DRAFT - Do not quote or cite
DRAFT
DATA QUALITY OBJECTIVES FOR THE RI/FS PROCESS,
Prepared for:
Office of Emergency and Remedial Response
and
Office of Waste Programs Enforcement
Office of Solid Waste and Emergency Response
U.S. ENVIRONMENTAL PROTECTION AGENCY
401 M Street, SW
Washington, DC 20460
November 5, 1985
AW3-4/1
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TABLE OF CONTENTS
Page
1.0 INTRODUCTION 1-1
1.1 DATA QUALITY OBJECTIVE BACKGROUND 1-7
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 2-6
2.2.3 IDENTIFY THE INTENDED USES OF THE DATA
TO BE COLLECTED 2-9
2.3 PRIORITIZE THE INTENDED USES OF THE DATA 2-11
2.4 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 •. 3-5
3.1.3 OTHER ANALYTICAL CONSIDERATIONS 3-17
3.2 STAGE TWO 8 OF THE RI/FS PROCESS ' 3-2.J ;«"-NT OF CONTAMINATION .. 5-5
AW3-20
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TABLE OF CONTENTS
(Continued)
5.1.4 CURRENT STATUS 5-7
5.1.5 DATA COLLECTION ACTIVITIES 5-3
5.2 SOURCE CHARACTERIZATION FOR REMOVAL- 5-3
5.3 PUBLIC HEALTH EVALUATION/ENOANGERMENT ASSESSMENT 5-8
5.4 FS DESIGN/PI LOT STUDY 5-9
5.4.1 AIR STRIPPING PILOT STUDY 5-10
5.4.2 STAGE ONE: DEFINITION OF PROGRAM OBJECTIVES
FOR THE AIR STRIPPING TREATMENT OPTION 5-15
5.4.3 STAGE TWO: ESTABLISHMENT OF DATA QUALITY
REQUIREMENTS 5-16
5.4.4 STAGE THREE: SELECTION OF ANALYTICAL SUPPORT
OPTIONS 5-20
5.5 HEALTH AND SAFETY SITE CHARACTERIZATION 5-20
6.0 BIBLIOGRAPHY 6-1
APPENDIX A REVIEW OF QAMS DQO CHECKLIST
APPENDIX 8 POTENTIALLY APPLICABLE OR RELEVANT AND APPROPRIATE REQUIREMENTS
APPENDIX C TOXICITY VALUES FOR USE AT SUPERFUND SITES
APPENDIX D PERFORMANCE CRITERIA FOR ORGANICS ANALYSIS
APPENDIX E LIST OF ACRONYMS
APPENDIX F ACCURACY TESTING DEFINITIONS
AW3-20
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LIST OF FIGURES
1-1 RI/FS OQO Process 1-5
3-1 Integration of Analytical Support Levels . 3-5
4-1 Integration of Analytical Support Levels 4-5
5-1 XYZ Site 5-2
LIST OF TABLES
1-1 .Data Quality Objectives Checklist 1-16
2-1 RI/FS Objectives Applicable to Air, Surface Water, Soil,
Groundwater, and Siological Media 2-2
2-2 Intended Data Uses 2-12
3-1 Guidelines for Minimal QA/QC Samples for Field Sampling
Programs 3-3
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 346 Accuracy, Precision, and MOL Information 4-11
4-4 Field Analytical Support Accuracy Information 4-13
AW 3-20
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DRAFT - Do not quote or cite,
NOTE
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, OERR)
James Occhialini (Camp Dresser' &. McKee Inc.)
Paul Clay (NUS)
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)
Sill Sunn (Region 7, Environmental Services Division)
Michael Kosakowski (CERCLA Enforcement Division)
Dennisse Beauchamp (CERCLA Enforcement Division)
Gary Lieberson (Consultant)
Technical editing was provided by Wendy Sydow of Camp Dresser & McKee Inc.
Contributions were also made from other EPA and contractor staff.
AW3-36/1
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DRAFT- Do not quote OP cite
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. These
quidance 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-35/002)
• Guidance on Feasibility Studies Under CERCLA (EPA 540/G-35/003)
• Data Quality Objectives for the RI/FS Process (draft)
• 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. OQOs 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 OQOs 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 or the mecnanics 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.
AW3-24/1
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DRAFT - Do not quote or cite.
1.0 INTRODUCTION
Data Quality Objectives (OQOs) are qualitative and quantitative statements
specifying the quality of environmental data required to-support-RI/FS
activities. OQOs are established prior to data collection and are critical
in developing a sampling and analytical plan consistent with CERCLA program
objectives. OQOs are developed to address the specific requirements of
individual sites and are based on the intended uses of the data. They
define the level or extent of sampling and analysis required to produce
sufficient data for evaluation of remedial alternatives for a specific
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 OQO
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 availaoility, site characteristics, public and
institutional considerations, and other factors. Therefore, each site must
have a unique set of OQOs. . .. ...
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 objective(s). The
sampling component of DQOs 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 witn
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 OQOs, this document addresses both.-
AW3-26 l-l
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DRAFT - Do not quote or cite.
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 3ACKGROUND
i
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
participation of the AAs in the development of OQOs during the stages in
which policy and guidance is crucial, and asked for identification and
scheduling of significant, ongoing environmental data collection
activities. A checklist for DQO reviews was issued in a memorandum from
Stanley Blacker on April 3, 1983. Appendix A includes a comparison of this
checklist with RI/FS DQO requirements. The Quality Assurance Management
Staff (QAMS) issued guidance to assist the Agency in development of OQOs
.(EPA 1984).
The approach to developing and implementing OQOs for the RI/FS process has
been established by a OQO Task Force comprising technical personnel from
EPA Headquarters (OERR and OWPE), Regions 1, 3 and 7,.and EPA remedial
contractors. The methodology used by tne OQO Task Force:involved applying
AW3-26 1-2
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DRAFT - Do not quote or cite.
the guidance provided by CAVS to the RI/FS process. As stated above, the
intent of DQO implementation has typically been addressed by various
planning documents prepares during an RI/FS. The efforts of the Task Force
included identifying the e-aments 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 becsses available.
1.2 THE RI/FS OQO PROCESS
The OQO process is designed to assure that all analytical 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 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,
geologist/hydrogeologists, toxicol.ogists field specialists, statisticians
and others, such as enforcement personnel, should interact with managers
early in the DQO process. OQOs ara 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 Plan.
AW3-25 1-3
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DRAFT - Do not quote or cite.
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. -l£
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. All
potential data users should be involved in this stage. Stage One is
common to both the analytical and sampling component of a DQO.
• STAGE TWO-A Although conducted simultaneously with Stage Two-8,
this stage is discussed as a discrete step in the analytical
component of an RI/FS DQO. This stage involves specifying the
level of analytical data certainty sufficient to meet the objectives
specified in Stage One.
• STAGE TWO-8 - 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 specifying the sampling
approach to be employed. As is the case for analytical options, a
variety of sampling considerations exist, including location (grids...
•stratified, random, etc.) types (grab, composites) and level of
sampling quality control (blanks, collocated). A more detailed
discussion of the sampling component will be presented in Section
3.2.
• STAGS 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-3. 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-8 - 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.
AW3-26 1-4
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STAGE ONE
-DEFINE PROGRAM OBJECTIVES
-IDENTIFY DATA USES
-INVOLVE DATA USERS
•EVALUATE RESOURCE CONTRA'INTS
ANALYTICAL COMPONENT
SAMPLING -COMPONENT
STAGE TWO-A -* . *" STAGE TWO-8
DEFINE LEVEL OF OAT* CERTAINTY
REQUIRED 3Y:
-SPECIFYING GENERAL USE CATEGORY
-SP6CIFYINQ QUANTITATIVE ACCURACY/PRECISION
-SPECIFYING REOUIHEO DETECTION LIMITS
-EVALUATING USE OF MULTIPLE-LEVEL
ANALYTICAL APROACH
DEFINE LEVEL OF SAMPLING REQUIRED 3Y:
-SPECIFYING AREAS AND CONTAMINANTS
OF CONCERN/RATIONALE
-SPECIFYING CRITERIA FOR DECISION MAKING
-EVALUATING SAMPLING APPROACHES
E.G..SHIOS. RANDOM. ETC.
-SPECIFYING QUANTITATIVE
SAMPLING CERTAINTY
INTEGRATION
STAGE THREE-A -*
-SELECT ANA/LTICAL 01
STAGE THREE-S
-SELECT SAMPLING
OUTPUT
SAMPLING AND ANALYTICAL 3LAN
COMPRISED OF 2QG STATEMENTS
Figure 1-1 RI/FS DQO Process
1-3
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ji-j-u . - ju"i,o«. quote or~ctte.
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 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
i
STAGE TWO B: To be added
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 objective.
- State QC sample level of effort (e.g., frequency of blanks,
replicates, and spikes)
STAGE THREE B: - To be added
OUTPUT OF THE RI/FS OQO PROCESS
- Detailed sampling and analytical plan
Note: Stages Two and Three can be interactive.
AW3-1S 1-6
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DRAFT - Do not quote or cite.
The OQO 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 case study
scenarios illustrating the OQO process for selected RI/FS activities.
AW3-26 1-7
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DRAFT - Do not quote or cisa.
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.
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 estaolished, 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.
Problem/Site Characterization
Initial field activities should establish which environmental 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.
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, eacn contaminated geological strata should be identified,
and each contaminates layer of a layered aqueous system should be
identified.
AW3-30 2-1
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TABLE 2-1
RI/FS Objectives
Applicable to Waste, Air. Surface Water, Soil, Groundwater, and Biological Hedla
Objective
HI
Activity
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)
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 environmental/public health threat;
identify applicable remedial technologies.
Evaluate costs to achieve relevant/applicable
standards
Evaluate effectiveness of containment
technologies
Identify potential receptor(s) and routes of
exposure
Evaluate costs to achieve relevant/applicable
standards; identify applicable remedial
technologies
Evaluate applicable standards or risk; identify
applicable remedial technologies
- Evaluate treatment schemes
AW3-19/1
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DRAFT - Do not quote or cit'e.
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. 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, the duration, extent or
nature of their exposure as a result of each potential remedial scenario
should be determined.
Identify Potential Remedies
Potential remedial technologies are identified in order to focus the
further gathering of site information. Remedial technologies are evaluated
based on current site information. Those that prove difficult to
implement, rely upon unproven techniques, or which may not achieve remedial
objectives within a 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.
AW3-30 2-3
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DRAFT - Do not quote or c
Determine the Effectiveness of Remedial Alternatives
Once potential remedial technologies have been identified and combined (i
appropriate) into comprehensive remedial alternatives, data should be
developed to fully characterize 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 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. 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/F5. is to determine the nature and
extent of the tnreat posed by the release of hazardous substances and to
evaluate proposed remedies. Achieving this objective requires that several
complicated and interrelated activities be performed; each having its own
particular set 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.
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 tne potential remedies. Each of these areas of the
RI/FS process involve various activities. These activities and their
objectives are presented in 7acle 2-1.
AW3-30 2-4
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DRAFT - Do not quote or cite.
T*e 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 tne RI/FS pro-cass:
t What contaminants are in pathways of concern above background?
• Are contaminants above action levels (e.g. What are applicable/
relevant standards, how clean is clean)?
• What are the three-dimensional 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 puolic health or the environment (e.g., source control,
alternate water supply)?
t Which alternatives are feasible and sufficient to protect public
health and :he environment.
AW3-30 2-5
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DRAFT - Do not quote or cite.
• 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?
• 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 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 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 oe 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.
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 or individual data collection activity; and, finally,
identifying data needs.
AW3-30 2-6
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DRAFT - Oo not quota
Or cite
Evaluating Existing Data
In many instances, previous studies have provided useful informat i.._
" upon
which further investigation can be based. For each of the major a,.
3 g •" eas in
the RI/FS process all available relevant information should be qan,
3 "Mered and
organized in a manner that will allow those additional data to fui^,,
Irill the
goals of the activities to be identified. Also important is the qu ,
valuation
of these data. The data developed through previous efforts shoul.) b
analyzed with respect to its quality to ensure that it is truly u.^ f ,
Quality assurance and quality control records should be evaluateM ^.
as simply the results of previous investigations.
A number of factors relate to the quality of existing data and ir« .
"• adequacy
for use in the RI/FS process; the working group has identified th*
following analytic considerations when evaluating data:
Age/comparabil ity - How long ago were the data collected? The u*hr
determine if the data collected, for example during the site invt»»»
*r'
is relevant or comparable to the present situation. It is not un,-,. ,
'>uai
the time between the site investigation and the RI/FS to be a co';^;a
years.
Analytic Methods - Were the analytic methods used in collecting >..,,
data consistent with present practices? The methods need not b* „ fi
Just because a newer method has a lower detection limit does no*;
necessarily imply that the older data are inadequate. However, -^
researcn might identify potential problems witn tne methods
Detection Limits - As implied above, care should be taken to
-
the detection limits of the analytical tests were sensitive to ^
standards and criteria against which the Agency is presently ev- ..>
data.
Laboratory - Was i~e laooratory performing the analysis in goo<* -*
1 — — ''
Are spike recovi^es .»cceptaole for intended use? Is tne
'J DJank
contaminated?
AW3-30 2-7
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DRAFT - Do not quote or cite.
2.2.3 IDENTIFY THE INTENDED USES OF THE DATA TO 3E 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 decisions that will need to be made
with the data that are collected. 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 ara 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 tne quality of data required for a given purpose. The
categories ars briefly described below:
• Healtn 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 tnere 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 conaitions/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.
t site Characterization - Data collected for site characterization
purposes are used to determine tne nature and extent of
contamination at a site. This category is usually the category that
requires tr:e most data collection. Site characterization data are
generates c-srougn the sampling and analysis of waste sources and
environn-?-'*i i nedi'a.
AW3-30 2'9
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DRAFT - Oo not quote or cite.
Sample Collection Considerations - Methods for sample collection methods
are as Important as methods for sample analysis methods. These
considerations 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:
• Were the samples collected using a random or non-random sampling
approach?
• Was the sampling plan followed? Were there deviations to 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 tne 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
contamination.
• 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.
0 How long were the samples held before being analyzed? As before,
this could relate to the amount of contaminant found. For example,
a holding time over 7-14 days for volatile organics increases the
likelihood of loss of contaminants from the samples. Chemists
should be consulted for appropriate holding time.
Once the available data have, been evaluated and compared to the data
requirements,.data gaps should ae identified.- Data needs should be
coordinated with intended use in tne decision-making process.
AW3-30 . 2-8
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Sines .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. Taole 2-2 presents a suggested format to
use. mis 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.
2.3 PRIORITIZE THE INTENDED USES OF THE DATA
Once the intended data uses are listed, which can be accomplished by using
the format just outlined in Section 2.3, the intended uses must be
prioritized. 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.
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
regarding analytica-1 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
OQO process.
The three categories may be represented on a aata quality continuum, as
follows:
Screening Engineering Confirmational
Increasing Data Quality
AW3-30 2-11
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DRAFT - Do not quote or cit<
Risk Assessment - Data collected for risk assessment purposes aTe
used to evaluate the threat posed by a site to public health and th
environment. The data must be qualitative so that the
chemical/physical properties, toxicity and persistence of
contaminants can be factored into the risk assessment. The dat-a
must also be quantitative to the degree that it may be compared g
against quantitative statements of health risk criteria (e.g., 10"
"cancer risk). Therefore, 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.
Engineering Screening of Alternatives - Data collected for
engineering screening purposes are used to evaluate various remedial
technologies. Usually, this involves performing bench-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.
Engineering Design of Remedial Action - Data collected for 4
engineering design purposes are used to evaluate and "fine-tune" trtl
performance of various remedial technologies. Usually, trtis
involves performing pilot-scale studies which precede design so that
any required adjustments/modifications can be maae 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.
Con fir/national - Data collected for Confirmational purposes are usea
to develop aosolute statements about the qualitative'and
quantitative presence or aosence of 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. Confirmational data are generated through
the sampling ana analysis of waste source areas and environmental
media.
Cost-Recovery - Data collected for cost recovery purposes are used
to document tne 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 tfte types of waste constituents which are characteristic
of a responsible party's waste stream and determining the media
affected by tnese constituents. Cost-recovery data are generated
through the sampling and analysis of waste source areas and
environmental rredia.
AW3-30 2-10
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DRAFT - Do not quote or cite.
Depending on the specific analytical methods and the level of effort
expended on quality control and documentation, these can.be significant
overlap among these general categories. Despite this, the use of the
general category concept can assist in the process of data quality
specification because it does not require as much knowledge of individual
analytical methods. 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.
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 OQO.
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. 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.
2.4 IDENTIFICATION OF RESOURCE CONSTRAINTS AND SPECIAL REQUIREMENTS
The final area to be considered in Stage One of the OQO development process
is the identification of any resource constraints or special requirements
that will affect the data collection activity. Time ana resource •
constraints can greatly influence the outcome of data collection and must
be. identified early to facilitate program design.
AW3-30 2-13
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TABLE 2-2
INTENDED DATA USES
V
SOURCE SAMPLING
SOIL SAMPLING
'CROUNOWATER SAMPLING
SURFACE WATER/SEDIMENT
SAMPLING
A IK SAMPLING
BIOLOGICAL SAMPLING
HEALTH &
SAFETY
j
SITE
CHARACTERIZATION
RISK
ASSESSMENT
1
ENGINEERING
SCREENING OF
ALTERNATIVES
ENGINEERING
DESIGN OF
REMEDIAL ACTION
CONFIRMATORY
COST-
RECOVERY
IM
I
r oach task, check the appropriate
AWi-JI/l
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DRAFT - Do not quote or cite.
3.0 STAGE TWO - DATA QUALITY REQUIREMENTS AND SAMPLING APPROACH
3.1 STAGE TAP 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. It 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. 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).
3.1.1 DATA QUALITY REQUIREMENTS
The concept of data quality refers to the level of uncertainty associated
with a data set. 3I/FS data are collected for a variety of uses.
Typically, 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 nost efficient use of analytical resources by defining
a given data quality need and selecting an analytical support option that
will produce data of that quality.
Sampling and analysis parameters must be defined. This should be done in a
way chat best acia.-esses tne proolem at hand and should be the product of
col laceration- between management and technical staff. The ultimate
decision, however lies wic.n the 3PM. •
AW3-L2 3-1
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DRAFT - Do not quote or cite.
The first issue to be considered is the sample turn-around time required
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.
Cost recovery issues, such as requiring fingerprint analysis, may also
present special requirements.
AW3-30 2-14
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DRAFT - Oo not quote or cite.
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,
the appropriate level of analytical support can be specified in Stage Three
to achieve maximum efficiency in the sampling and analytical program.
Once contaminants of concern are identified, multiple levels of analytical
support may be utilized simultaneously 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 s.ucceedingly 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 eacn ascending level of analytical support. The type
ana design of t.Tfs analytical approacn is ds'sminec ay hew the data being
collected will be uses. 3y strategically selecting wnic.n samples =re 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 cata collects^.
An example of C.TJS approach follows. Consider a hazardous waste site wnere
the soil is cort^na'ar! *itn volatile organic compouncs (VCCs). For tr-s
example, two as$•-.:-.":ons are:
AW3-12 3-3
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DRAFT - Do not quote or cite.'
Data quality requirements for a given program or activity can be specif
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 ""mTght~o"|
specifying engineering quality data with a given MDL or accuracy and -
precision information.
Examples of data use categories include screening use, engineering use and
confirmational use. Data needs/data use categories serve as general
guidelines and a 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 furtner classified to better define the quality that
will be required. For example, samples for risk assessment and litigation
uses may be required under the confirmational heading but each, use may
require a different quality of data.
AW3-12
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FIGURE 3-1
Integration of Analytical Support Levels:
a conceptualization of the example presented in the text.
Data
Percent of Samples Analyzed: 10%
Percent of Samples Analyzed: 25%
Percent of Samples Analyzed: 50%
Percent of Samples Analyzed: 100%
Cost
Quality and
Turnaround
Time
Rationale:
All samples are prescreened using Level I techniques. Based on this criteria,
30% of the samples are analyzed using onsite gas chrcsatcgrachy (Level II).
Using this information, a tctal cf 25% of the samples are sent cut for
analysis (25% Level 111/10% Level r/!. Many of these samples are split
sascies being analyzed by both levels and are Critical Data Points (G?s),
background samples or of strategic interest to the sampling program. Each
analytical level acts in a confirmaticnal capacity in relation to the level
beicw it. 3y 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_anaiyses as a calibration curve
for extrapolating concentrations frcm 300 Level I analyses, provided the 10
Level III analyses span Che concentration range of interest.
AW3-10
J-3
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1. The objectives of the sampling are to determine site boundaries and
direct contact threat.
2. The HNU.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-
this approach in general terms, data uses and data quality are .not
specified in this example. The analytical approach is as follows:
t All 300 samples are analyzed real time using HNU PI 101/OVA 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
semi-qualitative and quantitative results within a couple of days.
• Sased on these results, a specified number (e.g., 50) of samples arJ
sent to a commercial laboratory or to CLP screening (Level III) to "
confirm the field analysis.
• Twenty samples are selected for analysis by CLP RAS (Level IV) for
the Hazardous Substance List (HSL) compounds. Included in these
samples are all samples identified as critical data points (COPs).
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 '^ere utilized for .the
purposes of this example, but as few as two levels can be usec! effectively.
Figure 3-1 represents a conceptualization of this process.
*Use of trade names aoes not constitute an endorsement and is used for
discussion purposes j-iiy.
AW3-12 3-4
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DRAFT - Do not quote or cite.
Analytical options are selected by best matching the data quality required
with the data quality produced 'by a given option. The criteria used most
commonly 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 analyses 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 espected to be
obtained under normal conditions.
• 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
parameters are best expressed using a mixture of quantitative and
qualitative terms. 'All the PARCC parameters ara 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.
Eacn of the individual PARCC parameters is aaaressed 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 includes in
field sampling programs. It snould be stressed that these rates are
suggested guidelines only. As this table is only a summary, more detailed
information is induced in the text of tnis section. As is the case witn
all guidelines, t^ese recommendations rcust be applied on a site by site
basis.
AW3-12 3-7
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DRAFT - Do not quote or cite.
This approach can also be utilized in a time-phased manner, i.e., by
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.
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 how the data will be utilized,
it is the most accurate way to ensure that the 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 in Stage Three.
The output of Stage Two of the OQO development process is specific data
quality requirements. Stage Two also results in quantitative or
qualitative statements addressing each of the PARCC parameters and otner
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.
3.1.2 DATA QUALITY CRITERIA
The magnitude of uncertainty associated witn a data set is referred to as
"data quality." The amount of uncertainty that can ire tolerated depends on
the intended use of tne 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 neecec to support a specific decision or action.
Fundamental to this process is the use of separate analytical options which
produce data of Known cuality. Once QQOs are estaolisned, analytical
options to acnieve :-e OQCs nus; oe selected and integrated witn a sampling
plan for data col "*•::• on activities. Measures of data quality may be
affected by sanpl ir-; ^7/jr anafytical procedures.
AW3-12 3-6
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Precision
Precision is a measure of the reproducibtlity of analyses under a given set
.of conditions. Specifically, it is a quantitative measure of the variabil-
ity 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
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. Decisions on sampling plan development may
be more suojective and dependent on a phased approach than analytical
procedure specification.
The following definitions of duplicate samples are taken from the March 30,
1984 Calculation of Precision, 3ias, and Method Detection Limit for
Chemical and Physical Measurements issued by the EPA Quality Assurance
Manauement ana Scecial Studies staff.
Collocated samples are independent samples collected in sucn a
manner ir.at tr.ey are ecually representative of the parameters) of
interest at a given point in space and time. Exanplas of collocated
samples include: samples from two air quality analyzers sampling
from a common sample manifold, two water samples collected at
essentially trie 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 the1
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 'intarlaboratory precision.
information for the entire measurement system.
AW3-12 3-9
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TABLE 3-1
GUIDELINES FOK MINIMAL QA/QC SAMPLES
fOW FIELD SAMPLING PROGRAMS
DUPLICATES
I '
(X
Ml 1)1 A
Aqueous
So i 1 ,
Si.'di merit
Air
FIELD
(.01 LOCATED (IK REPLICATE
one in twenty
'
one in twenty
one in twenty
FIELD
BLANK
one in
twenty
one in
twenty
not
available
TRIP
BLANK
one per
day of
sampl iny
one per
day of
sampl iny
BACKGROUND
SAMPLE
in i n . of t wo
per sampl iny
event -media
in in. of two
per sampl iny
event -media
min. of two
per sampl iny
event -media
INTER-LAB
SPLIT SAMPLE
when required
to meet
objectives
when required
to meet
objectives
when required
to meet
objectives
Source
material
one In twenty
not ususally
rec|ii inert
when required
to meet
objectives
NOIL: 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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DRAFT - Do not quote or cite.
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
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 aver fielc replicate
samples for aqueous media is due to the hign degree of sample nomogenity
expected. Since collocated samples convey siore 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.
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• 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 groundwater 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
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.
mere are other issues that should be considered when specifying the
precision component of a OQO:
• 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
• The sample chosen to be collocated or replicated should be
representative of tne sampling rouna.
• 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 CL? requires laboratories
to use matrix spike duplicate analyses whereby duplicate samples are spi
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• 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
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.
Some of the biggest problems associated with field matrix spikes ara 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. 3ecause of this inherent
variability associated witn spike recoveries, trie acditicnal variaoility
fntroGucac by spiking samples in the field c=n 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 me spiking material and the technical capability of ,:ne
person doing tne spiking. Spiking materials that can be used are Standard
Deference Materials -;S?.Ms), EPA quality control ampules, or laooratory
prepared solutions naoe from pure compounds. SSMs are stand-alone
standards prep
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Accuracy
Accuracy fs 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 F).
Field/trip blanks. As an example of how the sampling process can impact
accuracy, consider the collection of groundwater 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 decontaminated sample collection
equipment (bailer, pump, auger etc.), and placing it in the appropriate
sample containers for analysis. 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 tne sampling event in tne actual sanple
containers and are kept witn tne investigative samples throughout the
sampling event. They are then packaged for shipment with the other samples
and sent for analysis. Ac no time after their preparation are the sample
containers opened before they reacn tne laboratory. All blanks should be
submitted for analysis "blind^"
The following guidelines for including blanks in-sampling programs are
suggested.
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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
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 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 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 tnat tne sample is representative
of the,underlying aquifer.
Representativeness can be assessed to some degree by tne use of collocated
samples. By definition, collocated samples are collected so that they ar=
equally representative of a given point in space and time. In this way,
they provide bocn precision and representativeness information. The
representativeness criterion is best satisfied by making certain that tne
sampling program contains the proper number of investigative samples.
In some cases, Ducce- or sample allocation constraints may require a
trade-off between Analysis of additional investigative samples and analysis
of additional ."? sjnples 'plan
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standards such as SRMs solves the "traceabil ity" .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 laboratory-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
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 OQOs 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 approac.n together with cne submittal of ,-}
blind, re-packaged SRM can provide a great deal of accuracy information.
It is the data user's responsibility to determine and "document tne requires
quality assurance/quality control and incorporate thac requirement into tne
DCO accordingly.
Representativeness
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 wnich is most concerned with the proper design of
the sampling prograns.
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Comparability in the data collection activity must take into consideration
if the events are even comparable in the first place. An examp.le would.be
trying to compare data from the same aquifer in a high water and.a. low
water situation. This criterion iS'most important whe;n conc.1usi.o-o-s.-a.re •••-.-
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.
3.1.3 OTHER ANALYTICAL CONSIDERATIONS.
There are a number of other factors which may affect development of OQOs
for a sampling and analytical plan. They include the following:
• Enforcement requirements
• Analytical quality control
• Media variability
• Method detection limit
t Matrix effects
• Tentatively identified organic compounds
• Data qualifiers
Enforcement Requirements
An SI/FS sncLild be conducted and documented so that sufficient data are
collected to make sound cecisions' concerning rerreoial action selection.
This is true for fund-leac, federal or state enfcrcenent-lead, and
potentially responsible party (PRP)-lead. The amount of data and
documentation should be similar for all types of RI/FSs. In other worcis,
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.
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circumstances, a balance must be made to ensure that the minimum number
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
under normal conditions. Completeness is usually expressed as a
percentage. 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 OQO process to assure that enough data of
sufficient 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 groundwater
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 ana every effort must 3e mace to obtain valid crata far
these samples. In some cases, taking critical data point samples in
duplicate may be appropriate.
Comparability
Comparability expresses tne confidence with which one data set can be
compared to another. In cne most general of circumstances, this refers to
the use of standard f:^\d ana analytical techniques and .the reporting of
analytical data .in ~n.* same units.-
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• Documentation should be sufficient to allow someone other than the
chemist or sampler to testify 2 to 5 years later concerning whicn
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
admissibil ity on its own merits.
• EPA's or the State's responsibility 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.
As stated previously, the above requirements pertain to civil cases only.
Criminal cases will require additional documentation and/or materials.
Analytical Quality Control
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 Sid (IF3) SAS
analytical support, the procedures are standardized and contract-specified.
When evaluating tne use of a non-01? laooratory or field operation, tne QA
plan of the laboratory or contractor should be reviewed. 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.
AW3-I2 3-19
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Enforcement/cost recovery actions do nave 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
requirements.
The following comments pertain to all data collected for RI/FSs (except
potentially 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 numoer, 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 maintained for sanples taken off-site for
analysis. This assures the decision maker that tne analysis given
is actually for the samples collected and has not oeen tampered
with. If analysis is performed onsite, documentation of We process
in field logs or otner media is sufficient. C-stody of samples
should still be maintained, hcv»ever, 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 witii standard industry practices. Methods utilized
should be referenced in tne RI/FS report or otner documents and a
statement givei tnac protocols were followed. Any deviation from
the references method should be documented and explained.
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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. Wh.en considering
the analysis of source materials, leachates or other complex matrices,
qualified analytical support personnel should be consulted to determine the
most appropriate analytical approach.
Method Detection Limit
The most basic consideration regarding detection limits is 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 is
so high that it required 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 lacoratory 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 tnat data quality parameters
are usually concentration dependent. The standard error of trie 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.
AW3-L2 3-21
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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 what 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
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. Using this framework, there is room
within a given support level for the data user to furtner adjust the
certainty of data quality output 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 true
continuum of analytical support services available to cover a wide spectrum
of data quality requirements.
Meg fa '/arfapility
Project planners ana data users should be aware tnat a great deal of
variaoility exists in regard to how a given analytical technique or met
responds to a given sample media. >fost of tne analytical methods utilized
in support of Rf/FS activities were developed, at least originally, for
aqueous samples anc -oc Tried for use with other media later on with varying
AW3-12 3-20
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developed. For non-aqueous matrices (soils, sediments, leachates, 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) and above action levels, samples may be re-run against a standard in
order to verify the compound parameter. 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 tne
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 tne
type of technical review requested by the data user.
Data qualifiers are ccmmonly used during the data validation process to
classify sample data as to it's conformance to QC requirements. The most
common qualifiers are listed below:
• A - Accepcaole.
• J - Estimate, qualitatively correct but quantitatively suspect.
• R - Reject, aaca not suitaole for any purpose.
• U - 'tot .letectea at specified detection limit (e.g., 10U)
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It is important to recognize that quantitative results reported at the
detection limit may not be reliable. If the action level of a contaminan
is 5 ug/1, an analytical method with a detection limit of 5 ug/1 may not be
suitable. Generally, the'limit of reliable quantisation may be
approximately two times higher than 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
results as being outside of criteria, whereas in all probability, the
replicate analyses show excellent precision. In general, caution must be
used when trying to apply 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 phenomena that occurs when the sample composition
interferes with the analysis of the analyte(s) of interest. 7nis can bias
the sample result either in a positive or in a negative way, witn the
negative bias being the most common.
The magnitude of a matrix effect is aest assessed by the use of matrix
spiices. Matrix spikes supply percent recovery information whicn accresses
the amount of bias present in the measurement system. This information can
be used to adjust reccrred 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 repor-ed values. It is not recommenced to actually adjust
sample values for p-rc^nt recovery unless a "worst case" scenario is being
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4.0 STAGE THREE - SELECTION OF ANALYTICAL AND SAMPLING OPTIONS
Stage Three of the DQO development process specifies the complete sampling
and analysis approach required to meet the objectives stated in Stage One.
It is in this stage that the actual sampling and analytical techniques
required to satisfy the objectives set in Stages One and Two are deter-
mined. 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-8.
The goal of integration is the selection of compatible analytical
and sampling approaches. Section 4.1 presents more detailed
discussion on the selection of analytical options and the use of a
multiple-level approach.
• • Stage Thrae-3: This stage involves the selection of the sampling
approach to be employed. As stated above, integration with Stage
Tnroo-A is of utmost importance to ensura compatibility with the
analytical option(s). 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-8.
4.1 ANALYTICAL OPTIONS
Staae Three consists of evaluating oojectives, resource constraints, anc
data quality requirements to detaraine tne most appropriate type of
analytical support. Formulating an analytical option to meet the QQO for a
specific activity may require selecting procedures from more than one
analytical level .
If requirements ara impossible to meet, such as research quality data with
a one day turnaround requirement, compromises must be macie. The technical
staff will evaluate possible alternatives and present their findings to the
Remedial Project Manager (RPM). The selection of an al ternative -is the
responsibi 1 i 'j "r -ne
AW3-5
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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
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 8 OF THE RI/FS PROCESS
To be prepared
AW3-12 "3-24
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Work for Organlcs Analysis - multi-media, multi-concentration, July 1985
revision.
4.1.4 LABORATORY ANALYSES-- 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 quantisation 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 laboratory data to support engineering studies.
Suitable for engineering studies - i.e., design, modeling and pilot/bench
studies. Also can be used for site characterizations, environmental
monitoring, and confirmation of field data.
Level III laboratory analysis provides the following:
• Data are used to support engineering design parameters.
• Data to be used to evaluate the site for further action, e.g., to
determine extent of environmental contamination.
• Rapid turnaround of data can be available.
• Detection limits for presence or absence of compounds comparable to
CL? SAS.
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CLP generated data provides for the following:
• Confirmed identification and quantisation of compounds (for HSL
parameters only unless otherwise specified) to the detection
specified in the IF3. ^
• Tentative identification of a contractually-specified number of
non-HSL parameters.
• Data deliverable package supplies sufficient documentation to allow
qualified personnel to review and evaluate data quality.
• Data may be used uniformly for all Superfund program activities.
Considerations (Level IV)
• Detection limits may not be sufficient for toxicological concerns
• Cost - CLP support is one of the most expensive routine analytical
support available to the Superfund Program, e.g., RAS for organics-
is about 51,000/sample. RAS for inorganics is about $200/samp1e-..--
• Time - RAS is contractually operating on a 30-40 day turnaround
although delays can occur.
Documentation Availaoie (Level IV)
The IF3 is very specific concerning the amount of laooratory documentation
that is supplied with every data package. The 3AS deliverables package
contains information on initial ana continuing calibration, GC/MS training,
surrogate percent recovery, and matrix spixe/natrix spike duplicates. In
addition, hard copies are provided of reconstruction ion cnromatogrims, GC
cnromatograms, 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 MOL Information (Level IV)
The Environmental Monitoring ana Support Laboratory - Las Vegas (EMSL-LV)
.is currently compiling accuracy, precision and MOL information for the RAS
program, whicn will se incorporated in a later revision of tnis document.
Appendix 3 contains :-e performance criteria specified in tne Statement of
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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 (IF3) - 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 availaoie
through CL? SAS and regional EPA E3D laboratories
Uses 'Level IV)
Level IV data quality is suitable for most SI/F3 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.
AW3-5 4-7
-------
DRAFT - Do not quote of c.ite.
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.
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 comparability 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 .-nay 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
famili.ar with the method. Once the method is understood, turnaround
time snould be method-specific.
• Relative .Vunicer of Samples Permitted - This will be determined by
factors inherent in the metnoo and by the numoer of laboratories
aole to perform the analysis.
Documentation Availaole (Level NS)
Level NS provides specific, case-by-case analytical support. The amount: of
documentation availaole to the user will vary depending on the sophistica-
tion of the technology used. If method development is required, t.nis
information should be requested and reviewed by the user.
AW3-5 4-5
-------
lll'ir.AI AUMIIICAI
mOIIIIIEMINIS fOll AN Hl/t S
Hi/rs ACIIVIU
o Initial Miioiniials
mjK.llvtlSI
Assess UMltllng silo conditions
UOIIIM al air quality lor huallh A
ntlulyj tolled llmllud
anvlruiimiinl al samples (surface
water, MI uiindwaliti I II existing
data itnf It.lunl; asstiss nuod Ii*
rutfwivitl , olc •
UMRAI.
DAIA CAICGOU
- Screening
IFrtL OF
ANA1.TIICAL SUCTOHI
lolal Vapor Scan (level l>
fluid Screening (level III:
Collect air samples via ambient
grali or torbonl/fhermal
diisivb/Photovac. tluadspace
analysis using OVA/ltiolovac all
(•IT VOCs.
RATIONALE
VOCs most ooltlle conlamlnanls;
likely Indicators Itir pathway
•Igrallon on almost roal-lluo
basis; data to to usod lur
general study dnslgn.
•odlIIcatIon; health and saluty*
i ki-%1 In/ill I-si In SnliMif la. ii
In...-.I I,,.il I.ins
• i lln-sllii/OII-tllo M>nllurl.^ Mull
InvlallalIon
o **llasel I nil* Snnpllng llounil
o "Uinl If m>ttiif y" Sampling Ittmml
f>uturnliiu eMtenl/i|uiiiit 11 y ul
on-sllu cunt »«lnallun via
bdilnijs, lust pits. iil<:>
Sample all n*n veils; surface
valw |ioliils] sudlflHints;
adilltlonal vills, ulc.
Samp In all ne« vttl It) surlacu
wal«N' |Hilnls; sudloviiils;
aiMlllniial vilU, iilc.
He-sample (joints based tin
l.avnllim .lila
- Scruonlng - Held screonlng (level III):
I n
Nuod United cont Irmal Ion data.
VOCs "ore mobile In yround».it>ir;
data to be used to ad|usl veil
location, determine op11mum mill
screen placement; chuck vast*
vater lor Inducud conlamlnatIon;
vasle handling needs.
Provide Initial data hasn lo
begin feasibility study; use lo
carefully design sampling plan
for CLP slots; Identity any data
gaps before lull diimobl 11 * at Ion
ol Held lean.
Provide litigation quality il
to adequately itocinMinl cosl
recovery; confirm screening
data.
o Inaslblllly Study
- pilot iliiillni, e.g.
•jjltir Ii ii.tlmnnt
Akiess fin Ilier si le-spocl I Ic - Screening
dim arlm I >l K:s IIN allernallve L'nglneei1 Ing
eviiliMl Inn Conl Irmal Ion
- Field screening I VOCs I (level
II) - check Mitral Ion effluent
fiir breakthrough; air stripping
Impact, etc.
- OC Screening (0/N/A) (level 11/
III - use whure these parameters
are ol concern.
- Httals utiere Indicated
- level IV or level III lor
limited
confirmation/documentation of
treatment effectIvnness.
- level NS as required.
Provide Mreal~tlmon asst'stuunl
of various treatment
al lernal I ves; data lo t>u usod In
alternative evaluation; Lnvnl I
samples to irovldu firm ruoi*"d
of effectiveness.
Level NS If si t«-sp.icl He
conditions warrant. o.
-------
DRAT I - DO not quo! 9 or cite.
<-i $iMM«r of Awirnc/u. uvns rm RI/FS
tyllon
I oval NS
l»vul III
I aval II
I aval I
fypu ol Analvilt
- ftin-ciinvant lal
paramulort
- MJ! l.o.) -specific
duluclliHi Haiti
- Modification of
e* 1 kl l«y nut hods
- AjtputtJI* H paranafert
t>l U/XS, A4; IIP.
- In" t'l'U Jofoitlon Halt
- y
It,"; Inurganti.i liy AA;
Mil
- funfatlve II); analyte-
- Uitactlon Hal It vary
fiun lov |)|MH lo lo* ppb
- Iota) organlc/lnnf yenlc
vapur italuil lim iiil'iy
psonce of
* I IHjIneiM Iny usut
• W't autl 1 ng
- (Valence i» Jlnonco of
- Relative coni.untrallont
- (nglnaarlng
* Atlltl In tam|ile
local loni
- llel.l iiruuiilng
- Ikiallli and taluly
Llnltallont
- Hoqulret method
lion
- Mochanlm lo obtain
servlcet raqulrat
tpeclal leadline
- fenfaHre Idtintlflca-
tlon of nan -HSt
paraAolert
Required for Validation
ot pacAagus
- Tentative 10 In »OM
caket
- lonlall va II)
- lechnlquai/lnttrtuwntt
United (Uklly lo
volalllet
- Inttrununts res|»ond to
nalaral 1 y -occurring
Cfjvpoundt
Data Quality Cott Ila»
- Motliod-tpeclflc - Initially high. If -.*>nfht lo yaart
not hod devalopawnt
It raqulrad'
- Goal It data of linoon - ll.OOO/Saepla - Contractually, JO
Out Hit dayt - 40 dayt
' Rigorous QVOC
- Slallar detection - flOOOYVM*>le - 71 dayt
ll«lt> lo CLP
- Lett rigorous QA/QC
- IXipundant on OVOC - |l»-<0/S*nple - Real-line to
ttept enployed tavaral hourt
- Data typically reported
In concentration rangat
- If Inttrunants call- - togllglble. If - Raal-tlna
brated and data capital cotl*
Interpreted correctly, ewcludud
can provl.Vt lnf*'*--» ' •••
-------
DRAFT - Do not quote or cite.
• 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 non qualitative; quantitative only as total
brganics.
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 oojective of this type of support is to provide the RI/FS process witrt
data that cannot be obtained through standard avenues of analytical
support.
Types of Analysis Available (Level NS)
.Analytical support of this type may involve tne research, development ana
documentation of a method, or more typically, the modification of an
existing method. EMSL, Las Vegas can be consulted for protocol
availability, mocification or development. Level NS methods are availaola
through CL? Special Analytical Services (SAS), university laboratories,
commercial laboratories, National Enforcement Investigation Center,, ana
Environmental Services division. The types of analyses available tnrougn
Level NS support .^ay ultimately be technology-limited.
AW3-5 4-3
-------
DRAFT - Do not qudte or'ci.te.
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.
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
investigations/feasibility 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 tne aata
produced at each level.
• LEVEL NS - Characterized by non-standard methods of analysis v»nfcn
may require .Tietnod modification anc/or development.
• LEVEL IV - CL? Routine Analytical Services (RAS< Invitation For 3fc
(IF3J Analysis. -Tiis level is characterized by rigorous QA/QC
protocols, documentation and provides qualitative and quantitative
analytical data. Some regions have ootainec similar support via
their own regional laooratories or subcontracting througn tne
REM/FIT programs.
• LEVEL III - Laooratory analysis using methods other than the CL? RAS
IPs. THTs I eve! is usea primarily in support of engineering
studies using standard £?A approves procedures.
• LEVEL II - Fi-rl.: analysis. This level is characterized by the use
or portao'-r analytical instruments which can be used on-sita, or in
mobile lar-C'-i-^ries stationed near a site (close-support laos).
Depending -,- - :ne types of contaminants, sample matrix, and
personne: j--"'5, Hualic»t:ve and quantitative data can De obtained.
AW3-5 " 4-2
-------
TABLE 4-3 SU-B46 ACCURACY, PRECISION, AND MDL INFORMATION
Method
Number
ORGANIC^:
no to
U020
11030
8040
1)060
8080
0090
8100
8120
8140
8150
8240
8250
8040
Method Name
tlalofjonated Volatile Oryanics
Aromatic Volatile Oranlcs
Acrolein, Acryloni trlle,
Acetoni trile
Phenols
Esters
Organochlorine Pesticides
and PCBs
Nitroaromatlcs and Cyclic
Ketones
Polynuclear Aromatic
Hydrocarbons
Chlorinated Hydrocarbons
Organophosphorous Pesticides
Chlorinated llorbicides
Volatile Organlcs
GC/MS Semivolatlles (Packed
Column)
GC/MS Somivolatilcs
(Capillary)
Data
Source
SU 846
SU 846
SU 846
SU 846
EPA 606
SU 846
SU 846
SU 846
SU 846
SU 846
SU 846
Accuracy as
X Recovery
75.1 - 106.1
77.0 - 120
96 - 107
41 - 86
82 - 94
86 - 97
63 - 71
NA
76 - 99
56.5 - 120.7
NA
95 - 107
41 - 143
NA
Precision
ii \
U l
2.0
9.4
5.6
7.9
1.3
1.3
3.1
NA
10
5.3
it *
NA
g _
20
NA
')
-25.1
- 27.7
- 11.6
- 16.5
- 6.5
- 6.5
- 5.9
- 25
- 19.9
28
-145
MDL
Mq/l
" «J*
0.03 - 0.52
0.2 - 0.4
0.5 - 0.6
058 - 2.2
0.29 - 3.0
0.29 - 3.0
0.06/ND
MA
nf\
0.03 - 1.34
0.1 - 5.0
O.I - 200
1.6 - 6.9
0.9 - 44
hi ft
NA
AU3-1B/1
-------
DRAFT - Do not quote or ci't
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 SlOOO/sample, depending on analysis.
0 Time - Turnaround time for Level III laboratory analysis orgam'cs is
expected to be about 21 or 14 days.
0 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 analys
requested. Data users should review an example sample report issued by
laboratory for the analysis requested to determine if tne degree of
documentation supplied is adequate or whether additional information must
be requested.
Available Ac-curacy. Precision MDL Information (Level III)
Accuracy, precision and MDL information tinat is considered representative
of this level of analytical support was compiles from S*~3~o, Test Me'.-icas
for Evaluating Solid Waste Physical/Chemical Methods, Second Edition, (EPA
1982). This information is compiled in Taole *-3. These procedures are
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 "besc case'1
information when non-aqueous media samples are analysed. .Also, these data
are presented irrespective of the sample pretreatme.it or preconcentration
AW3-5 4-10
-------
DRAFT - Do not quote or cite.
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 (MDL) 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 MOLs 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 MOL.
0 Precision data are used to measure the variaoility of these
repetitive analyses reported as a single standard deviation or, as a
percentage -of the recovery measurements. For presentation purposes
accuracy, precision and MOL 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 metnoa cited should be consulted.
Maintaining quality control data bases for hazardous wasta site analytical
support is a dynamic process because of new analytical instrumentation ana
techniques, tne trend toward improving setscticn limits, and an expanding
list of analytes to be evaluated. A lack of quality analytical standards,
proven analytical tecnniques (particularly for non-aqueous media), and a
central data base severely limits quantitation of quality control data.
AW3-5 4-13
-------
TABLE 4-3
Method
Number
Method Name
Oata
Source
H3IO
Polynuclear Aromalk
Hydrocarbons (IIPLC)
SW 846
: MetdJs (ICAP)
Series Metals (FLAME)
7000 Series Metals (FLAME LESS/GF)
/470 Metals (MERCIWY)
9010 Cyanides
9030 Sulfides
NA Not Available
- 116
7.3 - 12.9
EPA 200.7
EPA 200
EPA 200
EPA 245.2
EPA 335.2
EPA 376.1
NA
MA
If/1
NA
87 - 125
05 - 102
NA
ll/*
3 -
NA
NA
0.9
0.2
NA
21.9
- 4.0
- 15.2
MOL
Mg/1
0.03 - 2.3
]-3 - 75 Mg/1
0.01 - 5
°-0°l - 0.2 Mg/1
0.0002
0.02 Mg/1
1 Mg/1
AW3-1H/2
-------
DRAFT - Do not quote or cite,
Uses and Limitations (Level Hj
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 ana extent of release to amoient air).
t Detection limits for volatiles range from 0.5 ppb in air- 2-3 ppb in
water; 10 ppb for soil. Detection limits for PC3s in soil are aoouC
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 n-xmitaring.
• Volatile organic data can be used as early indicator or tracer of
off-site contaminant migration. Volatiles are t.ie most mobife of
contaminants in all media, and are typically found at some
concentration at virtually all sites.
Limitations. Field analysis generated data nave t~e following limitations:
t Subject to interferences in complex .-natricis.
• Rapid analysis tecnniques are most ssplica^e for volatile organic
compounds. Most of tne literature ana prccac-jres for fieia an,
pertains to volatiles.
• Trained personnel ana equipment must be availasTe to perform ?;
field analyses.
• Data must be reported as tentative.
Considerations (Level II)
*- S^nr0"311^ " °ata ^"^ for field analysis is dependent upon tr.e
QA/QC steps taken in the process, e.g., docjJentarfon of blank
injections, calibration standard runs, runs of qualitative standards
between samples, etc. •
AW3-5
4-15
-------
DRAFT - Do not quote or ci
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 fiejd
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
semi-qualitative 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,
including volatiles, Sase/Neutral/Acia (3/M/A] extraczaple organics, ana
pesticides/PCSs. Inorganic analysis can also be conducted using portable
atomic absorption (AA) .or other instruments. These analyses can be
ootained tnrougn tSD or remedial contractors.
Tne simplest type of field analysis is for volatile organic compounds.
Since the headspace analytical technique is used, the sample-preparation is
minimal. Extractaoie organic and inorganic analyses require additional
time and equipment.
AW3-S 4-14
-------
DRAFT - Do not quote or cite.
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 instrument. 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 livelihood of showing significant contamination through
subsequent analysis.
• Real-tine data to be used for health and safety considerations
during site reconnaissance.
AW3-5 4-17
-------
DRAFT - Do not quote or
t 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 moDilizinq
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 515. Per-sample
costs for mobile laboratory analyses may approach 5100.
0 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 chromatograpn 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
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 nave
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 wn;c:i *i11
contribute significantly to the Level II data quality criteria data base
are scheduled for completion by the end of 1935. These projects ars an EPA
Headquarters-directed compilation of all Level II analytical methods
currently used by Field Investigation Teams (FITs) and the operation of a
mooile field'analytical laboratory being directed by EPA/ESO in Region I1/.
Tne 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 incorporate into tnis document. Due to the increasing interest in
this analytical support.level, CC cata _from many different sources shoul i
be avail-able soon.
-------
DRAFT - Do not quote or cite
• 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:
• Some instruments show a response to naturally occurring,
non-hazardous substances (methane).
• Quantitative data for total organics.
• Qualitative data cannot be produced.
Considerations (Level I)
t 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 Availaoie (Level I)
A har-Cjpy strip chart recorder output can be obtained for instrunencation
operates in che general total vapor survey -^oce but it is not conroon
practice. The most available form of documentation for chis support level
is tne field operator log book. Sample identification, location,
instrument reading, calibration and blank information is usually contained
in the field log book.
AW3-5 4-19
-------
TABLE 4-4 FIELD ANALYTICAL SUPPORT ACCURACY INFORMATION
Range of Accuracy
Method Expressed as Relative Percent Difference*
1. Volatile organics 1n 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.
AW3-16 4-18
-------
DRAFT - Oo not quote OP cite.
5.0 IMPLEMENTATION OF THE OQO 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 araa southeast of the site. Each is served by a private well.
Two municipal production wells (#1 and #2) are located about 0.5 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 Idlawild 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
salvage metal operation. Local waste haulers 'would typically bring in used
drums for reconditioning. Invariably, the drums contained small quantities
of waste solvent whicn were disposed of by dumping into an unlined.pi;
(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 druns 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..
AW3a-2 5-1
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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,
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 DQQ 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 separata 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 is one wfticn incorporates multiple levels of analytical support
with a'sampling plan desiun that is specific for each level of analytical
support utilized.
AW3-5 4-20
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The pit measures about 60 feet by about 80 feet, and has an average depth
of 4 feet below ground surface.
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 8
on Figure 5-1). The majority of these transformers were in poor condition
and leaking oil containing polychlorinated biphenyls (PC3s). 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.
Sicin is a casror bean derivative and is typically in the fora 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.
AW3a-2 5-3
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DRAFT - Do not quote OP cite.
5.1.2 HYOROGEOLOGIC 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
site to over 100 feet in the vicinity of the Idlewild municipal well field.
A continuous layer of tight till is present on1the 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 well field.
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 groundwater flow in this
aquifer follows the bedrock surface previously described. That is,
groundwater flow is generally southeasterly from the XYZ site vicinity to
the Rambling River. Depths to groundwater range from 5-10 feet near the
XYZ site to E-5 feet in the vicinity of the Idlewild municipal well field.
The thickness of the aquifer in the vicinity of the Idlewild municipal
well field is 95 to 100 feet. Yields are estimated to be in excess of 400
gallons per minute (gpra).
Surface water and snallow groundwater discharge on the southwest border of
the XYZ site is to the swamp located there. The swa.-np 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 well field.
AW3a-2 5-4
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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.
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 absoroent 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: '-
Trichloroethylene 100-1500 ppm
Trans-l,2-dicn1oroethy1ene 10-50 ppra
1,1,1-Trichloroethane 10-15 ppra
Benzene 20-40 ppm
Toluene 100-20 ppm
Although analyses were conducted for other organic compounds ana
inorganic parameters, none were detected.
• Area 3 - Transformer Pile - Dimensions approximately 50 feet wide by
100 fest 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,
PC3s were the predominant contaminants detected. Total PCS
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 8 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 PCS concentrations of 50-100 ppm.
AW3a-2 5-5
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Area C - DoD Wasta 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.
Offsite Contamination
The site inspection team subsequently installed and sampled three shallow
groundwater 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:
Trichloroethylene 5-10 ppm
Trans-l,2-dichloroethylene 1-5 ppm
1,1,1-Trichloroethane 1-5 ppm
Benzene 10-20 ppm
Toluene 50-100 ppm
Several private drinking watar wells southeast of the site were sampled,
analyzed and found to contain volatile organics ac the following levels:
Trichloroethylene
Trans, 1,2-di cnl oroethylene
1,1,1-Trichloroethane
Benzene
Toluene
20-30 parts per billion (ppb)
NO
NO
100-200 ppb
100-200 ppb
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:
Municipal Well #1
Trichloroethylene
Trans 1,2-dicnloroethylane
1,1,1-trichloroethane
AW3a-2
5-6
1500 ppb
100 ppb
50 ppb
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Benzene 15 ppb
Toluene 10 ppb
Municipal Well #2
Trlchloroethylene 100 ppb
Trans 1,2-dichloroethylene 20 ppb
1,1,1-trichloroethane NO
Benzene NO
Toluene NO
Municipal Well #3 All. NO
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 watar
needs wera to be supplied by the development of additional wells
along the Rambling River have been placed on hold.
• Idlawild Municipal Well #3 is being sampled and analyzed for
volatile organic parameters on a *ee
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DRAFT - Do not quote or cite.
5.1.5 DATA COLLECTION ACTIVITIES
The scoping of the RI/FS has identified the following general data needs to
support remedial alternatives evaluation:
• Source Control Measures - The volume of contaminated soil in areas
A, 8, 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.
• Management of Migration Measures - The principal question to be
addressed involves the groundwater 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 groundwater samples during pumping tests, bench-scale
treatment studies and pilot tests.
A secondary management of migration issue is the movement of. PCS _
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/ENOANGERMENT ASSESSMENT
To be prepared
AW3a-2 5-3
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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 groundwater
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 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
treataent procsss will be determined by treatabil-ity assessments of
these and several other leading technologies. 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 detactaole levels of 1,1,1-trichloroethane, benzene and
toluene. Theoojective of any well head treatment system is to remove
these contaminants.to below concentration levels that are adverse to
human healtn and the environment since most of these chemicals are
suspected carc'^ogens. The stated action levels for this treatability
study will be :.j acnieve concentration levels below the excess
AW3a-2 5-9
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DRAFT - Do not quote or cite,
lifetime cancer risk of 1.0 x 10 for the drinking water supply.
Trichloroethylene (TCE) has an estimated excess lifetime cancer risk
of 1.0 x 10 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/l which takes into
account the initial concentration of other contaminants present.
In general, 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.
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 strippaole 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 cnoica. 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 effective-
ness of the treatment system for all volatile organic compounds. This
compound, although not the least strippable compound, (toluene is the •
least strippable) fs found in the water at concentration levels high
AW3a-2 5-10
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DRAFT - Do not quote OP cite.
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, 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 fully
evaluate the treatment system 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 following tables are an outline format of the data quality
objectives developed for the three phases of the air stripping pilot
studies.
AW3a-2 5-11
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DRAFT - Do not quote or cit,e,
DATA QUALITY OBJECTIVES FOR AIR STRIPPING PILOT STUDY.
OPTIMIZATION PHASE
Stage 1
• Optimize operating parameters
• Establishment of optimum operating conditions
9 Real-time analysis with the capability for a wide range of
concentration levels (5-2,000 ug/1)
t The lowest achievable contaminant concentration levels in
the effluent available using real-time procedures
Stage 2
• Screening quality data
• Minimal QA/QC required
• PARCC parameters addressed in text
Stage 3
• Portable gas chromatograph utilizing the headspace
technique to analyze for volatile organics of concern
• No method modification
t Data are suitable for optimization only
• Blanks will be included at 20%
• Replicates will be included at 20%
AW3a-2 5-12
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DATA QUALITY OBJECTIVES FOR AIR STRIPPING PILOT STUDY
MONITORING CONTINUOUS OPERATION
Stage : - , umtv with respect to changes in
• Monitor treatment variability wiu K
conditions
. Treatment feasibility for drinking water supply
. Rapid turnaround analysis (2 days) and cost effective
n • L- * * ^ ^« for use 1n this analysis are 1.0
• Orinkyig water standards r°r ^ .
x 10'° excess lifetime cancer nsfc.
Stage 2
• Engineering quality data
• Higher degree of certainty required
• PARCC parameters addre**** 1n text
Stage 3 , - , , u ..lysis utilizing SW-846 procedures
• Commercial laboratory *";" /SJi
0 No method modification
t Detection limits for GC/*S ' 5'10 ug/1
• Detection limit for GC - -z'2 ug/1
•* UT « -.^r^nq pilot plant operation and
• Data suitable for monT^r.ng v ^.^ treat;aent opC1Qn
determining overall su*'*011 J
• Blanks will be include^ -»c 10%
ac 10%
• Duplicates will be inc" ^
AW3a-2 5"13
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DATA QUALITY OBJECTIVES FOR AIR STRIPPING PILOT STUDY
DESIGN CRITERIA FOR FULL SCALE FACILITY
Stage 1
• The development of specific design criteria for the design
of a full scale facility
• Confinnational 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 watec standards of all contaminants must be below
the 1.0 x 10 excess lifetime cancer risk
Stage 2
• Confirmational quality data
• Maximum level of QA/QC and documentation required
• Highest degree of PARCC characteristics as addressed in
text
Stage 3
• Contract laboratory program routine analytical services
• No method modification
• Detection limit for GC/MS data approximately 5-10 ug/1
• Data is suitable for all RI/FS purposes
• Blanks will be included at 10%
9 Replicates will be included at 10%
AW3a-2 5-14
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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
effective 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 subtaslc
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 subtasic 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.
AW3a-2 5-15
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DRAFT - Do not quote or citse,
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: ESTA8LISWENT 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 recjuirsnents identified in Stage One for tne 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.
AW3a-2 5-15
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DRAFT - Do not quote OP cite,
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.
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 505 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 bias.
Representativeness. Samples will be taken from an influent and
effluent spigot hard pliunbed into the process stream. Samples will be
drawn after the process has been allowed to run for a minimum of 30
minutes to allow tne process to "warn-up." Samples will not be taken
when the systam is in a start-up or shut-down moce.
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.
AW3a-2 5-17
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DRAFT - Do not quote or cite.
Comparability. 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
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 pre-design 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 ,-nonitoring phase are addressed
below.
Precision. The precision of Method 3240, 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 3240 is
reported to be between 9 and 28%, depending on the particular
compound. The precision of method 3010 is 2-25.1% and the precision
of method 8020 is 9.4-27.75, reported as the range of the standard
deviations of the percent recovery data, reported as a percentage.
AW3a-2 5-18
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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 75.1-1-6.15 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.
Comparibility. See Comparability, Optimization Phase.
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 (RPO)
range for volatile organic analysis is listed in Appendix 8.
Accuracy. The contract required matrix spike recovery ranges for
volatile organic, acid/base-neutral extractables are listed in
Appendix B.
AW3a-2 5-19
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FT -
Do not quote OP cite,
mion Phase.
OPTI°NS
To best meet the
estal),isl,e(1
•"»• I" addition"
R« '- «». en '
- «d SOPS are ,„,.
any othi|r
« plant process
al laboratory
of th(s phase.
-7*t1e.l
M
' *
"°
-din
" ' '
1a
by
-
AW3a-2
COmP°unds that
5-20
may be
but
-------
DRAFT - Do not quote or cite.
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 confirnational 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.
The quality control sample level of effort is as follows for all
pnases.
Optimization Phase
201 blanks
205 replicates
Continuous Monitoring and Design Phases
101 blanks
105 replicates
5.5 HEALTH AND SAFETY SITE CHARACTERIZATION
To be added
AW3a-2 5-21
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DRAFT - Do not quote or cite.
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 03223-73, 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, O.C.
Ecology and Environment, Inc. 1982. FIT Operations and Field Manual, HNU
Systems PI 101 Photoionization Detector and Century Systems Model OVA-128
Organic Vapor Analyzer, prepared for U.S. EPA, Washington, O.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
Goulden, P. D. and Aignan, 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. 1963. Determination of Sub-Microgram Quantities
of Mercury by Atomic Absorption Spectrophotcmetry, 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. 3. 1972. Cold Vapor Method
for Determining Mercury, AWWA, Vol. 54, p. 20. January.
AW3-28 6-1
-------
DRAFT - Do not quote or cite.
Lockheed Engineering and 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, O.C.
Organochlorine Pesticides and PC3s, Method 608; 2,3,7,8-TCDO, Method- 613;
Purgeables (Volatiles), Method 6224; Base/Neutrals, Acids and Pesticides,
Method 625; Federal Register, Vol. 44, No. 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, East-nan 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
Wastewatar Components by Gas Chromatograpny - Mass Spectrometry.
Analytica Oiiaiica Acta.
Spittler, T. M. 1980. Use of Portable Organic Vapor Detectors for Hazardous
Waste Site Investigations. Secona 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 ?C3s 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.
AW3-28 6-2
-------
DRAFT - Do not quote OP cite!.
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 lie System. Technical Pub. #TA9-0460-00, Tarrytown, New York,
10591 . . . . -,- .-. :.-.,... ..--•• ;
U.S. Environmental Protection Agency. 1982. Draft Guidance For
Preparation of Combined Work/Quality Assurance Project Plans for Water
Monitoring. November 15.
. 1980. Environmental Monitoring and Support Laboratory, Cincinnati,
DRTo, Interim Methods for the Sampling and Analysis of Priority
Pollutants in Sediments and Fish Tissue. October.
. 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.
. 1979. Methods for Chemical Analysis of Water and Wastes. EPA Pub.
oU074-79-20. March.
. 1982. Office of Solid Waste and Emergency Response, Modification (By
Committee) of Method 3050. SW9846, 2nd Ed., Test Methods for Evaluating
Solid Waste. July.
. 1977. Procedures Manual for Groundwater Monitoring at Solid Waste
Disposal Facilities. EPA 530/SW-611.
. 1981. EMSL, Users Guide for the Continuous Flow Analyzer Automation
System. Cincinnati, Ohio.
. 1984. OE3R. User's Guide to the Contract Laboratory Program. July.
. 1984. Menwrandum frcra Stanley Blacke, about CAMS Checxlist for DQO
Review.
. 1984. Test Methods for Evaluating Solid Waste, Physical/Chemical
(Methods. SW-346.
. 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,
CTTculation of Precision, Bias, and Method Detection Limit for Chemical"
and Physical Measurements. March 30.
. 1984. Soil Sampling Quality Assurance User's Guide. .EMSL-LV
600/4-84-043. May.
AW3-28 . 6-3
-------
DRAFT - Do not quote or cite."
. 1985. Draft DQO Report for SI Superfund Process. March.
Wlnefordner, 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, 8. M.t Gel
Permeation Chromatography in the GC/MS Analysis of Organics in Sludges.
USEPA, Municipal Environmental Research Laboratory; Cincinnati, Onto
45268.
AW3-23 .6-4
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DRAFT - Do not quote or cite,
APPENDIX A
REVIEW OF QAMS OQO CHECKLIST
-------
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.
AW3-13 A-l
-------
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 DQQ 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.
8-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 1.0
summarizes SI/FS objectives.
Simply stated, the decision made
for each oojective is whether or
not a remedial response is
justified. The presence or absence
of contaminants and the
concentrations, if present, drive
the decision(s).
3-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 whicn 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.
AW3-13
A-2
-------
SUMMARY OF OQO CHECKLIST ITEMS WITH RESPECT TO
RI/FS OQO APPLICABILITY (continued)
OQO CHECKLIST ITEM
8-2. 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.
3-4. 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.
8-5. A definition of the
population to which each of the
conclusions apply, including
definitions of all subpopulations
or strata.
This is one of the goals of the
RI/FS: to determine population at
risx.
3-5. Definitions of trie
variables that will be measured.
See Sec-ion 3.0, Data Quality
Requirements.
8-7. The acceptable levels of
precision and accuracy for the
measurements to be made.
See Section 4.0, Analytical
Approacn Options and Section 3.0,
Data Quality Requirements. '
8-3. 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.
AW3-13
A-3
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DRAFT - Do not quote OP cite.
APPENDIX 8
POTENTIALLY APPLICABLE OR
RELEVANT AND APPROPRIATE REQUIREMENTS
excerpt from National Contingency Plan
final rule, October 10, 1985.
AW3-21/2
-------
POTENTIALLY APPLICABLE Q« RELSVANT AND APPSOP3IATS REQUIREMENTS
1. EPA's Office of Solid Waste administers, inter alia, the
Resource Conservation and Recovery Act of 1976, as amended
(Pub. L. 94-530, 90 Stat 95, 42 U.S.C. 6901 et se£.)
Potentially applicable or relevant requirements pursuant to
that Act are:
a. Open Dump Criteria - Pursuant to RCRA Subtitle D
criteria for classification of solid waste disposal
facilities (40 CFR Part 257).
Note: Only relevant to nonhazardous wastes.
b. In most situations Superfund wastes will be handled
in accordance with RCRA Subtitle C requirements
governing standards for owners and operators of
hazardous waste treatment, storage, and disposal
facilities: 40 CFR Past 264, far permitted
facilities, and 40 CFR Part 265, for interim status
facilities.
• Ground Water Protection (40 C?R 264.90-254.109).
a Ground-Water Monitoring (40 CFR 265.90-265.94).
• Closure and Post Closure (40 CFR 264.110-254.120,
265.110-265.112).
• Containers (40 CFR 264.170-264.173, 265.170-253.177)
• Tanks (40 CFR 264.190-254.200, 265.190-255.199).
0 Surface Impoundments (40 CFR 264.220-254.249,
265.220-265.230).
• Waste Piles (40 CFR 264.250-264.269, 265.250-255.253
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• Land Treatment (40 CFR 264.270-2S4.299/ 265.270-
265.232).
. • Landfills (40 CFR 264.300-264.339, 265.300-263.315)
* Incinerators (40 CFR 254.340-264.999, 265.340-
265.369).
• Dioxin-containing Wastes, (50 FR 1973). Includes
the the final rule for the listing of dioxin
containing waste.
2. iPA'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. 93-523, 38 Stat -1660, 42 O.S.C. 300f et sec. )
• Maximum Contaminant Levels (for all sources of
drinking water exposure). (40 CFH 141.11-141.15)
9 Underground Injection Control Regulations. (40
CFR Parts 144, 145, 146, and 147)
b. Clean Water Act as amended (Pub. L. 92-5CG, 35 Scat
815,.33 CJ.S.C. 1251 et. sac. )
* Requirements established pursuant tc sections
301, 302, 303 (including State water quality
standards), 306, 307, (including Federal pretreat-
ment requirements for discharge into a publicly
owned treatment works), and 403 of the Clean
Water Act. (40 CFR Parts 131, 400-469)
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-3-
c. Marine Protection, Research, and Sanctuaries Act (33
O.S.C. 1401).
• Incineration at sea requirements. (40 CFR Part
220-225, 227, 228. See also 40 CFR 125.120-125.124)
EPA's Office of Pesticides and Toxic Substances
Toxic Substances Control Act (15 U.S.C. 2601).
9 PC3 Requirements Generally: 40 CFR Part 761;
Manufacturing Processing, Distribution in Commerce,
and Use of PC3s and PC3 Items (40 CFR 761.20-761.30);
Markings of PC3s and PC3 Items (40 CFR 761.40-761.45);
Storage and Disposal (40 CFR 761.60-761.79). Records
and Reports (40 CFR 761.130-761.135). See also 40 CFR
' 129.105, 750.
9 Disposal of Waste Material Ccr.taining TCDD. (40
CFR Part 775i130-775.197}.
EPA's Office of External Affairs
9 Section 404(b)(l) Guidelines for Specification of
Disposal Sites for Dredged or Fill Material
(40 CFR Part 230).
9 Procedures for denial or Restriction of Disposal
Sites for Dredged Material (S404(c) Procedures, 40
CFR Part 231).
E?A's Office of Air and Radiation administers several'
potentially applicable or relevant and appropriate statutes
and regulations issued thereunder:
a. The Uranium Mill Tailings Radiation Control Act of
'1973 '(42 U.S.C. 2022) .
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-4-
• Uranium mill -ailing rules - Health and
Environmental ?rotection Standards for Uranium
and Thorium Mill Tailings, (40 CFR Part 192).
b. Clean Air Act (42 U.S.C. 7401).
• National Ambiant Air Quality Standards for
total suspended particulates (40 CJR Part 50.6-
50.7)
• National Ambient Air Quality Standards for ozone
(40 CFR 5 ) .
• Standards for Protection Against Radiation - high
and low level radioative waste rule, (10 CFR Part
20). See also 10 CFR Parts 10, 40, 60, 61, 72,
960, 961.
* National Emission Standard for Hazardous Air
Pollutants for Asbestos, (40 CFR 61.140-51.156).
See also 40 CFR 427.110-427.116, 763.
• National Emission Standard for Hazardous Air
Pollutants for Radicnuclides (4.0 CFR Par- 61, 10
CFR 20.101-20.108) .
6. Other Federal Requirements
a. CSHA 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:
9 Occupational Safety and Health Standards (General
Industry Standards) (29 CFR PArt 1910).
. • The Safety and Health Standards for Federal
• -~ - — . . - _^f
-Service Contracts .(29 CFR Part 1925).
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-5-
• The Shipyard and Longshore Standards (29 CFR
Parts 1915, 19.13) .
• Recordkeeping, reporting, and related regulations
(29 CFR Part 1904) .
b. Historic Sites, Buildings, and Antiquities Act (IS
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 Archaelogical Resources: Uniform
Regulations — Department of^Defense (32 CFR Part
229, 229.4), Department of the Interior (43 CFR Part
7, 7.4).
D.O.T. Rules for the Transportation of Hazardous
*
'Materials, 49 CFR Parts 107, 171.1-171.500-
Regulation of activities in or affecting waters o. tr.e
United States pursuant to 33 CFR Parts 320-329.
The fallowing requirements ars also triggered cy run
financed actions:
• Endangered Species Act of 1373, 16 U.S.C. 1-3..
(Generally, 50 CFR Parts 31, 225, 402).
Wild and Scenic Rivers Act, 15 U.S.C. 1271-
Compliance with SE?A required pursuant to 36 C.-R
Part 297.
• Fish and Wildlife Coordination Act, 16 U.S.C. 6ol
note .
Fisn and wildlife Improvement Act of 1978, and
F:sh and Wildlife "Act of. 1955,. 15 U.S.C. 742a note.
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-6-
Fish and Wildlife Conservation Act of 1930, 15
O.S.C. 2901. (Generally, 50 CFR Part 83).
Coastal Zone Management Act of 1972, 16 U.S.C.
1451. (Generally, 15 CFR Part 930 and IS CFR 923.45
for Air and Water Pollution Control Requirements).
OTHER FEDERAL CRITERIA, ADVISORIES, GUIDANCES ,.
AND STATS STANDARDS TO 3£ CONSIDERED
Federal Criteria, Advisories and Pr
• Health Effects Assessments (HEAs)
• Recommended Maximum Concentration Limits (RMCLs)
• Federal Water Quality Criteria (1976, 1930, 1984).
Note: Federal Water Quality Criteria are not legally
enforceable. State water quality standards are legally
enforceable, developed using appropriate aspects of
Federal Water Quality Criteria. In many cases, Stats
water quality -Standards do not include specific numerical
limitations on a large number of priority pollutants.
When neither State standards nor MCLs exist for a
given pollutant, Federal Water Quality Criteria are
pertinent and therefore are to be considered.
• Pesticide registrations.
* Pesticide and feed 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.
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-7-
• Public health basis for the decision to list pollutants
as hazardous under section 112 of the Clean Air Act.
8 EPA-'s Ground-water Protection Strategy.
0 New Source Performance Standards for Storage Vessels
.for Petroleum Liquids.
9 TSCA health data.
• Pesticide registration data.
• TSCA chemical advisories (2 or 3 issued to date).
0 Advisories issued -, FWS and NWFS under the- Fish and
Wildlife Coordination Act.
* Executive Orders related to Floodplains (11983) and
Wetlands (11990) as implemented by EPA's August 6, 1985,
Policy on Floodplains and Wetlands Assessments for
*
CERC1A Actions.
0 TSCA Compliance Program Policy.
• OSHA health and safety standards that may be used to
protect public health (non-workplace).
3 Health Advisories, EPA Office of Water
2. Stata Standards
* State Requirements on Disposal and Transport cf
Radioactive wastes.
0 State Approval of Water Supply System Additions or
Developments.
0 .State Ground Water Withdrawal Approvals.
• Requirements of authorized (Subtitle C of RCRA) State
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-3-
hazardous waste programs.
• Stata Implementation Plans and Delegated Programs
Under Clean Air Act.
* All other State requirements, not delegated through
EPA authority.
• Approved State NPDES programs under tha. Clean Water Act
• Approved State UIC programs under tha Safe Drinking
Water Act.
Note: Many other State and local requirements could
ba pertinent. Forthcoming guidance will include a
more comprehensive list.
3. US£?ARC3A Guidance Documents
9 Draft Alternate Concentration Limits (ACL) Guidance
A. £?A's SCSA Design Guidelines
1. Surface Impoundments, Liners Systems, Final Cover and
Freecoard Control.
2. Waste Pile Design - Liner Systems.
3. Land Treatment Units.
4. Landfill Design - Liner Systems and Final Cover.
3. Permitting Guidance Manuals
1. Parait Applicant's Guidance Manual for Hazardous Waste
Land Treatment, Storage, Disposal Facilities. .
2. Permit Writer's Guidance Manual for Hazardous Waste
Land Treatment, Storage, and Disposal Facilities.
3. Permit Writer's Guidance Manual for Subcart F.
4. Permit Applicants Guidance Manual for the General
Facilitv '5*3"d2r--s .
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-9-
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 RCHA Permit Applications for
Existing Storage Facilities.
10. Guidance Manual on closure and post-closure Interim
Status Standards.
C. Technical Resource Documents (TSDs)
1) Evaluating Cover Systems for Solid and Hazardous Waste.
2) Hydrologic Simulation of Solid Waste Disposal Sites.
3) • Landfill and Surface Impoundment Performance Evaluation
4) Lining of Water Impoundment and Disposal Facilities.
5) Management of Hazardous Waste Leachate.
6) Guide to the Disposal of Chemically Stabilized and
Solidified Waste.
7) Closure of Hazardous Waste Surface Impoundments.
3) 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.
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-10-
3) Hydrologic Evaluation of Landfill Performance (HELP)
Model Hydrologic Simulation on Solid Waste Disposal
Sites.
.4.) Procedures for Modeling Plow Through Clay Liners to
Determine Required Liner Thickness
5) Test Methods for Evaluating Solid Wastes
6} A Method for Determining the Compatibility of Hazardous
Wastes
7} Guidance Manual on Hazardous Waste Compatibility
4. USaPA Office of Water Guidance Documents
A. Pretreatment Guidance Documents
1) 304(g) Guidance Document Revised Pretreatment Guidelines
(3) Volumes)
3. Water Quality Guidance Documents
1) Ecological Evaluation of Proposed Discharge of Dredged
Material into Ocean Waters (1377)
2) Technical Support Manual: Waterscdy Surveys and
Assessmer.cs for Conducting Use Attainability Analyses
(1933)
3) Water-Related Environmental Fate of 129 Priority
Pollutants (1379)
4) Water Quality Standards Handbook (1333)
5) Technical Support Document for Water Quality-based
Toxics Control.
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-11-
C. NPOES Guidance Documents
1) NPDES Best Management Practices Guidance Manual (June
1981)
2) Case studies on toxicity reduction evaluation (May 1983)
D. Ground Water/UIC Guidance Document
1) Designation of a USDW
2) Elements of Aquifer Identification
3) Interim guidance for public participation
4) Definition of major facilities
5) Corrective action requirements
6) Requirements applicable to wells injecting into,
through or above an aquifer which has been exempted
pursuant to §146.104(b)(4) .
7) Guidance for UIC imp1ernencation on Indian lands..
5. USEPA Manuals from the Office of Research and Development
1) EW 346 methods - laboratory analytic methods
2) Lab protocols developed pursuant to Clean Water Act
S304(h).
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DRAFT --Do. x: quote OP cite
APPENDIX C
TOXICITY VALUES FOR USE AT SUPERFUND SHIS
AW3-21/3
-------
ATTACHMENT I
TOXIC1TY VALUES FOR US£ AT SUPEAFUND SITES
attached table contains toxicity values developed by-E?A's
1*Criteria and Assessaent Office for substances (or groups of ~
commonly found ac Superfund sices. Toxicity values-are given for
oral and inhalation exposure. A series of Health Effects Assessments
) chat docuaent these values is available through the Superfund Cocket
JUS"Cm 382-3046).
r potantially carcinogenic chamical*, both the estimated potency
- r and the concentration that yields a 10** lifetia* cancer risk are
'A in "he table. Th« potency factor is defined as ehe> upper 95 percent
*?dence~liffli= of the aaount of risk per unit of exposure. Multiplication
c w ootencv factor, expressed in inverse intake units [(ag/kg-day)" ], by
°f !-iLted' long-term intake in corresponding units (ag/kg-day) will yield
Ir-hound carcinogenic risk estiaate. For example, carcinogenic risk of
Sng-Hn «S«u« « benzene via drinking water ac 0.0078 ag/1 would b.
calculated as follows:
0.0073 (ag/D * [2 (I/day) » 70 (kg)] > 0.000222 (ag/kg-day);
O.GC0223 (og/kg-day) x 0.045 (ag/kg-day)~L « 0.00001
-v,.« t- -^is exasrale the predicted carcinogenic risk is 10 J.
inws t i-" *™
-ve carcinogenic potency factor for aost cheaicals in the attached table
.-, "q *" coefficient derived by fitting aniaai study data to the
7- --2ed -"'-^stage sodel. -However, huaan tp-.deaiologic data were used to
develop poeancy'fwtars for arsenic, benzene, cacaiM, cirsaiua, and
nickel.l^
Reworking the above equation by substituting 10~' for the carcinogenic
. ° ^;..7-.-2 by the sotency value vislds an intake lave! associatac wits
risK ana --•——* A
. ,,-i- risk of 10* . This intake level can then be converted to a
a^3r~r-j--"="r.~by using the standard exposure assumptions (e.g., 2 l.'day
^"8tll water!' for air or drinking watar, as appropriate. Acbient
(^^ • i fc^**^ ™ ^ *
-aciotis corresponding to an upper-bound risk of 10 have been
"ad'anc are Listed along with potancy values in' the attached cable.
--e dosa-resccr.se relationship fcr carcinogens is assuaec to be linear
lev exposure levels, the potency factor renains constant and concentrations
. „ ^ .---r.king water that yield carcinogenic risks of 10 or 10 can
1-iaatad'sisoly ^y multiplying the cabulacad concentration by. 10 or
.
^ al
dividng ic byia, respectively
r acditicr.al discussion of ErA's cancer risk'assessment sechods saa
Ande-sorec i"--. 1534, Quantitative approaches in use to assass cancer risk,
:- Risk"Analyse 2: 2"-195.
-------
iiUUtU: .Inly |M,
A 1C
-------
nv vAMir.-J HM H:;K AT surmnnw HMLUIAI. sm:s a/
( Aj!i} Cafcliioiienii: Cnlic. 4! 10-6
('liciilCdl Intdk* Unlit CIMIC. Iliilm |i/ I'oluncy Cdiicui Hiuk t,/
1 , i-> i ii -l>i fli 1 ul lie Iliy lone*
• 1,1 i,n ic NU NU
' ' Ulll'llll Illl 1C NU
1 , t-t I dits-Ui cli lul u«l hy IL-IIU*
! Clil tin 1C Nil NU
; • ^ulit In onto NU
»:i hy II.L-mtiiB
I'luonlL- ll.ll1*> 1.4 NA
; Utiliclif nun: O.V) 14
i* 1 yt:ti 1 el litti u*
I'liiimic ' NU Nil
' ttiiliclii onic NU
llUVdfll Illl IlI'VII/UIIO
t liluiuc NU 1.1 /.Mill J
• ' Sulit.-liiunic NU
llu «* fli 1 nli.liii lddl«ll«
(l.nmic mi ll. 0 'III 4.Mlir4
UllllL-lll tlilliC Nil
lltiiijflil niiicyc|u|ienl tftlliina
Cluonic Nil ' . HA
Uiiluliiunic. 0.070 4.4
riii mi ic . ... NU "A
iilll'flll OlklC i , HU '
I.OJ.I ll/ , , .. .
t hi ,,i,i.: . li.'llUM II. II Ml HA
»ulil Illlllllf Illl
I. Hill. lilt! ''!•'.
i liiiHii'f" -•>••• . NU I.I !l« J»l<»~*
":.,llr, IllOlllt- ' Illl
.'_.(; ' ,
' < i.i-tn.^ft ' 11.^1 I.I " NA
Ai-i:uiil aliU- Inldkt; (AIC ui A I3| Cdi . i no.junl c Cone. *l 10-4
Inldku "nils Cone. Unll* c/ l-niency Cancel Disk <:/
-
NU NU
NU
Nil NU
Nil
Nil NA
NU
Nil NO
NU
NU NU
Nil
NU NU
»«»
4.t>«iir* i.uiir* NA
O.O029 0.010
U.UOWi 0.0)0 NA
Nil
4. ii lo~4 u.onis HA •
NU
.,._
NU x- Nil
HU
1. nmir4 I.IIKIO- * NA
-t . ... ...- 1
-------
•lltXIl (TV VAMIK'i KlH USC AT MirillUUNII lllmiilAI. :i ITtS
(ton I imiu'll
li* IV
July IB. 1*114
\ ft l
' 1
('Ill-Mi CJl '' '
l'ol yiiui' 1 r al dti*ii4l|i:
liyill in al liollb ( I'Allu 1
1 lit 4»lll c
?*ultfli i oni c
I'yn-iic*
• In on l>: • • • •
Ulllit. Ill Oil 1C
Si- Icn linn
« In on 1C • '
Stllit'lll Illll C
l.'liinnlc "
2»ul»t-*lii on i c
:in 1 In t if Clll UIIIV
Te 1 1 A rli 1 01 ou 1 liy I tiilc
tin unlc
Uiiliijil on 1C
(In onur
!..il.. In .„. 1.:
1 Iti (iti i r
Stil't lit tMii i: .
,MM,-r,,,H
Ari:v|il ali|t> IpiJ^kf |M<.' nf Aly) Cjicliiixiunl c Cone. |i| ,ili|>- li|ldke (AIC or A I.1J. Cjiclno.jt.-nlo Cone. »l 10-t
Intake Units Cone. Unlla c/ foluiicy C«nc«c Mlak c/
(•'l/k'j-ilay | (••(/•'I (»<|/ln| -iljy (-1 (a9/o 1
Hit 4.1 i.7XIO-7
Nil
No NII
Nit
ii. iium u.uim NA
Nil
Nil NA
III!
Nit NA
Nil
Nit Nil
Ml
Nil ND
lilt
Nil NII
Nil
1 .% 4.2 NA
1.4 4.2
t. 1 U NA
II *7
-------
**">
»tMP)UU glTg«
A« i:ll4|>lll ll«lltt
A« • u I K I It
Ai I y I iMtl t I lie
AI Jl ill
AII I na>my
A!.c.l it
bal litm*
bc.il I Jliic
Heiylliuw
l.'d.lttiiiia*
l.'«ibun laiiiiuiiil*
C»ibiMi in Imtlilui ida*
Illtlui Jam:'
I l.l.il iitalod be ill run*
lkl««i:li lui
fenlach luiobaniina
Ti i tltlorubeimma
Hi*nui:li lui i4itfincita
Clilui iual.
ii|4ienu
i»|4iu
tt|>lle
ti|4tei
it|4iei
lui i
MlrAIlt 01 lEiCViMT »IQHI»EHEMT8 1 OTliM OlltlU. ADV1SOTUB. AND CUIDAMCI
PI IW INK INC 1
HAUH ACT 1 UJiAtt Alt ACT
Hll.a
(••/I)
0.01
1.0
0.01
•
MAAQ3
( ua/ai^)
40.000 (|-bour)4/
10,000 (g-huur)*^
CUAH UATII ACT
Ualar Quality Crilaria
for H.M.aa Health --
Vialt and IV ink lo| Walar
20 ug/l (Organolapllc)-'
120 ug/l
0 O« ng/l)?7
0 (0.0)4 ug/l)
lg/l
0 (0.6 ug/l)
0 (O.I) ug/l)
0 (|.» ug/l)
Inaulf iclaal 4ala
Inauf ficiaai 4ata
laauf iiclant 4ala
litaut lici*nl data
Inaulliclaat 4ala
O.I ug/l (OrgMolaplU)
O.I ug/l (Organolaft Ic)
0.04 ug/| (Qrga«olapllc)
0. i ug/l (Oiga.olaalic)
0.1 ug/l (teganolaalic)
0.1 ug/l (Oigaaolaaiic)
1.0 ug/l (Orgaaiolakllc)
419 <(1 ug/l)
CUAM UATU ACt
Ualar Quality Crltaria
lor Human Haalth —
Ad|ualad fur Drinking
Ualai Only a/
20 ug/l (OrganoUptlc)
140 ug/l
0 (61 ag/l)
0 (1.2 ag/l)
U6 ug/l
(1) ag/l)
(10.000 libar./l)
0 (0.4) ug/l)
0 (0.11 ag/l)
0 ().» ag/l)
10 ug/l
0 (0.41 ug/l)
0 (11 o./l)
0 (11 ng/l)
100 ug/l
110 ug/l
laaufllciant data
48* ug/l
0 (0.«4 ug/l)
19 "MJ/I
0 (0.4 ug/l)
0 (O.I) ug/l)
0 (1.4 ug/l)
laaufficlaol data
Inauf ticianc data .
laiiulliclanl 4ala
Inauf llciani data
Inauf ticlaat data
O.I ug/l (Ocganolaplic)
0. 1 ug/l (Organolapl ic)
0.04 ug/l (Organolaptic)
0.1 ug/l (Organolapi ic)
0.1 ug/| (Oiganolaplic)
0. ) ug/l (Oigaiiolapilc)
1.0 ug/l (Oigauulaplic)
IbOO ug/l
0 (|.» ug/l)
.»nn .... II «.» .„. |,tl
'
SAT! D« INX IMC UATCt ACT
Maalth AddiaorU*
(•g/l)
1-day | 10-day |Long*r-T«rai
0.1
0.0611
Inauf
1
0.11
0.01
0.0611
iciant 4
0.01
0.0011
la
1.0
k
-------
KITA ArtHltMT
AMD OI|Tlt«U fO« tllHtRHIMO RKHPUAI. SITES
I AmiCAllI OR RKUVANT REQUIREMENTS
Ik-Aftf IMINKIHC |
WATKR ACT j a.lAH AIR ACT
1MI1.
i.'titHiai.
1 Mi.- iliy 1 4 -i-hlui i>|Jicnul
1 tviliyl 6 ill 1 in ujiliciiul
l,i* In i hi in >i|.lii;iiu«y*i el u acij
1 /.<• U)
J , roj>i oiiiu
.. i J it. 4. VU)
II, l.n.i.lk y| tllicll
till I l-li lui Kuulliyl I ciltcr
1. 1 » ( V i: loruulliyl ) «u|>iii|>yl ) elliar
Mil. ii i.l. •!«.
(•In uuiiiiw I. i 6*
t: > )'
l.'i.|.|«r
Cyanide
nor* .
Ill ill 1 ui obcili cues (4 II inu.«fa)
|i| I'll luf ill* vii 1 1 .It iiue
III t li 1 ui ne 1 li y 1 ou« M
1 ,l-f)iililui <>iMliyl«ii«*
1 , 2- l>ly Ituc
III * ll 1 UI IHIll.' 1 ll 411 If *
? , 4 -III <~li 1 ur u|iliiiiiul
III 1 ll III* |1|>II>|. (lie 11/11 1 ill lui 0|>l 0|xlllc«
III i; li 1 ui u |u ii ji 411 e 11
ii ii
In vl Ji in
?.<> Itiiiulliyliiliciiul
2,4 -Oiii i u tic)
0 (0.11 ug/|)
0 (41 ng/l)
;M ug/l
1 ug/l
1.4 .g/l
1 • 1 '
42 ug/|
CLCAH WATM ACT
Weler Quality Criteria
for NUMO Heelth —
AVIjuated fur Or ink ing
Water Only a/
1000 ug/l (Organoleptic)
20 ug/l (Organoleptic)
0 (0.0019 ng/l)
0 (10 ng/l)
M./ ug/l
0 (O.I* ug/l)
O.I ug/l (Organoleelic)
)0 ug/l
129 .g/l
1 iag/1 (Urganalept ic )
200 >g/l
0 (-M.2 ng/l)
4)0 ug/l
0 (20. / ng/l)
0 (11 og/l)
Inaufficient date
ace Heloaetheaee
1.09 .g/l
••sufficient date
•' ug/l
0 (I.I ng/l)
400 ug/l (Orgenaleptic)
o (o.n ug/i)
0 (4* ng/l)
11* ug/l
1 ug/l
2.4 .g/l
IM ug/l
,
SAT! MIHK INC WATER. ACT
Heellh Ad*ieoriee
(.g/l)
1-day | 10-day (Lonier-Terei
t
1.0
4.0
2. /
1)
).6R
19.0
0.4 (c
0. 21 (l
1 .1
o. ua
0.0 JO/ 0.0 JO
o.o;
ieueier)
e»e ieoner)
0.1)
'
».i
1 '
1 ' - -- -
-------
!!?* *?!• !t?J.*!•ft1 ">mEHTa AMU <*imu fo« auregyumt REMEDIAL aiitg
: ii11.-UIBid411«<
He (ll •! ll I 01
' lie •>!« Ii I ui iii y t I i4i«: «4iii:ll
i.iii.unc mi g
iivi*-u:il
(1JIIWI4 IICII
.l.:lln-l»:il
.:(.« i tun IICII
lo.liiuol -It.'H
llf >4i li I ul oc y t l.i(ii:ii I ••! i ciia •
lly Ji UC4I (unit (iiun-.sllisns )
Kci iitl Oil |2
Meicur y •
^h: Illunyi'll I Of
H.:lliyl llliyl lUilune*
Nickel*
Nili«l« (as N>
N»iiobeiiic,i«
Ni li ugen dioiiJe
Hi ifi>|4itiiiols
2,4-Uiiiiiio-u-cr«sul
l>inilfu|4iciiul
nmiiMiiii ii|iiicii4>l
Tl I III I ( U |>ll tillU I
Hi liossnincii
it • Ni li u»u JIMUI iliy I a*ins
• ii Ni ll nu.iJl .:ll>yl ••inv
li Ni 11 imii.ll -ii but y I ••in*
ii NI I » I*«IH|I |ili»:iiy I sstinc
n Ni 11 i>Hii|>yi • ul iUia«
I'jl 1 l
hjl li!l
l*»'ii | ji li 1 »i| ii|*llrlkiit *
•.'«
IICII)'
J i CIIO •
III SIIS )
ul
• in*
•ins
(••in*
i.iitc
IIB
Arri.ii.AiiK OR HKUVAHT RCIJIIREMEHTS
UAVK IWINKIHt;
UAT«« ACT
NCI.i
(•|/l)
0.004
0.0)
0.001
O.I
10.0
CIJAH AIR ACT
MAAqS
(ug/.1)
160 (l-hour)^!-*
1 .i (90-dsy)
100 (l-yesr)*/
260 ( 24 IHMI )^
!•> { 24 lim-i)]/
OTHER ttlTMIA. ADVIEOHIRS. AMD Ol IDAHO!
CLEAN UATU ACT
Ualsr Quality Criteria
lor Huaaa Health —
rich and Di inking Uater
0 (0.19 ug/l)
0 (O.Ji .,g/|)
0 (0.4) ug/l)
0 (9.1 ng/l)
0 (16.1 ng/l)
0 (12.) ng/l)
Inaullicient data
Inaullicient dale
0 ().] ng/l)
104 ug/l
).l .g/l
M ug/l
144 og/l
Ineuflicent dale
11.4 ug/l
19.1 .g/l
11.4 ug/l
10 ug/l
Insufficient dele.
Insufficient dele.
0 (1.4 ng/l)
0 (0.1 ng/l)
0 (6.4 ng/l)
0 (4.* ug/l)
0 (14 «»/»}
1.01 .g/l
J.i .|/l
UJAN UAT1R ACT
Ualer Quality Criteria
lor Human Haelth --
Adjusted for Or ink ing
Uster Only e/
0 (0.19 ug/l)
0 (II ng/l)
0 (0.4) ug/l)
0 (1) ng/l)
0 (21.2 ng/l)
0 (11.4 ag/l)
Insufficient data
Inauf licient dale
0 (1.4 ng/l)
206 ug/l
).l .g/l
iO ug/l
10 ug/l
Insufficient date
l).4 ug/l
19. • .g/l
11. • ug/l
/O ug/l
Insufficient dele
Insufficient dale
0 (1.4 ng/l)
0 (O.f ng/l)
0 (4.4 ng/l)
0 ( 1.0 ug/l)
0 (16 ng/l)
1.01 .g/|
I.* .g/l
1AM ON IMC IMC UATU ACT
Health Advisories
(.g/l)
l-dsy I 10-day (Lone^r-Terei
" "' (
11
l.i
•
4.0
-f
0.2)
0.02)
0. 150
-------
"* *«""tNT
AM" oi im i A ruH guygimmt JBHIJDUI. SITES
••
\
1 .
ClltHIUI.
l'lilli«l«ln • •Idi*
|l|u.flltyl|>hlll«lal«
Hi «lliyl|>lilli«llilli4l*le
Hi • 2 -» lliyllioy 1 |i4i thai alt
Cut y fli 1 ur lual tf d bi |4i«iiy 1 a if^t*)*
I'lilyniii l««r ••"••lie liyi|ro<:arl>ona
liilncni!*
In >ii|i|.eil«
1 1 i. 'Ill tn oclliyl tuc*
Tl ilt«l<«u«lli4iic« (lulal)*/
Vinyl tli lull Jit
My 1 filed
il.it «
A^PI latif on i
• AW Ml INK INC
WATVH ACT
i FCi/|
IV i><:i/l
10.000 pCi/l
1 J.Ci/1
J/
0.01
0.0)
o.oov
0. 1
lEieviNT RiquimMDiTa
00! AM All ACT
MAAQS
(ug/.1)
'
I6» ( 24-hour)^/
BO (I'yvtr)*'
OTWI Ql
a BAM WATCI ACT
U«l*r Quality CrilirU
for HiMMin H««llh -~
fiih Mid Prinking U«l«r
111 «|/l
JiO .,/|
U .»/!
li -I/I
0 (0.0)9 •(/!)
0 ( !.• Bg/l)
10 u|/l
to ..,/!
0 (0.000011 Rg/l)
0 (0.« u,/M
1) U|/l
K.I ••/!
o (o.n «(/i>
0 (2.) ug/1)
o (2.0 m/i)
i •!/! (0(|MaUpticl
TIIIA, ADVISOiHS. AMD CU
CUAM UATH ACT
Water Quality Criteria
(or HUMH Naaltb —
Ad|ualad far Di taking
Water Only a/
1)0 .|/l
i)< .|/l
44 .g/l
21 •«/!
0 OI2.4 Of /I)
0 (1.1 at/1)
10 u|/l
SO UB/I
.
0 (O.OOOU 0(/l)
0 (O.M U|/l)
Ijr.g ug/l
1) -I/I
0 (24 ag/l)
0 O.i ug/l)
0 (2.0 ug/l)
i M/' (Orgaaoleftic)
DAM a
t
8ATI MIMKIMC WATKI ACT
Health Adviebriae
(•g/l )
l~day 10-day |lj>ngar-T«rai
0.12)
2. 1
11. i
1.0
12
1
0.012)
o.m
2.1
0.2
1 .2
O.O2
0.14
0.01)
0.42
-------
*a
""^l
DRAFT - Do not quote or cite.
APPENDIX D
PERFORMANCE CRITERIA FOR ORGANICS ANALYSIS
P?J
5K£,
w
tasa
ffij-r
^ft«
lyi AW3-21/4
-------
EXHIBIT C •
Hazardous Substance List (HSL) and
Contract Required Detection Liait« (CML)**
Detection Limits*
1.
2.
3.
4.
5.
6.
7.
3.
9.
10.
11.
12.
13.
14.
15.
16.
« ^
i. / .
13.
19.
20.
21.
22.
23.
24.
25.
Volatile*
Chloromethane
Bromoaethane
Vinyl Chloride
Chloroechane
Methylene Chloride
Acetone
Carbon Disulfide
1 , 1-Dichloroethene
1,1-Dichloroethar.e
trana-i ,2-Dichioroechene
Chlorafora
1 ,2-Dichloroethar.e
2-3utanor.e
1,1, 1-Trichloroe thar.e
Carbon Tetrachloride
Vinyl Aceta^a
Braaodichloroaethaae
1,1,2 ,2-Tetra ch lor se thane
1 ,2-3ichlor3srop«se
trans-l.l—Dichioroproper'.e
Trichloroethene ' •"
Dibroaoch lor one thane
1,1,2-Trichloroethar.e
Benzene
cis-l , 3-D ichlorop cope ne
CAS Huabar
74-87-3
74-83-9
75-01-4
75-00-3
75-09-2
67-64-1
75-15-0
75-35-4
75-35-3
156-60-5
67-66-3.
107-06-2
.78-93-3-
71-55-6
56-23-5
108-05-4
75-27-4
79-34-5
78-37-5
10061-32-6
79-01-9
124-43-1
79-00-5
71-43-2
10061-01-5
Low Water-*
u«/L
10
10
10
10
5
10
5
5
5
5
5
5
10
5
5
10
5
5
«
;
^
5
5
5
5
5
Low Soil/Sediaent3
ug/Xs
10
10
10
10
. 5
10
5
5
5
5
5
5
10
5
5
10
5
5
5
5
5
5
5
5
5
(continued)
C-l
10/34 Rev
-------
26
27
23
29
30,
2-Chloro«chyl Vinyl Ether
Broaofora
2-H«xanon«
4-M«thyl-2-?«ntjnon«
T«craehloro«ch«n«
31. Tolu«n*
32. Chlorob«nz«n«
33. Ethyl B«nzene
34. Styrent
35. Total Xyl«n«a
110-75-8
75-25-2
591-78-6
108-10-1
127-18-4
108-38-3
108-90-7
100-41-4
100-42-5
10
5
10
10
5
5
5
5
5
3
10
5
10
10
5
5
5
5
5
5
.„
C-2
10/84 Rev
-------
Detection Llalts*
36.
37.
38.
39.
40.
41.
42.
43.
44.
45.
46.
47.
43.
49.
50.
51.
52.
53.
54
55.
56.
57.
53.
S?.
60.
61.
62.
63.
Semi-Vol«tlle«
Phenol
bl«(2-Chloro«chyl) ether
2-Chlorophtnol
1 ,3-Olchlorobanzene
1 ,4-Dlchlocobenz«n«
Benzyl Alcohol
1 ,2-01chlorob«nz«n«
2-M«thylph«nol
bii(2-Chlorolaopropyl)
ether •
4-K*thylph«nol
N-Nitro«o-Dipropylaaine
Hexachloroc thane
Nitrobenzene
Isophorone
2-N*itro,phenol
2, 4-0 Inethyl phenol
Benzole Acid
bis(2-Chloroethox7>
ce thane
2 ,4-Dichlorophenol
1 ,2 ,4-Trichlorobenrene
Naphthalene
4-Chloroanlliae •
Hexachloro butadiene
4-Chloro-3— aethylphenol
(para-chioro-ceta-cresol)
2-Methyl naphthalene
Hexachlorocyclopentadlene
2 ,4 ,6-Trichlaraphenol
2 .4 ,5-Trichioraphenol
CAS Number
108-95-2
111-44-4
95-57-8
541-73-1
106-46-7
100-51-6
95-50-1
95-48-7
39638-32-9
106-44-5
621-64-7
67-72-1
98-95-3
78-59-1
88-75-5
105-67-9
65-35-0
111-91-1
120-33-2
120-82-1
91-20-7-
106-47-8
87-63-3 .
59-50-7
91-57-6
77-47-4
88-06-2
95-95-4
Low Water"
ua/L
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
10
50
10
10
10
10
10
10
10
10
10
10
50
Low Sol i/Sedizer. -f
ug/Ka
330
330
330
330 -
330
330
330
330
330
330
330
330
330
330
330
330
1600
330
330
330
330
330
330
330
330
330
330 -
IsCO
:- 3
4
i-1
C-3
(cone i nue-i)
-7/85 Rev
-------
Detection !.«-t ....'
64. 2-Chloron«phth*l«n«
65. 2-Nlero«a.llln«
66. Dlacehyl Phehalje*
67. Ac«tuphchyl«a«
63. 3-Nitro«ailine
69. Ac«n*phth«n*
70. 2,4-Oiaierophcnol
71. 4-JUcroph«nol
72. Dib«nzofur*n
73. 2,4-Dinitrotolu«n«
74. 2,6-Dlnicrocolu«n«
73. Dlechylphch«lJC«
76. 4-Chlorophenyl Pheayl ,
ccher
77. Fluorene
78. 4-.»fi:ro«niline
79. 4,6-Dlni£ro-2-3ethylpheftol
'80. N-nitrosodiphetiyljaine
81. 4-Broaoph«nyl Phenyl ether
82. Rcxachlorobenzene
33. Pentachiorophencl
84. Phenanchreae
85. Anthracene
86. Di-n-bucylph:halace
87. Fluoranchene
88. Pyrene
39. Bucyl i
90. 3,3'-DichL_JC,^;
91. Benzo(a)anthracene
92. v' "
93. Chrysen*
94. Di-n-oc:7l ...t.,.i-ce
95. Benzo(b)fluoranchene
96. Bcnzo(k)fluoranchese
9/. B«nza(a)pyrene
91-58-7
88-74-4
131-11-3
208-96-8
99-09-2
83-32-9
31-28-5
100-02-7
132-64-9
121-14-2
606-20-2
84-66-2
7005-72-3
86-73-7
100-01-6
534-52-1
86-30-6
101-55-3
113-74-1
87-36-5
85-01-3
120-12-/'
84-74-2
206-44-0
129-00-0
35-63-7
91-94-1
56-55-3
117-31-7
213-31-9
117-34-0
205-99-2
207-08-9
50-32-3
10
50
10
10
50
10
30
50
10
10
10
10
10
10
50
50
10
10
10
50
10
10
10
10
10
10
20
10
10
10
10
10
10
330
....1600
330
330
1600
330
1600
1600
330
330
330
330
330
330
1600
1600
330
330.
330
1600
330
330
330
330
330
33C
660
330
33C
330
330
330
330
330
C-4
(coruir.uei)
7/35 Rev
-------
Detection Liaics*
^MMMMM
98.
99.
100.
Seai-Vol
Iadeno(l
DlbenrU
B«nro(j
atila.
,2,3-cd)pyrene
,h)anthracene
,fc,i)perylena
CAS Number
193-39-5
53-70-3
m-2*-2
Low Water^
ug/L
10
10
10
Low Soii/Sedirer.:-
us/Kg
330
330
330 .
e««diua Water Contract Required Detection Liaita (CXOL) for Seal-Volatile
HSL Coapounda are 100 tiaea the individual Low Water CXDL.
dMediua Soil/S«dia«nt Contract R.quirtd Detection Limit* (CML) for Seoi-
Volatile HSL Coapounda art 60 timea the individual Low Soil/S«diaent CSDL,
•-C-5
7/35 Rev
J.
-------
p««ticlde«
101. alph*-5HC
102. b«ta-BHC
103. d«lta-3UC* .
104. faso&a-SHC (Liadan«)
105. Heptachlor
104. Aldria
107* Heptachlor Epoxld*
108. Zndosulfan I
109. Oieldrifl
110. 4,4'-OOE
111. Endrln
112. Eadoaulfao II
113. 4, 4 '-ODD
114. Endosulfin Sulfjce
115. 4,4'-DDT
116. Endrin Ketone
117. Methoxychlor
113. Chlordane
119. Toxaphene
120. ASOCLOR-1016
121. ASOCLOP.-1221
122. XROCLOR-1232
123. ASOCLOS-1242
124. ASOCLOR-1243
125. ASOCLOR-1254
126. AROCLOR-1260
CAS Vuaber
319-84-6
319-85-7
319-86-8
53-89-9
76-44-3-
309-00-2
1024-57-3
959-98-3
60-57-1
72-55-9
72-20-3
33213-65-9
72-54-3
1031-07-3
50-29-3
53494-70-5
72-43-5
57-74-9
8001-35-2
12674-11-2
11104-28-2,
11141-16-5'-
53469-21-9
12672-29-6
11097-69-1
11096-32-5
ug/L
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.05
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.10
0.5
0.5
1.0
0.5
0.5
0.5
0.5
0.5
1 .0
1.0
Detection Uait««
8.0
8.0
8.0
8.0
8.0
8.0
8.0
8.0
16.0
16.0
16.0
16.0
16.0
'16.0
16.0
16.0
80. 0
80.0
160.0
80
30
.0
.0
80.0
80.0
80.0
160.0
160.0
Water Concracf~aeqairtd Detection Li=i:s (CX2L) for Pesticide HSL
Coapounds art 100 tia«s tne individual Low Water CXSL.
fMediua Soil/Sed<3e=t Contract Required Detection Halts (CJCL) f=r Pesticide
HSL compounds ar« 15 ciaes the individual Lew Scii/Sedisent
•Detection Halts listed for loil/sediaent are based on we: weight. The decec-
tlon Halts calculated by Che laboratory for soil/sedirent, calculated on d-y
weight basis, as require* by the contract, will be higher.
•• Specific detection l:3Us are highly =atrix dependent. The detection
Halts listed herein ire ?r3Vided for guidance and aay not alvavs be
achievable.
•C-6
7/85 Rev
-------
FSCM d?
Contract l*s.uind.
Eleaeae
Aiuaiflua
Aaciaony
Araesic
Bariua
BetyiUua
Cadalua
Calciua
Chraaiua
Cabal:
Capper
Irsa
Lead
Sagaeslua
Maagiaese
Mercery
Nickel
Pacaaslua
Selenlua
Silver
Sodlua
Thalilua
Tla
Taaadlus
Ziac
2CO -
60
10
200
5
5
3000
10
50
25
100
3
5000
13
0.2
40
5000
5
10
5000
10
40
50
20
Cjaaide . 10
If Che »aasle ccccaacraclsa excaed* cvo :i2«3 she decasclsa lisi
of che lS3Cr,:=er: or aechad la uae, Che value, say b« reported
chough che iassruaea: or aechod dececsloa Lials 3^7 aoc e^uai c-
csasract required decsctlaa level.
2: These C2TL are che laacruaeac dececslaa liaicj obcilaed la pure
— vacer chac auat b« a«c uatag Che procedure la Ixhibi: Z. The
decsccloa LlsitJ for tasplea aay be csosiderablj higher depeadla
OQ cha la^iple aacrti.
-------
I
CJ
-J
Km,
WATER MATRIH SPIKE/MATRIX SPIKE DUPLICATE RECOVERY
C«alr«al N«.
INACTION
VOA
tMO
SAMPlf NO
tin
SMO
SAMFlf NO
AC ft)
SAMftf NO
COMfUUNO
1^ 1 D>cl><0k>.l>«1h««0
1 »».,.. ,!>—, ,0.
l..l..t«»
••»l<"«
1 J 4 fl,cMo.obT> OC Unxn
•uli<« OC kmin
ACM> wital.
ff$f _
OC
•/ttt
CO
u>
r
-------
w
•OIL MATRIR triKK/MATmX &PHU DUPLICATE
c*
I
CJ
oo
€••• M*.
Lev to«»J.
MAC,,*.
VOA
iMO
tAMf it MO
•'N
Vaunt NO
ACID
SAMTlf MO
MSI
iAMMi H4>
COMNHINO
1 1 Oxtvukx •«(<•«•
l..,i.t.»»«ih.««
C.»>I«
lul.Nnt
• tnito*
1 1 4 lnnV>l
4 Okxa 1 M^hylphioo*
4 Hiiiop^Avl
1 »>!•»«
miflMhHM
AU.M
«>»M..n
Inilon
4 4' 001
CONC STlHf
AOOiOlut«M«l
MUllf
"^
*
MC
CONC
tJSO
MC
ATO
-^rP1
""toM
11
14
11
)l
]1
11
It
4>
M
19
11
41
JS
SO
XI
W
M
11
4}
tt
44
La
HflfflSw-
V9I>1
41 1)1
60IJJ
M IM
M t«l
M I0>
it or
lie*
K 14}
41 lit
ir in
1S*0
n 101
MIDI
II 114
44>ll>
Ji l»
M 111
11 IM
41 IM
11 114
*AilldlSKlO VAlUf S ARl OUISIDf OC IIMIU
•«JIM|« OC I
tint vOAt
«/N_
ACID .
mi.
CcntRonl4U —
._ OU« «l .
_ out *l .
_. au< «l .
_ «K4l »l
HCCOVIMV: VOA*.
*u«u*> OC
hiwll
»MMIt
euioiH OC IMWM
ACID
KST
•*•(.
ml«4.
MM.M
hMM«
IMMI
fORM IM
tVM
111
VJ1
turra III. MS/MS I) R«--»uli» (noil).
-------
TABLE 5.2. MATRIX-SPIKE RECOVERY LIMITS*
Fraction
Matrix Spike Compound
Water*
Soil/Sedlnenc*
VGA
VOA
VOA
VOA
VOA
1, l-Oichloroethene
Trichlorethene
Chlorobenzen*
Toluene
Benzene
61-145
71-120
75-130
76-125
76-127
- 59-172
62-137
60-133
59-139
66-U2
BN
3S
BN
BN
BN
BN
Acid
Acid
Acid
Acid
Acid
Pest.
Pest.
Pest.
Pesc.
Past.
Pest.
Acsnaohthene
2,4-Oini
Pyrene
Phenol
2-Chlorophenol
4-Chloro-3-*e
4-Ntcrophenol
Lindane
Hepcachlor
ALdrln
D la Id r in
EndrIn
4,4'-ODT
lorobenzene 39-98
• 46-113
toluene 24-96
26-127
1-n-Propylamine 41-116
obenzene 36-97
phenol 9-103
. 12-39
nol 27-123
•Methyl phenol 23-97
ol 10-80
56-123
40-131
40-120
52-126
56-121
38-127
38-107
31-137
28-39
35-142
41-126
28-104
17-109
26-90
25-102
26-103
11-114
46-127
35-130
34-132
31-134
42-139
23-134
These Halts are for advisory aurposes only. They ara noc to be used Co
decemlne Lf a sample should be reanalyzed. When sufficianc aulti-Lab dara
are available, 'standard liaits will be calculated.
6.0
This section doe? noc replace or suoercsde specific ar.alycical methods
or QA/QC activities described In previous sections. The incenc of this subsection
Is to provide the Contractor laboratories with a brie: suaaary of on-going QC
activities involved with sample analysis. Specific references are provided to
help Che Contractor laboratories aeec specific Reporti^.z and Del iveranLes required
by.chis 1F3.
£-34
7/35 Rev
-------
--. •«»*--•
4.3 Surrogate »pik« recovery *u«t be evaluated for acceptance by deterain-
ln« whether th« concentration (»ea*ured •• percent recovery) fall* inside the
contract retired recovery li«it» listed in Table 4.2.
4.4 Tr«*taemt of *urrogat* *pika recovery information 1« according to
p«ra«raoh< 4.4.1 through 4.4.2*
4.4.1 M*tho4 Blank Surrogate Spike JUcovery
The laboratory «u«t take th« action* listed b«low if any en« of the follow-
ing condition* rxlct:
of aay- on® »urrot;ate coapound in th« volatile fraction is
outt id* the required »urrogat* *oik« recovery limits.
• Recovery of any ona aurrogatt compound in either the baae/neutral
or acid fraction ia outaide surrogata »oika recovery liaita.
TABLE 4.2. CONTRACT RSQUIXED SUHXOCATE SPIX2 R2C07WT LIMITS
Fraction
VOA
.VOA
VOA
SNA
SNA
SNA
3MA
SNA
3SA
Surrogate Compound
Toluene-'ig
4-3ronof luorobenzene
1 , 2-Dichloro«thane-d^
Nitrobenzene -d 5
2-r luorobiohenvl
o-Terohenyl-di/j
2-Fluorophenol
2 ,4 ,6-Tribroaophenol
• Lov/Mediua
Water
'* 88-110
86-115
76-114
35-114
43-116
33-141
10-94
21-100
10-123
Lov/Mediua
81-117
74-121
70-121
23-120
30-115
18-137
24-113
25-121
19-122
Olbntvlchlorsndate
(24-154)
(20150)
•i
* These liaits are far advisory purposes only. They are not used co decsr^ir.e
if a sample should b< reanalvz»d. When sufficient data becaaes available,
the USSPA aay set per'forstance b*sed contract required windows.
4.4.1.1 Check calculations to assure there are no errors; check in-
ternal standard and *urrc«ace sptkinz solutions for degradation, contaainat ion ,
ecc: also, check instrument performance.
r
4.4.1.2 Recalculate or rein1ect/reour?e the blank or extract if stess
in 4.4.1.1 fail to r»veal che caus» of the non-coaoiiant surrsfate recoveries.
4.4.1.3 Ra-excrac: ^nd reanalyze the blank.
4.4.1.4 If the =ieasur»9 listed tn 4.4.1.1 thru 4.4.1.3 fail
' " E-30 .
to correct
' 7./S5 Rev
-------
ORAFT - Do not quote or cite.
APPENDIX E
LIST OF ACRONYMS
AW3-21/5
-------
DRAFT - Do not quote or cite,
ACRONYMS
CERCLA Comprehensive Environmental Response, Compensation, and Liability
Act
CLP Contract Laboratory Program
OQO Data Quality Objective
EMSL-LV Environmental Monitoring and Support Laboratory - Las Vegas
ESO 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,
Comparaoility
PRP Potentially Responsible Party"
QAMS Quality Assurance Management Staff
QAPP Quality Assurance Project Plan
RAS Routine Analytical Service
REM Remedial
RI Remedial Investigation
RPM Remedial Project Manager - federal official designates by E?A or
another lead agency to coordinate,
monitor, or direct remedial activities
under the NC?
SAS Special Analytical Service
SRM Standard Reference Materials
AW3/29
-------
DRAFT - Do not quota or cite.
APPENDIX F
ACCURACY TESTING DEFINITIONS
-------
ACCURACY DEFINITIONS
Accuracy is usually referred to in terms of bias (8). 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:
3 « X- T
Alternative estimates of bias are percent bias
SB = 100(X-T)/T,
and average percent recovery P
n
P -£PI , and
1=1
Pt = 100 (A1 - BjJ/T,
where A. = the analytical result from the spiked sample and 8- = the
i 1
analytical result from separate analysis of the unsoiked sample. The
relationship between percent bias and percent recovery is:
S3 » P - 100
Tne 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 (N8S) Standard
Reference Materials (SRMs). As with precision data, this information only
refers to analytical accuracy and not .the accuracy of the entire
measurement system. OQOs for a given activity should be established with
this in mind.
AW3-38/1
wtf....iWA..<«Hr-r'q»gE^^
-------
ACCURACY DEFINITIONS
(Continued)
iNon-target
Spiking
Analyte
Internal Standard
Spike
Definition
Spiking of surrogate analytes into the sample. A
surrogate analyte is one which mimics the behavior
of target analytes in tarms 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.
Analyte(s) added to the prepared sample just prior
to instrumental analysis. Used primarily for
quantisation purposes :>;/ means of a calibrated
response factor relative'to target analytes,
determined prior to sample analysis. May also
provide'short term indication of instrument
performance.
-------
ACCURACY DEFINITIONS
Reference Material
Spiking Material
Target Analyte
Spiking
Matrix Spike
Field Matrix Spike
Laboratory Matrix
So ike
Analysis Matrix Spike
Definition
A material known or established concentration tr-2,-
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.
Spiking with the analyte that is of basic interest
in the environmental sample.
.A sample created by
target analyte to a
adding known amounts o1
portion of the sample.
the
4
A sample created by spiking target analytes into
portion of a sample in the field at the point of
sample acquisition. This data quality assess.-ent
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 wnen it is received in the
laboratory. It provides bias information regarding
sample preparation =nd analysis and is the most
common type of matrix spike. This type of matrix
spike dees not necessarily reflect the behavior of
tfle field-col lecte<2 target analyte,. especially if
the target analyte is not stable during snipping.
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 tne various forms of
atomic spectroscopy ana is often referred to as
"standard additions".
AW3-27
------- |