SR-120
 United State*
 Environmental Protection
 Agency
 Research and Development
Office of Research
and Development
Washington, DC 20460
        August 1992
 EMAP- Estuaries
 1992 Louisianian Province

 Quality Assurance
 Project Plan
Environmental Monitoring
and Assessment Program

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                                                  DRAFT 8/92
ENVIRONMENTAL MONITORING AND ASSESSMENT PROGRAM

        EMAP-ESTUARIES LOUISIANIAN PROVINCE

        1992 QUALITY ASSURANCE PROJECT PLAN


                         by

                   Tom Heitmuller
               Technical Resources, Inc.
                   1 Sabine Island
               Gulf Breeze, Florida 32561

                        and

                 Raymond M. Valente
       Science Applications International Corporation
                   27 Tarzweil Drive"
            Narragansett, Rhode Island 02882
       U.S. ENVIRONMENTAL PROTECTION AGENCY
       OFFICE OF RESEARCH AND DEVELOPMENT
       ENVIRONMENTAL RESEARCH LABORATORY
             GULF BREEZE, FLORIDA 32561

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                                       DISCLAIMER

The research described in this document has not been subject to U.S. Environmental Protection Agency
review and is intended for internal Agency distribution. It should be considered a draft document and
should not be cited, quoted or distributed without official approval.  Mention of trade names does not
constitute endorsement or recommendation for use.

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                                          PREFACE

        This document outlines the integrated quality assurance plan for the Environmental Monitoring and
Assessment Program's Estuarine Monitoring in the Louisianian Province.  The quality assurance plan is
prepared following the guidelines and specifications provided by the Quality Assurance Management Staff
of the U.S. Environmental Protection Agency Office of Research and Development.

        Objectives for five  data  quality indicators (completeness, representativeness, comparability,
precision, and accuracy) are established for the Estuarine Monitoring in the Louisianian Province.  The
primary purpose of the integrated quality assurance plan is to maximize the probability that data collected
over the duration of the project will meet or exceed these objectives, and thus provide scientifically sound
interpretations of the data in support of the project goals. Various procedures are specified in the quality
assurance plan to: (1)  ensure that collection and measurement procedures are standardized among all
participants; (2) monitor performance of the  measurement systems being used in the program to maintain
statistical control and to provide rapid feedback so that corrective measures can be taken before data quality
is compromised; (3) allow for the periodic assessment of the performance of these measurement systems
and  their  components; and, (4) to verify and validate that reported data are sufficiently representative,
unbiased, and precise so as to be suitable for their intended use.  These activities will provide users with
information regarding the degree  of uncertainty associated with the various components of the  EMAP-
Estuaries data base.

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                               TABLE OF CONTENTS


Section                                                                        Pa9e

Disclaimer  	   _'
Preface  	   j|
Table of Contents	   "j
Figure  	   v'
Table	  v»
Acknowledgments  	  v"'


1 INTRODUCTION	    1 of 4
  1.1  OVERVIEW   	    1 of 4
  1.2 QUALITY ASSURANCE PROJECT PLAN SPECIFICATIONS	    2 of 4

2 PROJECT ORGANIZATION	    1 of 3
  2.1  MANAGEMENT STRUCTURE  	    1 of 3

3 PROJECT DESCRIPTION 	    1 of 1
  3.1  PURPOSE	    1 of 1

4 QUALITY ASSURANCE OBJECTIVES  	    1 of 7
  4.1  DATA QUALITY OBJECTIVES  	    1 of 7
  4.2 REPRESENTATIVENESS	    3of7
  4.3 COMPLETENESS  	    4of7
  4.4 COMPARABILITY	    4of7
  4.5 ACCURACY (BIAS), PRECISION,  AND TOTAL ERROR  	    5 of 7

5 QUALITY ASSURANCE/QUALITY CONTROL PROTOCOLS,
   CRITERIA, AND CORRECTIVE ACTION 	   1 of 35

  5.1  CHEMICAL ANALYSIS OF SEDIMENT AND TISSUE SAMPLES	   1 of 35
      5.1.1  General QA/QC Requirements	   4of35
      5.1.2 Initial Calibration	   9of35
      5.1.3 Initial Documentation of Detetection  Limits	   9of35
      5.1.4 Initial Blind Analysis of Representative Sample 	   10 of 35
      5.1.5 Laboratory Participation in Intercomparison Exercises	   10of35
      5.1.6 Routine Analysis of Certified Reference Materials
                    or Laboratory Control Materials	   12 of 35
      5.1.7 Continuing Calibration  Check	   14 of 35
      5.1.8 Laboratory Reagent Blank	   14 of 35
      5.1.9 Internal Standards	   15 of 35
      5.1.10 Injection Internal Standards	   15 of 35
      5.1.11 Matrix Spike and  Matrix Spike Duplicate  	   16 of 35
      5.1.12 Field Duplicates and Field Splits  	   17 of 35
      5.1.13 Analytical Chemistry Data Reporting Requirements	   18 of 35
                                          Hi

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                               Contents (Continued)



Section                                                                       Page


  5.2  OTHER SEDIMENT MEASUREMENTS	   19 of 35
      5.2.1  Total organic carbon	  19 of 35
      5.2.2  Acid volatile sulfide	  20 of 35
      5.2.3  Butyltins	  21 of 35
      5.2.4  Sediment grain size	  22 of 35
      5.2.5  Apparent RPD depth	  23 of 35

  5.3  SEDIMENT TOXICITY TESTING	  23 of 35
      5.3.1  Facilities and Equipment  	  24 of 35
      5.3.2  Initial Demonstration of Capability 	  24 of 35
      5.3.3  Sample Handling and Storage	  25 of 35
      5.3.4  Quality of Test Organisms	  25 of 35
      5.3.5  Test Conditions	  26 of 35
      5.3.6  Test Acceptability 	  27 of 35
      5.3.7  Record Keeping and Reporting  	  27 of 35

  5.4  MACROBENTHIC COMMUNITY ASSESSMENT 	  27 of 35
      5.4.1  Sorting	  28 of 35
      5.4.2  Species Identification and Enumeration 	  29 of 35
      5.4.3  Blomass Measurements	  30 of 35

  5.5  FISH SAMPLING	  31 of 35
      5.5.1  Species ID. Enumeration and Length Measurements	  31 of 35
      5.5.2  Fish Gross Pathology and Histopathology 	  32 of 35

  5.6  WATER COLUMN MEASUREMENTS	  33of35
      5.6.1  Hydrolab Surveyor II	  33 of 35
      5.6.2  Hydrolab Datasonde 3	  34of35

  5.7  NAVIGATION 	  35of35

6 FIELD OPERATIONS AND PREVENTIVE MAINTENANCE	   1 of 3
  6.1  TRAINING AND SAFETY 	   1 of 3
  6.2  FIELD QUALITY CONTROL AND AUDITS	   2of3
  6.3  DATA RECORDING	,	   3of3
  6.4  PREVENTIVE MAINTENANCE  	   3of3

7 LABORATORY OPERATIONS 	   1 of 3
  7.1  DATA RECORDING	   1 of 3
  7.2  LABORATORY PERSONNEL, TRAINING, AND SAFETY	   1 of 3
  7.3  QUALITY CONTROL DOCUMENTATION	   2of3
  7.4  ANALYTICAL PROCEDURES 	   2of3
  7.5  LABORATORY PERFORMANCE AUDITS	   2 of 3
                                         iv

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                              Contents (Continued)



Section                                                                     Page


8 QUALITY ASSURANCE AND QUALITY CONTROL FOR MANAGEMENT
  OF DATA AND INFORMATION	   1 of 7
  8.1  SYSTEM DESCRIPTION	   1 of 7
  8.2 QUALITY ASSURANCE/QUALITY CONTROL  	   1 of 7
      8.2.1  Standardization  	   1 of 7
      8.2.2 Prelabeling of Equipment and Sample Containers  	   2 of 7
      8.2.3 Data Entry and Transfer	   2 of 7
      8.2.4 Automated Data Verification	   3 of 7
      8.2.5 Sample Tracking 	   4 of 7
      8.2.6 Reporting	   4of7
      8.2.7 Redundancy (Backups)  	   4 of 7
      8.2.8 Human Review	   5 of 7
  8.3 DOCUMENTATION AND RELEASE OF DATA	   6 of 7

9 QUALITY ASSURANCE REPORTS TO MANAGEMENT	   1 of 1

10 REFERENCES	   1 of 2

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                                         FIGURES

Figure                                                                               Page

2.1     Management Strucrure for the 1992 EMAP-Estuaries Louisianian
       Province	2of3
                                            vi

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                                            TABLES

Table                                                                                     Page

1.1     Sections in this report that address the 15 subjects required
       in a quality assurance project plan       	4 of 4

2.1     List of key personnel, affliations, and responsibilities for
       EMAP-Estuaries 1992 Louisianian Province monitoring	3 of 3

4.1     Measurement quality objectives for EMAP-Estuaries indicators and
       associated data	5 of 7

4.2     Quality assurance sample types, frequency of use, and types of data
       generated for EMAP-Estuaries Louisianian Province monitoring  (see
       Table 5.3 for chemical analysis QA/QC sample types)	6 of 7

5.1     Chemicals to be measured in sediments by EMAP-Estuaries Louisianian
       Province	i	;	2 of ,35

5.2     Chemicals to be measured in edible fish and shellfish tissue by
       EMAP-Estuaries Louisianian Province	3 of 35

5.3     Key elements for quality control of EMAP-Estuaries chemical analyses
       (see text for detailed explanations)	6 of 35

5^4     Target method detection limits for EMAP-Estuaries analyses	11  of 35

5.5     Codes for denoting QA/QC samples in submitted data packages	18 of 35

5.6     Maximum acceptable differences for instrument field
       calibration checks	34 of 35
                                              vii

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                                  ACKNOWLEDGMENTS

       The following individuals contributed to the development of this document: J. Pollard, K. Peres and
I. Chiang, Lockheed Engineering and Sciences Company, Las Vegas, Nevada; J. Schoenherr, C. Eller, and
D.  Cobb, Science Applications International Corporation, Narragansett,  Rhode Island; D. Bender and L
Johnson, Technology Applications Inc., Cincinnati, Ohio; R. Graves, U.S. Environmental Protection Agency,
Environmental  Monitoring Systems Laboratory, Cincinnati, Ohio;  C.A. Manen,  National Oceanic  and
Atmospheric Administration, Rockville, Maryland; K. Summers, U.S. Environmental Protection Agency, Envi-
ronmental Research Laboratory, Gulf Breeze, Rorida; R. Pruell, U.S. Environmental Protection Agency,
Environmental Research Laboratory, Narragansett, Rhode Island; F. Holland and S. Weisberg, Versar, Inc.,
Columbia, Maryland. The assistance provided by R. Graves in the development  of measurement quality
                            t           .                           -
objectives for analytical chemistry is especially appreciated.
                                             viii

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                                        SECTION 1

                                    INTRODUCTION


1.1     OVERVIEW

        The U.S. Environmental Protection Agency (EPA), in cooperation with other Federal agencies and
state organizations, has designed the Environmental Monitoring and Assessment Program (EMAP) to monitor
indicators of the condition and health of the Nation's ecological resources. Specifically, EMAP is intended
to respond to the growing demand for information characterizing the condition of our environment and the
type and location of changes in our environment.  Simultaneous monitoring of pollutants and environmental
indicators will allow for the identification of the likely causes of adverse changes. When EMAP has been fully
implemented, the program will answer the following critical questions:

        o     What is the  status, extent and geographic distribution of the nation's important ecological
              resources?

        o     What proportion of these resources is declining or improving? Where, and at what rate?

        o     What are the factors that are likely to be contributing to declining condition?

        o     Are control  and  mitigation programs achieving  overall  improvement  in  ecological
              conditions?

        o     Which resources are at greatest risk to  pollution Impacts?

To answer these types of questions, the Near Coastal Component of EMAP-Near Coastal (EMAP-NC) has
set four major objectives:

       o     Provide a quantitative assessment of the regional extent of coastal environmental problems
              by measuring pollution exposure and ecological condition.

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       o      Measure changes in the regional extent of environmental problems for the nation's estuarine
              and coastal ecosystems.

       o      Identify and evaluate associations between the ecological condition of the nation's estuarine
              and coastal ecosystems and pollutant exposure, as well as other factors known to affect
              ecological condition (e.g., climatic conditions, land use patterns).

       o      Assess the effectiveness  of pollution control actions and environmental  policies  on a
              regional scale (i.e., large estuaries like Chesapeake Bay, major coastal regions like the mid-
              Atlantic and Gulf Coasts) and nationally.

       The Near Coastal component of EMAP will monitor the status and trends in environmental quality
of the coastal waters of the United  States. This program will complement and eventually may merge with
the National Oceanic and Atmospheric Administration's (NOAA) existing National Status and Trends Program
for Marine  Environmental Quality  to produce a  single, cooperative, coastal and estuarine monitoring
program. To more efficiently manage Near Coastal activities, the Program has been further divided to study
the Great Lakes, the offshore (shelf) environment, and the Nation's estuaries, bays, tidal rivers, and sounds.
This last component (EMAP-Estuaries or EMAP-E) began in 1990 with the Virginian Province Demonstration
Project.

       The strategy for implementation of the EMAP-E project Is a regional, phased approach which started
with the 1990 Demonstration Project in the Virginian Province. This biogeographical province covers an area
from Cape  Cod, Massachusetts to Cape Henry, Virginia (Holland 1990).  In 1991, monitoring continued in
the Virginian Province and began in the Louisianian Province (Gulf of Mexico from near Tampa Bay, Florida
to the Texas-Mexico  border  at the Rio Grande).  Additional provinces will be added in future years,
eventually resulting in full national implementation of EMAP-Estuaries.

1.2    QUALITY ASSURANCE PROJECT PLAN SPECIFICATIONS

       The quality assurance policy of the EPA requires every monitoring and measurement project to have
a written and approved quality assurance plan (Stanley  and Vemer 1983).  This requirement applies  to all
environmental monitoring and measurement efforts authorized or supported by the EPA through regulations,

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grants,  contracts, or other means.  The quality assurance plan for the  project specifies the policies,
organization, objectives, and  functional  activities for the project  The plan also describes  the  quality
assurance and quality control activities and measures that will be implemented to ensure that the data will
meet all criteria for data quality established for the project All project personnel must be familiar with the
policies and objectives outlined in this quality assurance plan to assure proper interactions  among the
various data acquisition and management components of the project  EPA guidance (Stanley and Verner,
1983) states that the 15 items shown in Table 1.1 should be addressed in the QA Project Plan. Some of
these items are extensively addressed In other documents for this project and therefore are only summarized
or referenced  in this document.

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TABLE 1.1.    Sections in this report that address the 15 subjects required in a Quality Assurance Project
               Plan.
        Quality Assurance Subject                           This Report

        Title page                                           Title page
        Table of contents                                   Table of contents
        Project description                                  Section 3
        Project organization and responsibility                Section 2
        QA objectives                                       Section 4
        Sampling procedures                                Section 6
        Sample custody                                     Section 8
        Calibration procedures                               Section 5,6,7
        Analytical procedures                                Section 7
        Data reduction, validation, and reporting               Section 8,9
        Internal QC checks                                  Section 5
        Performance and system audits                       Section 5,6,7
        Preventive maintenance                              Section 6
        Corrective action                                    Sections
        QA reports to management                          Section 9

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                                      SECTION 2
                            PROJECT ORGANIZATION
2.1   MANAGEMENT STRUCTURE

        For the EMAP-Estuaries monitoring in the Louislanian Province, expertise in specific research and
monitoring areas will be provided by several EPA laboratories and their contracting organizations. The
Environmental Research Laboratory in Gulf Breeze, Rorida (ERL-GB) has been designated as the principal
laboratory for EMAP-E monitoring in the Louisianian Province, and therefore will provide direction and
support for all activities. Technical support is provided to ERL-GB by Technical Resources, Inc. (TRI) and
Computer Sciences Corporation (CSC).  ERL-GB has been designated as the principal laboratory for the
statistical design of the Estuarine monitoring effort. Figure 2.1 illustrates the management structure for the
EMAP-E 1992 Louisianian  Province monitoring.  All key personnel involved in the 1992 Lousianian Province
monitoring are listed in Table 2.1.

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       EMAP-E  QA
       Coordinator
       Ray Valente
Province QA
Coordinator
Tom Heitmuller
                            Associate Director
                              Near  Coastal
                               John Paul
                         Acting Technical Director
                                Estuaries
                              Richard Latimer
 Province Manager
  Kevin Summers
  EMAP-E
  Information
  Manager
  Jeff Rosen
Field Activities
  Coordinator
John Macauley
                 Processing
                Laboratories
           Team Leader 1
                                                        1
 Province
 Inform.
 Manager
 Matt Adams
                 Field Operations
                  Center Support
                      Staff
    Team Leader  2
            Field Crew I
Team Leader 3
     Field Crew 2
 Field Crew 3
  Rgure 2.1. Management structure for the 1992 EMAP-E Louisianian Province monitoring.

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TABLE 2.1.     List of key personnel,  affiliations, and  responsibilities  for the EMAP-Estuaries  1992
               Louisianian Province monitoring.
NAME
ORGANIZATION
RESPONSIBILITY
E. Martinko
F. Kutz
J. Paul
R. Latimer

K. Summers

J. Macauley

L Kirkland
R. Valente
T. Heitmuller

W. Benson
J. Brooks

B. Albrecht

J. Fournie
W. Walker

R. Heard

D. Heggam

J. Rosen
M. Adams
U.S. EPA-DC
U.S. EPA-DC
U.S. EPA-Narragansett
U.S. EPA-Narragansett

U.S. EPA-Gulf Breeze

U.S. EPA-Gulf Breeze

U.S. EPA-Cincinnati
SAIC-Narragansett
TRI-Gulf Breeze

U. Mississippi
Texas A&M Univ.

TRI-Guif Breeze

U.S. EPA-Gulf Breeze
Gulf Coast Research Lab.

Gulf Coast Research Lab.

U.S. EPA-Las Vegas

CSC-Narragansett
CSC-Gulf Breeze
EMAP Director
Deputy Director
NC Associate Director
EMAP-E Acting Technical Director

EMAP-E Design Lead and Louisianian
   Province Manager
Louisianian Province Field Coordinator

Acting EMAP QA Coordinator
EMAP-E QA Coordinator
Louisianian Province QA Coordinator

Contaminant Analyses-Tissue
Contaminant Analyses-Sediments and
   Field Sampling
Toxicity Testing

Fish Histopathology
Sediment Physical Analyses and Field
   Sampling
Benthic Analyses

Logistics Support

Information Management
Information Management

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                                        SECTION 3
                              PROJECT DESCRIPTION
3.1    PURPOSE

       Complete descriptions of the EMAP-E monitoring approach and rationale, sampling design, indicator
strategy, logistics, and data assessment plan are provided in the Near Coastal Program Plan for 1990:
Estuaries (Holland 1990). Briefly, the objectives of the 1992 Near Coastal Louisianian Province monitoring
are to:

       o      Obtain estimates of the variability associated with EMAP-E  indicators which will allow
              establishment of program level data quality objectives (DQOs).

       o      Evaluate the utility, sensitivity, and applicability of the EMAP-Estuaries indicators on a
              regional scale.

       o      Determine the effectiveness of the EMAP network design for quantifying the extent and
              magnitude of pollution problems in the  Louisianian Province.

       o      Demonstrate the usefulness  of results for the purposes of planning, prioritization, and
              determining the effectiveness of existing pollutant control actions.

       o      Develop methods for indicators that can be transferred to EMAP-E user groups.

       o      Identify and resolve logistical issues associated with implementing the network design in the
              Louisianian Province.

       The strategy for accomplishing the above objectives will be to continue to field test the sensitivity
of the proposed  indicators and  network design through a second year of sampling in the  Louisianian
Province estuaries.

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                                        SECTION 4
                       QUALITY ASSURANCE OBJECTIVES
4.1     DATA QUALITY OBJECTIVES

        EMAP-Estuaries  personnel are making a variety of measurements to monitor a defined set of
parameters (i.e., indicators of estuarine and coastal environmental quality). Complete descriptions of the
program's objectives and indicator strategy are presented in the Near Coastal Program Plan (Holland 1990)
and  will  not be repeated  here.  To successfully meet the  objectives, the program's assessments of
ecosystem health must be based on scientifically sound interpretations of the data.  To achieve this  end,
and as required by EPA for all monitoring and measurement programs, objectives must be established for
data quality based on the proposed uses of the data (Stanley and Vemer 1985).  The primary purpose of
the quality assurance program is to maximize the probability that the resulting data will meet or exceed the
data quality objectives (DQOs) specified for the project  Data quality objectives established for the EMAP-
Estuaries project, however, are based on control of the measurement system because error bounds cannot,
at present, be established for  end use of indicator  response data.  As a consequence, management
decisions balancing the cost of  higher quality data against program objectives are not presently possible.
As data are accumulated on indicators and the error rates associated with them are established, end use
DQOs can be established and quality assurance systems implemented to assure acceptable data quality
to meet pre-established program objectives.

        Data quality objectives for the various  measurements being made in EMAP-Estuaries can be
expressed in terms of accuracy, precision, and completeness goals  (Table 4.1). These data quality
objectives more accurately can be termed 'measurement quality objectives* (MQOs), because they are
based solely on the likely magnitude of error generated through the measurement process. The MQOs for
the Project were established by  obtaining estimates of the most likely data quality that is achievable based
on either the  instrument manufacturer's specifications  or  historical data   Scientists  familiar with  each
particular data type provided estimates of likely measurement error for a given measurement process.

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TABLE 4.1.    Measurement quality objectives for EMAP-Estuaries indicators and associated data.
                                   Maximum            Maximum
                                   Allowable            Allowable
                                   Accuracy (Bias)       Precision             Completeness
Indicator/Data Type                  Goal                 Goal                 Goal
Sediment contaminant analyses:
 Organics                          30%                 30%                 90%
 Inorganics                         15%                 15%                 90%

Fish tissue contaminant analyses:
 Organics                          30%                 30%                 90%
 Inorganics                         15%                 15%                 90%

Sediment toxicity                    NA                  NA                  90%

Benthic species composition
and biomass:
 Sorting                            10%                 NA                  90%
 Counting                          10%                 NA                  90%
 Taxonomy                         10%                 NA                  90%
 Biomass                          NA                  10%                 90%

Sediment characteristics:
 Grain size analyses                 NA                  10%                 90%
 Total organic carbon                10%                 10%                 90%
 Acid volatile  sulfide                 10%                 10%                 90%
Water Column Characteristics:
Dissolved oxygen
Salinity
Depth
PH
Temperature

± 1.0 mg/L
± 1 .0 ppt
± 0.5 m
± 0.5 units
± 0.5 °C

10%
10%
10%
NA
NA

90%
90%
90%
90%
90%
                                                                                (continued)

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TABLE 4.1. (Continued)
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Indicator/Data Type
Gross pathology of fish
Fish community composition:
Counting
Taxonomic identification
Length determinations
Fish histopathology
Apparent RPD depth
Maximum
Allowable
Accuracy (Bias)
Goal
NA
10%
10%
± 5 mm
NA
± 5 mm
Maximum
Allowable
Precision
Goal
10%
NA
NA
NA
NA
NA


Completeness
Goal
90%
90%
90%
90%
NA
90%
       The MQOs presented in Table 4.1 are used as quality control criteria both in field and laboratory
measurement processes to set the bounds of acceptable measurement error.  General speaking, DQOs or
MQOs are  usually established for five aspects  of data  quality:  representativeness, completeness,
comparability, accuracy, and precision (Stanley and Vemer 1985).  These terms are defined below with
general guidelines for establishing MQOs for each QA parameter.
4.2     REPRESENTATIVENESS

        Representativeness is defined as the degree to which the data accurately and precisely represent
a characteristic of a population parameter, variation of a property, a process characteristic, or an operational
condition" (Stanley and Vemer, 1985). Representativeness applies to the location of sampling or monitoring
sites, to the collection of samples or field measurements, to the analysis of those samples, and to the types
of samples being used to evaluate various aspects of data  quality.  The location of sampling sites and the

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design of the sampling program for EMAP-Estuaries monitoring in the Louisianian Province provide the
primary focus for defining representative population estimates from this region.

       The proposed sampling design combines the strengths of systematic and random sampling with
an understanding of estuarine systems, to collect data that will provide unbiased estimates of the status of
the Nation's estuarine resources.  Field protocols are documented in the 1992 Louisianian Province Field
Operations Manual (Macauley era/. 1992) for future reference and protocol standardization, as are laboratory
measurement protocols in the Laboratory Methods Manual (U. S. EPA, in preparation).  The types  of QA
documentation samples (i.e., performance evaluation material) used to assess the quality of chemical data
will be as representative as possible of the natural samples collected during the project with respect to both
composition and concentration.

4.3   COMPLETENESS

       Completeness is defined  as "a measure of the amount of data collected from a measurement
process compared to the amount that was expected to be obtained under the conditions of measurement*
(Stanley and Verner 1985). A criteria ranging from 75 to 90 percent valid data from a given measurement
process is suggested as being reasonable for the Project. As data are compiled for the various indicators,
more realistic criteria for completeness can be developed.  The suggested criteria for each data type to be
collected is presented in Table 4.1.
4.4    COMPARABILITY

       Comparability is defined as "the confidence with which one data set can be compared to another*
(Stanley and Vemer 1985).  Comparability of reporting units and calculations,  data  base management
processes, and interpretative procedures must be assured if the overall goals of EMAP are to be realized.
One goal of the EMAP-Estuaries program is to generate a high level of documentation for the above topics
to ensure that future EMAP efforts  can be made comparable.   For example, both field and laboratory
methods  are described in full  detail in manuals which will be made available to all field personnel and
analytical laboratories.  Field crews will undergo Intensive training In a single four week session prior to the
start of field work.  Finally, the sampling design for the Louisianian  Province monitoring has been made

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flexible enough to allow for analytical adjustments, when necessary, to ensure data comparability.
4.5    ACCURACY (BIAS), PRECISION, AND TOTAL ERROR

       The term "accuracy", which is used synonymously with the term bias in this plan, is defined as the
difference between a  measured value and the true or expected value, and represents an  estimate of
systematic error or net bias (Kirchner 1983; Hunt and Wilson 1986; Taylor 1987).  Precision is defined as
the degree of mutual agreement among individual measurements, and represents an estimate of random
error (Kirchner 1983; Hunt and Wilson 1986; Taylor 1987). Collectively, accuracy and precision  can provide
an estimate of the total error or uncertainty associated with an individual measured value. Measurement
quality objectives for the various indicators are expressed separately as maximum allowable accuracy (i.e.,
bias) and precision goals (Table 4.1).  Accuracy and precision goals may not be definable for all parameters
due to the nature of the measurement type. For example, accuracy measurements are not  possible for
toxicity testing and fish pathology identifications because "true" or expected values do not exist for these
measurement parameters (see Table 4.1).

       In order to evaluate the MQOs for accuracy and precision, various QA/QC samples will be collected
and analyzed for most data collection activities. Table 4.2 presents  the types of samples to  be used for
quality assurance/quality control for each of the various data acquisition activities except sediment and fish
tissue contaminant analyses. The frequency of QA/QC measurements and the types of QA data resulting
from these samples or processes are also presented in Table 4.2. Because several different types of QA/QC
samples are required for the complex analyses of chemical contaminants in sediment and tissue samples,
they are presented and discussed separately In Section 5.1  along with presentation of warning and control
limits for the various chemistry QC sample types.

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TABLE 4.2.
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Quality assurance sample types, frequency of use, and types of data generated for EMAP-
Estuaries Louisianian Province monitoring (see Table 5.3 for chemical analysis QA/QC
sample types).
Variable
QA Sample Type
or Measurement
Procedure
Frequency
of Use
Data Generated
for Measurement
Quality Definition
Sediment toxicity
tests
       Reference toxicant     Each experiment
                      Variance of replicated
                      tests over time
Benthic Species
Composition and Biomass:
   Sorting
   Counting and
   Identification

   Biomass
       Resort of complete
       sample including
       debris

       Recount and ID of
       sorted animals

       Duplicate weights
10% of each
tech's work
10% of each
tech's work

10% of samples
No. animals resorted
No. of count and ID
errors

Duplicate results
Sediment grain
size

Organic carbon
and acid vola-
tile sulfide
       Splits of a sample
       Duplicates and
       analysis of
       standards
10% of each
tech's work

Each batch
Duplicate results
Duplicate results
and standard
recoveries
Dissolved
Oxygen cone.
(Surveyor II)
       Water-saturated air
       calibration followed
       by air-saturated water
       measurement
Weekly
Difference between
measurement and
saturation table
values
Dissolved
Oxygen cone.
(DataSonde 3)
Side-by-side
comparison with
Surveyor II
At deployment
and retrieval
of unit
Difference between
DataSonde 3 and
Surveyor II
                                                                                     (continued)

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Table 4.2 (continued).
Variable
QA Sample Type
or Measurement
Procedure
Frequency
of Use
Data Generated
for Measurement
Quality Definition
Salinity
Secondary Sea-        Daily
water Standard
                      Difference between
                      probe measurement
                      and standard value
Temperature
Depth
Thermometer
reading
Check bottom
Daily
Each station
pH
Fish identification
Fish counts
Fish gross
pathology
Fish
histopathology

Apparent RPD
depth
depth against depth
finder on boat

QC check with
standard buffer
solutions

Fish preserved
for verification
by taxonomist

Duplicate counts
Specimens
preserved for
confirmation

Confirmation by
second technician
Duplicate
measurements
Once each day
Twice/crew for
each species
10% of trawls
Regular intervals
5% of slides
10% of samples
                                                                  Difference between
                                                                  probe and thermometer

                                                                  Difference
                                                                  from depth finder
Difference from
standard
Number of mis-
identifications
Replicated difference
between determinations

Number of mis-
identifications
Number of confirmations
Duplicate results

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                                     SECTION 5
 QUALITY ASSURANCE/QUALITY CONTROL PROTOCOLS,  CRITERIA,
                           AND CORRECTIVE ACTION
       Complete and detailed protocols for field and laboratory measurements can be found in the 1992
Louisianian Province Field Operations Manual (Macauley 1992) and in the EMAP-Estuaries Laboratory
Methods Manual (U.S. EPA, in preparation), respectively. Specific QA/QC procedures to be followed during
the 1992 Louisianian Province monitoring are presented in the following sections.

5.1    CHEMICAL ANALYSIS OF SEDIMENT AND  FISH TISSUE SAMPLES

       The EMAP-E program will measure a variety of organic and inorganic contaminants in estuarine
sediment and fish tissue samples (Tables 5.1 and 5.2); these compounds are identical to those measured
in NOAA's National Status and Trends (NS&T) Program.  No single analytical method has been approved
officially for low-level (i.e., low parts per billion) analysis of organic and inorganic contaminants in estuarine
sediments and fish tissue.  Recommended methods for the EMAP-E program are those used in the NS&T
Program (Lauenstein in prep.), as well as those documented in the EMAP-E Laboratory Methods Manual
(U.S. EPA in prep.).  EMAP-E does not require that a single, standardized  analytical method be followed,
but rather that participating laboratories demonstrate proficiency and comparability through routine analysis
of Certified Reference Materials1 (CRMs) or similar types of accuracy-based materials. Furthermore, through
an interagency agreement with the NOAA's NS&T Program, all EMAP-E analytical laboratories are required
to participate in an on-going series of laboratory intercomparison exercises
  Certified Reference Materials are samples in which chemical concentrations have been determined
accurately using a variety of technically valid procedures; these samples are accompanied by a certificate
or other documentation issued by a certifying body (e.g., agencies such as the National Research Council
of Canada (NRCC), U.S. EPA, U.S. Geological Survey, etc.).  Standard Reference Materials (SRMs) are
CRMs issued by the National Institute of Standards and Technology (NIST), formerly the National Bureau
of Standards (NBS). A useful catalogue of marine science reference materials has been compiled by Cantillo
(1990).

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TABLE 5.1.    Chemicals to be measured in sediments by EMAP-Estuaries Louisianian Province.
Polvnuclear Aromatic Hydrocarbons (PAHsi
Acenaphthene
Anthracene
Benz(a)anthracene
Benzo(a)pyrene
Benzo(e)pyrene
Biphenyl
Chrysene
Chrysene(Cl-C4)
Dibenz(a,h)anthracene
Dibenzothiophene
Dibenzothiophene(C1 -C3)
2,6-dimethylnaphthalene
Fluoranthene
Fluorene
Fluorene(Cl -C3)
2-methylnaphthalene
1-methyl napthalene
1 -methylphenanthrene
2,6-dimethylnaphtalene
Naphthalene
Naphtalene(Cl-C4)
Perylene
Phenanthrene
Phenanthrene(Cl -C4)
Pyrene
Benzo(b)fluoranthene
Acenaphthlylene
Benzo(k)fluoranthene
Benzo(g,h,i)perylene
ldeno(1,2,3-c,d)pyrene
2,3,5-trimethyl naphthalene
21 PCS Congeners:

PCB No.       Compound name
  8            2,4'-dichlorobiphenyl
  18           2,2',5-trichlorobiphenyl
  28           2,4,4'-trichlorobiphenyl
  44           2,2',315'-tetrachlorobiphenyt
  52           2,2'15,5'-tetrachlorobiphenyl
  66           2,3',4,4'-tetrachlorobiphenyl
 101           2,2'.4,5,5'-pentachlorobiphenyl
 105           2,313',4,4>-pentachlorobiphenyl
 110/77       2,3,3',4',6-pentachlorobiphenyl
               3,3',4,4'-tetrachlorobiphenyl
 118           2,3',4,4',5-pentachlorobiphenyl
 126           3,3',4,4',5-pentachlorobiphenyl
 128           2.2<,3,3>.4,4'-hexacnlorobiphenyl
 138           2,2',3.4,4'15'-hexachlorobiphenyl
 153           2,2'.4.4',5,5'-hexacnlorobiphenyl
 170           2,2',3.3',4,4',5-heptacnlorobiphenyl
 180           2,2I.3,4,4',5,5'-heptachlorobiphenyl
 187           2,2',3,4'15,5I,6-heptachlorobiphenyi
 195           2,2'.3,3>.4,4>,5,6-octachlorobiphenyl
 206           2,21,3,3',4,4'(5,5I16-nonachJorobiphenyl
 209           2,2'.3>3',4I4'1515t,6,6'-decachlorobiphenyl
Other measurements

Acid volatile sulfide
Total organic carbon
Tributyltln, Dibutyltln.  Monobutyltln
DDT and its metabolites

2,4'-DDD
4,4'-DDD
2,4'-DDE
4,4'-DDE
2,4'-DDT
4,4'-DDT
Chlorinated pesticides
other than DDT
Aldrin
Alpha-Chlordane
Dieldrin
Endosulfan
Endrin
Heptachlor
Heptachlor epoxide
Hexachlorobenzene
Lindane (gamma-BHC)
Mirex
Toxaphene
Trans-Nonachlor

Alkanes

C10-C34
Pristane
Phytane
Total alkanes

Trace Elements

Aluminum
Antimony
Arsenic
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Selenium
Silver
Tin
Zinc

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TABLE 5.2. Chemicals to be measured in fish and shellfish tissue by EMAP-Estuaries Louisianian Province.
        DDT and its metabolites
        2,4'-DDD
        4,4'-DDD
        2,4'-DDE
        4,4'-DDE
        2,4'-DDT
        4,4'-DDT

        Chlorinated pesticides
        other than DDT

        Aldrin
        Alpha-Chlordane
        Dieldrin
        Endosulfan
        Endrin
        Heptachlor
        Heptachlor epoxkje
        Hexachlorobenzene
        LJndane (gamma-BHC)
        Mirex
        Toxaphene
        Trans-Nonachlor

        21 PCB Congeners:
Trace Elements
Aluminum
Arsenic
Cadmium
Chromium
Copper
Iron
Lead
Mercury
Nickel
Selenium
Silver
Tin
Zinc
Butylins

Monobutyltin
Dibutyltin
Tributyltin
        PCB No.       Compound name
          8            2,4'-dichlorobiphenyl
         18            2,2',5-trichlorobiphenyl
         28            2,4,4'-trlchlorobiphenyl
         44            2,2',3,5>-tetracNorobiphenyl
         52            2,2',5,5'-tetrachlorobiphenyl
         66            2,3',4,4I-tetrachlorobiphenyl
        101            2,2',4,5,5'-pentachlorobiphenyl
        105           2,3,31,4,4'-pentachlorobiphenyl
        110/77        2,3,3',4',6-pentachlorobiphenyi
                       3,3',4,4'-tetracWorobiphenyl
        118           2,3',4,4',5-pentachlorobiphenyl
        126           3,3',4,4',5-pentachlorobiphenvl
        128           2,2',3,3I,4,4'-hexachlorobiphenyi
        138           2,2'.3,4,4>,5'-hexachlorobiphenyl
        153           2,21,4,4',5,5'-hexacWorobiphenyl
        170           2,2',3,3',4,4',5-heptachlorobiphenyl
        180           2,2',3,4,4',5,5'-heptachlorobiphenyl
        187           2,2',3,4',5,5',6-heptachlorobiphenyi
        195            2,2'>3,31,4,41.5.6-octc:chlorobiphenyl
        206           2,2113>3',4,4I,5,5'16-nonachlorobiphenyl
        209            2,2',3.3',4,4',515',6,6p-decachlorobiphenvl

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(round-robins), which are conducted jointly by the National Institute of Standards and Technology (MIST)
and  the National  Research Council of Canada (NRCC).   Laboratories must  participate In these QA
intercomparison exercises both to demonstrate initial capability (i.e., prior to the analysis of actual samples)
and  on a continual basis throughout  the  project.  The EMAP-E  laboratories will be required to initiate
corrective actions if their performance in these intercomparison exercises falls below certain pre-determined
minimal standards, described in later sections.

        The data quality objectives for EMAP-E were developed with the understanding that the data will not
be used for litigation purposes. Therefore, legal and contracting requirements as stringent as those used
in the U.S. EPA Contract Laboratory Program, for example, need not be applied to EMAP-E.  Rather, it is
the philosophy of EMAP-E that as  long as required QA/QC procedures are followed and comparable
analytical  performance is demonstrated through the  routine analysis of Certified Reference Materials and
through the on-going QA  intercomparison exercises, multiple procedures for  the  analysis  of  different
compound classes used by  different  laboratories should yield comparable results.  This represents a
"performance-based* approach for quality assurance of low-level contaminant analyses, involving continuous
laboratory evaluation through the use of  accuracy-based  materials (CRMs),  laboratory fortified sample
matrices,  laboratory  reagent blanks,  calibration standards,  and laboratory  and field replicates.  The
conceptual basis for the use of each of these types of quality control samples Is presented in the following
sections.

5.1.1    General  QA/QC Requirements

        The guidance provided in the following sections is based largely on the protocols developed for the
Puget Sound Estuary Program (U.S. EPA  1989); it is applicable to low parts-per-billlon analyses of both
sediment and tissue samples  unless otherwise noted. The QA/QC requirements are intended to provide
a commorv foundation for each laboratory's protocols; the resultant QA/QC data wyi enable an assessment
of the comparability of results generated by different laboratories and different analytical procedures. It
should be noted that the QA/QC requirements specified in this plan represent the minimum requirements
for any  given analytical method.  Additional requirements  which  are method-specific should always be
followed, as long as the minimum requirements presented in this document have been met

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        Data for all QA/QC variables must be submitted by the laboratory as part of the data package; the
completeness of each submitted data package will be checked by the Louisianian Province manager, quality
assurance coordinator, or their designee(s).  Data validation will be conducted by qualified personnel to
ascertain that control limits for QA/QC samples have been met, or, if exceeded, that acceptable narrative
explanations have been  provided  by the laboratory along with the  submitted  data (a  more  detailed
description of data reporting requirements is provided in Section 5:1.13).  The  QA/QC data will be used
initially to assess the accuracy and precision of individual laboratory measurements, and  ultimately to assess
comparability of data generated by different laboratories.

        The results for the various QA/QC samples should be reviewed by laboratory personnel immediately
following the analysis of each sample batch.  These results then should be used to determine when warning
and control  limit criteria have not  been met and corrective actions  must  be taken, before processing a
subsequent  sample  batch. When warning limit criteria have not been met, the laboratory is not obligated
to halt analyses, but  the analyst(s) is advised to investigate the cause of the exceedance. When control limit
criteria are not met, specific corrective actions are required before the analyses may proceed. Warning and
control  limit criteria  and recommended frequency of analysis for each QA/QC element or sample type
required in the  EMAP-E program  are summarized in Table 5.3.  Descriptions  of the use, frequency of
analysis, type of information obtained, and corrective actions for each of these QA/QC sample types or
elements are provided in the following sections.

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TABLE 5.3.
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Key elements for quality control of EMAP-Estuaries chemical analyses (see text for detailed
explanations).
    Element or
    Sample Type
               Warning Limit
               Criteria
Control Limit
Criteria
Frequency
1.) Initial Demonstration
   of Capability (Prior to
   Analysis of Samples):

   -  Instrument Calibration      NA
   - Calculation of Method
    Detection Limits
                                     NA
               Must be equal to or less than
               target values  (see Table 5.4)
   - Blind Analysis of
    Accuracy-Based
    Material                   NA
                                     NA
                      Initial and then
                      prior to analyzing
                      each batch of samples

                      At least
                      once each
                      year
                      initial
2.) On-going Demonstration
   of Capability:

   -  Blind Analysis of
     Laboratory Inter-
     comparison Exercise
     Samples
               NA
NA
Regular intervals
throughout the
year
3.) Continuing Calibration
   Checks using Calibration
   Standard Solutions
               NA
should be within
±15% of initial
calibration ori
average for all
analytes, not to
exceed  ±25% for
any one analyte
At a minimum,
middle and end
of each sample
batch
                                                                                      (continued)

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TABLE 5.3  (continued).
    Element or
    Sample Type
Warning Limit
Criteria
Control Limit
Criteria
Frequency
3.) Analysis of Certified Reference
   Material (CRM) or Laboratory
   Control Material (LCM):

    Precision (see NOTE 1):    NA
    Relative Accuracy
    (see NOTE 2):
                      Value obtained for
                      each analyte should
                      be within 3s control
                      chart limits
                      One with each
                      batch of samples

                      Value plotted on
                      control chart after
                      each analysis of the
                      CRM
       PAHs
        PCBs/pesticides

        inorganic elements
Lab's value should
be within ±25% of
true value on
average for all
analytes; not to
exceed  ±30% of
true value for
more than 30% of
individual analytes

same as above

Lab should be within
±15% of true value
for each analyte
Lab's value should
be within ±30% of
true value on
average for all
analytes; not to
exceed  ±35% of
true value for
more than 30% of
individual analytes

same as above

Lab should be within
±20% of true value
for each analyte
NOTE 1: The use of control charts to monitor precision for each analyte of interest should follow
generally accepted practices (e.g., Taylor 1987). Upper and lower control limits, based on three
standard deviations (3s) of the mean, should be updated at regular intervals.

NOTE 2: True" values in CRMs may be either 'certified'' or "non-certified' (it Is recognized that absolute
accuracy can only  be assessed using certified values, hence the term relative accuracy).  Relative
accuracy is computed by comparing the laboratory's value for each analyte against either end of the
range of values (I.e., 95% confidence limits) reported by the certifying agency. The laboratory's value
must be within ±35% of either the upper or lower 95% confidence interval value. Accuracy control limit
criteria only apply for analytes having CRM concentrations a10 times the laboratory's MDL
                                                                                 (continued)

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TABLE 5.3  (continued).
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    Element or
    Sample Type
Warning Limit
Criteria
Control Limit
Criteria
Frequency
4.) Laboratory Reagent
   Blank
5.) Laboratory Fortified
   Sample Matrix
   (Matrix Spike)
Analysts should use
best professional
judgement if analytes
are detected at <3
times the MDL

NA
No anaiyte should
be detected at > 3
times the MDL
Recovery should be
within the range
50% to 120% for at
least 80% of the
analytes
One with each
batch of samples
At least
5% of total
number of
samples
NOTE: Samples to be spiked should be chosen at random; matrix spike solutions should contain all the
analytes of interest. The final spiked concentration of each anaiyte in the sample should be at least 10
times the calculated MOL
6.) Laboratory Fortified
   Sample Matrix Duplicate
   (Matrix Spike Duplicate)
NA
RPD1 must be
£ 30 for each
anaiyte
Same as
matrix spike
7.) Field Duplicates
   (Field Splits)
NA
NA
number of
5% of total

samples
8.) Internal Standards
   (Surrogates)
9.) Injection Internal
   Standards
NA
       Lab develops
       Its own
Recovery must be
within the range
30% to 150%
Each sample


Each sample
      1 RPD =  Relative percent difference between matrix spike and matrix spike duplicate results (see
               section 5.1.11 for equation)

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5.1.2    Initial Calibration
        Equipment should  be calibrated prior to the analysis of each sample  batch, after each  major
equipment disruption, and whenever on-going calibration checks do not meet recommended control limit
criteria  (Table 5.3).   All calibration standards should be traceable to a recognized organization for the
preparation and certification of QA/QC materials (e.g., National Institute of Standards and Technology, U.S.
Environmental Protection Agency, etc.). Calibration curves must be established for each element and batch
analysis from a calibration blank and a minimum of three analytical standards of increasing concentration,
covering the range of expected sample concentrations. The calibration curve should be well-characterized
and must be established prior to the analysis of samples. Only data which results from quantification within
the demonstrated working calibration range may be reported by the laboratory (i.e., quantification based
on extrapolation is  not acceptable).   Samples  outside the calibration  range  should be diluted  or
concentrated, as appropriate, and reanalyzed.

5.1.3    Initial Documentation of Method Detection Limits

        Analytical chemists have coined a variety of terms to define limits* of detectability; definitions for
some of the more commonly-used terms are provided  in Keith er a/. (1983) and in Keith (1991).   In the
EMAP-E program, the Method Detection Limit (MDL) will be used to define the analytical limit of detectability.
The MDL represents  a quantitative estimate of low-level response detected at the  maximum sensitivity of a
method. The Code of Federal Regulations (40 CFR  Part 136) gives the following rigorous definition: "the
MDL is the minimum  concentration of a substance that can be measured and reported with 99% confidence
that the analyte concentration is greater than zero and is determined from analysis of a sample in a given
matrix containing the analyte.' Confidence in the apparent analyte concentration increases as the analyte
signal increases  above the  MDL

        Each EMAP-E analytical laboratory must calculate and report an MDL for each analyte of interest
in each matrix of interest (sediment or tissue) prior & thg analysis oj field samples for a given year.  Each
laboratory is required to follow the procedure specified in 40 CFR Part 136 (Federal Register, Oct 28,1984)
to calculate MDLs for each analytical method employed.  The matrix and the amount of sample (I.e., dry
weight of sediment or tissue) used in calculating the MDL should match as closely as possible the matrix
of the actual field samples and the amount of sample typically used. In order to ensure comparability of

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results among different laboratories, MDL target values have been established for the EMAP-E program
(Table 5.4).  The initial MDLs reported  by each laboratory should be equal to or less than these specified
target values before the analysis of field samples may proceed.  Each laboratory must periodically (i.e., at
least once each year) re-evaluate its MDLs for the analytical methods used and the sample matrices typically
encountered.
5.1.4    Initial Blind Analysis of a Representative Sample

        A representative sample matrix which is uncompromised, homogeneous and contains the analytes
of interest at concentrations of interest will be provided to each analytical laboratory new to the EMAP-E
program; this sample will be used to evaluate laboratory performance prior to the analysis of field samples.
The sample used for this initial demonstration of laboratory capability typically will be distributed blind (I.e.,
the laboratory will not know the concentrations of the analytes of interest) as part of the laboratory QA
intercomparison exercises.  A laboratory's performance generally will be  considered acceptable if its
submitted values are within ±30% (for organic analyses) and ±20% (for inorganic analyses)  of the known
concentration of each analyte  of interest in the sample. These criteria apply only for analyte concentrations
equal to or greater than 10 times the MDL established by the laboratory.  If the results for the initial analysis
fail to meet these criteria, the laboratory will be required to repeat the analysis until the performance criteria
are met, prior to the analysis of real samples.

5.1.5    Laboratory Participation in  Intercomparison Exercises

        The laboratory QA intercomparison exercises previously referred  to are sponsored  jointly by the
EMAP-E and NOAA NS&T Programs to evaluate both the individual and  collective performance of their
participating analytical laboratories.   Following  the  initial demonstration  of  capability, each EMAP-E
laboratory Is required to participate in these on-going intercomparison exercises as a continuing check on
performance and intercomparability. Usually, three or four different exercises are conducted over the course
of a year.  In a typical exercise, either NIST or NRCC will distribute performance evaluation  samples in
common to each laboratory, along  with detailed  instructions for analysis.  A  variety of performance
evaluation samples have been utilized in the past, including accuracy-based solutions, sample extracts, and
representative matrices (e.g.,  sediment or tissue samples). Laboratories are required to analyze the

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TABLE 5.4.  Target method detection limits for EMAP-Estuaries analytes.
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INORGANICS (NOTE: concentrations in
                                           (ppm), dry weight)
Aluminum
Antimony
Arsenic
Cadmium
Chromium
Copper
Iron
Lead
Manganese
Mercury
Nickel
Selenium
Silver
Tin
Zinc
                                    Tissue
                                    10.0
                                    not measured
                                    2.0
                                    0.2
                                    0.1
                                    5.0
                                    50.0
                                    0.1
                                    not measured
                                    0.01
                                    0.5
                                    1.0
                                    0.01
                                    0.05
                                    50.0
ORGANICS (NOTE: concentrations in ng/g (ppb), dry weight)
PAHs
PCB congeners
Chlorinated pesticides
                                    Tissue
                                    not measured
                                    2.0
                                    2.0
Sediments
   1500
   0.2
   1.5
   0.05
   5.0
   5.0
   500
   1.0
   1.0
   0.01
   1.0
   0.1
   0.01
   0.1
   2.0
Sediments
  10
   1.0
   1.0
sample(s) "blind" and must submit their results in a timely manner both to the Louisianian Province QA
Coordinator, as well as to either  NIST or  NRCC (as instructed).  Laboratories which fail to maintain
acceptable performance may be required to provide an explanation and/or undertake appropriate corrective
actions. At the end of each calendar year, coordinating personnel at NIST and NRCC hold a QA workshop
to present and discuss the intercomparison exercise  results.  Representatives from each laboratory are
encouraged to participate in the annual QA workshops, which provide a forum for discussion of analytical
problems brought to light in the intercomparison exercises.

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5.1.6   Routine Analysis of Certified Reference Materials or Laboratory Control Materials
        Certified Reference Materials  (CRMs) generally are considered the most useful QC samples for
assessing the accuracy of a given analysis (i.e., the closeness of a  measurement to the true" value).
Certified Reference Materials can be used to assess accuracy because they have "certified' concentrations
of the analytes of interest, as determined through replicate analyses by a reputable certifying agency using
two independent measurement techniques for verification.  In addition, the certifying agency may provide
"non-certified" or "informational" values for other analytes of interest.  Such values are determined using a
single measurement technique, which may introduce unrecognized bias.  Therefore, non-certified values
must be used with caution in evaluating the  performance of a laboratory using a method which differs from
the one used by the certifying agency.

        A Laboratory Control Material (LCM) is similar to  a Certified Reference Material in that It is  a
homogeneous matrix which closely matches the samples being analyzed. A true" LCM Is one which  is
prepared (i.e., collected, homogenized and stored in a stable condition) strictly for use in-house by a single
laboratory. Alternately, the material may be prepared by a central laboratory and distributed to others (so-
called regional or  program control materials).  Unlike CRMs, concentrations of the analytes of interest  in
LCMs are not certified but are based upon a statistically-valid number of replicate analyses by one or several
laboratories.  In  practice, this material can be used to assess the precision (I.e., consistency) of a single
laboratory, as well as to determine the degree of comparability among different laboratories. If available,
LCMs may be preferred for routine (i.e., day-to-day) analysis  because CRMs are relatively expensive.
However, CRMs still must be analyzed at regular Intervals (e.g., monthly or quarterly) to provide a check
on accuracy.

        Routine analysis of Certified Reference Materials or, when available, Laboratory Control Materials
represents a particularly vital aspect of the •performance-based" EMAP-E QA philosophy. At least one CRM
or LCM must be analyzed along with each batch of 25 or fewer samples (Table 5.3). For CRMs, both the
certified and non-certified concentrations of the target analytes should be known to the analyst(s) and should
be used to provide an immediate check on performance before proceeding with a subsequent sample batch.
Performance criteria for both precision and accuracy have been established for analysis of CRMs or LCMs
(Table 5.3); these criteria are discussed In detail  in the following paragraphs. If the laboratory fans to meet
either the precision or accuracy control limit criteria for a given analysis of the CRM or LCM, the data for

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the entire batch of samples is suspect.  Calculations and instruments should be checked; the CRM or LCM
may have to be re-analyzed (I.e., re-injected) to confirm the results. If the values are still outside the control
limits in the repeat analysis, the laboratory is required to find and eliminate the source(s) of the problem and
repeat the. analysis of that batch of samples until control limits gx§ met, before continuing with further sample
processing. The  results of the CRM or LCM analysis should never be used by the laboratory to "correct"
the data for a given sample batch.

       Precision criteria:  Each  laboratory is expected to maintain control charts for use by analysts in
monitoring  the overall precision of the  CRM or LCM analyses.  Upper and lower control chart limits (e.g.,
warning limits and control limits) should be updated at regular intervals; control limits based on 3 standard
deviations of the mean generally are recommended (Taylor 1987).  Following the analysis of all samples in
a given year, an RSD (relative standard deviation, a.k.a. coefficient of variation) will be calculated for each
analyte of interest in the CRM.  For each analyte having a CRM concentration >10 times the laboratory's
MDI_ an overall RSD of less than 30% will  be considered acceptable precision. Failure to meet this goal
will result in a thorough review of the laboratory's control charting procedures and analytical methodology
to determine if improvements  in precision are possible.

       Accuracy criteria:  The "absolute" accuracy of an analytical method can be assessed  using CRMs
only when certified values  are provided for the analytes of interest  However, the concentrations of many
analytes of interest to EMAP-E are provided only as non-certified values in some of the more commonly-
used CRMs. Therefore, control  limit criteria are based on 'relative accuracy", which is evaluated for each
analysis of the CRM or LCM by comparison of a given laboratory's values relative to the true' or 'accepted"
values in the LCM or CRM. In the case of CRMs, this includes both certified and noncertified values and
encompasses the 95% confidence interval for each value as described In Table 5.3.

       Accuracy control limit criteria have been established both for individual compounds and combined
groups of compounds (Table 5.3).  There are two combined groups of compounds for the purpose of
evaluating relative accuracy for organic analyses: PAHs and PCBs/pesticides.  The laboratory's value should
be within ±30% of the true value QQ average for each combined group of organic compounds, and the
laboratory's value should be within ±35% of either the upper or lower 95% confidence limit for at least 70%
of the compounds in each  group. For inorganic analyses, the laboratory's value should be within ±20% of
either the upper or lower 95%  confidence limit for each analyte of interest in the CRM. Due to the inherent

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variability in analyses near the method detection limit control limit criteria for relative accuracy only apply
to analytes having CRM true values which are a10 times the MDL established by the laboratory.

5.1.7   Continuing Calibration Checks

        The initial instrument calibration performed prior to the analysis of each batch of samples is checked
through the analysis of calibration check samples (I.e., calibration standard solutions)  inserted as part of the
sample stream.  Calibration standard solutions used for the continuing calibration checks should contain
all the analytes of interest  At a  minimum,  analysis of the calibration check solution should  occur
somewhere in the middle and at the end of each sample  batch.  Analysts should use best professional
judgement to determine if more frequent calibration checks are necessary or desirable.

        If the control limit for analysis of the calibration check standard is not met  (Table 5.3), the initial
calibration will have to be repeated,  if possible, the samples analyzed before the calibration check sample
that  failed the control limit criteria should be re-analyzed following the re-calibration. The laboratory should
begin by re-analyzing the last sample analyzed before the calibration standard which failed.  If the relative
percent difference (RPD) between the results of this re-analysis and the original analysis exceeds 30 percent,
the instrument is assumed to have been out of control during the original analysis.  If possible,  re-analysis
of samples should progress in reverse order until it is determined that there  Is less than 30 RPD between
initial and re-analysis results. Only the re-analysis results should be reported by the laboratory.  If it is not
possible or feasible  to perform re-analysis  of samples,  all earlier  data  (I.e., since the last  successful
calibration control check) is suspect.  In this case, the laboratory should prepare a narrative explanation to
accompany the  submitted data.

5.1.8   Laboratory Reagent Blank

        Laboratory reagent blanks  (also called method blanks or procedural blanks) are used to assess
laboratory contamination during all stages of sample preparation  and analysis.  For both organic and
inorganic analyses, one laboratory reagent blank should be run in every sample batch.  The reagent blank
should be processed  through the entire analytical procedure in a manner identical to the samples. Warning
and  control  limits for blanks  (Table 5.3) are  based  on the  laboratory's method detection limits as
documented prior to  the analysis of samples (see Section 5.1.3). A reagent blank concentration between

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the MDL and 3 times the MDL for one or more of the analytes of interest should serve as a warning limit
requiring further investigation based on the best professional judgement of the analyses). A reagent blank
concentration equal to or greater than 3 times the MDL for one or more of the analytes of interest requires
definitive corrective action to identify and eliminate the source(s)  of contamination before proceeding with
sample analysis.

5.1.9   Internal Standards

        Internal  standards  (commonly  referred to  as 'surrogates", 'surrogate spikes"  or 'surrogate
compounds') are compounds chosen to simulate the analytes of  interest in organic analyses.  The internal
standard represents a reference analyte against which the signal from the analytes of interest is compared
directly for the purpose of quantification.  Internal standards must be added to each sample,  including
QA/QC samples, prior to.  extraction. The reported concentration of each analyte should b_e adjusted &
correct for the recovery  oj the internal standard, as is done in the NOAA National Status and Trends
Program. The internal standard recovery data therefore should be carefully monitored; each laboratory must
report the percent recovery of the internal standard (s) along with the target analyte data for each sample.
If possible, isotopically-Jabeled analogs of the analytes should be used as internal standards.

        Control limit criteria for internal standard recoveries are  provided In Table 5.3. Each laboratory
should set its own warning limit criteria based on the experience and best professional judgement of the
analyst(s).  It is the responsibility of the analyst(s) to demonstrate that the analytical process is always "in
control* (i.e., highly variable internal standard recoveries are not acceptable for repeat analyses of the same
certified reference material and  for the matrix spike/matrix spike  duplicate).

5.1.10  Injection Internal Standards

        For gas chromatography (GC) analysis, injection internal standards  (also referred  to as "internal
standards" by some  analysts) are added to each sample extract just prior to. Injection to enable optimal
quantification, particularly of complex extracts subject to retention time shifts relative to the analysis of
standards. Injection  internal standards are essential If the actual  recovery of the internal standards added
prior to extraction is to be calculated. The  injection internal standards also can be  used to detect and
correct for problems in the GC injection port or other parts of the  instrument. The compounds used as

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injection internal standards must be different from those already used as internal standards.  The analyst(s)
should  monitor injection internal  standard retention times and  recoveries to  determine if instrument
maintenance or repair,  or changes in analytical procedures, are indicated.  Corrective action should be
initiated based on the experience of the analyst(s) and not because warning or control limits are exceeded.
Instrument problems that may have affected the data or resulted in the re-analysis of the sample should be
documented properly in logbooks and/or internal data reports and used by the laboratory personnel to take
appropriate corrective action.

5.1.11   Matrix Spike and Matrix Spike Duplicate

        A laboratory fortified sample matrix (commonly called a  matrix  spike, or MS) and a laboratory
fortified sample matrix duplicate (commonly called a matrix spike duplicate,,or MSD) will be used both to
evaluate the effect of the sample matrix on the recovery of the compound(s) of interest and to provide an
estimate of analytical precision.  A minimum of 5%  of the total number of  samples submitted to the
laboratory in a  given year should be selected at  random for analysis as matrix spikes/matrix  spike
duplicates.  Each MS/MSD sample is first homogenized and then split into three subsamples. Two of these
subsamples are fortified with the matrix spike solution and the third subsample Is analyzed as is to provide
a background concentration for each analyte of interest  The matrix spike solution should  contain all the
analytes of interest The final spiked concentration of each analyte in the sample should be at least 10 times
the MDL for that analyte, as previously calculated by the laboratory (see Section  5.1.3).

        Recovery  data  for the fortified compounds  ultimately will provide a basis for determining the
prevalence of matrix effects in the sediment samples analyzed during the project If the percent recovery
for any  analyte in the  MS or MSD Is less than  the recommended warning  limit of 50 percent, the
chromatograms and raw data quantitatlon reports should be reviewed.  If an explanation for a low percent
recovery value is not discovered, the instrument response may be checked using a calibration standard.
Low matrix spike recoveries may be a result of matrix interferences and further instrument response checks
may not be warranted, especially if the low recovery occurs In both the  MS and MSD and the other QC
samples in the batch Indicate that the analysis was 'in control'.  An explanation for low percent recovery
values for MS/MSO results should be discussed in a cover letter accompanying the data package.
Corrective actions  taken and verification of  acceptable instrument response must be included.

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        Analysis of the MS/MSD also is useful for assessing laboratory precision.  The relative percent
difference (RPD) between the MS and MSD results should be less than 30 for each analyte of interest (see
Table 5.3). The RPD is calculated as follows:

                                (C1 - C2\ x 100%
                       RPD =      (C1 + C2)/2
        where: C1  is the larger of the duplicate results for a given analyte
               C2 is the smaller of the  duplicate results for a given analyte'
        If results for any analytes do meet the RPD s 30% control limit criteria, calculations and instruments
should be checked. A repeat analysis may be required to confirm the results. Results which repeatedly faH
to meet the control limit criteria indicate poor laboratory precision.  In this case, the laboratory is obligated
to halt the analysis of samples and eliminate the source of the imprecision before proceeding.

5.1.12  Field Duplicates and Field Splits

        For the EMAP-E program, sediment will be collected at each station using a grab sampler.  Each
time the sampler is retrieved, the top 2 cm of sediment will be scraped off, placed In a large mixing container
and homogenized, until a sufficient amount of material has been obtained. At approximately 5% of the
stations, the homogenized  material will  be placed in four separate sample containers for subsequent
chemical analysis. Two of the sample containers will be submitted as blind field duplicates to the primary
analytical laboratory. The other two containers, also called field duplicates, will be sent blind to a second,
reference laboratory. Together, the two pairs of duplicates are called field splits. The analysis of the field
duplicates will provide an assessment of single laboratory precision. The analysis of the field duplicates and
field splits will provide an assessment of both inter- and intra-laboratory precision, as wed as an assessment
of the efficacy of the field  homogenization technique.

5.1.13  Analytical Chemistry Data Reporting Requirements

        As previously Indicated, data for all QA/QC samples (e.g., CRMs, calibration check samples, blanks,
matrix spike/matrix spike duplicates, etc.) must be submitted by the laboratory as part of the data package
for each  batch of  samples  analyzed.   The  laboratory  should  denote  QA/QC samples using  the

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recommended codes (abbreviations) provided in Table 5.5. The QA/QC results and associated data will

be subject to review by the Province Manager, QA Coordinator, or their designee(s).


       EMAP-E laboratories are responsible for assigning only two data qualifier codes or "flags" to the

submitted data.  If an analyte is not detected, the laboratory should report the result as "ND",  followed by

the letter "a".  The "a" code will be have the following meaning: The analyte was not detected.  The method

detection limit for this analyte has been supplied by the laboratory and can be found in an accompanying

dataset." If a quantifiable signal Is observed, the laboratory should report a concentration for  the analyte;

the data qualifier code "b" should be used to flag any reported values which are below the laboratory's MDL

The "b" code will have the following meaning: The analyte was detected at a concentration less than or

equal to the method detection limit. This reported concentration is an estimate which  may not accurately

reflect the actual concentration of this analyte in the sample."  All other results above the laboratory's MDL

should be reported without any additional qualification codes.
TABLE 5.5.  Codes for denoting QA/QC samples in submitted data packages.
Code          Description                                         Unit of measure

CLE           Continuing Calibration Evaluation                     Percent recovery
CRM           Certified Reference Material                          pg/g or ng/g (dry weight)
CRMPR        Percent Recovery for CRM values                     Percent recovery
LCM           Laboratory Control Material                          pg/g or ng/g (dry weight)
LCMPR        Percent Recovery for LCM values                     Percent recovery
LRB           Laboratory Reagent Blank                            pg/g or ng/g (dry weight)
LF1            Laboratory fortified sample matrix                     pg/g or ng/g (dry weight)
LF1 PR         Percent recovery for the LF1                          Percent recovery
LF2           Laboratory fortified sample matrix duplicate            pg/g or ng/g (dry weight)
LF2PR         Percent recovery for the LF2                          Percent recovery
MSDRPD       Relative percent different between LF1 and LF2         Percent
       Only data which  has met QA requirements should be submitted by the laboratory.  When QA

requirements have not been met the samples should be re-analyzed and only the results of the re-analysts

should be submitted, provided they are acceptable. There may be a limited number of situations where

sample re-analysis Is not possible or practical (i.e., minor exceedance of a single control limit criteria).  The

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laboratory is expected to provide a detailed explanation of any factors affecting data quality or interpretation;
this explanation should be in the form of a cover letter accompanying each submitted data package. Iba
narrative explanation is ]n lieu of additional data qualifier codes supplied tjy thg laboratory (other than the
"a" and "b" codes).  Over time, depending on the nature of these narrative explanations,  the EMAP-E
program expects to develop a limited list of codes for qualifying data in the database (in addition to the 'a"
and "b" codes).

5.2    OTHER SEDIMENT MEASUREMENTS

5.2.1   Total organic carbon

       As a check on precision, each laboratory should analyze at least one TOC sample in duplicate for
each batch of 25 or fewer samples.  The relative percent difference (RPD) between  the two duplicate
measurements should be less than 20%.  If this control limit is exceeded, analysis of subsequent sample
batches should stop until the source of the discrepancy is determined and the system corrected.

       At least one certified reference material (CRM) or, if available, one laboratory control material (LCM)
should be analyzed along with each batch of 25 or fewer TOC samples. Any one of several marine sediment
CRMs  distributed by the National Research Council of Canada's Marine Analytical Chemistry Standards
Program (e.g., the CRMs named "BCSS-I", "MESS-1" and TACS-1") have certified concentrations of total
carbon and are recommended for this use. Prior to analysis of actual samples, it is recommended that each
laboratory perform several total organic carbon analyses using a laboratory control material or one of the
aforementioned CRMs to establish a control chart (the values obtained by the laboratory for total organic
carbon should be slightly less than the certified value for total carbon in the CRM). The control chart then
should be used to assess the laboratory's precision for subsequent analyses of the LCM or CRM with each
sample batch.   In addition, a method  blank should be  analyzed with each sample batch.  Total organic
carbon concentrations should be reported as pg/g (ppm) dry weight of the unacWified sediment sample.
Data reported for each sample batch should include QA/QC sample results (duplicates, CRMs or LCMs, and
method blanks). Any factors that may have Influenced  data quality should be discussed in a cover letter
accompanying the submitted data.

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5.2.2   Acid volatile sulflda
        Quality control of acid volatile sulfide (AVS) measurements is achieved through the routine analysis
of a variety of QA/QC samples. These are outlined in the following section and described in full detail in
the EMAP-E Laboratory Methods Manual (U.S. EPA, in preparation).  Prior to the analysis of samples, the
laboratory must establish a calibration curve and determine a limit of reliable detection for sulfide for the
analytical method being employed. Following this, laboratory performance will be assessed through routine
analysis of laboratory duplicates, calibration check standards, laboratory fortified blanks (i.e., spiked blanks),
and laboratory fortified sample matrices (I.e., matrix spikes).

        One sample in every batch of 25 or fewer samples should be analyzed in duplicate as a check on
laboratory precision.  The relative percent difference (as calculated by the formula given in section 5.1.11)
between the two analyses  should be less than 20%.  If the RPD exceeds 20%, a third analysis should be
performed. If the relative  standard deviation of the three determined concentrations  exceeds 20%, the
Individual analyses should  be examined to determine if non-random errors may have occurred.

        Due to the Instability of acid volatile sulfides to drying and handling in air, CRMs have not been
developed for assessing overall measurement accuracy. Therefore, each laboratory must analyze at least
one calibration check standard, one laboratory fortified blank and one laboratory fortified  sample matrix In
each batch of 25 or fewer samples as a way of determining the accuracy of each step entailed In performing
the analysis.  The concentration of sulfide in each of these three types of accuracy check samples will be
known to the analyst; the calculated concentration of sulfide in each sample should be within ± 15% of the
known concentration.

        If the laboratory is  not within ± 15% of the known concentration for the calibration check solution,
Instruments used for AVS measurement must be recalibrated and/or the stock solutions redetermined by
titratlon. If the laboratory fails to achieve the same accuracy (within ± 15% of the true value) for AVS in the
laboratory fortified blank, sources of error (e.g., leaks, excessive gas flows, poor sample-acid slurry agitation)
should be determined for the analytical system prior to continuing.  If AVS recovery falls outside the 85%
to 115% range for the matrix spike, the system should be  evaluated for sources of error and the analysis
should be repeated. If recovery remains unacceptable, It is  possible that matrix Interferences are occurring.
If possible, the analysis  should  be repeated using smaller amounts of sample  to reduce the  interferant

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effects. Results for all QA/QC samples (duplicates, calibration check standards, spiked blanks and matrix
spikes) should be submitted by the laboratory as part of the data package for each batch of samples, along
with a narrative explanation for results outside control limits.

        As discussed in Section 5.1.12 for chemistry samples, field duplicates and splits will  also  be
collected for AVS determination to assess both inter- and intralaboratory precision.

5.2.3   Butvltlns

        Assessment of the distribution and environmental impact of butyltin species of interest to the EMAP-
E program (tributyltin, dibutyltin and monobutyitin) requires their measurement in marine sediment and tissue
samples at trace levels (parts per billion to parts per trillion). Quality control of these measurements consists
of checks on laboratory precision and accuracy.  One laboratory reagent blank must be run with each batch
of 25 or fewer samples. A reagent blank concentration between the MDL and 3 times the MDL should serve
as a warning limit requiring further investigation based on the best professional judgement of the analyst(s).
A reagent blank concentration equal to or greater than 3 times the MDL requires corrective action to identify
and eliminate the source(s) of contamination, followed by re-analysis of the samples in the associated batch.

        One laboratory fortified sample matrix (commonly called a matrix spike) or laboratory fortified blank
(i.e.,  spiked blank) should be analyzed along  with  each  batch  of 25 or fewer samples to evaluate the
recovery of the butyltin species of interest  The butyttins should  be added at 5 to 10 times their MDLs  as
previously calculated by the laboratory (see Section 5.1.3).  If the percent recovery for any of the butyltins
in  the matrix spike or spiked blank is outside the range 70 to 130 percent, analysis of subsequent sample
batches should stop untH the source of the discrepancy is determined and the system corrected.

        The NRCC sediment reference material  'PACS-1',  which has certified concentrations of the three
butyltin species of interest, also should be analyzed along with each batch of 25 or fewer sediment samples
as a  check  on accuracy and  reproducibility (I.e., batch-to-batch precision).  If values obtained by the
laboratory for butyltins in "PACS-1' are not within ±30% of the certified values, the data for the entire batch
of  samples is suspect  Calculations and instruments should  be checked;  the CRM may have to be  re-
analyzed to  confirm the results.  If the values are still outside the control limits in the repeat analysis, the
laboratory is required to determine the source(s) of the problem and repeat the analysis of that batch of
samples until control limits are met,  before continuing with further sample processing.

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5.2.4   Sediment grain size
        Quality control of sediment grain size analyses is accomplished by strict adherence to protocol and
documentation of quality control checks.  Several procedures are critical to the collection of high quality
particle size data.  Most important to the dry sieve analysis is that the screens are dean before conducting
the analysis, and that all of the sample is retrieved from them.  To dean a screen, it should be Inverted and
tapped on a table, while making sure that the rim hits the table evenly.  Further deaning of brass screens
may be performed by gentle scrubbing with a stiff bristle nylon brush.  Stainless steel screens may be
cleaned with a nylon or brass brush.

        The most critical aspect of the pipet analysis is knowledge of the temperature of the silt-day
suspension.  An Increase of only 1 °C will increase the settling velocity of a partide 50 pm in diameter by
2.3 percent.  It is generally recommended that the pipet analysis be conducted at a constant temperature
of 20 °C.  However,  Plumb (1981) provides a table to correct for settling velocities at other temperatures;
this table is included in the EMAP-E Laboratory Methods Manual (U.S.  EPA, in preparation).  Thorough
mixing of the silt-clay suspension at the beginning of the  analysis Is also critical. A perforated, plexiglass
disc plunger is very  effective for this purpose.  If the mass of sediment used for pipet analysis exceeds 25
g, a subsample should be taken as described  by Plumb (1981).  Silt-day samples in excess of 25 g may
give erroneous results because of electrostatic interactions between the particles. Silt-day samples less than
5 g yield a large experimental error in weighing relative to the total sample weight

        The analytical balance, drying oven, sieve shaker, and temperature bath used in the analysis should
be calibrated at least monthly. Quality assurance for the sediment analysis procedures will be accomplished
primarily by re-analyzing a randomly selected subset of samples from each batch, as described in full detail
in the EMAP-E Laboratory Methods Manual  (U.S. EPA, in preparation).  A batch of samples is defined as
a  set of samples  of a single textural dassification  (e.g., sat/clay, sand, gravel) processed  by a single
technician using a single procedure. Approximately  10% of each batch completed by the same technician
will be re-analyzed (I.e., reprocessed) in the same manner as the original sample batch.  If the absolute
difference between the original value and the second value is greater than 10% (in terms of the percent of
the most abundant sediment size dass), then a third analysis will be completed by a different technician.
The values dosest to the third value will be entered into the database. In addition, all the other samples in
the same  batch must be re-analyzed, and the laboratory protocol and/or technician's practices should be

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reviewed and corrected to bring the measurement error under control.  If the percent of the most abundant
sediment size class in the original sample and the re-analyzed sample differs by less than 10, the original
value will not be changed and the sediment analysis process will be considered in control.

5.2.5   Apparent RPD Depth

       The depth of the apparent RPD (redox potential discontinuity) wHI be determined in the field through
visual observation of clear plastic cores inserted into undisturbed sediment grab samples at each station.
In fine-grained sediments, the apparent RPD depth is measured from the sediment surface to the point at
depth where the color changes from light to dark.  As a QC check, sediment cores will be re-measured by
the QA Coordinator during field visits. The field crew's original measurement should be within ±5 mm of
the re-measurement; failure to achieve this agreement will result in re-training of the crew.

5.3   SEDIMENT TOX1CITY TESTING

       The toxicity of sediments collected by field crews will be determined as an integral part  of the
benthic indicator suite, using 10-day acute toxicity tests with the marine amphipod Ampelisca abdita and
4-day tests with mysid shrimp Mysidopsis bahia. Complete descriptions of the methods employed for the
sediment toxicity test are provided in the Laboratory Methods Manual (U.S.  EPA, in preparation).  The
various aspects of the test for which quality assurance/quality control procedures are specified include the
following: the condition of facilities and equipment, sample handling and storage, the source and condition
of test organisms, test conditions, instrument calibration, use of replicates, use of reference toxicants, record
keeping, and data evaluation.  In addition, any laboratory which has not previously performed the sediment
toxicity test using Ampelisca abdita or Mysidopsis bahia will be required to perform an initial demonstration
of capability,  as described below.

5.3.1   Facilities and Equipment

       Laboratory  and  bioassay  temperature  control equipment  must be adequate to  maintain
recommended test temperatures.  Recommended materials must be used In the fabrication of the test
equipment  in contact  with the water  or sediment being tested, as specified In the EMAP-E Laboratory
Methods Manual (U.S. EPA, in preparation).

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5.3.2   Initial Demonstration of Capability
        Laboratories which have not previously conducted sediment toxlclty tests with Ampelisca abdita or
Mysidopsis bahia must demonstrate the ability to culture, collect (If applicable), hold and test the organisms
without significant loss or mortality, prior to performing tests of actual samples. There are two types of tests
which must be performed as an initial demonstration of capability; these tests will serve to indicate the
overall ability of laboratory personnel to handle the organism adequately and obtain consistent, precise
results.  First, the laboratory must  perform  a minimum of five successive reference toxicant tests, using
sodium dodecyl sulfate (SDS) as the reference toxicant. For both Mysidopsis bahia and Ampelisca abdita,
short-term (I.e., 96-hour) tests without sediments (I.e., seawater only) can be used for this purpose.

        The  trimmed  Spearman-Karber method of regression analysis (Hamilton ef al.  1977)  or  the
monotonic regression analysis developed by DeGraeve et al. (1988) can be used to determine an LC50
value for each 96-hour reference toxicant test  The LC50 values should be recorded on a control chart
maintained in the laboratory (described in greater detail in section 5.3.4, to follow).  Precision then can be
described by the LC50 mean,  standard deviation, and percent relative standard deviation (coefficient of
variation, or CV) of the five (or more) replicate reference toxicant tests. If the laboratory fays to achieve an
acceptable level of precision in the five preliminary reference toxicant tests, the test procedure should be
examined for defects and the appropriate corrective actions should be taken.  Additional tests should be
performed until acceptable precision is demonstrated.

        The second series of tests which must be performed successfully prior to the testing  of actual
samples are 10-day, "non-toxicant" exposures of Ampelisca abdita or 4-day exposures for Mysidopsis bahia,
in which test chambers contain the control  sediment and seawater that  will be used under actual testing
conditions.  These 'control" tests should be performed concurrent with the reference toxicant tests used to
assess single laboratory  precision.  At least  five replicate test chambers should be used in each test  The
tests should be run in succession until two consecutive tests each  have mean survival equal to or greater
than 85% and survival in the individual test chambers is not less than 80%.  These are the control survival
rates which must be achieved during actual testing if a test Is to be considered acceptable (see section
5.3.6); therefore, the results of this preliminary demonstration will  provide evidence that facilities, water,
control sediment, and handling techniques are adequate to result In successful testing of samples.

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5.3.3   Sample Handling and Storage
        Techniques for sample collection, handling,  and storage are described in the Field Operations
Manual (Macauley 1992).  Sediment samples for toxicity testing should be chilled to 4°C when collected,
shipped on ice, and stored in the dark in a refrigerator at 4°C until used.  Sediments should be stored for
no longer than four weeks before the initiation of the test, and should not be frozen or allowed to dry.
Sample containers should be made of chemically inert materials to prevent contamination, which might result
in artificial changes in toxicity.

        To avoid contamination during collection, all sampling devices and any other instruments in contact
with the sediment should be cleaned with water and a mild detergent and thoroughly rinsed between
stations (see Macauley 1992).  All utensils in contact with the sample should be made of either teflon or
high quality stainless steel (304 or better).

5.3.4   Quality of Test Organisms

        All test organisms used in the tests should be disease-free and should be positively identified to
species. If the amphipods are collected from the field prior to testing, they should be obtained from an area
known to be free of toxicants and should  be held in clean, uncontaminated water and facilities. Mysids must
be obtained  from facilities that  have demonstrated successful  culturing  from  brood stocks held in
uncontaminated seawater.  Test organisms held prior to testing should be checked daily, and individuals
which appear unhealthy or dead should be discarded.  If greater than 5% of the organisms in holding
containers are dead or appear unhealthy during the 48 hours preceding a test, the entire group should be
discarded and not used in the test

        The sensitivity of each batch of test organisms obtained from an outside source  (e.g., field collected
or obtained from an outside culture facility) must be evaluated with the reference toxicant sodium dodecyl
sulfate (SDS) in a short-term toxicity test performed concurrently with the sediment toxicity tests. The use
of the reference  toxicant SDS is required  as a means of  standardizing  test results among different
laboratories.   For Ampelisca abdita and Mysidopsis bahia, a 96-hour reference toxicant test without
sediment is used to generate LC50 values, as previously described In section 5.3.2.

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        These LC50 values should be recorded on the same control chart used to record the results of the
five (or more) reference toxicant tests performed for the Initial demonstration of capability.  The control chart
represents a 'running plot" of the toxicity values (LCSOs) from successive reference toxicant tests. The mean
LC50 and the upper and lower control limits (±2S) are recalculated with  each successive point until the
statistics stabilize. Outliers, which are values which fall outside the upper and lower control limits, are readily
identified. The plotted values are used to evaluate trends in organism sensitivity, as well as the overall ability
of laboratory personnel to obtain consistent results.

        Reference toxicant tests results (i.e., LC50 values) which fall outside control chart limits should serve
as a warning to laboratory personnel. At the P=0.05 probability level, one in twenty tests would be expected
to fall outside control limits by chance only. The laboratory should try to determine the cause of the outlying
LC50 value, but a re-test of the samples is  not necessarily required. If the reference toxicant test results are
outside control chart limits  on  the next consecutive  test, the sensitivity of the organisms and the overall
credibility of the test are  suspect The  test procedure again should be examined for defects and additional
reference toxicant tests performed.  Testing of samples  should  not resume  until acceptable  reference
toxicant results can  be obtained; this may require the use of a different batch of test organisms.

5.3.5    Test Conditions

        Parameters such as water temperature, salinity (conductivity), dissolved oxygen, and pH should be
checked as required for each  test and maintained within the specified limits (U.S. EPA, in preparation).
Instruments used for routine measurements must be calibrated and standardized according to instrument
manufacturer's procedures.  All routine chemical and physical analyses must  Include established quality
assurance practices as outlined In Agency methods manuals (U.S. EPA 1979a and b).

        Overlying water must meet the requirements for uniform quality specified in the method (U.S. EPA,
in preparation). The  minimum requirement for acceptable overlying water Is that it allows acceptable control
survival without signs of organism disease or apparent  stress  (I.e., unusual  behavior or changes  In
appearance). The overlying water used in the sediment toxicity tests with test organisms may be natural
seawater, hypersaline brine (100 %o) prepared from natural seawater, or artificial seawater prepared from sea
salts.  If natural seawater Is used, it should be obtained from an uncontaminated  area known to  support a
healthy, reproducing population of the test organism or a comparably sensitive species.

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5.3.6    Test Acceptability
        Survival of organisms in control treatments should be assessed during each test as an indication
of both the validity of the test and the overall health of the test organism population.  The tests with
Ampelisca abdlta and Mysidopsis bahia are acceptable if mean control survival is greater than or equal to
85 percent, and if survival in individual control test chambers exceeds 80 percent.  Additional guidelines for
acceptability of individual sediment toxicity tests are presented in the EMAP-E Laboratory Methods Manual
(U.S. EPA, in preparation).  An individual test  may be conditionally acceptable if temperature, dissolved
oxygen (DO), and  other specified conditions fall outside specifications, depending on the degree of the
departure and the objectives of the tests. Any deviations from test specifications must be noted and
reported to the QA Coordinator when reporting the data so that a determination can be  made of test
acceptability.

5.3.7   Record Keeping and Reporting

        Proper record keeping is mandatory. Bound notebooks must be used to maintain detailed records
of the test organisms such as species, source, age, date of receipt, and other pertinent Information relating
to their history and health, and information on the calibration of equipment and instruments, test conditions
employed, and test results. Annotations should be made on a real time basis to prevent loss of information.
Data for all QA/QC variables,  such as reference toxicant test results and  copies of control charts, should
be submitted by trie laboratory along with test  results.

5.4    MACROBENTHIC COMMUNITY ASSESSMENT

        Sediment samples for macrobenthic community assessments will be collected at each station using
a Young-modified Van Veen grab sampler. In order to be considered acceptable, each grab sample must
be obtained following the specified protocol and must meet certain pre-«stablished quality control criteria,
as described in detail in  the Field Operations  and Safety Manual (Reifsteck ef a/. 1992).  The collected
sediment will be sieved  in the field through a  0.5 mm screen  and the material collected on the screen
preserved and returned to the laboratory for processing.  In the laboratory, QA/QC involves a series of
check systems for  organism sorting, counting and taxonomic identification. These checks are described
briefly in the following sections; more complete details can be found In the EMAP-E Laboratory Methods
Manual (U.S. EPA,  in preparation).

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5.4.1    Sorting
       The quality control check on each technician's efficiency at sorting (I.e., separating organisms from
sediment and debris) consists of an independent re-sort by a second, experienced sorter. A minimum of
10% of all samples sorted by each technician must be re-sorted to monitor performance and thus provide
feedback necessary to maintain acceptable standards.  These re-sorts should be conducted on a regular
basis on at least one sample chosen at random for each batch of 10 samples processed by a given sorter.
Inexperienced sorters require a more intensive QC check system.  It is recommended that experienced
sorters or taxonomists check each sample processed by inexperienced sorters until proficiency in organism
extraction is demonstrated.  Once proficiency has been demonstrated, the checks may be performed at
the required frequency of one every ten samples. Logbooks must be maintained in the laboratory and used
to record the number  samples processed by each technician, as well as the results of all sample re-sorts.
        For each sample that is re-sorted, sorting efficiency should be calculated using the following formula:

               	# of organisms originally sorted	   x 100
               # organisms originally sorted + additional # found in resort

        The results  of sample re-sorts may require that certain actions be taken for specific technicians.
If sorting efficiency is greater than 95%, no action is required. If sorting efficiency is between 90% and 95%,
problem areas should be identified and the technician should  be re-trained.  Laboratory supervisors must
be particularly sensitive to systematic errors (e.g., consistent failure to extract specific taxonomic groups)
which may suggest  the need for further training. Resort efficiencies below 90% will require re-sorting of all
samples in the associated batch and continuous monitoring of that technician to improve efficiency.

        If sorting efficiency is less than 90%, organisms found in the re-sort should be added to the original
data sheet and, if possible, to the appropriate vials for biomass determination. If sorting efficiency is 90%
or greater, the QC results should be recorded in the appropriate logbook, but the animals should not tj§
added to the original sample or used for biomass determinations.  Once all quality control criteria associated
with the sample re-sort have been met, the sample residues may be discarded.

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5.4.2    Species Identification and Enumeration
        Only senior taxonomists are qualified to perform re-identification quality control checks. A minimum
of 10% of all samples (i.e., one sample chosen at random out of every batch of ten samples) processed by
each  taxonomic  technician must be  checked  to  verify  the accuracy  of  species identification  and
enumeration. This control check establishes the level of accuracy with which identification and counts are
performed and offers feedback to taxonomists in the laboratory so that a high standard of performance is
maintained.  Samples should never be re-checked by the technician who originally processed the sample.

        Ideally, each batch often samples processed by an individual taxonomic technician should be from
a similar habitat type (e.g., all oligohaline stations). The re-check of one out of the ten samples in a batch
should be done periodically and in a timely manner so that subsequent processing steps (e.g.,  biomass
determinations) and data entry may proceed.  As each taxon is identified and counted during the re-check,
the results should be compared to the original data sheet. Discrepancies should be double-checked to be
sure of correct final results. Following re-identification, specimens should be returned to the original vials
and set aside for biomass determination.

        When the entire sample  has been re-identified and re-counted, the total number of errors should be
computed. The total number of errors will be based upon the number of misidentifications and miscounts.
Numerically, accuracy will be represented in the following manner

        Total # of organisms in QC recount - Total number of errors x 100
               Total # of organisms in QC recount

where the following three types  of errors are  included in the total # of errors:
   1.)    Counting errors (for example, counting 11 individuals of a given species as 10).
  2.)    Identification errors (for example,  identifying Species X as Species Y, where both are present)
  3.)    Unrecorded taxa errors  (for example, not identifying Species X when it is present)

        Each taxonomic technician must  maintain an identification and enumeration accuracy of 90% or
greater (calculated using the above formula).  If results fall  below this level, the entire sample batch must
be re-identified and counted. If taxonomic efficiency is between 90% and 95%, the original technician  should
be advised and species identifications reviewed. All changes in species identification should be recorded

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on the original data sheet (along with the date and the initials of the person making the change) and these
changes should be entered into the database. However, the numerical count for each taxonomic group
should not be corrected unless the overall accuracy for the sample is below 90%. Additional details on this
protocol are provided in the EMAP-E Laboratory Methods Manual (U.S. EPA, in preparation).  The results
of all QC rechecks of species identification and enumeration should be recorded in a timely manner  In a
separate logbook maintained for this purpose.

        As organisms are identified, a voucher specimen collection (taxonomic reference collection) should
be established.  This collection should consist of  representative specimens of each species Identified in
samples from an Individual Province in a given year. For some species, it may be appropriate to Include
in the reference collection individuals collected in different geographic locations within the Province.  The
reference collection should be used to train new taxonomists and should be sent to outside consultants to
verify the  laboratory's taxonomic identifications.   Any resulting discrepancies  should be resolved in
consultation with the EMAP-E Province Manager and/or the Province QA Coordinator.

5.4.3   Blomass Measurements

        Performance checks of the balance used for biomass determinations should be performed routinely
using a set of standard reference  weights (ASTM Class  3, NIST Class S-1, or equivalents).  In addition, a
minimum of 10% of all pans and  crucibles in each batch processed by a given technician must be  re-
weighed by a second technician  as a continuous monitor on performance.   Samples to be re-weighed
should be selected randomly from the sample batch; the results of the re-weigh should be compared against
the original final weight recorded on the biomass data sheet  Weighing efficiency should be calculated using
the following formula:
                                Original final weight    x 100
                               Reweighed final weight
        If weighing efficiency Is between 95% and 105%, the sample has met the acceptable quality control
criteria and no action Is necessary. If weighing efficiency Is between either 90% to 95% or 105% to 110%,
the sample has met acceptable criteria, but the technician who completed the original weighing should be

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consulted and proper measurement practices reviewed.  If the weighing efficiency Is less than 90% or
greater than 110%, then the sample has failed the quality control criteria and all samples in the associated
batch must be re-weighed (following technician re-training and/or troubleshooting of laboratory equipment
to determine and eliminate the source(s) of the inconsistency). Corrections to the original data sheet should
only be made in those cases where weighing efficiency is less than 90% or greater than 110%. The results
of all QC re-weighings should be recorded in a timely  manner In  a separate logbook or data sheet and
maintained as part of the documentation associated with the biomass data.

5.5   FISH SAMPLING

5.5.1   Species Identification. Enumeration and Length Measurements

       Fish species identification, enumeration and individual lengths will  be determined in  the field
following protocols presented in the Louisianian Province Reid Operations Manual (Macauley 1992). The
quality of fish identifications, enumerations and length measurements will be  assured principally through
rigorous  training of field personnel prior to field sampling. Qualified taxonomists will provide independent
confirmation of all fish identifications, enumerations and  length measurements made by crew members
during laboratory training sessions.  An emphasis will be placed on correct  identification of fish "target"
species to be saved by  the  field crews for  later chemical contaminant analyses.  Fish identifications,
enumerations and length  measurements also will be confirmed by the QA Coordinator, Province Manager,
or their designee(s) during field visits.  In addition, each field crew will be required to save two "voucher"
specimens of each species identified in the field. These voucher specimens will be preserved in fixative and
sent back to the Reid Operations Center on a regular basis throughout the field season.  A qualified fish
taxonomist will verify the species identifications and provide immediate feedback to the field crews whenever
errors are found.  The fish sent  to the ERL-GB  laboratory for gross pathological and histopathdogical
examination also will be checked for taxonomic determination accuracy. All  erroneous identifications for
a given field crew will be  corrected in the database. The preserved voucher fish wM be saved to provide
a reference collection for  use  in subsequent years' training.

       The overall accuracy goal for all fish Identifications, enumerations and length measurements in a
given sampling season Is 90% (i.e., less than 10% errors).  If this  goal Is not met, corrective actions will
include increased emphasis on training and more rigorous testing of field crews prior to the next year's

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sampling season.  During the field season, the QA Coordinator, Province Manager and/or RekJ Coordinator
must be informed of species misidentifications immediately so that the appropriate field crew can be
contacted and the problem corrected.

5.5.2   Fish Gross Pathology and Hlstopathology

        The field  procedures for gross pathological examination of fish are detailed in  the Louisianian
Province Field Operations Manual (Macauley 1992). As with fish identification and enumeration, the quality
of gross pathology determinations will be assured principally through rigorous training of field  personnel
prior to field sampling.  Qualified pathologists will be responsible for planning and  overseeing all crew
training and will provide independent confirmation of all pathologies noted by field personnel during the
training sessions.  During the actual  sample collection period, these qualified pathologists also will  record
any gross external pathologies they find in examining fish which the crews send back to the laboratory for
histopathological study (which will include those fish on which crews found pathologies as well as those
without pathologies). The laboratory pathologist(s) will perform these examinations without knowledge of
the gross external pathologies noted by the field crews; this will provide a measure of the number and type
of pathologies which were either incorrectly Identified or missed In the field (I.e.. false positives and false
negatives).  This information will also be used to "customize" crew training  In future years.

        A series of internal and external laboratory QC checks will be employed to provide verification of
the  fish  histopathology  Identifications.   In  laboratories having  multiple pathologists, all  cases bearing
significant lesions  should be examined and verified by the senior pathologist At least 5% of the slides read
by one pathologist should  be selected at random and read by a second pathologist without knowledge of
the diagnoses made by the initial reader.  For the external QC check, at least 5% of the slides should be
submitted for independent diagnosis to a pathologist not involved with the laboratory.  These slides  should
represent the range of pathological conditions found during the study, and the external pathologist  should
not be aware of the diagnoses made by the laboratory personnel.

        Each laboratory also should maintain a reference collection of slides that represent every type of
pathological condition identified in the EMAP-E fish. Each of these slides should be verified by an external
pathologist having experience with the species in question. The reference slide collection then can be used
to verify the  diagnoses made in future years to ensure Intralaboratory consistency. The reference slides also

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can be compared with those of other laboratories to ensure interlaboratory consistency.  A reference
collection of photographs also can be made, but this should not substitute for a slide collection.

5.6     WATER COLUMN MEASUREMENTS

        Characterization of the water column is accomplished in two ways: point-in-time vertical profiles and
continuous, long-term, near-bottom measurements. The Hydrolab Surveyor II Datalogger is used to obtain
vertical profiles of temperature, salinity, dissolved oxygen, and pH. The Hydrolab DataSonde 3 is used to
continuously record longer-term (24 hour) time series of temperature, salinity, dissolved oxygen, and pH in
the near-bottom waters (ca. 0.5  meter off the bottom).

        Quality control of the water column measurements made with these electronic instruments consists
of two aspects: calibrations and QC checks of the calibrations. The Surveyor II is calibrated daily,  usually
within a few hours of being used in the field. The DataSonde 3 units are calibrated and programmed for
internal recording within 24 hours of their deployment; this calibration Is then re-checked aboard the boat
immediately prior to deployment by conducting a side-by-side test against the Surveyor II.  In this case, the
calibrated Surveyor II is considered the "standard" against which the  performance of the DataSonde  3 is
evaluated.  Upon retrieval, the DataSonde 3 is again checked side-by-side against the Surveyor II. Specific
QC procedures for each instrument are discussed in the following sections.

5.6.1    Hvdrolab Surveyor II

        Calibration and Calibration Checks

        Each Surveyor I! instrument is calibrated daily just prior to beginning the day's field activities.  The
calibration  of the conductivity cell, for measuring salinity,  Is checked  and re-set,  if necessary, using a
secondary  seawater standard that has  been standardized against IAPSQ Standard Seawater using a
Guildline laboratory salinometer. The dissolved oxygen probe Is calibrated using the water-saturated air
procedure recommended by the manufacturer. This calibration is checked verified weekly by immersing the
probe in a bucket of air-saturated water and  checking the D.O. reading against the value from a saturation
table.  The calibration of the pH probe is checked and re-set, If necessary, using two standard pH buffers
(7 and  10) as recommended by the manufacturer.  The  pressure sensor, used to measure depth, is

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calibrated by setting the depth to zero meters while holding the instrument at the water's surface (i.e., sea-

level). The calibration of the temperature sensor is set at the factory and cannot be changed; this calibration

is checked by comparison with a thermometer  reading while the instrument  is immersed in  a bucket  of

ambient water.



TABLE 5.6.  Maximum acceptable differences for instrument field calibration checks.


Instrument
Hydrolab
Surveyor II


Hydrolab
DataSonde 3



Frequency
of Check
Daily



Pre- and
post-
deployment



Parameter
Temperature
Salinity
D.O.
PH
Temperature
Salinity
D.O.
PH

Checked
Against
Thermometer
Standard seawater
Saturation chart
pH buffer solution
Surveyor II
Surveyor II
Surveyor II
Surveyor II
Maximum
Acceptable
Difference
± 1°C
± 1 ppt
± 0.5 ppm
± 0.5 pH units
±1°C
± 1 ppt
± 0.5 ppm
± 0.5 pH units
5.6.2    Hvdrolab DataSonde 3


        The Hydrolab DataSonde 3 is a self-contained data-logging instrument used to measure temperature,

salinity, dissolved oxygen, pH, and depth; individual units are moored approximately 0.5 meter above the

bottom inside a protective PVC housing.  These instruments are programmed to record data internally at

15 minute intervals throughout their 24 hour deployments.


        Calibration
        Each DataSonde 3 instrument is calibrated under controlled laboratory conditions within 24 hours

of being deployed.  The conductivity ceil, for measuring salinity, Is calibrated using a secondary seawater

standard that has been standardized against IAPSO Standard  Seawater using a GuBdline laboratory

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salinometer.   The  dissolved oxygen  probe is  calibrated using  the  water-saturated air procedure
recommended by the manufacturer.  The pH probe is calibrated using two standard pH buffers (7 and 10)
as recommended by the manufacturer.  The pressure sensor used to measure depth is calibrated by setting
the depth to zero meters while holding the instrument at the water's surface (i.e., sealevel). The calibration
of the temperature sensor is set at the factory and cannot be changed.

        Calibration Checks

        Calibration checks are conducted aboard the boat immediately prior to deployment and immediately
following retrieval of each unit.  The DataSonde 3 is placed in a bucket of ambient water along with a
calibrated Hydrolab  Surveyor II unit which in this case is considered the "standard'.  Measurements of D.O.,
pH, salinity, temperature  and depth are recorded for each instrument and compared.   If the difference
between the Datasonde3 and Surveyor II exceeds the acceptable range for any parameter (Table 5.6), the
DataSonde 3 is recalibrated  and the side-by-side check is repeated. A second failure by the  DataSonde 3
is indicative of more serious problems and would necessitate the use of a back-up instrument.

5.7     NAVIGATION

        Station location information is recorded in the field on standard data forms.  In addition, the field
crews are required  to  maintain a navigation log book and record all LORAN-C calibration information.
Furthermore, the crews must record radar ranges and hand-held compass bearings for any sampling station
where the LORAN-C cannot be used for navigation.  All navigation logs will be checked for completeness
and accuracy during  field  audits.  Following the completion of field  activities, the range and bearing
information from a  subset  of stations visited by each  crew will be reviewed at random  to verify the
positioning accuracy achieved using the electronic navigation system.

        Due to the complexity of navigation and potential interferences, the most important aspect of quality
assurance is thorough training.  Especially important is the need for the Crew Chief to evaluate the quality
of all inputs and decide which are most appropriate at each station. Once this is decided, proper calibration
of the navigation system is critical. Calibration information will also be recorded in the navigation log. Proper
navigation must be extensively discussed during both crew chief and crew training.

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                                        SECTION 6

          FIELD OPERATIONS AND PREVENTIVE MAINTENANCE


6.1     TRAINING AND SAFETY

        Proper training of fieid personnel represents a critical aspect of quality control. Field technicians
are trained to conduct a wide variety of activities using standardized protocols to insure comparability  in
data collection among crews and across regions. Each field team consists of a Team Leader and one or
two, 3-member boat crews supported by a land-based, 2-member mobile laboratory crew. Each boat crew
is headed by a Crew Chief (one of which is the Team Leader), who is captain of the boat and chief scientist,
and, as such, is the ultimate on-site decision maker regarding safety, technical direction, and communication
with the Field Operations Center.

        The desired  qualifications for  the Team Leaders and  Crew Chiefs include a M.S. degree  in
biological/ecological sciences and three years of experience In field data collection activities, or a B.S.
degree and five years experience. The remaining crew members generally are required to hold B.S. degrees
and, preferably, at least one year's experience.

        Prior to the actual sample collection period, each  crew receives formal training and must undergo
a fairly elaborate check-out procedure. Both classroom and "hands-on" training are coordinated by staff
members at the Louisianian Province Field  Operations Center at ERL-GB; these personnel have extensive
experience instructing field technicians in routine sampling operations (e.g., collection techniques, small boat
handling, etc.). The expertise of the on-site EMAP staff is supplemented by local experts in such specialized
areas as fish pathology, fish identification, field computer/navigation system use, and first aid (including
cardiopulmonary resuscitation (CPR) training). All the sampling equipment (e.g., boats, instruments, grabs,
nets, computers, etc.) Is used extensively during the "hands-on" training sessions, and by the end of the
course, all crews members must demonstrate proficiency in all the required sampling activities.

       Upon completion of the formal crew training session, each crew (boat and mobile laboratory) must
pass a graded field certification exercise (passing score, normalized to per cent > 90%). The exercise, a

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full-scale sampling assignment, will incorporate all elements of field sampling and the associated support
activities of the mobile laboratory crew. The performance of the crew will be graded by a member of the
Province field management team (i.e., the Province Manager, Quality Assurance Coordinator, or the Field
Coordinator). If any deficiencies within a crew are noted, they are remedied prior to field sampling. This is
accomplished by additional training or by changing the crew composition. It is the responsibility  of the
Province QA Coordinator to develop and maintain on permanent file all records related to crew certifications
(e.g., examinations, field and laboratory check-out sheets, grading forms, etc.).

        All aspects of field operations are detailed in the Reid Operations Manual (Macauley 1992),  which
is distributed  to all trainees prior to the training period.  The manual includes a checklist of all equipment,
instructions on equipment use, and detailed written descriptions  of sample collection  procedures.  In
addition, the manual  includes flow charts and a schedule of activities to be conducted at each sampling
location, along with a list of potential hazards associated with each sampling site.
6.2    FIELD QUALITY CONTROL

        Quality control of measurements made during the actual field  sampling period Is accomplished
through the use of a variety of QC sample types and procedures, as described in Sections 4 and 5 of this
document. At least once during each field season, a QA evaluation of each field crew is performed by either
the QAC or the Field Coordinator to insure compliance with prescribed protocols. A standardized checklist,
which is updated annually, will be used to insure comparability and consistency in this process.  Reid crews
will be re-trained whenever discrepancies are noted.

6.3    DATA RECORDING

       On the EMAP-E program, portable field computers are used extensively for data recording in the
field.  However, it is the policy of the program that the primary means of data recording for both field and
laboratory activities will be hand-written hard copies. In the case of field activities, standardized data forms
have been prepared by the information management group; these forms are used as the primary means of

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data recording on board the research vessels. The field crews are responsible for sending the data forms
to the Province Field Operations Center on a continual basis throughout the field season.  At the Field
Operations Center, the forms are copied and the copies stored in a separate location as a means  of
permanent, duplicative archival.  In addition to the standardized data forms, each Crew Chief is required  to
maintain a boat log for recording ancillary information (e.g., boat movements, weather conditions, schedule
of activities, etc.) pertinent to the daily field activities.  These log books also are collected at the end of each
field season and maintained in permanent archival at the Reid Operations Center.

6.4    PREVENTIVE MAINTENANCE

        The importance of proper maintenance of all gear cannot be understated. Failure of any piece  of
major equipment, especially when back-up equipment is unavailable, can result in a significant loss of data.
Maintenance of equipment must be performed at regular intervals, as specified in the Field Operations
Manual  (Macauley 1992).  It is the responsibility of the Team Leader to maintain a logbook of equipment
usage and assure that proper maintenance is performed at the prescribed time  intervals. The equipment
maintenance logbook is examined during field QA visits and at the end of the fiekJ season to insure that
proper procedures have been followed.

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                                      SECTION 7
                           LABORATORY OPERATIONS
7.1    DATA RECORDING

       The EMAP-E program  will enforce a laboratory notebook  policy which requires  all  analytical
laboratories to maintain hard copy records of all information necessary to document the quality of the
resultant data. Examples of such hard copy records include, but are not limited to, notebooks, log books,
data forms, instrumental outputs, etc.  Laboratory personnel are expected to follow Good Laboratory
Practice in the maintenance and archival of these hard copy records.  Each laboratory will be required to
make all pertinent records available for review during QA audits and/or in  response to requests from the
Province Manager.
7.2    LABORATORY PERSONNEL, TRAINING, AND SAFETY

       This section addresses only general laboratory operations, while specific QA/QC requirements and
procedures are presented in sections 4 and 5.  Personnel in any laboratory performing EMAP analyses
should be well versed in standard safety practices; it is the responsibility of the laboratory manager and/or
supervisor to  ensure that safety training  is mandatory for all laboratory  personnel.   The laboratory is
responsible for maintaining a current safety manual in compliance with the Occupational Safety and Health
Administration (OSHA) regulations, or equivalent state or local regulations. The safety manual should be
readily available to laboratory personnel.  Proper procedures for safe storage, handling and disposal of
chemicals should be followed at all times; each chemical should be treated as a potential health hazard and
good laboratory practices should be implemented accordingly.

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7.3    QUALITY CONTROL DOCUMENTATION

       In each laboratory, the following EMAP-Estuaries documents must be current and available:

       o      Laboratory Methods  Manual  -  A  document  containing detailed instructions about
              laboratory and Instrument operations (U. S. EPA,  in preparation).

       o      Quality Assurance Project Plan - A document containing clearly defined laboratory QA/QC
              protocols (this document).

       In addition to the official EMAP-E documents,  each laboratory should maintain the following:

       o      Standard  Operating Procedures (SOPs)  - Detailed instructions for performing routine
              laboratory procedures, usually written  in "cookbook" format  In contrast to the Laboratory
              Methods Manual, SOPs offer step-by-step instructions describing exactly how the method
              is implemented in a particular laboratory.

       o      Instrument performance study information  -  Information on instalment baseline noise,
              calibration standard response, precision as a function of concentration, detection limits, etc.
              This information usually is recorded in logbooks or laboratory notebooks.

7.4    ANALYTICAL PROCEDURES

       Complete and detailed procedures for processing and analysis of samples in the field and laboratory
are provided in the Reid Operations Manual (Macauley 1992) and the Laboratory Methods Manual (U.S.
EPA, in preparation), respectively, and will not be repeated here.

7.5    LABORATORY PERFORMANCE AUDITS

       Initially, a QA  assistance and performance audit will be performed by QA personnel to determine
if each laboratory effort Is In compliance with the procedures outlined in the Methods Manual and QA Project
Plan and to assist the laboratory where needed.  In some cases, a formal performance evaluation will be

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required (see Section 5) before a laboratory will receive permission from the Province Manager  to begin

processing field samples. Additionally, technical reviews may be conducted by a team composed of the

QA Coordinator and his/her technical assistants. Reviews may be conducted at any time during the scope

of the study, but not necessarily every year.

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                                     SECTION 8
              QUALITY ASSURANCE AND QUALITY CONTROL
            FOR MANAGEMENT OF DATA AND  INFORMATION
 8.1  SYSTEM DESCRIPTION

       The Near Coastal Information Management System (NCIMS) is designed to perform the following
 functions:
       o      document sampling activities and standard methods,
       o      support program logistics, sample tracking and shipments,
       o      process and organize both the data collected in the field and the results generated at
              analytical laboratories,
       o      perform range checks on selected numerical data,
       o      facilitate the dissemination of information, and
       o      provide interaction with the EMAP Central  Information System.

       A complete and detailed description of the NCIMS is provided in Rosen et. al. (1991) and will not
 be repeated here.

 8.2    QUALITY ASSURANCE/QUALITY CONTROL

       Two general types of problems which must be  resolved in developing QA/QC  protocols for
 information and data management are:  (1) correction or removal of erroneous individual values and (2)
 inconsistencies that damage the integrity of the data base. The following features of the NCIMS will provide
 a foundation for the management and quality assurance of all data collected and reported during the life of
 the project.

8.2.1    Standardization

       A systematic numbering system will be developed for unique identification of individual samples,
sampling events, stations, shipments, equipment, and diskettes. The sample numbering system will contain

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codes which will allow the computer system to distinguish among several different sample types (e.g.,
actual samples, quality control samples, sample replicates, etc.). This system will be flexible enough to allow
changes during the life of the project, while maintaining a structure which allows easy comprehension of the
sample type.

        Clearly stated standard operating procedures will be given to the field crews with respect to the use
of the field computer systems and the entry of data in the field.  Contingency plans will also be stated
explicitly in the event that the field systems fail.

8.2.2    Prelabeling of Equipment and Sample Containers

        Whenever possible, sample containers, equipment, and diskettes will be prelabeled to eliminate
confusion in the field. The prelabeling will reduce the number of incorrect or poorly-affixed labels. Packages
with all the required prelabeled sample containers, sample  sheets, and data diskettes will be prepared for
the field crews prior to each sampling event (an event is defined as a single visit by a crew to a sampling
site).  These containers will be called 'station packets".  Each  station packet will have the station number
affixed to  it using both printed and bar code labels.

8.2.3    Data Entry. Transcription, and Transfer

       To minimize the errors associated with entry and transcription of data from one medium to another,
data will be  captured electronically.  When manual entry is required, the data should be entered twice by
different data entry operators and then checked for  non-matches to identify and correct errors. In  many
instances, the use of bar code labels should eliminate the need for manual entry of routine information.

        Each group transmitting data to the information center will be given a separate account on the Near
Coastal VAX 3300.  Standard formats for data transfer will be established by the Information Management
Team. A specific format will be developed for each file type within each discipline.  If data are sent to the
Near  Coastal Information Center in formats other than those specified, the files will  be deleted and the
sending laboratory or agency will  be asked to resubmit the data in the established format

       The  communications protocols used to transfer data electronically will have mechanisms by which

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the completeness and  accuracy of the transfer can be checked.  In  addition, the group sending the
information  should specify the number of bytes and file names of the transferred files.  These data
characteristics should be verified upon receipt of the data. If the file cannot be verified, a new file transfer
should be requested. Whenever feasible, a hard copy of all data should be provided with transfer files.

        The data files transmitted from the field will be fixed-format text files. These files will  be "parsed" by
the system.  The parsing process involves transferring records of similar type into files containing only those
types of records. For example, observation on fish species and size will be copied from the  original log file
transmitted from the field to a "fish" data file. After the records have been  parsed from the field log files, the
individual data files will be checked automatically for erroneous values, as described in the following section.
Records in the field log file which are not entered into the data base (e.g., comments in text form) will be
archived for documentation or future extraction.

8.2.4   Automated Data Verification

        Erroneous numeric data will be identified using automatic range checks and filtering algorithms.
When data fall outside of an acceptable range, they will be flagged in a report for the Quality Assurance
Coordinator (QAC), or his designee. This type of report will be generated routinely and should detail the
files processed and the status of the QA checks.  The report will  be generated both on disk and in hard
copy for permanent filing. The QAC will review the report and release data which have passed the QA check
for addition to the data  base.  All identified errors must be corrected before flagged files can be added to
a data base.   If the QAC finds that the data check ranges are not reasonable, the values can be changed
by written request. The written request should include a justification for changing the established ranges.
If the QAC finds the need for additional codes, they can be entered by the senior data librarian. After such
changes are made, the files may be passed through the QA procedure again.  In the event that the QA
check  identifies Incorrect data,  the QAC will archive the erroneous file and request that the originator
corrects the error and re-transmits the data.

        Data base entn'es which are In the form of codes should be compared to lists of valid values (e.g.,
look up tables) established by experts for specific data types.  These lists of valid codes wM be stored in
a central data base for easy access  by data base users. When a code cannot be verified In the appropriate
look up table, the observation  should be flagged in the QAC report for appropriate corrective action (e.g.,

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update of the look up table or removal of the erroneous code).

8.2.5    Sample Tracking

        Samples collected  in the field will be  shipped  to multiple analytical laboratories.  All  shipping
information required to adequately track the samples (sample numbers, number of containers, shipment
numbers, dates, courier ID numbers etc.) will be transmitted electronically by modem to the Information
Center at the end of each sample  day.  Once the field crew has transmitted the  data, it will be the
responsibility of the data management team to  confirm that the samples arrive at their destination. Each
receiving laboratories will be required, upon receipt of  the samples, to record  and similarly transmit all
tracking information (e.g., sample identification numbers, shipment numbers and the status of the samples)
to the Information Center, using either microcomputers or the VAX. The use of barcode labels and readers
will facilitate this process. The information management team will generate special programs to create fixed
format records containing this information.

8.2.6    Reporting

        Following analysis of the samples, the summary data packages transmitted from the laboratories
will include sample tracking information, results, quality assurance and quality control information,  and
accompanying text. If the laboratory has assigned internal identification numbers to the samples, the results
should include the original sample number and the internal number used by the laboratory. The analytical
laboratories will be responsible for permanent archiving  of all raw data used in generating the results.

8.2.7    Redundancy (Backups!

        All files In the NCIMS will  be backed up regularly. At least one copy of the entire system will be
maintained off-site to enable the information management team to reconstruct the data base  in the event
that one system is destroyed or incapacitated.  In the field, all information will be recorded both on paper
data sheets as well as in the computer.  All Information  saved to the hard drive will also be automatically
copied to a diskette immediately.   In addition, at the end  of each day the field computers will be "equalized"
to assure that the information contained on both are Identical. At this point all data will be contained on the
hard drives of both field computers and on a diskette. At the Louisianian Province Field Operations Center

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at ERL-GB, Incremental backups to removable disk will be performed on all files which have changed on
a daily basis.  In addition, backups of all EMAP directories and intermediate files will be ;>erformed on a
weekly basis to provide a backup in the event of a complete loss of the Field Operations Center facility.

        All original  data files will be saved  on-line for at least two years, after which   ,e files will be
permanently archived on floppy diskette. All original files, especially those containing the raw field data, will
be protected so that they can only be read (i.e., write and delete privileges will be removed from these files).
8.2.8   Human Review

        All discrepancies which are identified by the computer will be documented in hard copy. These
discrepancy logs will be saved as part of the EMAP archive. All identified discrepancies should be brought
to the attention of the QAC or his/her designee, who will determine the appropriate corrective action to be
taken.  Data will not be transferred to the data base until all discrepancies have been resolved by the QAC.
Once data have been entered into the data base, changes will not be made without the written consent of
the QAC, who will be responsible for justifying and documenting the change.  A record of all additions will
be entered into a data set index and kept in hard copy.

        Field data require additional review to assure the absence of transcription errors.  Following the
entry of data into the field computer, it will be the responsibility of the individual crew chiefs to review the
data files and assure that they are error-free. Once this review has occurred, the crew chief will lock* the
file preventing further editing in the field.  Upon return of the data sheets to the Information Center, a 100%
check of the files wiH be performed (I.e., all files will be compared to the paper data sheets to identify
transcription errors  that may not have been detected by the crew chiefs).  Corrections will be made as
necessary and a report generated for the QAC and Information Manager.
8.3     DOCUMENTATION AND RELEASE OF DATA

        Comprehensive documentation of information relevant to users of the NCI MS wfll be maintained and
updated as necessary.  Most of this documentation will be accessible on-line. In data bases which describe

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and interact with the system.  The documentation will include a data base dictionary, access control, and
data base directories (including directory structures), code tables, and continuously-updated information on
field sampling events, sample tracking, and data availability.

       A limited number of personnel will be authorized to make changes to the EMAP-E data base.  All
changes  will be carefully documented and controlled by the senior data librarian.  Data bases which  are
accessible to outside authorized users will be available in "read only* form. Access to data by unauthorized
users will be limited through the use of standard DEC VAX security procedures.  Information on access
rights to  all EMAP-E directories, files, and data bases will be provided to all  potential users.
       The release of data from the NCIMS will occur on a graduated schedule.  Different classes of users
will be given access to the data only after it reaches a specified level of quality assurance. Each group  will
use the data on a restricted basis, under explicit agreements with the Estuaries Task Group. The following
four groups are defined Tor access to data:

       I.      The Louisianian Province  central group, including the Information management team,  the
               field  coordinator, the Province Manager, the QA Coordinator and the field  crew chiefs.

       II.      EMAP-Estuaries primary users - ERL-GB and their contractor personnel, EMAP-E program-
               level  personnel  at ERL-Narragansett,  NOAA  EMAP-E personnel, and  EMAP quality
               assurance personnel.
                                              /
       III.      EMAP data users - All other task groups within  EPA, NOAA, and other federal agencies.

       IV.      General Public - university  personnel, other EPA  offices (includes regional offices), and
               other federal, state, and local governments.
        Prior to release at level IV (general public) all files will be checked and/or modified to assure that
values contain the appropriate number of significant figures. The purpose is to assure that the data released
do not imply greater accuracy than was realized.  This will be especially Important in files where data were
summarized. In such  cases additional figures beyond the decimal point may have been added by the
statistical program during averaging  or other manipulations.  It will be the responsibUity of the QAC  to

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determine the appropriate number of significant figures for each measurement.
        Requests for premature release of data will be submitted to the Information Management Team
through the Program Manager. The senior data analyst and the QAC will determine if the data can be
released.  The final authority on the release of all data is the Technical Director of EMAP-Estuaries.  The
long-term goal for the  Near Coastal Information Management Team will  be to  develop a user interface
through which all data will be accessed. This will improve control of security and monitoring of access to
the data, and it help ensure that the proper data files are being accessed.

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                                       SECTION 9
            QUALITY ASSURANCE REPORTS TO MANAGEMENT
       A quality assurance technical report (or relevant section of the Annual Statistical Summary) will be
prepared by the Province QA Coordinator following each year's sampling efforts. This report will summarize
results for the various quality control samples and assess whether measurement quality objectives for the
various indicators (as described in Sections 4 and 5 of this document) have been met. The Province QA
Coordinator also will assist the EMAP-Estuaries QA Coordinator (i.e., the Resource Group-level QA
Coordinator) in planning QA activities prior to  each  fiscal year.  The EMAP-E  QA Coordinator will be
responsible for documenting this planning information and reporting on each year's QA activities in a Quality
Assurance Annual Report and Work Plan (QAARWP), which will be submitted to the EMAP-E Technical
Director and the EMAP Program QA Coordinator prior to the beginning of each fiscal year.  In addition to
the annual QA technical report, which will likely be incorporated as part of the Province Annual Statistical
Summary, the Province QA Coordinator will report regularly to the Province Manager on an informal basis.
The purpose of this informal reporting, which will take the form  of memos, is to provide the Province
Manager with timely information on QA issues which potentially might affect data quality.

       Within 30 days of each audit (field or laboratory), the QA Coordinator will submit a draft audit report
to the Province Manager and a courtesy copy to the person in charge of the audited entity (e.g., field crew
chief,  laboratory manager, laboratory director, etc.). The Province Manager and the auditee wUI be given
two weeks to provide comments to the QA Coordinator on the draft  audit report.  Following receipt of
comments, the QA Coordinator will issue a final audit report within two weeks. This report will describe the
results of the audit in full detail and note any deficiencies requiring corrective action.  Upon receipt of the
final audit report, the auditee will be given two weeks to submit to the Province Manager a corrective action
plan.  The corrective action plan should be responsive to the audit report and should specify in detail the
actions  and the time table that will be implemented for correcting any deficiencies.   It will  be the
responsibility of the QA Coordinator to monitor the implementation of corrective actions and make regular
progress reports to the Province Manager until the corrective actions are complete.

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                                       SECTION 10

                                      REFERENCES
Cantillo,  A.Y.  1990.    Standard and  Reference Materials for Marine Sciences.   Intergovernmental
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Degraeve, G.M., N. G. Reichenbach, J. D. Cooney, P. I. Feder, and D. I. Mount.  1988.  New developments
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       Toxicol. Hazard Assess., Sparks,  Nev.

Federal Register, Part VIII, EPA, "Guidelines Establishing Test Procedures for the Analysis of Pollutants
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Hamilton,  M. A., R. C. Russo, and R. V. Thurston.  1977. Trimmed Spearman-Karber method for estimating
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Holland, A. F.,  ed. 1990.  Near Coastal Program Plan for 1990: Estuaries.   EPA 600/4-90/033.  U.S.
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Hunt, D. T. E., and A. L Wilson. 1986. The Chemical Analysis of Water General Principles and Techniques.
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Keith, L H., W. Crumett, J. Deegan, Jr.,  R. A. Libby, J. K.  Taylor, and G. Wentler.  1983.  Principles of
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Keith, L H. 1991. Environmental Sampling and Analysis: A Practical Guide. Lewis Publishers, Chelsea, Ml,
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Kirchner,  C. J. 1983. Quality  control In water analysis. Environ.  Sci. and Technol.  17(4):174A-181A.

Lauenstein, G. L in preparation. A Compendium of Methods Used in the NOAA National Status and Trends
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Macauley, J.   1992.   EMAP-Estuaries  1992 Louisianian  Province  Field  Operations  Manual.   U.S.
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Plumb, R.  H., Jr. 1981.  Procedures for handling and chemical analysis of sediment and water samples.
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       Station, Vicksburg, MS.  471 pp.

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Rosen, J. S., H. Buffum, J. Beaulieu, and M. Hughes. 1991. Information Management Plan for the EMAP-
       Near Coastal Program. U.S. Environmental Protection Agency, Environmental Research Laboratory,
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Stanley, T. W., and S. S. Verner.  1983.  Interim Guidelines and  Specifications for Preparing Quality
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Stanley, T. W., and S.  S. Verner.  1985.  The U. S.  Environmental Protection Agency's quality assurance
       program, pp 12-19 In: J. K. Taylor and T. W. Stanley (eds.).  Quality Assurance for Environmental
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       Pennsylvania.

Taylor, J.  K.   1987.  Quality Assurance  of  Chemical Measurements.  Lewis Publishers, Inc.,  Chelsea,
       Michigan.  328 pp.

U.S. Environmental Protection Agency, in preparation. EMAP Laboratory Methods Manual: Estuaries.  U.
       S. Environmental Protection Agency, Environmental  Monitoring Systems Laboratory, Office of
       Research and Development, Cincinnati, Ohio.

U.S. Environmental Protection Agency.   1979a.  Methods for chemical analysis of water and wastes.
       EPA-600/4-79/020.  U. S.  Environmental Protection Agency, Environmental Monitoring  Systems
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U.S. Environmental Protection Agency.   I979b.  Handbook  for analytical  quality control in  water and
       wastewater laboratories. U. S. Environmental Protection Agency, Environmental Monitoring and
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U.S. Environmental Protection  Agency.    1989.   Recommended  Protocols for Measuring Selected
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       Estuary Program, Office of Puget  Sound, Seattle, Washington.

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