DRAFT - Do not quote or  cite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.

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  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.

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    •   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.
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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?

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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.

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 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.


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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
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       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.
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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. •
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 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.
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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:
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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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                                         DRAFT - Do not quote or  cite.

     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.
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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.

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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.

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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.
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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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                                          DRAFT - Do not quote or cite.
      •  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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                                         DRAFT - Do not quote or cite.
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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                                         DRAFT - Do not quote  or  cite.  -
 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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                                          DRAFT - Oo not quote or cite.
 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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                                         DRAFT - Do not quote or cite.
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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                                         DRAFT  - Oo not quote or cite.
    •   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.
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                                         DRAFT - Do not quote or'cite.'

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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                                         DRAFT - Do not quote or cite.
 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.
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                                         DRAFT  - Do not quote or  cite.
 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

-------
                                          DRAFT  -  Do not quote or cite.
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)


AW3-12                                3-23

-------
                                         DRAFT - Do not quote or cite.,
 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

AW3-12.                                3-22

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                                              DRAFT - Do not quota or cite.
      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

-------
                                         DRAFT - Do not quote or  cite.
 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

-------
                                               DRAFT - Do not quote or cite,
 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.
AW3-5                                 4-9

-------
                                               DRAFT -  Do  not quote or cite.
 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

 AW3-5                                4-3

-------
                                               DRAFT - Oo not quote  or cite
 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

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                     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

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                                              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

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                                              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

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                               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

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                                                 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

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                                               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

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                                               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

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                                              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

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          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

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                                             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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                                              DRAFT - Do not quote  or  cit-e.
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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                                             DRAFT -  Do not  quote OP  cite.
 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

-------
tn
i
ro
                                                   SI A IE IIOUIE 123
                                                                                              o
                                                                                               'IT
          .'I.
          ft.
                                                                                                  '<.
             \
IDLE WILD     V
MUNICIPAL   "
WELL  FIELD
           MUODY CHEEK
            SI A IE I'AIIK
                                                                                                       t EG EN I).
                                                                                                           A -  soi vein rir
                                                                                                           0 -  i n AN sc OHM c n oisrosAi. I-H i
                                                                                                           <; -  SUSCtCII (I Ool) WASIt  AlltA
                                                                                                           
-------
                                             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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                                            DRAFT - Do not quote or cite.
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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                                            DRAFT - Do not quote OP.cite.
       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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                                             DRAFT - Do  not  quota or cite.
                   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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                                            DRAFT - Do not quote OP cite,
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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                                            DRAFT - Do not quote or cite,
          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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                                            DRAFT - Do not quote  OP cite,
         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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                                             DRAFT  -  Do  not  quote OP cite.
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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                                             DRAFT  -  Do  not  quote or cite.


 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

-------
                                                      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
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Camp Dresser & McKee Inc.  1985.  Performance of Remedial Response
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Clay, P. F. and Spittler, T. M. 1982. The Use of Portable Instruments in
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  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

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                                             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

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                                             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

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                                            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

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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

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               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

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               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

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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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                            -2-






         •  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

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                                                              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.

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                                                                                                 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

-------