UNITED STATES ENVIRONMENTAL PROTECTION AGENCY
WASHINGTON, D.C. 20460
OFFICE OF
SOLID WASTE AND EMERGENCY RESPONSE
9355.0-7A
MEMORANDUM
SUBJECT: Guidance on Data Quality Objectives for the RI/FS Process
The attached document provides information for your use on
incorporating the development of Data Quality Objectives (DQOs)
into the RI/FS process. DQOs are qualitative and quantitative
statements specifying the quality of environmental data needed
to meet decision-making requirements for remedial alternatives.
As the document stands, it addresses primarily analytical DQO
requirements. A more comprehensive DQO document under develop-
ment will address both the analytical and sampling considerations
of the process. A draft of this next version is scheduled for
release in late July 1986 for comment, and will include a work-
book providing a site specific application of the DQO process.
Your use of the attached document in the interim will provide
initial insight on applying DQOs to the RI/FS process, which can
be reflected in your comments on the upcoming comprehensive DQO
document.
The document attached and the upcoming DQO document, are
considered supplemental guidance to the RI/FS guidance for sampling
plan development and quality control. In addition, the draft
Quality Assurance/Field Operations Methods Manual, which will be
the Agency's Standard Operating Procedures, is out for review
and comment. Together, these references should ensure that all
applicable parties have a thorough understanding of the RI/FS
process.
The document supercedes the draft document that was sent to
you for comment on November 5, 1985. Comments received on the
draft have been incorporated or responded to in this revised
version. Responses to some of the comments have been deferred
to the next version, which will address the sampling component of
the process and integrate the sampling and analytical components.
For your convenience in reviewing this document, a summary of
FROM:
Henry L. Longest II, Director
Office of Emergency and Remedia
Addressees
TO:
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9355.0-7A
the changes, which presents the original and revised text side
oy side, is attached. Editorial corrections are not included in
the summary if they did not change the meaning of the text.
Rl/FS projects in the past have complied with the intent of
DUO development through the development of sampling and analytical
plans. This report provides a process to formalize the approach
in developing DQOs. The primary responsibility of developing and
incorporating DQOs into Rl/FS activities lies with the Remedial
Project Manager (RPM), with technical support provided by the
Regional Quality Assurance Officer and other appropriate staff.
This document establishes guidelines to assist the RPM. These
guidelines should be adjusted to the extent necessary to take
into consideration site specific characteristics.
Please use this document freely in planning and implement-
ing your remedial investigations. Any comments or questions
that arise as you use the document can be directed to Randall
Kaltreider at (202) 382-2448 or Linda Boornazian at (202) 382-4830.
Attachment
Addressees:
Director, Waste Management Division, Regions I, IV, V, VI, VII,
and VIII
Director, Emergency and Remedial Response Division, Region II
Director, Hazardous Waste Management Division, Region III
Director, Toxics and Waste Management Division, Region IX
Director, Hazardous Waste Division, Region X
Director, Environuiental Services Division, Regions I-X
Stanley Blacker, QAM3 (RD-680)
Gene Lucero, OWPE (WH-527)
Steve Dorrler, ERT
Tim Fields, ERD (WH-548D)
Thomas P. Gallagher, ivIEIC
Allan Brown, (LE-132G)
Dan Berry, (LE-132S)
Dr. Vernon Houk, CDC
Steve Lingle, HRSD (WH-548A)
Jim Lounsbury, OERR (WH-548D)
Mark McClanahan, ATSDR
Barbara Simcoe, ASTSWMO
John Skinner, ORD (RD-681)
Frederick R. Stiehl, OECM (LE-134S)
Noel Urban, USACE
Marcia E. Williams, OSW (WH-562)
Craig Wolff, - OPPE (PM-220)
Gary Dunbar, CDM
Ken Brown, EMSL
Bill Dehn, CH2M HilL
Paul Goldstein, NUS
Michael Yates, EBASCO
Work Group Members
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DATA QUALITY OBJECTIVES FOR THE RI/FS PROCESS
Prepared for:
Office of Emergency and Remedial Response
Office of Waste Programs Enforcement
Office of Solid Waste and Emergency Response
U.S. Environmental Protection Agency
401 M Street, SW
Washington, DC 20460
Document No. 9355.0-7A
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Document No. 9355.0-7A
TABLE OF CONTENTS
Page
1.0 INTRODUCTION 1-1
1.1 DATA QUALITY OBJECTIVE BACKGROUND 1-2
1.2 THE RI/FS DQO PROCESS 1-3
2.0 STAGE ONE - DEFINITION OF PROGRAM OBJECTIVES 2-1
2.1 RI/FS OBJECTIVES 2-1
2.2 IMPLEMENTATION OF STAGE ONE 2-4
2.2.1 SPECIFY DECISION MAKING PROCESS 2-5
2.2.2 CLARIFY THE NEED FOR NEW DATA 2-7
2.2.3 IDENTIFY THE INTENDED USES OF THE DATA
TO BE COLLECTED 2-10
2.3 IDENTIFICATION OF RESOURCE CONSTRAINTS AND
SPECIAL REQUIREMENTS 2-13
3.0 STAGE TWO 3-1
3.1 STATE TWO A: ESTABLISHMENT OF ANALYTICAL DATA QUALITY
REQUIREMENTS 3-1
3.1.1 DISCUSSION 3-1
3.1.2 DATA QUALITY CRITERIA 3-7
3.1.3 OTHER ANALYTICAL CONSIDERATIONS 3-18
3.2 STAGE TWO B OF THE RI/FS PROCESS 3-25
4.0 STAGE THREE - SELECTION OF ANALYTICAL AND SAMPLING OPTIONS .... 4-1
4.1 ANALYTICAL OPTIONS 4-1
4.1.1 OVERVIEW OF ANALYTICAL SUPPORT LEVELS 4-2
4.1.2 NON-STANDARD METHODS - LEVEL NS ANALYTICAL
SUPPORT 4-3
4.1.3 CONTRACT LABORATORY PROGRAM (CLP) ROUTINE ANALYTICAL
SERVICES (RAS) INVITATION FOR BIDS (IFB) - LEVEL IV
ANALYTICAL SUPPORT 4-7
4.1.4 LABORATORY ANALYSIS - LEVEL III ANALYTICAL
SUPPORT 4-9
4.1.5 FIELD ANALYSIS - LEVEL II ANALYTICAL SUPPORT 4-14
4.1.6 FIELD SCREENING - LEVEL I ANALYTICAL SUPPORT 4-17
4.2 STAGE THREE B - DETERMINATION OF SAMPLING PLAN APPROACH .. 4-20
4.3 OUTPUT OF THE RI/FS DQO PROCESS 4-20
5.0 IMPLEMENTATION OF THE DQO PROCESS 5-1
5.1 CASE STUDY SCENARIO - XYZ SITE 5-1
5.1.1 SITE HISTORY AND WASTE DISPOSAL FEATURES 5-1
5.1.2 HYDROGEOLOGIC FEATURES 5-3
5.1.3 EXTENT OF CONTAMINATION 5-4
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TABLE OF CONTENTS
(Continued)
Page
5.1.4 CURRENT STATUS 5-7
5.1.5 DATA COLLECTION ACTIVITIES 5-7
5.2 SOURCE CHARACTERIZATION FOR REMOVAL 5-8
5.3 PUBLIC HEALTH EVALUATION/ENDANGERMENT ASSESSMENT 5-8
5.4 FS DESIGN/PILOT STUDY 5-8
5.4.1 AIR STRIPPING PILOT STUDY 5-10
5.4.2 STAGE ONE: DEFINITION OF PROGRAM OBJECTIVES
FOR THE AIR STRIPPING TREATMENT OPTION 5-11
5.4.3 STAGE TWO: ESTABLISHMENT OF DATA QUALITY
REQUIREMENTS 5-15
5.4.4 STAGE THREE: SELECTION OF ANALYTICAL SUPPORT
OPTIONS . 5-18
5.5 HEALTH AND SAFETY SITE CHARACTERIZATION 5-20
6.0 BIBLIOGRAPHY 6-1
APPENDIX A REVIEW OF QAMS OQO CHECKLIST
APPENDIX B POTENTIALLY APPLICABLE OR RELEVANT AND APPROPRIATE REQUIREMENTS
APPENDIX C PERFORMANCE CRITERIA FOR ORGANICS ANALYSIS
APPENDIX D ACCURACY DEFINITIONS
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LIST OF FIGURES
ease
1-1 RI/FS DQO Process 1-5
3-1 Integration of Analytical Support Levels 3-6
4-1 Integration of Analytical Support Levels 4-5
5-1 XYZ Site 5-2
LIST OF TABLES
page
1-1 Data Quality Objectives Checklist 1-7
2-1 RI/FS Objectives Applicable to Air, Surface Water, Soil,
Groundwater, and Biological Media 2-2
2-2 Intended Data Uses 2-12
3-1 Guidelines for Minimal QA/QC Samples for Field Sampling
Programs 3-9
4-1 Example Analytical Support Requirements for an RI/FS 4-4
4-2 Summary of Analytical Levels for RI/FS ........................ 4-5
4-3 SW 846 Accuracy, Precision, and MDL Information 4-11
4-4 Field Analytical Support Accuracy Information ................. 4-18
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PREFACE
This is one of a series of guidance documents for remedial investigation/
feasibility study activities under CERCLA, prepared in accordance with the
National Contingency Plan final rule, published in the Federal Register
November 20, 1985 and effective February 18, 1986. These guidance
documents have been prepared under the Office of Solid Waste And Emergency
Response (OSWER). The guidance document series includes the following
titles:
• Guidance on Remedial Investigations Under CERCLA (EPA 540/G-85/002)
• Guidance on Feasibility Studies Under CERCLA (EPA 540/G-85/003)
• Superfund Public Health Evaluation Manual (OSWER Directive 9285.4-1)
• Data Quality Objectives for the RI/FS Process (draft)
• Exposure Assessment Guidance
• Field Operating Procedures (in preparation)
This document, Data Quality Objectives for the RI/FS Process, is intended
to guide the user through the process of developing data quality objectives
(DQOs) for site-specific RI/FS activities. DQOs are qualitative and
quantitative statements specifying the quality of data required to support
RI/FS activities. Individual site characteristics make it impossible to
apply a generic set of DQOs to the whole Superfund program. Site-specific
DQOs must be developed based on the end uses of the data from sampling and
analytical activities.
Guidance on Remedial Investigations Under CERCLA and Guidance on
Feasibility Studies Under CERCLA were both issued in June 1985. These
documents provide direction for the planning, preparation, execution and
conclusion of RI/FS projects consistent with legislation and site-specific
requirements. Field Operating Procedures, currently in preparation, will
present detailed descriptions of the mechanics of data and information
collection during the RI/FS process.
Collectively, these documents will provide guidance for the development of
technically sound and cost-effective RI/FS projects which will support the
program goals of both the OERR and the OWPE. In addition, states and
private parties conducting RI/FS response activities will be able to use
these documents as guidance to ensure that their activities are consistent
with the intent of CERCLA.
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NOTE
Document No. 9355.0-7A
This document was compiled for the Office of Solid Waste and Emergency
Response. The major participants of the task force are listed below.
Linda Boornazian (Hazardous Site Control Division, GERR)
James Occhialini {Camp Dresser & McKee Inc.)
Paul Clay (NUS Corporation)
Mike Carter (Hazardous Response Support Division)
Duane Geuder (Hazardous Response Support Division)
Dennis Gagne (Region 1, Waste Management Division)
Edward Shoener (Region 3, Hazardous Waste Management Division)
Bill Bunn (Region 7, Environmental Services Division)
Michael Kosakowski (CERCLA Enforcement Division)
Dennisse Beauchamp (CERCLA Enforcement Division)
Gary Liberson (Lloyd Associates)
Technical editing was provided by Wendy Sydow of Camp Dresser & McKee Inc.
Contributions were also made from other EPA and contractor staff.
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Document No. 9355.U-7A
ACRONYMS
CERCLA Comprehensive Environmental Response, Compensation, and Liability
Act
CLP Contract Laboratory Program
DQO Data Quality Objective
EMSL-LV Environmental Monitoring and Support Laboratory - Las Vegas
ESD EPA Environmental Services Division
FIT Field Investigation Team
FS Feasibility Study
HSL Hazardous Substance List
MDL Method Detection Limit
NBS National Bureau of Standards
NCP National Contingency Plan
NEIC National Enforcement Investigation Center
NPL National Priorities List
PARCC Precision, Accuracy, Representativeness, Completeness,
Comparability
PRP Potential Responsible Party
QAMS Quality Assurance Management Staff
QAPP Quality Assurance Project Plan
RAS Routine Analytical Service
RI Remedial Investigation
RPM Remedial Project Manager - federal official designated by EPA or
another lead agency to coordinate,
monitor, or direct remedial or other
response activities under the NCP
(Section 300.6)
SAS Special Analytical Service
SRM Standard Reference Materials
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Document No. 9355.0-7A
1.0 INTRODUCTION
Data Quality Objectives (DQOs) are qualitative and quantitative statements
specifying the quality of environmental data required to support an Agency
decision. This document presents guidance on the development of DQOs for
RI/FS activities. DQOs are established prior to data collection and are
critical in developing a sampling and analytical plan consistent with
CERCLA program objectives. DQOs are developed to address the specific
requirements of individual sites and are based on the intended uses of the
data. They define:
• The level of risk that is acceptable for making an incorrect
decision based on the data
• The quality of data (resulting from sampling an analysis) required
to keep the level of risk at or below the acceptable level
The process of developing DQOs assures that a formal plan is developed
describing the level or extent of sampling and analysis required to produce
adequate data for evaluation of remedial alternatives for a site. In
actual practice to date, RI/FS projects conducted under CERCLA have
complied with the intent of the DQO process. DQOs have been incorporated
as parts of sampling/analytical plans, quality assurance/ quality control
project plans, work plans, or remedial action master plans. The purpose of
this guidance is to provide a more formal approach to DQO development in
the sampling/analytical plan to improve the overall quality and cost
effectiveness of data collection and analysis activities.
The variable nature of RI/FS activities precludes development of generic
DQOs for use throughout the Superfund program. This document is intended
to guide the user through the process of DQO development. Each site will
have a unique history, data availability, site characteristics, public and
institutional considerations, and other factors. Therefore, each site must
have a unique set of DQOs.
DQOs establish the total amount of uncertainty in the data that is
acceptable for each specific activity in the RI/FS. Total uncertainty
includes both sampling error and analytical measurement error. Thus, the
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DQO process for RI/FS consists of two major components: the analytical
component and the sampling component. The analytical component of the DQO
process results in specifying a cost-effective chemical analysis method
which, when integrated with the selected sampling design, will satisfy the
given objective(s). The sampling component of the DQO process involves
specifying a sampling plan including numbers, types, locations and level of
sampling quality control which, when integrated with the analytical
component, will provide data consistent with the DQOs. Both of these
components have inherent variables which affect the environmental data
collection process and are highly interdependent. Because these two
components must be considered together in the overall approach to
developing RI/FS DQOs, this document addresses both.
DQO statements are an integral part of site-specific sampling and
analytical plans. According to Guidance for Remedial Investigations Under
CERCLA (EPA 1985) the key components of sampling and analytical plans are
as follows:
• Sampling
- Background
- Evaluation of existing data
- Determination of analytes of interest
- Determination of sample types
- Determination of sampling locations and frequency
• Analytical/Quality Control
- Objectives of quality control
- Evaluation of types of data needed
- Required level of certainty
- Availability of data collection and assessment procedures that can
provide desired level of reliability cost effectively
- Data limitations
1.1 DATA QUALITY OBJECTIVE POLICY BACKGROUND
Mr. Alvin Aim, then Deputy Administrator of the EPA, in his memorandum of
May 24, 1984, to the Assistant Administrators (AAs), stated that one of the
most important steps in assuring the quality of environmental data is
through the process of development of DQOs. He requested active
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Document No. 9355.0-7A
participation of the AAs in the development gf DQOs during the stages in
which policy and guidance is crucial, and asked for identification and
scheduling of significant, ongoing environmental data collection
activities. The Quality Assurance Management Staff (QAMS) issued guidance
to assist the Agency in development of DQOs in October 1984. A checklist
for DQO review was then issued in a memorandum from Stan Blacker on April
3, 1985. Appendix A includes a comparison of this checklist with RI/FS DQO
requi rements.
The approach to developing and implementing DQOs for the RI/FS process has
been established by a DQO Task Force comprising technical personnel from
EPA Headquarters (OERR and OWPE), Regions 1, 3 and 7, and EPA remedial
contractors. The methodology used by the DQO Task Force involved applying
the guidance provided by QAMS to the RI/FS process. As stated above, the
intent of DQO implementation has typically been addressed by various
planning documents prepared during an RI/FS. The efforts of the Task Force
included identifying the elements of the DQO process within the RI/FS
planning documents and organizing them into a formal implementation
approach. The DQO development process presented in this document is based
on the best available information but is expected to be revised as
additional information becomes available.
1.2 THE RI/FS DQO PROCESS
The DQO process is designed to assure that all environmental data collected
in support of RI/FS objectives is consistent with the end use of the data.
DQOs are specified for each activity that involves the collection of
analytical data. DQOs are qualitative and quantitative statements which
specify the data collection objectives, the data quality required, and the
most appropriate sampling and analytical approach considering special
constraints or requirements.
DQO development is actually a dynamic process involving a series of
discussions among decision makers, project managers, technical staff,
health and safety staff, and enforcement personnel. Data collection
activities are composed of a sampling component and an analytical
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Document No. 9355.0-7A
component. As the two components are interrelated, overall data quality
cannot be specified unless both components are addressed. In light of this
fact, personnel such as environmental scientists, chemists, geologist/-
hydrogeologists, toxicologists field specialists, statisticians,
enforcement personnel, and others should interact with managers early in
the DQO process. DQOs are meant to be flexible to meet program needs.
Once DQOs are formulated for a site, any changes required should be
approved by the Remedial Project Manager (RPM). The RPM, as defined in the
NCP in Section 300.6 (Federal Register Vol. 50, No. 224), is the federal
official designated by EPA or another lead agency to coordinate, monitor,
or direct remedial or other response activities under the National
Contingency Plan. The RPM will serve as the decision maker for the RI/FS
DQO development process.
Figure 1-1 illustrates the three-phased approach to RI/FS DQOs.
A brief discussion of each stage is presented below:
• STAGE ONE - This is the most important stage of the DQO process. It
involves defining program objectives, identifying end-users of the
data and evaluating resource constraints which may require
restrictions or modifications to a data collection program. The
decision maker and all potential data users should be involved in
this stage. Stage One results in a specification of the decision
making process and an understanding of why new data are needed.
Stage One is common to both the analytical and sampling components
of the DQO process.
• STAGE TWO-A - This stage results in the stipulation of the limits on
total uncertainty acceptable to the decision maker with respect to
conclusions drawn from the data. Although conducted simultaneously
with Stage Two-B, this stage is discussed as a discrete step in the
analytical component of the RI/FS DQO process. This stage involves
specifying the level of analytical data certainty sufficient to meet
the objectives specified in Stage One. Stages Two-A and Two-B must
be integrated so that uncertainty (including sampling and analytical
error) will be within limits that are acceptable to the RPM.
• STAGE TWO-B - Although conducted simultaneously with Stage Two-A,
this stage is discussed as a discrete step in the sampling component
of an RI/FS DQO. This stage involves a consideration of sampling
approaches and specification of the universe of interest, criteria
for decision making, and limits of acceptable sampling error.
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STAGE ONE
-DEFINE PROGRAM OBJECTIVES
- SPECIFY THE DECISION MAKING PROCESS
CLARIFY NEED FOR NEW DATA
• IDENTIFY AND PRIOFiTtZE OATA USES
-INVOLVE DATA USERS
-EVALUATE RESOURCE CONTRACTS
I
SPECIFY LEVELS OF TOTAL
UNCERTAINTY ACCEPTABLE TO
THE DECISION-MAKER
ANALYTICAL COMPONENT
SAMPLING COMPONENT
STAGE TWO-A
STAGE TWO-B
DEFINE LEVEL OF ANALYTICAL CERTAINTY
REQUIRES BY:
-SPECIFYING GENERAL USE CATEGORY
-SPECIFYfNG QUANTITATIVE ACCURACY/PRECISION
-SPECIFYING REQUIRED DETECTION LIMITS
-EV ALUATING USE 0 F MU L TI PL E-LE V E L
ANALYTICAL A PRO A C M
OSFINE LEVEL OF SAMPLING CERTAINTY REQUIRED BY:
-SPECIFYING AREAS AND CONTAMINANTS
OF CONCERN/RATIONALE
-SPECIFYING CRITERIA FOR DECISION MAKING
-EVALUATING SAMPLING APPROACHES
E.G. GRIDS. RANDOM. ETC
r >
* INTEGRATION "
STAGE THREE-A — STAGE THREE-B
TOTAL UNCERTAINTY MUST SE WITHIN
-SELECT ANAYLTICAL OPTIONtSl ACCEPTABLE LIMITS SET BY DECISION-MAKER -SELECT SAMPLING APPROACH
IF HOT. RETURN TO
STAGE ONE
OUTPUT
SAMPLING ANO ANALYTICAL PLAN
INCLUDING DOO STATEMENTS
Figure 1-1 RI/FS DQO Process
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Document No. 9355.0-7A
Stages Two-A and Two-B must be integrated so that total uncertainty
(including sampling and analytical error) will be within limits that
are acceptable to the RPM.
• STAGE THREE-A - This stage involves the actual selection of the
analytical option and evaluation of the use of a multiple-option
approach to effect a more timely or cost-effective program. Of
utmost importance is the integration of this stage and Stage
Three-B. The goal of the integration process is the selection of
compatible analytical and sampling approaches. Section 3.1 and 3.5
of this report present more detailed discussions on the selection of
analytical options and the use of a multiple analytical option
approach.
• STAGE THREE-B - This stage involves the selection of the sampling
approach to be employed. As stated above, integration with Stage
Three-A is of utmost importance to ensure compatibility with the
analytical option(s). In some cases, the use of the multiple-option
approach for analytical support will facilitate the optimum sampling
approach desired. Section 3.2 is reserved for this discussion.
• OUTPUT - The common output of the DQO process is a well-defined
sampling and analytical plan comprised of DQO statements for each
data collection activity of the RI/FS.
Table 1-1 is a DQO checklist for data users.
The DQO development process is described in detail in the following
sections. Section 2.0 describes Stage One of the process. Section 3.0
describes Stage Two of the process, including sampling and analytical
components, as well as data quality criteria. Section 4.0 describes Stage
Three of the process, including sampling and analytical options,
integration and output of the process. Section 5.0 presents a case study
scenario illustrating the DQO process for selected RI/FS activities.
Appendix A is a review of the QAMS DQO checklist, Appendix B is an excerpt
from the NCP on potentially applicable or relevant and appropriate
requirements, Appendix C includes performance criteria for organics
analysis, and Appendix D presents accuracy definitions.
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TABLE 1-1
DATA QUALITY OBJECTIVES CHECKLIST
STAGE ONE^ Definition of Program Objectives
- Specify decision making process
- Clarify need for new data
- Identify and involve all data users
- List and prioritize the intended uses of the data
- Identify all resource constraints and special requirements
STAGE TWO A: Establishment of Data Quality Requirements
- Specify levels of total uncertainty in the conclusions acceptable to
the decision maker
- Specify the criteria to be used in decision making based on the data
- Specify data quality requirements by general use category, or
specific accuracy and precision information subject to the limits on
total uncertainty
- Address the precision, accuracy, representativeness, completeness,
and comparability (PARCC) parameters and any additional
considerations
- Evaluate the simultaneous use of multiple levels of sampling and
analytical support
STAGE TWO B: To be added
STAGE THREE A: Selection of Analytical Support Options
- Stages Three-A and Three-B should be integrated so that sampling and
analytical options are specified as part of a single desing
- For each design considered, state the anticipated limitations of the
data in relation to the program objectives
- Specify the appropriateness of analytical support, including all
modi fications
STAGE THREE B: - To be added
OUTPUT OF THE RI/FS DQO PROCESS
- Detailed sampling and analytical plan
Note: Stages Two and Three can be interactive.
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2.0 STAGE ONE - DEFINITION OF PROGRAM OBJECTIVES
2.1 RI/FS OBJECTIVES
The overall objective of a remedial investigation/feasibility study (RI/FS)
is to determine the nature and extent of the threat posed by the release of
hazardous substances and to evaluate proposed remedies. The ultimate goal
is to select a cost-effective remedial alternative which mitigates threats
to and provides protection of public health, welfare, and the environment.
This selection process must be consistent with the NCP.
Although the major data collection process occurs during the RI, both the
RI and FS objectives must be taken into consideration. The RI/FS process
typically addresses data collection and site characterization from the
perspective of contaminant source and contaminant migration pathways. Once
pathways are established, the human and environmental receptors can be
identified, further data collection efforts can be directed toward
evaluating the potential impact upon receptors, and potential remedial
technologies and alternatives can be evaluated.
Table 2-1 lists general RI/FS objectives which are applicable to both
contaminant sources and pathways. Each objective identified in Table 2-1
usually requires some environmental data in order to answer questions
implied by the objective. The list of RI/FS activities helps to further
clarify the ways in which environmental data collected during an RI/FS will
be used.
Problem/Site Characterization
Initial field activities should establish the contaminants of concern and
which environmental media have been contaminated. Existing and potential
pathways of contaminant migration should also be identified. This
characterization is often performed in several stages of field investiga-
tion, each having more refined objectives.
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Document No. 9355.Q-7A
TABLE 2-1
General RI/FS Objectives
Applicable to Waste, Air, Surface Mater, Soil, Ground Water, and Biological Media
Objective
RI
Act i v i ty
FS
Activity
Determine presence or absence
of contaminants
- Determine types of contaminants
Determine quantities (concentrations)
of contaminants
Determine mechanism of contaminant
release to pathways
Determine direction of pathway(s)
transport
Determine boundaries of source(s)
and pathways
Determine environmental/public
health factors
Determine source/pathway contaminant
characteristics with respect to
mitigation (bench studies)
- Establish presence/absence of
contaminants at source and in
all pathways.
- Establish "nature" of contaminants
at source and in pathways; relate
contaminants to PRP-cost recovery
- Establish concentration gradients
Establish mechanics of source/
pathway(s) interface
Establish pathway(s)/transport
route(s), Identify potential
receptor(s)
Establish horizontal/vertical
boundaries of source(s) and
pathway(s) of contamination
Establish routes of exposure,
and environmental and public
health threat
Establish range of contaminants/
concentrations
Evaluate applicability of no action alternative
for source areas/pathways.
Evaluate environinental/public health threat;
identify applicable remedial technologies.
Evaluate costs to achieve relevant/applicable
standards
Evaluate effectiveness of containment
technologies
Identify most effective points in
pathway to control transport of
contaminants
Evaluate costs to achieve relevant/applicable
standards; identify applicable remedial
technologies
Evaluate applicable standards or risk; identify
applicable remedial technologies
Evaluate treatment schemes
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The determination of which media have been contaminated should also address
the contamination of the different strata or other components of each
medium. That is, each contaminated geological strata should be identified,
and each contaminated layer of a layered aqueous system should be
identi fied.
In addition to identifying the contaminated media, the investigation should
determine the mechanisms and pathways by which the contaminants migrate.
The site characterization should identify the specific contaminants, their
concentrations, quantities, and physical states. Often only a few, or
several specific contaminants, will play a large role in determining the
overall remedy. These substances are called indicator parameters. Usually
indicator parameters "represent" groups of substances; however in this
usage, indicators mean a small set of substances which by reason of their
large volume, high toxicity, difficulty of treatment or mobility determine
the overall remedy and/or degree of contamination. With regard to
indicator parameters, it should be noted that since certain contaminants
may exhibit differences in their environmental fate and transport and
varying degrees of toxicity in different environmental media, indicator
parameters may need to be different for different media. It is important
that other substances be identified and related to the indicator parameters
when possible. Further, the physical state of the contaminants (i.e.,
liquid, gas, etc.) is important in determining the risks imposed by various
exposure routes. The transformation of these substances, and the resulting
exposure and effects upon surrounding populations should be carefully
examined. All potentially exposed populations and the duration, extent or
nature of their exposure as a result of each potential remedial scenario
should be determined.
Identify Potential Remedies
Potential remedial technology types are identified and evaluated based on
current site information in order to focus the further gathering of site
information. Those that prove difficult to Implement, rely upon unproven
techniques, or which may not achieve remedial objectives within a
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reasonable time period are eliminated from further consideration. This
screening process focuses on site and waste characteristics which determine
the feasibility of remedial technologies or the potential for application
of innovative technologies.
Determine the Effectiveness of Remedial Alternatives
Once potential remedial technologies have been identified and combined (if
appropriate) into comprehensive remedial alternatives, data should be
developed to characterize fully the performance of the technologies under
the specific site conditions. These additional data should be sufficient
to allow a conceptual design of the process and to allow a cost estimate
with an accuracy of -30 to +50 percent. Such information may be obtained
as a result of field investigation or may require bench and/or pilot-scale
investigations. Objectives of these programs address the performance of
the remedial technologies and differ in form from the objectives of the
remedial field investigation, which address the characterization of current
environmental conditions. It is important to identify and understand the
design parameters associated with each potential remedial alternative.
This information can then be used to identify data that are needed in order
to generate performance estimates with a confidence level acceptable to the
decision maker (e.g., the +50%, -30% level associated with cost estimates
in the RI/FS). These data can be collected and evaluated concurrent with
the RI.
2.2 IMPLEMENTATION OF STAGE ONE
In a broad sense, the objective of an RI/FS is to determine the nature and
extent of the threat posed by the release of hazardous substances and to
evaluate proposed remedies. Achieving this broad objective requires that
several complicated and interrelated activities be performed, each having
its own particular set of objectives, acceptable levels of uncertainty, and
attendant data quality requirements. The expression of these objectives
and requirements in clear precise statements is the first step toward the
development of a cost-effective program for collection of sufficient data
for decision making.
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The identification of project objectives should address major areas of the
RI/FS process. These include characterizing the site with respect to the
environmental setting, proximity and size of human population, and nature
of the problem; identifying potential remedies; and determining specific
performance levels of the potential remedies. Each of these areas of the
RI/FS process involves various activities. These activities and their
objectives are presented in Table 2-1.
The components of Stage One were presented in Table 1-1 and are repeated
here:
• Specify decision making process.
• Clarify the need for new data.
• List the intended uses of the data to be collected.
• Prioritize the intended uses of the data to be collected.
• Identify any resource constraints or special requirements.
The following sections provide more detail for the Stage One components.
2.2.1 SPECIFYING DECISION MAKING PROCESS
As part of the development of the project objectives for the RI/FS, the
decision making process should be outlined. Specific decisions that will
be made, when they will need to be made and by whom they will be made are
critical in the outline development. Critical decisions need to be
considered when defining the data to be collected, the sampling and
analytical methods, the sensitivities of the methodologies, and the method
detection limits.
The following are some general decision steps from the RI/FS process:
i What contaminants are above background in pathways of concern?
• Is background an appropriate comparison?
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• Are contaminants above action levels as determined from available
standards or technical guidance? (e.g. What are applicable/
relevant standards, how clean is clean)?
• How do contaminant concentrations found at the site compare with
values for those contaminants which have public health or
environmental significance?
• Do we need a risk assessment if there are no standards?
• What are the three-dimensional and time boundaries of the
contamination above action levels?
• Are there defined concentration gradients that could be handled
separately?
• Are there any operable units that can be expedited in order to
protect public health or the environment (e.g., source control,
alternate water supply)?
• Which alternatives are feasible and sufficient to protect current
and future public health and the environment?
• Is treatment a viable option? Should treatment tests or pilot
plants be conducted concurrent with the RI?
• Has sufficient data been collected so that cost estimates are within
the -30% to +50% range?
• Which alternative should be selected in accordance with NCP? Would
remedy comply with other environmental laws?
• Is litigation (either injunctive relief or cost recovery)
contemplated?
• Are there viable responsible parties?
For reference, several tables are provided in Appendices B and C that
summarize potentially applicable or relevant requirements and toxicity
values. These tables were developed under a variety of statutes, and many
incorporate economic or scientific factors inappropriate for CERCLA. The
standards generally do not consider simultaneous exposure from multiple
routes. Standards may also be based on levels, durations, or frequencies
of exposure that are different from those at a specific site. The
standards and criteria that are used, especially when conducting public
health assessments, must correspond to the media for which they were
developed. As a result of the various technical aspects of standards
development, some concentration limits will require adjustment before being
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applied. It should also be noted that relevant or applicable ambient
concentration limits are not available for all media for many chemicals
commonly found at Superfund sites. In addition, it is possible that there
will be overlaps in the relevant and applicable standards, other criteria,
and toxicity values developed for EPA's Health Effects Assessments (HEAs).
For these reasons, it will be necessary to rank these values (where
available) and to consult with EPA to evaluate the environmental/public
health threat and determine the appropriate range of cleanup levels for the
constituents at each site. Where no applicable standards or criteria
exist, the estimated risk to public health should be determined. Thus, the
decision for remedial action would be based upon either standards/criteria
or upon some level of estimated risk.
2.2.2 CLARIFY THE NEED FOR NEW DATA
This component involves collecting and evaluating existing data,
identifying any data consistent with or usable for the overall project
objectives in compliance with all relevant environmental laws or individual
data collection activity; and, finally, identifying data needs.
Evaluating Existing Data
In many instances, previous studies have provided useful information upon
which further investigation can be based. For each of the major areas in
the RI/FS process all available relevant information should be gathered and
organized in a manner that will allow those data to fulfill the goals of
the activities to be identified. Also important is the evaluation of these
data. The data developed through previous efforts should be analyzed with
respect to its quality to ensure that it is truly useful. Quality
assurance and quality control records should be evaluated as well as the
results of previous investigations. These evaluations determine the level
of uncertainty associated with the conclusions drawn from the data. A
determination can then be made as to whether the achieved level of
uncertainty is adequate, or whether additional data are needed to further
reduce uncertainty.
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A number of factors relate to the quality of existing data and its adequacy
for use in the RI/FS process; the working group has identified the
following analytic considerations when evaluating data:
Age/comparability - How long ago were the data collected? The user must
determine if the data collected during, for example, the site investigation
are relevant or comparable to the present situation. It is not unusual for
the time between the site investigation and the RI/FS to be a couple of
years. Careful evaluation of QA/QC data is essential in determining the
compatibility of old and current data files. Intralaboratory precision
information and interlaboratory bias data are essential for this
evaluati on.
Analytic Methods - Were the analytic methods used in collecting the older
data consistent with present practices? The methods need not be identical.
Just because a newer method has a lower detection limit does not
necessarily imply that the older data are inadequate. However, new
research might identify potential problems with the methods used.
Detection Limits - As implied above, care should be taken to determine if
the detection limits of the analytical tests were sensitive to the
standards and criteria against which the Agency is presently evaluating
data.
Laboratory - Determine the quality an usability of the existing data by
asking such questions as: Are the spike recoveries acceptable for intended
use? Were the laboratory blanks contaminated?
Sample Collection Considerations - Methods for sample collection are as
important as methods for sample analysis. These considerations fall into
two broad categories: statistical and standard operating procedures
(SOPs). The statistical considerations relate to the representativeness of
the data and the level of confidence that may be placed in conclusions
drawn from the data. The SOPs relate to issues of well construction
information or other methods of sample collection. SOPs, if followed, will
ensure sample integrity and data comparability. The protocols for sample
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collection and analysis must be followed in order to reduce sampling and
analytical error. Typical considerations which will be addressed later in
this report are:
• Were the samples collected using a random or non-random sampling
approach?
• Was the sampling plan adequate? (i.e., were a sufficient number of
samples collected?)
• Was the sampling plan followed? Were there deviations from the
sampling plan? Where and how were the samples collected?
Sample Handling Considerations - There is a set of general sample handling
requirements which must be examined when evaluating the quality of
analytical data. These include:
• Were chain of custody procedures followed if the samples were
analyzed off-site? If not, this may not mean that the information
cannot be used. It merely implies that one should discuss with
legal staff the extent to which any conclusions may depend on these
data. If the data are critical in the decision-making process, a
determination should be made if the data would be legally
defensible.
• Were the samples preserved properly? Poor preservation may only
mean that the results actually understate the true extent of the
contaminati on.
• How were the samples shipped? Were the organic samples iced? This
again relates to how the data can be interpreted. It may also limit
the end use of data that were gathered.
• How long were the samples held before being analyzed? As before,
this could relate to the amount of contaminant found. For example,
when holding times are exceeded for volatile organics, the
likelihood of a change in concentration increases. Chemists should
be consulted for appropriate holding times.
Once the available data have been evaluated and compared to the data
requirements, data gaps should be identified. Data needs should be
coordinated with intended use in the decision-making process.
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2.2.3 IDENTIFY THE INTENDED USES OF THE DATA TO BE COLLECTED
The RI/FS process involves a number of data collection activities, each
having specific objectives. Since the objectives require varying degrees
of data quality to fulfill them, it is critical to identify the specific
use to which each set of collected data will be applied. This is done by
considering the number and types of uses to which the data will be put. Of
particular importance are situations where there may be more than one data
user.
The intended uses for data collected during an RI/FS can be described in
general purpose categories. These categories represent generic uses but
vary on a site-by-site basis. Further, specific sites may require the use
of data for purposes other than those described here. In this case,
site-specific data-use categories will be identified. These data use
categories are presented as an aid to site managers in establishing DQOs.
They represent the most common RI/FS data uses. They do not represent
different data qualities, only different uses which may require data of a
given quality. In other words, data collected for a site characterization
and for engineering screening use can be of the same quality even though
being used for two different purposes. These categories are presented to
help decide the quality of data required for a given purpose. The
categories are briefly described below:
• Health and Safety - Data collected for health and safety purposes
are typically used to establish the level of protection needed for
investigators or workers at a site, and if there should be an
immediate concern for the population living within the site
vicinity. Standard practice is to collect baseline health and
safety data, followed by collecting data during any site activities
which involve disturbing baseline conditions (e.g. test-pitting,
well drilling). Health and safety data are generally collected
using real-time, direct-reading portable instruments such as a
photoionization meter.
• Site Characterization - Data collected for site characterization
purposes are used to determine the nature and extent of contamina-
tion at a site. This category is usually the category that requires
the most data collection. Site characterization data are generated
through the sampling and analysis of waste sources and environmental
media.
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• Risk Assessment - Data collected for risk assessment purposes are
used to evaluate the threat posed by a site to public health and the
environment. Risk assessments should help determine (1) the
significance of environmental transport routes to cause human
exposure and environmental damage, (2) the significance of exposure
pathways to human health, (3) the potential health effects that have
or could result from known exposure, (4) the need for immediate
remedial action because of imminent risk or danger to public health,
(5) the need for long-term remedial action to prevent, limit, or
mitigate a potential}y dangerous (i.e., acute or chronic) situation
to public health or the environment in the future, (6) the
appropriate public health recommendations, and (7) the need for a
health study of potentially exposed population. To make such
determinations a high level of data certainty is necessary. Risk
assessment data are generated through the sampling and analysis of
environmental and biological media, particularly where the potential
for human exposure is great.
• Evaluation of Alternatives - Data collected for engineering
screening purposes are used to evaluate various remedial
technologies. This may involve performing bench-scale studies or
pilot-scale studies to determine, on a one or two order-of-magnitude
basis, if a particular process or material may be effective in
mitigating site contamination, and thus warrant further evaluation
or preliminary design. Engineering screening data are generated
through the collection of "before and after" samples of contaminated
media which are subjected to bench-scale tests. Engineering
screening data can also be collected in support of a removal
operation, contaminant modeling, or for many other purposes.
• Design of Remedial Action - Data collected for engineering design
purposes are used to evaluate and "fine-tune" the performance of
various remedial technologies. Usually, this involves performing
pilot-scale studies which precede design so that any required
adjustments/modifications can be made in order to achieve the
performance standards. Engineering design data are generated
through the collection of before and after samples of contaminated
media which are subjected to pilot-scale studies.
• PRP Determination - Data collected for this purpose are used to help
establish the liability at multiple party sites for known RPs by
linking their wastes to those found on the site and pollutants
released to the environment and for unknown RPs by developing a
fingerprint of the site wastes and matching it to pollutant profiles
of known waste streams. Data collected for injunctive actions, as
well as for cost recovery, are used to document the nature and
extent of contamination and to justify the Agency selection of the
remedial alternative as being consistent with the NCP.
Since RI/FS data collection activities must fulfill multiple uses, it is
suggested that each data collection task is listed and the general data use
categories identified for each. Table 2-2 presents a suggested format to
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TABLE 2-2
INTENDED DATA USES
HEALTH &
SAFETY
SITE
CHARACTERIZATION
RISK
ASSESSMENT
ENGINEERING
SCREENING OF
ALTERNATIVES
ENGINEERING
DESIGN OF
REMEDIAL ACTION
PRP
DETERMINATION
SOURCE SAMPLING
SOIL SAMPLING
GROUNDWATER SAMPLING
SURFACE WATER/SEDIMENT
SAMPLING
AIR SAMPLING
BIOLOGICAL SAMPLING
Note: For each task, check the appropriate boxes.
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use. This format or a facsimile can be used by personnel involved in RI/FS
work plan development to identify sampling and analysis needs. The actual
matrix developed should be site specific by task and use.
Once the intended data uses are listed, which can be accomplished by using
the format outlined above, the intended uses must be prioritized.
Establishing an order of priority for the intended data uses will help
identify the most demanding use of each type of data, i.e., the use
requiring the highest level of confidence and therefore the lowest level of
uncertainty. The data quality required will be a function of the
acceptable limits on uncertainty established by the decision maker. The
limits on uncertainty will drive the selection of both the analytical and
sampling approaches.
Prioritizing the intended data uses begins with examining the list of uses
for each data collection task and identifying the use which is most
important to the project objectives. Uses having lesser importance are
then arranged in order, under the first priority use. This is especially
true when there are different turn-around requirements. The data quality
required to support the highest priority use drives the setting of the DQO.
When a secondary use requires data of a much higher quality and the number
of samples required is different than the primary data use, it may be more
advantageous to treat the two uses as separate activities by collecting two
different data sets. Consideration may also be given to developing a
phased approach to the data collection, in which the design of each
subsequent data collection task for an intended use is built upon the
results of the preceding one.
2.3 IDENTIFICATION OF RESOURCE CONSTRAINTS AND SPECIAL REQUIREMENTS
The final area to be considered in Stage One of the DQO development process
is the identification of any resource constraints or special requirements
that will affect the data collection activity. Time and resource
constraints can greatly influence the outcome of data collection and must
be identified early to facilitate program design.
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An example of a time constraint would be the sample turn-around time
required to meet the project schedule. Turn-around times should be
carefully specified in light of what is actually required since they can
become deciding factors in the type of analytical support chosen in Stage
Three.
Resource constraints that must be identified at this time can include
laboratory allocation, sampling and analytical equipment, personnel,
budgets, and other special considerations that must be satisfied. Resource
constraints or special requirements can also be very site specific. These
can include any special requirements identified in a site's work plan.
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3.0 STAGE TWO - DATA QUALITY REQUIREMENTS AND SAMPLING APPROACH
3.1 STAGE TWO A: ESTABLISHMENT OF ANALYTICAL DATA QUALITY REQUIREMENTS
Stage Two of the DQO process begins once the need for new data has been
established and the objectives for the data collection activity have been
determined. The process of establishing the quality of data required
begins with the decision maker proposing limits (based on his or her best
judgment) on the level of uncertainty that will be acceptable in each
conclusion to be drawn from new environmental data. This statement will
address overall uncertainty, i.e., uncertainty resulting from both the
analytical and sampling components of the design. The integrated
evaluation of analytical options (in Stage Two-A) and sampling options (in
Stage Two-B) can then proceed. This integration will ensure that the
overall uncertainty resulting from a complete design is expected to be
within acceptable bounds. DQO development revolves around the limits on
overall uncertainty proposed in Stage Two. The selection of the specific
analytical and sampling support levels required to meet those limits occurs
in Stage Three. Often, Stage Two and Stage Three are combined in an
interactive process whereby the quality required may be limited by the
quality available. Any change in the objectives established in Stage Two
in response to limitations identified in Stage Three must be approved by
the Remedial Project Manager (RPM). Analytical support levels are
described in Section 4.0.
3.1.1 DATA QUALITY REQUIREMENTS
The concept of data quality refers to the level of uncertainty associated
with a data set. RI/FS data are collected for a variety of uses. Typical-
ly, data of various qualities are required for different uses. Data of the
highest quality obtainable is seldom required for all activities. What is
required, however, is that all data collected be of known quality. This
allows for the most efficient use of resources by defining a given data
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quality need, and selecting an analytical support option that, when
integrated with a specific sampling approach, will produce data of the
quality needed.
Sampling and analysis parameters must be defined. These definitions should
be a product of collaboration between management and technical staff. The
ultimate decision regarding the selection of an analytical approach lies
with the RPM. This decision will be made in Stage Three and will be based
on knowledge of the level of uncertainty that can be expected to result
from this approach when combined with a sampling plan.
Data quality requirements for a given program or activity can be specified
by using the Precision, Accuracy, Representativeness, Completeness, and
Comparability (PARCC) parameters. These parameters are discussed in detail
in Section 3.1.2. The relative importance of each of the PARCC parameters
will vary depending on the activity.
The PARCC parameters are not the only issue that needs to be addressed when
establishing data quality requirements. Of particular importance is the
method detection limit (MDL), the lowest amount detectable by the specific
method. The required MDL, as well as any other special requirements,
should be specified prior to the selection of an analytical option.
The data quality requirements can be specified in two general ways. The
first and least sophisticated way of specifying data quality requirements
is by general data needs/data use categories. The second way of specifying
data quality requirements is by specific accuracy, precision, detection
limit, and other analytical specifications. Often, data quality can be
specified using a combination of the above approaches. An example miyht be
specifying engineering quality data with a given MDL or accuracy and
precision information.
DQOs are formed on the concept that different data uses may require
different quality data. For the purpose of discussing variability in data
quality, these general categories of analytical support can be identified:
screening, engineering and confirmational. More specific information
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regarding analytical methods which fall into these categories is provided
in Section 4.0 of this document. This discussion is meant to introduce the
concept of variability in data quality in order to illustrate the Stage One
DQO process.
The three categories may be represented on a data quality continuum, as
follows:
Screening Engineering Confirmational
Increasing Data Quality
Data use categories serve as general guidelines and a tool for grouping
data quality requirements. Data within a certain group may have similar
quality requirements. However, categories may overlap, and different
levels of data quality may exist within each category. For this reason,
once a general category is selected, it should be further classified to
better define the quality that will be required. For example, samples for
risk assessment and litigation uses may be required under the confirmation-
al heading but each use may require a different quality of data.
The general use categories of screening, engineering and confirmation do
not match up directly with the five levels of analytical support described
in Section 4.1.2. However, by using these categories as a starting point,
data uses will become organized in a way that will be useful for determin-
ing the needed level of analytical support in Stage Three. The multiple-
level analytical support system is designed to provide efficient
utilization of available resources while providing data of adequate quality
and quantity to meet defined program objectives. Care must be taken to
insure that interpretation of the data does not exceed the defined quality
or validity of the data base. Results must not be separated from their
related QA/QC data and other information that defines their level of
validity.
Once the difficult process of identifying contaminants of concern is
completed, multiple levels of analytical support may be utilized simultan-
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eously in response to an RI/FS activity. The extent to which screening
mechanisms can be used depends on their ability to identify contaminants/-
concentrations of concern. A most powerful form of analytical support can
be developed by integrating aspects of individual analytical support levels
into one cohesive analytical system. This analytical system, coupled with
a sound sampling plan design, permits a larger number of samples to be
collected and analyzed with increased confidence.
Conceptually, this approach can be thought of as a large "inverted funnel"
whereby large numbers of samples can be initially analyzed quickly and cost
effectively in the field with succeedingly smaller numbers of samples
analyzed further at each ascending level of sophistication. This approach
combines the advantages of each level of analytical support and offsets
disadvantages. The use of less sophisticated techniques initially allows
for large numbers of samples to be screened quickly and at low cost. Next,
a proportion of these samples are analyzed by a more sophisticated
procedure to verify the results of the lower level analysis. This process
can be repeated at each ascending level of analytical support. The type
and design of this analytical approach is determined by how the data being
collected will be used. By strategically selecting which samples are to be
analyzed at each level, a much higher degree of certainty can be obtained
for the overall data set without sacrificing either the quantity of samples
to be analyzed or the quality of data collected.
An example of this approach follows. Consider a hazardous waste site where
the soil is contaminated with volatile organic compounds (VOCs). For this
example, two assumptions are:
1. The objectives of the sampling are to determine site boundaries and
direct contact threat.
2. The HNu photoionization detector will detect contaminants at the
levels of concern.
The site's sampling plan calls for 300 soil samples to be analyzed
according to locations determined by a random grid pattern. To illustrate
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this approach in general terms, data uses and data quality are not
specified in this example. The analytical approach is as follows:
• All 300 samples are analyzed in real time using HNu PI 101/0VA 128*
field headspace techniques {Level I).
• One hundred fifty samples register below the detection limits of
this instrumentation and are considered to be clean for the purposes
of this study.
• Ten percent of the clean samples (for which nothing was detected)
and all of the dirty (contaminated) samples (150) are analyzed
onsite using a portable gas chromatograph (Level II) to obtain
semiqualitative and quantitative results within a couple of days.
• Based on these results, a specified number (e.g., 50) of samples are
sent to a commercial laboratory or to CLP screening (Level III) to
confirm the field analysis.
• Twenty samples are selected for analysis by CLP Routine Analytical
Services (RAS) (Level IV) for the Hazardous Substance List (HSL)
compounds. Included in these samples are all samples identified as
critical data points (CDPs). This step provides confirmation for
all preceding work including verification that indicator parameters
are representative of contaminants of concern and are identified
appropriately. The results of all split samples analyzed by
different levels are interpreted for quality control purposes.
This example was set up for explanatory purposes only. There is no
significance attached to either the ratios of samples analyzed by each
level or the number of levels used. Four levels were utilized for the
purposes of this example, but as few as two levels can be used effectively.
Figure 3-1 represents a conceptualization of this process.
This approach can also be utilized in a time-phased manner, i.e., by using
the results of an initial sampling round with a lower level of analysis to
fine-tune the sampling approach for a subsequent sampling round using
higher level(s) of analytical support. This concept is explained in more
detail in Section 3.2.
*Use of trade names does not constitute an endorsement and is used for
discussion purposes only.
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FIGURE 3-1
Integration of Analytical Support Levels:
a conceptualization of the example presented in the text.
1
Data Cost
Quality and
Turnaround
Time
Percent
of
Samples Analyzed:
10%
Percent
of
Samples Analyzed:
25%
Percent
of
Samples Analyzed:
50%
Percent
of
Samples Analyzed:
100%
Rationale:
All samples are prescreened using Level I techniques. Based on this criteria,
50% of the samples are analyzed using onsite gas chromatography (Level II).
Using this information, a total of 35% of the samples are sent out for
analysis (25% Level 111/10% Level IV). Many of these samples are split
samples being analyzed by both levels and are Critical Data Points (CDPs),
background samples or of strategic interest to the sampling program. Each
analytical level acts in a confirmational capacity in relation to the level
below it. By comparing the results of the same sample analyzed by two
different levels, the higher level analysis can be used to "calibrate" the
lower level analysis, i.e. using 10 level III analyses as a calibration curve
for extrapolating concentrations from 300 Level I analyses, provided the 10
Level III analyses span the concentration range of interest.
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The second procedure that can be used to state data quality requirements is
the quantitative specification of the PARCC and other parameters. While
this method requires thorough knowledge of the ways that the data wU7 be
used and the level of uncertainty acceptable for each use, it is the best
way to ensure that data collected will meet the activity's objectives.
Accuracy and precision for a given activity can be specified generically
using the terminology outlined in Section 3.1.2. These specifications are
then used to select or modify the appropriate analytical options and match
them with corresponding sampling plans in Stage Three.
The output of Stage Two of the DQO development is a statement of the level
of uncertainty acceptable for each conclusion (based on data) needed to
meet objectives of the RI/FS. Stage Two also results in quantitative or
qualitative statements addressing each of the PARCC parameters and other
parameters deemed appropriate for the activity. These statements, together
with time and resource constraints, criteria for decision making, and any
other data quality requirements, are used in selecting the appropriate
analytical option and sampling approach in Stage Three.
3.1.2 DATA QUALITY CRITERIA
Analytical options are best selected by matching the data quality required
with the data quality produced by a given analytical option when combined
with a sampling approach. The criteria used most comnonly to specify
project data requirements and to evaluate the available analytical options
are the characteristics of precision, accuracy, representativeness,
completeness, and comparability (PARCC):
• Precision - a measure of the reproducibility of measurements under a
given set of conditions.
• Accuracy - a measure of the bias that exists in a measurement
system.
• Representativeness - the degree to which sample data accurately and
precisely represent selected characteristics.
• Completeness - a measure of the amount of valid data obtained from a
measurement system compared to the amount that was expected to be
obtained under normal conditions.
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• Comparability - expresses the confidence with which one data set can
be compared to another.
When using the PARCC parameters to assess data quality, only precision and
accuracy can be expressed in purely quantitative terms. The other paramet-
ers are best expressed using a mixture of quantitative and qualitative
terms. All the PARCC parameters are interrelated in terms of overall data
quality and they may be difficult to evaluate separately due to these
interrelationships. The relative significance of each of the PARCC
parameters depends on the type and intended use of the data being
collected.
Each of the individual PARCC parameters is addressed in some detail in the
following sections. Those parameters more specific to sampling are
developed in greater detail in Section 3.2.
Table 3-1 summarizes the rate that QA/QC samples should be included in
field sampling programs. It should be stressed that these rates are
suggested guidelines only. As this table is only a summary, more detailed
information is included in the text of this section. As is the case with
all guidelines, these recommendations must be applied on a site by site
basis.
Precision
Precision is a measure of the reproducibility of measurements under a given
set of conditions. Specifically, it is a quantitative measure of the
variability of a group of measurements compared to their average value.
Precision is usually stated in terms of sample standard deviation but other
estimates such as the coefficient of variation (sample relative standard
deviation), the range {maximum value minus minimum value), and the relative
range are common.
The overall precision of data is a mixture of sampling and analytical
factors. Analytical precision is much easier to control and quantify than
sampling precision. There are more historical data related to individual
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TABLE 3-1
GUIDELINES FOR MINIMAL QA/QC SAMPLES
FOR FIELD SAMPLING PROGRAMS
MEDIA
DUPLICATES
Fimi FIELD
COLLOCATED OR REPLICATE BLANK
TRIP
BLANK
BACKGROUND
SAMPLE
INTER-LAB
SPLIT SAMPLE
Aqueous
Soil,
sediment
Air
Source
material
one in twenty
one in twenty
one in twenty
one in twenty
one in
twenty
one in
twenty
not
available
not usually
required
one per
day of
sampling
one per
day of
sampling
min. of two
per sampling
event-media
min. of two
per sampling
event-media
min. of two
per sampling
event-media
when required
to meet
objecti ves
when required
to meet
objectives
when required
to meet
objecti ves
when required
to meet.
objectives
NOTE: These numbers are intended as guidelines only; QA/QC requirements must be developed on a
site-specific basis. Laboratory blanks and spikes are method specific and are not included in
this table.
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method performance and the "universe" is limited to the samples received in
the laboratory. In contrast, sampling precision is somewhat unique to each
site. Historical sampling plan performance may be totally irrelevant to
the site under consideration.
The following definitions of duplicate samples are taken from the March 30,
1984 Calculation of Precision, Bias, and Method Detection Limit for
Chemical and Physical Measurements issued by the EPA Quality Assurance
Management and Special Studies staff.
• Collocated samples are independent samples collected in such a
manner that they are equally representative of the parameter(s) of
interest at a given point in space and time. Examples of collocated
samples include: samples from two air quality analyzers sampling
from a common sample manifold, two water samples collected at
essentially the same time and from the same point in a lake, or
side-by-side soil core samples.
Collocated samples when collected, processed, and analyzed by the
same organization provide intralaboratory precision information for
the entire measurement system including sample acquisition,
homogeneity, handling, shipping, storage, preparation and analysis.
Collocated samples when collected, processed and analyzed by
different organizations provide precision information for the entire
measurement system.
• Replicated samples are samples that have been divided into two or
more portions at some step in the measurement process. Each portion
is then carried through the remaining steps in the measurement
process. A sample can be replicated in the field or at different
points in the analytical process. For field replicated samples,
precision information would be gained on homogeneity (to a lesser
extent than for collocated samples), handling, shipping, storage,
preparation, and analysis. For analytical replicates, precision
information would be gained on preparation and analysis. Examples
of field replicated samples include a soil core sample that has been
divided into two representative portions and a ground water sample
that has been collected and poured into a common container before
being placed in individual sample containers.
• Split samples are replicate samples divided into two portions and
sent to different laboratories and subjected to the same
environmental conditions and steps in the measurement process. They
serve as an oversight function in assessing the analytical portion
of the measurement system.
Collocated samples should be used to estimate the overall precision of a
data collection activity. Sampling error can be estimated by the inclusion
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of collocated and replicated versions of the same sample. If a significant
difference in precision between the two subsets is found, it can probably
be attributed to sampling error. As a data base on field sampling error is
accumulated, the magnitude of sampling error can be determined.
There are other issues that should be considered when specifying the
precision component of a DQO:
• For most parameters, analytical precision is concentration
dependent. When a wide range of values is expected for a parameter,
precision can be specified for a given concentration range.
t The sample chosen to be collocated or replicated should be
representative of the sampling round.
• The sample submitted in duplicate (replicated or collocated) should
contain the contaminants of interest at a measurable level.
Precision cannot be measured for a pair of samples that are both below
detection limits. To alleviate this problem, the CLP requires laboratories
to use matrix spike duplicate analyses whereby duplicate samples are spiked
and then evaluated for precision. However, these only measure analytical
precision.
In summary, the following are suggested guidelines for the inclusion of
collocated and replicated samples in field programs:
• Ground and surface water - one out of every 20 investigative samples
should be collocated. Replicated samples could be substituted where
appropriate. These samples should be spread out over the sampling
event, preferably at least one for each day of sampling.
• Soil, sediments and solids - one out of every 20 investigative
samples should be field replicated or collocated. To estimate
sampling error, collocated and field replicated samples should be of
the same investigative sample. These samples should be spread out
over the sampling event, preferably one per each day of sampling.
The use of both collocated and replicated samples in soil sampling is an
attempt to quantify the degree of error that can be attributed to the
sampling process. This approach is valid when the homogeneity of the
sample matrix is in question. Swiftly flowing streams or discharge pipes
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would also fall into this category. The use of these two types of
duplicate samples and the frequency of their inclusion is dependent on the
sample matrix and the use of the data. More duplicate samples are
generally taken when non-homogeneity is expected. The inclusion of
collocated samples into a sampling program also depends on the type of
sampling. It may not make sense to collocate deep soil boring samples, for
example. In this example, a field replicate sample would be taken rather
than the drilling of two separate, side-by-side boreholes.
The rationale for recommending collocated samples over field replicate
samples for aqueous media is due to the high degree of sample homogeneity
expected. Since collocated samples convey more overall precision
information for this sample media, they are more advantageous. Field
replicates of aqueous samples approximate the same precision information
that would be gained from laboratory duplicate analyses.
Accuracy
Accuracy is a measurement of bias that exists in a measurement system.
Unlike precision, accuracy is difficult to measure for the entire data
collection activity. Sources of error as it pertains to accuracy are the
sampling process, field contamination, preservation, handling, sample
matrix, and analysis. Accuracy is best assessed by evaluating the results
of field/trip blanks and matrix spikes. (A table of accuracy definitions
is included as Appendix D).
Field/trip blanks. As an example of how the sampling process can impact
accuracy, consider the collection of ground water samples for volatile
organic analysis. In the actual sampling, some portion of the volatile
components are lost. There is no way to measure this loss easily. Next,
the sample can be subjected to contamination from a wide range of sources
in the field and laboratory. To check the entire system for false
positives, trip/field blanks are used.
Field blanks are defined as samples which are obtained by running
analyte-free deionized water through sample collection equipment (bailer,
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pump, auger etc.) after decontamination, and placing it in the appropriate
sample containers for analysis. These samples will be used to determine if
decontamination procedures have been sufficient. To insure the integrity
of field blanks, they should be collected, stored, and shipped with the
other samples. Using the above definition, soil field blanks could be
called rinsate samples. These should be included in a sampling program as
appropriate.
Trip blanks generally pertain to volatile organic samples only. Trip
blanks are prepared prior to the sampling event in the actual sample
containers and are kept with the investigative samples throughout the
sampling event. They are then packaged for shipment with the other samples
and sent for analysis. At no time after their preparation are the sample
containers opened before they reach the laboratory. All blanks should be
submitted for analysis "blind."
The following guidelines for including blanks in sampling programs are
suggested.
• Ground and Surface Water - Field blanks should be submitted at the
rate of one field blank/matrix/per day or one for every 20
investigation samples, whichever results in fewer samples. Trip
blanks should be included at a frequency of one per day of sampling
or as appropriate.
• Soil sediments and solids - Rinsate samples should be submitted at
the rate of one for every 20 investigative samples for each matrix
being sampled or as appropriate. EMSL-LV is currently evaluating a
material which can be used as a soil field blank.
Matrix Spikes. Many samples exhibit matrix effects (see Matrix Effects
under Section 3.1.3), in which other sample components interfere with the
analysis of contaminants of interest. Matrix spikes provide the best
measurement of this effect. When done in the field, immediately after
collection, they also provide a measurement of sampling, handling and
preservation error. The field matrix spike does provide the best overall
assessment of accuracy for the entire measurement system, as collocated
samples do for precision assessment. However, there are some serious
issues regarding the field spiking of environmental samples that must be
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considered. Field matrix spikes are generally not recommended because of
the high level of technical expertise required for proper use and their
sensitivity to environmental variables. Spiking of soil samples in the
field is particularly difficult to perform.
Some of the biggest problems associated with field matrix spikes are due to
the fact that all spike recovery data must be interpreted very carefully.
Spike recoveries are subject to many competing factors, such as analyte
stability, holding time, and the sample matrix. Because of this inherent
variability associated with spike recoveries, the additional variability
introduced by spiking samples in the field can increase the overall
uncertainty associated with a data set rather than decrease it.
The two most important issues when considering field spiking as an option
are the source of the spiking material and the technical capability of the
person doing the spiking. Spiking materials that can be used are Standard
Reference Materials (SRMs), EPA quality control ampules, or laboratory
prepared solutions made from pure compounds. SRMs are stand-alone stan-
dards prepared by NBS that can be placed in the appropriate sample
containers and sent to the laboratory to be analyzed. The use of certified
standards such as SRMs solves the "traceability" issue concerning the
integrity of the blind standard and also does not require a skilled
technician to prepare the standard. However, because the SRM is a
stand-alone sample, it provides no information on the impact of the sample
matrix on the measurement system. An aliquot of an SRM can be used to
spike an environmental sample, but it would no longer be traceable and
would require a person skilled in the appropriate analytical techniques,
just as the use of quality control ampules or 1aboratory-prepared spikes
do. The competence of the person doing the spiking is critical. The exact
amount of spiking material must be recorded for future use in assessing
recoveries. Errors in measurement of the spike or use of the wrong spiking
material will cause serious problems in interpreting the usability of the
data.
In summary, field matrix spikes are not to be recommended unless the
appropriate technical support is available. Absolute attention to all
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details is required to obtain useful information from the procedure. If
field matrix spikes are used, the results should be compared with
laboratory matrix spike results.
Including laboratory matrix spikes as a part of the DQOs is viable for most
data uses. While not covering the entire measurement system, laboratory
matrix spikes provide information on potential sample matrix effects and
analytical technique. Using this approach together with the submittal of a
blind, re-packaged SRM can provide a great deal of accuracy information.
It is the data user's responsibility to determine and document the required
quality assurance/quality control and incorporate that requirement into the
DQO accordingly.
Representati veness
Representativeness expresses the degree to which sample data accurately and
precisely represent a characteristic of a population, parameter variations
at a sampling point, or an environmental condition. Representativeness is
a qualitative parameter which is most concerned with the proper design of
the sampling programs. The representativeness criterion is best satisfied
by making certain that sampling locations are selected properly and a
sufficient number of investigative samples are collected.
Representativeness is best addressed by describing sampling techniques and
the rationale used to select sampling locations. Sampling locations can be
biased (based on existing data, instrument surveys, observations, etc.) or
unbiased (completely random or stratified-random approaches). Either way,
the rationale used to determine sampling locations must be explicitly
explained. If a sampling grid is being utilized, it should be shown on a
map of the site. The proper location of sampling stations can be the
deciding factor in whether a data collection activity's objective will be
met. The type of sample, such as a grab or composite sample as well as the
relevant SOPs for sample collection should be specified.
Background chemical contamination must be taken into consideration.
Monitoring data as well as available literature on natural background
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concentrations of chemicals in the area should be collected, reviewed
and/or verified to determine background conditions. Background data should
be defined as either natural or anthropogenic chemical contamination
resulting from a source or sources other than the site undergoing
assessment. At least two background samples should be collected during
every sampling event. A sampling event is a specific media event over a
specified period of time. For example, quarterly ground water sampling
which required four one-week trips over the year would be considered four
sampling events; however, a single trip for soil sampling which covers four
consecutive weeks would be considered a single event. A background sample
is one taken from media characteristic of the site but outside of the zone
of contamination.
An example of the way representativeness is assured in a sampling program
is in the use of proper ground water sampling technique. The SOPs for
ground water sampling require that a well be purged a certain number of
well volumes prior to sampling, to be certain that the sample is
representative of the underlying aquifer at a point in time.
Representativeness can be assessed to some degree by the use of collocated
samples. By definition, collocated samples are collected so that they are
equally representative of a given point in space and time. In this way,
they provide both precision and representativeness information. In some
cases, budget or sample allocation constraints may require a trade-off
between analysis of additional investigative samples and analysis of
additional QC samples (blanks, duplicates, spikes). In such circumstances,
a balance must be made to ensure that the minimum number of investigative
and QC samples that are required to satisfy the sampling objectives are
included. A phased approach with more than one round of sampling may be
required, with information from the initial round being used to design
follow-up sampling activities.
Completeness
Completeness is a measure of the amount of valid data obtained from a
measurement system compared to the amount that was expected to be obtained
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under normal conditions. Completeness is usually expressed as a percent-
age. Site access, sampling problems, analytical problems, and the data
validation process can all contribute to missing data. A completeness goal
must be included in the DQO process to assure that enough data of suffi-
cient quality are obtained from the measurement system to fulfill the
objective of the study.
Critical data points should be identified in every completeness statement.
Critical data points are sample locations for which valid data must be
obtained in order for the sampling event to be considered complete, and/or
can be expressed by a percentage of samples taken in a medium. An example
of a critical data point may be an upgradient well in a ground water
contamination study or any other data point considered vital to the
decision making process or 50% of the perimeter data points. Critical data
points should be carefully considered in the sampling plan design of a data
collection activity and every effort must be made to obtain valid data for
these samples. In some cases, taking critical data point samples in
duplicate may be appropriate.
Comparability
Comparability expresses the confidence with which one data set can be
compared to another. In the most general of circumstances, this refers to
the use of standard field and analytical techniques and the reporting of
analytical data in the same units. In order to compare data, various
elements must be taken into account: sampling method, sample handling,
holding time, sample location, preservation, etc.
Comparability in the data collection activity must take into consideration
if the events are even comparable in the first place. An example would be
trying to compare data from the same aquifer in a high water and a low
water situation. This criterion is most important when conclusions are
being drawn from existing data. If an activity is being planned to augment
existing data, field conditions must be considered as well as sampling and
analytical techniques.
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3.1.3 OTHER ANALYTICAL CONSIDERATIONS
There are a number of other factors which may affect development of DQOs
for a sampling and analytical plan. They include the following:
• Enforcement requirements
• Analytical quality control
• Media variability
• Method detection limit
• Matrix effects
• Tentatively identified organic compounds
• Data qualifiers
Enforcement Requirements
An RI/FS should be conducted and documented so that sufficient data are
collected to make sound decisions concerning remedial action selection.
This is true for fund-lead, federal or state enforcement-lead, and
potentially responsible party (PRP)-lead. The amount of data and
documentation should be similar for all types of RI/FSs. In other words,
if enough data are collected using appropriate protocols, and the data are
found sufficiently valid upon which to base a decision on remedial action,
then the procedures and documentation should be sufficient to stand up in
court.
Enforcement/cost recovery actions do have at least one additional
requirement. This requirement is to identify viable PRPs. This may
require additional sample collection and more complex analysis on a few
samples. Regional enforcement personnel should be consulted prior to the
planning of sampling and analytical activities to assure that their data
needs will be met. Distinction must also be made between civil and
criminal cases, with the latter usually having much more stringent
requi rements.
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The following comments pertain to all data collected for RI/FSs (except
potential criminal cases).
These guidelines should be followed to assure that statements can be made
concerning the data and the decision making process:
• Appropriate plans (i.e., work plans, sampling plans, QAPP) should be
developed to document intentions.
• Field notebooks should include information on field conditions,
sample location, sample number, collection time, sample description
{chain of custody forms or other mechanism can be used to record
this information).
• Personnel throughout the process from planning, sample collection,
analysis and decision making should have experience or be
sufficiently trained.
• Chain of custody must be documented with a chain of custody form for
samples taken off-site for analysis. This assures the decision
maker that the analysis given is actually for the sample collected
and that the sample has not been tampered with. If analysis is
performed onsite, documentation of the process in field logs or
other media is sufficient. Custody of samples should still be
documented; however, the chain of custody form is not necessary.
• Methods used for sampling and analysis should be generally
considered valid from an engineering/scientific standpoint and be
consistent with standard analytical procedures. Methods utilized
should be referenced in the RI/FS report or other documents and a
statement given that protocols were followed. Any deviation from
the referenced method should be documented and explained.
• Documentation should be sufficient to allow the persons Involved in
the site studies to reconstruct the work years later when the matter
is litigated. If the documentation is adequate, the defendants may
be convinced by the strength of the Government's case not to contest
those particular points, and hence testimony by the Government or
contractor employees may not be necessary.
• EPA's or the State's responsibf1ity from a QA/QC standpoint would be
to audit randomly some RI/FS field sampling, analysis (QA/QC) and
data validation to confirm that procedures utilized were sufficient.
§ Actual samples, sample tags and sample bottles are not required to
be kept to prove that samples were taken and maintained. This is
the purpose of the chain of custody sheet, field notebook, or other
similar mechanisms.
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As stated previously, the above requirements pertain to civil cases only.
Criminal cases will require additional documentation and/or materials.
Analytical Qualify Cortrol
The classification of analytical support into broad levels takes into
account internal laboratory quality assurance quality control (QA/QC) in a
general manner only. Internal QA/QC refers to the surrogate and matrix
spikes, method blanks, and duplicate/replicate runs, among other laboratory
or field operation quality control. Within a given level of analytical
support, there may be differences in the way individual laboratories or
field operations approach internal QA/QC. For Invitation for Bid (IFEJ) RAS
analytical support, the procedures are standardized and contract-specified.
When evaluating the use of a non-CLP laboratory or field operation, the QA
plan of the laboratory or contractor should be reviewed. Documentation
requirements and appropriate QC requirements should also be specified. The
CLP list of contractors is a source of information on laboratories
currently performing analysis for the Superfund program.
Laboratory/field operation QA/QC plans should be reviewed. Items of
particular concern are calibration procedures, frequency of laboratory
blank and duplicate analysis, the use of surrogate standards and spikes,
and standard operating procedures. The laboratory/field operation report
format should also be evaluated in terms of wtiat information is reported
along with the sample data (method blanks, duplicates, spikes, etc.). At a
minimum, method blank, internal duplicate/replicate and matrix spike
information should be reported along with the sample data. Surrogate spike
information should also be reported for all GC/MS data.
When evaluating laboratory QA/QC, it is important for the reviewer to keep
the level of analytical support in perspective. These levels produce data
of different quality and documentation and should be reviewed with this in
mind. For example, it would be inappropriate to hold a screening
laboratory to CLP RAS standards, or expect a field screening operation to
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have as rigorous QA/QC as a laboratory. Expectations such as these would
be inconsistent with the concept of classifying analytical support by the
quality of the data needed.
Once the required data quality for a given activity is established, the
data user must select the appropriate level of analytical support that will
supply data of the required quality. For example, an analytical level can
be flexible by specifying more or less QA/QC. The cost and turnaround time
can be increased or decreased within a given level by adjusting the amount
of QA/QC. This reasoning results in a continuum of analytical support
services available to cover a wide spectrum of data quality requirements.
Media Variability
Project planners and data users should be aware that a great deal of
variability exists in regard to how a given analytical technique or method
responds to a given sample medium. Most of the analytical methods utilized
in support of RI/FS activities were developed, at least originally, for
aqueous samples and modified for use with other media later on with varying
results. Also, the quality control data published for most analytical
methods (concerning accuracy and precision information) were developed
using aqueous samples. The performance criteria published may not totally
apply to the use of the method with other sample media. When considering
the analysis of source materials, leachate or other complex matrices,
qualified analytical support personnel should be consulted to determine the
most appropriate analytical approach.
Method Detection Limit
Irrespective of the specified method detection limit, the actual detection
limit reported is sample specific. This is especially true of samples
having complex sample matrices. Since detection levels are important in
interpreting quantitative results, detection levels should be reported for
all analyses.
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If the concentration of a particular sample constituent is so high that it
requires dilution prior to analysis, the resulting detection limit for that
sample will be raised by the dilution factor. For example, consider a
sample being analyzed by GC/MS for volatile organics. If the laboratory's
normal detection limit for this method is 5. ug/1, and the sample contains
20. mg/1 of benzene, the sample will have to be diluted (say by at least a
1/10 ratio) and the resulting detection limit will be 50. ug/1. In some
cases, the laboratory can analyze the same sample twice to obtain the
specified detection limit but it is not always possible, is not considered
standard practice, and would have to be specified prior to sample
submittal.
Another factor regarding detection limits is that data quality parameters
are usually concentration dependent. The standard error of the analytical
method being used increases as the concentration of the analyte of interest
decreases. The surest way of predicting what the accuracy and precision
will be for analyses at the detection limit is by generating QC data using
the detection limit concentration. In light of this decrease in the level
of certainty as the concentration decreases, the relationship between
action levels and detection limits should be considered carefully.
It is important to recognize that quantitative results reported at the
detection limit may not be reliable. If the action level of a contaminant
is 5 ug/1, an analytical method with a detection limit of 5 ug/1 may not be
suitable. The limit of reliable quantitation is approximately twice the
detection limit.
When levels of interest are at or approaching MDL, caution must be used in
specifying precision in terms of a percentage. The use of percentages
distorts accuracy and precision information when relatively small numbers
are being compared. Accuracy and precision in terms of absolute values or
ranges may be more appropriate. For example, consider a precision
objective specifying that blind replicate samples must be within 50% of
each other. If the two replicate concentrations are 50. and 75. ug/1, the
use of this objective is reasonable. If the two replicate concentrations
are both in the 1-10 ug/1 range, the 50% objective would classify these
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results as being outside of criteria, whereas in all probability the
replicate analyses show excellent precision. Caution must be used when
applying objectives expressed in percentages to numbers less than fifty.
If the precision objective is specified using a percentage, the working
range of the objective should also be specified.
Matrix Effects
A matrix effect is a phenomenon that occurs when the sample composition
interferes with the analysis of the analyte(s) of interest. This can bias
the sample result either in a positive or in a negative way, with the
negative bias being the most common.
The magnitude of a matrix effect is best assessed by the use of matrix
spikes. Matrix spikes supply percent recovery information which addresses
the amount of bias present in the measurement system. This information can
be used to adjust reported concentrations by the application of a
correction factor based on percent recovery or as a part of a mental
process where sample results can be considered to be somewhat "higher" or
"lower" than the reported values. It is not recommended that sample values
actually be adjusted for percent recovery unless a "worst case" scenario is
being developed. For non-aqueous matrices (soils, sediments, leachate,
solid wastes, etc.), this type of data should be collected historically
over the life of a project so that certain expectations about the quality
of data being produced can be developed.
Tentatively Identified Organic Compounds (TICs)
Under the CLP RAS procedures, the top ten non-HSL peaks present in the
reconstructed ion chromatogram (RIC) per fraction are identified as
tentative compounds. Other laboratories may not address TICs or have
different reporting criteria. If compounds of interest are tentatively
identified by GC/MS and are high in spectra matching criteria (above 90%
match) for known contaminants and above action levels, samples may be
re-run against a standard in order to verify the compound's identity. For
non-HSL compounds where action levels do not exist, acceptable risk level
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needs to be determined. Chromatographic retention time consideration is an
important factor in assessing the probability of tentative identification
reliability. Approaches for providing more reliable tentative
identifications are under development.
Data Qualifiers
When analytical data are validated, the analytical results and the
associated QA/QC information are reviewed using criteria specific to the
analysis performed. This review can range from superficial to very
rigorous, depending on the level of analytical support utilized and the
type of technical review requested by the data user. All data users should
be provided with adequate documentation to determine whether sampling and
analytical quality control DQOs have been achieved. Exceptions should be
clearly identified and explained in the sample case narrative and/or data
validation report.
Data qualifiers are commonly used during the data validation process to
classify sample data as to its conformance to QC requirements. The most
common qualifiers are listed below:
• A - Acceptable
• J - Estimate, qualitatively correct but quantitatively suspect
• R - Reject, data not suitable for any purpose
• U - Not detected at specified detection limit (e.g., 10U)
Sample data can be qualified with a "J" or "R" for many different reasons.
Poor surrogate recovery, blank contamination, or calibration problems,
among other things, can cause sample data to be qualified. Whenever sample
data are qualified, the reasons for the qualification are stated in the
data validation report. Data users are reminded that data validation is
generally performed using strict analytical criteria which do not take the
sampling activity's DQOs into account. Data users should request that the
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technical staff "interpret" the validation report in relation to the
sampling activity's objectives and data uses. For example, data qualified
with a "J" may be perfectly suitable for some data uses.
3.2 STAGE TWO B OF THE RI/FS PROCESS
To be prepared
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4.0 STAGE THREE - SELECTION OF ANALYTICAL AND SAMPLING OPTIONS
Stage Three of the OQO development process specifies the complete sampling
and analysis approach required to meet the objectives stated in Stage One.
It is in this stage that various combinations of sampling and analytical
techniques are evaluated and a combined approach is selected that will
satisfy the objectives set in Stages One and Two, including the limit on
total uncertainty. Any and all modifications required in sampling or
analytical techniques are stated, as well as the limitations or
applicability of the data to be collected. Parts A and B of Stage Three
are summarized below:
• Stage Three-A: This stage involves the actual selection of the
analytical option and evaluation of the use of a multiple-level
approach to effect a more timely or cost-effective program. Of
utmost importance is integration of this stage with Stage Three-B.
The goal of integration is the selection of compatible analytical
and sampling approaches that, when combined will satisfy the limit
on total uncertainty. Section 4.1 presents more detailed discussion
on the selection of analytical options and the use of a multiple-
level approach.
• Stage Three-B: This stage involves the selection of the sampling
approach to be employed. As stated above, integration with Stage
Three-A is of utmost importance to ensure that the sampling approach
is compatible with the analytical option(s) and that the combined
approach will satisfy the limit on total uncertainty. In some
cases, the use of the multiple-level approach to analytical support
will facilitate the optimum sampling approach desired. Section 4.2
is reserved for a detailed discussion of Stage Three-B.
4.1 ANALYTICAL OPTIONS
Stage Three consists of evaluating objectives, resource constraints, and
data quality requirements to determine the most appropriate type of
analytical support. Formulating an analytical option to meet the DQO for a
specific activity may require selecting procedures from more than one
analytical level.
If requirements are impossible to meet, such as research quality data with
a one day turnaround requirement, compromises must be made. The technical
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Document No. 9355.0-7A
staff will evaluate possible alternatives and present their findings to the
Remedial Project Manager (RPM). The selection of an alternative is the
responsibility of the RPM.
The remainder of Section 4.0 includes an overview of the concept of
analytical levels and subsections on each of the five standard levels.
Each subsection provides a detailed description of the levels, including
uses, benefits, costs, documentation, accuracy, and precision and detection
limit information. This quantitative information on analytical options can
then be used in combination with similar information on sampling options
(from Stage Three-B) to estimate the total uncertainty that will arise from
combined sampling and analysis approaches.
4.1.1 OVERVIEW OF ANALYTICAL SUPPORT LEVELS
Currently, the Contract Laboratory Program (CLP) is a major source of
analytical support for Superfund program activities, including remedial
irtvestigations/feasibil ity studies (RI/FSs). In addition to CLP support,
alternative analytical support approaches have been identified. The type
of analytical support varies with site-specific project requirements and
regional resources and/or preferences. The analytical options available to
support Superfund program activities are presented in five general levels.
These levels are distinguished by the types of technology, documentation
used, and their degree of sophistication; there is some overlap between
levels.
The following is a brief summary of each analytical support level,
including a description, sources of services, and optimum uses of the data
produced at each level.
• LEVEL NS - Characterized by non-standard methods of analysis which
may require method modification and/or development.
• LEVEL IV - CLP Routine Analytical Services (RAS) Invitation For Bid
(IFB) Analysis. This level is characterized by rigorous QA/QC
protocols and docuinentation and provides qualitative and
quantitative analytical data. Some regions have obtained similar
support via their own regional laboratories or subcontracting
through the REM/FIT programs.
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• LEVEL III - Laboratory analysis using methods other than the CLP RAS
IFB. This level is used primarily in support of engineering studies
using standard EPA approved procedures.
• LEVEL II - Field analysis. This level is characterized by the use
of portable analytical instruments which can be used on-site, or in
mobile laboratories stationed near a site (close-support labs).
Depending upon the types of contaminants, sample matrix, and
personnel skills, qualitative and quantitative data can be obtained.
• LEVEL I - Field screening. This level is characterized by the use
of portable instruments which can provide real-time data to assist
in the optimization of sampling point locations and for health and
safety support. Data can be generated regarding the presence or
absence of certain contaminants (principally volatiles) at sampling
locations. Essentially nonqualitative; quantitative only as total
organics.
Table 4-1 summarizes these analytical levels.
Also, within each level, the different procedures used produce different
quality data to some extent. For example, Level II encompasses both mobile
laboratory procedures and less sophisticated "tailgate" operations which
produce data of different quality.
Table 4-2 summarizes typical RI/FS activities and the rationale used to
select the appropriate analytical levels. The information contained in
this and other sections as well as the case examples presented in Section
5.0 should enable data users to select analytical support options for most
RI/FS activities.
4.1.2 NON-STANDARD METHODS - LEVEL NS ANALYTICAL SUPPORT
Objective of Analytical Support (Level NS)
The objective of this type of support is to provide the RI/FS process with
data that cannot be obtained through standard avenues of analytical
support.
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TABLE 4-1 SUWARY OF ANALYTICAL LEVELS FOR RI/FS
Optlor
Type o1 Analysis
LlmttatIons
Oata Quality
- *Jon- con wen 11 a I
parameters
- Method-sp-ec 1 He
detect 1 on I In I ts
- Mod lit cat Ton of
existing methods
- Appendix 8 parameters
- Conftrwattonal
- Toxicology
- Slte-speclflc
condIt Tons/parameters
- RCRA compliance
- Requires method
development/mod 1flea
tlon
- Mechan1sm to obta I n
services requires
special leadtlme
- Method-spec 1Hc
In It lal I y h Igh, 1 f
Method development
Is required.
- Months to years
- HSL Organlcs/lnorgonlcs
by GC/MS; AA; ICP,
- Low ppb detection limit
Conftrmatlonal
To*Icology
Al I other program
Actlvlttes
Tentatl ve Identl f Ica-
tIon of non-KSL
parameters
Some time may be
Required for Validation
of packages
Goal Is data of
Qualtty
Rigorous QA/QC
- St,000/Sample
Contractually, 50
days - 40 days
-P*
I
-P*
Organlcs/Inorganles
using EPA procedures
other than IF0 can be
analyte-speelf!c
RCRA characteristic
tests
ConfIrmatlonaI but with
less documentation
Presence or absence of
contaminants
Engineering uses
Screening
Tentative ID Tr> some
cases
Simitar defection
1lml ts to CLP
Less rigorous QA/QC
SI,000/Sample
- 21 days
Variety of organlcs by
GC; Inorganics by AA;
XftF
Presence or absence of
contaminants
- Tentative ID
Dependent on QA/QC
steps employed
- $15-40/Sample
Real-ttme to
several hours
Tentative ID; analyte-
spec 1f1c
- Relative concentrations
TechnIques/Instruments
limited mostly to
volatlles
Data typically reported
In concentration ranges
Detection limits vary
frcm low ppm to io* ppb
Eng Ineer Irvg
Screening
Level
Total organlc/1norganIc
vapor detection using
portable Instruments
Assist In sample
locations
Field screening
Health and safety
Instruments respond to
naturally-occurrfng
compounds
- If Instruments cali-
brated and data
Interpreted correctly,
can provide Indication
of contamination
Keg 11 g 1 bIe, If
capital costs
exel uded
- Rea l-tlme
MUtl /«
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Document No. 9355.0-7A
TABLE 4-2
TYPICAL ANALYTICAL SUPPORT REQUIREMENTS FOR AH Rl/FS
Rl/FS ACTIVITY
Initial Reconnaissance
On-sIte/Off-slte Subsurface
Investigations
O0JECTIVE(S)
Assess existing site conditions
general air quality tor health &
safety; collect I In!ted
environmental samples (surface
water, groundwater) If existing
data deficient; assess need for
removal, etc.
Determine extent/quantity of
on-site contamination via
borings, test pits, etc.
GENERAL
DATA CATEGORY
- Screening
Screening
Engineering
Limited
conf trmatIon
LEVEL OF
ANALYTICAL SUPPORT
Total Vapor Scan (Level 1)
Field Screening (Level II);
Collect air samples via ambient
grab or sorbent/thermal
desorb/Photovac. Headspace
analysis using OVA/Photovac all
for VOCs.
• Field screening (Level ill):
(VOCs) soil headspace analysts.
GC Screening (Level
MIMB/N/As):
If no Indicator VOCs present.
On-site or off-site lab support
determined on slte-speclf 1c
basis.
Metals wtaere Indicated.
Selected Samples for Level IV.
RATIONALE
VOCs most mobile contaminants;
likely Indicators for pathway
migration on almost real-time
basis; data to be used tor
general study design,
modification; health and safety*
VOC "tracer" compounds may be
present; study area adjusted
pending results.
Limited B/N/A data may be
required; data to be used to
guide areas of Interest; adjust
locations/focus, etc.
Need limited con11rmatton data.
On-sIte/Off-slte Monitoring Hell
Installation
"Baseline" Sampling Round
Sample all new wells; surface
water points; sediments;
additional soils, etc.
Sample all new wells; surface
water points; sediments;
additional soils, etc.
- Screening
Screen Ing
Engineering
Field screening (Level II):
(VOCs) headspace analysts.
GC Screening (B/N/As):
(Level III) If no VOCs.
Metals where Indicated.
Field Screening (VOCs) (Level
II)
GC Screening (B/N/As) (Level
*1/111)
Provide several day turnaround
Other parameters: pH, TOC,
metals, etc.
VOCs more mobile In groundwater;
data to be used to adjust well
location, determine optimum well
screen placement; check wash
water tor Induced contamination;
waste handling needs.
Provide initial data base to
begin feasibility study; use to
careful Iy design sampling plan
for CLP slots; identify any data
gaps before full demobilization
of field team.
"Confirmatory" Sampling Round
Feasibility Study Field
Activities:
- pimp tests
- pilot studies, e.g.,
water treatment.
Re-sample points based on
baseline data
Assess further slte-specltIc
characteristics tor alternative
evaluatlon
Con f 1 rmat I on
Screening
Engineering
Confirmation
- Level IV or Level Ml
Field screening (VOCs) (Level
It) - check filtration effluent
for breakthrough; air stripping
Impact, etc.
GC Screening (B/N/A) (Level 11/
III - use where these parameters
are of concern.
Metals where indicated
Level IV or Level III tor
I 1m I ted
confirmation/documentation of
treatment effectiveness.
¦ Level NS as required.
Provide litigation quality data
to document cost recovery;
confirm screening data.
Provide "real-time" assessment
of various treatment
alternatives; data to be used in
alternative evaluation; Level t
samples to provide firm record
of effectiveness*
Level NS If site-speclf1c
conditions warrant, e.g.,
establIsh ACLs.
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Document No. 935b.0-7A
Types of Analysis Available (Level NS)
Analytical support of this type may involve the research, development and
documentation of a method, or more typically, the modification of an
existing method. EMSL, Las Vegas can be consulted for protocol
availability, modification or development. Level NS methods are available
through CLP Special Analytical Services (SAS), university laboratories,
commercial laboratories, National Enforcement Investigation Center, and
Environmental Services Division. The types of analyses available through
Level NS support may ultimately be technology-limited.
Uses and Limitations (Level NS)
• Use - Site specific, used when "off the shelf" procedures listed in
other levels will not provide the needed data. Required when
analytical standard operating procedures (SOPs) are not available or
non-standard techniques are required. Uses can also include the
modification of existing methods for lower detection limits or for
tentatively identified compounds verification.
t Limitations - Other than costs, limitations include the following:
the amount of lead-time for start-up, the possible "one-of-a-kind"
application of the method, the validity of the data if insufficient
documentation is maintained; and the lack of comparabi1ity of the
data.
Considerations (Level NS)
• Data Quality - PARCC parameters must be specified. If the methods
to be used are modifications of existing methods, PARCC parameters
may be extrapolated.
• Cost - Unit costs for sample analysis is dependent on the analysis
requested. Generally, initial unit costs may be high, reflecting
the costs of becoming familiar with the method. If the method is
used for other projects or sites, unit costs may decrease with the
demand, and the method may become standard.
• Time - The principal time factor is that required for becoming
familiar with the method. Once the method is understood, turnaround
time should be method-specific.
• Relative Number of Samples Permitted - This will be determined by
factors inherent in the method and by the number of laboratories
able to perform the analysis.
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Documentation Available (Level NS)
Level NS provides specific, case-by-case analytical support. The amount of
documentation available to the user will vary depending on the sophistica-
tion of the technology used. If method development is required, this
information should be requested and reviewed by the user.
Available Accuracy, Precision and Method Detection Limit (MDL) Information
(Level NS)
There is no accuracy and precision information available for Level NS due
to the type of analytical support it provides. Specific data quality
information can best be obtained on a case-by-case basis by reviewing the
laboratory's method development work prior to submitting samples. If the
specific support required represents a modification of an existing
procedure or protocol, data quality information can be extrapolated from
the existing procedure.
4.1.3 CONTRACT LABORATORY PROGRAM (CLP) ROUTINE ANALYTICAL SERVICES (RAS)
INVITATION FOR BIDS (IFB) - LEVEL IV ANALYTICAL SUPPORT
Objectives of Analytical Support (Level IV)
The primary objective of CLP support is to provide data of known quality.
A high level of quality assurance and documentation has been incorporated
in all aspects of program activities.
Types of Analyses Available (Level IV)
Briefly, the CLP provides for the analyses of all types of media (through
both RAS and SAS) for Hazardous Substance List (HSL) organic compounds and
priority pollutant inorganic compounds. These services are available
through CLP RAS and regional EPA ESD laboratories
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Uses (level IV)
Level IV analyses are currently used for most RI/FS activities. However,
the use of Level IV data for many RI/FS purposes may not be required.
Optimum uses are confirmation of lower level data, risk assessment and
providing highly documented data.
CLP generated data provides for the following:
• Confirmed identification and quantitation of compounds (for HSL
parameters only unless otherwise specified) to the detection
specified in the IFB.
• Tentative identification of a contractually-specified number of
non-HSL parameters.
• Sufficient documentation to allow qualified personnel to review and
evaluate data quality.
• Uniform data that may be used for all Superfund program activities.
Considerations (Level IV)
• Detection limits may not be sufficient for toxicological concerns
• Cost - Complete Hazardous Substance List CLP support is one of the
most expensive routine analytical services available to the
Superfund program, e.g., RAS for full organics is about
$l,Q00/sample. RAS for full inorganics is about $200/sample.
• Time - RAS is contractually operating on a 30-40 day turnaround
although delays can occur.
• Availability - Since demands fluctuate, space may be limited at
times for the Superfund program.
Documentation Available (Level IV)
The IFB is very specific concerning the amount of laboratory documentation
that is supplied with every data package. The RAS deliverables package
contains information on initial and continuing calibration, GC/MS training,
surrogate percent recovery, and matrix spike/matrix spike duplicates. In
addition, hard copies are provided of reconstruction ion chromatograms, GC
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Document No. 9355.0-7A
chromatograms, and spectra for every sample and every blank, standard or
spike run with a particular set of samples. Documentation is also provided
for blank analyses, internal chain of custody and holding times.
Available Accuracy, Precision and MDL Information (Level IV)
The Environmental Monitoring and Support Laboratory - Las Vegas (EMSL-LV)
is currently compiling accuracy, precision and MDL information for the RAS
program, which will be incorporated in a later revision of this document.
Appendix C contains the performance criteria specified in the Statement of
Work for Organics and Inorganics Hazardous Substance List Analyses -
multi-media, multi-concentration, July 1985 revision.
4.1.4 LABORATORY ANALYSIS - LEVEL III ANALYTICAL SUPPORT
Objectives of Analytical Support (Level III)
This is designed to provide laboratory analytical support using standard
EPA approved procedures other than current CLP RAS. This level is used
primarily in support of engineering studies.
Types of Analyses Available (Level III)
Generally the analyses performed using these techniques are designed to
provide confirmed identification and quantitation of organic and inorganic
compounds in water, sediment, and soil samples. These analysis are
available through commercial laboratories, ESD, CLP SAS, and the CLP
screening service (in development).
Uses and Limitations (Level III)
This level provides data used to support engineering studies, e.g., design,
modeling and pilot/bench studies. Also can be used for site
characterizations, environmental monitoring, and confirmation of field
data.
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Level III laboratory analysis provides the following:
• Data to support engineering design parameters.
« Data for use in evaluating the site for further action, e.g., to
determine extent of environmental contamination.
• Rapid turnaround of data may be available,
• Detection limits for presence or absence of compounds comparable to
CLP RAS.
Considerations (Level III)
• Data Quality - The protocols all have built-in QA/QC, including
calibration runs, surrogate standards, etc. External QA, which is
also used for the CLP, is employed in the form of trip blanks,
replicate and duplicate samples, and blind spikes submitted with the
samples.
• Costs range up to $100Q/sample, depending on analysis.
• Time - Turnaround time for Level III laboratory analysis organics is
expected to be about 14-21 days.
• CLP screening service, when developed, may be more appropriate for
hazardous waste analysis than the SW 846 methods. This service
would utilize CLP RAS methods excluding extensive documentation.
Documentation Available (Level III)
The type of laboratory support available under Level III ranges in
sophistication from GC/MS instrumentation to the measurement of pH. The
type and amount of documentation available depends on the type of analysis
requested. Data users should review an example sample report issued by the
laboratory for the analysis requested to determine if the degree of
documentation supplied is adequate or whether additional information must
be requested.
Available Accuracy, Precision MDL Information (Level III)
Accuracy, precision and MDL information that is considered representative
of this level of analytical support was compiled from SW-846, Test Methods
for Evaluating Solid Waste Physical/Chemical Methods, Second Edition, (EPA
1982). This information is compiled in Table 4-3. These procedures are
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TABLE 4-3 SW-846 ACCURACY,
PRECISION,
, AND MDL
INFORMATION*
Method
Data
Accuracy as
Precision
MDL
Number
Method Name
Source
% Recovery
(%)
Mg/1
ORGANICS:
8010
Halogenated Volatile Organics
SW 846
75.1
- 106.1
2.0 - 25.1
0.03 - 0.52
8020
Aromatic Volatile Oranics
SW 846
77.0
- 120
9.4 - 27.7
0.2 - 0.4
8030
Acrolein, Acrylonitrile,
SW 846
96 -
107
5.6 - 11.6
0.5 - 0.6
Acetonitrile
8040
Phenols
SW 846
41 -
86
7.9 - 16.5
058 - 2.2
8060
Esters
EPA 606
82 -
94
1.3 - 6.5
0.29 - 3.0
8080
Organochlorine Pesticides
SW 846
86 -
97
1.3 - 6.5
0.29 - 3.0
and PCBs
8090
Nitroaromatics and Cyclic
SW 846
63 -
71
3.1 - 5.9
0.06/ND
Ketones
8100
Polynuclear Aromatic
NA
NA
NA
Hydrocarbons
8120
Chlorinated Hydrocarbons
SW 846
76 -
99
10 - 25
0.03 - 1.34
8140
Organophosphorous Pesticides
SW 846
56.5
- 120.7
5.3 - 19.9
0.1 - 5.0
8150
Chlorinated Herbicides
SW 846
NA
NA
0.1 - 200
8240
Volatile Organics
SW 846
95 -
107
9-28
1.6 - 6.9
8250
GC/MS Semi volatiles (Packed
41 -
143
20 -145
0.9 - 44
Column)
8040
GC/MS Semi volatiles
NA
NA
NA
(Capi1lary)
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Document No. 9355.0-7A
TABLE 4-3 SW-846 ACCURACY, PRECISION AND MDL INFORMATION*
(CONTINUED)
Method
Number
Method Name
Data
Source
Accuracy as
% Recovery
Precision
(*>
MDL
Mg/1
8310
Polynuclear Aromalic
SW 846
78 -
116
7.3
- 12.9
Hydrocarbons (HPLC)
(Capillary)
INORGANICS:
Metals (ICAP)
EPA
200.7
NA
3 -
21.9 (RSD)
7000 Series
Metals (FLAME)
EPA
200
NA
NA
7000 Series
Metals (FLAME LESS/6F)
EPA
200
NA
NA
7470
Metals (MERCURY)
EPA
245.2
87 -
125
0.9
- 4.0
9010
Cyanides
EPA
335.2
85 -
102
0.2
- 15.2
9030
Sulfides
NA Not Available
EPA
376.1
NA
NA
0.03 - 2.3
1.3 - 75 Mg/1
0.01 - 5
0.001 - 0.2 Mg/1
0.0002
0.02 Mg/1
1 Mg/1
*For water only
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Document No. 9365.Q-7A
applicable for all sample matrices; however, the quality control
information presented in Table 4-3 was derived from the analysis of water
and wastewater samples and performance evaluation standards. Therefore,
the criteria specified in this table should be considered as "best case"
information when non-aqueous media samples are analyzed. Also, these data
are presented irrespective of the sample pretreatment or preconcentration
techniques used. These techniques may include liquid-liquid extraction
(3520) acid/base-neutral clean-up extraction (3530), soxhlet extraction
(3540), sonication extraction (3550), headspace (5020), and purge and trap
(5030). They are used in conjunction with the analytical procedures
presented in Table 4-3. Use of these techniques will introduce additional
variability in the QC data and should be taken into consideration.
For the purposes of Table 4-3:
• Method Detection Limit (MOL) is defined as the minimum concentration
of a substance that can be measured and reported with 99% confidence
that the value is above zero. For the following table MDLs were
obtained using reagent grade water. The MOL actually achieved for a
given analyte will vary depending on instrument sensitivity, matrix
effects and preparation techniques used.
• Accuracy, presented as an average percent recovery, was determined
from replicate (10-25) analyses of water and wastewater samples
fortified with known concentrations of the analyte of interest at or
near the detection limit. In most cases this was less than 10 times
the MDL.
• Precision data are used to measure the variability of these
repetitive analyses reported as a single standard deviation or, as a
percentage of the recovery measurements. For presentation purposes
accuracy, precision and MDL information is presented as an average
range of individual values for every analyte covered by the
procedure. If specific information on a particular compound is
required, the specific analytical method cited should be consulted.
Maintaining quality control data bases for hazardous waste site analytical
support is a dynamic process because of new analytical instrumentation and
techniques, the trend toward improving detection limits, and an expanding
list of analytes to be evaluated. A lack of quality analytical standards,
proven analytical techniques (particularly for non-aqueous media), and a
central data base severely limits quantitation of quality control data.
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4.1.5 FIELD ANALYSIS - LEVEL II ANALYTICAL SUPPORT
Objectives of Analytical Support (Level II)
This support is designed to provide real-time data for ongoing field
activities or when initial data will provide the basis for seeking
laboratory analytical support. There have also been a significant number
of instances where data derived from field analytical techniques have been
the sole basis for making decisions about site disposition or health and
safety.
Field analysis involves the use of portable or transportable instruments
which are based at or near a sampling site. The most common type of field
analysis is the use of portable gas chromatographs to analyze soil, air and
water samples for volatile organic compounds. The analysis is typically
conducted in a mobile van or trailer, and can generate quantitative and
semiqualitative data. Field analysis should not be confused with the
process of obtaining total vapor readings using portable meters.
Types of Analysis Available (Level II)
Field analysis can provide data from the analysis of air, soil and water
samples for many Hazardous Substance List (HSL) organic compounds, includ-
ing volatiles, Base/Neutral/Acid (B/N/A) extractable organics, and
pesticides/PCBs. Inorganic analysis can also be conducted using portable
atomic absorption (AA) or other instruments. These analyses can be
obtained through ESD or remedial contractors.
The simplest type of field analysis is for volatile organic compounds.
Since the headspace analytical technique is used, the sample preparation is
minimal. Extractable organic and inorganic analyses require additional
time and equipment.
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Document No. 9S55.0-7A
Uses and Limitations (Level II)
Uses. Used for onsite, real-time screening, baseline data development,
extent of contamination and onsite remedial activities. Time and
the number of samples are a major benefit of the use of this support
level.
Field analytical techniques provide the following:
• Rapidly available data for a variety of activities including
hydrogeologic investigations (establish depth/concentration profiles
as wells are installed); cleanup operations (determine extent of
contaminated soil excavation); and health and safety (determine
nature and extent of release to ambient air).
• Detection limits for volatiles range from 0.5 ppb in air; 2-3 ppb in
water; 10 ppb for soil. Detection limits for PCBs in soil are about
1.0 ppm. Detection limits for extractable organic compounds
analyzed in mobile labs are in the vicinity of 10 ppb.
• Special applications - e.g., vadose zone monitoring.
• Volatile organic data can be used as early indicator or tracer of
off-site contaminant migration. Volatiles are the most mobile of
contaminants in all media, and are typically found at some
concentration at virtually all sites.
Limitations. Field analysis generated data have the following limitations:
• Subject to Interferences in complex matrices.
t Rapid analysis techniques are most applicable for volatile organic
compounds. Most of the literature and procedures for field analysis
pertains to volatiles.
• Trained personnel and equipment must be available to perform the
field analyses.
• Data must be reported as tentative.
Considerations (Level II)
• Data Quality - The ability to assess data quality for field
activities is dependent upon the QA/QC steps taken in the process,
e.g., documentation of blank injections, calibration standard runs,
runs of qualitative standards between samples, etc.
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Document No. 9355.0-7A
• Cost - If capital expenditures are excluded, the costs of field
analysis are in terms of personnel time in performing analyses,
preparation/maintenance of equipment, etc. Costs for mobilizing and
staffing a field laboratory will increase per-sample costs. Based
on limited data from Region I FIT experience-, per-sample costs for
volatile and inorganic analyses are approximately $15. Per-sample
costs for mobile laboratory analyses may approach $100.
• Time - Depending on the type of analysis, time requirements per
analysis ranges from 10 minutes to 1-2 hours.
Documentation Available (Level II)
Since this is a field operation, the amount and type of documentation
available will vary with the type of analysis and the standard operating
procedures used. Typically, a gas chroinatograph operated in the field
provides the bulk of the analytical support at this level. The
documentation available utilizing this level of analytical support would
consist of the output of the strip chart recorder for all samples,
standards, and blanks analyzed. Field and analysis log books would also be
a source of additional documentation.
Available Accuracy, Precision and MDL Information (Level II)
At this writing, the data base for documenting accuracy, precision and MDL
information for Level II analyses is sparse. A number of factors have
recently stimulated an interest in the development of Level II methods.
This activity is centered primarily in various EPA Environmental Service
Divisions (ESD) and remedial contractors. Two ongoing projects which will
contribute significantly to the Level II data quality criteria data base
are scheduled for completion by the end of 1985. These projects are an EPA
Headquarters-directed compilation of all Level II analytical methods
currently used by Field Investigation Teams (FITs) and the operation of a
mobile field analytical laboratory being directed by EPA/ESD in Region IV.
The Region IV project, in particular, holds the promise of a significant
contribution, since virtually all organic Hazardous Substance List (HSL)
parameters are being analyzed for. As these data become available they
will be incorporated into this document. Due to the increasing interest in
this analytical support level, QC data from many different sources should
be available soon.
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Table 4-4 summarizes available data regarding specific Level II methods.
Split samples are analyzed for metals and volatile organics by field
procedures and the CLP.
4.1.6 FIELD SCREENING - LEVEL I ANALYTICAL SUPPORT
Objectives of Analytical Support (Level I)
The objective of this type of analysis is to generate data which can be
used in refining sampling plans and in determining the extent of
contamination. This information supplements background data and visual
evidence of contamination pathways. A second objective is to conserve
other analytical support resources. This type of support also provides
real time data for health and safety purposes.
Types of Analysis Available (Level I)
This type of analysis is generally limited to total vapor readings using
portable photoionization or flame ionization meters which respond to a
variety of volatile inorganic and organic compounds. Detection is limited
to volatiles which have characteristics enabling them to be measured by the
respective instruments. These analyses are available through ESD or
remedial contractors.
Uses and Limitations (Level I)
Uses. Provides data for onsite, real-time total vapor measurement,
evaluation of existing conditions, sample location optimization,
extent of contamination, health and safety evaluations. Data
generated from this type of analysis provide the following:
• Identification of soil, water, air and waste locations which have a
high likelihood of showing significant contamination through
subsequent analysis.
• Real-time data to be used for health and safety considerations
during site reconnaissance.
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TABLE 4-4 FIELD ANALYTICAL SUPPORT ACCURACY INFORMATION
Range of Accuracy
Method Expressed as Relative Percent Difference*
1. Volatile organics in water; 50
headspace prep, followed by
GC/PID
2. Total metals in soil and water; <50
Soils-direct analysis
water-ion exchange
followed by X-Ray
fluorescence analysis
*These values were determined by a comparison of replicate or duplicate
(metals) analysis. The "true" value was designated to be a CLP value. No
precision value data are available. Source: Region I FIT.
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• Quantitative data relative to a primary calibration standard if the
contaminant(s) being measured are unknown.
• Quantitative data if a contaminant is known and the instrument is
calibrated to that substance.
• Presence or absence of contamination.
Limitations. Data generated in this manner have the following limitations:
t Some instruments show a response to naturally occurring,
non-hazardous substances (methane) or other possible interferences.
Data from instruments may also be affected by weather and operator
skill and interpretive ability.
• Quantitative data for total organics.
0 Qualitative data cannot be produced.
Considerations (Level I)
• Data Quality - Standard operating procedures are followed to insure
that the instruments are calibrated and responding properly prior to
field use. Calibration logs are maintained for each instrument and
special training is provided to all personnel.
• Cost - Capital expenditures aside, the cost associated with using
this approach to field screening is minimal.
• Time - Data provided are real-time.
Documentation Available (Level I)
A hardcopy strip chart recorder output can be obtained for instrumentation
operated in the general total vapor survey mode but it is not common
practice. The most available form of documentation for this support level
is the field operator log book. Sample identification, location,
instrument reading, calibration and blank information is usually contained
in the field log book.
Available Accuracy, Precision and MDL Information (Level I)
There are no data quality criteria specified for Level I, Field Screening
Support, because this level is characterized by the use of non-qualitative,
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hand-held instrumentation (HNu PI 101, OVA 128, etc.). This instrumenta-
tion measures total organic vapor concentrations only, and as such, is not
conducive to the generation of qualitative data.
4.2 STAGE THREE-B: SAMPLING PLAN APPROACH
-- To be developed --
4.3 OUTPUT OF THE RI/FS DQO PROCESS
The output of the RI/FS DQO process is a well defined sampling and
analytical plan. This plan may be written as a separate document or as
part of the sampling/analysis plan or the quality assurance project plan
(QAPP). Sampling and analytical considerations must be thoroughly
addressed in order for data quality objectives to be developed. A sampling
and analytical plan written for individual activities is the best vehicle
for this purpose. This data quality objectives should be developed in a
separate section of the sampling analytical plan outlining the rationale
behind each separate development stage. Included in this DQO section
should be a chart which contains the most important objectives and comments
for each DQO development stage.
It is extremely important that the sampling and analytical components of
individual RI/FS activities are not developed independently of each other.
To a certain degree, each component has Stage Two conditions that must be
satisfied. Examples of these conditions can be a specific MDL that is
required of the analytical component and specific locations that must be
sampled as a requirement of the sampling component. However, as long as
all component-specific requirements are held constant, a completely
integrated sampling and analytical approach can be developed. The optimum
approach may be one which incorporates multiple levels of analytical
support with a sampling plan design that is specific for each level of
analytical support utilized.
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5.0 IMPLEMENTATION OF THE DQO PROCESS - CASE STUDY
5.1 CASE STUDY SCENARIO - XYZ SITE
The XYZ site is located in Hampshire County, Massachusetts on the outskirts
of the town of Idlewild (pop. 35,000). Figure 5-1 (not to scale) is a
schematic representation of the XYZ site and surrounding area. The site
occupies about 5 acres of cleared land and is entirely surrounded by a
chain-link fence. Access to the site is provided by a gate just off State
Route 123, which abuts the northern site boundary. Approximately 0.2 mile
east of the site, along Route 123, is a retirement apartment complex which
houses 120 senior citizens. Several private residences are scattered
through the area southeast of the site. Each is served by a private well.
Two municipal production wells (#1 and #2) are located about 0.6 mile from
the XYZ site along the Rambling River. Municipal well #3 is located across
the river opposite municipal well §2. The southwestern portion of the site
is bordered by a swamp which feeds the headwaters of Muddy Creek. Muddy
Creek flows south through Muddy Creek State Park and enters the Rambling
River at a point about 1 mile upstream of the Idlewild municipal well
field.
5.1.1 SITE HISTORY AND WASTE DISPOSAL FEATURES
The XYZ site was operated over a period of 15 years as a drum recycling and
metal salvage operation. Local waste haulers would typically bring in used
drums for reconditioning. Invariably, the drums contained small quantities
of waste solvent which were disposed of by dumping into an unlined pit
(Area A on Figure 5-1) located behind the drum washing building. A former
employee of the facility filed an affidavit with the state agency in which
the employee alleged that full drums of spent solvent from a local
electronics firm were emptied into the solvent pit over several years'
time. The quantities of wastes discharged to the pit are unknown.
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MUDDY CREEK
STATE PARK
STATE ROUTE 123
IDLE WILD
UNI C IP A L
WELL FIELD
XYZ SITE
# 3
LEGEND:
\ - solvern pi f
B - inAHSFOIIMEft DISPOSAL PILE
C - SUSPEClF.t) Ootl WASTE AREA
<^ MOMIIOMIIir. WEIL
( I rniVAIF. MOUSE'WELL
• MutncirM ritnuuciion well
Orf'EdAL GIIOUNDWAlf M ("LOW OinECIION
IDLEWtLD, MA.
FIGURE 5-1
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The pit measures about 60 feet by about 80 feet, and has an average depth
of 4 feet.
Empty drums were washed in a hot caustic bath located inside the drum
washing building (shown on Figure 5-1). The drums were then rinsed, dried,
painted and sold as reconditioned drums. Both the caustic bath and rinsate
water were discharged to a sewer under a permit issued by the regional
wastewater treatment authority. The terms of the permit required only that
the pH of the caustic bath be adjusted prior to discharge into the sewer.
The site owner also collected over several years a large number of old
transformers which were piled directly upon the ground (designated Area B
on Figure 5-1). The majority of these transformers were in poor condition
and leaking oil containing polychlorinated biphenyls (PCBs). The
dimensions of the transformer storage area are approximately 50 feet by 100
feet.
Based upon information obtained from the affidavit filed by the former
employee, it is also suspected that at one time during the site's history,
a number of drums suspected to contain a highly toxic military agent,
ricin, were brought to the site. The origin of the drums is alleged to be
a Department of Defense (DoD) research facility. The drum contents were
allegedly emptied Into a natural depression area on the site and covered
over with native soil. This area is designated as Area C on Figure 5-1.
Ricin is a castor bean derivative and is typically in the form of a solid
white powder. The alleged disposal area measures about 10 feet by 20 feet.
In late 1983, as a result of increasing state and federal regulatory agency
attention and public interest, the owner ceased operations at the site and
fled to Mexico. Prior to leaving, the owner destroyed all documents
related to site operations.
5.1.2 HYDROGEOLOGIC FEATURES
The XYZ site and its surrounding areas are underlain by sand and gravel.
The thickness of this unconsolidated layer ranges from 30 feet near the
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site to over 100 feet in the vicinity of the Idlewild municipal well field.
A continuous layer of tight till is present on the bedrock surface
throughout the site area. It is believed that the bedrock surface has a
minimal number of fractures.
Depths to bedrock range from 40 feet below ground surface near the XYZ site
to over 100 feet in the vicinity of the Idlewild municipal wellfield.
Thus, the bedrock surface slopes downward in a southeasterly direction away
from the XYZ site toward the Rambling River.
The aquifer present in the unconsolidated sediments of the XYZ site area is
highly productive. The general direction of ground water flow in this
aquifer follows the bedrock surface previously described. That is, ground
water flow is generally southeasterly from the XYZ site vicinity to the
Rambling River. Oepths to ground water range from 5-10 feet near the XYZ
site to 2-5 feet in the vicinity of the Idlewild municipal wellfield. The
thickness of the aquifer in the vicinity of the Idlewild municipal
wellfield is 95 to 100 feet. Yields are estimated to be in excess of 400
gallons per minute (gpm).
Surface water and shallow ground water discharge on the southwest border of
the XYZ site is to the swamp located there. The swamp is heavily vegetated
and consists of a 10-foot layer of peat overlying lake bottom deposits and
till. Muddy Creek drains the swamp, flows through Muddy Creek State Park
and enters the Rambling River about one mile upstream of the Idlewild
municipal wellfield.
5.1.3 EXTENT OF CONTAMINATION
Information regarding extent of contamination is primarily derived from the
site inspection activities conducted jointly by the state and EPA during
early 1983. These activities also led to the placing of the site on the
National Priorities List (NPL) and the subsequent funding of a remedial
investigation/feasibility study (RI/FS) for the site. The following
summarizes data gathered during the site inspection activities.
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Onsite Contamination
The following data were collected during the site inspection:
• Area A - Solvent Pit - Dimensions approximately 60 feet wide by 80
feet long; average depth 4 feet below ground surface. In early
spring, small pockets of standing water were observed. In the
summer, the pit was dry and appeared to contain a mixture of sawdust
(used as an absorbent for the drum reclamation process) and native
soil. OVA and HNu readings of 5-10 parts per million (ppm) were
recorded just above the surface at several areas around the pit. A
shovel was used to break the surface of the pit bottom at several
random locations. In every case, total vapor readings exceeded
1,000 or 2,000 ppm. Several random soil samples were obtained from
depths of 6 inches to 1 foot from the bottom of the pit. The most
predominant compounds and their concentration ranges were:
Although analyses were conducted for other organic compounds and
inorganic parameters, none were detected.
• Area B - Transformer Pile - Dimensions approximately 50 feet wide by
100 feet long; height of pile 3-5 feet above ground surface.
Evidence of numerous leaks of transformer oil observed. Several
samples were obtained from around the pile area. Samples were
analyzed for all Hazardous Substance List (HSL) parameters; however,
PCBs were the predominant contaminants detected. Total PCB
concentration ranges were 1,000 ppm to 10 percent. The site
inspection team also observed evidence of surface runoff and soil
erosion from the vicinity of Area B toward the swamp at the
southwest corner of the site. Several soil samples obtained from
along the surface runoff erosion areas were collected and found to
contain total PCB concentrations of 50-100 ppm.
• Area C - OoD Waste Disposal Area - The site inspection team observed
signs of soil disturbance in this area. Also, vegetation was
noticeably absent from this area. The team surveyed the area with
metal detection equipment and a ground penetrating radar unit. No
evidence of buried containers was found. A request was made through
EPA's Contract Laboratory Program (CLP) for sample analysis for
ricin. The CLP could not provide this analytical service, even
through its Special Analytical Services (SAS) program. No samples
were obtained from this area.
Tri cMoroethylene
Trans-I,2-dichlaroethylere
1,1,1-Trichloroethane
Benzene
Toluene
10-50 ppm
10-16 ppm
20-40 ppm
1Q3-20 ppm
100-1500 ppm
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Offsite Contamination
The site inspection team subsequently installed and. sampled three shallow
ground water monitoring wells, as indicated on Figure 5-1. A sample from
the well at the northwest corner of the site was analyzed by the CLP and
found to be free of contaminants, and is apparently upgradient of the site.
Samples obtained from both wells to the east and southeast of the site
contained several volatile organics in the following concentration ranges:
Several private drinking water wells southeast of the site were sampled,
analyzed and found to contain volatile organics at the following levels:
The state and EPA collected samples from Idlewild municipal wells #1, #2,
and #3. The wells were sampled while all were pumping. The following
volatile organic compounds were detected:
Trichloroethylene
Trans-1,2-di chloroethylene
1,1,1-Trichloroethane
Benzene
Toluene
5-10 ppm
1-5 ppm
1-5 ppm
10-20 ppm
50-100 ppm
Trichloroethylene
Trans-1,2-dichloroethylene
1,1,1-Trichloroethane
Benzene
Toluene
20-30 parts per billion (ppb)
ND
ND
100-200 ppb
100-200 ppb
Municipal Well #1
Trichloroethylene
Trans 1,2-dichloroethylene
1,1,1-trichloroethane
Benzene
Toluene
1500 ppb
100 ppb
50 ppb
15 ppb
10 ppb
Municipal Well #2
Trichloroethylene
Trans 1,2-dichloroethylene
1,1,1-trichloroethane
Benzene
Toluene
ND
ND
ND
100 ppb
20 ppb
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Municipal Well #3 All ND
NOTE: All samples analyzed through CLP.
Several sediment samples were collected from the swamp southwest of the
site and from several points along Muddy Creek. PCBs were detected at
concentrations ranging from 15-50 ppm.
5.1.4 CURRENT STATUS
As a result of the data collected during the site inspection activities
described above, the following immediate response actions were taken:
• Idlewild Municipal Wells #1 and #2 were taken out of service. This
eliminated 40% of the town's water supply and forced the town to
purchase water from a neighboring town to meet existing demands.
Plans for proposed industrial and residential expansion, whose water
needs were to be supplied by the development of additional wells
along the Rambling River have been placed on hold.
• Idlewild Municipal Well #3 is being sampled and analyzed for
volatile organic parameters on a weekly basis.
• Private residences where volatile organic compounds were detected in
drinking water well samples are being supplied with bottled water.
• EPA secured the XYZ site, collected the oil from transformers
remaining in the pile, removed empty transformers offsite and placed
a berm around Area B to prevent further runoff and erosion of
contaminated soil from the site to the swamp. Synthetic liners were
placed over areas A (solvent pit) and C (t)oD wastes).
• An RI/FS has been scheduled to begin immediately.
5.1.5 DATA COLLECTION ACTIVITIES
The scoping of the Rl/FS has identified the following general data needs to
support remedial alternatives evaluation:
t Source Control Measures - The volume of contaminated soil in areas
A, B, and C must be determined in order to evaluate onsite or
offsite disposal and/or treatment options. This can be accomplished
through a subsurface investigation to obtain the dimensions of the
contaminated areas.
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• Management of Migration Measures - The principal question to be
addressed involves the ground water contamination resulting in the
closure of Municipal Wells #1 and #2. It will be assumed for the
purposes of this example that aquifer restoration in order to place
municipal wells #1 and #2 back into service is the leading alterna-
tive, both from a political and technical perspective. Data
collection activities during the RI and FS should therefore focus
upon aquifer restoration. This will involve the collection and
analysis of ground water samples during pumping tests, bench-scale
treatment studies and pilot tests.
A secondary management of migration issue is the movement of PCB
contaminated sediments in Muddy Creek. For the purposes of this
presentation, it will not be addressed further, except as it relates
to conducting a risk assessment.
Another secondary issue is the release of airborne contaminants from
the site. Again, this will not be addressed, except as it relates
to conducting a risk assessment.
5.2 SOURCE CHARACTERIZATION FOR REMOVAL
To be prepared
5.3 PUBLIC HEALTH EVALUATION/ENDANGERMENT ASSESSMENT
To be prepared
5.4 FS DESIGN/PILOT STUDY
Based on the case study scenario of the XYZ site, two water supply wells
for the town of Idlewild are contaminated with volatile organic compounds
and had to be shut down, reducing the town water supply to 60% of current
demand. As a result of this shortage, proposed industrial and residential
expansion has been put on hold. The immediate goal of the RI/FS program
must be to improve the ground water quality for re-use as a drinking water
supply.
Both from a practical and an economic perspective, the preferred remedial
alternative is to place both municipal wells back into service as soon as
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possible. One of the most promising methods to restore the aquifer is well
head treatment. Toward this end, further discussion in this section will
deal with the development of treatability studies/pilot tests to evaluate
the feasibility of well head treatment.
Based on the nature of the chemical constituents found in the contaminated
well field, there are a number of treatment options with proven reliability
that will be evaluated for this application. The most promising are air
stripping using a packed tower, carbon adsorption or some combination of
the two. The final selection of the treatment process will be determined
by treatability assessments of these and several other leading technolog-
ies. For the purposes of this example, DQOs will only be developed for the
air stripping option.
Both municipal wells are contaminated with trichloroethylene and 1,2
dichloroethylene in appreciable quantities, while municipal well #1 also
has detectable levels of 1,1,1-trichloroethane, benzene and toluene. The
objective of any well head treatment system is to reduce these contaminants
to concentration levels that are protective of human health and the
environment. The stated action levels for this treatability study will be
to achieve concentration levels below the excess lifetime cancer risk of
-6
10" for the drinking water supply. Trichloroethylene (TCE) has an
estimated excess lifetime cancer risk of 10"6 at a concentration of 2.8
ug/1. Therefore, the action level for TCE will be set at 2.8 ug/1. In
addition, the effluent criteria of the treatment system will be established
at a total volatile organic compound concentration of 5.0 ug/1 which takes
into account the initial concentration of other contaminants present.
Pilot studies usually require a wide range of analytical support services.
Because this support plays such a key role in the process, DQOs have to be
developed to assure that the data collected are consistent with their
intended use. The remainder of this section will focus on the development
of data quality objectives for the air stripping treatment option. DQOs
will not be developed for the other alternative.
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5.4.1 AIR STRIPPING PILOT STUDY
Initially, batch experimental runs are conducted in. a packed tower under
set conditions of water flow rate, air flow rate, packing height, and
packing material. Analytical samples of the tower water effluent are
collected for each set of operating conditions to determine the removal
efficiency for those conditions. In some cases, a target or surrogate
parameter can be used as a screening mechanism to measure the effectiveness
of each set of operating conditions. For the air stripping process, one of
the least strippable organic compounds found in the water supply (based on
Henry's Law constants) is selected as the target parameter. However,
concentration levels also affect this choice. Quantifiable analysis need
only be performed for this specific "worst case" volatile organic compound.
In the case of municipal well #1, trans-1,2 dichloroethylene would be used
as the surrogate or target parameter to evaluate the effectiveness of the
treatment system for all volatile organic compounds. This compound,
although not the least strippable compound, (toluene is the least
strippable) is found in the water at concentration levels high enough to
allow quantification in the treatment effluent. Trans-1,2 dichloroethylene
also has a Henry's Law constant similar to toluene. For municipal well #2,
which only has two detectable contaminants, trichloroethylene would be used
as a surrogate or target parameter since it is found in concentration
levels high enough to quantify in the treatment effluent. However, since
these two contaminants have significantly different Henry's Law constants,
both contaminants should be quantified in order to evaluate fully the
treatment system's removal effectiveness.
The three phases of the air stripping pilot studies are (1) the
optimization of operating parameters, (2} the monitoring of a continuous
run at set operating conditions, and (3) the development of design criteria
for a full scale facility.
The tables on the following pages outline the data quality objectives
developed for the three phases of the air stripping pilot studies.
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5.4.2 STAGE ONE: DEFINITION OF PROGRAM OBJECTIVES FOR THE AIR STRIPPING
TREATMENT OPTION
Pilot studies will be conducted for the purposes of obtaining engineering
data for three phases that entail (1) the optimization of operating
parameters; (2) the monitoring of a continuous pilot run; and (3) the
development of design criteria for a full scale facility. The objectives
for each are discussed below.
Optimization Phase
The primary goal of the optimization study is to determine the most effec-
tive set of operating parameters. Additionally these data will be used to
determine the sensitivity of each parameter to overall system performance.
The data collection activities for this subtask will require the use of
real-time analysis for a large number of samples. The ability of the
analysis to detect a wide range of contaminant concentrations (20-5,000
ug/1) is required. A fixed set of operating parameters for the continuous
pilot run will be developed during this phase.
Monitoring Continuous Operation Phase
The primary goal of the monitoring study is to evaluate the technical
performance of the treatment system at set operating parameters. The
variability of contaminant removal will be assessed with respect to
variable environmental conditions (i.e. weather changes). The data
collection activities for this subtask will require a turnaround time of
about two days for a limited number of samples to insure the proper
operation of the pilot system. Influent samples will have concentration
levels within the range of 50-2,000 ug/1 for particular organics whereas
effluent samples may have concentration levels as low as 1-10 ug/1. A
technical assessment of air stripping as a feasible well head treatment
system will be made based on these data. At this point, the next phase of
the pilot study would proceed only if a favorable technical assessment was
concluded.
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Stage 1
Stage 2
Stage 3
DATA QUALITY OBJECTIVES FOR AIR STRIPPING PILOT STUDY
OPTIMIZATION PHASE
• Optimize operating parameters
• Establishment of optimum operating conditions
• Real-time analysis with the capability for a wide range of
concentration levels (5-2,000 ug/1)
• The lowest achievable contaminant concentration levels in
the effluent available using real-time procedures
• Screening quality data
• Minimal QA/QC required
• PARCC parameters addressed in text
• Portable gas chromatograph utilizing the headspace
technique to analyze for.volatile organics of concern
• No method modification
• Data are suitable for optimization only
• Blanks will be included at 20%
• Replicates will be included at 20%
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Stage 1
Stage 2
Stage 3
DATA QUALITY OBJECTIVES FOR AIR STRIPPING PILOT STUDY
MONITORING CONTINUOUS OPERATION
• Monitor treatment variability with respect to changes in
conditions
• Treatment feasibility for drinking water supply
• Rapid turnaround analysis (2 days) and cost effective
• Drinking water standards for use in this analysis are 1.0
x 10" excess lifetime cancer risk.
• Engineering quality data
• Higher degree of certainty required
• PARCC parameters addressed in text
• Commercial laboratory analysis utilizing SW-846 procedures
• No method modification
• Detection limits for GC/MS - 5-10 ug/1
• Detection limit for GC - .2-2 ug/1
• Data suitable for monitoring pilot plant operation and
determining overall suitability of this treatment option
• Blanks will be included at 10%
• Duplicates will be included at 10%
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Stage 1
Stage 2
Stage 3
DATA QUALITY OBJECTIVES FOR AIR STRIPPING PILOT STUDY
DESIGN CRITERIA FOR FULL SCALE FACILITY
The development of specific design criteria for the design
of a full scale facility
Confirmational evaluation of treatment effectiveness for a
drinking water supply
Highest level of certainty and documentation required to
assure the quality of the treated water
Drinking wateg standards of all contaminants must be below
the 1.0 x 10" excess lifetime cancer risk
• Confirmational quality data
• Maximum level of QA/qc and documentation required
• Highest degree of PARCC character!sties as addressed in
text
• Contract laboratory program routine analytical services
• No method modification
t Detection limit for GC/MS data approximately 5-10 ug/1
t Data is suitable for all RI/FS purposes
• Blanks will be included at 10%
• Replicates will be included at 107o
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Design Criteria Phase
The primary goals of the design study are to determine (1) design criteria;
(2) Special management needs; (3) maximum waste loadings; and (4) costing
information for a full scale facility. The data quality for this must meet
the most stringent degree of precision and accuracy due to the costs
incurred with the implementation of a full scale treatment facility.
Effective use of the treated water as a drinking water supply necessitates
the need to provide adequate safety factors into the design. The ability
of the analysis to accurately determine low concentration levels down to 1
ug/1 in a reproducible manner is required. The development of a properly
designed well head treatment system for a drinking water supply is
dependent on the results of the data analysis in this phase of the study.
5.4.3 STAGE TWO: ESTABLISHMENT OF DATA QUALITY REQUIREMENTS
As stated previously, there are three general phases of the air stripping
pilot study (optimization, continuous monitoring and design phase). Data
quality requirements will be developed independently for each phase.
Optimization Phase
The special requirements identified in Stage One for the optimization phase
are the need for real-time, cost effective data collection. To meet this
requirement, all analytical support required for this phase will be
performed at the pilot plant in the treatability trailer. Integration of
analytical support levels is not feasible due to the real-time constraint,
and on-site analysis is considered sufficient for this phase.
Generally speaking, the data required by this phase of the pilot study are
of screening quality. Documentation and overall QA/QC requirements are
minimal. Data must be of sufficient quality for the optimization of the
pilot plant, no more or no less data quality is required.
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The PARCC parameters for the optimization phase, using the above approach
for the analysis of the compounds of interest, are addressed below.
Precision. The precision of this technique has been reported in the field
to be within 50% relative percent difference (RPD)(Table 4-4, Section 4.0).
Precision will be assessed using replicate samples. The 50% RPD value will
be used as a goal for concentrations at or near the detection limit.
Accuracy. There are no percent recovery data available for this procedure.
A percent recovery range of 75-110% will be used as a goal, using matrix
spike technique. Both field and method blanks will be utilized to check
for false positive bfas.
Representativeness. Samples will be taken from an influent and effluent
spigot hard plumbed into the process stream. Samples will be drawn after
the process has been allowed to run for a minimum of 30 minutes to allow
the process to "warm-up." Samples will not be taken when the system is in
a start-up or shut-down mode.
Completeness. The treatment process will be optimized using pairs of
influent/effluent data points. As such, influent data will not be usable
without the corresponding effluent value and vice versa. The optimization
phase of this pilot study will be complete when the process reaches
equilibrium, achieving the highest attainable removal efficiencies. Pairs
of samples will be taken corresponding to the adjustment of individual
process variables.
Comparabi1ity. Samples will be analyzed under identical conditions (same
instrument, operating conditions, SOP, etc.). All results will be reported
in ug/1 and percent removal.
Continuous Monitoring Phase
After the completion of the optimization runs, a continuous operation will
be conducted at the selected operating conditions. The special
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requirements identified in Stage One for this phase of the pilot study are
the need for both real-time and quick turnaround laboratory data. The bulk
of the data collected in support of this phase will, be from a single level
of analytical support (Level III). This is because operating conditions
are constant and real-time analysis is not required. Samples will be
collected periodically and sent out for analysis. However, the portable
gas chromatograph used in support of the optimization phase will be used
occasionally to verify real-time conditions.
In general, the data quality requirements for this phase would be
classified as engineering quality. The rationale for this is that for the
predesign phase, the data have to be generated with more certainty than for
screening. This will be accomplished by utilizing a commercial laboratory,
where analyses are conducted under a more controlled environment.
The PARCC parameters for the continuous monitoring phase are addressed
below.
Precision. The precision of Method 8240, as reported in SW-846, is
reported as the range of the standard deviations of the percent recovery
data, reported as a percentage. The range for method 8240 is reported to
be between 9 and 28%, depending on the particular compound. The precision
of method 8010 is 2-25.1% and the precision of method 8020 is 9.4-27.7%,
reported as the range of the standard deviations of the percent recovery
data, reported as a percentage.
Accuracy. The accuracy of method P240, as matrix spike recovery, is
reported to be in the range of 95-107%. The accuracy of method 8010 is
75.1-1-6.1% and the accuracy of method 8020 is 77.0-120%, both reported as
matrix spike percent recovery.
Representativeness. See Representativeness, Optimization Phase.
Completeness. See Completeness, Optimization Phase.
Comparability. See Comparability, Optimization Phase.
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Document No. 9355.0-7A
Design of Full Scale System Phase
After the successful completion of the continuous monitoring phase to
establish the feasibility of the stripping option, the design phase is
started if the decision is made to proceed. There are no special
requirements for this phase other than the need for data of high quality.
In general, the data for this phase would be classified as confirmational
quality. The rational for this is that since these data are for design
purposes, a high degree of certainty and documentation is required.
The PARCC parameters for the design phase of this pilot study are addressed
below.
Precision. The contract required Relative Percent Difference (RPD) range
for volatile organic analysis is listed in Appendix C.
Accuracy. The contract required matrix spike recovery ranges for volatile
organic, acid/base-neutral extractables are listed in Appendix C.
Representativeness. See Representativeness, Optimization Phase.
Completeness. See Completeness, Optimization Phase.
Comparability. See Comparability, Optimization Phase.
5.4.4 STAGE THREE: SELECTION OF ANALYTICAL SUPPORT OPTIONS
Optimization Phase
To best meet the requirements established in Stage Two, headspace technique
portable gas chromatography will be used in support of this phase. There
are no modifications to the procedure. Specific equipment, operating
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Document No. 9355.0-7A
conditions, and SOPs are included in the work plan. In addition, one
influent sample will be analyzed by the CLP RAS for the entire Hazardous
Substances List (HSL) to determine if there are any. other parameters
besides volatile organics that may be of concern. Analytical data
collected using the portable gas chromatograph can only be used for
optimizing the pilot plant process. It is not suitable for any other
purpose.
Continuous Monitoring Phase
A commercial laboratory utilizing SW-846 procedures will be used in support
of this phase. There are no method modifications required. The analytical
approach to be taken requires that all influent samples be analyzed by
SW-846 procedure 8240 and all effluent samples be analyzed by SW-846
procedures 8010 and 8020. Sample pretreatment in both cases will be SW-846
method 5030, purge and trap. The rationale for this approach is as as
follows: Gas chromatography/mass spectrometry (GC/MS) technique (method
824) is utilized for the influent samples due to the high degree of
qualitative certainty it provides in determining not only the compounds of
interest but the identification of any other compounds that may be present.
Gas chromatography procedures (8010, 8020) are utilized for the effluent
samples because the identifications have already been established and most
importantly, the detection limits for this procedure are lower. GC/MS
techniques provide the qualitative certainty required, and the GC
techniques provide the low detection limits required.
In addition, one pair of influent and effluent samples will be analyzed by
the CLP RAS for confirmational purposes. The data produced using these
procedures are suitable for monitoring pilot plant operation and
determining the overall suitability of this treatment option.
Design Phase
CLP RAS analysis will be used in support of this phase. There are no
modifications required. The data collected for this phase is suitable for
all uses, Including the evaluation of drinking water requirements.
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Document No. 9355.0-7A
The quality control sample level of effort is as follows for all phases.
Optimization Phase
20% blanks
20% replicates
Continuous Monitoring and Design Phases
10% blanks
10% replicates
5.5 HEALTH AND SAFETY SITE CHARACTERIZATION
To be added
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Document No. 9355.0-7A
6.0 BIBLIOGRAPHY
American Public Health Association, American Water Works Association, Water
Pollution Control Federation. 1975. Standard Methods for Examination of
Water and Wastewater, 14th Ed.
American Society for Testing Materials. 1976. Annual Book of ASTM
Standards, Part 31, "Water", Standard D3223-73, p. 343
Bishop, J. N. 1971. Mercury in Sediments, Ontario Water Resources Comm.,
Toronto, Ontario, Canada
Boston Society of Civil Engineers. 1985. Controlling Hazardous Wastes.
Lecture Series.
Brandenberger, H, and Bader, H. 1967. The Determination of Nanogram Levels
of Mercury in Solution by a Flameless Atomic Absorption Technique, Atomic
Absorption Newsletter 6, 101
Camp Dresser & McKee Inc. 1985. Performance of Remedial Response
Activities at Uncontrolled Hazardous Waste Sites, Technical Operations
Manual. April
Clay, P. F. and Spittler, T. M. 1982. The Use of Portable Instruments in
Hazardous Waste Site Characterizations, Proceedings of the Third National
Conference on Management of Uncontrolled Hazardous Waste Sites,
Washington, D.C.
Ecology and Environment, Inc. 1982. FIT Operations and Field Manual, HNu
Systems PI 101 Photoionizatlon Detector and Century Systems Model OVA-128
Organic Vapor Analyzer, prepared for U.S. EPA, Washington, D.C.
Garbarino, J. R. and Taylor, H. E. 1979. An Inductively-Coupled Plasma
Atomic Emission Spectrometric Method for Routine Water Quality Testing.
Applied Spectroscopy 33, No. 3
Gouldten, P. D. and Aighan, B. K. 1970. An Automated Method for Determining
Mercury in Water. Technicon, Adv. in Auto. Analy. 2, p. 317
Government Institutes. 1982. Superfund Comprehensive Environmental
Response, Compensation, and Liability Act of 1980. Third Edition.
Hatch, W. R. and Ott, W. L. 1968. Determination of Sub-Microgram Quantities
of Mercury by Atomic Absorption Spectrophotometry, Analytical Chemistry
40, 2085
Jacot, Brian. 1983. OVA Field Screening at a Hazardous Waste Site,
proceedings of the Fourth National Conference on Management of
Uncontrolled Hazardous Waste Sites, Washington, D.C.
Kopp, J. F., Longbottom, M. C. and Lobring, L. B. 1972. Cold Vapor Method
for Determining Mercury, AWWA, Vol. 64, p. 20. January.
AW3-3
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Lockheed Engineering arid Management Series Co., Inc. 1984.
Characterization of Hazardous Waste Sites, A Methods Manual. Volume 3 -
Available Laboratory Analytical Methods, May
Martin, T. D. (EMSL/Cincinnati). Inductively Coupled Plasma - Atomic
Emission Spectrometric Method of Trace Elements Analysis of Water and
Waste, Method 200.7, Modified by CLP Inorganic Data/Protocol Review
Committee.
Martin, T. D., Kopp, J. F., and Ediger, R. D. 1975. Determining Selenium in
Water, Wastewater, Sediment and Sludge by Flameless Atomic Absorption
Spectroscopy, Atomic Absorption Newsletter 14, 109
Mehran, Moshen, et al., 1983. Delineation of Underground Hydrocarbon Leaks
by Organic Vapor Detection. Proceedings of the Fourth National Conference
on Management of Uncontrolled Hazardous Waste Sites, Washington, D.C.
Organochlorine Pesticides and PCBs, Method 608; 2,3,7,8-TCDD, Method 613;
Purgeables (Volatiles), Method 6224; Base/Neutrals, Acids and Pesticides,
Method 625; Federal Register, Vol. 44, Mo. 233, Monday, December 3, 1979
pp. 69501, 69526, 69532 and 69540.
Owerbach, Daniel. The Use of Cyanogen Iodide (CNI) as a Stabilizing Agent
for Silver in Photographic Processing Effluent Sample. Photographic
Technology Division, Eastman Kodak Company, Rochester, New York, 14650.
Panaro, J. M. 1984. Air Monitoring and Data Interpretation During Remedial
Action at a Hazardous Waste Site. Proceedings of the Hazardous Waste and
Environmental Emergencies Conference. Houston, Texas
Quimby, J. M. et al. 1982 Evaluation and Use of a Portable Gas
Chromatograph for Monitoring Hazardous Waste Sites. Proceedings of the
Third National Conference on Management of Uncontrolled Hazardous Waste
Sites. Washington, D.C.
Shackelford, W.M., Cline, D.M., Faas, L., and Kurth, G. 1983. An
Evaluation of Automated Spectrum Matching for Survey Identification of
Wastewater Components by Gas Chromatography - Mass Spectrometry.
Analytica Chimica Acta.
Spittler, T. M. 1980. Use of Portable Organic Vapor Detectors for Hazardous
Waste Site Investigations. Second Oil and Hazardous Materials Spill
Conference and Exhibition. Philadelphia, Pennsylvania
Spittler, T. M., et al. 1981. Ambient Monitoring for Specific Volatile
Organics Using a Sensitive Portable PID GC. Proceedings of the Second
National Conference on Management of Uncontrolled Hazardous Waste Sites.
Washington, D.C.
Spittler, T. M. 1983. Field Measurement of PCBs in Soil and Sediment Using
a Portable Gas Chromatograph. Proceedings of the Fourth National
Conference on Management of Uncontrolled Hazardous Waste Sites.
Washington, D.C.
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Taylor, J.U. 1981. Quality Assurance of Chemical Measurements Analytical
Chemistry. Volume 53, No. 14. December
Technicon Industrial Systems. 1980. Operation Manual for Technicon Auto
Analyzer 11C System. Technical Pub. #TA9-0460-00, Tarrytown, New York,
10591
U.S. Environmental Protection Agency. Handbook for Analytical Quality
Control in Water and Wastewater Laboratories, USEPA-600/4-79-019.
. 1973. Handbook for Monitoring Industrial Wastewater, USEPA
Technology Transfer.
. 1974. Methods for Chemical Analysis of Water and Wastewater, USEPA
Technology Transfer.
. 1977. Procedures Manual for Groundwater Monitoring at Solid Waste
Disposal Facilities. EPA 530/SW-611.
. 1979. Methods for Chemical Analysis of Water and Wastes. EPA Pub.
~OT/4-79-20, March.
. 1980. Environmental Monitoring and Support Laboratory, Cincinnati,
(5hTb, Interim Methods for the Sampling and Analysis of Priority
Pollutants in Sediments and Fish Tissue. October.
. 1982. Office of Solid Waste and Emergency Response, Modification (By
Committee) of Method 3050. SW9846, 2nd Ed., Test Methods for Evaluating
Solid Waste. July.
. 1982. Draft Guidance For Preparation of Combined Work/Quality
Assurance Project Plans for Water Monitoring. November 15.
1981. EMSL, Users Guide for the Continuous Flow Analyzer Automation
System. Cincinnati, Ohio.
. 1984. 0ERR. User's Guide to the Contract Laboratory Program. July.
1984. Memorandum from Stanley Blacker, about QAMS Checklist for DQ0
Review.
. 1984. Test Methods for Evaluating Solid Waste, Physical/Chemical
Methods. SW-846.
. 1984. Quality Assurance Handbook for Air Pollution Measurement
Systems. Volumes 1 and 2, EPA - 600/9-76-005. January 19.
. 1984. Quality Assurance Management and Special Studies Staff,
Calculation of Precision, Bias, and Method Detection Limit for Chemical
and Physical Measurements. March 30.
. 1984. Soil Sampling Quality Assurance User's Guide. EMSL-LV
—5011/4-84-043. May.
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. 1985. Draft Superfund Public Health Evaluation Manual. OSWER
Di recti ve 9285.4-1. December.
. 1985. Draft DQO Report for SI Superfiwd Process. March.
Winefordner, J. D., Trace Analysis: Spectroscopic Methods for Elements.
Chemical Analysis, Vol. 46, pp. 41-42.
Winge, R. K., Peterson, V. J., and Fassel, V. A. Inductively Coupled Plasma
- Atomic Emission Spectroscopy Prominent Lines. EPA-600/4-79-017.
Wise, R. H., Bishop, D. F., Williams, R. T., and Austern, B. M., Gel
Permeation Chromatography in the GC/MS Analysis of Organics in Sludges.
USEPA, Municipal Environmental Research Laboratory; Cincinnati, Ohio
45268.
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APPENDIX A
REVIEW OF QAMS DQO CHECKLIST
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Document No. 9355.0-A
APPENDIX A
REVIEW OF QAMS DQO CHECKLIST
In a memorandum dated April 3, 1983, Mr. Stanley Blacker, Director of the
Quality Assurance Management Staff (QAMS) issued a checklist to be used by
QAMS staff during their review of DQOs. The purpose of this section is to
review the QAMS checklist with respect to this RI/FS DQO guidance.
The RI/FS process involves multiple levels of data and data uses, and
culminates in a decision regarding the degree of remedial response to be
implemented for a site. Decisions are based on analytical and other
measurement data which are often integrated to interpret various aspects of
a site's characteristics. Thus, many different sets of DQOs may be
required for a given RI/FS.
The QAMS checklist is designed for use in reviewing specific DQOs rather
than an approach to DQO development for a complex process such as an RI/FS.
This appendix presents a review of the checklist items, along with a
reference to the section where the item is addressed and/or a comment
regarding the applicability of the item to the RI/FS DQO process.
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Document No. 9355.Q-A
SUMMARY OF DQO CHECKLIST ITEMS WITH RESPECT TO
RI/FS DQO APPLICABILITY
DQO CHECKLIST ITEM
A-l. The decision maker and
associated users are clearly
identified.
COMMENT RE: RI/FS DQO APPLICABILITY
The primary decision maker is the
regional EPA Remedial Project
Manager (RPM), who is responsible
for the planning and implementation
of and RI/FS. The secondary
decision maker is the EPA official
(Assistant Administrator or
Regional Administrator) who signs
the Record of Decision (ROD).
Associated data users include
technical personnel from various
disciplines (engineers,
toxicologists, geologists,
chemists) who interpret data and
state conclusions in the RI/FS
report.
A-2. The decision maker and
associated data users have been
involved in the development of
DQOs.
B-la. A statement of the
decision(s) that depend(s) on
the results of this data
collection activity.
See Section 2.0, Stage One of DQO
Implementation.
The decision(s) that result from
the RI/FS process involve multiple
levels of data for multiple
purposes. Table 1-1 of Section l.o
summarizes RI/FS objectives.
Simply stated, the decision made
for each objective is whether or
not a remedial response is
justified. The presence or absence
of contaminants and the
concentrations, if present, drive
the decision(s).
B-lb. If the data collection
activity is of an exploratory
nature and not formally linked
with a regulatory decision, then
the document should include a
clear explanation of the purpose
for which the environmental data
are intended.
Stage One of the RI/FS DQO process
will identify and prioritize all
data needs, both regulatory and
non-regulatory. See Section 2.0.
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Document No. 9355.Q-A
SUMMARY OF DQO CHECKLIST ITEMS WITH RESPECT TO
RI/FS DQO APPLICABILITY (continued)
DqO CHECKLIST ITEM
B-2. Statements of each specific
question that will be addressed
in the data collection activity
and the type of conclusion that
is anticipated as an appropriate
answer to each question. The
conclusions should depend only on
measurement data.
COMMENT RE: RI/FS DQO APPLICABILITY
See Table 1-1 of Section 1.0, which
summarizes RI/FS objectives. The
conclusion for each objective is:
(1) presence or absence of
contaminants, and (2) if present,
contaminant concentration levels.
These drive the decision.
B-3. A clear statement of the
way in which each conclusion of
the study will be represented, in
terms of the results of
statistical calculations made
with the data.
The conclusions of an RI/FS study
are highly interdependent. The
format for data presentation will
vary, based upon data quantity. A
statistical approach may not be
feasible.
B-4. Statements of the
acceptable levels of precision
and accuracy associated with each
of the conclusions depend on
measurement data.
See Section 3.0, Data Quality
Criteria.
B-6, A definition of the
population to which each of the
conclusions apply, including
definitions of all subpopulations
or strata.
This is one af the goals af the
RI/FS: to determine population at
risk.
B-6. Definitions of the See Section 3.0, Data Quality
variables that will be measured. Requirements.
B-7. The acceptable levels of
precision and accuracy for the
measurements to be made.
See Section 4.0, Analytical
Approach Options and Section 3.0,
Data Quality Requirements.
B-8. A flow chart or spread
sheet illustrating the
relationship between the measure-
ment data and each conclusion
that will be made with the data.
This statement refers to data
review and validation. This review
process is specified in each site
work plan.
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APPENDIX B
POTENTIALLY APPLICABLE OR
RELEVANT AND APPROPRIATE REQUIREMENTS
excerpt from National Contingency Plan final rule
Federal Register, Vol. 50, No. 224
November 20, 1985
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Federal Register / Vol. 50. No. 224 I Wednesday, November 20, 1985 I Rules and Regulations
Potentially Applicable or Relevant and
Appropriate Requirements
l. EPA s Office of Solid Waste
administers, inter aJia, the Resource
Conservation and Recovery Act of 1975,
as amended (Pub. L 94-&0.90 Slat 93,
42 U-S.C. 6901 et seq.j. Potentially
applicable or relevant requirements
pursuant to that Act are:
a. Open Dump Criteria—Pursuant to
RCRA Subtitle 0 criteria for
classification of solid waste disposal
facilities [40 CFR Part 257).
Note.—Only relevant to nonhazardom
wattes.
b. In most situation* Superfund
wastes will be handled in accordance
with RCRA Subtitle C requirement*
governing standards for owners and
operators of hazardous waste treatment
storage, and disposal faril'ties: 40 CFR
Part 264, for permitted facilities, and 40
CFR Part 263, for interim status
facilities.
• Ground Water Protection [40 CFR
264.90-264.109).
• Ground Water Monitoring (40 CFR
263.90-265.94).
• Closure and Post Closure (40 CFR
264.110-264.120. 265.110-269.112).
• Containers (40 CFR 204.170-264.178.
263.170-265.177).
• Tanks (40 CFR 264.190-264.200.
265.190-265.199).
• Surface Impoundments [40 CFR
264.220-264.249. 265.220-265.230J.
• Waste Piles (40 CFR 264.250-
264.269. 265.250-265.25B).
• Land Treatment [40 CFR 2W.270-
264.299. 265.270-235.262).
• Landfills (40 CFR 264.300-264.339.
265.300-265.316).
• Incinerators (10 CFR 254.340-
264.999. 2:5.340-265.369).
• Oioxin-containing Wastes (50 FR
197S). kciudes the final rule for the
listing of dioxin containing waste.
2. EPA s Office of Water administers
several potentially applicable or
relevant and appropriate statutes and
regulations issued thereunder
a. Section 14.2 of the Public Health
Service Act as amended by the Safe
Drinking Water Act as amended (Pub. L.
93-023. aa Stat 1660. 42D.S.C. 300f et
sec.)
• Maximum Contaminant Levels (for
ali sources of drinking water exposure).
[40 CFR 141.11-1*1.16).
• Underground Injection Control
Regulations. (40 CFR Parts 144.143.146.
and 147).
b. Clean Water Act as amended (Pub.
L 92-500, 66 Stat. 616, 33 U.S.C. 1251 et
seq.)
• Requirements established pursuant
to sections 301, 302.303 (including State
water quality standards), 306, 307.
(including Federal pretreatment
requirements for discharge into a
publicly ow.'ned treatment works), and
403 of the Clean Water Act. (40 CFR
Parts 131, 400-469).
c. Marine Protection. Research, and
Sanctuaries Act (33 U.S.C. 1401).
• Incineration at sea requirements.
(40 CFR Parts 220-225. 227,226. See also
4(J CFR 125.120-125.124).
3. EPA's Office of Pesticides end Toxic
Substances
Toxic Substances Control Act (15
U.S.C. 2601).
• PCB Requirements Generally: 40
CFR Part 761: Manufacturing Processing,
Distribution in Commerce, and Use of
PCBs and PCB Items (40 CFR 761.20-
761.10); Markings of PCBs and FCB
Items (40 CFR 761.40-761.45); Storage
and Disposal (40 CFR 761*60-761.79].
Records and Reports (40 CFR 761.180-
761.165). See also 40 CFR 129.109, 750.
• Disposal of Waste Material
Containing TCDD. (40 CFR Parts
77S.1B0-775.197).
4. EP. 1 '$ Office of External Affairs
• Section 404(b)(1) Guidelines for
Specification of Disposal Sites for
'Dredged or Fill Material (40 CFR Part.
230).
• PTcced-ires for denial or Restriction
of Disposal Sites for Dredged Material
[§ 404(c) Procedures, 40 CFR Part 231).
5 EPA's Office of Air and Radiation
administers several potentially
applicable or relevant and appropriate
statutes and regulations issued
thereunder
a. The Uranium Mil] Tailings
Radiation Control Act of 1978 (42 U.S.C.
2022|.
• Uranium mill tailing rules—Health
and Environmental Protection Standards
for Uranium and Thorium Mill Tailinss
1-33 CFR Part 132).
b. Clean Air Act [42 U.S.C. 7401).
• National Ambient Air Quality
SiardaMs for total suspended
particulates (40 CFR Parts 50.6-50.7).
• National Ambient Air Quality
Standards for oione (40 CFR 50.9}.
• Standards for Protection Against
Radiation—high and low level
radioactive waste rule. [10 CFR Part 20).
See aiso 10 CFR Parts 1C, 40, 60.61.72.
960.961.
• National Emission Standard for
Hazardous Air Pollutants for Asbestos.
[40 CFR 81.140-61.156). See also 40 CFR
427.110-427.116. 763.
• National Emission Standard for
Hazardous Air Pollutants for
Radionuclides (40 CFR Part 61.10 CFR
20.101-20.10e).
6. Other Federal Requirements.
a. OSHA requirements for workers
engaged in response activities are
codified under the Occupational Safety
and Health Act of 1970 (29 U.S.C. 651).
The relevant regulatory requirements
are included under
• Occupational Safety and Health
Standards (General Industry Standards]
(29 CFR Part 1910).
• The Safety and Health Standards
for Federal Service Contracts (29 CFR
Part 1926).
• The Shipyard and Longshore
Standards (29 CFR Parts i915.1918).
• Recordkeeping, reporting, and
related regulations (29 CFR Pan 1904).
b. Historic Sites. Buildings, aad
Antiquities Act (16 U.S.C. 461).
c. National Historic Preservation Act.
16 U.S.C. 470. Compliance with NEPA
required pursuant to 7 CFR Part 650.
Protection of Archaeological Reaources:
Uniform Regulations—Department of
Defense (32 CFR Part 229.229.4),
Department of the Interior (43 CFR Part
7, 7.4).
d. D.O.T. Rules for the Transportation
of Hazardous Materials. 49 CFR Parts
107,17l.l-i7l.500. Regulation of
activities in or affecting waters of the
United States pursuant to 33 CFR Parts
320-329. The following requirement are
also th;83red by Fur.d-fi3ar.csd actions:
• Endangered Species Act of 1973.18
U.S.C. 1531. (Generally, 50 CFR Parts 81.
225. 402). Wild and Scenic Rivers Act 16
U.S.C. 1271.
• Fish and Wildlife Coordination Act.
16 U.S.C. 661 note.
• Fish and Wildlife Improvement Act
of 1978. and Fish and Wildlife Act of
1956.16 U.S.C. 742a note.
• Fish and Wildlife Conservation Act
of 1980.16 U.S.C. 2901. (Generally. 50
CFR Part 83).
• Coastal Zone Management Act of
1972.16 U.S.C. 1451. (Generally, 15 CFR
Par: ?30 and 15 CFR 923.45 for Air and
Water Pollution Control Requirements).
Other Federal Criteria, Advisories,
Guidance, and State Standards To Be
Considered
1. Federal Criteria, Advisories and
Procedures
• Health Effects Assessments (HEAs).
• Recommended Maximum
Concentration Limits (RMCLa).
• Federal Water Quality Criteria
(1976.198a 1964). Note: Federal Water
Quality Criteria are not legally
enforceable. State water quality
standards are legally enforceable, and
are developed using appropriate aspects
-------
of Federal Water Quality Criteria. In
many cases. State water quality
standards do not include specific
numerical limitations on a large number
of priority pollutants. When neither
State standards nor MCLs exist Cor a
given pollutant Federal Water Quality
Criteria are pertinent and therefore are
to be considered.
• Pesticide registrations.
• Pesticide and food additive
tolerances and action levels. Note:
Germane portions of tolerances and
action levels may be pertinent and
therefore are to be considered in certain
situations.
• Waste load allocation procedures,
EPA Office of Water.
• Federal sole source aquifer
requirements.
• Public health basis for the decision
to list pollutants a* hazardous under
section 112 of the Clean Air Act.
• EPA's Ground-water Protection
Strategy.
• New Source Performance Standards
for Storage Vessels for Petroleum
Liquids.
• TSCA health data.
• Pesticide registration data.
• TSCA chemical advisoriea (2 or 3
issued to dale).
• Advisories issued by FWS and
NWFS under the Fish and Wildlife
Coordination Act
• Executive Orders related to
Floodplains (11988) and Wetlands
(11990) as implemented by EPA's August
6.1985, Policy on Floodplains and
Wetlands Assessments for CERCLA
Actions.
• TSCA Compliance Program Policy.
• OS HA health and s afety standards
that may be used to protect public
health (non-workplace).
• Health Advisories. EPA Office of
Water.
2. State Standards
• S-ate Requirement on Disposal and
Transport of Radioactive wastes.
• State Approval of Water Supply
System Additions or Developments.
• State Ground Water Withdrawal
Approvals. -
• Requirements of authorized
(Subtitle C of RCRA) Stale hazardous
waste programs.
• Stale Implementation Plans and
Delegated Programs Under Clean Air
Act.
• All other State requirements, not
delegated through EPA authority.
• Appioved State NPDES programs
under the Clean Water Act.
• Approved State UIC programs
under the Safe Drinking Water Act.
Note: Many other Slate and local
requirements could be psr!;nent.
Forthcoming guidance will include a
more comprehensive list.
3. US£PA RCRA Guidance Documents
• Draft Alternate Concentration
Limits (ACL) Guidance.
A. EPA's RCRA Design Guidelines
1. Surface Impoundments. Liners
Systems, Final Cover and Freeboard
Control.
2. Waste Pile Design—Liner Systems.
3. Land Treatment Units.
4. Landfill Design—Liner Systems and
Final Cover.
B. Permitting Guidance Manuals
1. Permit Applicant's Guidance
Manual for Hazardous Waste Land
Treatment Storage, and Disposal
Faciliues.
2. Permit Writer's Guidance Manual
for Hazardous Waste Land Treatment
Storage, and Disposal Facilities.
3. Permit Writer's Guidance Manual
for Subpart F.
4. Permit Applicant's Guidance
Manual for the General Facility
Standards.
5. Waste Analysis Plan Guidance
Manual.
6. Permit Writer's Guidance Manual
for Hazardous Waste Tanks.
7. Model Permit Application for
Existing Incinerators.
8. Guidance Manual for Evaluating
Permit Applications for the Operation of
Hazardous Waste Incinerator Units.
9. A guide for Preparing.RCRA Permit
Applications for Existing Storage
Facilities.
10. Guidance Manual on Closure end
Post-Closure Interim Status Standards.
C. Technical Resource Documents
(TRDs)
(1) Evaluating Cover Systems for Solid
and Hazardous Waste.
(2) Hydrologic Simulation of Solid
Waste Disposal Sites.
(3) Landf;1.! and Surface Impoundment
Performance Evaluation.
(4) Lining of Water Impoundment and
Disposal Facilities.
(5) Management of Hazardous Waste
Leachate.
18] Guide to the Disposal of
Chemically Stabilized and Solidified
Waste.
(7) Closure of Hazardous Waste
Surface Impoundments.
(9) Hazardous Waste Land Treatment.
(9) Soil Properties. Classification, and
Hydraulic Conductivity Testing.
D. Test Methods for Evaluating Solid
Waste
(1) Solid Waste Leaching Procedure
Manual.
(2) Methods for the Prediction of
Leachate Plume Migration and Mixing.
(3) Hydrologic Evaluation of Landfill
Performance (HELP) Model Hydrologic
Simulation on Solid Waste Disposal
Sites.
(4) Procedures for Modeling Row
Through Clay Liners to Determine
Required Liner Thickness.
(3) Test Methods for Evaluating Solid
Wastes.
(6) A Method for Determining the
Compatibility of Hazardous Waatea.
(7) Guidance Manual on Hazardous
Waste Compatibility.
4. USEPA Office of Water Guidance
Documents
A. Pre treatment Guidance Document*
(:) 304(g) Guidance Document Revised
Pretreatment Guidelines (3 Volumes)
B. Water Quality Guidance Documents
(1) Ecological Evaluation of Proposed
Discharge of Dredged Material into
Ocean Waters (1977)
(2) Technical Support Manual:
WaUrbody Surveys and Assessments
for Conducting Use Attainability
Analyses (1683)
(3) Water-Related Environmental Pate
of 129 Priority Pollutants (1979)
(4) Water Quality Standards
Handbook 11983)
(5) Technical Support Document for
Water Quality-based Toxics Control.
C. NPDES Guidance Documents
(1) NPDES Best Management Practices
Guidance Manual ()une 1981)
(2) Case studies on toxicity reduction
evaluation (May 1983).
D. Ground Water/UlC Guidance
Document
(1] Designation of a USDW
(2) Elements of Aquifer Identification
(31 Interim guidance foi public
participation
(4i Definition of major facilities
(51 Corrective action requirement*
(6) Requirements applicable to w«Ua
injecting into, through or above an
aquifer which has been exempted
pursuant to $146.104(b)(4).
(7) Guidance for UIC implementation
on Indian lands.
5. USEPA Manuals from the Office of
Research and Development
(1) EW M6 methods—laboratory
analytic methods.
(2) Lab protocols developed pursuant
to Clean Water Act | 304(h).
-------
Document No. 9355.0-7A
APPENDIX C
PERFORMANCE CRITERIA FOR HSL ANALYSIS
UTILIZING CLP IFB PROCEDURES
-------
9355.0-7A
Hazardous Substance List (HSL) and
Contract Required Detection Limits (CRDL)**
Detection Limits*
Low Water*" Low Soll/Sedlmentb
Volatlles CAS Number ug/L ug/Kg
1. Chloromethane
74-87-3
10
10
2. Bromooethane
74-83-9
10
10
3. Vinyl Chloride
75-01-4
10
10
4. Chloroethane
75-00-3
10
10
5. Methylene Chloride
75-09-2
5
5
6. Acetone
67-64-1
10
10
7. Carbon Disulfide
75-15-0
5
8. 1,1-Dichloroethene
75-35-4
5
¦9. 1,1-Dichloroethane
75-35-3
5
10. trans-1,2-Dichloroethene
156-60-5
5
11. Chloroform
67-66-3
5
12. 1,2-Dichloroethane
107-06-2
5
13. 2-Butanone
78-93-3
10
10
14. 1,1,1-Trichloroethane
71-55-6
5
15. Carbon Tetrachloride
56-23-5
5
16. Vinyl Aceta-te
108-05-4
10
10
17. Bromodichloromethane
75-27-4
5
18. 1,1,2,2-Tetrachloroethane
79-34-5
5
19. 1,2-Dichloropropane
78-87-5
5
20. trans-1,3-Dichloropropene
10061-02-6
5
21. Trichloroethene
79-01-6
5
22. Dibromochloromethane
124-48-1
5
23. 1,1,2-Trichloroethane
79-00-5
5
24. Benzene
71-43-2
5
25. cis-1,3-Dichlorop*6pene
10061-01-5
5
(continued)
10/84 Rev
-------
9355.0-7A
Detection Limits*
Low Water* Low Soll/Sed!
Volatile!
CAS Number
ug/L
Ufi/KF!
26. 2-Chloroethyl Vinyl Ether
110-75-8
10
10
27. Bromoform
75-25-2
5
5
28. 2-Hexanone
591-78-6
10
10
29. 4-Methyl-Z-pentanone
108-10-1
10
10
30. Tetrachloroethane
127-18-4
5
5
31. Toluene
108-88-3
5
5
32. Chlorobenzene
108-90-7
5
5
33. Ethyl Benzene
100-41-4
5
5
34. Styrene
100-42-5
5
5
35. Total Xylenes
5
5
'Mediate Water Contract Required Detection Limits (CRDL) for Volatile HSL
Compounds are 100 times the individual Low Water CRDL.
^Medium Soil/Sediment Contract Required Detection Limits (CRDL) for Volatile
HSL Compounds are 100 times the individual Low Soil/Sediment CRDL.
10/84 Rev
-------
9355.0-7A
Seal-Volitllee
CAS Number
Low Waterc
"S/L
Detection Limits*
Low Soll/Sedlmenta
_u&/K£_
36. Phenol 108-95-2
37. bla(2—Chloroethyl) ether 111-44-4
38. 2-Chlorophenol 95-57-8
39. 1,3-Dichlorob«nzene 541-73-1
40. 1,4-Dichlorobenzene 106-46-7
41. Benzyl Alcohol 100-51-6
42. 1,2-Dlchlorobenzene 95-50-1
43. 2-Methylphenol 95-48-7
44. bla(2-Chlorolaopropyl)
ether 39638-32-9
45. 4-Kethylphettol 106-44-5
46. N-NItroso-Dlpropylamine 621-64-7
47. Hexachloroethane 67-72-1
48. Nitrobenzene 98-95-3
10
10
10
10
10
10
10
10
10
10
10
10
10
330
330
330
330
330
330
330
330
330
330
330
330
330
49. Isophorone
50. 2-Nicrophenol
51. 2,4-Dloethylphenol
52 . Benzoic Acid
53. bls(2-Chloroethoxy)
ne thane
78-59-1
88-75-5
105-67-9
65-85-0
111-91-1
10
10
10
50
10
330
330
330
1600
330
54 2,4-Dlchlorophenol 120-83-2
55. 1,2,4-Trlchlorobenzene 120-82-1
56. Naphthalene 91—20—J
57. 4-Chloroanlline 106-47-8
58. Hexachlorobutadlene 87-68-3
10
10
10
10
10
330
330
330
330
330
59. 4-Chloro-3-nethylphenol
(para-chloro-neta-cresol) 59-50-7
60. 2-Methylnaphthalene 91-57-6
61. Hexachlorocyclopentadlene 77-47-4
62. 2,4,6-Trlchlorophenol 88-06-2
63. 2,4,5-Trichlorophenol 95-95-4
10
10
10
10
50
330
330
330
330
1600
(cone inued)
7/85 Rev
-------
9355.0-7A
Detection Limlts*
Low Waterc
Low Soil/Sediment*1
Scml"Volatile*
CAS Number
ug/L
ug/Kfc
64. 2-Chloronaphthalene
91-58-7
10
330
65. 2-Nitroaniline
88-74-4
50
1600
66. Dimethyl Phthalate
131-11-3
10
330
67. Acenaphthyleoe
208-96—B
10
330
68. 3-Nltroanilioe
99-09-2
50
1600
69. Acenaphthene
83-32-9
10
330
70. 2,4-Dlnltrophenol
51-28-5
50
1600
71. 4-Nitroph«nol
100-02-7
50
1600
72. Dlbenzofuran
132-64-9
10
330
73. 2,4-Dlnltrotoluene
121-14-2
10
330
74. 2,6-Dinitrotoluene
606-20-2
10
330
75. Dlethylphthalate
84-66-2
10
330
76. 4-Chlorophenyl Phenyl
ether
7005-72-3
10
330
77. Fluorene
86-73-7
10
330
78. 4-Nitroaniline
100-01-6
50
1600
79. 4,6-Dlnitro-2-tnethylphehol
534-52-1
50
1600
80. N-nltrosodlphenylamlne
86-30-6
10
330
81. 4-Bromophenyl Phenyl ether
101-55-3
10
330
82. Kexachlorobenzene
118-74-1
10
330
83. Pentachlorophenol
87-86-5
50
1600
84. Phenanthrene
85-01-8
10
330
85. Anthracene
120-12-7'
10
330
86. Dl-n-butylphthalate
84-74-2
10
330
87. Fluoranthene
206-44-0
10
330
88. Pyrene
129-00-0
10
330
89. Butyl Benzyl Phthalate
85-68-7
10
330
90. 3,3'-Dichlorobenzldlne
91-94-1
20
660
91. Benzo(a)anthracene
56-55-3
10
330
92. bis(2-ethylhexyl)phthalate
117-81-7
10
330
93. Chryaene
218-01-9
10
330
94. Di-n-octyl Phthalate
117-84-0
10
330
95. Benzo(b)fluoranthene
205-99-2
10
330
96. Benzo(k)fluoranthene
207-08-9
10
330
97. Benzo(a)pyrene
50-32-8
10
330
(cont inued)
7/85 Rev
-------
9355.0-7A
Detection Limits*
Low Water0 Low Sell/Sediment5
Seal-Vol*tlle» CAS Number ug/L ur/Kr
98. Ind«no
-------
9355.0-7A
Detection Limits*
r® Lau •snt 1 /Ca.1
Pesticides
CAS Number
Low Watere
ug/L
Low Sol1/SedlBPnrI
u*/K* '
101. alpha-BHC
319-84-6
0.05
8.0
102. beta-BHC
319-85-7
0.05
8.0
103. delta-BIIC"
319-86-8
0.05
8.0
104. gamma-BHC (Lindane)
58-89-9
0.05
8.0
105. Keptachlor
76-44-8
0.05
8.0
106. Aldrin
309-00-2
0.05
8.0
107. Heptachlor Epoxide
1024-57-3
0.05
8.0
108. Endosulfan 1
959-98-8
0.05
8.0
109. Dleldrln
60-57-1
0.10
16.0
110. 4,4'-DDE
72-55-9
0.10
16.0
111. Endrln
72-20-8
0.10
16.0
112. Endosulfan 11
33213-65-9
0.10
16.0
113. 4,4*-DDD
72-54-8
0.10
16.0
114. Endosulfan Sulfate
1031-07-8
0.10
16.0
115. 4,4*-DDT
50-29-3
0.10
16.0
116. Endrln Ketone
53494-70-5
0.10
16.0
117. Methoxychlor
72-43-5
0.5
80.0
113. Chlordane
57-74-9
0.5
80.0
119. Toxaphene
8001-35-2
1.0
160.0
120. AROCLOR-1016
12674-11-2
0.5
80.0
121. AROCLOR-1221
11104-28-2
0.5
80.0
122. AR0CL0R-1232
11141-16-5
0.5
80.0
123. AR0CL0R-1242
53469-21-9
0.5
80.0
124. AROCLOR-1248
12672-29-6
0.5
80.0
125. AROCLOR-1254
11097-69-1
1.0
160.0
126. AROCLOR-1260
11096-82-5
1.0
160.0
eMedlum Uater Contract Required Detection Limits (CRDL) for Pesticide HSL
Compounds ere 100 timet the Individual Low Uater CRDL.
^Medium Soil/Sediment Contract Required Detection Limits (CRDL) for Pesticide
HSL compounds art 15 tiies the individual Low Soil/Sediment CRDL.
*Detection limits listed for soil/sediment are based on wet weight. The detec
tlon limits calculated by the laboratory for soil/sediment, calculated on dry
weight basis, as required by the contract, will be higher.
** Specific detection limits are highly matrix dependent. The detection
Units listed herein are provided for guidance and may not always be
achievable.
7/85 Rev
-------
9355.C-7A
METHX DETECTION UMTS FOR HAS INORGANICS FRCK CLP
Contract lequired
Detection L*vel*,2
Eleaent (ug/L)
Aluminua
200
Antinony
60
Araeoic
10
Bariua
200
Beryllium
5
Cadmium
5
Calcium
5000
Chromium
10
Cobalt
50
Copper
25
Iron
100
Lead
5
Magnesium
5000
Manganese
15
Mercury
0.2
Nickel
40
Foeaaalum
5000
Seleniua
5
Silver
10
Sodium
5000
Thalllua
10
Tic
40
Vanadiua
50
Zinc
20
Cyanide 1(J
1: Any analytical method specified in SOU Exhibit D a*y be utilised as
long as Che docuaented iaatruaent or acchod detection licita neec
the Contract Required Detection Level (CRflL) requlreaanta. Higher
detection levels.aay oaly b* used la the following circusscance;
If the aaaple concentration exceeds two tlaes the detection Halt
of Che lnetruaeat or method la use, the value may b« reported even
Chough the instrument or aethod detection limit maj sot equal the
contract required detection level.
2: These C8J5L are the Instrument detection Haiti obtained In pure
~~ Wacer that must be a«t uaing eh* procedure ia Exhibit Z. The
detection limits for samples may be considerably higher depending
on the sample matrix.
-------
9355.0-7A
WATCH MATRIX SPIKE/MATRIX SPIKE DUPLICATE MCI
Cm* *•' CmUHIm CwHract N«.
fraction
COMPOUNO
CONC SPIKE
AOOEO l«it/LI
SAMPLE
RESULT
CONC
MS
ft
NEC
CONC
MSO
ft
REC
RPO
"W
[i^V
VOA
SMO
SAMPLE NO
MDxMpMlKM
14
¦ 1 I4S
ThiMwiiIhk
14
n >20
CNiH«>hp«/r«tt
13
Ti 130
1}
'•US
II
Illl!
0/N
SMO
SAMPLE MO
I /.4 fncMo«otai|f(t|
20
34 ••
AcvniS^lHfic
31
4« i ia
J 4 0*n*i»oiotyf««c
31
74 »«
31
?• ur
N Nitiow O^^OprlMM
11
41 lis
1 4 D'CMOffllWIIIMt
21
mi;
ACIO
SMO
SAMPLE NO
NniKhkMOphcnoi
SO
9 10]
Phenol
47
17 19
9 ***-« ¦ -' «
« tMOfOlMnOI
40
7M73
4 CMml MnfcylpNawt
41
7147
4 MtliopMol
SO
10 «0
PEST
SMO
l-wllrf
IS
S« 173
MeirtjcMof
70
40 131
Atdxn
77
40 170
SAMPLE NO
D«h)"n
It
S7 170
Enkm
11
SO 171
4.4' DOT
31
30 Ml
ASTERISKED VALUES ARE OUTSIOE QC LIMITS.
MO
VOAl _
«/N_
ACIO-
rt st .
. OKI Ol .
M 0> .
M •! .
. M Ol .
i QC UffMli
OiHud* OC kHHIl
•mWtOCMi
•uiwM OC
RECOVERY:
VOAa.
«/N_
ACH}.
PEST.
.M af.
.Mil.
_ MM •> .
.mat •'.
OC built
QC Im
OC Im<
QC lamu
FORM m
was
Fnria (|f. *»S/MSII K.- ..lis
-------
9355.0-7A
SOIL MATRIX SPIKE /MATRIX MWf DUPLICATE RECOVERY
Cm* M*- CMlr««l«r CwMract M«.
U* Ut«< MOIm lw*l
fraction
COMPOUND
COMC SPIKE
AOOEO lut/MI
SAMPLE
result
COM
*
REC
CONC
MSO
%
NEC
MPO
O
VOA
SMO
MNPtfNO
I I OaMnHNm
n
win
riKMWIMMlM
M
U 11/
OtoaoMnim
21
CO 113
Tolutm
31
49 I3»
ItMltfll
21
M 142
¦/N
SMO
SAMPLE NO
1 M (ncMgiakmm
»
M 10/
14
31 111
1 * OiMionlmin
47
70 «
3C
» 14]
*1 Kkom * ftmliwi
3*
41 IM
1.4 OwMomtKmim
27
* «M
ACIO
^MtcMgraflwial
*t
if m
Ami
y&
»90
1 ¦*»- "
• unmpmim
so
7S 103
4 CMvo MMk^lfNial
33
20-103
4 Nilfpphiwol
SO
11 114
ffST
Inlm
SO
«II)
!
t
1
31
35-130
SMO
Ahtun
4]
Kin
SAMPLE NO
OwMnn
M
31 134
€ nbi ifl
«
42139
««'oor
SO
23 114
*AST
-------
9355.0-7A
TABLE 5.2. MATRIX SPIKE RECOVERY LIMITS*
Fraction Matrix Spike Compound Water* Soil/Sediment*
VOA
1,l-Dichloroethene
61-145
59-172
VOA
Trichlorethene
71-120
62-137
VOA
Chlorobenzene
75-130
60-133
VOA
Toluene
76-125
59-139
VOA
Benzene
76-127
66-142
BN
I,2,4-Trlchlorobenrene
39-98
38-107
BN
Acenaphthene
46-118
31-137
BN
2,4-Dinitrotoluene
24-96
28-89
BN
Pyrene
26-127
35-142
BN
N-Nltroso-Di-n-Propylamine
41-116
41-126
BN
1,4-Dichlorobenzene
36-97
28-104
Acid
Pentachlorophenol
9-103
17-109
Acid
Phenol
12-89
26-90
Acid
2-Chlorophenol
27-123
25-102
Acid
4-ChIoro-3-Methy1phenol
23-97
26-103
Acid
4-Nitrophenol
10-80
11-114
Pest.
Lindane
56-123
46-127
Pest.
Heptachlor
40-131
35-130
Pest.
Aldrin
40-120
34-132
Pest.
Dieldrin
52-126
31-134
Pest.
Endrin
56-121
42-139
Pest.
4,4'-DDT
38-127
• • mmMrmtm mm wi
23-134
* These limits are for advisory purposes only. They are not to be used to
determine if a sample should be reanalyzed. When sufficient multi-lab data
are available, 'standard limits will be calculated.
A C 32** ' C ** ' S i °
6.0 SUMMARY
This section does not replace or supercede specific analytical methods
or QA/QC activities described in previous sections. The intent of this subsection
is to provide the Contractor laboratories with a brief summary of on-going qc
activities involved with sample analysis. Specific references are provided to
help the Contractor laboratories meet specific Reporting and DelivorahLes required
by this IFB.
H85 Rev
-------
9355.0-7A
4.3 Surrogate solke recovery must he evaluated for acceptance by determin-
ing whether tha concentration (measured at percent recovery) falls Inside the
contract required recovery Halts listed In Table 4.2.
4.4 Treatment of surrogate spike recovery information is according to
paragraphs 4.4.1 through 4.4.2.
4.4*1 Method Blank Surrogate Spike Recovery
The laboratory aust take the actions listed below if any one of the follow-
ing conditions exist:
• Recovery of any one surrogate coapound in the volstlle fraction Is
outside the required surrogate spike recovery limits.
• Recovery of any one surrogate coapound in either the base/neutral
or acid fraction is outside surrogate spike recovery limits.
TABLE 4.2. CONTRACT REQUIRED SURROGATE SPIRE RECOVERY LIMITS
m us»« • • • • m • • wav* • • • • • mmrmmm mmm umm «s m • wora m*m mm m •
Low/Hediua Lov/Medlua
Fraction Surrogate Compound Uater Soli/Sediment
VOA
Toluene-dg
88-110
81-117
VOA
4-Bromofluorobenzene
86-115
74-121
VOA
1,2-Dichloroethane-d4
76-114
70-121
BNA
Nitrobenrene-d5
35-114
23-120
BNA
2-Fluorobiphenvl
43-116
30-115
BNA
p-Terphenyl-dj4
33-141
18-137
BNA
Phenol-d5
10-94
24-113
BNA
2-Fluorophenol
21-100
25-121
BNA
2,4,6-Tribromophenol
10-123
19-122
Pest.
Dlbutylchlorendate
(24-154)*
(20-150)*
* These Halts are for advisory purposes only. They are not used to determine
If a sample should b« reanalvzed. Vhen sufficient data becomes available,
the USEPA aay set performance based contract required windows.
4.4.1.1 Check calculations to sssure there are no errors; check In-
ternal standard and surrogate spiking solutions for degradation, contamination,
etc; also, check Instrument performance.
f
4.4.1.2 Recalculate or relnlect/repurge the blank or extract If steos
in 4.4.1.1 fail to reveal the caus* of the non-comoliant surrogate recoveries.
4.4.1.3 Re-extract and reanalyze the blank.
4.4.1.4 If the measures listed In 4.4.1.1 thru 4.4.1.3 fall to correct
7/85 Rev
-------
Document No. 9355.0-7A
APPENDIX D
ACCURACY DEFINITIONS
-------
Document No. 9355.0-7A
ACCURACY DEFINITIONS
Accuracy is usually referred to in terms of bias (B). Bias is defined as
the difference between the average value X of a set of measurements of a
standard and the reference value of the standard T given by:
B = X- T
Alternative estimates of bias are percent bias
%B = 100(X-T)/T,
and average percent recovery P
n
P =X#Pi • and
i =1
P,. = 100 (Ai - B.)/T,
where A. = the analytical result from the spiked sample and = the
analytical result from separate analysis of the unspiked sample. The
relationship between percent bias and percent recovery is:
%B = P - 100
The accuracy values listed for analytical procedures under a given level of
analytical support are obtained from percent recovery data from internally
spiked samples and the use of National Bureau of Standards (NBS) Standard
Reference Materials (SRMs). As with precision data, this information only
refers to analytical accuracy and not the accuracy of the entire
measurement system. DQOs for a given activity should be established with
this in mind.
AW3-38/1
-------
Document No. 9355.0-7A
ACCURACY DEFINITIONS
Defi ni tion
Reference Material
Spiking Material
A material known or established concentration that
is used to calibrate or to assess the bias of a
measurement system. Depending on requirements,
reference materials may be used as prepared or may
be diluted with inert matrix and used as blind
environmental samples.
A material of known or established concentration
added to environmental samples and analyzed to
assess the bias of environmental measurements.
Target Analyte
Spiking
Matrix Spike
Field Matrix Spike
Laboratory Matrix
Spike
Analysis Matrix Spike
Spiking with the analyte that is
in the environmental sample.
of basic interest
A sample created by adding known amounts of the
target analyte to a portion of the sample.
A sample created by spiking target analytes into a
portion of a sample in the field at the point of
sample acquisition. This data quality assessment
sample provides information on the target analyte
stability after collection and during transport and
storage, as well as on losses during sample
preparation and on errors of analysis.
A sample created by spiking target analytes into a
portion of a sample when it is received in the
laboratory. It provides bias information regarding
sample preparation and analysis and is the most
common type of matrix spike. This type of matrix
spike does not necessarily reflect the behavior of
the field-collected target analyte, especially if
the target analyte is not stable during shipping.
A sample created by spiking target analytes into a
prepared portion of a sample just prior to
analysis. It only provides information on matrix
effects encountered during analysis, i.e.,
suppression or enhancement of instrument signal
levels. It is most often encountered with
elemental analyses involving the various forms of
atomic spectroscopy and is often referred to as
"standard additions".
AW3-27
-------
Document No. 9355.0-7A
ACCURACY DEFINITIONS
(Continued)
Definition
Non-target Analyte Spiking of surrogate analytes into the sample. A
Spiking surrogate analyte is one which mimics the behavior
of target analytes in terms of stability,
preparation losses, measurement artifacts, etc.,
but does not interfere with target analyte
measurement. This approach is most frequently used
with organic compound determinations and is a
compromise which is dependent on the target
compounds and surrogates involved. Surrogates,
like matrix spikes, can be added in the laboratory
or in the field; results are interpreted in a
fashion similar to matrix spikes. This is a
quality control measure; it monitors the analytical
process. Surrogate recovery results may not have a
direct relationship with target analyte recoveries.
Internal Standard Analyte(s) added to the prepared sample just prior
Spike to instrumental analysis. Used primarily for
quantitation purposes by means of a calibrated
response factor relative to target analytes,
determined prior to sample analysis. May also
provide short term indication of instrument
performance.
AW3-27
-------
Section 5.0
CHANGES TO:
DATA QUALITY OBJECTIVES FOR THE Rl/FS PROCESS
Present Text
(November 5, 1985)
Changed Text
(June 6, 1986)
Preface
This is one of a series of guidance documents for
remedial Investigation/feasibility study activities
under CERCLA, prepared In accordance with the National
Contingency Plan final rule dated October 10, 1985,
This Is one of a series of guidance documents for
remedial Investigation/feasibility study activities
under CERCLA, prepared In accordance with the National
Contingency Plan final rule published In the Federal
Register November 20, 1985 and effective February 18,
1986.
Preface
o Guidance on Remedial Investigations Under CERCLA
(EPA 540A3-85/0O2)
o Guidance on Feasibility Studies Under CERCLA (EPA
540/G-85/003)
o Guidance on Remedial Investigations Under CERCLA
(EPA 540/G-85/002)
o Guidance on Feasibility Studies Under CERCLA (EPA
540/G-85/003)
c Data Qua I Ity Objectives for the Rl/FS Process
(draft!
o Fiel-d Operating Procedures (In preparation)
o Super fund health Evaluation Manual C05WEF.
Directive 92B5,4-1 )
o Data Quality Objectives for the R1/FS Process
(draw
Page 1-1, PI
Data Quality Objectives (DQOs) are qualitative and
quantitative statements specifying the quality of data
required to support RI/FS activities. DQOs are
established ...
o Exposure Assessment Guidance
o Field Operating Procedures (in preparation)
Data Quality Objectives (DQOs) are qualitative and
quantitative statements specifying the quality of data
required to support an Agency decision. This document
presents guidance on the development of DQOs for Rl/FS
activities. DQOs are established ...
AW3a-20
1-1
-------
Section 1.0
Page 1-1, PI
They define the level or extent of sampling and
analysis required to produce sufficient data for
evaluation or remedial alternatives for a specific
site. In actual practice...
They define:
o The level of risk that Is acceptable for making an
Incorrect decision based on the data
o The quality of data (resulting from sampling and
analysis) required to keep the level of risk at or
below the acceptable level.
The process of developing DQOs assures that a formal
plan Is developed describing the level or extent of
sampling and analysis required to produce adequate data
for evaluation of remedial alternatives for a site. In
actual practice ...
Page 1-1, P3
DQOs for RI/FS activities consist of two major
components, the analytical component and the sampling
component. The analytical component of DQOs involves
specifying a cost-effective chemical analysis method,
Including analytical quality control, which satisfies
the given object Ive(s). The sampling component of DQOs
DQOs establish the total amount of uncertainty |n the
data that Is acceptable for each specific activity |n
the RI/FS. Total uncertainty Includes both sampling
error and analytical measurement error. Thus, the DQO
process for RI/FS consists of two major components: the
analytical component and the sampling component. The
analytical component of the DQO process results In
specifying a cost-effective chemical analysis method
which, when Integrated with the selected sampling
design, will satisfy the given objectlve(s). The
sampling component of the DQO process ...
Page 1-2. P2
A checkl1st for DQO reviews was Issued In a memorandum
from Stanley Blacker on April 3, 1983. Appendix A
Includes a comparison of this checkl1st with RI/FS DQO
requirements. The Quality Assurance Management Staff
(QAMS) issued guidance to assist the Agency in
development of DQOs (EPA 1984).
The Quality Assurance Management Staff (QAMS) Issued
guidance to assist the Agency In development of DQOs In
October 1984. A checklist for DQO reviews was then
Issued In a memorandum from Stan Blacker on April 3f
1985. Appendix A Includes a comparison of this
checklist with RI/FS DQO requirements.
Page 1-3, P2
The DQO process is designed to assure that al
ana IytIcaI data co11ected In support of ...
The DQO process Is designed to assure that all
environmental data collected In support of ...
AW3a-20
1-2
-------
Section 1.0
Page 1-3, P3
DQO development Is actually a dynamic process Involving
a series of discussions between project management and
technical staff. Data collection activities are
composed of a sampling component and an analytical
component. As the two components are Inter-related,
overall data quality cannot be specified unless both
components are addressed. In light of this fact,
personnel such as environmental scientists, chemists,
geologlsts/hydrogeologlsts, toxlcologlsts field
specialists, statisticians, and others, such as
enforcement personnel, should Interact with managers
early In the DQO process. DQOs are meant to be
flexible to meet program needs. Once DQOs are
formulated for a site, any changes required should be
approved by the Remedial Project Manager. The RPM, as
defined by EPA, is the federal official designated by
EPA or another lead agency to coordinate, monitor, or
direct remedial activities under the National
Contingency PI an.
Page 1-4, PI (Stage One)
All potential data users should be Involved In this
stage. Stage One Is common to both the analytical and
sampling component of a DQO.
Paoe 1-4, P2 (Stage Two-A)
Mthough conducted simultaneously with Stage Two-8,
this stage Is discussed as a discrete step In the
analytical data certainty sufficient to meet the
objectives specified In Stage One ...
DQO development is actually a dynamic process Involving
a series of discussions among decision makers, project
managers, technical staff, health and safety staff, and
enforcement personnel. Data collection activities are
composed of a sampling component and an analytical
component. As the two components are Inter-related,
overall data quality cannot be specified unless both
components are addressed. In light of this fact,
personnel such as environmental scientists, chemists,
geologlsts/hydrogeologlsts, toxlcologlsts, field
specialists, statisticians, enforcement personnel, and
others should Interact with managers early In the DQO
process. DQOs are meant to be flexible to meet program
needs. Once DQOs are formulated for a site, any
changes required should be approved by the Remedial
Project Manager (RPM). The RPM, as defined In the NCP
In Section 300.6 (Federal Register Vol. 50, No. 224),
Is the federal official designated by EPA or another
lead agency to coordinate, monitor, or direct remedial
or other response activities under the National
Contingency Plan. The RPM will serve as the decision
maker for the Rl/FS DQO development process.
The decision maker and all potential data users should
be Involved In this stage. Stage One results In a
specification of the decision making process and an
understanding of why new data are needed. Stage One Is
common to both the analytical and sampling components
of the DQO process.
This stage results In the stipulation of the limits on
total uncertainty acceptable to the decision maker with
respect to conclusions drawn from the data. Although
conducted simultaneously with Stage Two-B, this stage
Is discussed as a discrete step In the analytical
component of the Rl/FS DQO process. This stage
Involves specifying the level of analytical data
certainty sufficient to meet the objectives specified
In Stage One, Stages Two-A and Two-B must be
Integrated so that total uncertainty (Including
sampling and analytical error) will be within limits
that are acceptable to the RPM,
AW3a-20
1-3
-------
Section 1.0
Page 1-4, P3
This stage Involves specifying the sampling approach to
be employed. As Is the case ...
This stage Involves a consideration of sampling
approaches and specification of the universe of
Interest, criteria for decision making, and limits of
acceptable sampling error. Stages Two-A and Two-B must
be Integrated so that total uncertainty (Including
sampling and analytical error) will be within limits
that are acceptable to the RPM.
Page 1-6, P2
STAGE TWO-A: Establishment of Data Quality Requirements
- Specify the criteria to be used In decision making
based on the data
- Specify data quality requirements by general use
category, or specific accuracy and precision
Information
- Address the precision, accuracy, representativeness,
completeness, and comparability (PARCC) parameters
and any additional considerations
- Evaluate the simultaneous use of multiple levels of
sampling and analytical support.
STAGE TWO-A: Establishment of Data Quality Requirements
- Specify levels of total uncertainty In the
conclusions acceptable to the decision maker.
- Specify the criteria to be used In decision making
based on the data.
- Specify data quality requirements by general use
category, or specific accuracy and precision Infor-
mation subject to the limits on total uncertainty.
- Address the precision, accuracy, representativeness,
completeness, and comparability (PARCC) parameters
and any additional considerations.
- Evaluate the simultaneous use of multiple levels of
sampling and analytical support.
Page 1-6, P3
STAGE THREE A: Selection of Analytical Support Options
- Specify the appropriate means of analytical support,
Including all modifications
- State the limitations and applicability of the data
to be collected, In relation to the program's
obj ect I ve
- State QC sample level of effort (e.g., frequency of
blanks, replicates, and spikes)
STAGE THREE A: Selection of Analytical Support Options
- Stages Three-A and Three-B should be Integrated so
that sampling and ana-lytlcal options are specified as
part of a single design.
- For each design considered, state the anticipated
limitations of the data In relation to the program
object Ives.
- Specify the appropriateness of analytical support.
Including all modifications.
AW3a-20
1-4
-------
Section 2.0
CHANGES TO:
DATA QUALITY OBJECTIVES FOR THE RI/FS PROCESS
Present Text
(November 5, 1985)
Changed Text
(June 6, 1986)
Page 2-1, Pt
Add sentence to end of paragraph
Page 2-1. P3
Table 2-1 lists general RI/FS objectives which are
applicable to both contaminant sources and pathways.
Page 2-1, P4
Initial field activities should establish which envi-
ronmental media have been contaminated and Identify
existing and potential pathways of contaminant
migration. This characterization Is often performed In
several stages of field Investigation, each having a
different (and generally progressively greater) level
of detail and precision.
Page 2-2, Table 2-1 (Title)
RI/FS Objectives Applicable to Waste, Air, Surface
Hater, Soil, Groundwater, and Biological Media
Pa(]e 2-2, Table 2-1
Under Rl Activity:
Establish pathway(s)/transport route(s)
Under FS Activity:
Identify potential receptor(s) and routes-of exposure
This selection process must be consistent with the NCP.
Table 2-1 lists general RI/FS objectives which are
applicable to both contaminant sources and pathways.
Each objective Identified In Table 2-1 usually requires
some environmental data In order to answer questions
Implied by the objective. The list of RI/FS activities
helps to further clarify the ways in which environmen-
tal data collected during an RI/FS will be used.
Inftlal field activities should establish the contami-
nants of concern and which environmental media have
been contaminated. Existing and potential pathways of
contaminant migration should also be identified. This
characterization Is often performed In several stages
of field Investigation,.each having more refined
objectives.
General RI/FS Objectives Applicable to Waste, Air,
Surface Water, Soil, Ground Water, and Biological Media
Under Rl Activity:
Establish pathway(s)/transport route(s); Identify
potential receptor(s)
Under FS Activity:
Identify most effective points In pathway to control
transport of contaminants
AW3a-24
2-1
-------
Section 2.0
Page 2-3, P2
...large volume, high toxicity, dffflcutty of treatment
or mobility determine the overall remedy and/or degree
of contamination. It Is Important that other
substances...
...large volume, high toxicity, difficulty of treatment
or mobility determine the overall remedy and/or degree
of contamination. With regard to Indicator parameters,
It should be noted that since certain contaminants may
exhibit differences In their environmental fate and
transport and varying degrees of toxicity In different
environmental media. Indicator parameters may need to
be different for different media. It Is Important that
other substances...
Page 2-3, P3
Potential remedial technologies are Identified In order
to focus the further gathering of site Information.
Remedial technologies are evaluated based on current
site Information.
Page 2-4. PI
It Is Important that the design parameters of each
potential remedial technology be Identified and
understood so appropriate data can be obtained that
will allow a reliable estimate of Its performance.
Page 2-4. P2
Achieving this objective requires that several
complicated and Interrelated activities be performed;
each having Its own particular sets of objectives and
attendant data quality requirements. The expression of
these objectives and requirements In clear, precise
statements will allow the development of a balanced,
Justifiable, cost-effective approach to the RI/FS.
Potential remedial technology types are Identified and
evaluated based on current site Information In order to
focus the further gathering of site Information.
It Is Important to Identify and understand the design
parameters associated with each potential remedial
alternative. This Information con then be used to
Identify data that are needed In order to generate
performance estimates with a confidence level
acceptable to the decision maker (e.g., the +50%, -30J
level associated with cost estimates In the RI/FS).
Achieving this broad objective requires that several
complicated and Interrelated activities be performed;
each having Its own particular set of objectives,
acceptable levels of uncertainty and attendant data
quality requirements. The expression of these
objectives In clear precise statements Is the first
step toward the development of a cost-effective program
for collection of sufficient data for decision making.
AW3a-24
2-2
-------
Section 2.0
Pacta 2-5, P3 to Page 2-6, PI
o What contaminants are In pathways of concern above
background?
o Are contaminants above action levels (e.g., What are
applicable/relevant standards, how clean Is clean?)
o What are the three-dimensional boundaries of the
contamination above action levels?
o Are there defined concentration gradients that could
be handled separately?
o Are there any operable units that can be expedited
In order to protect public health or the environment
(e.g., source control, alternate water supply)?
o Which alternatives are feasible and sufficient to
protect public health and the environment,
o Is treatment a viable option? Should treatment tests
or pilot plants be conducted concurrent with the Rl?
o Has sufficient data been collected so that cost
estimates are within the -30f to +50$ range?
o Which alternative should be selected In accordance
with NCP?
o Are there viable responsible parties?
o What contaminants are In pathways of concern above
background?
o Is background an appropriate comparison?
o Are contaminants above action levels as determined
from available standards or technical guidance?
(e.g., What are applIcable/re levant standards,
public health Issues, and environmental risks? How
clean Is clean?)
o How do contaminant concentrations found at the site
compare with values for those contaminants which
have public health or environmental significance?
o Do we need a risk assessment If there are no
standards?
o What are the three-dimensional and time boundaries
of the contamination above action levels?
o Are there defined concentration gradients that could
be handled separately?
o Are there any operable units that can be expedited
In order to protect public health or the environment
(e.g., source control, alternate water supply)?
o Which alternatives are feasible and sufficient to
protect current and future public health and the
envIronment?
o Is treatment a viable option? Should treatment tests
or pilot plants be conducted concurrent with the Rl?
o Has sufficient data been collected so that cost
estimates are within the -30$ to +50? range?
o Which alternative should be analyzed In accordance
with NCP? Would remedy comply with other
environmental laws?
o Is litigation (either Injunctive relief or cost
recovery) contemplated?
o Are there viable responsible parties?
AW3a-24
2-3
-------
Section 2.0
Page 2-6, P2
Standards may also be based on levels, durations, or
frequencies of exposure that are different from those
at a specific site. The standards that are used,
especially when conducting...For these reasons. It will
be necessary to rank these values (where available) and
to consult with EPA to evaluate the environmental/-
publlc health threat and determine the appropriate
range of cleanup levels for the constituents at each
site.
Page 2-6, P3
This component Involves collecting and evaluating
existing data. Identifying any data consistent with or
usable for the overall project objectives or Individual
data collection activity; and, finally. Identifying
data needs.
Page 2-7, PI
In many Instances, previous studies have provided
useful Information upon which further Investigation can
be based. For each of the major areas In the RI/FS
process all available relevant Information should be
gathered and organized In a manner that will allow
those additional data to fulfill the goals of the
activities to be Identified. Also Important Is the
evaluation of these data. The data developed through
previous efforts should be analyzed with respect to Its
quality to ensure that It Is truly useful, Quality
assurance and quality control records should be
evaluated as well as simply the results of previous
Investigations.
Page 2-7. P3
Age/comparablIIty - ...and the RI/FS to be a couple of
years.
Standards may also be based on levels, durations, or
frequencies of exposure that are different from those
at a specific site. The standards and criteria that
are used, especially when conducting...For these
reasons. It will be necessary to rank these values
(where available) and to consult with EPA to evaluate
the envlronmentaI/pubIIc health threat and determine
the appropriate range of cleanup levels for the
constituents at each site. Where no applicable
standards or criteria exist, the estimated risk to
public health should be determined. Thus, the decision
for remedial action would be based upon either
standards/criteria or upon some level of estimated
r Isk.
This component Involves collecting and evaluating
existing data. Identifying any data consistent with or
usable for the overall project objectives In compliance
with all relevant environmental laws or Individual data
collection activity; and, finally, Identifying data
needs.
In many Instances, previous studies have provided
useful Information upon which further Investigation can
be based. For each of the major areas In the RI/FS
process all available relevant Information should be
gathered and organized In a manner that will allow
those data to fulfill the goals of the activities to be
Identified. Also Important Is the evaluation of these
data. The data developed through previous efforts
should be analyzed with respect to Its quality to
ensure that It Is truly useful. Quality assurance and
quality control records should be evaluated as well as
the results of previous Investigations. These evalua-
tions determine the level of uncertainty associated
with the conclusions drawn from the data. A determina-
tion can then be made as to whether the achieved level
of uncertainty Is adequate, or whether additional data
are needed to further reduce uncertainty.
Acie/comparabl 1 Ity - ...and the RI/FS to be a couple of
years. Careful evaluation of QA/QC data Is essential
In determining the compatibility of old and current
data flies. Intralaboratory precision Information and
1nterlaboratory bias data are essential for this
evaluation.
AW3a-24
2-4
-------
Section 2.0
Page 2-7, P6
Laboratory - Was the laboratory performing the analysis
In good standing? Are spike recoveries acceptable for
Intended use? Is the laboratory blank contaminated?
Page 2-6, PI
Methods for sample collection methods are as Important
as methods for sample analysis methods. These consi-
derations fall Into two broad categories: statistical
and standard operating procedures (SOPs). The
statistical considerations relate to the conclusions
that can be drawn from the data. The SOPs relate to
Issues of well construction Information or other
methods of sample collection. Each procedure for
collecting samples has appropriate protocols which must
be followed In order to reduce sampling and analytical
error. Typical considerations which will be addressed
later In this report are:
o Were the samples collected using a random or
non-random sampling approach?
o Was the sampling plan followed? Were there deviations
to the sampling plan? Where and how were the samples
collected?
Page 2-8, P2. 4th bullet
o How long were the samples held before being analyzed?
As before, this could relate to the amount of contam-
inant found. For example, a holding time over 7-14
days for volatile organlcs Increases the likelihood
of loss of contaminants from the samples. Chemists
should be consulted for appropriate holding time.
Page 2-9, PI
This Is done by considering the number and- types of
decisions that will need to be made with the data that
are collected.
Laboratory - Determine the quality and usability of the
existing data by asking questions such as: Are the
spike recoveries acceptable for Intended use? Were the
laboratory blanks contaminated?
Methods for sample collection are as Important as
methods for sample analysis. These considerations fall
Into two broad categories: statistical and standard
operating procedures (SOPs). The statistical
considerations relate to the representativeness of the
data and the level of confidence that may be placed in
conclusions drawn from the data. The SOPs relate to
Issues of well construction Information or other
methods of sample collection. SOPs, if followed, will
ensure sample Integrity and data comparability. The
protocols for sample collection and analysis must be
followed In order to reduce sampling and analytical
error. Typical considerations which will be addressed
later In this report are:
o Were the samples collected using a random or
non-random sampling approach?
o Was the sampling plan adequate? (I.e., were a
sufficient number of samples collected?)
o Was the sampling plan followed? Were there
deviations from the sampling plan? Where and how
were the samples collected?
o How long were the samples held before being analyzed?
As before, this could relate to the amount of contam-
inant found. For example, when holding times are
exceeded for volatile organlcs the likelihood of a
change In concentration Increases. Chemists should
be consulted for appropriate holding times.
This Is done by considering the number and types of
uses to which the data will be put.
AW3a-24
2-5
-------
Section 2.0
Page 2-10, PI
Risk Assessment - Data collected for risk assessment
purposes are used to evaluate the threat posed by a
site to public health and the environment. The data
must be qualitative so that the Cham lea I/physical
properties, toxicity and persistence of contaminants
can be factored Into the risk assessment. The data
must also be quantitative to the degree that It may be
compared agafnst qugntltatfve statements of health risk
criteria (e.g., 10 cancer risk). Therefore, a high
level of data certainty Is necessary.
Risk Assessment - Data collected tor risk assessment
purposes are used to evaluate the threat posed by a
site to public health and the environment. Risk
assessments should help determine (1) the significance
of environmental transport routes to cause human
exposure and environmental damage, (2) the significance
of exposure pathways to human health, (3) the potential
health effects that have or could result from known
exposure, (4> the need for Immediate remedial action
because of Imminent risk or danger to public health,
(5) the reed tor long-term remedial action to prevent,
limit, or mitigate a potentially dangerous (I.e., acute
or chronic) situation to public health or the
environment In the future, and (7) the need for a
health study of potentially exposed population* To
make such determinations a high level of data certainty
Is necessary.
Page 2-10, P2
Engineering Screening of Alternatives
Page 2-10, P3
Engineering Design of Remedial Action
Evaluation of Alternatives
Design of Remedial Action
Page 2-10, P4
ConfIrmatlonal - Data collected for confIrrratIonaI delete
purposes are used to develop absolute statements about
the qualitative and quantitative presence or absence cf
contaminants, these data are characterized by a higher
level of certainty to verify the concentrations of
contaminants and can be used to validate data having
less certainty. ConfIrmatlonal data are generated
through the sampling and analysis of waste source areas
and environmental media.
Page 2-10, P5
Cost Recovery - Data collected for cost recovery pur-
poses are used to document the degree of remedial
response (and ultimately, the cost) required to clean
up a site. These data are also used to help apportion
the liability for costs at multiple-party-sites by
Identifying the types of waste constituents which are
characteristic of a responsible party's waste stream
and determining the media affected by these constitu-
ents. Cost recovery data are generated through the
sampling and analysis of waste source areas and
environmental media.
PRP Determination - Data collected for this purpose er*
used to help establish liability. At multiple party
sites for known RPs, data are used to link their wastes
to those found at the site and pollutants released to
the environment and for unknown RPs to match their
wastes to pollutant profiles of known waste streams at
the site. Data collected for Injunctive actions, as
wett as for cost recovery, are used to document the
nature and extent of contamination and to support the
Agency's selection of the remedial alternative as being
consistent with the NCP.
Page 2-11, Section 2.3
2.3 PRIORITIZE THE INTENDED USES OF THE DATA
DeIete head I ng
AW3a-24
2-6
-------
Section 2.0
Page 2-11, P2
Once the Intended data uses are listed, which can be
accanp I I shed by using the format Just outlined In
Section 2.3 ...
Once the Intended data uses are listed, which can be
accomplished by using the format outlined above ...
Page 2-11, P2
Establishing an order of priority for the Intended data
uses Is necessary to Identify the data quality required
for each data collection task. Where the uses for a
given task require planning data quality decisions must
be made as to the analytical approach.
Establishing an order of priority tor Intended data
uses will help Identify the most demanding use of each
type of data, I.e., the use requiring the highest level
of confidence and therefore the lowest level of
uncertainty. The data quality required will be a
function of the acceptable limits on uncertainty
established by the decision maker. The limits on
uncertainty will drive the selection of both the
analytical and sampling approaches.
Page 2-11, P3 to Page 2-12, PI
DQOs are formed on the concept that different data uses
may require different quality data. ... Using a general
category to Identify the range of data quality required
simplifies the selection of the specific analytical
method and also simplifies the process of prioritizing
the Intended uses of the data.
move to Page 3-2
Page 2-12, Table 2-2
Column heads:
HeaIth & Safety
Site Characterization
Risk Assessment
Engineering Screening of Alternatives
Engineering Design of Remedial Action
Con fIrmatory
Cost Recovery
Column heads:
Health & Safety
Site Characterization
Risk Assessment
Evaluation of Alternatives
Design of Remedial Action
PRP Determination
Page 2-13, P3
When a secondary use requires data of a much higher
quality and the quantity of samples required Is
different than the primary data use, It may be more
advantageous to treat the two uses on separate
activities by collecting two different data sets.
When a secondary use requires data of a much higher
quality and the number of samples required Is different
than the primary data use. It may be more advantageous
to treat the two uses as separate activities by
collecting two different data sets.
Page 2-14. PI
The first Issue to be considered Is the sample
turnaround time required to meet the project schedule.
Page 2-14. P2
Cost recovery Issues, such as requiring fingerprint
analysis, may also present special requirements.
An example of a time constraint would be the sample
turnaround time required to meet the project schedule.
Delete
AW 3a-24
2-7
-------
Section 3.0
CHANGES TO:
DATA QUALITY OBJECTIVES FOR THE RI/FS PROCESS
Present Text
(November 5, 1985)
Changed Text
(June 6, 1986)
Page 3-1. PI
tt Is during this stage that the quality of data
required to meet these objectives Is determined. The
amount of acceptable variability In data quality Is an
Important decision criterion. Project management and
technical staff must use their professional Judgment to
determine the quality of data required to meet the
objectives defined In Stage One. DQO development
revolves around the data quality requirements
established In Stage Two and the selection of the
analytical support level to meet those requirements In
Stage Three.
It Is during this stage that the overall quality of
data required to meet these objectives Is determined.
The process of establishing the quality of data
required begins with the decision maker proposing
limits (based on his or her best judgment) on the level
of uncertainty that will be acceptable In each
conclusion to be drawn from new environmental data.
This statement will address overall uncertainty, I.e.,
uncertainty resulting from both the analytical and
sampling components of the design. The Integrated
evaluation of analytical options (In Stage Two-A) and
sampling options (In Stage Two-8) can then proceed.
This Integration will ensure that the overall
uncertainty resulting from a complete design Is
expected to be within acceptable bounds. 0Q0
development revolves around the limits on overall
uncertainty proposed In Stage Two. The selection of
the specific analytical and sampling support levels
required to meet those limits occurs In Stage Three.
Page 3-1, Pi
Add to end of paragraph
Analytical support levels are described In Section 4.0.
Page 3-1, P2
This allows for the most efficient use of analytical
resources by defining a given data quality need and
selecting an analytical support option that will
produce data of that qua IIty.
This allows for the most efficient use of resources by
defining a given data quality need, and selecting an
analytical support option that, when Integrated with a
specific sampling approach, will produce data of the
quality needed.
Page 3-1, P3
Sampling and analysis parameters must be defined. This
should be done In a way that best addresses the problem
at hand and should be the product of collaboration
between management and technical staff. The ultimate
decision, however, lies with the RPM.
Sampling and analysis parameters must be defined.
These definitions should be a product of collaboration
between management and technical staff. The ultimate
decision regarding the selection of an analytical
approach ties with the RPM. This decision will be made
In Stage Three and will be based on knowledge of the
level of uncertainty that can be expected to result
from this approach when combined with a sampling plan.
AW3a-23
3-1
-------
Section 3.0
Page 3-2, P4
Examples of data use categories Include screening use,
engineering use and contIrmatlonal use. Data needs/-
data use categories serve as general guidelines and a a
tool for grouping data quality requirements.
DQOs are formed on the concept that different data uses
may require different quality data. For the purpose of
discussing variability In data quality, these general
categories of analytical support can t>e identified:
screening, engineering and confIrmatlonal. More
specific Information regarding analytical methods which
fall Into these categories Is provided In Section 4.0
of this document. This discussion Is meant to
Introduce the concept of variability In data quality In
order to Illustrate the Stage One DQO process.
Data use categories serve as general guidelines and a
tool for grouping data quality requirements.
Page 3-3, PI
However, by using these categories as a starting point,
the appropriate level of analytical support can be
specified In Stage Three to achieve maximum efficiency
In the sampling and analytical program.
Page 3-3, P2
Once the contaminants of concern are Identified,
multiple levels of analytical support may be utilized
simultaneously In response to an RI/FS activity.
However, by using these categories as a starting point,
data uses will become organized In a way that will be
useful for determining the needed level of analytical
support In Stage Three. The multiple-level analytical
support system Is designed to provide efficient
utilization of available resources while providing data
of adequate quality and quantity to meet defined
program objectives. Care must be taken to Insure that
Interpretation of the data does not exceed the defined
quality or validity of the data base. Results must
not be separated from their related QA/QC data and
other Information that defines their level of validity.
Once the difficult process of Identifying contaminants
of concern Is completed, multiple levels of analytical
support may be utilized simultaneously in response to
an RI/FS activity.
Page 3-6, P2
While this method requires thorough knowledge of how
the data will be utilized, It is the most accurate way
to ensure that the data collected will meet the
activity's objectives.
While this method requires thorough knowledge of the
ways that the data will be used and the level of
uncertainty acceptable for each use. It Is the best way
to ensure that data collected will meet the activity's
objectIves.
Page 3-6, P2
These specifications are then used to select or modify
the appropriate analytical options In Stage Three,
These specifications are then used to select or modify
the appropriate analytical options and match them with
corresponding sampling plans In Stage Three.
AW3a-23
3-2
-------
Section 3.0
Page 3-6, P3
The output of Stage Two of the DQO development process
Is specific data quality requirements. Stage Two also
results In quantitative or qualitative statements
addressing each of the PARCC parameters and other
parameters deemed appropriate for the activity. These
statements, together with the resource constraints
Identified In Stage One and any other data quality
requirements, are used In selecting the appropriate
analytical option In Stage Three.
The output of Stage Two of the DQO development Is a
statement of the level of uncertainty acceptable for
each conclusion (based on data) needed to meet
objectives of the RI/FS. Stage Two also results In
quantitative or qualitative statements addressing each
of the PARCC parameters and other parameters deemed
appropriate for the activity. These statements,
together with time and resource constraints, criteria
for decision making, and any other data qualIty
requirements are used In selecting the appropriate
analytical option and sampling approach In Stage Three.
Page 3-6, P4
The magnitude of uncertainty associated with a data set delete
Is referred to as "data quality." The amount of
uncertainty that can be tolerated depends on the
Intended use of the data. It Is Important to realize
that data of too high quality may be as Inappropriate
for an Intended purpose as data of too low quality.
The DQO process results In statements that address the
quality of data needed to support a specific decision
or action. Fundamental to this process Is the use of
separate analytical options which produce data of Known
quality. Once DQOs are established, analytical options
to achieve the DQOs must be selected and Integrated
with a sampling plan for data collection activities.
Measures of data quality may be affected by sampling
and/or analytical procedures.
Page 3-7, PI
Analytical options are selected by best matching the
data quality required with the data quality produced by
a given option.
Analytical options are best selected by matching the
data quality required with the data quality produced by
a given analytical option when combined with a sampling
approach.
Page 3-9, P2
Decisions on sampling plan development may be more delete
subjective and dependent on a phased approach than
analytical procedure specification.
Page 3-12, P3
Field blanks are defined as samples which are obtained
by running analyte-free del on I zed water through
decontaminated sample collection equipment (bailer,
pump* auger, etc.), and placing It In the appropriate
sample containers for analysis. Using the above
definition, soli field blanks could be called rlnsate
samples. These should be Included In a sampling
program as appropriate.
Field blanks are defined as samples which are obtained
by running analyte-free delon I zed water through sample
collection equipment (bailer, pump, auger, etc.) after
decontamination, and placing It In the appropriate
sample containers for analysis. These samples will be
used to determine If decontamination procedures are
sufficient. To Insure the Integrity of field blanks,
they should be collected, stored, and shipped with the
other samples. Using the above definition, soil field
blanks could be called rlnsate samples. These should
be Included in a sampling program as appropriate.
AW3a-23
3-3
-------
Section 3.0
Page 3-13, P2
Field matrix spikes are generally not recommended
because of the high levef of technical expertise
required for proper use artd their sensitivity to
envlronmentaI variables.
Page 3-14, ?4
Representativeness Is a qualitative parameter which Is
most concerned with the proper design of the sampling
programs.
Page 3-15, P2
At least two background samples should be collected
during every sampling event. A background sample Is
one taken from media characteristic of the site but
outside of the zone of contamination.
Page 3-15, P3
An example of the way representativeness Is assured In
a sampling program Is In the use of proper groundwater
sampling technique. The SOPs for groundwater sampling
require that a well be purged a certain number of well
volumes prior to sampling, to be certain that the
sample Is representative of the underlying aquifer.
Page 3-15, P4
The representativeness criterion Is best satisfied by
makTrtg certain that the sampling program contains the
proper number of Investigative samples.
Page 3-16, P4
y In the most general of circumstances, this refers to
the use of standard field and analytical techniques and
the reporting of analytical data In the same units.
Field matrix spikes are generally not recommended
because of the high level of technical expertise
required for proper use and their sensitivity to
environmental variables. Spiking of soil samples In
the field Is particularly difficult to perform.
Representativeness is a qualitative parameter which is
most concerned with the proper design of the sampling
programs. The representativeness criterion Is best
satisfied by mak'ng certain ttet s-ampling locations are
selected properly and a sufficient number of
InvestIgattva samples are collected.
At least two background samples should be collected
during every sampling event. A sampling event 1s a
specific media event over a specified period of time.
For example, quarterly ground water sampUng which
requires four one-week trips over the year would be
considered four sampling events, However, a single
trip for soli sampling which covered four consecutive
weeks could be considered a single event. A background
sample Is one taken from media characteristic of th©
site but outside of the zone of contamination.
An example of the way representativeness Is assured In
a sampling program Is In the use of proper ground water
sampling technique. The SOPs for ground water sampling
require that a well be purged a certain number of well
volumes prior to sampling, to be certain that the
sample Is representative of the underlying aquifer at a
point in time.
delete sentence
In the most general of circumstances, this refers to
the use of standard field and analytical techniques and
the reporting of analytical data In the same units, in
order to compare data, various elements must be taken
Into account: sampling method, sample handling, holding
time, sample location, proservatlon, etc.
Page 3-18, P2
The following comments pertain to all data collected
for RI/FSs (except potentially criminal cases).
The following comments pertain to all data collected
for RI/FSs (except potential criminal cases}.
AW3a-23
3-4
-------
Section 3.0
Page 3-18, P3
o Chain of custody must be maintained for samples taken
off-site for analysis. This assures the decision
maker that the analysis given Is actually for the
samples collected and has not been tampered with. If
analysis Is performed on-site, documentation of the
process In field logs or other media Is sufficient.
Custody of samples should still be maintained,
however, the chain of custody form Is not necessary,
o Methods used for sampling and analysis should be
generally considered valid from an englneerlng/-
sclentlflc standpoint and be consistent with standard
Industry practices.
Page 3-19. PI
Documentation should be sufficient to allow someone
other than the chemist or sampler to testify 2 to 5
years later concerning which methods were used, that
methods were followed except In specific situations and
that the data were certified valid by the chemist
performing the work. If documentation Is adequate,
testimony may not actually be required; the data
package may be sufficient for admissibility on Its own
merits.
o Chain of custody must be documented with a chain of
custody form for samples taken off-site for analysis.
This assures the decision maker that the analysis
given Is actually for the sample collected and that
the sample has not been tampered with. If analysis
Is performed on-site, documentation of the process In
field logs or other media Is sufficient. Custody of
samples should still be documented; however, the
chain of custody form Is not necessary.
o Methods used for sampling and analysis should be
generally considered valid from an engtneerlng/-
sclentlflc standpoint and be consistent with standard
analytical procedures.
Documentation should be sufficient to allow the chemist
or someone other than the chemist or sampler to testify
2 to 5 years later concerning which methods were used,
that methods were followed except In specific
situations and that the data were certified valid by
the chemist performing the work. If documentation Is
adequate, testimony may not actually be required; the
data package may be accepted by the defendants.
Page 3-19, P4
Deliverable (documentation) requirements and
appropriate QC requirements should also be specified.
The CLP list of current contractors Is an excellent
source of Information on competent laboratories.
Page 3-20, P3
Using this framework, there Is room within a given
support level for the data user to further adjust the
certainty of data quality output by specifying more or
less QA/QC.
Documentation requirements and appropriate QC
requirements should also be specified. The CLP list of
contractors Is a source of Information on laboratories
currently performing analysis for the Superfund
program.
For example, an analytical level can be flexible by
specifying more or less QA/QC.
Page 3-21. P2
The most basic consideration regarding detection limits
fs that Irrespective of the specified limit, the actual
detection limit reported Is sample specific. This Is
especially true of samples having complex sample
matrices. Also, If the concentration of a particular
sample constituent ...
Irrespective of the specified method detection limit,
the actual detection limit reported Is sample specific.
This is especially true of samples having complex
sample matrices. Since the detection levels are
Important In Interpreting quantitative results,
detection levels should be reported for all analyses.
If the concentration of a particular sample constituent
AW3a-23
3-5
-------
Section 3.0
Page 3-22, Pt
Generally, the limit of reliable quantitation may be
approximately two times higher than the detection
IImlt.
Page 3-22, P2
In general, caution must be used when trying to apply
objectives expressed In percentages to numbers less
than fifty.
Page 3-23, P2
It compounds of Interest are tentatively Identified by
GC/MS and are high In spectra matching criteria (above
90)1 match) and above action levels, samples may be
re-run against a standard In order to verify the
compound parameter. Chromatographic retention time
consIderatlon Is an Important factor In assessing the
probability of tentative Identification reliability.
Page 3-23, P3
This review can range from superficial to very
rigorous, depending on the level of analytical support
utilized and the type of technical review requested by
the data user.
The limit of reliable quantitation Is approximately
twice the detection limit.
Caution must be used when applying objectives expressed
In percentages to numbers less than fifty.
If compounds of Interest are tentatively Identified by
GC/MS and are high In spectra matching criteria (above
90J match) for known contaminants and above action
levels, samples may be re-run against a standard in
order to verify the compound's Identity. For non-HSL
compounds where action levels do not exist, acceptable
risk level needs to be determined. Chromatographic
retention time Is an Important factor In assessing the
probability of tentative identification reliability.
This review can range from superficial to very
rigorous, depending on the level of analytical support
utilized and the type of technical review requested by
the data user. All data users should be provided with
adequate documentation to determine whether sampling
and analytical quality control DQOs have been achieved.
Exceptions should be clearly Identified and explained
In the sample case narrative and/or data validation
report.
AW3a-23
3-6
-------
Section 4.0
CHANGES TO:
DATA QUALITY OBJECTIVES FOR THE RI/FS PROCESS
Present Text
(November 5, 1985)
Changed Text
(June 6, 1986)
Page 4-1, P)
It Is In this stage that the actual sampling and
analytical techniques required to satisfy the
objectives set In Stages One and Two are determined.
Page 4-1. 1st bullet
The goal of Integration Is the selection of compatible
analytical and sampling approaches.
Page 4-1. 2nd bullet
As stated above. Integration with Stage Three-A Is of
utmost Importance to ensure compatibility with the
analytical optlon(s).
Page 4-2. PI
Each subsection provides a detailed description of the
levels. Including uses, benefits, costs, documentation,
accuracy, and precision and detection limit
Information.
It Is In this stage that various combinations of
sampling and analytical techniques are evaluated and a
combined approach Is selected that will satisfy the
objectives set In Stages One and Two, Including the
limit on total uncertainty.
The goal of Integration Is the selection of compatible
analytical and sampling approaches that, when combined,
will satisfy the limit on total uncertainty.
As stated above. Integration with Stage Three-A Is of
utmost Importance to ensure that the sampling approach
Is compatible with the analytical optlon(s) and that
the combined approach will satisfy the limit on total
uncertainty.
Each subsection provides a detailed description of the
levels. Including uses, benefits, costs, documentation,
accuracy, and precision and detection limit Informa-
tion. This quantitative Information on analytical
options can then be used In combination with similar
Information on sampling options (from Stage Three-B) to
estimate the total uncertainty that will arise from
combined sampling and analysis approaches.
Page 4-7, P4
Level IV data quality Is suitable for mos* RI/FS
activities.
Level IV analyses are currently used for most RI/FS
activities.
Page 4-8. Pi
o Data deliverable package supplies sufficient
documentation to allow qualified personnel to review
and evaluate data quality.
o Sufficient documentation to allow qualified personnel
to review and evaluate data quality.
AW3a-22
-------
Section 4.0
Page 4-8, P2
o Cost - CLP support Is one of the most expensive
routine analytical support available to the Superfund
Program, e.g., RAS for organIcs Is about
J1,000/sample. RAS for Inorganics Is about
S200/sample.
o Time - RAS Is contractually operating operating on a
30-40 day turnaround although delays can occur.
Page 4-8, P4 to Page 4-9, PI
Appendix B contains the performance criteria specified
I n the Statement of Work for Organ Ics Analysis -
mu11l-medla, mult1-concentrat1 on, July 1985 revision.
Page 4-9, P4
This level provides laboratory data to support
engineering studies.
Page 4-9, P5
o Rapid turnaround of data can be available.
Page 4-11, Table 4-3
TABLE 4-3 SW-846 ACCURACY, PRECISION, AND MDL
INFORMATION
Page 4-15, P4
o Data Quality - Data quality tor field analysis Is
dependent upon the QA/QC steps taken In the process,
e.g., documentation of blank Injections, calibration
standard runs, runs of qualitative standards between
samples, etc.
Page 4-19, P2
o Some Instruments show a response to naturally
occurring non-hazardous substances (methane).
o Cost - Complete Hazardous Substance List CLP support
Is one of the most expensive routine analytical
services available to the Superfund Program, e.g.,
RAS tor full organlcs Is about 11,000/sampte. RAS
for full Inorganics Is about $200/sample.
o Time - RAS Is contractually operating operating on a
30-40 day turnaround although delays can occur.
o Availability - Since demands fluctuate, space may be
limited at times for the Superfund program.
Appendix 0 contains the performance criteria specified
In the Statement of Work for Organlcs and Inorganics
Hazardous Substance List Analysis - mu It l-med la p
multi-concentration, July 1985 revision.
This level provides data used to support engineering
studles.
o Rapid turnaround of data may be available.
TABLE 4-3 SW-846 ACCURACY, PRECISION, AND MDL
INFORMATION*
ADD FOOTNOTE:
•For water only.
o Data Quality - The ability to assess data quality tor
field activities Is dependent upon the QA/QC steps
taken In the process, e.g., documentation of blank
Injections, calibration standard runs, runs of
qualitative standards between samples, etc.
o Some Instruments show a response to naturally
occurring non-hazardous substances (methane) or other
possible Interferences. Data from Instruments may
also be affected by weather and operator skill and
Interpretive ability.
AW3a-22
4-2
-------
Sactlon 4.0
Page 4-20, P3
The output of the RI/FS DQO process Is a well defined
sampling and analytical plan.
Page 4-20. P3
Included tn this DQO section should be a chart which
contains the most Important objectives and comments for
each DQO development stage.
Page 4-20. P4
The optimum approach Is one which Incorporates multiple
levels of analytical support with a sampling plan
design that Is specific for each level of analytical
support utilized.
The output of the RI/FS DQO process Is a well defined
sampling and analytical plan that Is expected to
produce data of a quality acceptable to the RPM.
Included In this OQO section should be statements of
the overall level of uncertainty acceptable In the
conclusions that will be made with the data and a chart
which contains the most Important objectives and
comments for each OQO development stage.
The optimum approach may be one which Incorporates
multiple levels of analytical support with a sampling
plan design that is specific for each level of
analytical support utilized.
AW3a-22
4-3
-------
Section 5.0
CHANGES TO:
DATA QUALITY OBJECTIVES FOR THE RI/FS PROCESS
Present Text
(November 5, 1985)
Changed Text
(June 6, 1986)
p»g« 5-'. P2
The XYZ site was operated over a period of 15 years as
a drum recycling and salvage metal operation.
Page 5-9. P4
The objective of any well head treatment system Is to
remove these contaminants to below concentration levels
that are adverse to human health and the environment
since most of these chemicals are suspected
carcinogens.
Page 5-10. PI
lifetime cancer risk of 1.0 x 10 for the drinking
water supply. Trlchloroethylene (TCE) hgs an estimated
excess lifetime cancer risk of 1.0 x 10 at a
concentration of 2.8 ug/l.
Page 5-10. P2
In general, pilot studies usually require a wide range
of analytical support services.
Page 5-11, PI
enough to allow quantification In the treatment
effluent that are above Its detection limit. Trans-1,2
dIchloroethylene also has a similar Henry's Law
constant to toluene. For municipal well #2, which only
has two detectable contaminants, trlchloroethylene
would be used as a surrogate or target parameter since
It is found In concentration levels high enough to
quantify In the treatment effluent.
The XYZ site was operated over a period of 15 years as
a drum recycling and metal salvage operation.
The objective of any well head treatment system Is to
reduce these contaminants to concentration levels that
are protective of human health and the environment.
lifetime cancer risk of 10 for the drinking water
supply. Trlchloroethylene (TCE) hgs an estimated
excess lifetime cancer risk of
of 2.8 ug/l.
10 at a concentration
Pilot studies usually require a wide range of
analytical support services.
enough to allow quantification in the effluent.
Trans-1,2 dIchIoroethyIene also has a Henry's Law
constant similar to toluene. For municipal well #2,
which only has two detectable contaminants,
trlchloroethylene would be used as a surrogate or
target parameter since It Is found In concentration
levels high enough to quantify In the effluent.
AW3a-21
5-1
------- |