&EPA
United States
Environmental Protection
Agency
Office of Water
4303T
Washington, DC 20460
EPA-823-R-09-008
Quality Assurance Project Plan for
Data Analysis Activities for the
National Study of Chemical Residues in
Lake Fish Tissue
Prepared for:
Leanne Stahl, National Study Manager
U.S. Environmental Protection Agency, Office of Science and Technology
1200 Pennsylvania Avenue, NW (MC 4305T)
Washington, D.C. 20460
Prepared by:
Tetra Tech, Inc.
Center for Ecological Sciences
400 Red Brook Blvd., Suite 200
Owings Mills, MD 21117
April 2007
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Data Analysis Activities for the
National Study of Chemical Residues in Lake Fish Tissue
Contract No. EP-C-04-030
Work Assignment No. 3-02
Prepared for:
Office of Water, Office of Science and Technology
Standards and Health Protection Division
U.S. Environmental Protection Agency
1200 Pennsylvania Avenue, NW
Washington, D.C. 20460
Prepared by:
Tetra Tech, Inc.
400 Red Brook Boulevard, Suite 200
Owings Mills, MD 21117
April 20, 2007
Revision 0
This quality assurance project plan (QAPP) has been prepared according to guidance provided in EPA Requirements for Quality
Assurance Project Plans (EPA QA R-5. EPA 240 B-01 003, U.S. Environmental Protection Agency, Office of Environmental
Information. Washington, DC, March 2001) to ensure that environmental and related data are collected, compiled, and. or
generated for this project are complete, accurate, and of the type, quantity, and quality required for their intended use. Tetra
Tech will conduct work in conformance with the quality assurance program described in the quality management plan for Terra
Tech's Fairfax Group and with the procedures detailed in this QAPP.
Approvals:
Blaine Snyder
Task Leader
Talra Tech, Inc.
Date
Date
Leanne Stahl
Project Manager
£flce of Science and Technology
Tarlgela Cooper Date
Project Officer
U.S. EPA, £$jce of Science and Technology
Tony Olsen
Senior Statistician
U.S. EPA, Office of Research and Development
Esther Peters
Quality Assurance Officer
Tetra Tech, Inc.
Wathen
iing Chief, FSBOB
U.S. EPA, Office of Science and Technology
i
KtfDertSWppen
Quality Assurance Coordinator
U.S. EPA, Office of Science and Technology
Marion Kelly
Quality Assurance Officer
U.S. EPA, Office of Science and Technology
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CONTENTS
Tables iv
Figures iv
Distribution List v
A Project Management
1.0 Project/Task Organization 1
2.0 Problem Definition/Background 4
3.0 Project/Task Description 6
4.0 Quality Objectives and Criteria for Measurement Data 7
4.1 Project Quality Objectives 7
4.2 Measurement Performance Criteria 8
5.0 Special Training Requirements/Certification 12
6.0 Documentation and Records 12
B Data Acquisition
7.0 Sampling Process Design 12
7.1 Sample Type 13
7.2 Sampling Period 14
7.3 Sample Frame 14
7.4 Selection of Lakes for Sampling 15
7.5 Non-target Population, Inaccessible Lakes, and Lakes for Which
Access Is Denied 16
7.6 Reserve Sample of Lakes 17
7.7 Estimates of Uncertainty 17
7.8 Statistical Analysis of Study Data 18
7.8.1 Estimating the Number of National Lake Fish Tissue Study
Lakes 18
7.8.2 Estimating the Number of Lakes in the Sampled Population 19
7.5.3 Estimating Fish Tissue Concentrations 19
8.0 Sampling Methods 19
9.0 Sample Handling and Custody Requirements 20
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10.0 Analytical Methods Requirements 20
11.0 Quality Control Requirements 20
12.0 Instrument/Equipment Testing, Inspection, and Maintenance Requirements 20
13.0 Instrument Calibration and Frequency 20
14.0 Inspection/Acceptance Requirements for Supplies and Consumables 21
15.0 Data Acquisition Requirements (Non-direct Measurements) 21
16.0 Data Management 21
C Assessment/Oversight
17.0 Assessment and Response Actions 22
18.0 Reports to Management 22
D Data Validation and Usability
19.0 Data Review, Validation, and Verification Requirements 23
20.0 Validation and Verification Methods 23
21.0 Reconciliation with Data Quality Objectives 24
Literature Cited 25
Appendices
A Target Lakes
B Input Data File Example (A Portion of Year 4 Data from Rhode Island)
C Electronic Data Deliverable Data Dictionary
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TABLES
1 Time Line of Project Milestones and Associated Data Analysis Activities 7
2 Numbers of Lakes by Size Category in Sample Frame (Based onRF3) 15
3 Number of Lakes Selected for Sampling by Size Category and Panel 16
4 Number of Lakes (by Size Category and Panel) Selected as a Reserve Sample 17
FIGURES
1 Organizational Diagram for National Lake Fish Tissue Study Data Analysis Tasks 2
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DISTRIBUTION LIST
Tangela Cooper
USEPA/OST (4305T)
1200 Pennsylvania Ave., N.W.
Washington, DC 20460
202/566-0369 (phone)
202/566-0409 (fax)
Neal Jannelle
Computer Sciences Corporation
6101 Stevenson Avenue
Alexandria, VA 22304
703/461-2145 (phone)
703/461-8056 (fax)
Marion Kelly
USEPA/OST (4303T)
1200 Pennsylvania Avenue, N.W.
Washington, DC 20460
202/566-1045 (phone)
202/566-1053 (fax)
Tony Olsen
ORD/NHEERL
Western Ecology Division
200 SW 35th Street
Corvallis, OR 97333-4902
541/754-4790 (phone)
541/754-4716 (fax)
Esther Peters
Tetra Tech, Inc.
10306 Eaton Place, Suite 340
Fairfax, VA 22030
703/385-6000 (phone)
703/385-6007 (fax)
Jennifer Pitt
Tetra Tech, Inc.
400 Red Brook Blvd., Suite 200
Owings Mills, MD 21117
410/356-8993 (phone)
410/356-9005 (fax)
Erin Salo
Computer Sciences Corporation
6101 Stevenson Avenue
Alexandria, VA 22304
703/461-2350 (phone)
703/461-8056 (fax)
Robert Shippen
USEPA/OST (4305T)
1200 Pennsylvania Ave., N.W.
Washington, DC 20460
202-566-0391 (phone)
202/566-0409 (fax)
Elaine Snyder
Tetra Tech, Inc.
400 Red Brook Blvd., Suite 200
Owings Mills, MD 21117
410/356-8993 (phone)
410/356-9005 (fax)
Leanne Stahl
USEPA/OST (4305T)
1200 Pennsylvania Ave., N.W.
Washington, DC 20460
202/566-0404 (phone)
202/566-0409 (fax)
John Wathen
USEPA/OST (4305T)
1200 Pennsylvania Ave., NW
Washington, DC 20460
202/566-0367 (phone)
202/566-0409 (fax)
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A. PROJECT MANAGEMENT
1.0 PROJECT/TASK ORGANIZATION
This Quality Assurance Project Plan (QAPP) describes the quality assurance (QA) and quality
control (QC) activities/procedures that will be used during the data analysis phase of the National
Study of Chemical Residues in Lake Fish Tissue (hereafter referred to as the National Lake Fish
Tissue Study). The purpose of this document is to present the methods and procedures that will
be used for statistical analysis offish tissue data from lakes and reservoirs throughout the
contiguous United States, including the quality assurance procedures that will be employed.
This document addresses only the data analysis effort of the National Lake Fish Tissue Study.
This QAPP was prepared according to guidance presented in the document EPA Requirements
for Quality Assurance Project Plans, EPA QA/R-5 (USEPA 2001). Reference to the QAPP
elements described in the guidance document is included herein. The sample collection
methods, procedures and protocols follow the guidelines and recommendations of Guidance for
Assessing Chemical Contaminant Data for Use in Fish Advisories. Volume I: Fish Sampling
and Analysis, Third Edition (USEPA 2000a).
The project team organization provides the framework for conducting the data analysis task to
meet study objectives. The organizational structure and function also facilitate project
performance and adherence to QC procedures and QA requirements. Key roles are filled by
those persons responsible for ensuring the collection, processing, and analysis of valid data and
for routinely assessing the data for precision and accuracy, as well as the persons responsible for
approving and accepting final products and deliverables. The project and QA personnel include
staff from USEPA, Computer Sciences Corporation, and Tetra Tech, Inc. The project
organizational chart is presented in Figure 1, and includes relationships and lines of
communication among key project team members.
The USEPA Project Manager is Leanne Stahl, who will supervise the assigned project
personnel to provide for their efficient utilization by directing their efforts either directly or
indirectly. As Project Manager she will also have the following responsibilities:
• providing programmatic oversight for statistical analysis offish tissue data,
coordinating the development of the data analysis plan,
• reviewing and approving the data analysis QAPP and other materials developed to
support activities during the data analysis and reporting phase of the project, and
coordinating with contractors to integrate statistical analysis information into final
report development.
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USEPA Office of Science and Technology
Director
Marion Kelly
USEPA QA Manager
Robert Shippen
USEPA QA Coordinator
Leanne Stahl
USEPA Project Manager
Esther Peters
Tetra Tech QA Officer
Blaine Snyder
Tetra Tech Task Leader
Tony Olsen
USEPA Senior Statistician
Sample Control Center
Data Management Team
Key
Project Management
Authority
Lines of Communication
Data Analysis Team
Figure 1. Organizational Diagram for National Lake Fish Tissue Study Data Analysis Tasks.
The USEPA Quality Assurance Manager is Marion Kelly, who will be responsible for
reviewing and approving all Quality Assurance Project Plans (QAPPs). Additional USEPA QA
Manager responsibilities include the following:
• reviewing and evaluating project procedures,
conducting external performance and system audits of the procedures, and
• participating in Agency QA reviews of the study.
The USEPA Quality Assurance Coordinator is Robert Shippen, who will be responsible for
reviewing and approving all Quality Assurance Project Plans (QAPPs). Additional USEPA QA
Manager responsibilities include the following:
resolving project QA issues and
performing internal system audits.
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The Tetra Tech Task Leader is Elaine Snyder, who will participate in study report preparation
and data analysis review processes. Other specific responsibilities of the Task Leader include
the following:
• coordinating project assignments in establishing priorities and scheduling,
ensuring completion of high-quality projects within established budgets and time
schedules,
providing guidance, technical advice, and performance evaluations to those
assigned to the project,
• implementing corrective actions and providing professional advice to staff,
preparing and/or reviewing preparation of proj ect deliverables,
• providing support to USEPA in interacting with the project team (including the
sample control center and project statisticians), technical reviewers, and USEPA
Regions/States/Tribes to ensure technical quality requirements are met in
accordance with project design objectives, and
coordinating with the USEPA Proj ect Manager and proj ect statisticians to
integrate statistical analysis information into final report development.
The Tetra Tech Quality Assurance (QA) Officer is Esther Peters, whose primary
responsibilities include the following:
• monitoring quality control (QC) activities to determine conformance,
• reviewing the QAPP for completeness and noting inconsistencies,
• providing support to USEPA and the Tetra Tech Task Leader in preparation of the
work plan and QAPP and in their distribution, and
approving the QAPP.
The USEPA Senior Statistician is Tony Olsen, whose primary responsibilities include the
following:
developing the data analysis plan in coordination with the USEPA Project
Manager,
performing statistical analysis offish tissue data and/or providing technical
support for data analysis,
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• providing oversight for statistical analysis and support activities of other staff
statisticians on the Data Analysis Team.
• developing statistical analysis summary information for integration into the final
report, and
developing graphics to display results of statistical analysis offish tissue data.
The Sample Control Center Data Management Team comprises data managers and database
specialists from Computer Sciences Corporation, whose primary responsibilities include:
• maintaining the National Lake Fish Tissue Study master database,
developing data packages for delivery to the USEPA Senior Statistician,
• coordinating with the USEPA Project Manager, USEPA Senior Statistician, and
Tetra Tech Task Leader to ensure that technical quality requirements are met for
data packages and data transfers, and
• reviewing data inputs and statistical outputs to verify that the appropriate set of
data was used for analysis, and that the statistical results are reproducible or can
be recreated.
2.0 PROBLEM DEFINITION/BACKGROUND
The USEPA Office of Water conducted a national screening-level investigation in 1987 (USEPA
1992) to determine the prevalence of selected bioaccumulative pollutants in fish and to correlate
elevated fish tissue contaminant levels with pollutant sources. Gamefishes and bottom-dwelling
fishes were collected from 388 locations across the country thought to be influenced by various
point and nonpoint sources. These fish tissue samples were analyzed to determine levels of 60
target analytes, including dioxins and furans, PCBs, pesticides and herbicides, mercury, and
several other organic compounds. Results of the 1987 study indicated that target analytes were
present in fish tissue at many of the sampling sites, and some of the contaminants (e.g., PCBs,
dieldrin, mirex, and combined chlordane) occurred at levels posing potential human health risks.
The Office of Science and Technology (OST) within the Office of Water is conducting a new
four-year national study of chemical residues in fish tissue, which is designed to expand the
scope of the 1987 study. In October 1998, USEPA convened a two-day workshop of more than
50 scientists from state, federal, and tribal agencies to obtain technical input on sampling design,
target analytes, sampling methods and data management. Input from scientists at the workshop
and other technical experts that participated in numerous study planning meetings was used to
develop a final study design (USEPA 1999). The contemporary study is statistically designed
and will provide screening-level data on fish tissue contaminants from a greater number of
waterbodies than were sampled in 1987.
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This study broadens the scope of the 1987 study (USEPA 1992), which focused on chemical
residues in fish tissue near point source discharges. The new study will:
• provide information on the national distribution of selected persistent,
bioaccumulative, and toxic (PBT) chemical residues in gamefish and bottom-
dwelling fish in lakes and reservoirs of the contiguous United States (excluding
the Great Lakes and the Great Salt Lake),
• include lakes and reservoirs selected according to a probability design,
• involve the collection offish from those randomly selected lakes and reservoirs
over a four-year survey period (2000-2003),
not be used to set fish consumption advisories; however, states and Native
American tribes may choose to initiate a detailed fish study in a particular lake
based on the screening contaminant concentrations provided by the national
study, and
• include the analysis offish tissue for PBT chemicals selected from USEPA's
multimedia candidate PBT list of 451 chemicals and from a list of 130 chemicals
from several contemporary fish and bioaccumulation studies. A final target
analyte list of 268 PBT chemicals (including breakdown products and PCB
congeners) was compiled based on input from study design workshop participants
and a review team of analytical experts convened in October 1998 and March
1999, respectively. The final statistical year offish tissue samples is also being
analyzed for polybrominated diphenyl ethers (PBDEs).
Lakes and reservoirs were chosen as the target population because they:
are accumulative environments where contamination is detectable,
• provide important sport fisheries nationwide, and
offer other recreational (non-fishing) access and opportunities.
Lakes and reservoirs are the focus of this study rather than other waterbody types because:
Fish consumption advisories represent 35% of the Nation's total lake acres (plus
100% of the Great Lakes), compared to 24% of the Nation's total river miles
(USEPA 2004). [Note: The Great Lakes will not be included in this study because
substantial fish tissue contaminant information is available and continues to be
collected in ongoing Great Lakes monitoring programs.]
• Estuaries are currently being studied by USEPA's Environmental Monitoring and
Assessment Program (EMAP). EMAP has sampled fish from East, West, and
Gulf Coast estuaries as part of their National Coastal Assessment.
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The specific objective of the new National Lake Fish Tissue Study is to estimate the national
distribution of the mean levels of selected persistent, bioaccumulative, and toxic chemical
residues in fish tissue from lakes and reservoirs of the contiguous United States.
In so doing, the study will provide the following types of information:
information about persistent, bioaccumulative, and toxic chemicals (PBTs) for the
Agency's PBT Chemical Program that addresses the following objective:
— The PBT Chemical Program seeks to identify areas of concern for human
and/or ecological health. Study offish tissue may reveal where PBTs not
previously considered a problem are present at levels of concern.
data to answer important questions concerning the national occurrence of fish
tissue contamination, such as the following:
— What is the national extent of selected chemical contaminants in fish from
lakes and reservoirs of the contiguous United States (excluding the Great
Lakes)?
— Are contaminant levels in fish high enough to warrant further
investigation?
3.0 PROJECT/TASK DESCRIPTION
The study design reflects the study goal and objectives defined by USEPA. The study goal can
be stated simply — to determine the extent to which fish in waters of the United States are
contaminated with persistent, bioaccumulative, and toxic chemicals (PBTs). The project field
sampling tasks, methods, and procedures are presented and discussed in the Sample Collection
Activities QAPP for the National Lake Fish Tissue Study (USEPA 2000b). The Analytical
Activities QAPP (USEPA 2000c) discusses the following study topics and tasks: sample
preparation, compositing, and homogenization; target analytes; analytical methods; and chemical
analysis offish tissue samples. Sample collection and analytical activities have been completed,
and subsequent data analysis tasks are presented in this document.
Full implementation of the study (i.e., sample collection) began in 2000 and ended in the winter
of 2003 (Table 1). Review offish tissue analysis results was completed in April 2005.
Statistical analysis activities began in mid-2005, as the complete cumulative data set (i.e., all
years of validated fish tissue data) was released from the analytical laboratories and Sample
Control Center. Results of the statistical analysis of the fish tissue data will be presented in the
final study report, which is scheduled to be released in September 2007.
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Table 1. Time Line of Project Milestones and Associated Data Analysis Activities.
Activities and
Milestones
(1999 - 2007)
1999
J
A
S
O
N
D
Sample Collection
Activities QAPP
and Field Sampling
Plan development
Orientation for
sampling and field
QC personnel in
EPA Regions
Sample collection
from target lakes
Fish tissue analysis
and data validation
Statistical analysis
of fish tissue data
Final report
preparation
2000-
J F M A
M
J
2007
J
[2000 only]
[2000 only]
A
S
O
N
D
[2000 through 2003]
[2001 through April 2005]
[May 2005 through February 2007]
[November 2006 through September 2007]
EPA began analyzing fish study data once the full 4-year analytical data set was available. The
data analysis plan focuses on the following core components:
calculation of national ranges, medians, and percentiles for target PBT chemicals
in fish tissue,
• preparation of cumulative distribution function plots for chemicals and composite
types with sufficient data, and
• calculation of estimates of sampling variability based on replicate sample data.
4.0 QUALITY OBJECTIVES AND CRITERIA FOR MEASUREMENT DATA
4.1 Project Quality Objectives
Data of known and documented quality are essential to the success of any monitoring or
sampling program. USEPA recommends the development of Data Quality Objectives for all
environmental data collection activities. DQOs are qualitative and quantitative statements that
clarify the intended use of the data, define the type of data needed to support the decision,
identify the conditions under which the data should be collected, and specify tolerable limits on
the probability of making a decision error due to uncertainty in the data. DQOs are developed by
data users to specify the data quality needed to support specific decisions. Sources of error or
uncertainty for the sampling phase of the program include the following:
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• Sampling error: The difference between sample values and in situ true values
from unknown biases due to collection methods and sampling design,
• Measurement error: The difference between sample values and in situ true values
associated with the measurement process,
• Natural variation: Natural spatial heterogeneity and temporal variability in
population abundance and distribution, and
• Error sources or biases: Associated with compositing, sample handling, storage,
and preservation.
This QAPP addresses only data analysis activities, so the relevant quality objectives are
primarily related to data summary and statistical analysis issues. The DQOs established for the
National Lake Fish Tissue Study can be expressed as a program level goal to estimate the status
(i.e., the proportion of the population that is above or below some level of concern for a
particular chemical) of the population of lakes and reservoirs within the contiguous United
States with 95% confidence. Discussion of conventional data quality indicators, i.e., precision,
accuracy, completeness, representativeness, and comparability, follows in this section. Methods
and procedures described in this document are intended to reduce the magnitude of the sources
of uncertainty (and their frequency of occurrence) by applying the following approaches:
use of standardized, accepted, and published statistical methods and treatments,
• use of tested, peer reviewed, and published statistical analysis software, and
use of experienced statisticians to perform the statistical analysis activities.
4.2 Measurement Performance Criteria
Measurement performance criteria are quantitative statistics that are used to interpret the degree
of acceptability or utility of the data to the user. These criteria, also known as data quality
indicators (DQIs), include the following:
precision,
• accuracy,
• representativeness,
completeness, and
comparability.
Precision
Precision is a measure of internal method consistency. It is demonstrated by the degree of
agreement between individual measurements (or values) of the same property of a sample,
measured under similar conditions. As the analytical testing is beyond the scope of this QAPP,
no specific criteria are required for this parameter. However, sufficient sample volumes (i.e., the
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five-fish composites described in USEPA 2000b) will be collected to allow for the assessment of
precision during analytical laboratory testing (USEPA 2000c).
For this study, all fish in a lake cannot be sampled, and the laboratory analytical process is not
perfect. The combined variability introduced by the sampling at a lake, the compositing offish,
the subsampling of the composite for analysis, and the chemical analysis itself can be considered
the "index" variability. The detection limits and analytical precision are one part of the
analytical process that can be specified ahead of time (however, analytical processes are not part
of this QAPP). The orientation and training of sampling crews, and the process that they use to
collect fish from a lake, can also be standardized. Besides standardizing training, this dimension
of variability cannot be reduced. The general rule of thumb is that if the combined index
variability is less than 10% of the total variability, it will have little impact on the ability to
estimate status. For this study, the best way to develop an estimate of index variability is to
simply revisit a randomly selected subset, 10% of the sites, and repeat the lake sampling
procedure, compositing, and analytical analyses. Sampling teams will obtain replicate fish
samples from 10% of the target lakes and reservoirs during the four-year sampling period,
according to random selection results provided by the USEPA Project Manager.
Accuracy
Accuracy is defined as the degree of agreement between an observed value and an accepted
reference or true value. Accuracy is a combination of random error (precision) and systematic
error (bias), introduced during sampling and analytical operations. Bias is the systematic
distortion of a measurement process that causes errors in one direction, so that the expected
sample measurement is always greater or lesser to the same degree than the sample's true value.
As mentioned previously, analytical testing is beyond the scope of this QAPP. Accuracy criteria
are presented in the QAPP for Analytical Control and Assessment Activities (USEPA 2000c).
Representativeness
Representativeness expresses the degree to which data accurately and precisely represent a
characteristic of a population, parameter, variations at a sampling point, a process condition, or
an environmental condition.
The National Lake Fish Tissue Study probability survey design selects a set of lake objects from
the sample frame (see Section 7.3) to meet the survey design requirements, in particular the
desired sample size. Lake objects may not be sampled in the field for several reasons. First, the
lake object in the sample frame may not meet the definition of a lake given for the National Lake
Fish Tissue Study. For example, it may be a wetland or a saline lake, or it may be a lake but not
have a permanent fish population. These lake objects are classified as "non-target" or NT. A
landowner may not give permission to access the lake. These are classified as "landowner
denial" or LD. In some cases, it may be unsafe or extremely difficult to obtain access to or travel
to the lake. These lakes are classified as "physical barrier" or PB. Both LD and PB lakes are
assumed to be lakes that meet the National Lake Fish Tissue Study lake definition. The
evaluation status is compiled based on information gathered during office evaluation of each lake
and, if necessary, a field visit.
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The evaluation status provides the data necessary to estimate the number of lakes in the
contiguous United States that meet the National Lake Fish Tissue Study lake definition. It is also
used to estimate the number of lakes that one would expect to be unavailable due to landowners
denying access or no physical access.
The survey design assigns a weight to each lake object. These weights must be used in the
statistical analyses to estimate mean concentrations for all lakes in the contiguous United States.
The weights are in units of numbers of lakes, e.g., a weight of 2.28 means that the concentration
data from the sampled lake represents the concentration that would be observed in 2.28 lakes.
The weights differ by lake area classes used in the survey design. The weight assignments
assume that the survey will be implemented as planned, i.e., that 900 lakes would be evaluated
for potential field sampling. A design is rarely implemented as planned. For example, if 1000
lakes have to be evaluated to identify 500 lakes that meet the National Lake Fish Tissue Study
lake definition, are available to sample due to permission from landowners, and are physically
accessible, then the design is not implemented as planned. Consequently, the weights must be
re-calculated, i.e., adjusted to account for the evaluation of 1000 lakes.
The study plan states that when an additional lake is required, the next lake in the oversample list
of lakes will be used (Section 7.6). Under this provision, a single national weight adjustment is
required. In addition, the total number of lake objects for each of the six lake area categories
used in the design can be summarized from the sample frame. This information, along with the
actual number of lake objects evaluated in each lake area category, is used to adjust the weights.
The adjusted weight for a lake area category is the number of lakes in the sample frame divided
by the number of lakes evaluated. The result is then assigned to each lake evaluated within that
area category. The sum of the weights for all lakes evaluated will equal the total number of lake
objects in the sample frame.
The representativeness goal will be satisfied by using qualified and experienced statisticians for
designing the probability survey, assigning weights to each lake object, and adjusting weights (as
needed). The USEPA Project Manager will ensure that the data are collected, reviewed,
validated, and verified as specified for the study (USEPA 1999, USEPA 2000b, and USEPA
2000c) and that the complete four-year analytical dataset is delivered to the USEPA Senior
Statistician.
Completeness
Completeness is defined as the percentage of measurements made that are judged to be valid
according to specific criteria and entered into the data management system. To optimize
completeness, every effort is made to avoid sample and/or data loss. Refer to USEPA (2000b)
for a complete description of completeness objectives for the National Lake Fish Tissue Study.
Completeness, in the case of this project, is the number of valid samples collected relative to the
number of samples that are planned to be collected. The completeness goal for this project is
90%. The completeness goal is achieved when 90% or more of the available samples from the
final list of target lakes found to contain target fishes are collected and shipped with no errors in
documentation or sample handling procedures. All 1,003 samples collected and shipped
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throughout the four years were received frozen and in good condition by the sample preparation
laboratory.
Comparability
Comparability is an expression of the confidence with which one data set can be compared with
another. Comparability is dependent on the proper design of the sampling program and on
adherence to accepted sampling techniques, standard operating procedures, and quality assurance
guidelines. For the National Lake Fish Tissue Study, comparability of data will be accomplished
by standardizing the sample collection and handling methods, training field participants,
providing consistent sampling materials, using approved analytical methods, using consistent
laboratories for analyses for the duration of the study, and applying a tested and reproducible
statistical design:
All samples were collected and prepared for shipment using consistent sampling
methods and materials for all field teams across the country, according to standard
operating procedures contained in the Quality Assurance Project Plan for Sample
Collection Activities for a National Study of Chemical Residues in Lake Fish
Tissue (USEPA 2000b). These procedures are consistent with the
recommendations of USEPA's Guidance for Assessing Chemical Contaminant
Data for Use in Fish Advisories, Volume 1: Fish Sampling and Analysis, Third
Edition (USEPA 2000a).
• All field personnel involved with sampling had adequate training and appropriate
experience, and project orientation workshops were conducted in 10 EPA Regions
for all participating state partners.
• All chemical analyses were based on published, EPA-approved analytical
methods (detailed in USEPA 2000c). A single set of methods was used for each
target chemical, and was applied consistently throughout the four years of study.
Additionally, laboratories were assigned a specific group of chemicals for
analysis, and those laboratories, chemicals, and methods remained consistent for
the duration of the study.
The probability-based sample design is similar to that of EPA's Environmental
Monitoring and Assessment Program (EMAP). The statistical procedure used to
estimate the total from an unequal probability sample of lakes is described
explicitly in Diaz-Ramos et al. (1996), and the associated variance estimates
follow Stevens and Olsen (2003). Standard, fundamental statistical procedures
will be used to calculate a population range, mean (where appropriate), median,
variance, and percentiles for all target chemicals, and to construct cumulative
distribution function (CDF) plots.
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5.0 SPECIAL TRAINING REQUIREMENTS/CERTIFICATION
Training and project orientation aspects of the National Lake Fish Tissue Study are discussed in
USEPA (2000b). Statisticians participating in the data analysis elements of this study will have
experience with national probabilistic study designs (e.g., EMAP experience), associated
variance estimates, and applicable statistical analysis software (e.g., R, S-Plus, or S-Plus
Professional).
6.0 DOCUMENTATION AND RECORDS
Thorough documentation of all sample collection and handling activities is necessary for proper
processing in the laboratory and, ultimately, for the interpretation of study results. A complete
description of National Lake Fish Tissue Study documentation and record keeping is included as
part of the Sample Collection Activity QAPP (USEPA 2000b), and the Analytical Control and
Assessment Activity QAPP (USEPA 2000c). Once analytical data has passed all internal review
procedures at each laboratory, data are proofed and verified by the Sample Control Center. At
the direction of the USEPA Project Manger, Sample Control Center data managers maintain a
project database, and they prepare and transfer data submission packages (Appendix B) to the
USEPA Senior Statistician. Additional information on data transfer and acquisition and an
Electronic Data Deliverable Data Dictionary are provided in Section 15.0 and Appendix C,
respectively. Field data files will be retained by Tetra Tech (the Field Support Contractor)
(USEPA 2000b) and analytical data files will be retained by Computer Sciences Corporation (the
Sample Control Center) (USEPA 2000c) after all data are uploaded to EPA's STORET Data
Warehouse. All documents, records, and data files associated with data analysis activities are to
be retained and archived by the statistical analysis team (USEPA Office of Research and
Development, Corvallis, Oregon) following completion of the project, as directed by the USEPA
Project Manager. Tetra Tech, CSC, and ORD will provide copies of all critical program and data
files to the USEPA Project Manager at the end of the project.
B. DATA ACQUISITION
7.0 SAMPLING PROCESS DESIGN
The objective of the National Lake Fish Tissue Study is to estimate the national distribution of
the mean levels of selected persistent, bioaccumulative, and toxic chemical residues in fish tissue
from lakes and reservoirs of the contiguous United States.
In so doing, the study will provide the following types of information:
• information about persistent bioaccumulative toxic chemicals (PBTs) for the
Agency's PBT Chemical Program, and
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• data to answer important questions concerning the national occurrence of fish
tissue contamination.
An unequal probability sample design was applied to address the study objectives. Probability
sampling provides the basis for estimating resource extent and condition, for characterizing
trends in extent or condition, and for representing spatial pattern, all with known certainty. A
probability sample has some inherent characteristics that distinguish it from other samples: first,
the population being sampled is explicitly described; second, every element in the population has
the opportunity to be sampled with known probability; and third, the selection is carried out by a
process that includes an explicit random element. A probability sample from an explicitly
defined resource population is a means to certify that the data collected are free from any
selection bias, conscious or not. This probability sample is an essential requirement for a
program such as the National Lake Fish Tissue Study that aims to describe the condition of
national resources.
For the purposes of this study design, the target population is all lakes and reservoirs within the
contiguous United States, excluding the Laurentian Great Lakes and the Great Salt Lake. This
study defines a lake as a permanent body of water of at least one hectare (2.47 acres) in surface
area with a minimum of 1,000 m2 of open (unvegetated) water and a minimum depth of one
meter. The lakes in this study must also have a permanent fish population. A total of 500
locations were sampled over the course of four years.
7.1 Sample Type
To meet the study objectives, the National Lake Fish Tissue Study includes composite sampling
offish fillets for predator/gam efish species and whole fish for bottom-dwelling species from
each sample lake. Five individuals per composite were targeted, all of which had to be large
enough to provide sufficient tissue for analysis of the group of target analytes. It was determined
that at least 560 grams of edible tissue for predators, and 560 grams of total body tissue for
bottom dwellers, would be required from the composites to allow for analysis of all target
analytes. Based on the recommendations of USEPA's Guidance for Assessing Chemical
Contaminant Data for Use in Fish Advisories, Volume 1: Fish Sampling and Analysis, Third
Edition (USEPA 2000a), fish used in a composite sample must meet the following criteria:
all be of the same species,
• satisfy any legal requirements of harvestable size or weight, or at least be of
consumable size if no legal harvest requirements are in effect,
• be of similar size so that the smallest individual in a composite is no less than
75% of the total length of the largest individual,
be collected at the same time (i.e., collected as close to the same time as possible
but no more than 1 week apart) [Note: This assumes that a sampling crew was
unable to collect all fish needed to prepare the composite sample on the same day.
If organisms used in the same composite are collected on different days (no more
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than 1 week apart), individual fish will be frozen until all the fish to be included
in the composite are available for delivery to the laboratory.], and
• be collected in sufficient numbers (five per composite) and of adequate size (five
harvestable size adult specimens that collectively will provide greater than 560
grams of edible tissue for predators, and 560 grams of total body tissue for
bottom-dwellers) to allow analysis of recommended target analytes.
Individual organisms used in composite samples must be of the same species because of notable
differences in the species-specific bioaccumulation potential. Accurate taxonomic identification
is essential in preventing the mixing of closely related species with the target species. Under no
circumstance should individuals from different species be used in a composite sample.
7.2 Sampling Period
Field sampling was conducted during the period when water and weather conditions were
conducive to safe and efficient field sampling, and when the target species are most frequently
harvested by anglers. For most inland freshwaters, the most desirable sampling period is from
late summer to early fall, since lipid content is usually highest and water levels are usually
lowest at that time. Where possible, sampling should not occur during the spawning period of
the particular target species being sought. With these recommendations in mind, and considering
the geographic extent of the study area (i.e., range of latitudes and longitudes) the field sampling
period was scheduled to begin in August and last through November (and possibly into January
or February in warmer regions). Any adjustments to this schedule had to be approved by the
USEPA Project Manager.
7.3 Sample Frame
For the purposes of this study, the target population is all lakes and reservoirs within the
contiguous United States, excluding the Laurentian Great Lakes and the Great Salt Lake. For
this study, a lake is defined as a permanent body of water of at least one hectare (2.47 acres) in
surface area with a minimum of 1,000 m2 of open (unvegetated) water, and a minimum depth of
one meter. The lakes in this study must also have a permanent fish population. Examples of
nonpermanent fish populations are lakes that are subject to annual fish winterkill, or are recently
stocked with fmgerlings. Stocked lakes with adult fish are defined as having a permanent fish
population.
The River Reach File Version 3 (RF3) was used to generate the list of lakes in the target
population. RF3 constitutes the sample frame, and includes GIS coverage for almost all lakes in
the target population for this study. Noted exclusions are newly constructed reservoirs.
To ensure the sample frame included all lakes and reservoirs with an area greater than 5,000
hectares, a list of such lakes was constructed from multiple sources. The list was sent to USEPA
Regional Offices, and subsequently to each state, to verify that each lake on the list was greater
than 5,000 ha and to add any lakes greater than 5,000 hectares that were not on the list. The
corrected list of lakes was integrated into the RF3 list of lakes before sample selection was
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initiated. Table 2 summarizes the number of lakes in the sample frame used for sample
selection.
Table 2.
Numbers of Lakes by Size Category in Sample Frame (Based on RF3).
Lake area (ha)
>l-5
>5-10
>10-50
>50-500
>500-5000
>5000
Number of Lakes
172,747
44,996
40,016
11,228
1,500
274
Frequency (%)
63.8
16.6
14.8
4.1
0.6
0.1
Cumulative
Number of Lakes
172,747
217,743
257,759
268,987
270,387
270,761
Cumulative
Frequency (%)
63.8
80.4
95.2
99.3
99.9
100.0
7.4 Selection of Lakes for Sampling
The procedures described by Olsen et al. (1998) were used to select an unequal probability
sample of lakes. The probability of selection for a lake depends on its area as given by RF3. In
Table 3, the expected weight is the reciprocal of the probability of selection (inclusion
probability). The inclusion probability was determined by the goal of obtaining approximately
an equal number of lakes to sample in each size category. A higher percentage of the lakes in the
smaller size categories would include lakes not meeting the target population definition of a lake.
The probability of selection was adjusted so that the smaller size categories had a greater sample
size. No adjustment was required for size categories 50-500 hectares, 500-5000 hectares, or >
5000 hectares. The adjustments for the remaining size categories were as follows: for 1-5
hectares, increase by 40%; for 5-10 hectares, increase by 30%; and for 10-50 hectares, increase
by 20%. These adjustments were based on limited information from the EMAP northeastern
lake survey.
Although it was not a requirement for the statistical survey design, study planners decided to
select the sample by allocating the lakes to be sampled in each year, or "Panel," of the study.
Lakes were assigned to a particular Panel (1 through 4) to maintain the unequal probability
across all sampling years. Each Panel number coincides with the same sampling year. Thus,
Panel 1 lakes should be sampled during sampling Year 1 (1999-2000), Panel 2 lakes should be
sampled in sampling Year 2 (2001), etc. It was recommended that the lakes should be sampled
in the year specified. The advantage of adhering to this approach was that if any year-to-year
differences exist in fish tissue contaminants, then the sample will be balanced across years. In
the event that the study must be stopped before all lakes can be sampled, sampling all lakes from
a subset of the Panels is a legitimate unequal probability sample of all lakes. The expected
weights must be adjusted to account for the Panels not sampled.
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Table 3. Number of Lakes Selected for Sampling by Size Category and Panel.
Lake area
(ha)
>l-5
>5-10
>10-50
>50-500
>500-5000
>5000
Total
Panel 1
39
44
32
34
36
40
225
Panel 2
41
40
47
37
30
30
225
Panel 3
47
47
46
29
31
25
225
Panel 4
47
46
25
34
41
32
225
All Panels
174
177
150
134
138
127
900
Expected
Weight
938.84
261.61
256.51
85.06
11.36
2.21
7.5 Non-target Population, Inaccessible Lakes, and Lakes for Which Access Is Denied
A critical element of the statistical survey design is the determination of the status of each lake in
the sample. This means that each lake is checked to determine if it meets the definition of a lake
for the study (Section 7.3). In many cases, a field visit was not necessary to confirm that the lake
met the definition. In other cases, it was necessary to actually visit the lake to determine if it met
the definition. Regardless, it was essential that a complete record of this information was
reported to the USEPA Project Manager, since this information is required to complete the
survey estimation procedures. Two other situations sometimes occurred that resulted in a lake
not being sampled. First, the lake may be on private land and require landowner permission to
visit the lake. If a landowner refused access to a lake selected for the study, that situation was
documented in reconnaissance files. Second, occasionally a lake may have been physically
inaccessible. If there were logistical or safety constraints that made a lake inaccessible, then the
reason for inaccessiblility was recorded and reported to the USEPA Project Manager and/or the
Tetra Tech Task Leader.
Information that was determined during pre-sampling reconnaissance of each lake included the
following:
Does the lake meet the definition of the target population (Section 7.3)? If the
lake does not meet the definition, what are the reasons? For example:
— lake < 1 ha in surface area
— lake < 1 m depth
— lake < 1000 m2 of open water (unvegetated)
— saline lake with no fish population
— lake has no annual fish population (winterkill lake)
— other (list specific reasons)
Has the landowner denied access to lake? (Record landowner information)
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• Is the lake physically inaccessible during the sampling period of study? If so,
state why.
7.6 Reserve Sample of Lakes
As a contingency, a second sample of lakes was selected as a reserve. Table 4 summarizes the
sample sizes for the reserve sample. This sample could be used if the initial sample was
determined to have a larger than expected number of non-target population lakes, resulting in an
insufficient sample size. Decisions regarding use of the reserve sample of lakes (or subsets of
the reserve sample) were made only by the USEPA Project Manager.
Table 4. Number of Lakes (by Size Category and Panel) Selected as a Reserve Sample.
Lake area (ha)
>l-5
>5-10
>10-50
>50-500
>500-5000
>5000
Total
Panel 1
47
45
36
36
38
23
225
Panel 2
48
52
39
26
29
31
225
Panel 3
48
40
42
40
30
25
225
Panel 4
49
42
41
22
37
34
225
All Panels
192
179
158
124
134
113
900
Expected Weight
938.84
261.61
256.51
85.06
11.36
2.21
7.7 Estimates of Uncertainty
The study will allow the USEPA Office of Water to report on the extent of PBTs in fish tissue in
lakes with known confidence. Therefore, study results should allow statements such as: 35% of
the sampled population of lakes in the U.S. have PBT levels in fish that exceed the criteria of
concern. If the estimate of uncertainty is ± 5%, results would suggest that the proportion of lakes
that are of concern might be as low as 30% or as high as 40%. This estimate of uncertainty is
derived from the fact that a probability sample was used to select the sites to visit. It is this
estimate of uncertainty that should be considered the project level data quality objective (DQO).
Ideally, the required DQO should be determined by those who will use the results, and this DQO
then should be used to drive the details of the study design. However, determination of a DQO is
usually more complex. Frequently, the data users will request a best estimate and some measure
of uncertainty, i.e., loosely translated as an unbiased estimate with reasonable confidence. From
experience, many data users are comfortable with the results when the uncertainty estimate
ranges from ± 2 - 10%.
It is important to consider the basis on which estimates of uncertainty are made. Assume for a
moment that every fish in every lake in the country could be sampled with absolute truth. If that
were possible, an absolute result (concentration) could be developed with no associated
uncertainty. Now assume PBT levels could be measured in every fish with absolute truth, but
not every lake could be visited. Some uncertainty exists in the results because inferences are
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made about all lakes from a sample of lakes. The uncertainty results from the statistical
sampling process, i.e., fish are analyzed from a sample of lakes rather than all lakes. The
uncertainty associated with this process can be roughly estimated by the binomial distribution
equation:
n
where:
SE is the standard error,
p is the proportion of population in exceedance,
and n is the sample size.
For example, if an uncertainty estimate of ± 5% is desired with 95% confidence and it is likely
that the proportion of the population in exceedance is on the order of 0.2, then a sample size of
roughly 256 lakes would be necessary.
To reduce the uncertainty to ± 2% would require a sample size of about 1,600 lakes. In this
study, the budget has set a fixed sample size of 500 lakes, which would result in an uncertainty
of roughly ± 3.6% with 95% confidence for the national estimate. As the sample size decreases
for subpopulation estimates, the uncertainty in the subpopulation estimates will increase. For
example, if the sample size for a subpopulation of lakes is 150, then the uncertainty would be
± 6.5%.
7.8 Statistical Analysis of Study Data
The National Lake Fish Tissue Study uses a probability survey design with unequal probability
of selection based on lake area. The study objectives require estimates for the national
distribution of the mean levels of 268 persistent, bioaccumulative, and toxic (PBT) chemicals in
fish tissue from lakes and reservoirs of the contiguous United States. To calculate these
estimates, the statistical analysis must incorporate survey design elements as well as information
from the field and laboratory operations.
The following steps are essential to the statistical analysis process: (1) compiling evaluation
status for each lake in the study (Section 4.2), (2) adjusting the survey design (sample) weights
based on lake status (Section 4.2), (3) estimating the number of lakes within the contiguous
United States that meet the project definition of a lake (Section 7.0), (4) estimating the number
and proportion of lakes in the sampled population, and (5) estimating the cumulative distribution
and percentile concentrations of the PBT chemicals in fish tissue.
7.8.1 Estimating the Number of National Lake Fish Tissue Study Lakes
The data necessary for estimating the number of lakes are the evaluation status results recorded
for all lake objects evaluated for potential field sampling. Diaz-Ramos et al. (1996) describe the
statistical procedure to use in estimating a total from an unequal probability sample. An
associated variance estimate, termed a local neighborhood variance estimate, is described by
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Stevens and Olsen (2003). Both procedures are available at
http://www.epa.gov/NHEERL/arm/analysispages/software in the R library for probability survey
population estimation (psurvey.library) (Version 2.6) maintained by the USEPA/ORD National
Health and Environmental Effects Research Laboratories (NHEERL), Corvallis, Oregon. In
addition to national estimates, an option exists to complete the same estimates for sub-regions of
the contiguous United States. Although an estimate can be made for any sub-region, unless the
sample size is sufficiently large, the confidence intervals for the estimates may be so large that
the estimate provides little information. Estimates for sub-regions are not planned as part of this
study because of insufficient sample size to develop estimates with reasonable confidence
intervals.
7.8.2 Estimating the Number of Lakes in the Sampled Population
As described earlier, a lake may meet the definition of a National Lake Fish Tissue Study lake,
but it may not be sampled due to landowner denial or physical inaccessibility. In either case, it is
important to estimate the number of lakes meeting the National Lake Fish Tissue Study lake
definition that could be sampled, i.e., the "sampled population." Alternatively, an estimate can
be derived for the number of lakes expected to have landowner access denials and the number of
lakes expected to be physically inaccessible. These estimates use the same procedures referred
to above in Section 7.8.1.
7.8.3 Estimating Fish Tissue Concentrations
If available, both a predator fish composite and a bottom-dweller fish composite were collected
from each lake. Chemical analyses provided tissue concentration data for each composite and all
target chemicals. Each chemical and fish composite type constitutes a data set to be used for
estimating the fish tissue concentration for the sampled population of lakes. Each lake also has
an associated adjusted weight calculation. This information will be used to estimate percentile
concentrations for each target chemical, and to estimate the cumulative distribution of tissue
concentrations for the sampled population of lakes. This procedure has been described by Diaz-
Ramos et al. (1996) (Estimation Method 1: Cumulative Distribution Function for Proportion of a
Discrete or an Extensive Resource). Variance estimates will be derived using the local
neighborhood variance estimator described by Stevens and Olsen (2003 and 2004). These
statistical analyses will utilize the R statistical software (R Development Core Team 2004) and
an R contributed library for probability survey population estimation (psurvey.analysis) (Version
2.6) (http://www.epa.gov/NHEERL/arm/analysispages/software). This statistical package was
selected for tissue data analysis because it is readily available, it has robust capabilities, and
statisticians in ORD have extensive experience using this software for analysis of unequal
probability survey data.
8.0 SAMPLING METHODS
Field sampling activities and standard operating procedures for sample collection are outside the
scope of this QAPP. See USEPA (2000b) for sample collection activity details.
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9.0 SAMPLE HANDLING AND CUSTODY REQUIREMENTS
Sample handling and custody procedures are outside the scope of this QAPP. See USEPA
(2000b and 2000c) for description of sample handling and custody requirements.
10.0 ANALYTICAL METHODS REQUIREMENTS
Samples were shipped under chain of custody to locations designated by the USEPA Project
Manager for processing and analytical testing. Sample processing and analytical methods are
outside the scope of this QAPP; they are discussed in the Analytical Control and Assessment
Activities QAPP (USEPA 2000c).
11.0 QUALITY CONTROL REQUIREMENTS
Data quality is addressed, in part, by consistent performance of valid procedures documented in
standard operating procedures. It is enhanced by the training and experience of project staff and
documentation of project activities. The National Lake Fish Tissue Study Sample Collection
Activities QAPP (USEPA 2000b) and Analytical Control and Assessment Activities QAPP
(USEPA 2000c) were distributed to all USEPA Regional/State/Tribal Fish Sampling
Coordinators, and other project personnel. This QAPP addresses data analysis activities, and
will be distributed to core project team members and project statisticians. The data analysis team
will be required to read this QAPP, and the USEPA Senior Statistician will verify that each team
member read the QAPP and understood the procedures and requirements.
12.0 INSTRUMENT/EQUIPMENT TESTING, INSPECTION, AND MAINTENANCE
REQUIREMENTS
Instrumentation descriptions and associated testing/inspection/maintenance requirements are
outside the scope of this QAPP. See the National Lake Fish Tissue Study Sample Collection
Activities QAPP and the Analytical Control and Assessment Activities QAPP (USEPA 2000b
and 2000c, respectively) for instrumentation details.
13.0 INSTRUMENT CALIBRATION AND FREQUENCY
Instrument calibration requirements are outside the scope of this QAPP. See USEPA (2000b and
2000c) for calibration details.
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14.0 INSPECTION/ACCEPTANCE REQUIREMENTS FOR SUPPLIES AND
CONSUMABLES
Inspection requirements are outside the scope of this QAPP. See USEPA (2000b and 2000c) for
acceptance requirements for supplies and consumables.
15.0 DATA ACQUISITION REQUIREMENTS (NON-DIRECT MEASUREMENTS)
An analytical data package was prepared by the Sample Control Center and delivered to the
USEPA Senior Statistician. Example pages from the data package are provided in Appendix B.
Data types are discussed in USEPA (2000b) (i.e., supporting field sampling data) and USEPA
(2000c) (i.e., analytical data), and data elements and terms are defined in the Electronic Data
Deliverable Data Dictionary (Appendix C).
16.0 DATA MANAGEMENT
At the direction of the USEPA Project Manager, validated data will be transferred from the
Sample Control Center to the USEPA Senior Statistician. The USEPA Senior Statistician will
serve as the point of contact for data management activities conducted by the Data Analysis
Team at the USEPA/ORD NHEERL, Corvallis, Oregon. The NHEERL information
management system includes both hard copy and electronic means of storing and archiving data.
The central repository for the incoming data is an alpha server system located in Corvallis. The
information management staff are responsible for maintaining the security and integrity of both
the data and the system. National Lake Fish Tissue Study data may be released externally from
the system only with the permission of the USEPA Project Manager.
All data files in the information management system are protected from corruption by computer
viruses, unauthorized access, and hardware or software failures. Data files are accessible only to
information management staff and the Data Analysis Team, and are marked read-only to prevent
corruption by inadvertent editing, additions, or deletions. All data will be stored (and archived)
on redundant systems. This ensures that if one system is destroyed or incapacitated, information
management staff will be able to reconstruct the database. Data files will be retained and
archived by USEPA/ORD NHEERL for storage on a long-term basis after project completion.
Copies of the data files will also be forward to the USEPA Project Manager at the end of the
project for retention with other program and data files.
All data analysis activities (e.g., statistical outputs) will be prepared and reviewed by the USEPA
Senior Statistician before submittal to the USEPA Project Manager (see Sections 19.0 and 20.0).
Subsequent reviews will be conducted by the USEPA Project Manager, the Sample Control
Center Data Management Team, and Tetra Tech. If there is any indication that requirements for
data quality and integrity have not been met, the USEPA Project Manager, Sample Control
Center Data Management Team, and the OST QA Coordinator will work with the USEPA
Senior Statistician to determine the best way to rectify the problem and obtain accurate and
useable output data.
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C. ASSESSMENT/OVERSIGHT
17.0 ASSESSMENT AND RESPONSE ACTIONS
Assessment activities and corrective response actions have been identified to ensure that data
analysis activities are conducted as prescribed. The QA program under which this project
operates includes performance and system audits with independent checks of the statistical
analysis of the original data. These audits could indicate the need for corrective action. The
essential steps in the program are as follows:
• identify and define the problem,
assign responsibility for investigating the problem,
• investigate and determine the cause of the problem,
assign and accept responsibility for implementing appropriate corrective action,
• establish effectiveness of and implement the corrective action, and
verify that the corrective action has eliminated the problem.
Performance audit techniques include checks on the appropriateness of the statistical inputs, the
reproducibility of the results, and sensitivity of the statistical methods. System audits are
qualitative reviews of project activity to check that the overall quality program is functioning and
that the appropriate QC measures identified in this QAPP are being implemented. The OST QA
Coordinator will conduct one internal system audit during the data analysis phase of the project
and report the results to the USEPA Project Manager.
18.0 REPORTS TO MANAGEMENT
The Sample Control Center data managers will provide a statistical QA/QC report to the USEPA
Project Manager following their review of the statistical inputs and outputs (see Section 20.0).
Copies of this report will be submitted to the USEPA Project Manager, the USEPA Senior
Statistician, and the Tetra Tech Task Leader. This Sample Control Center review and report will
be considered as part of the internal system audit. Following completion of the system audit, the
OST QA Coordinator will prepare an Audit Report Form and submit copies to both the USEPA
Project Manager and the USEPA QA Officer.
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D. DATA VALIDATION AND USABILITY
19.0 DATA REVIEW, VALIDATION, AND VERIFICATION REQUIREMENTS
The data validation and verification phase will involve a secondary data QA/QC review, as the
raw data will have already been thoroughly reviewed and validated as described in the Quality
Assurance Project Plan for Analytical Control and Assessment Activities in the National Study of
Chemical Residues in Lake Fish Tissue (USEPA 2000c). The data review, validation, and
verification checks associated with this Data Analysis QAPP will occur in two steps, one on the
data inputs and one on the statistical outputs. The first step will be to verify that the statistical
input (raw data) is correct, and that the appropriate set of data is being used for each analysis.
The second step is to perform QA/QC checks on the statistical output. Sample Control Center
data managers will conduct both steps of review, using input files and output results provided by
the USEPA Senior Statistician. The Sample Control Center will document instances of
agreement and disagreement between the analysis reviews and the original analyses. Additional
data review, validation, and verification procedures may be considered necessary as this phase of
the project evolves. Any additional procedures will be approved by the USEPA Project Manager
and thoroughly documented by the Sample Control Center. The results of the review will be
reported to the USEPA Project Manager, the USEPA Senior Statistician, and the Tetra Tech
Task Leader. Areas of disagreement between the review and the original analyses will be
discussed among, and resolved by, the Sample Control Center, the USEPA Senior Statistician,
and the USEPA Project Manager. The USEPA Project Manager will authorize and direct all
resolved action activities. A report of all review activities and all resolved actions will be
submitted to the USEPA Project Manager (see Section 18.0).
20.0 VALIDATION AND VERIFICATION METHODS
The Sample Control Center will review the data sets used as statistical input to verify that the
correct data set is used for each type of analysis. There are several methods that can be used to
verify that the correct set of data is being applied for each analysis. One option is to count the
number of observations going into the analysis, and then calculate the average of the
observations. This number is then compared to the same counts in the original database.
After this initial check, the Sample Control Center data managers will employ a multi-tiered
approach to verify the statistical analyses that have been performed on the study data set and to
demonstrate the reproducibility of the results. The first step will be to verify that the
methodologies employed are sound and will allow for re-creation of the final results. The data
managers will:
attempt to re-create the original results (e.g., number of responses, percentiles,
confidence limits, etc.)
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National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP Revision 0
Date: 20 April 2007
Page 24 of 26
• verify the appropriate application of results for comparison with thresholds and
screening values (e.g., summed values were used for applicable chemicals, such
as DDT and chlordane)
A second phase will be undertaken if the initial methodology assessment finds alternative
approaches that are more or equally appropriate. This phase will incorporate a sensitivity
analysis to determine the extent that the choice of methodology affects the final results. The
Sample Control Center data managers will ensure that the new methodology is fully documented
and that the final results can be re-created. This may require interaction with the USEPA Project
Statistician and USEPA Project Manager if questions arise that need to be resolved. All actions
requiring resolution will be reported to the USEPA Project Manager (see Section 18.0), and the
USEPA Project Manager will authorize and direct all resolved action activities.
21.0 RECONCILIATION WITH DATA QUALITY OBJECTIVES
Final reconciliation with Data Quality Objectives (DQOs) is outside the scope of this QAPP.
Precision, accuracy, and completeness measures were assessed and compared to performance
criteria immediately following completion of the sample collection and sample analysis phases
of this project. That process represented the final determination of whether the data were of the
correct type and quality to support their intended use for this project. Data Quality Assessment
results are detailed in the Quality Assurance Report for the National Study of Chemical Residues
in Lake Fish Tissue: Year 1 through Year 4 Analytical Data (USEPA 2005).
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National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP Revision 0
Date: 20 April 2007
Page 25 of 26
LITERATURE CITED
Diaz-Ramos, S., D. L. Stevens, Jr, et al. 1996. EMAP Statistical Methods Manual. Corvallis,
Oregon, U.S. Environmental Protection Agency, Office of Research and Development,
NHEERL-Western Ecology Division, ISBN EPA/620/R-96/002.
Olsen, A.R., D.L. Stevens, Jr., and D. White. 1998. Application of global grids in
environmental sampling. Computing Science and Statistics. 30:279-284.
R Development Core Team 2004. R: A language and environment for statistical computing.
Vienna, Austria, R Foundation for Statistical Computing, ISBN 3-900051-07-0,
http ://www.R-proj ect. org.
Stevens, D. L., Jr. and A. R. Olsen. 2003. Variance estimation for spatially balanced samples of
environmental resources. Environmetrics 14: 593-610.
Stevens, D. L., Jr. and A. R. Olsen 2004. Spatially-balanced sampling of natural resources.
Journal of American Statistical Association 99(465): 262-278.
U.S. Environmental Protection Agency (USEPA). 1992. National Study of Chemical Residues
in Fish. U.S. Environmental Protection Agency, Office of Science and Technology,
Washington, D.C. EPA 823-R-92-008.
U.S. Environmental Protection Agency (USEPA). 1999. National Study of Chemical Residues
in Lake Fish Tissue: Study Design. U.S. Environmental Protection Agency, Office of
Science and Technology, Washington, D.C.
U.S. Environmental Protection Agency (USEPA). 2000a. Guidance for Assessing Chemical
Contaminant Data for Use in Fish Advisories, Volume 1: Fish Sampling and Analysis,
Third Edition. U.S. Environmental Protection Agency, Office of Water, Washington,
D.C. EPA-823-B-00-007.
U.S. Environmental Protection Agency (USEPA). 2000b. Quality Assurance Project Plan for
Sample Collection Activities for a National Study of Chemical Residues in Lake Fish
Tissue. U.S. Environmental Protection Agency, Office of Science and Technology,
Washington, D.C. EPA-823-R-02-005.
U.S. Environmental Protection Agency (USEPA). 2000c. Quality Assurance Project Plan for
Analytical Control and Assessment Activities in the National Study of Chemical
Residues in Lake Fish Tissue. U.S. Environmental Protection Agency, Office of Science
and Technology, Washington, D.C. EPA-823-R-02-006.
U.S. Environmental Protection Agency (USEPA). 2001. EPA Requirements for Quality
Assurance Project Plans (EPA/QA/R-5). U.S. Environmental Protection Agency, Office
of Environmental Information, Washington, D.C. EPA/240/B-01/003.
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National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP Revision 0
Date: 20 April 2007
Page 26 of 26
U.S. Environmental Protection Agency (USEPA). 2004. National Listing of Fish Advisories.
Fact Sheet. U.S. Environmental Protection Agency, Office of Water, Washington, D.C.
EPA 823-F-04-016.
U.S. Environmental Protection Agency (USEPA). 2005. Quality Assurance Report for the
National Study of Chemical Residues in Lake Fish Tissue: Year 1 through Year 4
Analytical Data. U.S. Environmental Protection Agency, Office of Science and
Technology, Washington, D.C. EPA 823-R-05-005.
-------
Appendix A
Target Lakes
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National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
Revision 0
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Page A-1 of A-18
State
Lake Name
County
Lake
ID
Statistical
Year
Sampling
Year
Latitude
Deg
Min
Sec
Longitude
Deg
Min
Sec
Lake Area
(ha)
ALABAMA: 16 Lakes
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
AL
Bankhead Reservoir
Candles Lake
Choccolocco Lake
Clark's Lake
Jones Bluff Lake
Lake Martin
Lewis Smith Lake
Payne Lake
Pine Lake
Unnamed lake
Unnamed lake
Unnamed lake
Walter F. George Reservoir
Wheeler Lake
William "Bill" Dannelly Reservoir
Wilson Reservoir
Walker
Talladega
Calhoun
Russell
Lowndes
Tallapoosa
Cullman/Walker/Winston
Hale
Houston
Walker
Monroe
Marshall
Henry/Barbour
Lauderdale
Wilcox
Colbert
0272
1497
1436
0560
1072
0236
0136
0947
0622
0022
0923
0961
0072
0161
0197
0311
R
4
4
2
3
R
1
3
2
1
3
3
1
1
1
R
2003
2003
2003
2001
2002
2003
2000
2002
2001
2000
2002
2002
2000
2000
2000
2003
33
33
33
32
32
33
34
32
31
33
31
34
31
34
32
34
37
10
36
26
23
26
4
53
9
56
26
7
56
39
5
49
17.76
9.84
47.52
55.32
20.4
27.96
51.24
10.68
14.04
55.32
51
22.44
3.84
49.932
53.88
27.084
87
86
85
85
86
85
87
87
85
87
87
86
85
87
87
87
12
23
59
8
45
34
7
26
19
19
17
17
5
2
22
30
11.52
45.24
37.68
22.56
8.64
42.456
55.2
34.08
28.2
53.4
45.96
52.08
48.84
23.208
56.28
14.328
1346.43
25.75
6.97
2.68
5063
15783
8793.13
46.02
3.25
4.37
1.87
3.37
15281.91
27143
4738.41
6272.6
ARIZONA: 3 Lakes
AZ
AZ
AZ
Apache Lake
Lake Havasu
Lake Mohave
Maricopa
Mohave
Mohave
0045
1520
1020
1
4
3
2000
2002
2001
33
34
35
35
30
27
15.36
3.24
14.04
111
114
114
17
21
38
32.28
56.52
10.32
888.11
7223
10446.12
ARKANSAS: 11 Lakes
AR
AR
AR
AR
AR
AR
AR
AR
AR
Beaver Reservoir
Greers Ferry Lake
Horseshoe Lake
Lake Dardanelle
Lake DeGray
Lake Ouachita
Lake Terkington
Millwood Lake
Norfolk Lake
Benton
Cleburne
Crittenden
Logan
Clark
Garland
Arkansas
Little River
Baxter
1493
0571
1522
0247
1449
1371
1396
1398
0143
4
2
4
R
4
4
4
4
1
2002
2000
2001
2003
2002
2002
2002
2002
1999
36
35
34
35
34
34
34
33
36
22
33
55
21
15
37
27
45
24
1.20
39.60
50.16
7.92
25.56
0.84
58.68
2.16
22.68
93
92
90
93
93
93
91
94
92
56
9
20
24
14
23
23
0
14
58.56
47.16
13.20
21.6
14.64
22.20
35.88
14.40
31.20
8310.84
4803
872.26
12640.98
4575.86
15815.64
23.57
9667.69
7546.18
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Page A-2 of A-18
State
AR
AR
Lake Name
Ozark City Lake
ReReg Lake
County
Franklin
Clark
Lake
ID
0497
0623
Statistical
Year
2
2
Sampling
Year
2000
2000
Latitude
Deg
35
34
Min
31
11
Sec
54.84
4.92
Longitude
Deg
93
93
Min
49
6
Sec
57.00
13.32
Lake Area
(ha)
166.23
151.71
CALIFORNIA: 18 Lakes
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
CA
Claire Engle Reservoir
Clear Lake
Crag Lake
El Capitan Reservoir
Finnon Reservoir
Guadalupe Reservoir
Jewelry Lake
Lake Oroville
Lake Thomas Edison
Little Grass Valley Reservoir
Meadow Lake
New Melones Reservoir
Pete's Valley Reservoir
Pine Flat Reservoir
San Leandro Reservoir
San Luis Reservoir
Shasta Lake
Woodward Reservoir
Trinity
Lake
El Dorado
San Diego
El Dorado
Santa Clara
Tuolumne
Butte
Fresno
Plumas
Nevada
Calaveras
Lassen
Fresno
Alameda
Merced
Shasta
Stanislaus
1426
0126
1026
0468
1526
0303
0027
0151
0977
0301
1351
0227
0077
0002
0051
0503
0476
1002
4
1
3
2
4
R
1
1
3
R
4
R
1
1
1
2
2
3
2003
2000
2002
2002
2003
2003
2001
2001
2003
2003
2003
2003
2003
2001
2002
2002
2002
2002
40
39
38
32
38
37
38
39
37
39
39
37
40
36
37
37
40
37
53
1
59
54
47
11
9
34
22
43
24
59
32
52
47
2
49
51
42.36
35.76
27.96
44.64
53.52
33
45.72
47.64
46.92
44.4
41.04
30.84
40.56
28.92
9.96
38.04
31.08
10.44
122
122
120
116
120
121
119
121
118
120
120
120
120
119
122
121
122
120
46
46
9
46
44
52
46
21
58
59
29
30
26
14
6
7
23
50
10.56
13.8
18.36
51.6
54.6
21.72
52.32
35.64
39.36
36.6
34.08
26.64
56.04
5.64
58.68
39
51
58.56
6757.19
15956.2
8.38
589.97
8.58
25.64
2.61
1730.03
755.47
564.03
89.41
726.39
10.86
2336.88
309.21
5214.08
5467.73
718.84
COLORADO: 8 Lakes
CO
CO
CO
CO
CO
CO
CO
CO
Cherry Creek Reservoir
Fuchs Reservoir
Left Hand Valley
Stalker Lake
Trujillo Meadows Reservoir
Turk's Pond
Williams Fork Reservoir
Willow Creek Reservoir
Arapahoe
Rio Grande
Boulder
Yuma
Conejos
Baca
Grand
Weld
1569
0969
0228
0469
0319
0019
0552
0903
4
3
R
2
R
1
2
3
2000
2001
2003
2001
2003
2000
2001
2000
39
37
40
40
37
37
40
40
38
28
5
5
3
29
1
48
22.92
23.16
49.92
7.44
2.88
10.32
3.72
8.64
104
106
105
102
106
102
106
104
51
31
15
16
27
22
12
27
15.48
1.92
56.88
34.68
9
56.28
22.68
47.16
347.28
6.1
45.82
6.63
29.16
22.13
546.12
1.21
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National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
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Date: 20 April 2007
Page A-3 of A-18
State
Lake Name
County
Lake
ID
Statistical
Year
Sampling
Year
Latitude
Deg
Min
Sec
Longitude
Deg
Min
Sec
Lake Area
(ha)
CONNECTICUT: 2 Lakes
CT
CT
Barkhamsted Reservoir
Rainbow Lake
Litchfield
Fairfield
1117
0938
3
3
2001
2001
41
41
58
20
13.44
27.24
72
73
57
29
17.64
45.24
890.54
15.25
FLORIDA: 16 Lakes
FL
FL
FL
FL
FL
FL
FL
FL
FL
FL
FL
FL
FL
FL
FL
FL
Brown Lake
Chipco Lake
Crescent Lake
Eagle Lake
Lake Apopka
Lake Butler
Lake Manatee
Lake Okeechobee
Lake Reedy
Lake Tohopekaliga
Lake Tsala Apopka
Long Pond
Mill Dam Lake
Unnamed lake
Unnamed lake
Unnamed lake
Osceola
Putnam
Putnam/Flagler
Polk
Orange
Union
Manatee
Palm Beach/Hendry
Polk
Osceola
Citrus
Hillsborough
Marion
Walton
Broward
Palm Beach
1425
1060
0260
1575
0500
0060
1050
0150
0975
1000
0100
0600
0135
0498
0625
0325
4
3
R
4
2
1
3
1
3
3
1
2
1
2
2
R
2003
2002
2003
2002
2001
2000
2002
2001
2002
2002
2000
2001
2000
2001
2001
2003
28
29
29
27
28
30
27
27
27
28
28
27
29
30
26
26
9
37
27
59
37
2
28
10
44
13
55
57
10
28
1
35
38.16
42.24
1 1 .628
16.08
8.76
12.12
46.2
30.72
16.8
57
27.228
57.96
49.44
57.36
34.32
5.64
81
81
81
81
81
82
82
80
81
81
82
82
81
86
80
80
25
53
29
46
37
20
18
47
29
22
21
15
50
19
15
11
55.2
31.92
34.296
3.72
19.56
21.84
27
45.6
58.2
20.28
2.52
57.24
37.32
40.44
39.6
10.68
57.37
18.28
6459
259.22
12439.41
362.69
593.3
4830.28
1399.66
7642.87
7733.98
22.39
140.03
1.53
5.43
2.32
GEORGIA: 15 Lakes
GA
GA
GA
GA
GA
GA
GA
GA
GA
Allatoona Lake
Boatright Lake
Demott Lake
J. Strom Thurmond Reservoir
Johnson's Lake
Lake Ashley ("Fishing Lake")
Lake Blue Ridge
Lake Seminole
Lake Sinclair
Bartow/Cherokee
Washington
Colquitt
Columbia
Warren
Carroll
Fannin
Seminole
Putnam
1035
0661
1411
1461
0286
1360
0261
1547
1561
3
2
4
4
R
4
R
4
4
2000
2000
2003
2000
2003
2003
2003
2003
2001
34
32
31
33
33
33
34
30
33
8
48
11
39
21
39
50
47
13
12.48
40.32
7.08
32.04
54.72
14.76
29.04
6.72
50.52
84
82
83
82
82
84
84
84
83
37
42
49
23
38
55
15
54
17
54.84
29.52
23.16
53.88
8.52
21.72
57.6
48.96
8.88
4661.32
12.58
4
10306.7
25.72
6.2
1339.82
5137.63
2070.71
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Date: 20 April 2007
Page A-4 of A-18
State
GA
GA
GA
GA
GA
GA
Lake Name
Qualatchee Lake
Reservoir 29
Unnamed lake
Unnamed lake
Unnamed lake
West Point Lake
County
White
Madison
Elbert
Stewart
Thomas
Troup
Lake
ID
0061
0636
0186
0036
1097
0086
Statistical
Year
1
2
1
1
3
1
Sampling
Year
2002
2001
2000
2003
2003
2002
Latitude
Deg
34
34
34
31
30
33
Min
38
3
5
57
52
3
Sec
56.04
52.56
3.12
21.6
22.08
44.28
Longitude
Deg
83
83
82
84
83
85
Min
48
13
46
40
49
8
Sec
3.6
38.64
48.72
42.24
57.36
0.6
Lake Area
(ha)
15.64
32.62
1.94
1.39
4.77
9215.38
IDAHO: 7 Lakes
ID
ID
ID
ID
ID
ID
ID
Bear Lake
Blackfoot Reservoir
Brownlee Reservoir
Enos Lake #1
Loon Creek Lake #2
Palisades Reservoir
Priest Lake
Bear Lake
Caribou
Washington
Valley
Valley
Bonneville
Bonner
0627
1452
0079
1028
0904
0127
0554
2
4
1
3
3
1
2
2000
2002
2000
2002
2002
2000
2000
42
42
44
45
45
43
48
0
54
40
5
5
14
34
13.32
15.012
32.736
58.452
37.5
36.96
4.368
111
111
117
115
115
111
116
19
35
4
50
55
6
51
58.476
9.672
42.348
48.876
14.808
40.68
27.504
28329
6475.2
6070.5
3.01
2.62
6061.57
9453.8
ILLINOIS: 10 Lakes
IL
IL
IL
IL
IL
IL
IL
IL
IL
IL
Buck Lake
Kincaid Lake
Lake Inverness
Otter Lake
Rend Lake
Shock's Pond
Unnamed lake
Unnamed lake
Unnamed lake
Wolf Lake
De Kalb
Jackson
Cook
Macoupin
Franklin
Rock Island
Williamson
Tazewell
Saline
Cook
0041
1565
0241
0115
1065
0140
0015
0515
1465
0491
1
4
R
1
3
1
1
2
4
2
2000
2002
2003
2001
2001
2000
2000
2000
2002
2001
41
37
42
39
38
41
37
40
37
41
38
49
5
27
4
27
46
35
44
39
51
7.32
39.48
4.32
52.32
17.64
23.88
1.68
13.2
52.2
88
89
88
89
88
90
88
89
88
87
39
28
5
53
58
36
47
35
30
31
36
42.24
3.12
35.16
26.76
11.16
0.6
7.8
28.08
57.72
3.56
972.39
6.57
126.16
832.64
1.67
6.2
17.48
7.87
323
INDIANA: 7 Lakes
IN
IN
IN
IN
IN
Baire Lake
Fox Lake
Geist Reservoir
Hardy Lake
Turtle Creek Reservoir
Putnam
Steuben
Hamilton
Scott
Sullivan
0141
1516
0616
0941
0590
1
4
2
3
2
2000
2003
2001
2002
2001
39
41
39
38
39
43
37
55
46
4
58.8
36.48
41.52
21.36
1.92
86
85
85
85
87
45
1
56
41
31
17.64
24.96
33
20.04
42.96
3.03
53.2
683.06
315.77
605.95
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Page A-5of A-18
State
IN
IN
Lake Name
Unnamed lake
Winona Lake
County
Montgomery
Kosciusko
Lake
ID
1541
0466
Statistical
Year
4
2
Sampling
Year
2003
2001
Latitude
Deg
40
41
Min
2
13
Sec
5.64
22.44
Longitude
Deg
86
85
Min
57
50
Sec
10.8
0.96
Lake Area
(ha)
5.24
216.43
IOWA: 5 Lakes
IA
IA
IA
IA
IA
Diamondhead Lake
Morse Lake
Percival Lake
Saylorville Lake
Unnamed lake
Guthrie
Wright
Fremont
Polk
Wapello
1090
0165
0615
1040
0965
3
1
2
3
3
2002
2000
2001
2002
2002
41
42
40
41
40
32
50
46
45
58
59.28
20.04
37.56
11.52
26.4
94
93
95
93
92
15
41
48
43
22
33.84
41.28
36.72
53.76
25.68
40.03
41.11
6.39
2041.2
12.99
KANSAS: 4 Lakes
KS
KS
KS
KS
Tuttle Creek Lake
Unnamed lake
Unnamed lake
Unnamed lake
Pottawatomie
Jackson
Greenwood
Woodson
0119
1119
0293
1568
1
3
R
4
2000
2002
2003
2003
39
39
37
37
27
30
56
53
25.2
8.64
5.28
13.56
96
95
96
95
42
36
10
36
4.68
3.6
45.84
43.2
2152.55
5.43
1.53
1.81
KENTUCKY: 7 Lakes
KY
KY
KY
KY
KY
KY
KY
Barkley Lake
Green River Lake
Herrington Lake
Lake Cumberland
Unnamed lake
Unnamed lake
Unnamed lake
Lyon
Adair
Boyle
Pulaski
Livingston
Nelson
Fleming
1361
1012
0641
1062
0465
0640
0266
4
3
2
3
2
2
R
2003
2002
2001
2003
2001
2001
2003
37
37
37
36
37
37
38
1
14
41
58
16
47
23
24.24
0.6
6
26.4
55.92
52.08
12.84
88
85
84
84
88
85
83
7
16
42
46
29
38
31
18.48
15.6
52.56
44.76
39.12
50.28
20.64
7.75
3190.89
1084.43
231.04
13.42
2.56
7.11
LOUISIANA: 7 Lakes
LA
LA
LA
LA
LA
LA
LA
Catahoula Lake
Lacdes Allemands
Lake Bistineau
Lake Bussey Brake
Miller's Lake
Salt Lake
Unnamed lake
LaSalle
St. John the Baptist
Webster
Morehouse
Evangeline
Calcasieu
Pointe Coupee
0274
0999
0173
1548
1374
1074
1474
R
3
1
4
4
3
4
2002
2000
1999
2002
2002
2001
2003
31
29
32
32
30
30
30
30
55
26
51
45
15
42
20.34
14.95
17.16
52.20
6.84
23.40
43.20
92
90
93
91
92
93
91
7
34
23
55
21
24
43
30.72
18.05
12.48
44.04
18.00
56.88
56.64
10846
5957.2
6282.91
848.31
1245.69
63.59
16.31
MAINE: 25 Lakes
ME
ME
Chandler Pond
Cuxabexis Lake
Piscataquis
Piscataquis
1460
0660
4
2
2003
2001
46
46
18
6
23.04
22.68
69
69
3
17
46.08
54.24
51.83
247.09
-------
National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
Revision 0
Date: 20 April 2007
Page A-6 of A-18
State
ME
ME
ME
ME
ME
ME
ME
ME
ME
ME
ME
ME
ME
ME
ME
ME
ME
ME
ME
ME
ME
ME
ME
Lake Name
Green Lake
Hadley Lake
Hale Pond
Heald Ponds
Little Pond
Little River Lake
McCurdy Pond
Megunticook Pond
Middle Range Pond
Moose Pond
Moosehead Lake
Mooselookmeguntic Lake
Parker Pond
Peaked Mountain Pond
Pemadumcook Lake
Puffer's Pond
Ragged Lake
Seboomook Lake
Spednik Lake
Stiles Lake
Upper Middle Branch Pond
Wallagrass Lakes
Wood Pond
County
Hancock
Washington
Piscataquis
Somerset
Oxford
Washington
Lincoln
Waldo
Androscoggin
Cumberland
Piscataquis
Oxford
Kennebec
Piscataquis
Piscataquis
Penobscot
Piscataquis
Somerset
Washington
Hancock
Hancock
Aroostook
Somerset
Lake
ID
0566
0917
0285
0042
0192
0516
0642
1366
0617
0217
0492
0667
1067
0935
1041
0242
0210
1560
0966
0166
0092
0635
1442
Statistical
Year
2
3
R
1
1
2
2
4
2
1
2
2
3
3
3
R
1
4
3
1
1
2
4
Sampling
Year
2001
2002
2003
2000
2000
2001
2001
2003
2001
2000
2001
2001
2002
2002
2002
2003
2000
2003
2002
2000
2000
2001
2003
Latitude
Deg
44
44
45
45
44
45
44
44
44
44
45
44
44
46
45
45
45
45
45
44
44
47
45
Min
38
47
48
11
9
9
0
15
1
3
40
53
29
30
41
0
49
54
37
58
52
6
37
Sec
53.88
10.68
36
4.2
11.88
33.84
35.28
46.08
16.32
14.04
43.104
12.48
8.88
27.36
15
56.88
13.08
54
17.76
23.16
34.32
20.16
9.12
Longitude
Deg
68
67
68
69
70
67
69
69
70
70
69
70
70
69
68
69
69
69
67
68
68
68
70
Min
29
26
58
51
35
49
27
6
23
48
43
49
1
5
54
15
22
52
38
0
13
42
16
Sec
53.52
56.04
35.76
48.6
16.44
14.52
11.88
47.52
57.12
17.64
19.092
43.68
49.44
14.64
5.4
37.08
4.08
13.44
32.28
34.2
37.2
51.48
58.44
Lake Area
(ha)
1267.24
680.2
64.84
8.72
10.67
29.41
79.6
573.61
14.61
679.43
30308
6597
611.44
5.01
7453.06
46.36
1046.61
2571.1
5570.94
16.99
103.76
100.43
819.41
MARYLAND: 1 Lake
MD | Deep Creek Lake
Garrett
1439
4
2002
39
30
15.48
79
19
17.4
1449.35
MASSACHUSETTS: 7 Lakes
MA
MA
MA
Bent's Pond
Carbuncle Pond
North Watuppa Pond
Worcester
Worcester
Bristol
0493
0592
0017
2
2
1
2001
2001
2000
42
42
41
31
8
42
37.92
7.08
11.16
71
71
71
59
52
6
55.68
7.32
27
8.72
3.94
673.72
-------
National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
Revision 0
Date: 20 April 2007
Page A-7 of A-18
State
MA
MA
MA
MA
Lake Name
Quabbin Reservoir
Rockwell Pond
Seymour Pond
Westboro Reservoir
County
Worcester
Worcester
Barnstable
Worcester
Lake
ID
0567
1443
0467
0992
Statistical
Year
2
4
2
3
Sampling
Year
2001
2003
2001
2002
Latitude
Deg
42
42
41
42
Min
24
31
43
14
Sec
5.4
37.92
26.04
36.6
Longitude
Deg
72
71
70
71
Min
18
46
5
36
Sec
31.32
9.12
34.08
16.92
Lake Area
(ha)
9535.65
3.68
68.75
1.33
MICHIGAN: 21 Lakes
Ml
Ml
Ml
Ml
Ml
Ml
Ml
Ml
Ml
Ml
Ml
Ml
Ml
Ml
Ml
Ml
Ml
Ml
Ml
Ml
Ml
Burt Lake
Chenango Lake
Cloverleaf Lake
Fire Lake
Glen Lake
Gogebic Lake
Haney Lake
Horseshoe Lake
Houghton Lake
Lake Chapin
Lake Paradise
Lake Roland
Long Lake
Miner's Lake
Norvell Lake
Seven Mile Pond
Torch Lake
Walloon Lake
West Lake
White Lake
Wintergreen Lake
Cheboygan
Livingston
Alger
Baraga
Leelanau
Gogebic
Van Buren
Ogemaw
Roscommon
Berrien
Emmet
Houghton
Kalamazoo
Alger
Jackson
Alpena
Antrim
Emmet
La peer
Oakland
Kalamazoo
0459
1564
0934
0309
1459
1534
0591
0589
0639
0016
0659
0534
1116
0284
0664
0984
0634
0009
0014
0464
0116
2
4
3
R
4
4
2
2
2
1
2
2
3
R
2
3
2
1
1
2
1
2001
2003
2002
2003
2003
2003
2003
2001
2001
2000
2001
2001
2002
2003
2001
2002
2001
2000
2000
2001
2000
45
42
46
46
44
46
42
44
44
41
45
46
42
46
42
45
44
45
43
42
42
27
30
33
29
52
30
15
24
20
55
41
53
11
28
8
5
58
18
5
40
23
35.784
13.68
32.4
57.12
14.88
29.556
8.64
57.96
59.64
37.56
6.72
18.24
41.28
50.52
48.12
48.48
41.52
1.8
56.76
8.76
51.36
84
83
86
88
86
89
86
84
84
86
84
88
85
86
84
83
85
85
83
83
85
39
53
5
11
1
35
7
16
42
20
45
51
31
32
12
30
18
0
24
33
23
55.584
41.28
13.92
29.76
5.16
10.5
29.28
49.8
59.4
52.8
2.52
5.4
14.16
16.8
29.52
34.92
54.72
41.4
53.64
51.48
5.64
6928.25
12.35
4.79
10.83
559.97
5170
11.9
14.45
8067.91
220.36
767.18
107.27
198.23
6.01
12.38
555.78
7503.08
1832.12
1.12
198.12
13.49
MINNESOTA: 58 Lakes
MN
MN
MN
MN
Agate Lake
Bass Lake
Belle Lake
Blind Lake
Crow Wing
Wright
Meeker
Aitkin
0630
0507
1357
1455
2
2
4
4
2001
2001
2003
2000
46
45
44
46
29
19
58
39
45.96
18.12
53.04
0.72
93
94
94
93
54
6
25
44
46.8
7.92
33.24
45.96
65.74
86.47
361.91
119.92
-------
National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
Revision 0
Date: 20 April 2007
Page A-8of A-18
State
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
Lake Name
Cantlin Lake
Cass Lake
Charlotte
Cork Lake
Dead Lake
Diamond Lake
Dick Lake
East Leaf Lake
First Lake
Fish Lake Reservoir
Flat Lake
Florida Lake
Fox Lake
Fox Lake
Hendricks Lake
Hubert Lake
Isabella Lake
Kabekona Lake
Kekekabic Lake
La Salle Lake
Lac La Croix
Lake Carlos
Lake Geneva
Lake Minnetonka
Lake of the Woods
Lake Pepin
Lake Washington
Lake Washington
Lake Winona
Leech Lake
Linwood Lake
Long Lake
County
Sherburne
Beltrami
Wright
Douglas
Otter Tail
Kandiyohi
Cook
Otter Tail
Pine
St. Louis
Becker
Kandiyohi
Becker
Beltrami
Lincoln
Crow Wing
Lake
Hubbard
Lake
Hubbard
St. Louis
Douglas
Freeborn
Hennepin
Lake of the Woods
Goodhue
Le Sueur
Meeker
Winona
Cass
St. Louis
Hubbard
Lake
ID
0033
0205
1508
0257
1431
1382
0085
0906
0633
0605
1506
0957
0081
0655
0457
0155
0985
1480
0035
0005
0485
1532
0207
1032
1430
1457
1057
0307
0932
1055
0130
0031
Statistical
Year
1
1
4
R
4
4
1
3
2
2
4
3
1
2
2
1
3
4
1
1
2
4
1
3
4
4
3
R
3
3
1
1
Sampling
Year
2000
1999
2000
2003
2000
2003
2001
1999
2001
1999
2003
2001
1999
2001
2000
2000
2003
2003
2002
2000
1999
2000
2000
2002
2003
2003
2002
2003
2003
2002
2000
2000
Latitude
Deg
45
47
45
45
46
45
47
46
46
46
46
45
46
47
44
46
47
47
48
47
48
45
43
44
48
44
44
45
44
47
47
46
Min
29
25
9
52
28
10
51
23
18
56
58
14
46
36
29
29
48
10
4
20
17
57
47
54
58
30
15
4
2
9
19
53
Sec
9.24
23.484
3.24
25.68
45.48
59.52
54.72
54.96
52.56
20.76
44.4
10.32
49.8
33.48
43.8
13.92
39.6
0.48
7.68
29.4
33.72
50.76
31.2
34.2
12.072
55.8
15.12
15.6
29.4
20.484
10.92
10.68
Longitude
Deg
93
94
93
95
95
94
90
95
92
92
95
95
95
94
96
94
91
94
91
95
92
95
93
93
95
92
93
94
91
94
92
94
Min
35
31
44
29
44
50
29
25
49
16
39
3
54
50
27
16
17
45
10
9
4
21
16
38
12
18
52
22
39
23
6
59
Sec
13.2
53.94
48.12
2.76
58.2
33.72
39.48
19.92
11.64
25.32
17.28
49.68
30.24
30.48
44.64
7.32
29.04
26.28
26.4
52.92
40.08
22.32
26.76
10.68
13.248
25.56
38.64
20.64
22.32
29.688
20.52
57.84
Lake Area
(ha)
41.26
12050
94.11
41.04
2987.93
626.23
52.8
170.1
31.02
1214.34
741.28
210.53
55.54
63.87
616
510.95
666.76
974.89
690.72
90.11
5768.93
1039.76
693.82
1699.75
384622
5075
582.48
979.68
32.22
44280
2.5
783.5
-------
National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
Revision 0
Date: 20 April 2007
Page A-9 of A-18
State
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
MN
Lake Name
Many Point Lake
Mille Lacs
Moberg Lake
Mora Lake
Mud Lake
Namakan Lake
North Turtle Lake
O'Dowd Lake
Pokegama Lake
Portage Lake
Red Lake
Rice Lake
Rice Lake
Shamineau Lake
Snowbank Lake
South McDougal Lake
Spider Lake
Sturgeon Lake
Vermilion Lake
White Iron Lake
White Sand Lake
Woman Lake
County
Becker
Mille Lacs
St. Louis
Cook
Traverse
St. Louis
Otter Tail
Scott
Itasca
Cass
Beltrami
Stearns
Itasca
Morrison
Lake
Lake
Itasca
Pine
St. Louis
St. Louis/Lake
Crow Wing
Cass
Lake
ID
0481
0933
0530
0010
0905
0110
1380
0182
0055
0280
0980
0157
0255
0908
0235
0460
1530
0183
1110
1010
0083
0180
Statistical
Year
2
3
2
1
3
1
4
1
1
R
3
1
R
3
R
2
4
1
3
3
1
1
Sampling
Year
2001
2003
2001
2001
2002
1999
2001
2000
2000
2003
2002
2000
2003
2002
2003
2000
2003
2000
2002
2001
2000
2000
Latitude
Deg
47
46
46
48
48
48
46
44
47
47
47
45
47
46
47
47
47
46
47
47
46
46
Min
4
14
48
1
19
33
18
44
10
20
57
22
12
15
59
36
29
22
52
53
21
57
Sec
39
17.16
48.96
17.4
45.552
28.512
22.68
28.32
51.6
35.16
43.02
29.64
48.24
13.32
3.48
51.48
27.6
48.72
5.196
53.88
6.48
30.96
Longitude
Deg
95
93
92
90
95
92
95
93
93
94
95
94
93
94
91
91
93
92
92
91
94
94
Min
32
38
54
56
58
49
47
31
34
18
1
36
40
36
25
33
34
45
18
45
17
16
Sec
17.16
35.16
40.32
33.36
18.48
25.932
57.48
0.48
37.2
42.12
30.288
56.52
56.64
1.8
9.12
29.16
36.84
22.32
26.172
13.32
12.48
21.72
Lake Area
(ha)
676.86
51699.73
13.94
94.49
9591
5686
600.51
118.14
6313
605.98
61512.47
617.62
276.63
547.87
1889.88
112.64
546.03
666.38
19875
2404.36
158.52
2395.76
MISSISSIPPI: 9 Lakes
MS
MS
MS
MS
MS
MS
MS
MS
MS
Bailey Lake
Ben Lilly Pond
Enid Lake
Grenada Lake
H Johnson Pond
Hollis Lee's Lake
Lake Lucille
Sardis Reservoir
Unnamed lake
Carroll
Monroe
Yalobusha
Grenada
Yazoo
Claiborne
Lauderdale
Panola
Carroll
0146
1122
0997
1096
0322
0624
0098
0672
1546
1
3
3
3
R
2
1
2
4
2000
2002
2002
2002
2003
2001
2000
2001
2003
33
33
34
33
32
32
32
34
33
28
43
8
49
37
1
34
26
35
37.2
17.4
50.676
54.804
41.16
49.44
30
55.032
58.2
89
88
89
89
90
90
88
89
90
50
42
51
44
28
46
32
42
1
15
40.32
43.452
2.364
49.8
57.36
38.76
46.476
49.44
50.29
4.76
11230
26154
5.53
37
12
23684
8.1
-------
National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
Revision 0
Date: 20 April 2007
Page A-lOof A-18
State
Lake Name
County
Lake
ID
Statistical
Year
Sampling
Year
Latitude
Deg
Min
Sec
Longitude
Deg
Min
Sec
Lake Area
(ha)
MISSOURI: 11 Lakes
MO
MO
MO
MO
MO
MO
MO
MO
MO
MO
MO
Lake Wapapello
Mark Twain Lake
Table Rock Lake
Tressle Hole
Truman Reservoir
Unnamed lake
Unnamed lake
Unnamed lake
Unnamed lake
Unnamed lake
Unnamed lake
Wayne
Rails
Stone
New Madrid
St Clair
Dade
Jasper
Cooper
Polk
Knox
Callaway
0290
1440
0543
1437
1393
0618
1068
0240
0318
1490
1515
R
4
2
4
4
2
3
R
R
4
4
2003
2003
2003
2003
2003
2002
2002
2003
2003
2003
2003
36
39
36
36
38
37
37
38
37
40
38
58
30
33
33
10
22
17
54
46
1
57
3.72
46.44
32.4
12.6
12
33.6
22.92
46.44
16.32
54.12
54.36
90
91
93
89
93
93
94
92
93
92
91
21
42
23
26
34
41
31
47
33
4
58
15.12
36
45.96
58.92
18.84
24
58.08
36.96
17.28
6.96
57.72
2523.23
3551.37
12409.59
9.93
9246.25
3
14.27
4.83
5.54
4.27
9.35
MONTANA: 16 Lakes
MT
MT
MT
MT
MT
MT
MT
MT
MT
MT
MT
MT
MT
MT
MT
MT
Bighorn Lake
Bynum Reservoir
Clear Lake
Cliff Lake
Ennis Lake
Fort Peck Reservoir
Frenchman Pond
Hebgen Lake
Krieder's Pond
Laird Pond
Lake Elwell
Lake Koocanusa
Leigh Lake
Rape Creek Reservoir
Upper Cold Lake
Upper Two Medicine Lake
Big Horn
Teton
Mineral
Flathead
Madison
Valley
Phillips
Gallatin
Garfield
Carter
Liberty
Lincoln
Lincoln
Beaverhead
Missoula
Glacier
0053
1429
1104
1079
1504
0084
1434
0952
0104
0178
0029
0604
1029
0153
0454
0254
1
4
3
3
4
1
4
3
1
1
1
2
3
1
2
R
2001
2003
2001
2002
2003
2000
2003
2002
2000
2000
2000
2002
2002
2000
2001
2003
45
47
47
48
45
47
48
44
47
45
48
48
48
44
47
48
10
56
16
9
25
44
42
47
7
37
22
35
13
59
33
27
14.16
45.6
9.12
46.08
51.24
0.6
19.8
13.02
47.28
24.24
39
11.04
15.6
50.28
25.2
54.72
108
112
115
113
111
106
107
111
107
104
111
115
115
113
113
113
6
26
24
53
40
44
13
14
28
40
12
14
39
11
54
27
14.04
0.6
24.84
22.92
55.56
36.6
33.24
58.74
39.36
28.92
15.84
5.28
55.08
42
4.32
27
6942.75
1295.69
3.09
9.3
1490.89
98766.25
231.25
4856.25
5.88
7.75
1075.54
11462.51
52
9.64
22.84
61.42
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National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
Revision 0
Date: 20 April 2007
Page A-ll of A-18
State
Lake Name
County
Lake
ID
Statistical
Year
Sampling
Year
Latitude
Deg
Min
Sec
Longitude
Deg
Min
Sec
Lake Area
(ha)
NEBRASKA: 5 Lakes
NE
NE
NE
NE
NE
Enders Reservoir
Harlan County Reservoir
Jeffrey Reservoir
Lake McConaughy
Lake Minatare
Chase
Harlan
Lincoln
Keith
Scotts Bluff
1444
0244
0494
1403
0453
4
R
2
4
2
2002
2003
2000
2002
2000
40
40
40
41
41
25
3
56
15
56
55.92
30.6
27.6
1.08
1.32
101
99
100
101
103
33
18
24
50
29
14.04
12.96
34.2
53.16
42
652.43
5185.54
226.1
11464.25
784.3
NEVADA: 4 Lakes
NV
NV
NV
NV
Chimney Reservoir
Lake Mead
Pyramid Lake
Ruby Lake
Humboldt
Clark
Washoe
Elko
1451
0652
0902
0926
4
2
3
3
2002
2000
2003
2001
41
36
40
40
24
16
1
10
52.56
57.36
19.2
20.64
117
114
119
115
9
22
33
28
11.88
23.16
11.88
10.2
880.93
39372.55
44232.8
38.43
NEW HAMPSHIRE: 5 Lakes
NH
NH
NH
NH
NH
Big Diamond Pond
Horn Pond
Lake Winnipesaukee
Little Island Pond
Newfound Lake
Coos
Carroll
Carroll/Belknap
Hillsborough
Grafton
0292
0317
0167
0243
0517
R
R
1
R
2
2003
2003
2000
2003
2001
44
43
43
42
43
57
33
36
43
39
11.16
39.6
9.36
39.72
34.2
71
70
71
71
71
18
57
20
17
46
44.28
41.4
27.6
16.08
2.64
67.92
91.56
18545.11
64.89
1717.53
NEW JERSEY: 2 Lakes
NJ
NJ
Unnamed lake
Verona Lake
Camden
Essex
0013
1063
1
3
2000
2002
39
40
47
49
5.28
36.84
74
74
51
14
45.72
50.28
4
5.47
NEW MEXICO: 2 Lakes
NM
NM
Brantley Reservoir
Navajo Reservoir
Eddy
Rio Arriba
1369
0169
4
1
2001
2000
32
36
36
31
46.19
4.08
104
107
21
36
3.46
37.80
8498
1892.41
NEW YORK: 17 Lakes
NY
NY
NY
NY
NY
NY
NY
Brant Lake
Chautauqua Lake
Colgate Lake
Copake Lake
Goldfish Pond
Grizzle Ocean
Jamesville Reservoir
Warren
Chautauqua
Greene
Columbia
Suffolk
Essex
Onondaga
0593
0114
0488
0138
1463
1518
0238
2
1
2
1
4
4
R
2000
1999
2000
2000
2003
2002
2003
43
42
42
42
40
43
42
42
7
14
8
56
49
58
55.44
59.196
8.16
38.76
31.2
13.8
23.52
73
79
74
73
72
73
76
42
22
7
35
19
35
4
25.2
40.116
8.4
47.4
45.12
42.72
9.12
571.85
5438
10.67
157.5
1.34
7.6
87.71
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National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
Revision 0
Date: 20 April 2007
Page A-12of A-18
State
NY
NY
NY
NY
NY
NY
NY
NY
NY
NY
NC
NC
NC
NC
NC
NC
NC
NC
ND
ND
ND
ND
ND
ND
ND
ND
OH
OH
OH
Lake Name
Lake DeForest
Little Wolf Pond
Moose Lake
Mud Pond
Northville Pond
Seneca Lake
Southern South Lake
Sylvia Lake
Tupper Lake
Whitney Pond
B. Everett Jordan Lake
Kings Mountain Reservoir
Lake Gaston
Lake Norman
Lake Phelps
Mountain Island Reservoir
San-Lee Park Lake
Smith Lake
Devils Lake
Dry Lake
Dry Lake
Epping - Springbrook Dam
Homme Lake
Horsehead Lake
Long Lake
Twin Lakes South
Clouse Lake
Darrell Rose's Pond
Lake Rupert
County
Rockland
Franklin
Herkimer
Clinton
Fulton
Yates
Putnam
St. Lawrence
Franklin
Oswego
IS
Chatham
Cleveland
Warren
Catawba
Washington
Gaston/Mecklenburg
Lee
Cumberland
Ramsey
Mcintosh
Ramsey
Williams
Walsh
Kidder
Kidder
La Moure
Perry
Marion
Vinton
Lake
ID
1488
0542
1513
1542
1013
0088
0613
0113
0067
0913
IORTH C
0162
0062
0164
0262
0139
0537
0312
0612
NORTH
0030
1456
0105
0484
0230
0956
0006
0281
01
1491
0541
0066
Statistical
Year
4
2
4
4
3
1
2
1
1
3
:AROLINA:
1
1
1
R
1
2
R
2
DAKOTA: !
1
4
1
2
R
3
1
R
HIO: 7 Lake
4
2
1
Sampling
Year
2002
2000
2003
2002
2001
2003
2001
1999
2001
2001
8 Lakes
2000
2000
2000
2003
2000
2001
2003
2002
3 Lakes
2001
2000
2001
2001
2003
2001
2000
2003
s
2003
2001
2000
Latitude
Deg
41
44
43
44
43
42
41
44
44
43
35
35
36
35
35
35
35
35
48
46
48
48
48
47
46
46
39
40
39
Min
9
15
50
33
13
37
30
15
11
26
46
18
32
37
46
21
28
8
13
7
15
15
24
2
44
24
46
37
11
Sec
42.12
13.32
0.96
42.12
44.76
39.72
9.36
9.72
29.04
0.96
23.52
3.6
27.6
35.4
7.356
2.88
53.04
9.6
15.6
5.88
8.64
43.92
24.84
34.8
20.4
8.28
1.56
20.28
23.28
Longitude
Deg
73
74
74
73
74
76
73
75
74
75
79
81
78
80
76
80
79
78
98
99
98
103
97
99
100
98
82
83
82
Min
57
28
50
55
10
55
42
24
30
59
0
27
1
56
27
58
7
55
48
28
58
25
48
47
3
15
17
7
31
Sec
31.32
47.64
41.64
21.36
13.44
6.96
14.76
50.04
0.72
23.28
59.4
21.24
8.4
40.2
36.18
11.28
31.08
38.64
19.08
20.28
27.12
0.48
4.68
2.76
46.8
45.72
56.4
39.36
19.56
Lake Area
(ha)
93.52
65.08
507.45
45.43
7.6
17413.27
4.26
124.86
2583.95
32.07
5787
551.51
7951
13211.68
6718
1403.92
7.29
34.07
7119.61
203.78
2196.46
59.85
75.74
1355.91
1299.72
108.46
13.14
2.16
133.07
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National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
Revision 0
Date: 20 April 2007
Page A-13of A-18
State
OH
OH
OH
OH
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
OK
Lake Name
Tom Porter's Pond
Unnamed lake
Unnamed lake
Unnamed lake
Broken Bow Lake
Camp Simpson Lake
Coalgate City Lake
Fort Cobb Lake
Great Salt Plains Lake
Hugo Lake
Keystone Lake
Lake Altus-Lugert
Lake El Reno
Lake Hudson
Lake Lawtonka
Lake Ponca
Oologah Lake
Sardis Lake
Tenkiller Ferry Lake
Unnamed lake
Unnamed lake
Unnamed lake
Unnamed lake
Unnamed lake
Wewoka Lake
County
Licking
Lucas
Trumbull
Hancock
Mccurtain
Johnston
Coal
Caddo
Alfalfa
Choctaw
Creek/Pawnee
Kiowa
Canadian
Mayes
Comanche
Kay
Rogers
Latimer
Cherokee
Mcclain
Osage
Stephens
Le Flore
Rogers
Seminole
Lake
ID
0513
1114
1514
0963
OKLAH
0499
1123
0924
0069
1544
0099
0219
1494
0944
1093
0269
0294
0068
0249
1468
0544
0669
1423
1524
1543
1469
Statistical
Year
2
3
4
3
OMA: 21 L,
2
3
3
1
4
1
1
4
3
3
R
R
1
R
4
2
2
4
4
4
4
Sampling
Year
2001
2002
2003
2002
akes
2000
2001
2001
1999
2002
2000
1999
2002
2001
2001
2003
2003
2000
2003
2002
2000
2000
2002
2002
2002
2002
Latitude
Deg
39
41
41
41
34
34
34
35
36
34
36
34
35
36
34
36
36
34
35
34
36
34
35
36
35
Min
57
36
18
3
16
25
34
11
44
5
14
55
31
26
45
44
34
46
42
59
36
35
16
32
11
Sec
9.36
25.92
24.84
4.32
49.08
7.32
40.80
53.52
1.32
8.52
53.16
32.52
19.56
2.04
28.44
19.68
55.56
21
41.76
12.48
48.60
12.12
8.76
46.32
49.20
Longitude
Deg
82
83
80
83
94
96
96
98
98
95
96
99
97
95
98
97
95
95
94
97
96
97
94
95
96
Min
14
40
34
34
40
32
14
29
10
25
22
18
59
11
30
2
35
4
57
31
47
38
48
38
31
Sec
1.68
48.72
16.68
28.56
46.92
49.20
16.80
27.24
39.36
26.04
4.80
42.12
31.56
30.12
50.04
4.56
31.92
9.84
21.24
44.76
36.60
8.52
20.52
43.80
1.92
Lake Area
(ha)
1.52
5.3
2.38
1.18
5342.04
41.33
159.1
1654.07
4041.26
4950.45
5454.54
1810.44
62.72
8.22
959.22
184.84
6099.87
63.2
5350.48
12.21
2.18
14.67
1.18
99.47
144.51
OREGON: 9 Lakes
OR
OR
OR
OR
OR
Barney Reservoir
Crater Lake
Denley Reservoir
Elk Lake
Lake Owyhee
Washington
Klamath
Douglas
Marion
Malheur
1454
0451
1001
0901
1353
4
2
3
3
4
2003
2001
2002
2002
2003
45
42
43
44
43
26
56
22
49
29
42.612
57.84
22.476
22.872
57.084
123
122
123
122
117
23
5
14
7
21
19.968
41.1
38.724
7.968
3.672
81.14
5318.03
5.91
25.95
4576.85
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National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
Revision 0
Date: 20 April 2007
Page A-14of A-18
State
OR
OR
OR
OR
Lake Name
Lake Umatilla
Malheur Lake
Unnamed lake
Wickiup Reservoir
County
Klickitat
Harney
Linn
Deschutes
Lake
ID
0629
0326
0076
1501
Statistical
Year
2
R
1
4
Sampling
Year
2002
2003
2002
2003
Latitude
Deg
45
43
44
43
Min
43
18
33
41
Sec
32.916
35.24
9.54
29.868
Longitude
Deg
120
118
123
121
Min
31
47
14
43
Sec
53.544
32.03
20.112
19.668
Lake Area
(ha)
11697.92
5961.67
7.23
4110.44
PENNSYLVANIA: 9 Lakes
PA
PA
PA
PA
PA
PA
PA
PA
PA
Crooked Creek Lake
Francis Slocum State Park Lake
Keystone Lake
Lake Sabula
Pike Lake #3
Shenango River Lake
Unnamed lake
Unnamed lake
Whitney Lake
Armstrong
Luzerne
Westmoreland
Clearfield
Pike
Mercer
Franklin
Bradford
Wayne
0489
0288
0239
0039
0188
1014
0089
0213
1088
2
R
R
1
1
3
1
1
3
2000
2003
2003
2002
1999
2001
1999
2000
2001
40
41
40
41
41
41
39
41
41
40
20
22
9
15
17
56
56
28
55.92
12.48
24.96
29.16
1.44
34.08
42.36
39.48
9.12
79
75
79
78
74
80
77
76
75
29
53
22
39
57
25
48
23
15
8.52
40.56
58.08
57.24
5.04
28.92
43.56
19.68
0.72
151.44
66.62
23.52
13.36
5.61
1490.57
1.6
9.65
46.01
RHODE ISLAND: 2 Lakes
Rl
Rl
Arnold Mills Reservoir
Gorton Pond
Providence
Kent
1567
1517
4
4
2003
2003
41
41
59
42
2.04
18.72
71
71
24
27
23.4
33.84
6.44
21.82
SOUTH CAROLINA: 3 Lakes
SC
sc
SC
Hartwell Reservoir
Lake Murray
Lake Wateree
Oconee
New berry
Kershaw
1486
0987
1562
4
3
4
2001
2000
2001
34
34
34
34
5
25
42.24
15.72
9.48
83
81
80
6
28
48
6.12
0.12
32.04
6881.09
19601.57
5548.26
SOUTH DAKOTA: 9 Lakes
SD
SD
SD
SD
SD
SD
SD
SD
SD
Angostura Reservoir
Corsica Lake
Hayes Lake
Lake Mitchell
Lake Oahe
Mud Lake
Pelican Lake
Shadehill Reservoir
South Waubay Lake
Fall River
Douglas
Stanley
Davison
Dewey
Kingsbury
Codington
Perkins
Day
1553
1031
0982
0007
1056
1107
0107
0056
1507
4
3
3
1
3
3
1
1
4
2002
2001
2000
2000
2002
2001
2001
2000
2002
43
43
44
43
44
44
44
45
45
18
24
21
45
52
28
52
46
22
28.08
53.64
57.6
23.04
26.76
44.76
4.08
11.64
49.08
103
98
101
98
100
97
97
102
97
25
17
0
3
31
35
10
15
27
4.44
31.2
44.64
21.6
59.16
33
48.36
16.92
5.04
1741.5
37.99
24.6
283.62
61520.39
119.08
1124.44
958.83
940.18
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Revision 0
Date: 20 April 2007
Page A-15of A-18
State
Lake Name
County
Lake
ID
Statistical
Year
Sampling
Year
Latitude
Deg
Min
Sec
Longitude
Deg
Min
Sec
Lake Area
(ha)
TENNESSEE: 8 Lakes
TN
TN
TN
TN
TN
TN
TN
TN
Dale Hollow Lake
Douglas Reservoir
J. Percy Priest Lake
Kentucky Lake
N orris Lake
Pine Lake
Ridgetop Lake
Tellico Lake
Clay
Jefferson
Davidson
Henry/Stewart
Union
Henderson
Robertson
Monroe
0487
1487
0087
1036
0187
0561
0587
1536
2
4
1
3
1
2
2
4
2001
2003
2000
2002
2000
2001
2001
2003
36
35
36
36
36
35
36
35
33
59
5
25
18
33
24
36
54.36
50.28
56.76
53.76
40.68
29.16
46.08
30.96
85
83
86
88
83
88
86
84
16
21
33
4
49
24
45
13
29.28
54.36
37.08
45.12
58.8
54
51.84
4.8
10725.65
11138.56
5369.73
46342.27
3749.23
184.41
5.41
6638.63
TEXAS: 41 Lakes
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
Arnold Lake
ASCS Lake Riser 638
B.A. Steinhagen Lake
Bardwell Reservoir
Caddo Lake
E.V. Spence Reservoir
Hubbard Creek Reservoir
Lake Arrowhead
Lake Belton
Lake Caballo
Lake Childress
Lake Coleman
Lake Conroe
Lake Corpus Christ!
Lake Falcon
Lake Lavon
Lake Lewisville
Lake Logan
Lake Palestine
Lake Pat Mayse
Lake Proctor
Houston
Collin
Tyler/Jasper
Ellis
Marion
Coke
Stephens
Clay
Bell
Zavala
Childress
Coleman
Montgomery
Live Oak
Zapata
Collin
Denton
Navarro
Henderson
Lamar
Comanche
0220
0598
0524
0246
1373
0021
0596
0048
0921
0196
0495
0471
1570
0221
1571
0948
1473
0496
0673
0573
1045
1
2
2
R
4
1
2
1
3
1
2
2
4
1
4
3
4
2
2
2
3
1999
2002
2000
2003
2003
2000
2000
2000
2001
2000
2000
2000
2002
1999
2003
2001
2002
2000
2000
2001
2001
31
33
30
32
32
31
32
33
31
28
34
32
30
28
26
33
33
32
32
33
32
10
18
50
17
44
56
46
42
9
54
27
2
28
12
55
7
8
0
11
49
1
9.84
28.08
56.29
11.04
56.76
13.56
31.08
37.08
59.40
23.40
40.68
13.20
4.08
4.68
17.76
49.44
57.84
52.20
9.60
37.20
8.04
95
96
94
96
94
100
99
98
97
99
100
99
95
97
99
96
96
96
95
95
98
41
40
11
40
7
34
0
22
34
38
20
30
35
55
19
32
59
49
29
35
30
0.24
9.48
30.59
10.92
32.16
39.72
24.48
44.40
25.68
57.84
57.12
50.40
8.52
42.24
7.68
39.84
12.48
37.92
17.16
54.24
18.36
23.46
6.77
5549
1125.31
10794
6055
5960.07
6561
1052.24
4.95
120.72
705.13
8029.64
7831
15801.88
80.66
8589.78
12.44
9533.34
2389.57
1913.14
-------
National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
Revision 0
Date: 20 April 2007
Page A-16of A-18
State
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
TX
Lake Name
Lake Sam Rayburn
Lake Tawakoni
Lake Texoma
Lake Travis
Richland Reservoir
Rogers Lake
Stillhouse Hollow Reservoir
Toledo Bend Reservoir
Toledo Bend Reservoir
Unnamed lake
Unnamed lake
Unnamed lake
Unnamed lake
Unnamed lake
Unnamed lake
Unnamed lake
Unnamed lake
Unnamed lake
Unnamed lake
Wright Patman Lake
County
Nacogdoches
Hunt
Grayson
Travis
Navarro/Freestone
Montgomery
Bell
Panola
Sabine
Young
Smith
Henderson
Nacogdoches
Hopkins
Karnes
Mcculloch
Collin
Ellis
Montague
Bowie
Lake
ID
0324
0223
0473
0070
1446
0020
0645
0974
1399
1021
1098
0998
1049
1073
1395
1421
1498
1370
1523
0973
Statistical
Year
R
1
2
1
4
1
2
3
4
3
3
3
3
3
4
4
4
4
4
3
Sampling
Year
2003
2000
2001
2000
2003
1999
2000
2002
2002
2001
2001
2002
2002
2002
2002
2002
2002
2003
2003
2003
Latitude
Deg
31
32
33
30
31
30
31
32
31
33
32
32
31
33
28
31
33
32
33
33
Min
7
56
51
24
58
11
0
1
31
23
34
4
33
6
56
18
11
14
29
17
Sec
0.516
57.12
21.96
55.44
47.14
6.36
22.32
39.72
22.80
43.80
5.52
54.48
15.12
4.32
11.40
57.24
22.56
28.32
19.32
3.84
Longitude
Deg
94
96
96
98
96
95
97
94
93
98
95
96
94
95
98
99
96
96
97
94
Min
9
0
47
1
13
23
36
9
46
40
30
2
33
31
0
14
21
49
36
19
Sec
37.332
38.52
23.64
32.88
1.92
14.64
31.32
57.24
16.32
37.56
57.96
20.40
7.92
55.20
58.32
0.60
46.08
17.40
39.60
55.56
Lake Area
(ha)
46336.7
15333.32
23548.87
7239.69
18124
9.31
2663.76
4.96
67141.13
8.72
6.07
10.27
3.24
5.18
8.01
5.97
8.58
9.12
5.38
11360.46
UTAH: 5 Lakes
UT
UT
UT
UT
UT
Gunlock Reservoir
Olsen Slough
Strawberry Reservoir
Unnamed lake
Utah Lake
Washington
San pete
Wasatch
Cache
Utah
0102
0526
1051
0927
1476
1
2
3
3
4
2000
2003
2002
2003
2002
37
39
40
41
40
15
4
11
49
12
42.48
14.52
13.56
53.4
8.856
113
111
111
111
111
46
50
8
53
48
31.8
15.72
41.64
17.88
26.208
100.83
14.5
3171.67
6.96
39231
VERMONT: 2 Lakes
VT
VT
Lake Whitingham
Lake Willoughby
Windham
Orleans
0093
0942
1
3
2000
2002
42
44
49
44
41.52
52.8
72
72
53
3
29.4
33.12
1564.85
670.01
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National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
Revision 0
Date: 20 April 2007
Page A-17of A-18
State
Lake Name
County
Lake
ID
Statistical
Year
Sampling
Year
Latitude
Deg
Min
Sec
Longitude
Deg
Min
Sec
Lake Area
(ha)
VIRGINIA: 10 Lakes
VA
VA
VA
VA
VA
VA
VA
VA
VA
VA
Banister Lake
Big Lake
Griggs Pond
John H. Kerr Reservoir
Lake Anna
Lake Caroline
Lake Chesdin
Lone Star Lake
Unnamed lake
Unnamed lake
Halifax
Halifax
Henrico
Mecklenburg
Louisa
Caroline
Chesterfield
Suffolk
Caroline
Prince William
1089
0512
0614
0314
0064
0264
1539
0964
0090
0914
3
2
2
R
1
R
4
3
1
3
2001
2000
2000
2003
1999
2003
2002
2001
2001
2001
36
36
37
36
38
37
37
36
37
38
47
40
25
33
3
59
15
52
58
49
14.28
55.2
23.88
54.72
51.84
23.28
43.2
1.56
1.92
14.52
78
79
77
78
77
77
77
76
77
77
57
5
18
28
50
31
36
34
18
42
14.76
25.08
37.44
36.48
37.68
35.4
8.64
13.44
43.92
14.04
154.42
10.42
5.81
16907.08
5254.27
1 1 1 .22
1315.57
13.14
10.88
2.99
WASHINGTON: 14 Lakes
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
WA
Buffalo Lake
Calligan Lake
Crescent Lake
Dorothy Lake
Frenchman Hills Lake
Keechelus Lake
Lake Chelan
Lake Nahwatzel
Lake Wallula
Lone Lake
Patterson Lake
Pend Oreille River
Potholes Reservoir
Rimrock Lake
Okanogan
King
Clallam
King
Grant
Kittitas
Chelan
Mason
Benton
Island
Okanogan
Pend Oreille
Grant
Yakima
1379
1554
0202
0654
0179
0004
0504
0279
1479
0979
0304
1354
1054
0529
4
4
1
2
1
1
2
R
4
3
R
4
3
2
2002
2002
1999
2000
1999
2001
2000
2003
2003
2001
2003
2002
2001
2000
48
47
48
47
46
47
48
47
46
48
48
48
46
46
3
36
5
35
58
20
1
14
0
1
27
25
59
38
47.016
18.54
5.316
3.408
54.876
2.94
33.96
35.34
17.208
17.472
31.896
48
12.48
25.08
118
121
123
121
119
121
120
123
118
122
120
117
119
121
53
39
46
22
35
21
19
19
58
27
14
17
19
9
14.496
57.168
2.712
59.88
17.772
34.056
55.38
56.532
54.156
34.812
40.308
33.072
19.992
42.444
226.24
116.96
1995.24
101.93
138.34
955.35
13091
111.16
12960.93
34.21
51.6
935.8
11333
951.97
WEST VIRGINIA: 1 Lake
WV
Summersville Lake
Nicholas
0637
2
2003
38
14
27.24
80
51
15.12
843.74
-------
National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
Revision 0
Date: 20 April 2007
Page A-18of A-18
State
Lake Name
County
Lake
ID
Statistical
Year
Sampling
Year
Latitude
Deg
Min
Sec
Longitude
Deg
Min
Sec
Lake Area
(ha)
WISCONSIN: 18 Lakes
Wl
Wl
Wl
Wl
Wl
Wl
Wl
Wl
Wl
Wl
Wl
Wl
Wl
Wl
Wl
Wl
Wl
Wl
Big Gibson Lake
Castle Rock Lake
Hatch Lake
Irogami (Fish) Lake
Keyes Lake
Lake DuBay/Big Eau Pleine
Reservoir
Lake Winnebago
Lake Winter
Pacwawong Lake
Pewaukee Lake
Rainbow Flowage
Spirit River Flowage
Sweeney Lake
Turtle Flambeau Flowage
Warner Lake
Whitefish Lake
Wolf Lake
Yellow River Barren Flowage #3
Vilas
Adams/Juneau
Waupaca
Waushara
Florence
Marathon
Winnebago
Sawyer
Sawyer
Waukesha
Oneida
Lincoln
Oneida
Iron
Burnett
Sawyer
Fond Du Lac
Barren
1084
0458
0983
0008
0259
0208
0666
0133
0958
1566
0308
0283
0134
0608
0058
0258
0291
1058
3
2
3
1
R
1
2
1
3
4
R
R
1
2
1
R
R
3
2002
2001
2003
2001
2003
2002
2003
2001
2002
2003
2003
2003
2003
2001
2002
2003
2003
2002
46
43
44
44
45
44
44
45
46
43
45
45
45
46
45
45
43
45
8
56
31
3
53
42
0
48
9
4
51
26
51
5
47
51
51
24
15.36
6.72
50.52
57.24
58.2
0
7.2
42.12
1.8
22.44
32.4
38.76
42.84
8.52
49.2
47.52
51.48
48.6
89
89
89
89
88
89
88
90
91
88
89
89
89
90
92
91
88
91
33
59
6
13
18
40
24
59
20
18
30
49
35
10
13
26
12
51
9.72
9.6
52.56
56.28
23.76
48
56.52
3.48
21.84
25.92
51.84
24.24
21.84
8.724
19.56
36.24
28.44
57.24
48.45
5010.01
46.13
116.45
76.26
5356.14
53756.72
110.43
76.05
984.62
1291.37
640.24
77.73
7648.59
71.36
322.36
33.84
20.56
WYOMING: 6 Lakes
WY
WY
WY
WY
WY
WY
Baptiste Lake
Buffalo Bill Reservoir
Lake 79
Lake DeSmet
Lewis Lake
Yellowstone Lake
Fremont
Park
Fremont
Johnson
Teton
Teton
0527
0528
0052
1478
0602
1078
2
2
1
4
2
3
2001
2000
2001
2001
2003
2003
42
44
43
44
44
44
52
29
0
29
17
27
21.36
33
30.24
3.48
59.28
17.532
109
109
109
106
110
110
18
15
19
45
37
21
18
30.96
58.8
12.24
39.72
58.428
73.34
1384.63
4.04
821.12
1115.92
35223.98
-------
Appendix B
Input Data File Example
(A Portion of Year 4 Data from Rhode Island)
-------
-------
National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
Revision 0
Date: 20 April 2007
PageB-1 ofB-3
State
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
Rhode Island
County
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Kent
Site Name
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Gorton Pond
Latitude
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
41.7052
Longitude
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
-71.4594
Lake_ID_
Number
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
1517
Water Body Type
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Lake
Surface Area
(ha)
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
21.82
Composite Sample ID
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
RI031517PS
-------
National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
Revision 0
Date: 20 April 2007
PageB-2ofB-3
Composite_
Type
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Predator
Preparation
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
Filleted Prior to Homogenization
EPA_Sample_
Number
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
63252
Analyte
1, 2,3,4 ,6,7,8-HPCDD
1, 2,3,4 ,6,7,8-HPCDF
1,2,3,4,7,8,9-HPCDF
1,2,3,4,7,8-HXCDD
1,2,3,4,7,8-HXCDF
1,2,3,6,7,8-HXCDD
1,2,3,6,7,8-HXCDF
1,2,3,7,8,9-HXCDD
1,2,3,7,8,9-HXCDF
1,2,3,7,8-PECDD
1,2,3,7,8-PECDF
2,3,4,6,7,8-HXCDF
2,3,4,7,8-PECDF
2,3,7,8-TCDD
2,3,7,8-TCDF
OCDD
OCDF
1 ,2,3-TRICHLOROBENZENE
1 ,2,4,5-TETRACHLOROBENZENE
1 ,2,4-TRICHLOROBENZENE
1,2-DICHLOROBENZENE
1 ,2-DIPHENYLHYDRAZINE
1,3-DICHLOROBENZENE
1,4-DICHLOROBENZENE
2,3,6-TRICHLOROPHENOL
2,4,5-TRICHLOROPHENOL
2,4,6-TRICHLOROPHENOL
2,4,6-TRIS(1,1-DIMETHYLETHYL)PHENOL
2,4-DICHLOROPHENOL
2,4-DIMETHYLPHENOL
2,4-DINITROPHENOL
2,4-DINITROTOLUENE
2,6-DINITROTOLUENE
2-CHLORONAPHTHALENE
2-CHLOROPHENOL
CAS Number
35822469
67562394
55673897
39227286
70648269
57653857
57117449
19408743
72918219
40321764
57117416
60851345
57117314
1746016
51207319
3268879
39001020
87616
95943
120821
95501
122667
541731
106467
933755
95954
88062
732263
120832
105679
51285
121142
606202
91587
95578
Amount
0.07
0.03
-------
National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
Revision 0
Date: 20 April 2007
PageB-3ofB-3
Replimit
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
0.5
1
1
333
333
333
333
666
333
333
333
333
333
333
333
333
1665
333
333
333
333
Unit
NG/KG (ppt)
NG/KG (ppt)
NG/KG (ppt)
NG/KG (ppt)
NG/KG (ppt)
NG/KG (ppt)
NG/KG (ppt)
NG/KG (ppt)
NG/KG (ppt)
NG/KG (ppt)
NG/KG (ppt)
NG/KG (ppt)
NG/KG (ppt)
NG/KG (ppt)
NG/KG (ppt)
NG/KG (ppt)
NG/KG (ppt)
UG/KG (ppb)
UG/KG (ppb)
UG/KG (ppb)
UG/KG (ppb)
UG/KG (ppb)
UG/KG (ppb)
UG/KG (ppb)
UG/KG (ppb)
UG/KG (ppb)
UG/KG (ppb)
UG/KG (ppb)
UG/KG (ppb)
UG/KG (ppb)
UG/KG (ppb)
UG/KG (ppb)
UG/KG (ppb)
UG/KG (ppb)
UG/KG (ppb)
SCC Code
B, RNON
J
J
B, RNAF
Comments
BLANK CONTAMINATION
ESTIMATED VALUE
ESTIMATED VALUE
BLANK CONTAMINATION
Method_
Number
1613B
1613B
1613B
1613B
1613B
1613B
1613B
1613B
1613B
1613B
1613B
1613B
1613B
1613B
1613B
1613B
1613B
1625C
1625C
1625C
1625C
1625C
1625C
1625C
1625C
1625C
1625C
1625C
1625C
1625C
1625C
1625C
1625C
1625C
1625C
Analysis
Dioxins and Furans
Dioxins and Furans
Dioxins and Furans
Dioxins and Furans
Dioxins and Furans
Dioxins and Furans
Dioxins and Furans
Dioxins and Furans
Dioxins and Furans
Dioxins and Furans
Dioxins and Furans
Dioxins and Furans
Dioxins and Furans
Dioxins and Furans
Dioxins and Furans
Dioxins and Furans
Dioxins and Furans
Semi-volatile Organic Cmpds.
Semi-volatile Organic Cmpds.
Semi-volatile Organic Cmpds.
Semi-volatile Organic Cmpds.
Semi-volatile Organic Cmpds.
Semi-volatile Organic Cmpds.
Semi-volatile Organic Cmpds.
Semi-volatile Organic Cmpds.
Semi-volatile Organic Cmpds.
Semi-volatile Organic Cmpds.
Semi-volatile Organic Cmpds.
Semi-volatile Organic Cmpds.
Semi-volatile Organic Cmpds.
Semi-volatile Organic Cmpds.
Semi-volatile Organic Cmpds.
Semi-volatile Organic Cmpds.
Semi-volatile Organic Cmpds.
Semi-volatile Organic Cmpds.
Percent_
Lipids
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
0.28
Sampling_
Year
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
2003
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Appendix C
Electronic Data Deliverable
Data Dictionary
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National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
Revision 0
Date: 20 April 2007
Page C-l of C-3
National Lake Fish Tissue Study - Year Three (2002) and Year Four (2003)
Electronic Data Deliverable (EDO)
Data Dictionary
Worksheet Name: -RESULTS(A-M) and RESULTS(N-Z)
Worksheet Description: - These worksheets store the analytical results for all of the composite samples.
Worksheet Organization: - These worksheets are sorted by the State, Method, and then Analyte fields.
Column Name
State
County
Site Name
Latitude
Longitude
Lake_ID_Number
Water_Body_Type
Surface_Area(ha)
Composite_Sample_ID
Description
The full name of the state in which the sample was collected.
An example of a record found in this field would be Alabama.
The county where the sampling site is located. An example is
Becker (MN).
The name of the water body where the samples were collected.
An example of an entry in this field is Flat Lake. Sampling
locations without an official name were identified as
"Unnamed lake."
The latitude (represented as a decimal value) associated with
the sampling location. An example is "46.9790".
The longitude (represented as a decimal value) associated with
the sampling location. An example is "-95.6548".
The unique 4-digit code assigned to individual lakes or
reservoirs by EPA; this number uniquely identifies a particular
site. An example of a record found in this field is 1506.
The type of water body from which the individual fish
specimens were collected. Records found in this field include
Lake and Reservoir.
The total area covered by a water body in hectares (ha); a
hectare is about 2.5 acres.
This is the alpha-numeric code (ten characters in length) used
to describe a sample. The first two characters of the code are
the state abbreviation; the third and fourth characters are the
last two digits of the year in which the sample was collected;
the fifth through eighth characters represent the lake ID
number designated by EPA; the ninth character represents the
composite type ("B" for bottom dweller and "P" for predator);
and the tenth, and final, character represents the sample type
("S" for standard and "D" for duplicate). Examples of records
found in this field would be AL030236BS or AL030236BD.
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National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP
Revision 0
Date: 20 April 2007
PageC-2ofC-3
Worksheet Name: -RESULTS(A-M) and RESULTS(N-Z) (cont.)
Column Name
Composite_Type
Preparation
EPA_Sample_Number
Analyte
CAS Number
Amount
Replimit
Unit
SCC Code
Comments
Method Number
Description
This field describes the type offish species sampled. This
field contains the designations "Bottom-dweller" or
"Predator."
A description of how the sample was prepared. The only two
entries found in this field are "Homogenized Whole" for the
bottom dwellers and "Filleted Prior to Homogenization" for
the predators.
The unique 5-digit EPA sample number assigned by the
sample prep laboratory to distinguish samples from one
another. Examples are 63287 and 63289.
The chemical compound analyzed by the laboratory.
The unique Chemical Abstract Services (CAS) Number
assigned to each analyte. Please note that for those PCB
congeners that co-elute, the CAS Number was left blank.
Also, since Total Inorganic Arsenic does not have a CAS
Number associated with it, this field was left blank for this
analyte.
The concentration of a particular analyte (chemical) for which
the data are being reported. Please note that a blank field
indicates that the analyte was not detected above the Method
Detection Limit (MDL).
The minimum level of quantitation (ML), adjusted for dilution
or concentration, if necessary.
Unit of measure. Examples include NG/KG (ppt), UG/KG
(ppb), and UG/G (ppm).
This column is used to represent Sample Control Center's
(SCC's) data considerations or "qualifiers." Examples of
records found in this field include "B, RNON" and "HLBL."
Please note that a Data Qualifier Key is provided with the
results and this key describes all of the SCC Codes that are
applied to the results.
A brief explanation or description of the SCC Code.
Examples of records found in this field include Blank
Contamination and Estimated Value.
The EPA method number used by the laboratory to analyze
the samples for a particular analyte of interest. This field is
limited to the following method numbers: 1613B, 1625C,
163 IB, 1632A, 1656A, 1657A, and 1668A.
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National Study of Chemical Residues in Lake Fish Tissue Data Analysis QAPP Revision 0
Date: 20 April 2007
Page C-3 of C-3
Worksheet Name: -RESULTS(A-M) and RESULTS(N-Z) (cont.)
Column Name Description
Analysis The full text description of the analysis performed on the
sample. This field is limited to the following: "Metals (Hg +
As Species)", "Polychlorinated Biphenyls", "Dioxins and
Furans", "Pesticides", and "Semi-volatile Organic Cmpds."
Percent_Lipids Measure of the amount of lipid content of a fish composite
sample; represented as a percentage of total sample weight,
rounded to two decimal places.
Sampling_Year The year that the sample was collected.
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