otherwise directed, all validation data must be generated according to the analytical
and quality assurance/quality control (QA/QC) procedures specified in this study plan and the
draft procedure. Alternatively, the data must be the result of pre-approved and documented
changes to the procedure.

2.	All data produced must be capable of being verified for accuracy and inconsistencies by an
independent reviewer of the analytical data package.

To meet these quality objectives, EPA and GDIT will employ the following QA/QC strategies:

•	All project activities will be performed in accordance with this study plan.

•	The participating laboratories (either contracted or volunteer) must have demonstrated experience
in performing work of a similar nature, preferably experience in EPA Method 1650 (AOX) or
similar sorption and combustion procedures in water samples and ion chromatography and must
have a comprehensive QA program in place and operating throughout their study operations. The
laboratory will be required to follow all QC procedures defined in Section 5 of this Study Plan.
(These requirements will be included in the laboratory statement of work or memorandum of
understanding.)

•	The study report and final draft method will be reviewed by GDIT, EPA, and the EPA workgroup
to ensure the QC requirements meet the study objectives.

Cumulatively, these requirements are intended to ensure that the data produced in this study are of
appropriate and documented quality.

Approval of this Study/QA Plan by EAD Engineering & Analytical Support Branch will be obtained
prior to any of the following activities taking place. The planned schedule for the study is as follows,
but may change due to circumstances beyond GDIT's or EPA's control:

Schedule

Month 1

Month 2

Month 3
Month 4
Month 5

Activity

•	Solicit and contract services from commercial environmental laboratories

•	Obtain agreement for participation and a signed memorandum of understanding
from each volunteer laboratory

•	Procure standards, selected supplies, and study samples for the participating
laboratories

•	Prepare and ship sample collection kits to the major wastewater treatment facilities
that will be collecting the samples for use in the study.

•	Collection and shipment of real-world wastewater samples from major wastewater
treatment facilities. The samples will be shipped from the collectors to GDIT's
facility in Falls Church, Va., for aliquoting.

•	Analysis of water quality parameters for study samples by a contracted laboratory
(Sections 4.2.2 and 4.4)

Initial demonstration of capability by all laboratories.

Ship study samples to the participating analytical laboratories
Laboratory analyses and delivery of the data to GDIT
Conduct data quality review of analytical and QC data
Develop project-specific databases for storage and retrieval of analytical data
Compile data files for each target analyte for statistical analysis
Prepare summary project information and graphics for final reporting

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Section 3 Study Management

The study will be managed by S. Bekah Burket, the Alternate Work Assignment Contracting Officer's
Representative (Alt WACOR) and EAD Project Manager, under the supervision of Adrian Hanley, the
EPA WACOR, who will provide technical direction to GDIT. The EAD Project Manager will be
responsible for recruiting and providing formal direction to any EPA laboratories that may participate in
the study (see Section 4.1). Lemuel Walker, EAD Quality Assurance Coordinator, will provide QA
oversight for EPA.

Day-to-day management and coordination of study activities, including procurement of services from and
oversight of commercial (paid) environmental laboratories, and monitoring of laboratory progress, both
paid and voluntary, will be performed by GDIT Study Manager, Mirna Alpizar, under the supervision of
the GDIT Work Assignment Manager, Harry McCarty, and the GDIT Program Manager, Lynn Walters,
and in accordance with EAD guidance. Ms. Alpizar will be supported by a team of GDIT technical staff
(i.e., study coordinator, data reviewer, statistician), who will assist with details of study implementation,
such as identification of qualified laboratories, coordinating with GDIT's purchasing department,
coordinating shipment of supplies and study samples, data review and data analysis. Marguerite Jones,
GDIT Quality Assurance Manager, will provide QA oversight for GDIT, with assistance from GDIT's
QA Coordinator, Emily Surpin. The organization chart in Figure 1 below illustrates the relationship of
these parties.

Figure 1. Organization Chart

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The laboratories performing the study will be identified in the first phase. In keeping with the approach
described in ASTM Standard D2777 (Ref. 8.2), EPA will solicit participation from the largest number of
laboratories practical, recognizing the possibility that some participants may drop out or otherwise fail to
provide usable data. Currently, EPA plans to include at least 10 laboratories in the study, if practical. Part
of the rationale for the number of participants is to gain additional support for promulgation of the final
method from the commercial laboratory community. However, the final number of laboratories also will
be determined by EPA based on factors such as cost, availability of instrumentation, and EPA's ability to
enlist voluntary (unpaid) participation of suitable vendor and/or EPA Regional laboratories.

For this study, the participating laboratories must own and be familiar with the operation of a CIC system
and will be responsible for ensuring proper operation of the system for the entirety of this study. The
laboratories will, with oversight from the GDIT Study Manager, perform various studies needed to
optimize the method. Once the initial tests are complete and findings reviewed and approved by the GDIT
Study Manager and EAD Project Manager, the laboratories will prepare and analyze real-world samples
for this study.

The laboratories will submit their analytical results to GDIT. GDIT staff, under EAD direction, will
review and evaluate all the analytical data and assist EAD in drawing conclusions from the results. GDIT
staff will prepare a draft study report that summarizes the results and conclusions for EAD review.
Throughout each phase listed in Section 4, GDIT and EPA will also share all data generated during the
study with ASTM Committee D19.

GDIT will be responsible for providing the method-required reference standards to each laboratory. To do
so, GDIT staff will procure the standards from one or more commercial vendors and coordinate shipment
of the standards directly from the vendor(s) to each participating laboratory.

Section 4 Technical Approach

The study will be performed in seven phases. Phase 1 (Section 4.1) involves identification and solicitation
of appropriate laboratories with the necessary analytical instrumentation. Phase 2 (Section 4.2) involves
the procurement of standards, supplies, and study samples. Phase 3 (Section 4.3) consists of each
laboratory performing initial calibration and demonstration of capability. Phase 4 (Section 4.4) involves
the evaluation of real-world wastewater study samples. Phase 5 (Section 4.5) involves a special study for
calibration with organic fluoride standard. Phase 6 (Section 4.6) involves data verification and validation.
Phase 7 (Section 4.7) involves the development of QC acceptance criteria.

The testing under Phase 3 through Phase 7 will be performed using a set of two GAC columns, placed
in series on the absorption module. Each column will be combusted separately, and the percent
breakthrough calculated for each sample, using Equation 1.

Equation 1 Percent Breakthrough

(C2 -B2) X 100
% Breakthrough = ^ ^ +

where:

Ci =	Measured |ag F" for the first column

C2 =	Measured |_ig F" for the second column

Bi =	|ag F for first column from reagent water blank

B2 =	(ig F" for second column from reagent water blank

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4.1	Phase 1 - Solicitation of Laboratories

The focus of Phase 1 is to identify and solicit at least 10 laboratories to participate in the study. As noted
earlier, some of the laboratories will be contracted by GDIT and others may participate as volunteers. The
contracted laboratories are likely to be commercial environmental laboratories, whereas volunteer
participants may be EPA Regional laboratories or other organizations that are unlikely to be able to accept
payment for their participation.

Participating laboratories will:

•	Possess a CIC instrument and the necessary sample processing equipment

•	Have experience running the sample preparation process for EPA Method 1650 (AOX) or similar
sorption and combustion procedures

•	Have staff available who are experienced in method development and evaluation

•	Have management support for the project

•	Have a comprehensive QA program in place and operating throughout their study operations

•	Follow all QC procedures defined in Section 5 of this Study Plan

GDIT and EPA will develop a broad list of likely participants and contact them in advance of a formal
solicitation to determine their potential interest. Once the list of potential participants has been
established, GDIT staff will competitively solicit bids using government-approved procurement
procedures and an EAD-approved statement of work (SOW), or equivalent documentation that details the
requirements for sample preparation, storage, shipment, analysis, QA/QC, and reporting. The SOW also
will stipulate that the laboratory must have a comprehensive laboratory QA program in place and
operating at all times during performance under the SOW and this program must be consistent with EPA
Guidance for Developing Quality Systems for Environmental Programs (Ref. 8.3) and the general
laboratory procedures specified in the Handbook for Analytical Quality Control in Water and Wastewater
Laboratories (Ref. 8.4). The GDIT Study Manager will also work with EPA to develop suitable
mechanisms to engage any volunteer laboratories identified by EPA. Such mechanisms may involve a
memorandum of understanding (MOU) and/or a voluntary participation agreement form previously
developed by EPA for similar studies.

Regardless of the nature of a laboratory's participation, contracted or volunteer, the same study
requirements will apply and will be described in a study-specific statement of work and study-specific
instructions.

4.2	Phase 2 - Procurement of Standards, Supplies, and Study Samples

Phase 2 of the study involves procuring sufficient quantities of the analytical standards needed to perform
the method, GAC columns, column holders, and the samples that will be analyzed in the study.

4.2.1 Standards and Selected Supplies

Providing the same standards, GAC columns, and column holders to each laboratory removes these as
sources of variability and provides an incentive for both contracted and volunteer laboratories to
participate.

After identifying likely commercial sources for the standards and GAC columns, GDIT will use
government-approved procurement procedures and an EPA-approved SOW (or equivalent) to obtain
sufficient quantities of the needed materials and have them shipped directly to the participating
laboratories. GDIT anticipates that these materials will need to be procured from multiple existing
commercial sources.

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Once the GDIT purchase orders are in place, GDIT staff will work with the vendors to schedule and
direct the shipments of materials to each participating laboratory. GDIT Study Manager will notify each
laboratory of impending shipments, track each shipment from the vendor to the laboratory, and confirm
condition of the materials on receipt with each laboratory. GDIT Study Manager will work with the
vendors and laboratories to resolve any issues or discrepancies and will communicate with EPA regularly.

4.2.2 Study Samples

The focus of the study is on the analysis of real-world aqueous environmental matrices. EPA and GDIT
will work with municipal, state, and EPA Regional contacts to obtain sufficient volumes of up to ten real-
world wastewaters to be used in the study. The wastewater samples will include effluents from a publicly
owned treatment works (POTW) and wastewaters from specific industrial discharges if they can be
obtained in sufficient quantities. At least one of the wastewater matrix types should have one of the
following characteristics, such that each criterion below is represented by at least one wastewater:

•	Total suspended solids (TSS) greater than 40 mg/L

•	Total dissolved solids (TDS) greater than 100 mg/L

•	Oil and grease greater than 20 mg/L

•	NaCl greater than 120 mg/L

•	CaC03 greater than 140 mg/L

The study samples will be collected in bulk quantities by water treatment facilities and shipped to GDIT.
GDIT staff will then prepare and ship aliquots of each sample to each of the laboratories participating in
the study. Prior to shipping study samples, GDIT staff will coordinate schedules with laboratory staff.
GDIT Study Manager also will confirm condition of the samples on receipt, work with the laboratories to
resolve any issues or discrepancies, and communicate regularly with EPA.

4.3 Phase 3 - Initial Calibration and Demonstration of Capability

Prior to analyzing any of the study samples, each laboratory will perform an initial multi-point calibration
and conduct an initial demonstration of capability. Before proceeding with later phases of the effort,
EAD, GDIT, and the laboratories will discuss the results from Phase 3. To further reduce analytical
variation, the laboratories will be required to use the same ion chromatography (IC) columns based on
their IC instrument manufacturer. For example, if more than one laboratory uses a Thermo-Fisher IC
instrument, then these laboratories will be required to use the same IC column model, mobile phase, and
gradient.

4.3.1 Initial Calibration

Each laboratory will perform an initial calibration using a sodium fluoride standard as specified in Draft
Method 1621. The calibration must contain at least 5 calibration levels and fall within the applicable
range of 1 |ag F"/L to 100 (ig F~/L.

The calibration model to be used will be external standard calibration by combustion. A simple linear
regression model will be used, not forced through the origin. The acceptability of the calibration curve
shall be determined using the relative standard error (RSE). The goal of this study is that the RSE be at or
below 20% in order to establish linearity. However, the final method acceptance criteria will be derived
from the results of the study. The RSE is to be calculated using Equation 2 below.

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Equation 2. Relative Standard Error

RSE = 100 X
where:

x, = Nominal concentration (true value) of each calibration standard
x'i = Measured concentration of each calibration standard
n = Number of standard levels in the curve
p = Type of curve (1 = average, 2 = linear, 3 = quadratic)

4.3.2	Method Detection Limit Study

Following successful demonstration of the calibration range and linearity, the laboratory will determine
the Method Detection Limit (MDL) using the revised MDL procedure published in 2017 at Code of
Federal Regulations (CFR), Title 40, Part 136, Appendix B (Ref. 8.5). The laboratory will prepare and
analyze at least seven replicate reagent water samples spiked with sodium perfluorohexanesulfonate
(PFHxS) and an equal number of unspiked reagent water samples over three non-consecutive days and
determine the MDLS (the MDL based on spiked samples) and MDLb (the MDL based on method blanks),
respectively. The spiking level will be based on the guidance in the revised MDL procedure, the results
for the initial calibration, and other information, such as recovery data from the SLV study.

Given the prevalence of low levels of PFAS components in sampling equipment and instrumentation, the
MDL for the procedure may be based on the MDLb, rather than the MDLS. Several iterations of the MDL
study may be required. EAD, GDIT, and the laboratories will discuss the results from the MDL study
before proceeding with later phases of this effort.

4.3.3	IPR Determin ation

Each laboratory will perform an initial precision and recovery (IPR) study to provide sufficient data for
development of performance specifications. The IPR consists of four replicate samples of reagent water
spiked with PFHxS at around the midpoint of the calibration range and carried through the entire
analytical process (sample preparation and analysis).

Each laboratory will calculate the percent recovery (% R) using Equation 3 below and report it to three
significant figures (e.g., 102%).

Equation 3. Percent Recovery

Cs

o/o R = -JL x 100

^n

where:

Cs = Measured concentration of the spiked sample aliquot
Cn = Nominal (theoretical) concentration of the spiked aliquot

Each laboratory will also calculate the relative standard deviation (RSD) from the results of the four
replicates using Equation 4 below and report it to two significant figures.

l—i n — p

i = 1

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Equation 4. Relative Standard Deviation

SD

RSD = 		X 100

^avg

where:

SD = Standard deviation of Cs for the four replicates
Cavg = Average measured concentration for the four replicates

IPR results generated during Phase 3 will be used to develop the final IPR performance criteria (% R and
RSD) during Phase 7 of the study.

4.4 Phase 4 - Analyses of Study Samples

Pre-shipment Reconnaissance Analyses

Because some study participant laboratories (e.g., instrument vendors, university research laboratories)
may not have the capability to perform the sample pretreatment checks required in the draft method, a
single laboratory will be selected to perform reconnaissance of the study samples by analyzing for pH,
chlorine, inorganic fluoride, and background AOF levels, prior to shipment of study samples to the
participating laboratories. EPA and GDIT will use the reconnaissance analyses results to establish the
spike levels to be used by the laboratories and to determine if any of the samples will need pH adjustment
or dilution prior to analysis.

Study Samples and Aliquots

Each participating laboratory will receive up to ten samples, consisting of:

•	ten (10) 125-mL sample aliquots for up to nine of the aqueous matrices, and

•	twenty-six (26) 125-mL sample aliquots of one aqueous matrix

The number of containers ensures the laboratories will have enough volume in the event reanalysis is
required or an accidental spill happens during sample shipment.

Parts 1, 2, and 3 Analyses

The sample analyses in this study will be divided into three parts, as described below and outlined in
Table 1. The study design will yield up to 100 unspiked sample results and up to 580 spiked sample
results if 10 laboratories participate in the study and all 10 complete all required analyses.

•	For Part 1, each laboratory will be required to analyze each of the study samples unspiked for the
laboratory-specific AOF background. Each laboratory will use their unspiked sample results to
adjust the concentration of their spiked results and calculate the percent recoveries for the spiked
sample results from Part 2 and Part 3 of the study.

•	For Part 2, each laboratory will spike a matrix spike/matrix spike duplicate (MS/MSD) pair for
each sample at two spiking levels using PFHxS.

•	For Part 3, each laboratory will use one sample, selected by EPA, to prepare separate MS/MSD
pairs spiked with the following standards: PFOS, PFBA, and a mixed PFAS standard, and spiked
at two spike levels (i.e., six MS/MSD pairs total).

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Table 1 Study Analytical Design

Study Part

Matrix ID

ID

Spiked Analyte

# Replicates
per Lab

Nominal Value*

Part #1

1-10

Unspiked

None

1 per Matrix

None

Part #2

#1

MS/MSD-1

PFHxS

2

Spike Level Low





MS/MSD-2

PFHxS

2

Spike Level High



#2

MS/MSD-1

PFHxS

2

Spike Level Low





MS/MSD-2

PFHxS

2

Spike Level High



#3

MS/MSD-1

PFHxS

2

Spike Level Low





MS/MSD-2

PFHxS

2

Spike Level High



#4

MS/MSD-1

PFHxS

2

Spike Level Low





MS/MSD-2

PFHxS

2

Spike Level High



#5

MS/MSD-1

PFHxS

2

Spike Level Low





MS/MSD-2

PFHxS

2

Spike Level High



#6

MS/MSD-1

PFHxS

2

Spike Level Low





MS/MSD-2

PFHxS

2

Spike Level High



#7

MS/MSD-1

PFHxS

2

Spike Level Low





MS/MSD-2

PFHxS

2

Spike Level High



#8

MS/MSD-1

PFHxS

2

Spike Level Low





MS/MSD-2

PFHxS

2

Spike Level High



#9

MS/MSD-1

PFHxS

2

Spike Level Low





MS/MSD-2

PFHxS

2

Spike Level High



#10

MS/MSD-1

PFHxS

2

Spike Level Low





MS/MSD-2

PFHxS

2

Spike Level High

Part #3

#X

MS/MSD-1

PFOS

2

Spike Level Low



To be

MS/MSD-2

PFOS

2

Spike Level High



selected by

MS/MSD-1

PFBA

2

Spike Level Low



EPA

MS/MSD-2

PFBA

2

Spike Level High





MS/MSD-1

Mixed PFAS

2

Spike Level Low





MS/MSD-2

Mixed PFAS

2

Spike Level High

* Spike concentrations will be selected after analysis of the reconnaissance AOF background concentrations. The
laboratories will be informed what nominal concentration to use for each spike level.

Determination of MS/MSI) Precision and Recovery

The laboratories will calculate the percent recovery and precision of the MS/MSD samples using
Equation 5 and Equation 6 below. Percent recoveries and the relative percent difference (RPD) will be
reported to two significant figures.

Equation 5. Percent Recovery for MS/MSD Samples

o/o R = _L_—- X 100
kn

where:

Cs = Measured concentration of the spiked sample aliquot
C = Measured concentration of the unspiked sample aliquot
Cn = Nominal (theoretical) concentration of the spiked aliquot

Equation 6. Relative Percent Difference

lซ2 "Si!

RPD~ (/?1 + /?2)/2

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where:

Ri =	Recovery for MS

R2 =	Recovery for MSD

4.5	Phase 5 - Special Study for Calibration with Organic Fluoride Standard

One laboratory will be directed to perform a special study for comparison of instrument calibration using
inorganic fluoride vs. organic fluoride. That laboratory will perform an initial calibration as in Phase 3 but
using PFHxS instead of sodium fluoride. All the acceptance requirements spelled out in Section 4.3.1 will
apply to this calibration as well.

That laboratory will also analyze one sample, selected by EPA, spiked at two concentrations using a
mixed PFAS standard. The laboratory will analyze one MS/MSD pair for each spike level.

4.6	Phase 6 - Data Verification and Validation

All the results from laboratories participating in the study will be reviewed and validated by GDIT staff,
relative to the study's goals. Every data submission will be checked for completeness (e.g., verify that all
study samples were analyzed, and all required results were submitted) and to determine if the supporting
documentation indicates that the laboratory followed the method and study-specific instructions.

Each laboratory will be required to submit the raw data (e.g., instrument printouts and copies of sample
preparation records) that supports the study results. GDIT staff will examine all the raw data, perform
spot checks of a percentage of the calculations from each laboratory, and ensure that the reported results
can be traced back through all steps in the analytical process. If any issues are identified, GDIT Study
Manager will work with the laboratory to clarify the situation, obtain any missing information, and
document the resolution. GDIT Study Manager will advise EPA of the status of the review efforts on a
regular basis.

Because this is a method validation effort, there are no a priori quality control acceptance criteria, and
data from the study will not be excluded from consideration simply because they appear to fail the draft
method performance criteria which were based on the SLV study. Every effort will be made to retain as
many results as practical. GDIT staff will flag results from samples with obvious documented failures
(e.g., adsorption unit contamination) for exclusion from use in developing method performance
information and will document the rationale for such exclusions in the project files and/or the project
database. However, in the absence of evidence of such failures, all the results will be included in the
initial data set. GDIT and EPA will use statistical tests to determine if results for specific laboratories or
samples may be outliers that should be removed from use in developing QC acceptance criteria.

Suspected outliers will be examined in detail by the GDIT Study Manager and the laboratory before they
are excluded from use in developing method performance summaries.

4.7	Phase 7 - Development of QC Acceptance Criteria

The last major phase of the study will be to develop statistically based QC acceptance criteria and
summarize method performance in real-world samples. The overall procedures used for that process are
described in Section 7 of this study plan.

Section 5 Quality Assurance and Quality Control Procedures

For this study, the laboratories will perform the following traditional QC checks found in Draft EPA
Method 1621:

• Initial calibration (ICAL), 5-point minimum

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•	Initial precision and recovery (IPR)

•	Calibration verification (CV)

•	Method blanks carried through the entire procedure

•	Ongoing Precision and Recovery (OPR)

Because the study will analyze many pairs of spiked samples, there is no requirement to prepare
additional routine MS/MSD samples with the study sample batches.

See Table 2 below for frequency and study requirements for each of the QC checks.

Table 2 QC Checks

QC Check

Frequency

Acceptance Criteria

Study Requirements

Initial calibration
(ICAL), 5-point
minimum

Once at the beginning of the
study and as needed
throughout the study

% RSE of the calibration curve
should be < 20%. Report all
results as generated.

ICAL data will be provided by
each laboratory and compared to
typical calibration criteria

Initial demonstration of

capability

(IPR and MDL)

Once

IPR % recovery and % RSD
criteria will be established after
review of study data. Report all
results as generated

Each laboratory will provide IPR
data. Study data will be used to
develop criteria

Calibration verification
(CV)

Beginning and at the end of
the analytical batch. Initial
calibration can be used in
place of initial CV if
samples are analyzed within
24 hours of initial
calibration.

CV % recovery should be within
ฑ 20% of the mid-level standard
from the initial calibration.
Report all results as generated.

CV data will be provided by each
laboratory and compared to typical
calibration criteria

Method blank

Two per batch of 10 field
samples or fewer

To be determined based on study
data. Report all results as
generated.

Perform as specified in the
procedure

Ongoing precision and
recovery (OPR)

One per preparation
batch of 10 field samples or
fewer

To be determined based on study
data. Report all results as
generated. Study data will be
used to develop criteria.

Perform as specified in the draft
method to demonstrate
performance at the OPR
concentration.

Matrix spike/ Matrix
spike duplicate
(MS/MSD)

One pair per spike level per
study sample. See Table 1.

To be determined based on study
data. Report all results as
generated.

MS/MSD results will be used to
demonstrate method performance.

RPD between the MS and MSD
analyses will be used to develop
acceptance criteria for duplicate
unspiked analyses.

Qualitative Identification
Criteria

Fluoride peak in all analyses

RT within ฑ0.2 min of initial
CV or ICAL RT if the ICAL was
performed with the batch of
samples

Perform as specified in procedure

It is each of the laboratories' responsibility to maintain their instrumentation and to ensure that all study
samples are analyzed on a properly calibrated instrument. If the calibration linearity is outside the
nominal criteria, the laboratory will take standard measures to attempt to correct the problem before any
study samples are analyzed. The laboratories are also responsible for inspecting all study samples and
standards to ensure they meet all the study requirements. If typical measures do not correct the problem or
if study schedules will be impacted due to necessary repairs or replacement of study samples or standards,
the laboratory will notify the GDIT Study Manager to indicate the impact on study schedules, the
laboratory's plans to resolve the problem(s), and if any study samples will need to be reanalyzed.

Each laboratory will report the results from the QC operations, either in electronic format, or if necessary,
in hard copy. GDIT staff will compile the QC results in a database specific to this project (See Section 6).

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Section 6 Data Reporting and Management
6.1 Laboratory Reporting Requirements

Each laboratory will be required to submit summary-level data. The summary-level data must be
submitted in PDF and electronic format and must include:

•	GDIT-assigned sample number

•	Analyte identification

•	Laboratory sample number (if applicable)

•	Type of sample (e.g., method blank, OPR, sample)

•	Dilution factor (if applicable)

•	Spike levels nominal concentration

•	Measured concentration

•	Reporting units (|_ig F/L)

•	Sample preparation date

•	Time of analysis (hour and minute)

•	Analytical batch ID (if applicable)

•	% Breakthrough

Each laboratory will be required to report supporting raw data for all analyses performed and maintain
their raw data for a period of seven (7) years and provide them upon request (at additional cost negotiated
as necessary).

Raw data shall include:

•	Calibration data summary

•	Chromatogram and quantitation report for analysis of each sample, blank, calibration standard,
and calibration verification standard and all manual worksheets pertaining to sample or QC data
or the calculations thereof. Chromatograms must contain the following header information:
laboratory-assigned identifier (lab file ID), date and time of analysis, and instrument ID.
Chromatograms should be labeled with the name of the analyte, either directly out from the peak
or on a printout of retention times. Quantitation reports must contain determined concentrations,
area or peak responses, and RTs.

•	Sample preparation bench sheets

•	Copies of laboratory notebooks showing weights, volumes, and calculations for preparation of
standards

•	Certificates of analysis for all standards used

•	Other data that will allow verification of the calculations performed, such that a third party can
recalculate the final results from the raw data.

The laboratory will adhere to the following rules when reporting data:

•	All reports and documentation, including instrument printouts and other raw data, must be
sequentially paginated, clearly labeled with the laboratory name, and labeled to provide sufficient
identification for method blanks, calibration, etc., necessary to link the raw data with associated
summary reports.

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•	Results from all analyses, including failed experiments, must be reported, including calibration
data and any dilutions or re-analyses performed. The laboratory must also include an explanation
for any re-analyses performed and identify which of the analyses the laboratory considers to be
the most appropriate for use.

•	Results of all measurements must be reported to two significant figures in (.ig F/L to facilitate
review and evaluation.

•	The terms "zero" and "trace" are not to be used; the term "not detected" (ND) is to be used for
each measurement for which no signal is produced or if method-specified qualitative
identification criteria are not met.

•	Every value must be reported, even if the value is negative. If the value is below the lowest
calibration standard, a "J" flag must be applied to this value.

•	Results must be reported for all study samples, including QC samples. Although sample results
are blank corrected, the results for both method blanks must also be reported with the associated
sample data.

In addition, the laboratory will be required to submit a written "narrative report" with each data package.
The narrative report will contain detailed descriptions of any difficulties encountered in the generation of
the analytical results and QC data and any attempts to resolve the difficulties. It also will contain a
detailed description of any necessary modifications to the draft AOF procedure.

Each laboratory must have a comprehensive data management plan in place that is consistent with the
principles set forth in the Good Automated Laboratory Practices (Ref. 8.6), or with commonly employed
data management procedures approved by The NELAC Institute (TNI). This data management plan must
be in place and in use at all times during the performance of this study.

6.2 GDIT Data Management and Reporting

GDIT will store all study records and submitted data (hard copy and electronic) in an organized fashion
on a secure local area network that is backed up nightly and as needed in hardcopy files in their secure
office facility, throughout the duration of their contract. Cumulatively, these files will include the
following documents and records:

•	This study plan (including all submitted draft versions, comments, and revisions)

•	Documentation of the procedures used to assess the competency of laboratories participating in
this study

•	Documents and records associated with the solicitation and award of participant laboratories,
including the SOWs or equivalent that describe participant laboratory requirements

•	Documents and records associated with the procurement of standards and study samples,
including SOWs or equivalent that describe the process used to collect and produce study samples

•	The name, address, phone number and primary contact at the standards vendor and each
participating laboratory

•	Copies of all written correspondence (excluding emails) with laboratory staff, sampling
personnel, and EPA staff regarding the study

•	A log (or other record) that documents verbal communication with laboratory staff, sample
coordinators, sampling personnel, and EPA staff regarding study status or problems

•	Records concerning sample shipment and receipt

•	All analytical data resulting from this study

•	All laboratory comments on the method resulting from this study

•	Records of all GDIT data review assessments and statistical analyses submitted to EPA

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•	All draft and final reports submitted to EPA pertaining to this study
Section 7 Evaluation of Method Performance

EPA's overall goal is to develop method performance data for Draft EPA Method 1621 and statistically-
derived QC acceptance criteria that reflect method performance. The results of the analyses in Phases 3
and 4 of this study will be evaluated using common statistical procedures (References 8.2, 8.7 - 8.8) such
as:

•	/-tests, to determine if the mean result for an analyte differs between "treatments" (e.g., spiking
levels or background levels of potential interferences)

•	F-tests, to determine if the variance (standard deviation squared) for an analyte differs between
"treatments"

•	Analysis of variance (ANOVA), to determine how the differences between the components and
the treatments affect overall variability

All study results will be subjected to statistical evaluations, and suspected outliers will be examined in
detail by the GDIT Study Manager and the laboratory before they are excluded from use in developing
method performance summaries. GDIT technical staff will perform the statistical evaluations that will be
used for the establishment of method QC acceptance criteria; however, GDIT will not perform the
evaluation for the Youden pair graphical method. ASTM may choose to use the data provided by EPA for
that evaluation.

EPA and GDIT will use the results from the replicate samples to develop QC acceptance criteria for
initial precision and recovery (IPR) studies, ongoing precision and recovery (OPR) samples, MS/MSD
recovery limits, relative percent difference (RPD) limits, etc. A general description of the derivation of
those QC acceptance criteria is provided in Appendix A and is based on EPA's protocol for evaluation of
new methods (Reference 8.9).

EPA and GDIT will develop tables of method performance data, including precision and accuracy, as a
function of analyte concentration that will provide an indication of expected performance of the
procedures under typical conditions. Such tables will be included in the revised procedure as further
evidence of its overall capabilities or limitations.

Finally, EPA and GDIT will prepare a formal report on the results of the multi-laboratory validation
study. EPA will submit that draft report to appropriate levels of management review within EPA and
revise the report as needed. The study report will also be shared with the ASTM D19 workgroup. If the
study is successful and EPA decides to move forward with rulemaking to approve EPA Method 1621 at
40 CFR Part 136 for use in nationwide compliance monitoring, the study report and records from the
study will be placed into the rulemaking docket (Ref 8.10).

Section 8 References

8.1	Draft Method 1621 Screening Method for the Determination of Adsorbable Organic Fluorine
(AOF) in Aqueous Matrices by Combustion Ion Chromatography (CIC). April 2022, USEPA,
Office of Water, Engineering and Analysis Division.

https://www.epa.gov/svstem/files/documents/2022-Q4/draft-method-1621 -for-screening-aof-in-
aqueous-matrices-bv-cic O.pdf

8.2	ASTM 2013. ASTM D2777-21, Standard Practice for Determination of Precision and Bias of
Applicable Test Methods of Committee D19 on Water, ASTM International, West
Conshohocken, Pennsylvania.

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8.3	US Environmental Protection Agency. 2002. Guidance for Developing Quality Systems for
Environmental Programs. U.S. Environmental Protection Agency. Office of Environmental
Information. EPA QA/G-1, EPA/240/R-02/008.

8.4	US Environmental Protection Agency. 1979. Handbook for Analytical Quality Control in Water
and Wastewater Laboratories. U.S. Environmental Protection Agency. Office of Research and
Development. EPA-600/4-79-019.

8.5	Federal Register. Vol. 82, No. 165. August 28, 2017. Definition and Procedure for the
Determination of the Method Detection Limit, pp. 40939 - 40941, Federal Register Online via
the Government Printing Office.

8.6	US Environmental Protection Agency. 1995. Good Automated Laboratory Practices. U.S.
Environmental Protection Agency. Office of Information Resource Management. EPA-2185.

8.7	SAS Institute Inc. 1994. SAS/STAT User's Guide, Volume 2, GLM-VARCOMP. Version 6, 4th
Edition, June 1994.

8.8	Berry, D. A.; Lindgren, B. W. 1990. Statistics: Theory and Methods, pp. 286-290, 600-618.
Brooks/Cole Publishing Company. Pacific Grove, California.

8.9	US Environmental Protection Agency. 2016. Protocol for Review and Validation of New
Methods for Regulated Organic and Inorganic Analytes in Wastewater Under EPA's Alternate
Test Procedure Program. U.S. Environmental Protection Agency. Office of Water, Engineering
and Analysis Division. EPA 821-B-16-001.

8.10	Federal Register Volume 82, Number 165. August 28, 2017. Clean Water Act Methods Update
Rule for the Analysis of Effluent; Final Rule. pp. 40836 - 40941, Federal Register Online via the
Government Printing Office.

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Appendix A

Procedures for Derivation of QC Acceptance Criteria from the Validation Study Results

The information below has been excerpted from Reference 8.9, and all citations to section numbers and
references apply to the original document, not this study plan. The calculations used for this study will be
adjusted for the actual number of laboratories involved.

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Quality Control Acceptance Criteria Development for New Methods

Method Detection Limits and Minimum Levels

Each laboratory participating in the validation study must perform an MDL study as described in Section
3.1.1. The organization responsible for developing the new method must establish an MDL for the
method, using a pooled MDL from at least six laboratories. A pooled MDL is calculated from m
individual laboratory MDLs by computing the square root of the mean of the squares of the individual
MDLs and multiplying the result by a ratio of Z-values to adjust for the increased degrees of freedom.

Note: The MDL values used in this calculation are those determined in each of the six or more

laboratories. If one laboratory reports an MDLS (from spiked samples), that value is used in
conjunction with the MDL values from the other laboratories, including any values reported as
MDLb (from blanks).

MDL

pooled.



d-1

(MDL

Lab 1

+ d-

(MDL

Lab 2

1 V ฃ(0.99,di) / 2 V ฃ(0.99,d2)

+ d-i

(MDL

Lab m

V ฃ(0.99Am)

d^ + c?2 + ••• dr

x t,

(0.99, [dx+ d2+ ฆฆฆdm]

where:

m = The number of laboratories, and

di = The number of degrees of freedom used by Lab i to derive the MDL.

In the case of 9 laboratories with 7 replicates per laboratory, the equation simplifies to:

MDLpooied

M

MDLlab i + MDL\ab2 +- MDL2Lab9 2.41
9	3.14

The organization responsible for developing the method must also use this MDL to develop an ML.
Procedures for determining the ML are given in Section 3.1.1.

Calibration Linearity

The instrument or analytical system is then calibrated with six standards specified in the method to
calculate an initial RSD for the response factor.

The RSD and the RSD limit for the CF, RF, or RR is determined as follows:

1. Calculate the mean and standard deviation of the CFs, RFs, or RRs for each laboratory.

	 YH=\Factori

Mean Factor = Factor =	

n

Y!i=1(Fact ori — Factor)2

s

\ n'

where:

Factor = The "Factor" terms are replaced by the CF, RF or RR terms, based on the quantitation
approach described in the method in question, and
n = The number of calibration points used in each laboratory.

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2. Calculate the relative standard deviation of the CFs, RFs, or RRs of each laboratory and analyte as:

RSD, = 100 x

Factor,

where s and Factor are the standard deviation and mean of the CFs, RFs, or RRs for laboratory /.

3. Calculate the pooled RSD of the CFs, RFs, or RRs for each analyte from all laboratories. The pooled
RSD is calculated as the square root of the mean of the squares of the sample RSDs from each
individual laboratory. For example, for nine laboratories, the pooled RSD is calculated as:

where:

k = The square root of the 95th percentile of an F distribution with n- 1 degrees of freedom in the

numerator and m(n - 1) degrees of freedom in the denominator,
m = The number of laboratories, and
n = The number of calibration points.

For nine laboratories using a five-point calibration (m = 9,n = 5), the value of k is 1.6. The maximum
allowable specification for RSDmax is 35%.

Calibration Verification

As noted in Section 2.2, acceptance limits for calibration verifications can be determined in three different
ways, each of which is described below.

The calibration verification criterion may be specified as a maximum relative distance between the mean
CF, RF, or RR obtained by a future laboratory's initial calibration (Factor) and the CF, RF or RR
obtained from its calibration verification standard (FactorVER). The maximum allowable deviation is based
on the pooled relative standard deviation (RSDpooied) calculated in Section 3.2.2.

1. Determine kVER by multiplying the 97.5th percentile of a Student's t distribution with (m[n-l])

degrees of freedom times the square root of (1+1/h), where there are n points in the calibration and m

For a five-point calibration, the Student's t value is 2.0, resulting in combined multipliers of 2.4 for a
three-point calibration, and 2.2 for a five-point calibration.

2. The calibration verification criterion for the new method would then be stated as the maximum
percent difference as follows:

4. Calculate RSDmax as the smaller of 35% and:

RSDmax k(RSDpooied)

laboratories:

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(FactorVER — Factor\

Percent Difference = 100 x I		I < kVER RSDpooied

y Factor J

where:

Factor = The "Factor" terms are replaced by the CF, RF or RR terms, based on the quantitation
approach described in the method in question

For example, if the calibration verification criterion, calculated as kvm RSDpooled, equals 17%, then the
difference between the Factor from the initial calibration and the FactorVER from the calibration
verification sample must be less than or equal to 17% of the Factor.

When using either the concentration or the recovery approach, the calculations are very similar to
those used for the "factor" limits shown above.

3. Calculate the upper and lower QC acceptance criteria for the known concentration of the analyte in
the calibration verification standard, using the lower and upper percentages calculated in Step 2
above:

Lower limit = (Lower Percentage inStep 2) x (Known Concentration in Standard)
Upper limit = (Upper Percentage in Step 2) x (Known Concentration in Standard)

Alternatively, calibration verification criteria may be specified as the range of acceptable recoveries
calculated for the analytes in the calibration verification standard, using the lower and upper percentages
calculated in Step 2 above to create a window around 100% recovery.

Initial and Ongoing Precision and Recovery

For the IPR and OPR tests, QC acceptance criteria are calculated using the mean percent recovery and the
standard deviation of recovery from the IPR tests of four aliquots of the reference matrix and the OPR test
of one aliquot of the reference matrix (for a total of five samples) in nine laboratories. The QC acceptance
criteria are developed using the following steps:

1. Calculate the mean percent recovery (X) for each analyte, based on all data points from all

laboratories, the between-laboratory standard deviation (sb) of the mean results for each of the six or
more laboratories (standard deviation of the nine laboratory means X1 + X2 + ... X9), and the pooled
within-laboratory standard deviation (s„). The value of s„ is calculated as the square root of the mean
of all within-laboratory variances. For example, for nine laboratories:

2™ iO0 -

where:

Xj = The mean percent recovery for the jth laboratory
m = The number of laboratories, and

X = The overall mean of the percent recoveries from all laboratories

S,2 + Sn +

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Note: GDIT will provide direction to the participating laboratories to ensure they are spiking IPR
and OPR samples at the same concentration.

2. QC acceptance criteria for IPR recovery - Calculate the combined standard deviation for
interlaboratory variability and estimation of the mean (s) as:

3.	Calculate the QC acceptance criteria for recovery in the IPR test by constructing a ฑ 2.3 sc window
around the mean percent recovery X, where 2.3 is the 97.5th percentile Student's t value for 10
degrees of freedom (an estimated degrees of freedom based on the variance ratios observed with EPA
Method 1625):

Lower limit (%) = X — 2.3sc
Upper limit (%) = X + 2.3sc

If more than 9 laboratories are used, the degrees of freedom for t will increase, but a complete
calculation is beyond the scope of this document. An approximation of degrees of freedom equal to
the number of laboratories will serve for most situations.

4.	QC acceptance criterion for IPR precision - The maximum acceptable RSD for the four IPR aliquots
is approximated by a 95% upper confidence limit around the observed RSD of the results from all of
the laboratories. The RSDipr (computed as sw divided by X) is multiplied by the square root of a 95th
percentile lvalue with 3 degrees of freedom in the numerator and m (n - 1) degrees of freedom in the
denominator, where m = the number of laboratories, and n is the number of data points per laboratory.
For example, the resulting multiplier on the RSD for nine laboratories and five data points per
laboratory will then be 1.7, and the QC acceptance criterion for precision in the IPR test is calculated
as follows:

Maximum RSDipr = (1.7) x RSDipr

5.	QC acceptance criteria for OPR recovery - Calculate the combined standard deviation for
interlaboratory variability and estimation of the mean (sc) as:

where:

m = the number of laboratories, and
n = the number of data points per laboratory.

For 9 laboratories and 5 data points per laboratory, the calculation becomes:

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where:

m = the number of laboratories, and
n = the number of data points per laboratory.

For 9 laboratories and 5 data points per laboratory,

M

6. Calculate the QC acceptance criteria for recovery in the OPR test by constructing a ฑ 2.1 sc window
around the mean percent recovery X, where 2.1 is the 97.5th percentile Student's t value for 19
degrees of freedom (an estimated degrees of freedom based on the variance ratios observed with EPA
Method 1625):

Lower limit (%) = X — 2.1 sc
Upper limit (%) = X + 2.1 sc

If more than 9 laboratories are used, the degrees of freedom for t will increase, but a complete
calculation is beyond the scope of this document. An approximation of degrees of freedom equal to
the number of laboratories will serve for most situations.

Matrix Spike and Matrix Spike Duplicate

Results of the MS/MSD analyses performed in the validation study are used to develop the MS/MSD QC
acceptance criteria. Calculate the MS/MSD performance criteria as follows:

1. Calculate the mean and sample standard deviation of the recoveries of each MS/MSD pair, and then
compute the overall mean recovery X, the between-laboratory standard deviation (sb) of the mean
results for each of the nine laboratories, and the pooled within-laboratory standard deviation (s„) for
each target analyte using the MS and MSD analyses.

where:

Xj = The mean percent recovery for the jth laboratory
m = The number of laboratories, and

X = The overall mean of the percent recoveries from all laboratories

In order to allow for interlaboratory variability, calculate the combined standard deviation (sc) for
interlaboratory variability and estimation of the mean as:

where:
m = t

the number of laboratories.

For nine labs, this becomes:

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*-JCtVฉ4

2.	QC acceptance criteria for MS/MSD recovery - Calculate the QC acceptance criteria for recovery in
the MS/MSD test by constructing a ฑ 2.2sc window around the mean percent recovery (X) using the
combined standard deviation. This factor comes from a t value for an estimated 11 degrees of
freedom (based on this experimental design and variance ratios observed in Method 1625):

Lower limit (%) = X — 2.2sc
Upper limit (%) = X + 2.2sc

If more than 9 laboratories are used, the degrees of freedom for t will increase, but a complete
calculation is beyond the scope of this document. An approximation of degrees of freedom equal to
the number of laboratories plus 2 will serve for most situations.

Note: For highly variable methods, it is possible that the lower limit for recovery for both the IPR
and OPR analyses will be a negative number. In these instances, the data should either be log-
transformed and the recovery window recalculated, or the lower limit established as
"detected," as was done with some of the methods in 40 CFR Part 136, Appendix A.

3.	QC acceptance criteria for MS/MSD relative percent difference (RPD) - To evaluate a 95% upper
confidence limit for precision, the RSD (computed using the pooled within-laboratory standard
deviation s„ of the MS/MSD samples, divided by X, is multiplied by the square root of the 95th
percentile /ฆ' value with 1 degrees of freedom in the numerator and m degrees of freedom in the
denominator multiplied by the square root of 2 (i. e., a/2), where m is the number laboratories. The
resulting multiplier on the RSD for 3 laboratories will then be 3.2. The QC acceptance criterion for
precision in the MS/MSD test (RPDmax) is calculated as follows:

RPDmax = 3.2 RSD

Blanks

Establish the QC acceptance criteria for blanks. The historical requirement has been that the concentration
of an analyte in a blank must be below the ML or below one-third (1/3) the regulatory compliance level,
whichever is higher. However, other limits (including those below the ML) may be used for a specific
method. In instances where the level of the blank is close to the regulatory compliance level or the level at
which measurements are to be made, it may be necessary to require multiple blank measurements and
establish the QC acceptance criteria based on the mean of the blank measurements plus two standard
deviations of the blank measurements.

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Appendix B

Draft EPA Method 1621

Given the size of the method document, it will be provided as a separate file. The method can also be
found at Draft Method 1621 Screening Method for the Determination of Adsorbable Organic
Fluorine(AOF) in Aqueous Matrices by Combustion Ion Chromatography (CIC)

Note: Draft EPA Method 1621 in its current form does not represent a final product and the method has
been released for public comment. EPA and GDIT anticipate revising the method as a result of
the multi-laboratory validation study. Therefore, EPA and GDIT ask that readers and reviewers of
this study plan not to distribute the plan without first consulting S. Bekah Burket (EPA/OW). If
needed, a version of this study plan can be provided by GDIT. Laboratory participants in the
study may be asked to sign a non-disclosure agreement prior to the start of the study.

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