Validation of U.S. EPA Environmental Sampling Techniques
November 2017
Validation
of U.S. Environmental Protection Agency
Environmental Sampling Techniques that Support the
Detection and Recovery of Microorganisms
The U.S. Environmental Protection Agency Forum on
Environmental Measurements (FEM)
Prepared by:
The FEM Method Validation Team
FEM Document Number 2012-01
December 2012
MINOR REVISION: November 28, 2017
Prepared for:
Contributors:
Alan Lindquist, Ph.D.
National Homeland
Security Research Center
Cincinnati, OH
Key a Sen, Ph.D.
Office of Water
Cincinnati, OH
Eric Rhodes, PhD.
National Exposure
Research Laboratory
Cincinnati, OH
Ann Grimm, PhD.
National Exposure
Research Laboratory
Cincinnati, OH
Sarah Perkins, PhD.
National Homeland
Security Research Center
Cincinnati, OH
Sarah Taft, Ph.D.
National Homeland
Security Research Center
Cincinnati, OH
Eunice Varughese, M.S.
National Exposure
Research Laboratory
Cincinnati, OH
Margo Hunt, Ph.D.
Retired, U.S. EPA/
Consultant
Denver, CO
Mark Meckes, PhD.
National Risk Management
Research Laboratory
Cincinnati, OH
Frank Schaefer, PhD.
National Homeland
Security Research Center
Cincinnati, OH
Charlena Yoder Bowling
National Homeland
Security Research Center
Cincinnati, OH
Matthew Arduino,
Dr.P.H
Centers for Disease
Control and Prevention
Atlanta, GA
Sanjiv Shah, Ph.D.
Stephen Morse, PhD.
Centers for Disease
Control and Prevention
Atlanta, GA
Mano Sivaganesan, PhD.
National Risk Management
Research Laboratory
Cincinnati, OH
Michele Burgess
Office of Emergency
Management
Washington, D.C.
National Homeland
Security Research Center
Washington, D.C.
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Validation of U.S. EPA Environmental Sampling Techniques
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Disclaimer
This document provides internal guidance to U.S. Environmental Protection Agency (EPA)
personnel; EPA retains the discretion, however, to adopt, on a case-by-case basis, approaches
that differ from this guidance. The guidance set forth in this document does not create any rights,
substantive or procedural, enforceable by law for a party in litigation with EPA or the United
States.
The intent of the document is not to supersede established practices. Rather, it is to collect
information from various documents and assemble them in one place. The use of mandatory
language such as "must" and "require" in this guidance manual reflects sound scientific practice
and does not create any legal rights or requirements. The use of nonmandatory language such as
"may," "can" or "should" in this guidance does not connote a requirement but does indicate
EPA's strong preference for validation and peer review methods prior to publication for general
use.
References within this document to any specific commercial product, process or service by trade
name, trademark, manufacturer or otherwise does not necessarily imply its endorsement or
recommendation by EPA. Neither EPA nor any of its employees make any warranty, expressed
or implied, nor assume any legal liability of responsibility for any third party's use, or the results
of such use, of any information, apparatus, product or process disclosed in this manual, nor
represent that its use by such third party would not infringe on privately owned rights.
Some text in this document is taken from the companion document U.S. EPA. 2009 Method
Validation of U.S. Environmental Protection Agency Microbiological Methods of Analysis, FEM
2009-01 (U.S. EPA 2009).
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Validation of U.S. EPA Environmental Sampling Techniques
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Table of Contents
Foreward v
Acknowledgement vi
Executive Summary viii
Acronyms ix
Glossary x
1. Introduction 1
1.1 Purpose 2
1.2 Intended Audi ence 2
1.3 Scope of Guidance 2
1.4 Terminology 3
2. Planning and Initiating Validation Studies 4
3. General Guidelines for Sampling Procedure Validation 5
3.1 Sampling Technique Selection 5
3.2 Sampling Technique Optimization 8
3.3 Sampling Operational Limits 9
3.4 Critical Sampling Technique Performance Characteristics 10
3.4.1 Sampling Technique Selectivity 10
3.4.2 Sampling Technique Sensitivity 11
3.4.3 Sampling Technique Specificity 12
3.4.4 Sampling Technique Viability 12
3.4.5 Required Sampling Measurements 13
3.4.6 Mass, Area or Volume Sampled 13
3.4.7 Sampling Technique Robustness 14
3.4.8 Sampling Technique Ruggedness 14
3.4.9 Resource Requirements 14
3.5 S afety and S ecurity 14
3.6 Waste Minimization and Waste Management 15
3.7 QAandQC 15
3.7.1 Management System 15
3.7.2 Training 16
3.7.3 SOPs 16
3.7.4 Records 17
3.7.5 Equipment Maintenance and Calibration 17
3.7.6 Sampling Plan 17
3.7.6.1 Data Quality Objectives (DQOs) 18
3.7.7 QC 18
3.7.8 Sampling Documentation 19
3.7.9 Data and Reporting 19
3.7.10 QA Checks 19
3.8 Sample Integrity and Tracking 20
3.8.1 Sample Receipt, Preservation, Storage and Disposal 20
3.8.2 Chain of Custody Considerations 21
3.8.3 Shipping 22
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4. Writing the Technique 23
5. Sampling Technique Validation Reports 24
6. Multi-laboratory Validation Studies 26
7. Peer Review 27
References 28
Further Reading and Additional Guidance 29
Appendix A: Sampling Technique Validation Plan 31
Figure 1. Sampling Technique Selection Decision Tree 6
Table 1. Minimum Sampling Technique Validation Report Topics 24
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Foreword
The EPA's mission is to protect human health and the environment in which people live, learn
and work. Microbes are ubiquitous in the environment and have the potential to both provide
benefits and inflict harm on people and the environment. Because of the potential risk posed by
microbes, EPA is involved extensively in the study, monitoring and environmental measurement
of microorganisms in the environment. Sampling the air, water and soil for microbial flora is an
integral part of environmental measurement. However, before a sampling project can begin, a
sampling technique must be selected. Sampling techniques adopted by EPA require an extensive
evaluation process to be validated; i.e., to be proven reliable, successful, replicable and well
suited for the task.
The technique validation process is central to EPA's ability to monitor and measure microbial
life. The EPA Science Policy Council established the Forum on Environmental Measurements
(FEM) in April 2003. The FEM BioSampling Workgroup was formed in 2008 to address
sampling issues related to microorganisms, and create Agency-wide, internal guidance for
validation and peer review of associated methods prior to publication and general use. This
comprehensive guidance document is the result of the Workgroup's multi-year effort and should
prove useful not only to EPA personnel, but to EPA clients as well as contractors, researchers
and other agencies that are interested in EPA's process for validation, approval and acceptance
of EPA methods.
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Acknowledgements
FEM BioSampling Document Workgroup
In addition to the contributing authors listed on the cover, the following are additional members
of the Workgroup who provided further input and reviewing:
Gene Rice, EPA
Worth Calfee, EPA
Lara Phelps, EPA
Tonya Nichols, EPA
Phillip Campagna, EPA
Marissa Mullins, EPA
Nanci Hemberger, The Scientific Consulting Group, Inc.
Joanne Brodsky, The Scientific Consulting Group, Inc.
Denise Hoffman, The Scientific Consulting Group, Inc.
EPA's Science Policy Council's Peer Review Handbook (U.S. EPA 2006a) provides Agency-
wide requirements and options for developing documents. All individuals and groups who had
the opportunity to review and comment on this work prior to its submission for approval by the
FEM are listed below.
Individual Reviewers
Noreen Adcock (EPA ORD)
Kristen Keteles (EPA Region 8)
Mark Rodgers (EPA ORD)
Jennifer Best (EPA OW)
Andrew Lincoff (EPA Region 9)
Laura Rose (CDC)
Zia Bukhari (American Water)
Carrie Miller (EPA OW)
Jim Seidel (EPA OCEFT)
Jennifer Cashdollar (EPA ORD)
Robin Oshiro (EPA OW)
Mike Ware (EPA ORD)
Mark Doolittle (Contractor Rl)
Sandhya Parshionikar (EPA OW)
Elizabeth Hedrick (EPA
OW)
Stephanie Harris (EPA Region 10)
Viola Reynolds (EPA Region 4)
FEM Members and FEM Participants with Their EPA Office or Region (R)
Michael Shapiro (OW)
Tom Norris (NEIC)
Kim Kirkland (ORCR)
Lara Phelps (OSA)
Marilyn Livingood (OITA)
Pamela Barr (OW)
Deb Szaro (R2)
Marty Monell (OCSPP)
Gregory Carroll (OW)
Anand Mudambi (OSA)
Denise Rice (OCSPP)
Jan Matuszko (OW)
Bill Lamason (OAR)
Thomas Behymer (ORD)
Maria Gomez-Taylor (OW)
Robin Segall (OAR)
Denise MacMillan (ORD)
Louise Camalier (OEI)
Ron Fraass (OAR)
Jeff Heimerman (OSWER)
Dennis Wesolowski (R5)
John Griggs (OAR)
Dan Powell (OSWER)
Melanie Hoff (OSWER)
Michael Brody (OCFO)
James Michael (ORCR)
Mary Greene (OSA)
David Charters (OSWER)
Dennis Mikel (OAR)
Tim Hanley (OAR)
Elizabeth Flynt (OCSPP)
Marietta Echeverria (OPP)
Yaorong Qian (OCSPP)
Stephen Wente (OCSPP)
John McKernan (ORD)
Teresa Harten (ORD)
Tim Watkins (ORD)
Michael Johnson (OSWER)
Shen-Yi Yang (ORCR)
Susan Holdsworth (OW)
Marion Kelly (OW)
Darvene Adams (R2)
Kevin Kubik (R2)
Dale Bates (R7)
Brenda Bettencourt (R9)
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Christopher Cagurangan (R9)
Robert Hall (R9)
Charles Sellers (ORCR)
Troy Strock (R5)
Patricia Mundy (OEI)
Christian Byrne (ORD)
Eric Nottingham (NEIC)
Gerry Sotolongo (Rl)
Thuy Nguyen (OCSPP)
Eric Villegas (ORD)
Swinburne Augustine (ORD)
Charles Kovatch (OW)
Jeffery Robichaud (R7)
Laurie Trinca (OAR)
Michelle Henderson (ORD)
Judy Brisbin (OW)
Kevin Bolger (R5)
Patrick Churilla (R5)
JeffPritt (R7)
Linda Mauel (R2)
Kenna Yarbrough (NEIC)
Glynda Smith (OW)
Beth Mishalanie (NEIC)
Dale Bates (R7)
Carolyn Bernota (OECA)
Francisca Liem (OECA)
Carrie Middleton (NEIC)
Cary Secrest (OECA)
Carole Braverman (R5)
Motria Caudill (R5)
Barbara Sheedy (ORD)
EPA Offices: NEIC, National Enforcement Investigations Center; OAR, Office of Air and Radiation; OCEFT,
Office of Criminal Enforcement, Forensics and Training; OCFO, Office of Chief Financial Officer; OCSPP, Office
of Chemical Safety and Pollution Prevention; OECA, Office of Enforcement and Compliance Assurance; OEI,
Office of Environmental Information; OGC, Office of General Counsel; OITA, Office of International and Tribal
Affairs; OPP, Office of Pesticide Programs; ORCR, Office of Resource Conservation and Recovery; ORD, Office of
Research and Development; OSA, Office of the Science Advisor; OSW, Office of Solid Waste and Emergency
Response; OW, Office of Water; R, Regional Office
Other Offices: CDC, Centers for Disease Control and Prevention
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Executive Summary
The EPA Science Policy Council established the FEM, a standing committee of senior EPA
managers, in April 2003, to provide EPA and the public with a focal point for addressing
measurement and methods issues that have a multi-program impact; action teams are
commissioned by the FEM to address specific issues. In October 2008, the BioSampling
Workgroup was established to develop Agency-wide, internal guidance for validating and peer
reviewing EPA methods prior to publication for general use.
This document provides Agency-wide guidance for EPA personnel who will evaluate the
performance and suitability of new sampling techniques for microbiological parameters before
publication by EPA. The validation principles in the document are based on current, international
approaches and guidelines for intra-laboratory (single laboratory) and inter-laboratory (multiple
laboratory) validation studies. Please note that this document relates to culture-based and
molecular-based microbiological analytical methods. The Workgroup's goal was to collect
information from the referenced documents into one guidance document; the document is not
intended to supersede established practices.
EPA's recommended format for writing sampling techniques is the Environmental Monitoring
Management Council (EMMC) Method Format, which includes the following components:
scope and application, technique summary, definitions, interferences, health and safety,
equipment and supplies, reagents and standards, sample collection, preservation and storage,
quality control (QC), calibration and standardization, procedural steps, calculations and data
analysis, technique performance, pollution prevention, and waste management. In particular,
Section 17 of the EMMC addresses validation data. In addition, this guidance document
recommends including the numerical and descriptive specifications of the techniques'
operational limits and performance attributes that are determined from intra-laboratory testing
results during primary validation.
Peer review is required for all EPA sampling techniques for microbiological parameters prior to
publication. The EPA Science Policy Council's 2006 Peer Review Handbook (U.S. EPA 2006a)
provides Agency-wide requirements and options for that process.
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Acronyms
AOAC
AOAC International (formerly Association of Analytical Chemists)
ASTM
ASTM International (formerly American Society for Testing and Materials)
ATCC™
(formerly American Type Culture Collection)
CAS
Chemical Abstract Service
CDC
Centers for Disease Control and Prevention
CFR
Code of Federal Regulations
DNA
deoxyribonucleic acid
DOT
U.S. Department of Transportation
DQI
data quality indicator
DQO
data quality objective
EMMC
Environmental Monitoring Management Council
EPA
U.S. Environmental Protection Agency
FEM
Forum on Environmental Measurements
FN
number of false negatives
FP
number of false positives
GPS
global positioning system
HMR
hazardous materials regulations
I AT A
International Air Transportation Association
ISO
International Organization for Standardization
LOD
limit of detection
LOQ
limit of quantitation
MDL
method detection limit
NIST
National Institute of Standards and Technology
OSHA
Occupational Safety and Health Administration
QA
quality assurance
QC
quality control
SHEM
Safety, Health, and Environmental Management
SPC
specimen processing control
SOP
standard operating procedure
SOW
statement of work
TN
number of true negatives
TP
number of true positives
UN/ICAO
United Nations International Civil Aviation Organization
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Glossary
accuracy: The degree of agreement between an observed value and an accepted reference value.
Accuracy includes a combination of random error (precision) and systematic error (bias)
components, which are due to sampling and analytical operations; a data quality indicator
blank: A specimen that is intended to contain none of the analytes of interest and is subjected to
the usual analytical or measurement process to establish a zero baseline or background value
bias: The constant or systematic distortion of a measurement process, different from random
error, which manifests itself as a persistent positive or negative deviation from the known or true
value. This can result from improper data collection, poorly calibrated analytical or sampling
equipment, or limitations or errors in analytical methods and techniques
calibration: Set of operations that establish, under specified conditions, the relationship between
values of quantities indicated by a measuring instrument or measuring system, or values
represented by material measure or a reference material, and the corresponding values realized
by standards
compatibility: The capability for one data set to be reconciled or integrated with another; often
expressed as a statistical measure
data quality objectives (DQOs): Qualitative and quantitative statements derived from the DQO
Planning Process that clarify the purpose of the study, define the most appropriate type of
information to collect, determine the most appropriate conditions from which to collect that
information, and specify tolerable levels of potential decision errors
holding time: (1) The maximum times that samples may be held, after the sample is taken, prior
to analysis and still be considered valid or not compromised; (2) The maximum times that
samples may be held, after the sample is taken, prior to preparation and/or analysis and still be
considered valid or not compromised
Latin square: Ann x n array filled with n2 different Latin letters or numbers, each occurring
exactly once in each row and exactly once in each column. Such an arrangement can be used as
the basis of experimental procedures in which it is desired to control or allow for two sources of
variability while investigating a third
limit of detection (LOD) and limit of quantitation (LOQ): The LOD and LOQ concentrations
are calculated by applying the compound's calibration curve to the noise response of a sample to
obtain a value which is then multiplied by a factor of 3 for LOD (3 times of noise) and 10 for
LOQ (10 times of noise). The responses of the analytes are not considered in this approach. Only
the noise level is included in the calculation. In some cases, the concentration of the lowest
calibration standard is treated as the LOQ. The LOD is not defined in this case, although the
LOD is often assumed to be 1/3 of the LOQ. The lowest possible LOD and LOQ values are not
critical in these cases. The rationale of this approach is that the expected analyte concentrations
in the samples are high and above the lowest calibration concentration and knowledge of the
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actual LOD/LOA is not necessary
method detection limit (MDL): The minimum concentration of a substance that can be
measured and reported with 99% confidence that the analyte concentration is greater than zero
and is determined from analysis of a sample in a given matrix containing the analyte. The MDL
is determined using the procedure provided in 40 CFR 136
method: (1) A body of procedures and techniques for performing an activity (e.g., sampling,
analysis, quantification) systematically presented in the order in which they are to be executed.
(2) Logical sequence of operations, described generically, used in the performance of
measurements
precision: The consistency of measurement values quantified by measures of dispersion, such as
the sample standard deviation. Precision must be defined in context—e.g., for a certain analyte,
matrix, method, perhaps concentration, laboratory or group of laboratories
procedure: A specified way to carry out an activity or process
quality assurance (QA): An integrated system of management activities involving planning,
implementation, documentation, 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 control (QC): (1) The overall system of technical activities whose purpose is to measure
and control the quality of a product or service so that it meets the needs of users; (2) 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; operational techniques and activities that are used to fulfill requirements for
quality
robustness: The ability to match a particular sample collection technique with multiple
analytical assay techniques
ruggedness: The degree of reproducibility obtained by the analysis of the same samples under a
variety of test conditions, such as pH, temperature, humidity, etc.
sample size: The number of items or the quantity (volume, mass or area) of material constituting
a sample
sample stability: The capability of a sample material to retain the initial property of a measured
constituent for a period of time within specified limits when the sample is stored under defined
conditions
selectivity: The extent to which a method can determine particular analytes in mixtures or
matrices without interferences from other components
sensitivity: (1) The capability of a method or instrument to discriminate between small
differences in analyte concentration; (2) A qualitative description of an instrument's or analytical
method's detection limit
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specificity: The measure of the proportion of negatives that are correctly identified
standard operating procedure: (1) A written document outlining an analytical method that
provides a level of detail intended to allow advanced analysts or analysts familiar with the
method outlined in the SOP to perform that analytical method; (2) A written document that
details the method of an operation, analysis or action whose techniques and procedures are
thoroughly prescribed and which is accepted as the method for performing certain routine or
repetitive tasks.
standardization: The process of adjusting instrument output to a previously established
calibration; the experimental establishment of the concentration of a reagent solution; correlation
of an instrument response to a standard of known accuracy
systematic error: Consistent biases in measurement which cause the mean "observed" value of
many separate measurements to differ significantly from the "actual" value of the measured
quantity or attribute; equal to total error minus random error
technique: The systematic procedure by which a complex or scientific task is accomplished
uncertainty: (1) The range of values that contains the true value of what is being evaluated at
some level of confidence; (2) A measure of the total variability associated with sampling and
measuring that includes the two error components: systematic error (bias) and random error.
validation: (1) Confirmation by examination and provision of objective evidence that the
particular requirements for a specific intended use are fulfilled; (2) In design and development,
the process of examining a product or result to determine its conformance to user needs
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1. Introduction
EPA program offices publish a wide variety of measurement methods and techniques for use by
EPA personnel, other government agencies and the private sector. These methods and techniques
originate from many sources, such as EPA laboratories and contractors, scientific organizations,
other government laboratories and the private sector. Because these methods could be published
as regulations, incorporated as references in regulations or published as guidance, they must be
tested thoroughly and peer reviewed prior to publication as EPA methods.
The FEM is a standing committee of senior EPA managers who provide EPA and the public with
a focal point for addressing measurement and methods issues that have a multi-program impact.
The FEM commissions action teams to address specific issues to provide Agency-wide, internal
guidance for validating and peer reviewing EPA methods and techniques prior to their
publication for general use. The BioSampling Workgroup, a FEM action team, developed this
document to assist EPA staff charged with developing or reviewing microbiological sample
collection techniques.
Understanding the fate of microorganisms in the environment and their impact on the
environment and human health are important aspects of EPA's mission. The Agency extensively
studies and monitors microorganisms in a variety of environmental matrices, and sampling is an
integral part of environmental measurements of microbiological contaminants. Effective
sampling approaches must address the overwhelming complexities in environmental
microbiology, including the different forms of microorganisms, types of samples and sampling
devices, and interfering substances and organisms. Sampling technique validation is the process
of demonstrating that a sampling technique is suitable for its intended use; multiple studies are
required to evaluate a technique's performance under defined conditions. Properly designed and
successful sampling-technique validation studies ensure the reliability of a sampling technique.
EPA depends on proven and reliable microbial sampling methods to understand the impact of
microbes on the environment and human health.
Analytical methods, used in conjunction with sampling techniques, depend on effective sampling
and recovery of target microorganisms. Sampling is merely a portion of a method, as a typical
method includes sample collection and processing, extraction or isolation procedures, analyte
detection, data analysis and other essential information. Any determination of uncertainty or bias
in an environmental measurement must include both the analytical procedures and the sampling
technique. To fulfill accurate measurement objectives, each step of the process should be
analyzed and validated. (Note that this document relates to culture-based and molecular-based
microbiological analytical methods.)
All sampling techniques must be peer reviewed before publication. The authors refer readers to
the current version of the EPA Science Policy Council's Peer Review Handbook
(U.S. EPA 2006a), an excellent source of information for both internal and external peer review
processes.
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1.1 Purpose
This guidance document describes the process for validating environmental sampling techniques
that support the detection and recovery of microorganisms. It describes the scientific principles
that should be addressed during sampling technique validation studies for microbiological
parameters and provides guidelines concerning the minimum levels of required validation and
peer review before EPA recommends specific methods or techniques. This document provides
general guidance for the validation of microbiological sampling techniques likely to be used in
EPA methods.
This document also provides information on selecting an appropriate sampling technique for
specific applications (e.g., clearance, characterization), as well as general background material
on the wide range of approaches to microorganism sampling in environmental media. Testing
should be conducted to ensure that sampling techniques written for a specific organism are
effective for additional organisms prior to use, even when the microbes are closely related.
Similarly, validation is needed to ensure that techniques tested for collecting samples for one
type of assay will perform with equal proficiency with the proposed assays.
The EPA is involved in collecting microorganism samples from numerous matrices, such as
water, biofilms, biosolids, soil, sediment, air, and other matrices. The sampling literature
includes several EPA methods for microorganism detection (http://www.epa.gov/microbes).
1.2 Intended Audience
This guidance was written for EPA personnel who are responsible for sampling techniques for
microbiological parameters that will be: (a) published as serially numbered EPA methods,
(b) published as regulations or (c) incorporated by reference in regulations. In some cases, the
validated methods may be needed for research by EPA and other organizations. This document
also may be used by clients, contractors or other interested parties who, upon reviewing an EPA
method or technique for potential use, are interested in EPA's process for method validation,
approval and acceptance.
1.3 Scope of Guidance
In exploring requirements to validate a specific technique, the FEM BioSampling Workgroup
concluded that specific guidance on how to conduct validation studies for every sampling
technique was beyond the scope of this document; therefore, detailed validation protocols for
specific techniques are not covered. Instead, guidelines for developing validation protocols are
presented. This document also references validation protocols developed by EPA and other
standards setting organizations, such as the International Organization for Standardization (ISO),
ASTM International (formerly American Society for Testing and Materials) and AO AC
International (formerly Association of Analytical Chemists). The intent of the document is not to
supersede established practices but rather to collect information from the documents mentioned
above and incorporate that information into one document.
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Each step of a method, from the sampling technique through processing and assays, influences
its selectivity, sensitivity and specificity. Performance measures of sampling techniques cannot
be measured in the absence of appropriate analytical assays or set of assays. The performance
measures cannot be interpreted in the absence of the specific combination of matrix analyte,
sampling technique, analytical assay and other processing or analytical procedures used to
develop the measure. This guidance was developed for EPA microbiological sampling
techniques not validated prior to publishing as EPA methods or adapted as Agency-accepted
regulatory standards, or for existing techniques not yet validated with a desired assay. The
document avoids the term "method" with regard to sampling because stand-alone sampling
methods for microorganisms are not typical. In addition, sampling techniques are not
independent of the assay used; assay results depend on how the sample is delivered to the assay.
If either the sampling technique or the assay is changed, the results also are likely to change. A
separate guidance document was prepared to address validation issues concerning extraction
procedures and the analytical detection of microbes (see U.S. EPA. 2009. Method Validation of
U.S. Environmental Protection Agency Microbiological Methods of Analysis, FEM 2009-01).
Within the context of this document, microbiology includes viruses, bacteria, fungi, yeasts,
toxins, algae, protozoa, metazoan parasites and DNA or other materials associated with these
microorganisms collected in environmental matrices such as air, water bio-solids and soil. In
addition, this information is designed to apply to all sampling techniques associated with
antimicrobial agent testing. The Agency may need additional documents to address sampling
needs for other macroscopic living organisms such as fish, shellfish, annelid worms, insects or
birds. Although the document may be broad enough to encompass validation of sampling
methods used in other areas of biology, it is not designed for that purpose.
The precise procedures of a sampling technique must be addressed when developing or
validating sampling tools and techniques. All physical sampling techniques or collection tools
that are used must be indicated, as well as whether the procedure is a field measurement process
such as screening or a direct reading. This document does not address site characterization
issues, nor the number of samples required for a representative study.
1.4 Terminology
Scientific terms and meanings change with time. For many years, national and international
standards organizations have sought to harmonize terminology within scientific disciplines. For
the purpose of this guidance, a glossary of terms and definitions is included on page x. Where
possible, definitions were obtained from the FEM Environmental Measurement, ISO, and
National Institute of Standards and Technology (NIST) glossaries.
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2. Planning and Initiating Validation Studies
Proper planning is critical for successful validation studies. A sampling validation plan should
encompass all aspects of validation activities and follow a standardized format similar to that
shown in Appendix A. Sampling techniques are closely associated with the development of
analytical techniques, and care must be taken to ensure that new collection techniques are
consistent with the planned analytical techniques.
Sampling technique validation depends heavily on the environment in which the sample is
collected. Temperature variations, variations in media type and the technique used to collect
samples (e.g., pressure placed on a surface wipe) can cause sample collection variability. Care
must be taken to document these variables and either limit the variables tested or ensure that a
range of conditions are included in the test. In addition, the sample collection process should be
well documented. For example, soil samples, typically collected via mechanical means, can be
either grab or composite samples. Sampling techniques that are simple deviations from existing
processes (e.g., new size of a split spoon sampler) require less rigorous validation than a novel
sampling technology with little technical basis (e.g., extraction of microorganisms from drinking
water samples using traveling wave electrostatic charge separation). The key to effective
validation activity is control and documentation of technique variability. Through control and
documentation, the developer validation body, or end user, may determine if the range of
conditions is appropriate for a particular sampling technique or if conditions indicate that use of
another technique may be more appropriate. Further, these factors allow a user to determine if
the technique is performing as designed. Finally, well-controlled and documented procedures
permit the data generated from the application of the procedure to be used in decision-making.
Normally, samples collected from multiple locations and under differing conditions should be
tested in conjunction with matrix spikes and proficiency evaluation testing so a variety of
performance characteristics such as interferences, reproducibility, robustness and ruggedness can
be determined. This practice of performance verification provides a range of operating criteria
and a better understanding of the consistency of the sampling technique. However, this practice
should be balanced against the costs of sampling technique validation studies. Unfortunately,
sampling technique difficulties may be revealed only after performing multiple tests, and it may
be necessary to troubleshoot and optimize a technique after conducting additional validation
studies that address those difficulties. If procedural changes are required, the changes may affect
the technique performance characteristics, and repeating some or all aspects of the study may be
necessary. Although site characterization is beyond the scope of this document, the process for
selecting a location representative of the analyte(s) distribution in the local environment should
be documented.
Safety is a prime consideration in any sampling event and should be addressed in both the
sampling technique and the validation plan, including personal protective equipment and first
aid. Additional safety concerns include physical and biological hazards such as harmful
microorganisms.
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3. General Guidelines for Sampling Procedure Validation
This section addresses elements to consider when developing a validation protocol. Including
these components in a sampling technique validation plan should add value to the data generated.
Omitting multiple items of this information may limit the applicability of a sampling technique
or protocol.
This section is not intended to provide specific guidance for developing protocols for particular
sampling techniques, as the possible range of variables to be considered is too great to cover in a
general document. Information such as the definitions of verification and validation levels;
development and contents of quality assurance (QA) project plans; and health and safety plans
for the testing plan, data treatment and manipulation, and development of acceptance criteria for
particular techniques are generally available elsewhere. (A selection of citations is provided in
the "Further Reading and Additional Guidance" section of this document.) Depending on the
proposed use of the data generated, this information may be specified by regulation or policy.
The specific activities of a validation process depend on the type of sampling technique or
protocol being developed and tested, and on the potential application of the data. If a sampling
technique is tested to improve an aspect of an existing method used for regulatory compliance, a
different criterion would be expected than for a method being developed for research. These
differences may be in the number and type of conditions tested, the level of QA, the treatment of
the data and in the acceptance criteria, or in other areas of validation.
3.1 Sampling Technique Selection
Sampling technique options often are mandated by regulatory constraints. Several sampling
techniques may be available if the regulatory framework is flexible or if the sample collection is
not in direct response to a regulatory mandate.
Choosing an appropriate sampling technique should be based on an evaluation of various
sampling techniques according to the project goals and requirements; therefore, the first step is to
list and understand the mission requirements. The decision tree in Figure 1 will assist users with
choosing the appropriate sampling technique to validate for a given purpose.
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Determine study question(s), regulatory and/or data quality objectives
(DQOs, type and quality of data), organism(s), and matrix(s)
Survey available methods (including assay and
sampling techniques) and monitor scientific
communication outlets
Analyze available data concerning sampling
(both methods and sampling techniques)
Is the method or detection
assay associated with a sampling technique appropriate
for the organism and matrix?
NO
Is only one sampling
technique compatible with the detection assay,
organism, or matrix available?
YES ~
*- YES ~
Determine requirements with respect to sampling (e.g., cost, time, recovery,
volume, and number of samples) arising from study question, regulatory and/or
DQO requirements, and/or selected detection assay
Generate a list of potential sampling techniques
Collect performance data on the sampling techniques
with respect to the identified criteria
Has the best or
acceptable sampling technique been identified with
respect to the established criteria?
NO
Revisit decision criteria, list of sampling techniques,
and performance data, or conduct research on sampling techniques
YES ~
Are study,
regulatory, and/or DQO
requirements being met?
NO
YES
Figure 1. Sampling Technique Selection Decision Tree
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Additional questions that may help clarify sampling technique requirements include:
What size is the sample, or how much material should be collected?
What characteristics of the underlying population to be sampled (e.g., initial and final
volume, temperature, collection location, other characteristics) are required to provide
adequate information to address the underlying question(s)? What question(s) is the
sampling and analysis effort attempting to address?
Is there a mandatory maximum sample holding time between sample collection and
sample analysis?
If no single sampling technique is mandated, is there a subset of sampling techniques
from which a technique should be selected so that the data are acceptable?
Are there requirements that will allow data from a particular sampling technique to be
considered in future decisionmaking? If there are multiple requirements, how are they
prioritized? What are the requirements for collecting a representative sample, and will
multiple samples be required? Is there a requirement to sample the same location
multiple times, or must samples be collected from diverse locations? Will multiple
samples be used to make a composite sample or is each sample to be analyzed
individually?
What are the logistical constraints, such as cost restrictions, on the sampling effort? Are
the logistical requirements for potential sample collection techniques within these
constraints?
Additional characteristics to consider when selecting sampling equipment and techniques
include:
Material compatibility (gloves, sampling implements, sampling containers, etc.);
Chemical compatibility;
Sample volume capabilities;
Physical requirements;
Ease of operation;
Convenience;
Decontamination effort needed for sampling equipment;
Field processing requirements;
Existence of techniques optimized for this sample type, assay and purpose.
It might be useful to evaluate possible required performance characteristics for the sampling
technique. These characteristics may include:
Selectivity;
Microbial viability;
Sample storage and preservation;
Area or volume sampled;
Detection and quantitation limits;
Robustness;
Ruggedness;
Resource requirements;
Safety;
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Waste minimization;
Operational limits;
QA/quality control (QC); and
Chain of custody.
3.2 Sampling Technique Optimization
Techniques are developed to perform under a defined set of conditions and may be adjusted to
provide higher quality data. Optimization is the process of altering a technique, measuring the
effect on the data and retaining changes that improve technique outcomes. Optimization implies
an improved data parameter as measured by some predefined criterion, and optimization of a
technique for one parameter frequently results in changes to other parameters. Secondary
changes may be beneficial or detrimental to the overall criteria by which the technique is judged.
Optimization of a sampling technique is possible when the analytical method is constant.
Some parameters are difficult to quantify and optimize, and parameters that are easier to measure
often are optimized first. Technique developers should consider the prioritization of these
parameters, and optimization should be weighted toward parameters that represent significant
programmatic concerns rather than those that are easiest to measure.
Most techniques require optimization of several parameters; the simplest optimization technique
for multiple parameters is to optimize each significant parameter serially. After a parameter is
optimized, previously optimized parameters must be tested to ensure that they remain optimal,
and necessary adjustments made. Multi-parameter optimization is a cost-effective technique
when optimizing several parameters. This technique combines multiple parameters to form a
Latin square-type design and arrives at a simultaneous optimization without testing each square.
There are numerous algorithms for minimizing testing with this strategy, but selection of an
appropriate algorithm is beyond the scope of this document as it is situationally dependent.
A general technique description could be developed to provide suboptimal data for a wide range
of conditions but should address optimization levels. Alternately, a description could be written
for a narrow application and be optimized for specific parameters within a narrow range of
conditions. The technique description should detail the conditions and parameters considered in
optimization—how to ensure that the conditions exist in a given sample, how to address samples
that are not within the conditions described and how to treat data collected outside the optimal
range.
There are potential discontinuities in optimization parameters. A parameter may have a relatively
continuous distribution throughout a range of conditions, but may change radically in other
conditions; the technique description should note these discontinuities. Often, these conditions
are revealed only after a technique is applied over a period of time. In these cases, the technique
must be modified, amended or otherwise annotated so users are aware of the changes.
The interplay of programmatic objectives and optimization parameters cannot be understated.
For instance, optimization for a low cost per sample may result in a decrease in percent recovery
and an increase in variability. To compensate for these deficits, the number of samples would
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have to increase, eliminating the overall cost savings. To select the applicable optimization state,
therefore, factors other than cost/sample must be considered. Although cost/sample is higher,
single-sample techniques might prove useful when obtaining multiple samples is impractical,
costly or impossible because of restricted site access. Alternatively, the option with a lower
cost/sample may suffice when the area or medium being sampled requires flexibility,
adaptability or multiple sampling sites. If cost or statistical performance of different optimization
states is equivalent, other operational concerns must be considered.
To optimize a technique effectively, it is necessary to define and reconcile parameters, their
performance criteria and the conditions under which they may be tested based on their
programmatic components. This should provide an acceptable range of response variables prior
to technique optimization. Because multiple parameter optimization will require decisions that
value one parameter over another, acceptable trade-off conditions should be considered in
advance.
The optimization parameters, data ranges, test conditions and trade-offs should be developed in
consultation with, and accepted by, the user community, and decisions should be documented.
The user community should understand that it is not possible to guarantee that all recognized
performance measures and ranges will be met. The user community also should be provided with
information that occurs during the optimization process, as it is EPA policy to consult with
stakeholders. Developers should not promise delivery on performance criteria during the
parameter-formulation period, as this might influence parameter selection and bias outcomes.
3.3 Sampling Operational Limits
The operational limits of a sampling technique represent constraints on the use or operation of
the technique. Sampling technique descriptions should list these limits because they may affect
decisionmaking regarding technique selection for a particular application. For example, a wetted-
wall cyclonic sampler that uses water to entrain particulates from a stream of air may
malfunction at temperatures below freezing. Another example is the operational limits of cascade
impactor samplers that collect airborne microorganisms from an air stream onto a semisolid agar
medium. Semisolid media are subject to dehydration, depending on atmospheric conditions,
which may limit the duration of sampling time. The duration also may be related to the sample
flow rate.
Other sampling technique constraints may be related to meteorological conditions, altitude and
distance from the sample or other known factors. Holding time and temperature can affect
microbiological samples, potentially causing either an artificial increase or decrease in the
number and viability of target organisms. Increased logistical support can overcome or moderate
some operational limits, however. A temperature-controlled enclosure, for example, can
overcome the operational limits of a temperature-sensitive sampling device.
Operational limits often are not tested by or obvious to developers, who frequently develop
techniques in laboratory settings. Field conditions such as meteorological conditions, low light
levels, the absence of horizontal surfaces or the requirement to wear protective gear may limit
the performance of a technique, and laboratory tests might not reveal these limits. Technique
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documentation should include known operational limits. In addition, testing conditions should be
described so that potential users can assess whether test conditions accurately replicate potential
difficulties.
3.4 Critical Sampling Technique Performance Characteristics
Each step of a method, from sampling technique through processing and assays, influences its
selectivity, sensitivity and specificity. Performance measures of sampling techniques cannot be
measured in the absence of an appropriate analytical assay or set of assays. The performance
measures cannot be interpreted in the absence of specific combinations of matrix analyte,
sampling technique, analytical assay and other processing or analytical procedures used to
develop the measure. However, method steps can be investigated and verified separately, as was
done for Methods 1622 and 1615.
The sampling technique development team also must incorporate all technique performance
components. These factors may include personnel, laboratory facilities, reagents, supplies,
equipment, calibrations, reporting standards, record keeping, data analysis, safety and quality.
These decisions should be based on the impact that these factors will have on the technique used,
the data quality and whether or not the data are acceptable for use.
3.4.1 Sampling Technique Selectivity
Sampling technique selectivity determines whether the procedure can be used to collect the
target biological material appropriately, with or without its non-target
surroundings/interferences—the more selective the technique, the narrower the range of targets.
For example, the non-selective grab sample technique would have substantial drawbacks for a
narrow range of targets. This may result in a false negative if the sampling technique is not
specific enough to the assay. The selected sampling technique should be evaluated carefully
based on project goals, matrix, location of microbes, heterogeneity, sampling device, the target
itself, exposure to sunlight and introduction of dissolved oxygen.
An internal control functions like the target in its ability to be collected, concentrated and
detected. A sample process control, or internal control, may be required or needed when the
target organism is low in prevalence and highly pathogenic (i.e., low infectious dose), or if the
surrogate is an indicator for the sanitary condition of the water rather than a specific pathogen or
set of pathogens. Care should be given when selecting surrogates to ensure that the properties of
the control(s) are similar to those of the target organisms especially with regard to sampling (i.e.,
is the interaction of the surrogate with the matrix and sampling device the same as that of the
target?). Although a control organism or compound may occur naturally in the environment,
often it is added ("over-spiked") into a sample in precise numbers as a specimen-processing
control (SPC) or to understand the effects of treatment, antibiotics, etc. Thus, nonpathogenic
surrogate organisms, such as other strains of Bacillus spp., have been shown to be acceptable for
use in place of B. anthracis; Hafnia alvei is used in place of E. coli 0157:H7 and Salmonella
spp. in other matrices. The ability to capture the surrogate in a manner similar to the target
should be considered when selecting a sampling technique. Conversely, a surrogate can be
selected if it is adequate for the sampling technique chosen for the target. Standards such as
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EasySeed™ for protozoa and ColorSeed™ (both BTF Pty Ltd) for Giardia spp. and
Cryptosporidium spp.; BioBall™(BTF Pty Ltd, BIOMERIEUX Inc., Pittsburgh, PA) for
bacteria; and Armored RNA® (Ambion, Inc., Applied Biosystems, Foster City, CA) for viruses,
can be spiked directly into water to determine the efficacy of the test technique to monitor
respective organisms.
3.4.2 Sampling Technique Sensitivity
Sensitivity measures the proportion of actual positives that are identified correctly. For example,
sensitivity would be the proportion of target organisms that can be detected and is expressed
mathematically as:
Sensitivity = TP / (TP + FN) * 100%
Where:
TP = Number of true positives
FN = Number of false negatives
Data to calculate sensitivity typically are generated by repeated testing of serial dilutions of a
known spike standard.
Limit of Detection (LOD)
The LOD is the minimum amount of analyte that can be detected reliably and distinguished from
a known and characterized background with a given level of confidence; LODs establish a
baseline detection value for optimal conditions. If no organisms are detected in a sample, results
should be reported as less than the LOD per sample area or volume. The method detection limit
(MDL) is defined as the minimum amount of an analyte that can be measured and for which it
can be reported with 99 percent confidence that the analyte concentration in an interference-free
matrix is greater than zero. The MDL is determined by analyzing a matrix sample containing the
analyte. (Refer to U.S. EPA Method Validation of U.S. Environmental Protection Agency
Microbiological Methods of Analysis, FEM 2009-01 for more information on the MDL).
Limit of Quantitation (LOQ)
The LOQ is the lowest amount of analyte that can be measured with acceptable precision and
accuracy as required by data quality objectives. What is considered "acceptable" is determined
by the method, if it requires it, or by the user. Both the LOQ and the range of quantitation are
established from a standard curve of reference sample measurements. The standard curve defines
the relationship between the detector or instrument response and the analyte amount. Methods
designed to obtain a quantitative analysis may have several required operational limits and
performance attributes, one of which is a standard curve.
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3.4.3 Sampling Technique Specificity
Specificity measures the proportion of negatives that are correctly identified. Specificity is
expressed mathematically as:
Specificity = TN / (TN + FP) * 100%
Where:
TN = Number of true negatives
FP = Number of false positives
Microbiology methods and media specificity traditionally are demonstrated using pure positive
and negative control cultures. For example, appropriate ATCC™ strains for several groups of
enteric control culture bacteria are provided in Section 5.1.6.4 of EPA's Manual for the
Certification of Laboratories Analyzing Drinking Water, 5th Edition (U.S. EPA, 2005). Positive
cultures listed for Enterococci include Enterococcus faecalis ATCC 11700 and Enterococcus
faecium ATCC 6057. Appropriate negative controls include Staphylococcus aureus ATCC 6538,
Escherichia coli ATCC 8739 or 25922, and Serratia marcescens ATCC 14756. Appropriate
target and nontarget control culture definitions, or other standards for both validation and routine
QC use, are expected when developing new microbial methods. In an effective method, a single
target organism should be discernible in complex matrices that may contain millions of nontarget
organisms.
3.4.4 Sampling Technique Viability
The most important aspect of effective sampling is maintaining the integrity of target
microorganism(s) until samples are analyzed. Although simply detecting organisms in an
environmental matrix can be informative, risk assessment may require information on viability.
Thus, if a study's purpose is to determine human health risk, including a viability assay within a
detection method could be essential. Certain bacteria strains can enter a viable but nonculturable
state, for example, thereby preventing detection of potentially viable organisms. In such cases,
holding or incubating samples under specific conditions may be necessary to allow cells to
resuscitate.
For methods that include a viability assay, the way in which samples are collected and processed
is important. If viability measurements are included or if viable organisms are to be detected,
then collection and storage techniques may or may not differ from those that are used to detect
nonviable organisms, or DNA or toxins from the organism. For most organisms to be detected in
a viable condition, sampling and further downstream processing should be conducted at lower
temperatures (4°C) within hours to days. Additionally, other conditions such as incubation,
growth media or anaerobic conditions may be required, depending on the microorganism and its
condition. Sampling technique standard operating procedures (SOPs) should specify each of
these conditions so that technique selection is based on project goals.
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3.4.5 Required Sampling Measurements
Documentation during sampling may be required or suggested for some data parameters or
sample-matrix parameters. These may be specified in the sampling plan or may be integral to the
sample collection process and should be included in the sampling process description. For some
data parameters (e.g., alkalinity, turbidity and hardness), data may be collected in the field, or a
portion of the collected sample may be sent to an analytical laboratory. If a split or replicate of a
sample is to be sent to a laboratory for analysis, the potential impact that sample collection and
transportation might have on the parameter of interest must be considered. For example, air
incorporated into a water sample during collection may change the pH of the sample from an
anoxic environment. Some parameters are required by the method (e.g., to ensure viability of the
targeted microorganisms); others are collected for research purposes (e.g., comparing the
presence of a microorganism to pH or turbidity).
Examples of sampling site and matrix parameters include but are not limited to:
Date of sample collection;
Location (possible global positioning system [GPS] coordinates);
Time of day;
Current and past weather conditions;
Percent of canopy cover at sample location area;
Description of vegetation;
Depth of water at which sample was collected;
Presence of animals or other materials (e.g., feces) at collection site;
Dissolved oxygen levels;
Turbidity;
Temperature;
Salinity;
Volume;
. pH;
Hardness;
• Alkalinity;
Depth;
Biological oxygen demand;
Total organic carbon;
• Ammonia-nitrogen levels;
Oxidation-reduction potential;
Percent solid or amount of suspended solids;
Indicator microorganisms (fecal coliforms, E. coli, enterococci, bacteriophages)
and/or total heterotrophic bacteria; and
Disinfectant residuals.
3.4.6 Mass, Area or Volume Sampled
Sample collection areas must be specified within the collection parameters to determine the final
quantity (e.g., spores/cm2). If samples are not collected from a surface area, the volume or mass
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must be recorded to establish the basis of the found quantity (e.g., spores/m3 air or viable
cells/mL liquid). Without a known mass, area or volume, concentration of the analyte cannot be
calculated. In addition, the sampling amounts must conform to the sampling plan. Volume or
area sampled also should consider spatial heterogeneity in the matrix.
3.4.7 Sampling Technique Robustness
Robustness is the ability to match the performance of a sample collection technique with
multiple microorganisms and analytical assay techniques; each collection and assay combination
must be verified.
3.4.8 Sampling Technique Ruggedness
Ruggedness is the degree of reproducibility that is obtained by analyzing the same samples under
a variety of test conditions; conditions may include different laboratories, sample collectors,
temperatures, pH and relative humidity.
3.4.9 Resource Requirements
Personnel are a primary resource that should be addressed in all techniques. Technique
descriptions should include the number of people required to complete the technique, training
and skill requirements, and the initial evaluation and continuing assurance of personnel
performance. Methods to monitor personnel and corrective actions to take if personnel fail to
meet specified requirements also must be included.
Personnel descriptions help ensure that sample collectors are trained and experienced (whether in
the laboratory or in the field), so that costly operator errors are prevented and public health risks
are minimized. Inadequate or unnecessary requirements for training, performance evaluation and
experience may limit a technique's usefulness and the availability of useful data. Other resources
include time, funding, supplies, equipment, transportation, laboratory space, etc.
3.5 Safety and Security
Live organisms such as pathogenic microorganisms create potentially high biohazard and
infection risks. It is the user's responsibility to establish appropriate safety and health practices
prior to adopting a sampling technique. In particular, users must develop a safety plan and
observe all safety procedures within the plan. Sampling technique safety considerations should
include but are not limited to:
Toxicity, carcinogenicity or other potential health hazards of reagents and organisms;
Controlling and limiting exposure to health hazards through protective measures
(e.g., gloves and glove boxes, particle masks, protective eyewear);
Occupational Safety and Health Administration (OSHA) regulations for safe handling
of chemicals and organisms;
Material Safety Data Sheets on file and readily available;
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Biosafety in Microbiological and Biomedical Laboratories (BMBL) for biosafety;
All hazards associated with collecting a sample, including physical and
environmental dangers (e.g., inclement weather, slip hazards, unsafe atmospheric
conditions, shock hazards);
All hazards associated with packing and shipping samples and wastes, including
ensuring that shipping containers are free from contamination;
Medical clearances and appropriate vaccinations;
Disinfection and clearance procedures required for specific microbes;
Emergency procedures, incident reporting and recordkeeping;
Department of Transportation (DOT), Centers for Disease Control and Prevention
(CDC), International Air Transport Association (IATA), state and other hazardous
material shipping regulations;
Locations and contact information for local hospitals, and emergency contacts for
personnel;
Locations and availability of emergency showers, eyewash stations and other first aid;
and
Chain of custody requirements (see Section 3.8.2 of this document).
In addition, the corresponding health and safety plan must be approved by the local Safety,
Health and Environmental Management (SHEM) office or the chemical hygiene officer before
starting a project. A security plan also should be developed that includes the site, staff, storage
and transport of potentially hazardous materials.
3.6 Waste Minimization and Waste Management
Waste management considerations, including treatment and ultimate disposal of both the sample
and the sampling materials, should be factored into the sampling technique. State or local
regulatory agencies should be contacted early to determine state or local requirements and
available treatment and disposal options. Please refer to Section 3.8.3 of this document for
information about shipping hazardous wastes.
3.7 QA and QC
QA and QC programs should provide scientifically sound and legally defensible documented
data. As risk assessment often drives biological sampling, sampling and analytical procedures
should correspond to the precision necessary to understand the nature and extent of
contamination and enable proper assessment of potential human health or ecological risks. This
section provides general descriptions of quality practices and goals for sampling procedures for
various biological environmental matrices. The guidelines provide basic QA and QC
considerations. It is the project managers'/coordinators' responsibility to incorporate additional
requirements to ensure adequate and proper data quality.
3.7.1 Management System
Before sampling or analytical work begins, a management system should be in place that
accurately reflects the operating and QA/QC programs in the laboratory. The management
system should be documented in the laboratory's quality manual and other referenced quality
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documents. The QA manual should address but is not limited to the following elements:
Quality manual maintenance and update procedures;
QA objectives and policies;
QA project plan specific to the project (see http://www.epa.gov/quality/qapps.html
for more information on QA project plans);
Personnel qualifications and training;
Control of records and documents;
Data management;
Analytical methods;
Equipment calibration and maintenance procedures;
Reagents and standards;
Sampling materials and procedures;
Handling and transportation of samples;
Sample retention and disposal;
Internal QC procedures, including who is responsible for QC but not involved in
routine work;
Data validation and reporting;
QA reports.
The quality manual should be updated as needed, and reviewed and approved by appropriate
personnel at least annually.
3.7.2 Training
Persons responsible for overseeing or coordinating sampling are required to ensure that sample
collectors are trained properly in procedures and techniques. Development of proficiency tests
for sampling assays is recommended. Training should be documented in laboratory records,
including a description of the training program content and duration; training records and
performance evaluation records should be maintained and readily available.
3.7.3 SOPs
SOPs describe all sampling procedures including sample collection, transportation, analysis,
storage and disposal as well as SOPs for equipment use, QA/QC, calibration, and production of
reports. SOPs should include all relevant steps in a procedure and be written so that appropriately
trained personnel can apply the procedures. Any required operator training or apparatus for a
procedure (including all required reagents and materials) must be stated. SOPs can cross-
reference other SOPs or documents if necessary, but referenced documents should be cited
properly and available for review. Personnel should review SOPs annually and make
modifications as necessary. Initial sampling technique SOPs may be refined when compared to
another sampling SOP that changes a parameter (e.g., pressure when applying a wipe to a
surface, filtration volume, filter membrane type, etc.).
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3.7.4 Records
Staff must maintain proper and adequate records and files. Records include but are not limited to:
Sample numbering and tracking system;
Analytical data and results for all samples;
Reports generated from analysis;
QC data.
Hard copy records (e.g., sampler forms, original hand written data) should be electronically
scanned or otherwise converted to an electronic format. Electronic records should be backed up
regularly, and each laboratory is responsible for ensuring that records are stored securely and can
be retrieved easily.
3.7.5 Equipment Maintenance and Calibration
Sampling and sample analysis equipment must be maintained as documented in the appropriate
SOPs or manufacturer's guidelines to ensure analytical quality. Laboratories should apply
standards that use the established limits for all equipment; this applies to general equipment such
as pH meters as well as to sophisticated analytical instruments and vehicles. Field equipment
such as balances, pipetters and pH meters in particular should have regular maintenance and/or
calibration schedules. Frequency of calibration checks should be based on established practices
and the stability of the equipment; form and frequency of these checks should be documented
properly. Calibration and maintenance records should be kept for all equipment, which will aid
in assessing repair status.
3.7.6 Sampling Plan
Variations in sampling procedures can have a significant effect on analyses. All sampling
procedures, therefore, should be well documented, with clear details provided for sampling
precautions and sampling strategies.
Recommendations for sampling QA include:
Strictly adhere to sampling SOPs.
Ensure that all equipment is clean and in working order.
Record all applicable conditions during sampling.
Take strict precautions to avoid sample contamination.
A sampling plan must be prepared in advance for all sampling programs. Carefully considered
plans ensure that changes between two sampling rounds are attributable to changes in the
environment and not to procedural changes. Sampling plans should include the sampling
objective (e.g., to test the prevalence of a certain microorganism in soil), site selection (location,
type of environmental matrix), the time and date that samples are collected, the number and
amount of samples collected, as well as methods for holding samples prior to analysis
(e.g., temperature and maximum time). When designing the sampling plan, researchers must
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ensure that collected samples properly represent the specific environment that is being sampled.
3.7.6.1 Data Quality Objectives (DQOs)
DQOs establish the sampling performance or acceptance criteria that are the basis for the
sampling plan design and ensure that samples of sufficient quality and quantity are collected
(U.S. EPA 2004). Detailed guidelines on the DQO process are available in the EPA's Guidance
on Systemic Planning Using the Data Quality Objectives Process (U.S. EPA 2006b) or online at
http://www.epa.gov/qualitv/dqos.html
Data quality indicators (DQIs) provide quantitative measures of identified DQOs by assessing
completeness, comparability, representativeness, precision and accuracy. Completeness
measures the amount of useable data from a data collection activity; comparability expresses the
confidence with which data are considered equivalent; representativeness measures the extent to
which the sampling data reflect the sample site; precision refers to the amount of agreement
between independent test results; and accuracy is the closeness of agreement between a test
result and the accepted reference value (U.S. EPA 2002).
3.7.7 QC
Ensuring QC in the field and laboratory includes using blanks and duplicate, replicate or spiked
samples. In addition to normal variability in microorganism concentrations among samples,
contamination is possible at all phases of the procedure. QC is specific to the purpose of
sampling and how the samples will be analyzed. The following considerations will help ensure
that reliable data are obtained:
1. A matrix blank is unspiked so that background levels of the microbe of interest can be
measured, which is then subtracted from the recovery calculations.
2. Unspiked blank samples (using a sterile form of the environmental matrix sampled)
should be run each time a sampling procedure is completed. If the blanks are positive for
the selected microorganism, the procedure is contaminated, and data from that run may
need to be discarded or repeated.
3. Duplicate or replicate samples should be acquired whenever feasible. Variability in the
microbiological concentration between one sample volume and another is normal.
Replicates provide additional QA and allow for averaging two or more samples to ensure
the most accurate results. The required number of replicates should be determined
statistically.
4. Spiked samples or positive controls should be run for each sampling procedure to establish
that the technique was performed correctly. If positive controls are not positive for the
microorganism of interest, there may be some concern about the technique used—for
example, the media is not good or the incubation temperature is not correct. Spiked
positive controls should be run to check for any matrix interference issues that may cause
false negative results. Spiked negative control also can be run for the opposite reason. If
additional sample is available, the technique may need to be repeated or the results
discarded/invalidated.
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5. Trip or travel blanks are samples of analyte-free media taken from the laboratory to the
sampling site and returned to the laboratory unopened. A trip blank is used to document
contamination attributable to shipping and field handling procedures.
Sufficient QA/QC procedures (blank samples, duplications and positive controls) can increase
the cost of a sampling program substantially but is less costly than the costs associated with
discarding sampling results because of questionable outcomes or inadequate QA.
3.7.8 Sampling Documentation
Careful documentation is required during sampling so that all relevant sample information is
recorded clearly at the time of sampling. Field sampling forms (paper or electronic) should be
included in the sampling plan and be completed by the person conducting the sampling. Forms
should include sampling location, time and date of sample collection (and receipt of the sample
by the analytical laboratory) and conditions; field-measured variables; equipment used (including
inventory numbers); necessary sample preparation; and the sampler's name. A bound field log
book generally is acceptable for record keeping. Electronic recording also may be acceptable
when consistent with an organization's data requirements.
Field measurements such as pH and temperature must be performed on a separate subsample that
subsequently is discarded to avoid contaminating samples for laboratory analysis; for example, a
conductivity measurement should not be prepared with a sample that previously was used to
measure pH, as potassium chloride from the pH probe may affect the conductivity reading.
3.7.9 Data and Reporting
A primary goal of QA is to ensure that data are suitable for their intended use, including results
and interpretations. Data should be checked comprehensively and analyzed by experienced
specialists, and results should be reported accurately and allow for individual interpretation.
Reports should include information that affects interpretation, such as sampling conditions or the
method of analysis; calibration and data QC should be referenced and readily available.
3.7.10 QA Checks
Regular quality compliance checks are necessary to maintain a QA system. Such procedures
involve annual reviews as well as QA system audits, which should be independent, thorough and
preferably unannounced. Reviews and audits should be documented formally and made available
to persons responsible for the work. Deviations from required standards must be corrected as
soon as possible.
(See EPA's Guidance for Quality Assurance Project Plans [U.S. EPA 2002]).
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3.8 Sample Integrity and Tracking
3.8.1 Sample Receipt, Preservation, Storage and Disposal
Recommended preservation methods are used for all collected samples. If samples involve
chemical preservatives, the chemicals must be checked first for efficacy. Sample preservation
stabilizes parameters of interest by retarding chemical or biological changes. Samples containing
microorganisms in particular deteriorate with time, and proper storage and timely transport can
minimize deterioration and preserve sample integrity. Sample integrity is the unimpaired
chemical and biological composition of a test sample upon the extraction of an aliquot for
analysis. Preserving sample integrity ensures that samples arrive at laboratories in the same
condition in which they were collected in the field. Field and transportation measures protect
samples from physical contamination, loss of volume, volatilization, light exposure or damaging
temperature change. Requirements and conditions for preserving and storing samples depend
primarily upon the intended method of analysis. For example, if samples are collected from
chlorinated water sources and the target analyte is a viable organism, as for culture-based
microbiology methods, sample bottles must contain sufficient sodium thiosulfate to neutralize
the residual chlorine present. Samplers and analysts must be vigilant in preventing contamination
of samples and reagents.
Sample integrity elements that must be evaluated include but are not limited to:
Temperature control;
Storage times and conditions;
Preservation chemicals;
Container compatibility;
Labeling/seal integrity;
Volume; and
• Contamination control.
For direct field measurements, sample integrity involves no gain or loss of analyte when
acquiring samples for the detector. In addition, appropriate QC steps must verify sample
integrity.
Samples should be protected from contamination and deterioration before their arrival to a
laboratory. To facilitate sample protection, equipment should be clean—sterile whenever
possible—and in good working condition. Sample containers should be sterile and kept in a
clean environment and away from dust, dirt and fumes. The sample container's inner portion
should not be touched or handled by the operator. Reusable containers must be cleaned properly,
sterilized and proven to be free of quantifiable target analyte before use. Sample collectors
should use sterile gloves and other necessary techniques, such as washing hands and wearing
facemasks, to reduce sample contamination. After collection, samples should be placed in sealed
containers to prevent contamination during storage and/or transport. Storage (i.e., storage
conditions), holding time (i.e., maximum time before analysis for unstable parameters) and
transport procedures also must be considered.
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Laboratory staff should record when samples arrive to ensure that samples are documented as
they pass through the laboratory's analytical systems and that relevant SOPs are followed.
Samples should be logged in and stored so that deterioration is minimized, and sample
conditions and storage locations should be recorded. Subsampling, sample splitting to allow
different storage conditions or sample pretreatment to increase stability also must be recorded.
The source and identity of samples should be marked clearly and uniquely to avoid confusion.
Arrangements for disposal or appropriate disposition of samples and sampling materials should
be made when samples exceed stable storage times and after the samples are no longer needed.
BMBL should be followed for biosafety.
3.8.2 Chain of Custody Considerations
The primary objective of chain of custody is to create an accurate written record that traces the
sample from the moment of collection through its destruction or disposal. Chain of custody helps
avoid indefensible evidence in court by documenting samples as they pass from one person to
the next. An agency must demonstrate the reliability of its evidence by proving the chain of
custody of its samples. A chronological record must be maintained that records who has
possessed the sample(s) and all analyses that were performed on the samples. Following chain-
of-custody procedures when handling samples and data helps provide assurance that no
tampering has occurred. A sampling technique must include chain-of-custody considerations and
instructions for the lifespan of the sample. In general, the following chain-of-custody guidelines
should be followed:
1. A minimum number of people should collect and handle samples and data.
2. Only people associated with the project should handle samples and data.
3. The transfer of samples and data from one person to another must be documented on chain-
of-custody forms and site security for these samples should be maintained.
4. Chain-of-custody forms must accompany samples and data.
5. Samples and data must include identification that is legible and written with permanent ink.
Chain of custody is a progression of steps, each of which has its own chain-of-custody form.
These may include, but are not limited to:
Chain-of-Custody Steps
Necessary Forms
Reagents and Supplies Form
Field Sampling Data Sheet
Shipping and Receiving Form
Sample Receipt and Record Log
Analytical Data Sheet
Archive Contents Record
1. Sampling preparations
2. Taking the sample
3. Transporting the sample to the
laboratory
4. Receipt, storage and transfer of the
sample
5. Sample analysis
6. Data record keeping
These forms are available at http://www.epa. gov/apti/coc/.
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3.8.3 Shipping
Samples and wastes may be subject to DOT hazardous material regulations (HMR)
(see HMR, 49 CFR Parts 171-180) and the CDC's Select Agent Program requirements
(http://www.asm.org/index.php/policv/select-agent-background-information-and-web-
sites.html). In addition, air shipments also must comply with IATA Dangerous Goods
Regulations. Samples collected and wastes generated during field investigations or in response to
hazardous material incidents must be classified by certified DOT/IATA personnel prior to
shipment as either environmental or hazardous materials (dangerous goods) samples. Most
uncharacterized environmental samples (including drinking water) and most groundwater and
ambient surface water, soil, sediment and treated municipal and industrial wastewater effluent
may not require a permit to ship, but organizational policy should be followed with regard to
sample shipments. Suspected contaminated samples or wastes must be shipped as dangerous
goods or possibly as select agents.
All hazardous goods shipments must comply with the regulations and guidance described above.
Personnel with approved DOT/IATA training must perform all shipments of potentially
hazardous materials, and such shipments should be packaged, labeled and shipped according to
the appropriate ground or air regulations. Sample and packaging integrity must be maintained to
ensure safe shipment. In addition, shipments may be subject to the Select Agent Rules (42 CFR
72.6), which are part of the Select Agent Program that is administered by the CDC and U.S.
Department of Agriculture. Samples or wastes should be stored in a secure area that is protected
from vermin and adverse weather conditions, and hazardous and nonhazardous samples and
wastes must be separated.
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4. Writing the Technique
The validation process includes preparing a written description of the technique. Historically,
EPA techniques use the EMMC format that includes the following components: scope and
application; technique summary; definitions; interferences; health and safety; equipment and
supplies; reagents and standards; sample collection, preservation, and storage; QC; calibration
and standardization; procedural steps; calculations and data analysis; technique performance;
pollution prevention; and waste management. In particular, Section 17 of the EMMC addresses
validation data. The EMMC can be accessed online at http://www.epa. gov/ttn/emc/guidlnd/gd-
045.pdf. Table 1 in this report describes the components. Note that this is a recommended format
and not a requirement. It is recommended that the numerical and descriptive specifications of the
technique's operational limits be included as well as the performance attributes determined
during validation. The validation process should be sufficient for meeting the technique's
intended use.
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5. Sampling Technique Validation Reports
SOPs and good recordkeeping are essential elements of validated sampling techniques. A
specific sampling technique should document that the technique was validated appropriately and
verified by field studies. Successful completion of such studies should be documented in the
sampling technique validation report.
A suitable report should be prepared for placing in the public docket. The report should address
the sampling technique validation topics outlined in this guidance document and summarized in
Table 1 and provide: (a) background information on sampling technique development; (b) a
description of the sampling technique; (c) a description of the sampling technique validation
practices; (d) changes made to the sampling technique as a result of the validation studies; and
(e) recommendations for future work. At a minimum, the sampling technique validation report
must address the information contained in Table 1.
Table 1. Minimum Sampling Technique Validation Report Topics
Topic
Explanation
Sampling
Technique
Provide the SOP or a thorough description of the sampling technique that is being
validated.
Summary
Provide an overall summary of the validation report.
Introduction
1. Provide background information on the sampling technique development.
2. State the purpose of the technique, including the measurement objectives and
the intended use of the data.
Methodology
1. Describe the experimental design for validating the sampling technique,
including:
• The test method/procedure;
• Details of equipment/locations used, with calibration status.
2. Describe the technique's scope and applicability, including:
• How the scope and applicability define the range of technique
performance;
• Sampling or field measurement process components to be validated;
• Matrix to be sampled and unique properties of the sampling matrix
(e.g., soil heterogeneity);
• Nature of the analytes;
• Range of analyte levels for which the technique is suited;
• Advantages and limitations of the sampling technique;
• Sampling equipment and supplies;
• How the technique and analytical parameters meet the DQOs for the specific
application.
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Table 1: Minimum Technique Validation Report Topics, cont'd.
Sampling
Technique
Characteristics
1. Selectivity: Describe how selectivity was evaluated and how the sampling
plan identified and addressed interferences.
2. Sensitivity: Describe the sensitivity of the technique and how the sampling
plan addressed it.
3. Specificity: Describe how specificity was evaluated and how the sampling
plan addressed it.
4. Viability/Sample Integrity: Describe how the sampling plan addresses
viability assays, if required/applicable, and what the requirements are for
maintaining/
preserving viability. Describe sample security from the collection site to the
analytical laboratory.
5. Sample Size/Area or Volume Sampled: Discuss the number of items or the
quantity that constitutes an adequate sample for the technique, and whether
the samples are composites or grab.
6. Robustness: Describe how the sampling technique matches the performance
of the applicable analytical assay technique(s).
7. Ruggedness: Describe sampling technique performance after experiencing
minor changes in operating or environmental conditions.
8. Resource Requirements and Required Measurements: Describe the
applicable resource requirements, such as personnel, skills, and equipment,
as well as the required measurements to be taken, such as site parameters
and matrix parameters.
Safety
Considerations
Describe safety concerns and procedures that should be addressed, including
personal protective equipment and first aid as well as physical and chemical
hazards.
QC/QA
Describe the QC/QA checks used.
Discussion
1. Discuss technique development.
2. Discuss validation testing results. Evaluate the testing, including
comparison with reference materials and preparations, acceptance criteria
and recommendations.
3. Discuss sampling technique changes that were made as a result of the
validation studies.
Conclusions
1. Discuss formal acceptance/rejection of work.
2. Provide recommendations for future work.
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6. Multi-laboratory Validation Studies
Generally, EPA has recommended using inter-laboratory collaborative studies when validating
techniques that are expected to be used widely or support regulatory activity. EPA typically uses
a tiered approach that was developed under the streamlining initiative for validating
microbiological techniques; this approach takes into consideration the level of intended use for a
technique. This approach also minimizes the validation requirements of limited-use techniques
(single-laboratory and single-industry use) and instead focuses resources on validating
techniques that are intended for nationwide use. Because QC acceptance criteria are developed
from validation studies and validation requirements vary with each tier, appropriate statistical
procedures to develop the criteria will vary by tier as well.
For an in-depth discussion of multi-laboratory validation studies, refer to Method Validation of
U.S. Environmental Protection Agency Microbiological Methods of Analysis, FEM 2009-01
(U.S. EPA 2009).
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7. Peer Review
Prior to publication, EPA sampling techniques are peer reviewed according to the information
provided in the current version of the EPA Science Policy Council's Peer Review Handbook
(U.S. EPA, 2006a). The Handbook provides Agency-wide guidance for consistent
implementation of peer review, and program offices have the flexibility to design peer reviews
for their specific needs. The Handbook also provides detailed information about the products that
are subject to peer review. In addition, information is available on selecting peer review
mechanisms (internal and external), planning a peer review process, conducting a peer review
and preparing peer-review records.
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References
USEPA (U.S. Environmental Protection Agency). 2002. Guidance for Quality Assurance Project
Plans. Washington, D.C.: USEPA, Office of Environmental Information. EPA/240/R-
02/009. http://www.epa.gov/qualitv/qapps.html
USEPA. 2004. Quality Assurance/Quality Control Guidance for Laboratories Performing PCR
Analyses on Environmental Samples. Cincinnati, OH: USEPA, Office of Water.
EPA/815/B-0/-001.
USEPA. 2005. Manual for the Certification of Laboratories Analyzing Drinking Water, Criteria
and Procedures Quality Assurance, 5th ed.; Cincinnati, OH: USEPA. Office of Water.
EPA/815/R-05/004.
USEPA. 2006a. Peer Review Handbook, 3rd ed., Washington, D.C.: USEPA, Science Policy
Council. EPA/100/B-06/002.
USEPA. 2006b. Guidance on Systemic Planning Using the Data Quality Objectives Process.
Washington, D.C.: USEPA, Office of Environmental Information. EPA/240/B-06/001.
USEPA. 2009. Method Validation of U.S. Environmental Protection Agency Microbiological
Methods of Analysis. FEM 2009-01.
USEPA. 2010. EPA Microbiological Alternate Test Procedure (ATP) Protocol for Drinking
Water, Ambient Water, Wastewater, and Sewage Sludge Monitoring Methods.
Washington, D.C.: USEPA, Office of Water. EPA/821/B-10/001.
USEPA. 2010. Environmental Measurement Glossary of Terms. Forum of Environmental
Measurements. Online at
http://epa.gov/fem/pdfs/Env Measurement Glossary Final Jan 2010.pdf
USEPA. Environmental Measurement Monitoring Council (EMMC) Methods Format. Online at
http ://www. epa. gov/ttn/emc/ guidlnd/ gd-045. pdf
U.S. Pharmacopoeia Convention. 2006. United States Pharmacopoeia-National Formulary,
(editions: USP 29, NF 24). Rockville, MD: U.S. Pharmacopoeial Convention.
Wood, J. P., P. Lemieux, D. Betancourt, P. Kariher, N. Griffin. 2008. "Pilot-scale experimental
and theoretical investigations into the thermal destruction of a Bacillus anthracis
surrogate embedded in building decontamination residue bundles." Environ. Sci. Technol.
42 (15): 5712-7.
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Further Reading and Additional Guidance
American Public Health Association, American Water Works Association, Water Environment
Federation. 2017. Standard Methods for the Examination of Water and Wastewater, 23rd
ed., Editors: Rice, E. W., R. B. Baird, A. D. Eaton, L. S. Clesceri, and Washington, D.C.:
American Public Health Association, Water Environment Federation, and American
Water Works Association.
ASTM D 6232-00. 2002. Standard Guide for Selection of Sampling Equipment for Waste and
Contaminated Media Data Activities. Annual Book of ASTM Standards, (11.04), 456-64.
West Conshohocken, PA: ASTM International.
Bell, S. 1999. A Beginner's Guide to Uncertainty of Measurement. Measurement Good Practice
Guide No. 11 (Issue 2). Teddington, U.K.: National Physical Laboratory.
Birch, K. 2001. Estimating Uncertainties in Testing. Measurement Good Practice Guide No. 36.
Teddington, U.K.: National Physical Laboratory.
Chen, P. E., K. M. Willner, A. Butani, S. Dorsey, M. George, et al. 2010. Rapid identification of
genetic modifications in Bacillus anthracis using whole genome draft sequences
generated by 454 pyrosequencing. PLoS One 5 (8): el2397.
doi: 10.1371/journal.pone.0012397
[editors, L. Casey Chosewood, Deborah E. Wilson], Biosafety in Microbiological and
Biomedical Laboratories. [Washington DC.]: U.S. Dept. of Health and Human Services,
Public Health Service, Centers for Disease Control and Prevention, National Institutes of
Health, 2009. https://www.cdc.gov/biosafety/publications/bmbl5/bmbl.pdf
International Organization for Standardization (ISO). 1998. Soil Quality - Vocabulary - Part 2:
Terms and Definitions Relating to Sampling, ISO 11074-2: 1998. Geneva, Switzerland:
International Organization for Standardization.
Kim, J., R. H. Linton, 2008. Identification of non-pathogenic surrogate organism for
chlorine dioxide (CIO 2) gas treatment. Food Microbiol. 25 (4): 597-06.
Montville, T. J., T. DeSiano, A. Nock, S. Padhi, D. Wade. 2006. Inhibition of Bacillus anthracis
and potential surrogate bacilli growth from spore inocula by nisin and other antimicrobial
peptides. J. FoodProt. 69 (10): 2529-33.
Packard, B. H., M. J. Kupferle. 2010. Evaluation of surface sampling techniques for collection of
Bacillus spores on common drinking water pipe materials. J. Environ. Monit. 12 (1):
361-8.
Sen, K., N. A. Schable, D. J. Lye. 2007. Development of an internal control for evaluation and
standardization of a quantitative PCR assay for detection of Helicobacter pylori in
drinking water. Appl. Environ. Microbiol. 73 (22): 7380-7.
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USEPA. 2012. Selected Analytical Methods for Environmental Remediation and Recovery
(SAM). Cincinnati, OH: USEPA, Office of Research and Development. EPA/600/R-
12/555. Online at http://epa.gov/sam/
USEPA. 2007. Guidance for Preparing Standard Operating Procedures. Washington D.C.:
USEPA, Office of Environmental Information. EPA/600/B-07/001.
USEPA. 1993. Health and Safety Plan (HASP) Users' Guide. Washington, D.C.: USEPA, Office
of Solid Waste and Emergency Response (OSWER). PB93-963414. EPA/540/C-93/002.
USEPA. 1992. Guidance for Data Usability in Risk Assessment (Part A). Washington, D.C.:
USEPA, Office of Solid Waste and Emergency Response (OSWER), Office of
Emergency and Remedial Response Directive 9285.7-09A. PB92-963356.
Vasconcelos, J., S. Harris. 1992. Consensus Methodfor Determining Groundwaters Under the
Direct Influence of Surface Water Using Microscopic Particulate Analysis. Port Orchard,
WA: USEPA, Environmental Services Division, Manchester Environmental Laboratory.
EPA 910/9-92-029.
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Appendix A: Sampling Technique Validation Plan
The sampling validation process is an integral element of the sampling technique, and planning
documents should be included within the plan as a section or as a stand-alone document attached
as an appendix. It should integrate the contributions and requirements of all stakeholders and
present this information in a clear, concise format. To achieve this goal, validation planning
should be part of the initial planning (e.g., directed planning process). The information and
documentation identified in the plans should be communicated to the laboratory as part of the
statement of work, project or study plan, standard operating procedure (SOP), or quality
assurance (QA) project plan.
The sampling validation plan must address, but is not limited to, the following information:
1. Purpose of validation
2. Sampling procedure, including:
a. Description of the main principle of the test method;
b. Description of test procedures and test conditions (including precautions, reagents,
reference and preparation substances);
c. Details of equipment and facilities to be used (including measuring/recording
equipment), with calibration status;
d. Variables to be monitored.
3. Performance characteristics, as listed in this document:
a. Selectivity;
b. Sensitivity;
c. Specificity;
d. Viability;
e. Required measurements;
f. Area, volume or mass sampled;
g. Robustness;
h. Ruggedness; and
i. Resource requirements.
4. Safety and security
5. Waste minimization and waste management
6. QA/quality control (QC), including:
a. Blanks, equipment rinsate samples and field duplicates;
b. QA/QC management system;
c. Laboratory QC sample;
d. Documentation and records management;
e. Training;
f. SOPs;
g. Equipment maintenance and calibration.
7. Sample integrity
a. Sample receipt, labels, logs, preservation, holding times, sample containers,
transportation, etc.; and
b. Chain-of-Custody forms.
8. Shipping considerations
9. Details of methods for recording and evaluating results, including statistical analysis
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