Multi-Agency Radiological

Laboratory Analytical Protocols Manual

Accompaniment to CD ñ Executive Summary (Roadmap)

IMPLEMENTATION

PLANNING

ASSESSMENT

MARLAP

NUREG-1576, Supp. 1

July 2004

NUREG-1576, Supp. 1

Multi-Agency Radiological

Laboratory Analytical Protocols Manual

(MARLAP)

Accompaniment to CD — Executive Summary (Roadmap)

United States Environmental Protection Agency

United States Department of Defense

United States Department of Energy

United States Department of Homeland Security

United States Nuclear Regulatory Commission

United States Food and Drug Administration

United States Geological Survey

National Institute of Standards and Technology

July 2004
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JULY 2004 III MARLAP

ABSTRACT

The Multi-Agency Radiological Laboratory Analytical Protocols (MARLAP) manual provides

guidance for the planning, implementation, and assessment of projects that require the laboratory

analysis of radionuclides. MARLAP’s basic goal is to provide guidance for project planners,

managers, and laboratory personnel to ensure that radioanalytical laboratory data will meet a

project’s or program’s data requirements. To attain this goal, the manual offers a framework for

national consistency in the form of a performance-based approach for meeting data requirements

that is scientifically rigorous and flexible enough to be applied to a diversity of projects and

programs. The guidance in MARLAP is designed to help ensure the generation of radioanalytical

data of known quality, appropriate for its intended use. Examples of data collection activities that

MARLAP supports include site characterization, site cleanup and compliance demonstration,

decommissioning of nuclear facilities, emergency response, remedial and removal actions,

effluent monitoring of licensed facilities, environmental site monitoring, background studies, and

waste management activities.

MARLAP is organized into two parts. Part I, intended primarily for project planners and

managers, provides the basic framework of the directed planning process as it applies to projects

requiring radioanalytical data for decision making. The nine chapters in Part I offer

recommendations and guidance on project planning, key issues to be considered during the

development of analytical protocol specifications, developing measurement quality objectives,

project planning documents and their significance, obtaining laboratory services, selecting and

applying analytical methods, evaluating methods and laboratories, verifying and validating

radiochemical data, and assessing data quality. Part II is intended primarily for laboratory

personnel. Its eleven chapters provide detailed guidance on field sampling issues that affect

laboratory measurements, sample receipt and tracking, sample preparation in the laboratory,

sample dissolution, chemical separation techniques, instrumentation for measuring radionuclides,

data acquisition, reduction, and reporting, waste management, laboratory quality control,

measurement uncertainty, and detection and quantification capability. Seven appendices provide

complementary information and additional details on specific topics.

MARLAP was developed by a workgroup that included representatives from the U.S. Environmental Protection Agency (EPA), Department of Energy (DOE), Department of Defense (DOD),

Department of Homeland Security (DHS), Nuclear Regulatory Commission (NRC), National

Institute of Standards and Technology (NIST), U.S. Geological Survey (USGS), and Food and

Drug Administration (FDA), and from the Commonwealth of Kentucky and the State of

California.

JULY 2004 V MARLAP

FOREWORD

MARLAP is organized into two parts. Part I, consisting of Chapters 1 through 9, is intended

primarily for project planners and managers. Part I introduces the directed planning process

central to MARLAP and provides guidance on project planning with emphasis on radioanalytical

planning issues and radioanalytical data requirements. Part II, consisting of Chapters 10 through

20, is intended primarily for laboratory personnel and provides guidance in the relevant areas of

radioanalytical laboratory work. In addition, MARLAP contains seven appendices—labeled A

through G—that provide complementary information, detail background information, or concepts

pertinent to more than one chapter. Six chapters and one appendix are immediately followed by

one or more attachments that the authors believe will provide additional or more detailed

explanations of concepts discussed within the chapter. Attachments to chapters have letter

designators (e.g, Attachment “6A” or “3B”), while attachments to appendices are numbered (e.g.,

“B1”). Thus, “Section B.1.1” refers to section 1.1 of appendix B, while “Section B1.1” refers to

section 1 of attachment 1 to appendix B. Cross-references within the text are explicit in order to

avoid confusion.

Because of its length, the printed version of MARLAP is bound in three volumes. Volume I

(Chapters 1 through 9 and Appendices A through E) contains Part I. Because of its length, Part II

is split between Volumes II and III. Volume II (Chapters 10 through 17 and Appendix F) covers

most of the activities performed at radioanalytical laboratories, from field and sampling issues

that affect laboratory measurements through waste management. Volume III (Chapters 18

through 20 and Appendix G) covers laboratory quality control, measurement uncertainty and

detection and quantification capability. Each volume includes a table of contents, list of

acronyms and abbreviations, and a complete glossary of terms. 

MARLAP and its periodic revisions are available online at www.epa.gov/radiation/marlap and

www.nrc.gov/reading-rm/doc-collections/nuregs/staff/sr1576/. The online version is updated

periodically and may differ from the last printed version. Although references to material found

on a web site bear the date the material was accessed, the material available on the date cited may

subsequently be removed from the site. Printed and CD-ROM versions of MARLAP are

available through the National Technical Information Service (NTIS). NTIS may be accessed

online at www.ntis.gov. The NTIS Sales Desk can be reached between 8:30 a.m. and 6:00 p.m.

Eastern Time, Monday through Friday at 1-800-553-6847; TDD (hearing impaired only) at 703-

487-4639 between 8:30 a.m. and 5:00 p.m Eastern Time, Monday through Friday; or fax at 703-

605-6900.

MARLAP is a living document, and future editions are already under consideration. Users are

urged to provide feedback on how MARLAP can be improved. While suggestions may not

always be acknowledged or adopted, commentors may be assured that they will be considered

carefully. Comments may be submitted electronically through a link on EPA’s MARLAP web

site (www.epa.gov/radiation/marlap).

JULY 2004 VII MARLAP

ACKNOWLEDGMENTS

The origin of the Multi-Agency Radiological Laboratory Analytical Protocols (MARLAP)

manual can be traced to the recognition by a number of agencies for the need to have a nationally

consistent approach to producing radioanalytical data that meet a program’s or project’s needs. A

workgroup was formed with representatives from the U.S. Environmental Protection Agency

(EPA), Department of Energy (DOE), Department of Homeland Security (DHS), Nuclear

Regulatory Commission (NRC), Department of Defense (DOD), U.S. Geological Survey

(USGS), National Institute of Standards and Technology (NIST), and Food and Drug Administration (FDA) to develop guidance for the planning, implementation, and assessment of projects

that require the laboratory analysis of radionuclides. Representatives from the Commonwealth of

Kentucky and the State of California also contributed to the development of the manual.

Contractors and consultants of EPA, DOE, and NRC—and members of the public—have been

present during open meetings of the MARLAP workgroup. 

MARLAP would not have been possible without the workgroup members who contributed their

time, talent, and efforts to develop this guidance document:

John Griggs*, EPA, Chair

EPA: H. Benjamin Hull

Marianne Lynch*

Keith McCroan*

Eric Reynolds

Jon Richards

FDA: Edmond Baratta

DOD: Andrew Scott (Army)

 Ronald Swatski* (Army)

Jan Dunker (Army Corps of Engineers)

William J. Adams (Navy)

Troy Blanton (Navy)

David Farrand (Navy)

Dale Thomas (Air Force)

DOE: Emile Boulos*

Stan Morton*

Stephanie Woolf*

DHS†

: Carl Gogolak*

Pamela Greenlaw*

Catherine Klusek*

Colin Sanderson*

NRC: Rateb (Boby) Abu Eid

Tin Mo

George Powers

NIST: Kenneth G.W. Inn*

USGS: Ann Mullin*

*

 These workgroup members also served as chapter chairs.

†

 All with the Environmental Measurements Laboratory, which was part of DOE prior to the establishment of DHS

on March 1, 2003.
Acknowledgments

MARLAP VIII JULY 2004

Special recognition is given to John Volpe, Commonwealth of Kentucky, and Penny Leinwander,

State of California, for their contributions to the development of the MARLAP manual. The

following federal agency contractors provided assistance in developing the MARLAP manual:

EPA: N. Jay Bassin (Environmental Management Support, Inc.)

U. Hans Behling ( S. Cohen & Associates, Inc.)

Richard Blanchard (S. Cohen & Associates, Inc.)

Leca Buchan (Environmental Management Support, Inc.)

Jessica Burns (Environmental Management Support, Inc.)

Harry Chmelynski

Diane Dopkin (Environmental Management Support, Inc.)

Scott Hay (S. Cohen & Associates, Inc.)

Patrick Kelly (S. Cohen & Associates, Inc.)

Robert Litman

David McCurdy

Charles (Chick) Phillips (S. Cohen & Associates, Inc.)

William Richardson III (S. Cohen & Associates, Inc.)

Steven Schaffer (S. Cohen & Associates, Inc.)

Michael Schultz

Robert Shannon (Time Solutions Corp.) 

 DOE: Stan Blacker (MACTEC, Inc.)

Pat Harrington (MACTEC, Inc.)

David McCurdy

John Maney (Environmental Measurements Assessments)

Mike Miller (MACTEC, Inc.)

Lisa Smith (Argonne National Laboratory)

NRC: Eric W. Abelquist (ORISE)

Dale Condra (ORISE)

The MARLAP workgroup was greatly aided in the development of the manual by the

contributions and support provided by the individuals listed below.

John Arnold (USGS)

David Bottrell (DOE)

Lloyd Currie (NIST)

Mike Carter (EPA)

Mary Clark (EPA)

Ron Colle (NIST)

Mark Doehnert (EPA)

Steve Domotor (DOE)

Joan Fisk (EPA)

David Friedman (EPA)

Lino Fragoso (Navy)

Richard Graham (EPA)

Patricia Gowland (EPA)

Larry Jensen (EPA)

K. Jack Kooyoomjian (EPA)

Jim Kottan (NRC)

Ed Messer (EPA)

Kevin Miller (DOE)

Jim Mitchell (EPA)

Colleen Petullo (EPA)

Steve Pia (EPA)

Phil Reed (NRC) 

Cheryl Trottier (NRC)

Mary C. Verwolf (DOE)

John Warren (EPA)

Mary L. Winston (EPA)

Tony Wolbarst (EPA)
Acknowledgments

JULY 2004 IX MARLAP

EPA’s Science Advisory Board (SAB) Radiation Advisory Committee’s Review Subcommittee

that conducted an extensive peer review of the MARLAP includes:

Chair

Dr. Janet A. Johnson, Shepherd Miller, Inc.

SAB Members 

Dr. Lynn R. Anspaugh, University of Utah

Dr. Bruce B. Boecker, (Scientist Emeritus), Lovelace Respiratory Research Institute

Dr. Gilles Y. Bussod, Science Network International

Dr. Thomas F. Gesell, Idaho State University

Dr. Helen Ann Grogan, Cascade Scientific, Inc.

Dr. Richard W. Hornung, University of Cincinnati

Dr. Jill Lipoti, New Jersey Department of Environmental Protection

Dr. Genevieve S. Roessler, Radiation Consultant

SAB Consultants 

Dr. Vicki M. Bier, University of Wisconsin

Dr. Stephen L. Brown, R2C2 (Risks of Radiation and Chemical Compounds)

Dr. Michael E. Ginevan, M.E. Ginevan & Associates

Dr. Shawki Ibrahim, Colorado State University

Dr. Bernd Kahn, Georgia Institute of Technology

Dr. June Fabryka-Martin, Los Alamos National Laboratory

Dr. Bobby R. Scott, Lovelace Respiratory Research Institute

Science Advisory Board Staff 

Dr. K. Jack Kooyoomjian, Designated Federal Officer, EPA

Ms. Mary L. Winston, Management Assistant, EPA

Dozens of individuals and organizations offered hundreds of valuable comments in response to

the Call for Public Comments on the draft MARLAP between August 2001 and January 2002,

and their suggestions contributed greatly to the quality and consistency of the final document. 

While they are too numerous to mention individually, Jay A. MacLellan, Pacific Northwest

National Laboratory; Daniel J. Strom, Pacific Northwest National Laboratory; and James H.

Stapleton, Department of Statistics and Probability of Michigan State University are especially

acknowledged for their comments and suggestions.

JULY 2004 XI MARLAP

TABLE OF CONTENTS

ABSTRACT . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . III

FOREWORD . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . V

ACKNOWLEDGMENTS ..................................................... VII

EXECUTIVE SUMMARY . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Purpose of the Manual . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 2

Use and Scope of the Manual . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 3

Key MARLAP Concepts and Terminology . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Data Life Cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Directed Planning Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Performance-Based Approach . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 5

Analytical Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 6

Analytical Protocol . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Analytical Method ....................................................7

Uncertainty and Error . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 7

Precision, Bias, and Accuracy ...........................................9

Performance Objectives: Data Quality Objectives and Measurement Quality

Objectives . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 10

Analytical Protocol Specifications . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

The Assessment Phase . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 11

The MARLAP Process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 12

Structure of the Manual . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 13

Overview of Part I . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 15

Overview of Part II . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 17

Overview of the Appendices . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 18

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19

List of Figures

Figure 1 — The data life cycle . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 4

Figure 2 — Typical components of an analytical process ...............................6

Figure 3 — The MARLAP process . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 14

Figure 4 — Key MARLAP terms and processes (roadmap) . . . . . . . . . . . . . . . . . . . . . . . . . . . . 16

JULY 2004 1 MARLAP

EXECUTIVE SUMMARY

Overview

Each year, hundreds of millions of dollars are spent on projects and programs that rely, to varying

degrees, on radioanalytical data for decisionmaking. These decisions often have a significant

impact on human health and the environment. Of critical importance to informed decisionmaking

are data of known quality, appropriate for their intended use. Making incorrect decisions due to

data inadequacies, such as failing to remediate a radioactively contaminated site properly,

necessitates the expenditure of additional resources, causes delays in project completions and,

depending on the nature of the project, can result in the loss of public trust and confidence. The

Multi-Agency Radiological Laboratory Analytical Protocols (MARLAP) Manual addresses the

need for a nationally consistent approach to producing radioanalytical laboratory data that meet a

project’s or program’s data requirements. MARLAP provides guidance for the planning,

implementation, and assessment phases of those projects that require the laboratory analysis of

radionuclides. The guidance provided by MARLAP is both scientifically rigorous and flexible

enough to be applied to a diversity of projects and programs. This guidance is intended for

project planners, managers, and laboratory personnel.

MARLAP is divided into two main parts. Part I is primarily for project planners and managers

and provides guidance on project planning with emphasis on analytical planning issues and

analytical data requirements. Part I also provides guidance on preparing project plan documents

and radioanalytical statements of work (SOWs), obtaining and evaluating radioanalytical

laboratory services, data validation, and data quality assessment. Part I of MARLAP covers the

entire life of a project that requires the laboratory analysis of radionuclides from the initial

project planning phase to the assessment phase.

Part II of MARLAP is primarily for laboratory personnel and provides guidance in the relevant

areas of radioanalytical laboratory work. Part II offers information on the laboratory analysis of

radionuclides. The chapters in Part II cover the range of activities performed at radioanalytical

laboratories, including sample preservation, shipping and handling, sample preparation, sample

dissolution, separation techniques, instrument measurements, data reduction, quality control,

statistics, and waste management. Part II is not a compilation of analytical procedures but rather

is intended to provide information on many of

the radioanalytical options available to laboratories and discuss the advantages and

disadvantages of each.

MARLAP was developed collaboratively by the

following federal agencies: the Environmental

Protection Agency (EPA), the Department of

Energy (DOE), the Department of Homeland

Contents

Overview . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 1

Purpose of the Manual . . . . . . . . . . . . . . . . . . . . . . . . 2

Use and Scope of the Manual . . . . . . . . . . . . . . . . . . 3

Key MARLAP Concepts and Terminology . . . . . . . . 4

The MARLAP Process . . . . . . . . . . . . . . . . . . . . . . 12

Structure of the Manual . . . . . . . . . . . . . . . . . . . . . . 13

References . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . . 19
MARLAP Executive Summary

MARLAP 2 JULY 2004

Security (DHS), the Nuclear Regulatory Commission (NRC), the Department of Defense (DOD),

the National Institute of Standards and Technology (NIST), the United States Geological Survey

(USGS), and the Food and Drug Administration (FDA). State participation in the development of

MARLAP involved contributions from representatives from the Commonwealth of Kentucky

and the State of California. 

Purpose of the Manual

MARLAP’s basic goal is to provide guidance for project planners, managers, and laboratory

personnel to ensure that radioanalytical laboratory data will meet a project’s or program’s data

requirements and needs. To attain this goal, MARLAP provides the necessary framework for

national consistency in radioanalytical work in the form of a performance-based approach for

meeting a project’s data requirements. In general terms, a performance-based approach to

laboratory analytical work involves clearly defining the analytical data needs and requirements of

a project in terms of measurable goals during the planning phase of a project. These projectspecific analytical data needs and requirements then serve as measurement performance criteria

for decisions as to exactly how the laboratory analysis will be conducted during the implementation phase of a project. They are used subsequently as criteria for evaluating analytical data

during the assessment phase. The manual focuses on activities performed at radioanalytical

laboratories as well as on activities and issues that direct, affect, or can be used to evaluate

activities performed at radioanalytical laboratories.

Specific objectives of MARLAP include:

• Promoting a directed planning process for projects involving individuals from relevant

disciplines including radiochemistry;

• Highlighting common radioanalytical planning issues;

• Providing a framework and information resource for using a performance-based approach for

planning and conducting radioanalytical work;

• Providing guidance on linking project planning, implementation, and assessment;

• Providing guidance on obtaining and evaluating radioanalytical laboratory services;

• Providing guidance for evaluating radioanalytical laboratory data, i.e., data verification, data

validation, and data quality assessment;

• Promoting high quality radioanalytical laboratory work; and

• Making collective knowledge and experience in radioanalytical work widely available.
MARLAP Executive Summary

JULY 2004 3 MARLAP

Use and Scope of the Manual

The guidance contained in MARLAP is for both governmental and private sectors. Users of

MARLAP include project planners, project managers, laboratory personnel, regulators, auditors,

inspectors, data evaluators, decisionmakers, and other end users of radioanalytical laboratory

data.

Because MARLAP uses a performance-based approach to laboratory measurements, the

guidance contained in the manual is applicable to a wide range of projects and activities that

require radioanalytical laboratory measurements. Examples of data collection activities that

MARLAP supports include:

• Site characterization activities;

• Site cleanup and compliance demonstration activities;

• License termination activities;

• Decommissioning of nuclear facilities;

• Remedial and removal actions;

• Effluent monitoring of licensed facilities;

• Emergency response activities;

• Environmental site monitoring;

• Background studies;

• Routine ambient monitoring; and

• Waste management activities.

MARLAP and the Multi-Agency Radiation Survey and Site Investigation Manual

(MARSSIM, 2000) are complementary guidance documents in support of cleanup and

decommissioning activities. MARSSIM provides guidance on how to plan and carry out a study

to demonstrate that a site meets appropriate release criteria. It describes a methodology for

planning, conducting, evaluating, and documenting environmental radiation surveys conducted to

demonstrate compliance with cleanup criteria. MARLAP provides guidance and a framework for

both project planners and laboratory personnel to ensure that radioanalytical data will meet the

needs and requirements of cleanup and decommissioning activities.

While MARLAP supports a wide range of projects, some topics specifically are not discussed in

the manual. These include high-level waste, mixed waste, and medical applications involving

radionuclides. While they are not specifically addressed, much of MARLAP’s guidance may be

applicable in these areas. Although the focus of the manual is to provide guidance for those

projects that require the laboratory analysis of radionuclides, much of the guidance on the

planning and assessment phases can be applied wherever the measurement process is conducted,

for example, in the field. In addition, MARLAP does not provide specific guidance on sampling

design issues, sample collection, field measurements, or laboratory health and safety practices.
MARLAP Executive Summary

MARLAP 4 JULY 2004

	
	

 		





















 




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FIGURE 1 — The data life cycle

However, a brief discussion of some aspects of these activities has been included in the manual

because of the effect these activities often have on the laboratory analytical process.

Key MARLAP Concepts and Terminology

Some of the terms used in MARLAP were developed for the purpose of this manual, while

others are commonly used terms that have been adopted by MARLAP. Where possible, every

effort has been made to use terms and definitions from consensus-based organizations (e.g.,

International Organization for Standardization [ISO], American National Standards Institute

[ANSI], American Society for Testing and Materials [ASTM], International Union of Pure and

Applied Chemistry [IUPAC]). 

The following sections are

intended to familiarize the reader

with the key terms and concepts

used in MARLAP. In general,

each term or concept is discussed

individually in each section

without emphasizing how these

terms and concepts are linked.

The section on page 12 ties these

terms and concepts together to

provide an overview of the

MARLAP process.

Data Life Cycle

The data life cycle (EPA, 2000)

approach provides a structured

means of considering the major

phases of projects that involve

data collection activities

(Figure 1). The three phases of

the data life cycle are planning,

implementation, and assessment.

Although the diagram represents

the data life cycle in a linear

fashion, it is important to note that the actual process is an iterative one, with feedback loops.

MARLAP provides information on all three phases for two major types of activities: those

performed at radioanalytical laboratories and those that direct, affect, or evaluate activities
MARLAP Executive Summary

JULY 2004 5 MARLAP

performed at radioanalytical laboratories (such as project planning, development of plan

documents, data verification, and data validation). 

One of MARLAP’s specific objectives is to emphasize the importance of establishing the proper

linkages among the three phases of the data life cycle. This results in an integrated and iterative

process that translates the expectations and requirements of data users into measurement

performance criteria for data suppliers. The integration of the three phases of the data life cycle is

critical to ensuring that the analytical data requirements (defined during the planning phase) can

serve as measurement performance criteria during the implementation phase and subsequently as

data evaluation criteria during the assessment phase.

Without the proper linkages and integration of the three phases, there is a significant likelihood

that the analytical data will not meet a project’s data requirements. The data may be evaluated

using criteria that have little relation to their intended use. Therefore, failure to integrate and

adequately link the three phases of the data life cycle increases the likelihood of project cost

escalation or project failure. 

Directed Planning Process

MARLAP recommends the use of a directed or systematic planning process. A directed planning

process is an approach for setting well-defined, achievable objectives and developing a costeffective, technically sound sampling and analysis design that balances the data user’s tolerance

for uncertainty in the decision process with the resources available for obtaining data to support a

decision. While MARLAP recommends and promotes the use of a directed planning process, it

does not recommend or endorse any particular directed planning process. However, MARLAP

employs many of the terms and concepts associated with the data quality objective (DQO)

process (ASTM D5792; EPA, 2000). This was done to ensure consistent terminology throughout

the manual, and also because many of the terms and concepts of this process are familiar to those

engaged in environmental data collection activities. 

Performance-Based Approach

MARLAP provides the necessary guidance for using a performance-based approach to meet a

project’s analytical data requirements. In a performance-based approach, the project-specific

analytical data requirements that are determined during directed planning serve as measurement

performance criteria for analytical selections and decisions. The project-specific analytical data

requirements also are used for the initial, ongoing, and final evaluation of the laboratory’s

performance and the laboratory’s data. MARLAP provides guidance for using a performancebased approach for all three phases of the data life cycle for those projects that require

radioanalytical laboratory data. This involves not only using a performance-based approach for

selecting an analytical protocol, but also using a performance-based approach for other project
MARLAP Executive Summary

MARLAP 6 JULY 2004

	







 



















 
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FIGURE 2 — Typical components of an analytical process

activities, such as developing acceptance criteria for laboratory quality control samples,

laboratory evaluations, data verification, data validation, and data quality assessment.

There are three major steps associated with a performance-based approach. The first is clearly

and accurately defining the analytical data requirements for the project. This process is discussed

in more detail on page 10 under “Performance Objectives.” The second step uses an organized,

interactive process to select or develop analytical protocols to meet the specified analytical data

requirements and to demonstrate the protocols’ abilities to meet the analytical data requirements.

The third major step uses the analytical data requirements as measurement performance criteria

for the ongoing and final evaluation of the laboratory data, including data verification, data

validation, and data quality assessment (page 11). Within the constraints of other factors, such as

cost, a performance-based approach allows for the use of any analytical protocol that meets the

project’s analytical data requirements. For all relevant project activities, the common theme of a

performance-based approach is the use of project-specific analytical data requirements that are

developed during project planning and serve as measurement performance criteria for selections,

evaluations, and decisionmaking.

Analytical Process

Most environmental data

collection efforts center around

two major processes: the sampling

process and the analytical process.

MARLAP does not provide

guidance on the sampling process,

except for brief discussions of

certain activities that often affect

the analytical process (field

processing, preservation, etc.).

The analytical (or measurement)

process is a general term used by

MARLAP to refer to a

compilation of activities starting

from the time a sample is

collected and ending with the

reporting of data. Figure 2

illustrates the major components

of an analytical process. A

particular analytical process for a

project may not include all of the

activities listed. For example, if a

project involves the analysis of
MARLAP Executive Summary

JULY 2004 7 MARLAP

tritium in drinking water, then the analytical process for the project will not include sample

dissolution and the chemical separation of the radionuclide of concern. It is important to identify

the relevant activities of the analytical process for a particular project early in the planning phase.

Once the activities have been identified, the analytical requirements of the activities can be

established, which will ultimately lead to defining how the activities will be accomplished

through the selection or development of written procedures. 

Analytical Protocol 

MARLAP uses the term “analytical protocol” to refer to a compilation of specific procedures and

methods that are performed in succession for a particular analytical process. For example, a

protocol for the analysis of drinking water samples for tritium would be comprised of the set of

procedures that describe the relevant activities, such as sample tracking, quality control, field

sample preparation and preservation, sample receipt and inspection, laboratory sample preparation (if necessary), preparing the samples for counting, counting the samples, and data reduction

and reporting. A written procedure may cover one or more of the activities, but it is unlikely that

a single procedure will cover all of the activities of a given analytical process. With a performance-based approach, there may be a number of alternative protocols that might be appropriate

for a particular analytical process. Selecting or developing an analytical protocol requires

knowledge of the particular analytical process, as well as an understanding of the analytical data

requirements developed during the project planning phase.

Analytical Method 

A major component of an analytical protocol is the analytical method, which normally includes

written instructions for sample digestion, chemical separation (if required), and counting. It is

recognized that in many instances the analytical method may cover many of the activities of a

particular analytical process. Therefore attention is naturally focused on the selection or

development of an analytical method. However, many analytical methods do not address

activities such as field preparation and preservation, certain aspects of laboratory preparation,

laboratory subsampling, etc., which are often important activities within an analytical process.

The analytical protocol is generally more inclusive of the activities that make up the analytical

process than the analytical method.

Uncertainty and Error

An important aspect of sampling and measurement is uncertainty. The term “uncertainty” has

different shades of meaning in different contexts, but generally the word refers to a lack of

complete knowledge about something of interest. In the context of metrology (the science of

measurement), the more specific term “measurement uncertainty” often will be used. “Uncertainty (of measurement)” is defined in the Guide to the Expression of Uncertainty in Measurement

(ISO 1995—“GUM”) as a “parameter, associated with the result of a measurement, that charac-
MARLAP Executive Summary

MARLAP 8 JULY 2004

terizes the dispersion of values that could reasonably be attributed to the measurand.” The

“measurand” is the quantity being measured. MARLAP recommends the terminology and

methods of GUM for describing, evaluating, and reporting measurement uncertainty. The

uncertainty of a measured value is typically expressed as an estimated standard deviation, called

a “standard uncertainty” (or “one-sigma uncertainty”). The standard uncertainty of a calculated

result usually is obtained by propagating the standard uncertainties of a number of other

measured values, and in this case, the standard uncertainty is called a “combined standard

uncertainty.” The combined standard uncertainty may be multiplied by a specified factor called a

“coverage factor” (e.g., 2 or 3) to obtain an “expanded uncertainty” (a “two-sigma” or “threesigma” uncertainty), which describes an interval about the result that can be expected to contain

the true value with a specified high probability. MARLAP recommends that either the combined

standard uncertainty or an expanded uncertainty be reported with every result. Chapter 19

discusses the terminology, notation, and methods of GUM in more detail and provides guidance

for applying the concepts to radioanalytical measurements.

While measurement uncertainty is a parameter associated with an individual result and is

calculated after a measurement is performed, MARLAP uses the term “method uncertainty” to

refer to the predicted uncertainty of a measured value that likely would result from the analysis of

a sample at a specified analyte concentration. Method uncertainty is a method performance

characteristic much like the detection capability of a method. Reasonable values for both

characteristics can be predicted for a particular method based on typical values for certain

parameters and on information and assumptions about the samples to be analyzed. These

predicted values can be used in the method selection process to identify the most appropriate

method based on a project’s data requirements. Chapter 3 provides MARLAP’s recommendations for deriving analytical protocol selection criteria based on the required method uncertainty

and other analytical requirements.

When a decisionmaker bases a decision on the results of measurements, the measurement

uncertainties affect the probability of making a wrong decision. When sampling is involved,

sampling statistics also contribute to the probability of a wrong decision. Because decision errors

are possible, there is uncertainty in the decisionmaking process. MARLAP uses the terms

“decision uncertainty” or “uncertainty of the decision” to refer to this type of uncertainty.

Decision uncertainty is usually expressed as the estimated probability of a decision error under

specified assumptions. Appendix B discusses decision uncertainty further in the context of the

DQO process.

A concept that should not be confused with uncertainty is error. In general, error refers to

something that deviates from what is correct, right or true. In terms of measurements such as

laboratory analyses, the difference between the measured result and the actual value of the

measurand is the error of the measurement. Because the actual value of the measurand is

generally not known, the measurement error cannot be determined. Therefore, the error of a

measurement is primarily a theoretical concept with little practical use. However, the
MARLAP Executive Summary

JULY 2004 9 MARLAP

measurement uncertainty, which provides an estimated bound for the likely size of the

measurement error, is very useful and plays a key role in MARLAP’s performance-based

approach.

Precision, Bias, and Accuracy

Analytical data requirements often have been described in terms of precision and bias. Precision

is usually expressed as a standard deviation, which measures the dispersion of measured values

about their mean. It is sometimes more natural to speak of “imprecision,” because larger values

of the standard deviation indicate less precision. MARLAP considers bias to be a persistent

difference between the measured result and the true value of the quantity being measured, which

does not vary if the measurement is repeated. If the measurement process is in statistical control,

then precision may be improved by averaging the results of many independent measurements of

the same quantity. Bias is unaffected by averaging (see Chapter 6).

A bias in a data set may be caused by measurement errors that occur in steps of the measurement

process that are not repeated, such as the determination of a half-life. Imprecision may be caused

by measurement errors in steps that are repeated many times, such as weighing, pipetting, and

radiation counting. However, distinguishing between bias and precision is complicated by the

fact that some steps in the process, such as instrument calibration or tracer preparation, are

repeated at frequencies less than those of other steps, and the measurement errors in seldom

repeated steps may affect large blocks of data. Consequently, measurement errors that produce

apparent biases in small data sets might adversely affect precision in larger data sets.

Because the same type of measurement error may produce either bias or precision, depending on

one’s point of view, the concept of measurement uncertainty, described on page 7, treats all types

of measurement error alike and combines estimates of their magnitudes into a single numerical

parameter (i.e., combined standard uncertainty). The concepts of precision and bias are useful in

context when a measurement process or a data set consisting of many measurement results is

considered. When one considers only a single measurement result, the concept of measurement

uncertainty tends to be more useful than the concepts of precision and bias. Therefore, it is

probably best to consider precision and bias to be characteristics of the measurement process or

of the data set, and to consider measurement uncertainty to be an aspect of each individual result.

Quality control samples are analyzed for the purpose of assessing precision and bias. Spiked

samples and method blanks are typically used to assess bias, and duplicates are used to assess

precision. Because a single measurement of a spike or blank cannot in principle distinguish

between precision and bias, a reliable estimate of bias requires a data set that includes many such

measurements.
MARLAP Executive Summary

MARLAP 10 JULY 2004

Different authors have given the word accuracy different technical definitions, expressed in

terms of bias and precision. MARLAP avoids all of these technical definitions and uses the term

“accuracy” in its common, ordinary sense, which is consistent with its definition in the

International Vocabulary of Basic and General Terms in Metrology (ISO, 1993). In MARLAP’s

terminology, the result of a measurement is “accurate” if it is close to the true value of the

quantity being measured. Inaccurate results may be caused either by bias or precision in the

measurement process.

While it is recognized that the terms bias, precision, and accuracy are commonly used in data

collection activities, these terms are used somewhat sparingly in this manual. MARLAP

emphasizes and provides guidance in the use of measurement uncertainty as a means of

establishing analytical data requirements and in the evaluation of single measurement results.

Performance Objectives: Data Quality Objectives and Measurement Quality Objectives

One of the outputs of a directed planning process is DQOs for a project or program. DQOs are

qualitative and quantitative statements that clarify the study objectives, define the most

appropriate type of data to collect, determine the most appropriate conditions from which to

collect the data, and specify tolerable limits on decision error rates (ASTM D5792; EPA, 2000).

DQOs apply to all data collection activities associated with a project or program, including

sampling and analysis. In particular, DQOs should encompass the “total uncertainty” resulting

from all data collection activities, including analytical and sampling activities.

From an analytical perspective, a process of developing the analytical data requirements from the

DQOs of a project is essential. These analytical data requirements serve as measurement performance criteria or objectives of the analytical process. MARLAP refers to these performance

objectives as “measurement quality objectives” (MQOs). The MARLAP Manual provides

guidance on developing the MQOs from the overall project DQOs (Chapter 3). MQOs can be

viewed as the analytical portion of the DQOs and are therefore project-specific. MARLAP

provides guidance on developing MQOs during project planning for select method performance

characteristics, such as method uncertainty at a specified concentration; detection capability;

quantification capability; specificity, or the capability of the method to measure the analyte of

concern in the presence of interferences; range; ruggedness, etc. An MQO is a statement of a

performance objective or requirement for a particular method performance characteristic. Like

DQOs, MQOs can be quantitative and qualitative statements. An example of a quantitative MQO

would be a statement of a required method uncertainty at a specified radionuclide concentration,

such as the action level—i.e., “a method uncertainty of 3.7 Bq/kg (0.10 pCi/g) or less is required

at the action level of 37 Bq/kg (1.0 pCi/g).” An example of a qualitative MQO would be a

statement of the required specificity of the analytical protocol—the ability to analyze for the

radionuclide of concern given the presence of interferences—i.e., “the protocol must be able to

quantify the amount of 226Ra present given high levels of 235U in the samples.” 
MARLAP Executive Summary

JULY 2004 11 MARLAP

The MQOs serve as measurement performance criteria for the selection or development of

analytical protocols and for the initial evaluation of the analytical protocols. Once the analytical

protocols have been selected and evaluated, the MQOs serve as criteria for the ongoing and final

evaluation of the laboratory data, including data verification, data validation, and data quality

assessment. In a performance-based approach, analytical protocols are either selected or rejected

for a particular project, to a large measure, based on their ability or inability to achieve the stated

MQOs. Once selected, the performance of the analytical protocols is evaluated using the projectspecific MQOs. 

Analytical Protocol Specifications

MARLAP uses the term “analytical protocol specifications” (APSs) to refer to the output of a

directed planning process that contains the project’s analytical data requirements in an organized,

concise form. In general, there will be an APS developed for each analysis type. These

specifications serve as the basis for the evaluation and selection of the analytical protocols that

will be used for a particular project. In accordance with a performance-based approach, the APSs

contain only the minimum level of specificity required to meet the project’s analytical data

requirements without dictating exactly how the requirements are to be met. At a minimum, the

APSs should indicate the analyte of interest, the matrix of concern, the type and frequency of

quality control (QC) samples, and provide the required MQOs and any specific analytical process

requirements, such as chain-of-custody for sample tracking. In most instances, a particular APS

document would be a one-page form (see Chapter 3, Figure 3.2). Depending on the particular

project, a number of specific analytical process requirements may be included. For example, if

project or process knowledge indicates that the radionuclide of interest exists in a refractory

form, then the APSs may require a fusion step for sample digestion.

Within the constraints of other factors, such as cost, MARLAP’s performance-based approach

allows the use of any analytical protocol that meets the requirements in the APSs. The APSs—in

particular the MQOs—are used to select and evaluate the analytical protocols. Once the

analytical protocols have been selected and evaluated, the APSs then serve as criteria for the

ongoing and final evaluation of the laboratory data, including data verification, data validation,

and data quality assessment. 

The Assessment Phase

The MARLAP Manual provides guidance for the assessment phases for those projects that

require the laboratory analysis of radionuclides. The guidance on the assessment phase of

projects focuses on three major activities: data verification, data validation, and data quality

assessment.

Data verification assures that laboratory conditions and operations were compliant with the

statement of work and any appropriate project plan documents (e.g., Quality Assurance Project
MARLAP Executive Summary

MARLAP 12 JULY 2004

Plan), which may reference laboratory documents such as laboratory standard operating

procedures. Verification compares the material delivered by the laboratory to these requirements

(compliance) and checks for consistency and comparability of the data throughout the data

package, correctness of calculations, and completeness of the results to ensure that all necessary

documentation is available. The verification process usually produces a report identifying which

requirements are not met. The verification report may be used to determine payment for

laboratory services and to identify problems that should be investigated during data validation.

Verification works iteratively and interactively with the generator (i.e., laboratory) to assure

receipt of all available, necessary data. Although the verification process identifies specific

problems, the primary function should be to apply appropriate feedback resulting in corrective

action improving the analytical services before the work is completed.

Validation addresses the reliability of the data. The validation process begins with a review of the

verification report and laboratory data package to screen the areas of strength and weakness of

the data set. The validator evaluates the data to determine the presence or absence of an analyte

and the uncertainty of the measurement process for contaminants of concern. During validation,

the technical reliability and the degree of confidence in reported analytical data are considered.

Validation “flags” (i.e., qualifiers) are applied to data that do not meet the acceptance criteria

established to assure data meet the needs of the project. The product of the validation process is a

validation report noting all data sufficiently inconsistent with the validation acceptance criteria in

the expert opinion of the validator. The appropriate data validation tests should be established

during the project planning phase.

Data quality assessment (DQA), the third and final step of the assessment phase, is defined as the

“scientific and statistical evaluation of data to determine if data are of the right type, quality, and

quantity to support their intended use.” DQA is more global in its purview than the previous

verification and validation steps. DQA, in addition to reviewing the issues raised during verification and validation, may be the first opportunity to review other issues, such as field activities

and their impact on data quality and usability. DQA should consider the combined impact of all

project activities in making a data usability determination, which is documented in a DQA report.

The MARLAP Process

An overarching objective of the MARLAP Manual is to provide a framework and information

for the selection, development, and evaluation of analytical protocols and the resulting laboratory

data. The MARLAP process is a performance-based approach that develops APSs and uses these

requirements as criteria for the analytical protocol selection, development and evaluation

processes, and for the evaluation of the resulting laboratory data. This process, which spans the

three phases of the data life cycle for a project—planning, implementation and assessment—is

the basis for achieving MARLAP’s basic goal of ensuring that radioanalytical data will meet a
MARLAP Executive Summary

JULY 2004 13 MARLAP

project’s data requirements. A brief overview of this process, which is referred to as the

MARLAP process and is the focus of Part I of the manual, is provided below.

The MARLAP process starts with a directed planning process. Within a directed planning

process, key analytical issues based on the project’s particular analytical processes are discussed

and resolved. The resolution of these key analytical issues produces the APSs, which include the

MQOs. The APSs are documented in project plan documents (e.g., Quality Assurance Project

Plans, Sampling and Analysis Plans). A SOW is then developed that contains the APSs. The

laboratories receiving the SOW respond with proposed analytical protocols based on the requirements of the APSs and provide evidence that the proposed protocols meet the performance

criteria in the APSs. The proposed analytical protocols are initially evaluated by the project

manager or designee to determine if they will meet the requirements in the APSs. If the proposed

analytical protocols are accepted, the project plan documents are updated by the inclusion or

referencing of the actual analytical protocols to be used. During analyses, resulting sample and

QC data will be evaluated primarily using MQOs from the respective APSs. Once the analyses

are completed, an evaluation of the data will be conducted, including data verification, data

validation, and data quality assessment with the respective MQOs serving as criteria for

evaluation. The role of the APSs (particularly the MQOs, which make up an essential part of the

APSs) in the selection, development, and evaluation of the analytical protocols and the laboratory

data is to provide a critical link between the three phases of the data life cycle of a project. This

linkage helps to ensure that radioanalytical laboratory data will meet a project’s data requirements, and that the data are of known quality appropriate for their intended use. The MARLAP

process is illustrated in Figure 3. Although the diagram represents the MARLAP process in a

linear fashion, it is important to note that the process is an iterative one, and there can be many

variations on this stylized diagram. Also, the phases shown at the right of Figure 3 only illustrate

the relationship of the MARLAP process to the data life cycle.

Structure of the Manual

MARLAP is divided into two main parts. Part I provides guidance on implementing the

MARLAP process as described in the previous section. This part of the manual focuses on the

sequence of steps involved when using a performance-based approach for projects requiring

radioanalytical laboratory work starting with a directed planning process and ending with DQA.

Part I provides the overall guidance for using a performance-based approach for all three phases

of a project. A more detailed overview of Part I is provided on page 15. While the primary users

for most of the Part I chapters are project managers and planners, other groups can benefit from

the guidance in Part I. 
MARLAP Executive Summary

MARLAP 14 JULY 2004

Directed Planning Process (Chapter 2)

• Key Analytical Issues (Chapter 3)

• Development of Analytical Protocol Specifications

• Includes MQOs (Chapter 3)

Develop Plan Documents That Incorporate

Analytical Protocol Specifications (Chapter 4)

(e.g., QAPP, SAP, Data Validation Plan)

Laboratory Responds with Analytical Protocols

(Chapter 6)

• Selected to Meet Requirements of Analytical Protocol Specifications

• Performance Data Provided

Initial Evaluation of Analytical Protocols and Laboratory

(Chapter 7)

• Review of Performance Data

• Performance Evaluation (PE) Samples/Certified Reference

Materials (CRMs) Analyzed

• Quality Systems Audit

Protocols

Rejected

Development of SOW (Chapter 5)

• Includes Analytical Protocol Specifications (MQOs)

Corrective

Actions

Update Plan Documents

(Chapter 4)

• Include or Reference Accepted Analytical Protocols

Start Analysis of Samples

Protocols Accepted

Ongoing Evaluation of Laboratory Performance

(Chapter 7)

• Evaluation of QC and PE Sample Results

• Laboratory Audits

• Evaluation of Sample-Specific Parameters (i.e., yield)

Analyses Completed

Data Evaluation and Assessment

• Data Verification (Chapter 8)

• Data Validation (Chapter 8)

• Data Quality Assessment (Chapter 9)

Data of Known Quality for Decision Making

Project Manager

Project Planning Team

Assessment

Phase

Implementation

Phase

Planning

Phase

FIGURE 3 — The MARLAP process
MARLAP Executive Summary

JULY 2004 15 MARLAP

Part II of the manual provides information on the laboratory analysis of radionuclides to support

a performance-based approach. Part II provides guidance and information on the various

activities performed at radioanalytical laboratories, such as sample preparation, sample

dissolution, chemical separations, preparing sources for counting, nuclear counting, etc. The

primary users for Part II are laboratory personnel. Using the overall framework provided in Part I,

the material in Part II can be used to assist project planners, managers, and laboratory personnel

in the selection, development, evaluation, and implementation of analytical protocols for a

particular project or program. Figure 4, the MARLAP roadmap on page 16, illustrates the

interaction of the project manager and the laboratory using key MARLAP terms and processes

(roadmap). A more detailed overview of Part II is provided on page 17. In addition to Part I and

Part II, MARLAP has several appendices that support both Part I and Part II of the manual. An

overview of the appendices is provided on page 18.

Because of the structure and size of the manual, most individuals will naturally focus on those

chapters that provide guidance in areas directly related to their work. Therefore, to help ensure

that key concepts are conveyed to the readers, there is some material is repeated, often in very 

similar or even the same language, throughout the manual.

Overview of Part I

Figure 3, the MARLAP Process on page 14, illustrates the sequence of steps that make up a

performance-based approach for the planning, implementation, and assessment phases of

radioanalytical projects. The chapters of Part I closely track this sequence:

• Chapter 1, Introduction to MARLAP, is substantially the same as this Executive Summary.

• Chapter 2, Project Planning Process, provides an overview of the directed planning process

and its outputs.

• Chapter 3, Key Analytical Planning Issues and Developing Analytical Protocol Specifications, describes key analytical planning issues that need to be addressed during a directed

planning process and provides guidance on developing APSs, which are outputs of the

planning process. 

• Chapter 4, Project Plan Documents, provides guidance on the linkage between project

planning and project plan documents, with an overview of different types of project plan

documents (e.g., work plans, quality assurance project plans, sampling and analysis plans).

• Chapter 5, Obtaining Laboratory Services, provides guidance on developing a statement of

work that incorporates the APSs. 
MARLAP Executive Summary

MARLAP 16 JULY 2004

FIGURE 4 — Key MARLAP terms and processes (roadmap)
MARLAP Executive Summary

JULY 2004 17 MARLAP

• Chapter 6, Selection and Application of an Analytical Method, provides guidance on selecting

or developing analytical protocols that will meet the MQOs and other requirements as

outlined in the APSs. Unlike the rest of Part I, this chapter is intended primarily for laboratory personnel, because under a performance-based approach, a laboratory may use any

protocol that meets the requirements of the APSs. (Other factors, such as cost, also will

influence the selection of analytical protocols.)

• Chapter 7, Evaluating Methods and Laboratories, provides guidance on the initial and

ongoing evaluation of analytical protocols and also provides guidance on the overall

evaluation of radioanalytical laboratories. 

• Chapter 8, Radiochemical Data Verification and Validation, provides an overview of the data

evaluation process, provides general guidelines for data verification and validation, and

provides “tools” for data validation. 

• The last chapter of Part I, Chapter 9, Data Quality Assessment, discusses data quality

assessment and provides guidance on linking data quality assessment to the planning process.

Overview of Part II

The chapters in Part II are intended to provide information on the laboratory analysis of

radionuclides. The chapters provide information on many of the options available for analytical

protocols, and discuss common advantages and disadvantages of each. The chapters highlight

common analytical problems and ways to identify and correct them. The chapters also serve to

educate the reader by providing a detailed explanation of the typical activities performed at a

radioanalytical laboratory. Consistent with a performance-based approach, the chapters in Part II

do not contain detailed step-by-step instructions on how to perform certain laboratory tasks, such

as the digestion of a soil sample. The chapters do contain information and guidance intended to

assist primarily laboratory personnel in deciding on the best approach for a particular laboratory

task. For example, while the chapter on sample dissolution does not contain step-by-step

instructions on how to dissolve a soil sample, it does provide information on acid digestion,

fusion techniques, and microwave digestion, which is intended to help the reader select the most

appropriate technique or approach for a particular project.

The primary audience for Part II is laboratory personnel and the chapters generally contain a

significant amount of technical information. While the primary target audience is laboratory

personnel, other groups, such as project planners and managers, can benefit from the guidance in

Part II. Listed below are the chapters that make up Part II of the manual. It should be noted that

Part II of the manual does not provide specific guidance for some laboratory activities that are

common to all laboratories, such as laboratory quality assurance, and laboratory health and safety

practices. This is primarily due to the fact that these activities are not unique to radioanalytical

laboratories and considerable guidance in these areas already exists.
MARLAP Executive Summary

MARLAP 18 JULY 2004

Chapter 10 Field and Sampling Issues That Affect Laboratory Measurements

Chapter 11 Sample Receipt, Inspection, and Tracking

Chapter 12 Laboratory Sample Preparation

Chapter 13 Sample Dissolution

Chapter 14 Separation Techniques

Chapter 15 Quantification of Radionuclides

Chapter 16 Data Acquisition, Reduction, and Reporting for Nuclear Counting

Instrumentation

Chapter 17 Waste Management in a Radioanalytical Laboratory

Chapter 18 Laboratory Quality Control

Chapter 19 Measurement Uncertainty

Chapter 20 Detection and Quantification Capabilities

Chapters 10 through 16 provide information on the typical components of an analytical process

in the order in which activities that make up an analytical process are normally performed. While

not providing step-by-step procedures for activities such as sample preservation, sample

digestion, nuclear counting, etc., the chapters do provide an overview of options available for the

various activities and importantly, provide information on the appropriateness of the assorted

options under a variety of conditions. 

Chapter 17, Waste Management in a Radioanalytical Laboratory, provides an overview of many

of the regulations for waste disposal and provides guidance for managing wastes in a

radioanalytical laboratory. Chapter 18, Laboratory Quality Control, provides guidance on

monitoring key laboratory performance indicators as a means of determining if a laboratory’s

measurement processes are in control. The chapter also provides information on likely causes of

excursions for selected laboratory performance indicators, such as chemical yield, instrument

background, quality control samples, etc. 

Chapters 19, Measurement Uncertainty, and 20, Detection and Quantification Capabilities,

provide information on statistical principles and methods applicable to radioanalytical

measurements, calibrations, data interpretation, and quality control. Topics covered in the chapter

include detection and quantification, measurement uncertainty, and procedures for estimating

uncertainty.

Overview of the Appendices

Seven appendices provide additional details on specific topics discussed in Part I and Part II

chapters. Appendices A through E primarily support Part I chapters (project planning issues) and

Appendices F and G primarily support the chapters in Part II (laboratory implementation issues).

• Appendix A, Directed Planning Approaches, provides an overview of a number of directed

planning processes and discusses some common elements of the different approaches.
MARLAP Executive Summary

JULY 2004 19 MARLAP

• Appendix B, The Data Quality Objectives Process, provides an expanded discussion of the

Data Quality Objectives Process including detailed guidance on setting up a “gray region”

and establishing tolerable decision error rates.

• Appendix C, Measurement Quality Objectives for Method Uncertainty and Detection and

Quantification Capability, provides the rationale and guidance for developing MQOs for

select method performance characteristics.

• Appendix D, Content of Project Plan Documents, provides guidance on the appropriate

content of plan documents.

• Appendix E, Contracting Laboratory Services, contains detailed guidance on contracting

laboratory services.

• Appendix F, Laboratory Subsampling, provides information on improving and evaluating

laboratory subsampling techniques.

• Appendix G, Statistical Tables, provides a compilation of statistical tables.

References

American Society for Testing and Materials (ASTM) D5792. Standard Practice for Generation

of Environmental Data Related to Waste Management Activities: Development of Data

Quality Objectives, 1995.

International Organization for Standardization (ISO). 1993. International Vocabulary of Basic

and General Terms in Metrology. ISO, Geneva, Switzerland.

International Organization for Standardization (ISO). 1995. Guide to the Expression of

Uncertainty in Measurement. ISO, Geneva, Switzerland.

MARSSIM. 2000. Multi-Agency Radiation Survey and Site Investigation Manual, Revision 1.

NUREG-1575 Rev 1, EPA 402-R-97-016 Rev1, DOE/EH-0624 Rev1. August. Available at

www.epa.gov/radiation/marssim/.

U.S. Environmental Protection Agency (EPA). 2000. Guidance for the Data Quality Objective

Process (EPA QA/G-4). EPA/600/R-96/055, Washington, DC. Available at www.epa.gov/

quality1/qa_docs.html.

BIBLIOGRAPHIC DATA SHEET

(See instructions on the reverse)

NRC FORM 335

(2-89)

NRCM 1102,

3201, 3202

U.S. NUCLEAR REGULATORY COMMISSION 1. REPORT NUMBER

 (Assigned by NRC, Add Vol., Supp., Rev.,

 and Addendum Numbers, if any.)

NUREG-1576, Supp. 1

DATE REPORT PUBLISHED

MONTH

July

YEAR

2004

4. FIN OR GRANT NUMBER

2. TITLE AND SUBTITLE

Multi-Agency Radiological Laboratory Analytical Protocols Manual (MARLAP)

Accompaniment to CD - Executive Summary (Roadmap)

5. AUTHOR(S) 6. TYPE OF REPORT

FINAL

7. PERIOD COVERED (Inclusive Dates)

8. PERFORMING ORGANIZATION - NAME AND ADDRESS (If NRC, provide Division, Office or Region, U.S. Nuclear Regulatory Commission, and mailing address; if contractor,

Department of Defense, Washington, DC 20301-3400 Food and Drug Administration, Rockville, MD 20857

9. SPONSORING ORGANIZATION - NAME AND ADDRESS (If NRC, type "Same as above"; if contractor, provide NRC Division, Office or Region, U.S. Nuclear Regulatory Commission, 

Same as above

provide name and mailing address.)

and mailing address.)

10. SUPPLEMENTARY NOTES

Rateb (Boby) Abu-Eid, NRC Project Manager

11. ABSTRACT (200 words or less)

The Multi-Agency Radiological Laboratory Analytical Protocols (MARLAP) manual provides guidance for the planning,

implementation, and assessment of projects that require the laboratory analysis of radionuclides. MARLAP's goal is to provide

guidance for project planners, managers, and laboratory personnel to ensure that radioanalytical laboratory data will meet a

project's or program's data requirements. The manual offers a framework for national consistency in the form of a

performance-based approach for meeting data requirements that is scientifically rigorous and flexible enough to be applied to a

diversity of projects and programs. The guidance in MARLAP is designed to help ensure the generation of radioanalytical data

of known quality, appropriate for its intended use. Examples of data collection activities that MARLAP supports include site

characterization, site cleanup and compliance demonstration, decommissioning of nuclear facilities, emergency response,

remedial and removal actions, effluent monitoring of licensed facilities, environmental site monitoring, background studies, and

waste management activities.

MARLAP is organized into two parts. Part I, Volume 1, is intended for project planners and managers, provides the basic

framework of the directed planning process as it applies to projects requiring radioanalytical data for decision making. Part II,

Volumes 2 and 3, is intended for laboratory personnel. Supplement 1 is the executive summary and roadmap to be distributed

with the CD containing the electronic versions of NUREG-1576.

12. KEY WORDS/DESCRIPTORS (List words or phrases that will assist researchers in locating the report.)

Multi-Agency Radiological Laboratory Analytical Protocols, MARLAP, radiological , laboratory, 

laboratory sample, analytical protocols, performance-based approach, planning, measurement, 

quality assurance, survey(s), decommissioning, statistics, waste management, 

radioanalytical laboratory services, data validation, data quality assessment, data collection

14. SECURITY CLASSIFICATION

13. AVAILABILITY STATEMENT

unlimited

(This Page)

unclassified

(This Report)

unclassified

15. NUMBER OF PAGES

16. PRICE

NRC FORM 335 (2-89) This form was electronically produced by Elite Federal Forms, Inc.

3.

Department of Energy, Washington, DC 20585-0119 National Institute of Standards and Technology, Gaithersburg, MD 20899

Department of Homeland Security, Washington, DC 20528 Nuclear Regulatory Commission, Washington, DC 20555-0001

Environmental Protection Agency, Washington, DC 20460-0001 U.S. Geological Survey, Reston, VA 20192