o
Guidance for Labeling Externally
Validated Laboratory Analytical
Data for Superfund Use
-------
This page left intentionally blank.
-------
OSWER No. 9200.1-85
EPA 540-R-08-005
13 January 2009
www.epa.gov
Guidance for Labeling Externally Validated
Laboratory Analytical Data for Superfund Use
U.S. Environmental Protection Agency
Office of Solid Waste and Emergency Response
Washington, DC 20460
-------
This page left intentionally blank.
-------
NOTICE
The policies and procedures set forth here are intended solely as guidance to the United States
Environmental Protection Agency (EPA), other government employees and contractors. This
guidance does not constitute rulemaking by the EPA, and cannot be relied upon to create a
substantive or procedural right enforceable by any party in litigation with the United States.
EPA may take action that is at variance with the policies and procedures in this guidance and
may change them at any time without public notice.
-------
This page left intentionally blank.
-------
Table of Contents
Page
1.0 Background 1
2.0 Scope of this Guidance 1
3.0 Context for Superfund Laboratory Analytical Data Verification and Validation 3
4.0 Recommended Approach to Laboratory Analytical Data Verification and
Validation 4
5.0 Describing the Stages and Processes Used to Verify and Validate Laboratory
Analytical Data 5
6.0 Communicating the Stages and Process Used for Laboratory Analytical Data
Verification and Validation 6
7.0 Conclusion 7
8.0 References 7
Appendix A: Laboratory Analytical Data Verification and Validation Stages and
Checks: Description, Order, and Labeling of Validated Laboratory Analytical Data
Packages 8
Appendix B: Recommended Terminology and Labels for Communicating the Stages
and Processes Used for Laboratory Analytical Data Verification and
Validation 14
Appendix C: Suggested Narrative(s) for Laboratory Analytical Data Package
Verification and Validation "Summary" Section(s) 15
Appendix D: Example Laboratory Analytical Results Electronic Spreadsheet with
Analytical Data Package Validation Stage Column 16
Appendix E: Glossary of Terms 17
-------
This page left intentionally blank.
11
-------
1.0 Background
Each year, well over $25 million are spent through Superfund contracts to analyze soils,
water, sediments, and other media for the presence of contaminants of potential concern.
Additional resources are often used by the U.S. Environmental Protection Agency (EPA) to
review (i.e., verify and validate) the resulting laboratory analytical data packages. These reviews
are conducted in part to ensure that data produced in support of EPA's environmental decision
making are of adequate quality and usability for their intended purpose (see CIO 2105.0). Since
there are often different procedures used to evaluate laboratory data quality in different EPA
organizations and through different EPA contracts, the manner in which the results of these
reviews are communicated to decision-makers may also vary. Such variability may create
problems when data sets developed by different organizations or contractors are evaluated
together in support of a particular site activity (e.g., when data are gathered over long periods of
time; or when data are gathered quickly by multiple groups in support of a time-critical response
action). Because of this potential variability, and because of the complex nature of commonly
used analytical data verification and validation procedures, it is important to minimize ambiguity
in communicating the nature of the procedures used for laboratory data reviews to data users.
This guidance is designed to help increase national consistency and improve communication and
understanding about the nature of verification and validation conducted on laboratory analytical
data for Superfund use.
The attached guidance recommends the use of consistent terminology by external data
reviewers in describing the scope and content of verification and validation conducted on
laboratory analytical data packages developed in support of Superfund site activities. Through
the use of this guidance, EPA decision makers should be readily able to determine which
analytical data verification or validation procedures have been performed on each laboratory
analytical data package regardless of which region, program office, or contractor provided the
review.
Note: Analytical data verification by an external party generally consists of a completeness
check to confirm that all data requested from the laboratory have been received and comply with
specified requirements. Analytical data validation by an external party generally consists of an
analyte and sample specific process for evaluating compliance of the laboratory data received
with methods, procedures or contract requirements. Definitions of terms (including verification
and validation) used in this guidance are given in the Glossary (Appendix E). Generally, this
guidance uses terms consistent with other EPA documents and guidance.
2.0 Scope of this Guidance
This guidance focuses on the data verification and validation of chemical and
radiochemical laboratory analytical data by external parties. For the purposes of this guidance,
external parties are defined as organizations (including Governmental entities, contractors, or
vendors) that conduct analytical data review, verification, and validation activities and that are
not part of the immediate laboratory that generates the subject analytical data (but that are part of
the overall project-specific data review process).
-------
This guidance draws on generally accepted procedures used in the verification and
validation of laboratory analytical data generated for chemical and radiochemical parameters.
EPA Regions are encouraged to use this guidance in conjunction with the EPA Contract
Laboratory Program National Functional Guidelines (NFGs) for Data Review, EPA Regional
guidance, contract, or method-specific data validation documents (e.g., Multi-Agency
Radiological Laboratory Analytical Protocols Manual). The types of review addressed by this
guidance correspond to the analysis verification and validation portion of the data review steps
given in the Uniform Federal Policy for Quality Assurance Project Plans (UFP-QAPP) Manual
(IDQTF 2005). The most appropriate approach for verifying and validating a particular analytical
data set typically will depend on many factors, including the goals of the specific data collection
activity, the nature and completeness of the data package received (hard copy and/or electronic),
and available program resources (time and/or personnel).
This guidance does not address or discuss the evaluation of the sampling portion or
overall usability (e.g., data usability assessments outlined in the UFP-QAPP Manual) of
laboratory analytical data sets. Nor does it attempt to address the verification and validation of
all types of analytical data (e.g., this guidance does not address data collected from field
sampling measurements like pH and conductivity, or microbiological methods). However, if the
appropriate quality control documentation and information is provided and defined, this guidance
may be useful in labeling the scope and content of verification and validation performed on
analytical data generated by less traditional means such as field analytical methods (e.g., X-ray
fluorescence, image analysis, immunoassay methods, direct sensing, etc.).
In addition, this guidance does not address the following:
• Specifications and types of Quality Assurance Project Plans (QAPPs), method,
procedural, or contract requirements;
• Specific actions taken to determine analytical data quality based on comparing the
laboratory reported data to any QAPP, method, procedural, or contract requirements;
• Validation qualifiers used to qualify the analytical data;
• Exact procedures used to carry out these analytical data verification and
validation checks;
• The appropriate "independence" of the external parties carrying out the analytical
data validation;
• Reporting requirements (hardcopy and/or electronic);
• Appropriate scope and content (e.g., levels, tiers, or stages) of analytical data
verification or validation required for specific site decisions; or
-------
• Routine internal analytical data verification, validation, or review procedures used
by laboratories that generate analytical data.
3.0 Context for Superfund Laboratory Analytical Data Verification and Validation
Figure 1 presents the broader context in which analytical data verification and validation
by external parties typically occurs. The shaded area depicts the part of the process that is the
focus of this guidance.
Since the collection and review of environmental information is often expensive, data are
generated typically only when a specific decision requires it (e.g., to define the nature and extent
of contamination; to determine the need for emergency or remedial action; to evaluate the
effectiveness of cleanup technologies, or progress in the remediation of contaminated media).
Therefore, the first recommended step in this process is for the anticipated data users to scope the
nature of the decisions of interest and the related data requirements (Figure 1, Step 1). A project-
specific QAPP should be developed to document the procedures for the collection, review, and
use of the environmental data that reflect project scoping decisions (Step 2). A project-specific
QAPP may provide many instructions and project requirements pertaining to (but not limited to)
the contaminants of potential concern, field sampling locations, field sampling procedures,
sample preservation techniques and analytical data validation criteria. The QAPP may also
contain specific information regarding the analyses to be performed by a laboratory that includes
(but is not limited to) target analyte and/or parameter lists, the analytical and field Quality
Control (QC) criteria, along with the hardcopy and electronic reporting requirements. All
portions of the QAPP relevant to sample analysis and reporting should be communicated to the
laboratory before samples are sent to the laboratory.
FIGURE 1: TYPICAL SUPERFUND DATA GENERATION AND REVIEW PROCESS
QAPP ANALYTICAL REQUIREMENTS SENT TO LABORATORY
Project Scope
Defined
Data May Support
Future
Projects
Quality Assurance
Project Plan
(QAPP)
Requirements
Identified
©
Data Repository
e.g., Database
(Project or
General)
Field Activities
FIELD LOGS
INFORMATION
DATA USED IN PROJECT
DECISION(S)
SAMPLES
CHAIN OF
CUSTODY
INFORMATION
Data Quality
And Usability
Assessment of
Field and
Laboratory Data
Laboratory
Analysis
and Reporting
VALIDATED
ANALYTICAL
DATA
ANALYTICAL DATA
PACKAGE
(with Laboratory Qualifiers)
External Party
Validation of the
Laboratory
Analytical Data
-------
Generally, samples are then taken in the field based on the QAPP procedures and
requirements (Step 3). There are typically two data flows created as a result of the field
sampling activities:
(1) Samples and chain-of-custody information can be sent to a laboratory or laboratories;
and,
(2) Field data, including sample location information, can be sent to the Project Manager and
support staff.
The laboratory (or laboratories) then analyzes the samples and reports the results
according to the protocols specified in the contract, or analytical method(s) (Step 4). The
laboratory analytical data package (with any qualifiers noted by the laboratory itself) may then
be sent to an external party (data validator) who can verify and validate the analytical data (or
some percentage of it) using guidelines and/or requirements identified in specific national or
regional analytical data validation guidance, analytical method(s) or contract (Step 5). The
validated laboratory analytical data (now with external party validation qualifiers) then may be
merged with information from the field logs (including sample location data). Generally, the
overall data quality and usability is then assessed based on the review of field procedures and
conditions during sampling (Step 6). Finally, any ultimate decisions made that rely on this data
may be documented and stored in a data repository along with supporting field and laboratory
data (Step 7). When stored appropriately, these data may be re-used or considered in future site
decisions.
This guidance addresses only those verification and validation procedures that are
provided by external parties for laboratory analytical data (see shaded area in Figure 1). In
context of the UFP-QAPP Manual (IDQTF 2005), these procedures would be part of the UFP-
QAPP Table 8 data review steps I (completeness) and Ha (check compliance with method,
procedure, and contract requirements) for analysis.
4.0 Recommended Approach to Laboratory Analytical Data Verification and
Validation
When called for by the QAPP, a laboratory analytical data package (electronic and/or
hardcopy) developed for the Superfund program may be verified and validated by an external
party (Figure 1, Step 5) as follows:
(1) First, the analytical data package should be checked or verified for completeness to
ensure that all data requested is actually present in the data deliverables. The reporting
requirements for the laboratory analytical data package should be specified by the project,
contract or method. This is a critical step as analytical data validation (given in the following
sub sections) may not be possible if any part of the requested laboratory data deliverable is not
present.
(2) This completeness check should be followed by a compliance check to compare the
documented sample receipt conditions and analytical QC results in the analytical data package to
-------
the acceptance criteria, requirements or guidelines present in national or regional data validation
documents, analytical method(s) or contract. The analytical QC results generally consist of two
parts: (1) sample-related QC; and, (2) instrument-related QC.
(3) The completeness and compliance checks may be followed by recalculation checks. The
laboratory reported values (e.g., sample results, instrument calibration results) can be checked by
recalculating them using the data from instrument outputs reported by the laboratory to ensure
that the laboratory used proper procedures to determine the final reported values. This may be
done on a fraction or percentage of results or on all results reported by the laboratory. When a
fraction or percentage of results is checked, additional results should be recalculated and checked
if any issues are noted with the first recalculated values.
(4) Finally, the actual instrument outputs may be checked to ensure that the laboratory-
reported analytes have been correctly identified and quantitated. This also generally may be
done on a fraction or percentage of instrument outputs. Additional outputs should be checked if
any issues are noted with the first fraction or percentage reviewed.
External party reviewers should document their findings by adding appropriate validation
qualifiers (as necessary) to the sample results in the laboratory data packages based on the
compliance, recalculations, and instrument output checks.
The process by which analytical data verification and validation should be carried out
depends on the type of the laboratory analytical data package received by the external party. The
laboratory analytical data package may be a hard copy data package, an electronic data
deliverable, or both. The external party may verify and validate the analytical data using wholly
manual, wholly electronic or a combination of manual and electronic processes, depending on
the type of laboratory analytical data package and review instructions received. The nature and
extent of verification and validation of analytical data needed to meet project goals should be
specifically identified in the QAPP. The verified and validated analytical data may be sent either
as a hard copy or an electronic file to the data recipient or EPA customer.
5.0 Describing the Stages and Processes Used to Verify and Validate Laboratory
Analytical Data
For the purposes of this guidance, the following terminology is recommended for use by
external parties to describe the stages (extent) and processes used to validate laboratory
analytical data packages.
5.1 Analytical Data Verification and Validation Stages
(1) A verification and validation based only on completeness and compliance of sample
receipt condition checks should be called a Stage 1 Validation.
(2) A verification and validation based on completeness and compliance checks of sample
receipt conditions and ONLY sample-related QC results should be called a Stage 2A Validation.
-------
(3) A verification and validation based on completeness and compliance checks of sample
receipt conditions and BOTH sample-related and instrument-related QC results should be called
a Stage 2B Validation.
(4) A verification and validation based on completeness and compliance checks of sample
receipt conditions, both sample-related and instrument-related QC results, AND recalculation
checks should be called a Stage 3 Validation.
(5) A verification and validation based on completeness and compliance checks of sample
receipt conditions, both sample-related and instrument-related QC results, recalculation checks,
AND the review of actual instrument outputs should be called a Stage 4 Validation.
The recommended minimum baseline checks conducted for each stage of analytical data
verification and validation are described in more detail in Appendix A.
Note: Using higher stages of analytical verification and validation does not typically result in
higher data quality. However, the quality of the analytical data becomes more transparent as
more stages of verification and validation are conducted. As a result, the usability of the
analytical data for its intended use becomes more apparent.
5.2 Analytical Data Verification and Validation Processes
(1) A verification and validation based only on an electronic deliverable received from the
laboratory and conducted using automated electronic data review tools should be described as
Electronic Validation.
(2) A verification and validation based on an electronic deliverable as well as a hardcopy
data package received from the laboratory using electronic data review tools and manual
procedures should be described as Electronic and Manual Validation.
(3) A verification and validation based on only a hardcopy data package received from the
laboratory using manual procedures should be described as Manual Validation.
Recommended summary terminology and labels that communicate both the stages of
analytical data verification and validation and the processes used for conducting the verification
and validation are given in Appendix B.
6.0 Communicating the Stages and Processes Used for Laboratory Analytical Data
Verification and Validation
External parties should use one of the labels given in Appendix B to describe the stages
and processes used to verify and validate particular laboratory analytical data packages (e.g.,
Sample Delivery Group). The verified and validated laboratory analytical data packages (with
the appropriate labels) can then be sent to the data recipient for further data quality assessment
(Figure 1, Step 6).
-------
Suggested narratives for external parties to summarize the stage and manner of
verification and validation for each verified and validated laboratory analytical data package are
provided in Appendix C. It is recommended that this type of language be included in the
accompanying transmittal memorandum in a section entitled "Analytical Data Package
Validation Stage Summary."
If the external party delivers verified and validated laboratory analytical data in an
electronic data deliverable (e.g., spreadsheet, a text file, an extensible Markup Language [XML]
file, etc.), it is recommended that one of the labels given in Appendix B be appended to each
analyte or parameter (by analytical method) in a column or data element named "Analytical Data
Package Validation Stage." In this case the label appended to each analyte or parameter should
correspond to the stage and process used by the external party to verify and validate the overall
laboratory analytical data package (hardcopy and electronic). An example of an electronic
spreadsheet format linking analyte-specific information with a recommended label is given in
Appendix D.
Note: It is recommended that the external party label laboratory analytical data (within a
validated laboratory analytical data package) that have not been verified and validated by them
as "Not Validated".
7.0 Conclusion
The recommended stages used for verifying and validating laboratory analytical data
addressed in this guidance constitute an important part of the overall laboratory analytical data
quality assessment and usability assessment processes. Use of these labels by external parties
should provide a consistent mechanism to communicate the nature and extent of their analytical
data verification and validation procedures to their clients. The labels also should assist data
recipients and future data users in merging verified and validated laboratory analytical data sets
from different sources.
Note: In order to assess the usability of the laboratory analytical data, additional information
should be considered including (but not limited to) the procedures used to collect the samples,
field parameters, field location measurements, comparison of results with QAPP measurement
performance criteria, and overall project quality objectives.
8.0 References
CIO 2105.0 (May 2000). Policy and Program Requirements for the Mandatory Agency-wide
Quality System, U.S. Environmental Protection Agency, Washington, DC,
http://www.epa.gov/qualitv/qa docs.html
IDQTF. 2005. (March 2005), Uniform Federal Policy for Quality Assurance Project Plans
(UFP-QAPP) Evaluating, Assessing, and Documenting Environmental Data Collection
and Use Programs., Intergovernmental Data Quality Task Force, EPA-505-B-04-900A.
March, http://www.epa.gov/fedfac/pdf/ufp qapp vl 0305.pdf
-------
APPENDIX A
Laboratory Analytical Data Verification and Validation Stages and Checks:
Description, Order, and Labeling of Validated Laboratory Analytical Data Packages
1.0 Recommended Minimum Baseline Checks Used in the Stages of Laboratory
Analytical Data Verification and Validation.
A recommended sequence of laboratory analytical data verification (completeness) and
validation (compliance, recalculations, and instrument output evaluations) checks is summarized
below (including the minimum baseline checks for each validation stage). Specific checks will
depend on the analytical method being verified and validated and the requirements and
guidelines present in national or regional data validation documents, analytical method(s) or
contract. Each higher stage of verification and validation should include all the relevant checks
defined in the next lower stage or stages. For example, there are 23 checks listed as part of a
Stage 2B verification and validation (these include check numbers 1-9 noted in Stage 1, numbers
10-16 noted in Stage 2A, and numbers 17-23 noted in Stage 2B). The recommended checks
discussed below are not a complete list of all the checks that can be done for a particular
laboratory analytical data package as these will vary depending on the method(s) used to
generate the data. However, the list of checks given in each stage covers a majority of checks
conducted during the verification and validation of Superfund laboratory analytical data and
represents a recommended baseline level of checks that can be performed during the verification
and validation process (as appropriate for the method).
1.1 Recommended Stage 1 Verification and Validation Checks
Stage 1 validation of the laboratory analytical data package consists of verification and
validation checks for the compliance of sample receipt conditions, sample characteristics (e.g.,
percent moisture), and analytical results (with associated information). It is recommended that
the following minimum baseline checks (as relevant) be performed on the laboratory analytical
data package received for a Stage 1 validation label:
(1) Documentation identifies the laboratory receiving and conducting analyses, and includes
documentation for all samples submitted by the project or requester for analyses.
(2) Requested analytical methods were performed and the analysis dates are present.
(3) Requested target analyte results are reported along with the original laboratory data
qualifiers and data qualifier definitions for each reported result (and the uncertainty of each result
and clear indication of the type of uncertainty reported if required, e.g., for radiochemical
analyses).
(4) Requested target analyte result units are reported (along with their associated uncertainty
units if required, e.g., for radiochemical analyses).
-------
(5) Requested reporting limits for all samples are present and results at and below the
requested (required) reporting limits are clearly identified (including sample detection limits if
required).
(6) Sampling dates (including times if needed), date and time of laboratory receipt of
samples, and sample conditions upon receipt at the laboratory (including preservation, pH and
temperature) are documented.
(7) For radiochemical analyses, the sample-specific critical values (sometimes called "critical
level," "decision level" or "detection threshold") and sample specific minimum detectable value,
activity or concentration for all samples are reported and results at and below the requested
(required) critical values are clearly identified.
(8) For radiochemical analyses, the chemical yield (if applicable to the method) and
reference date and time (especially for short lived isotopes) is reported for all samples (as
appropriate).
(9) Sample results are evaluated by comparing sample conditions upon receipt at the
laboratory (e.g., preservation checks) and sample characteristics (e.g., percent moisture) to the
requirements and guidelines present in national or regional data validation documents, analytical
method(s) or contract.
1.2 Recommended Stage 2A Verification and Validation Checks
Stage 2A validation builds on the validation conducted in Stage 1. Stage 2A validation of
the laboratory analytical data package consists of the Stage 1 validation plus the verification and
validation checks for the compliance of sample-related QC. It is recommended that the
following additional minimum baseline checks (as relevant) be performed on the laboratory
analytical data package received for a Stage 2A Validation label:
(10) Requested methods (handling, preparation, cleanup, and analytical) are performed.
(11) Method dates (including dates, times and duration of analysis for radiation counting
measurements and other methods, if needed) for handling (e.g., Toxicity Characteristic Leaching
Procedure), preparation, cleanup and analysis are present, as appropriate.
(12) Sample-related QC data and QC acceptance criteria (e.g., method blanks, surrogate
recoveries, deuterated monitoring compounds (DMC) recoveries, laboratory control sample
(LCS) recoveries, duplicate analyses, matrix spike and matrix spike duplicate recoveries, serial
dilutions, post digestion spikes, standard reference materials) are provided and linked to the
reported field samples (including the field quality control samples such as trip and equipment
blanks).
(13) Requested spike analytes or compounds (e.g., surrogate, DMCs, LCS spikes, post
digestion spikes) have been added, as appropriate.
-------
(14) Sample holding times (from sampling date to preparation and preparation to analysis) are
evaluated.
(15) Frequency of QC samples is checked for appropriateness (e.g., one LCS per twenty
samples in a preparation batch).
(16) Sample results are evaluated by comparing holding times and sample-related QC data to
the requirements and guidelines present in national or regional data validation documents,
analytical method(s) or contract.
1.3 Recommended Stage 2B Verification and Validation Checks
Stage 2B validation builds on the validation conducted in Stage 2A. Stage 2B validation
of the laboratory analytical data package consists of the Stage 2A validation plus the verification
and validation checks for the compliance of instrument-related QC. It is recommended that the
following additional minimum baseline checks (as relevant) be performed on the laboratory
analytical data package received for a Stage 2B Validation label:
(17) Initial calibration data (e.g., initial calibration standards, initial calibration verification
[ICV] standards, initial calibration blanks [ICBs]) are provided for all requested analytes and
linked to field samples reported. For each initial calibration, the calibration type used is present
along with the initial calibration equation used including any weighting factor(s) applied and the
associated correlation coefficients, as appropriate. Recalculations of the standard concentrations
using the initial calibration curve are present, along with their associated percent recoveries, as
appropriate (e.g., if required by the project, method, or contract). For the ICV standard, the
associated percent recovery (or percent difference, as appropriate) is present.
(18) Appropriate number and concentration of initial calibration standards are present.
(19) Continuing calibration data (e.g., continuing calibration verification [CCV] standards and
continuing calibration blanks [CCBs]) are provided for all requested analytes and linked to field
samples reported, as appropriate. For the CCV standard(s), the associated percent recoveries (or
percent differences, as appropriate) are present.
(20) Reported samples are bracketed by CCV standards and CCBs standards as appropriate.
(21) Method specific instrument performance checks are present as appropriate (e.g., tunes for
mass spectrometry methods, DDT/Endrin breakdown checks for pesticides and aroclors,
instrument blanks and interference checks for ICP methods).
(22) Frequency of instrument QC samples is checked for appropriateness (e.g., gas
chromatography-mass spectroscopy [GC-MS] tunes have been run every 12 hours).
(23) Sample results are evaluated by comparing instrument-related QC data to the
requirements and guidelines present in national or regional data validation documents, analytical
method(s) or contract.
10
-------
1.4 Recommended Stage 3 Verification and Validation Checks
Stage 3 validation builds on the validation conducted in Stage 2B. Stage 3 validation of
the laboratory analytical data package consists of the Stage 2B validation plus the recalculation
of instrument and sample results from the laboratory instrument responses, and comparison of
recalculated results to laboratory reported results. It is recommended that the following
additional minimum baseline checks (as relevant) be performed on the laboratory analytical data
package received for a Stage 3 Validation label:
(24) Instrument response data (e.g., GC peak areas, ICP corrected intensities) are reported for
requested analytes, surrogates, internal standards, and DMCs for all requested field samples,
matrix spikes, matrix spike duplicates, LCS, and method blanks as well as calibration data and
instrument QC checks (e.g., tunes, DDT/Endrin breakdowns, interelement correction factors, and
Florisil cartridge checks).
(25) Reported target analyte instrument responses are associated with appropriate internal
standard analyte(s) for each (or selected) analyte(s) (for methods using internal standard for
calibration).
(26) Fit and appropriateness of the initial calibration curve used or required (e.g., mean
calibration factor, regression analysis [linear or non-linear, with or without weighting factors,
with or without forcing]) is checked with recalculation of the initial calibration curve for each (or
selected) analyte(s) from the instrument response.
(27) Comparison of instrument response to the minimum response requirements for each (or
selected) analyte(s).
(28) Recalculation of each (or selected) opening and closing CCV (and CCB) response from
the peak data reported for each (or selected) analyte(s) from the instrument response, as
appropriate.
(29) Compliance check of recalculated opening and/or closing CCV (and CCB) response to
recalculated initial calibration response for each (or selected) analyte(s).
(30) Recalculation of percent ratios for each (or selected) tune from the instrument response,
as appropriate.
(31) Compliance check of recalculated percent ratio for each (or selected) tune from the
instrument response.
(32) Recalculation of each (or selected) instrument performance check (e.g., DDT/Endrin
breakdown for pesticide analysis, instrument blanks, interference checks) from the instrument
response.
11
-------
(33) Recalculation and compliance check of retention time windows (for chromatographic
methods) for each (or selected) analyte(s) from the laboratory reported retention times.
(34) Recalculation of reported results for each reported (or selected) target analyte(s) from the
instrument response.
(35) Recalculation of each (or selected) reported spike recovery (surrogate recoveries, DMC
recoveries, LCS recoveries, duplicate analyses, matrix spike and matrix spike duplicate
recoveries, serial dilutions, post digestion spikes, standard reference materials etc.) from the
instrument response.
(36) Each (or selected) sample result(s) and spike recovery(ies) are evaluated by comparing
the recalculated numbers to the laboratory reported numbers according to the requirements and
guidelines present in national or regional data validation documents, analytical method(s) or
contract.
Note: Selection of analytes, spikes, and performance evaluation checks for the Stage 3
validation checks for a laboratory analytical data package being verified and validated generally
will depend on many factors including (but not limited to) the type of verification and validation
being performed (manual or electronic), requirements and guidelines present in national or
regional data validation documents, analytical method(s) or contract, the number of laboratories
reporting the data, the number and type of analytical methods reported, the number of analytes
reported in each method, and the number of detected analytes.
1.5 Recommended Stage 4 Verification and Validation Checks
Stage 4 validation builds on the validation conducted in Stage 3. Stage 4 validation of
the laboratory analytical data package consists of the Stage 3 validation plus the evaluation of
instrument outputs. It is recommended that the following additional minimum baseline checks
(as relevant) be performed on the laboratory analytical data package received for a Stage 4
Validation label:
(37) All required instrument outputs (e.g., chromatograms, mass spectra, atomic emission
spectra, instrument background corrections, and interference corrections) for evaluating sample
and instrument performance are present.
(38) Sample results are evaluated by checking each (or selected) instrument output (e.g.,
chromatograms, mass spectra, atomic emission spectra data, instrument background corrections,
interference corrections) for correct identification and quantitation of analytes (e.g., peak
integrations, use of appropriate internal standards for quantitation, elution order of analytes, and
interferences).
(39) Each (or selected) instrument's output(s) is evaluated for confirmation of non-detected or
tentatively identified analytes.
12
-------
Note: Selection of instrument outputs for the Stage 4 validation checks for a laboratory
analytical data package being verified and validated generally will depend on many factors
including, but not limited to, the type of verification and validation being performed (electronic
or manual), requirements and guidelines present in national or regional data validation
documents, analytical method(s) or contract, the number of laboratories reporting the data, the
number and type of analytical methods reported, the number of analytes reported in each method,
and the number of detected analytes.
2.0 Order of Stages and Checks
It is recommended that all relevant Stage 1 checks be performed first, followed by all
relevant checks in the remaining validation stages in order of increment as required by the
project. The checks within a Stage (used for verification and validation) need not be done in any
particular order as this will vary depending on the importance of the check, type of laboratory
analytical data package received (hardcopy, electronic or both), the type of laboratory analytical
data reported (methods used), and the documents and tools used to verify and validate the
laboratory analytical data.
3.0 Labeling of Verified and Validated Laboratory Analytical Data Packages
Generally, all relevant checks within each stage should be done and validation qualifiers
added (as appropriate) to the sample results in the laboratory analytical data package (e.g.,
Sample Delivery Group) in order to label the laboratory analytical data package (or the reported
analyte or parameter) as being verified and validated to that stage.
Note: When automated data review tools are used to review analytical data sent by laboratories
in electronic data deliverables, the tools should (a) conduct all relevant checks within each stage
for each reported analyte or parameter in the electronic data deliverable; (b) automatically label
each analyte or parameter with the appropriate label from Appendix B, and (c) provide this label
for each analyte or parameter in the tool's electronic outputs (in a column or a data element
named "Analytical Data Validation Stage").
13
-------
APPENDIX B
Recommended Terminology and Labels for Communicating the Stages and Processes
Used for Laboratory Analytical Data Verification and Validation
The following labels and/or codes are recommended for use by external parties when
communicating to data recipients and data users the steps as well as the manner used for
laboratory analytical data verification and validation.
Label
Stage 1 Validation Electronic
Stage 1 Validation Manual
Stage 1 Validation Electronic and Manual
Stage 2 A Validation Electronic
Stage 2 A Validation Manual
Stage 2A Validation Electronic and Manual
Stage 2B Validation Electronic
Stage 2B Validation Manual
Stage 2B Validation Electronic and Manual
Stage 3 Validation Electronic
Stage 3 Validation Manual
Stage 3 Validation Electronic and Manual
Stage 4 Validation Electronic
Stage 4 Validation Manual
Stage 4 Validation Electronic and Manual
Not Validated
Corresponding Label Code
S1VE
S1VM
S1VEM
S2AVE
S2AVM
S2AVEM
S2BVE
S2BVM
S2BVEM
S3VE
S3VM
S3VEM
S4VE
S4VM
S4VEM
NV
14
-------
APPENDIX C
Suggested Narrative(s) for Laboratory Analytical Data Package Verification and
Validation "Summary" Section(s)
Section Name: Analytical Data Package Validation Stage Summary
Example 1:
Sample Delivery Groups ABC123, ABC124, and ABC125 have the following label:
Stage_4_Validation_Manual (S4VM).
Example 2:
All sample results in the attached laboratory analytical data package Number 23 have the
following label:
Stage_2B_Validation_Electronic_And_Manual(S2BVEM).
Example 3:
Sample Delivery Groups ABC 126 and ABC 127 have the following label:
Stage_4_Validation_Electronic_And_Manual (S4VEM).
Sample Delivery Group ABC128 has the following label:
Stage_2B_Validation_Manual(S2BVM).
Example 4:
All sample results (except those analyzed by Method 8260 Volatile Organic Analysis) in Sample
Delivery Group ABC 129 have the following label:
Stage_4_Validation_Manual (S4VM).
All sample results for Method 8260 in Sample Delivery Group ABC 129 were not validated (per
client request) and have the following label:
Not_Validated (NV).
15
-------
APPENDIX D
Example Laboratory Analytical Results Electronic Spreadsheet
With a Column for the Analytical Data Package Validation Stage
Lab
Name
ABC
ABC
ABC
ABC
ABC
ABC
ABC
ABC
ABC
ABC
ABC
Client
Sample
ID
A1231
A1231
A1231
A1231
A1231
A1231
A1231
A1231
A1231
A1231
A1231
Matrix
ID
Water
Water
Water
Water
Water
Water
Water
Water
Water
Water
Water
Analyte
Name
Benzene
Toluene
Ethyl
Benzene
m,p-
Xylene
Acetone
Chloro
methane
Styrene
Chloro
ethane
o-Xylene
Vinyl
Chloride
Cyclo
Hexane
Client
Method
ID
CLPVOA
CLPVOA
CLPVOA
CLPVOA
CLPVOA
CLPVOA
CLPVOA
CLPVOA
CLPVOA
CLPVOA
CLPVOA
Result
6.6
<5.0
7.7
<5.0
<5.0
<5.0
<5.0
<5.0
<5.0
<5.0
<5.0
Result
Units
ug/L
ug/L
ug/L
ug/L
ug/L
ug/L
ug/L
ug/L
ug/L
ug/L
ug/L
Validation
Qualifier
J
UJ
J
UJ
U
U
U
U
U
U
U
Analytical
Data
Package
Validation
Stage
S3VE
S3VE
S3VE
S3VE
S3VE
S3VE
S3VE
S3VE
S3VE
S3VE
S3VE
16
-------
APPENDIX E
GLOSSARY OF TERMS1
Aliquot — A measured portion of a sample taken for analysis.
Analyte — A property which is to be measured.
Analytical batch — A group of samples, including quality control samples, which are processed
together using the same method, the same lots of reagents, and at the same time or in continuous,
sequential time periods. Samples in each batch should be of similar composition and share
common internal quality control standards.
Blank — A sample subjected to the usual analytical or measurement process to establish a zero
baseline or background value; a sample that is intended to contain none of the analytes of
interest. A blank is used to detect contamination during sample handling preparation and/or
analysis.
Calibration — A set of operations that establish, under specific conditions, the relationship
between values of quantities indicated by a measuring instrument or measuring system, or
value's represented by a material measure of a reference material, and the corresponding values
realized by standards.
Completeness — A measure of the amount of valid data obtained from a measurement system
compared with the amount that was expected to be obtained under correct, normal conditions.
Continuing calibration verification (CCV) — A check of the initial calibration that is
performed during the course of an analytical shift at periodic intervals using a Calibration Check
Standard. Continuing calibration verification applies to both external standard and internal
standard calibration techniques, as well as to linear and non-linear calibration models. The
purpose is to assess the continued capability of the measurement system to generate accurate and
precise data over a period of time.
Data review — The process of examining and/or evaluating data to varying levels of detail and
specificity by a variety of personnel who have different responsibilities within the data
management process. It includes verification, validation, and usability assessment.
Data user — Technical and other personnel responsible for engineering, scientific, and legal
evaluations that are the basis for site decisions. Data users are responsible for determining data
needs required to satisfy project objectives from their perspective (remedy, risk, compliance,
etc.).
1 Where available, the definitions and terms were taken from the "Glossary of Quality Assurance and Related
Terms" in the Intergovernmental Data Quality Task Force, (March 2005), Uniform Federal Policy for Quality
Assurance Plans (UFP-QAPP) Manual, EPA-505-B-04-900A,
http://www.epa.gov/fedfac/documents/qualitvassurance.htm
17
-------
Electronic data evaluation — The use of computers and/or software to assess and process
laboratory analytical data in meeting compliance with established quality control requirements.
Environmental data — Any parameters or pieces of information collected or produced from
measurements, analyses, or models of environmental processes, conditions, and effects of
pollutants on human health and the ecology, including results from laboratory analyses or from
experimental systems representing such processes and conditions. It also includes information
collected directly from measurements, produced from models, and compiled from other sources
such as databases or the literature.
Equipment blank — A sample of water, or other appropriate media, free of measurable
contaminants poured over or through decontaminated field sampling equipment that is
considered ready to collect or process an additional sample. The purpose of this blank is to
assess the adequacy of the decontamination process. Also called rinse blank or rinsate blank.
External party(ies) — Organizations (including Governmental entities, contractors, or vendors)
that conduct analytical data review, verification, and validation activities and that are not part of
the immediate laboratory that generates the analytical data.
Extensible Markup Language (XML) — A flexible way to create common information
formats and share both the format and the data on the World Wide Web, intranets, and
elsewhere. XML can be used by any individual or group of individuals or companies that wants
to share information in a consistent way.
Holding time — The period of time a sample may be stored prior to its required preparation
and/or analysis.
Instrument quality control (QC) sample — A sample of known composition analyzed
concurrently with environmental samples to verify the performance of one or more components
of the analytical measurement process. Those components can include retention time, resolution,
recovery, degradation, etc.
Internal standard — A standard added to a test portion of a sample in a known amount and
carried through the entire determination procedure as a reference for calibrating and controlling
the precision and bias of the applied analytical method.
Laboratory(ies) — A place equipped for experimental study in science or for testing and
analysis. Laboratories can be found in government or industry facilities, schools and
universities, or in mobile or semi-moveable structures (e.g., specialized vehicles, trailers,
temporary office structures, ships, and aircraft).
Laboratory control sample (LCS) — A sample of known composition prepared using
contaminant-free water or in inert solid that is spiked with analytes of interest at the midpoint of
the calibration curve or at the level of concern. It is prepared and analyzed in the same batch of
regular samples using the same sample preparation method, reagents, and analytical methods
employed for regular samples.
18
-------
Laboratory duplicates/replicates — Two or more representative aliquots taken from one
sample by the laboratory and analyzed in the same laboratory. Laboratory duplicate/replicate
samples are quality control samples that are used to assess intralaboratory preparatory and
analytical precision as well as sample homogeneity.
Manual data evaluation — The examination of laboratory analytical data by individuals or
groups of people using standard operating procedures and guidance in meeting compliance with
established quality control requirements.
Matrix — The material of which the sample is composed, such as water, soil/sediment, or other
environmental medium.
Matrix spike — A sample prepared by adding a known concentration of a target analyte to an
aliquot of a specific homogenized environmental sample for which an independent estimate of
the target analyte concentration is available. The matrix spike is accompanied by an independent
analysis of the unspiked aliquot of the environmental sample. Spiked samples are used to
determine the effect of the matrix on a method's recovery efficiency.
Matrix spike duplicate — A homogeneous sample used to determine the precision of the
intralaboratory analytical process for specific analytes in a sample matrix. The duplicate sample
is prepared simultaneously as a split with the matrix spike sample, and each is spiked with
identical, known concentrations of targeted analyte(s).
Method — A body of procedures and techniques for performing an activity (e.g., sampling,
chemical analysis, quantification), systematically presented in the order in which they are to be
executed.
Method blank — A sample of a matrix similar to the batch of associated samples (when
available) in which no target analytes or interferences are present at concentrations that impact
the analytical results. It is processed and analyzed simultaneously with samples of similar matrix
and under the same conditions as the samples.
Quality — The totality of features and characteristics of a product or service that bears on its
ability to meet the stated or implied needs and expectations of the user.
Quality assurance — An integrated system of management activities involving planning,
implementation, assessment, reporting, and quality improvement to ensure that a process, item,
or service is of the type and quality needed and expected by the client.
Quality assurance project plan (QAPP) — A formal document describing in comprehensive
detail the necessary quality assurance (QA), quality control (QC), and other technical activities
that should be implemented to ensure that the results of the work performed will satisfy the
stated performance criteria.
19
-------
Quality control (QC) — A term that may be applied in several different contexts: (1) The
overall system of technical activities that measures the attributes and performance of a process,
item, or service against defined standards to verify that they meet the stated requirements
established by the customer; (2) operational techniques and activities that are used to fulfill
requirements for quality; also, (3) the system of activities and checks used to ensure that
measurement systems are maintained within prescribed limits, providing protection against "out
of control" conditions and ensuring that the results are of acceptable quality.
Quality control (QC) sample — One of any number of samples, such as a Proficiency Test
(PT) sample, intended to demonstrate that a measurement system or activity is in control.
Quality system — A structured and documented management system describing the policies,
objectives, principles, organizational authority, responsibilities, accountability, and
implementation plan of an organization for ensuring quality in its work processes, products
(items), and services. The quality system provides the framework for planning, implementing,
and assessing work performed by the organization and for carrying out required quality
assurance (QA) and quality control (QC) activities.
Raw data — The documentation generated during sampling and analysis. This documentation
includes, but is not limited to, hard copies of electronic data, magnetic tapes, untabulated sample
results, QC sample results, printouts of chromatograms, instrument outputs, and handwritten
notes.
Reagent blank — An aliquot of water or solvent free of measurable contaminants analyzed with
the analytical batch and containing all the reagents in the same volume as used in the processing
of the samples. The method blank goes through preparatory steps; the reagent blank does not.
Spike — A substance that is added to an environmental sample to increase the concentration of
target analytes by known amounts. A spike is used to assess measurement accuracy (spike
recovery). Spike duplicates are used to assess measurement precision.
Standard operating procedures (SOPs) — A document that details the method for an
operation, analysis, or action, with thoroughly prescribed techniques and steps written for and
followed by its intended user. SOPs are officially approved as the methods for performing
certain routine or repetitive tasks.
Surrogate spike or analyte — A substance with properties that mimic the analyte of interest. It
is unlikely to be found in environmental samples and is added to them for quality control
purposes (e.g., Deuterated Monitoring Compounds).
Trip blank — A clean sample of water, or other appropriate media, free of measurable
contaminants that is taken to the sampling site and transported to the laboratory for analysis
without having been exposed to sampling procedures. Trip blanks are analyzed to assess
whether contamination was introduced during sample shipment (typically analyzed for volatile
organic compounds only).
20
-------
Usability assessment — Evaluation of data based upon the results of data validation and
verification for the decisions being made. In the usability step, reviewers assess whether the
process execution and resulting data meet quality objectives based on criteria established in the
QAPP.
Validation — Confirmation by examination and provision of objective evidence that the
particular requirements for a specific intended use are fulfilled. For the purpose of this guidance,
data validation consists of an analyte and sample specific process for evaluating compliance of
the laboratory data received with methods, procedures or contract requirements.
Verification — Confirmation by examination and provision of objective evidence that the
specified requirements (analytical) have been met. This is to be a completeness check. For the
purpose of this guidance, data verification consists of a completeness check to confirm that all
data requested from the laboratory have been received and comply with specified requirements.
21
------- |