National Coastal Condition Assessment 2020
Version 1.2 February 2021
Quality Assurance Project Plan
Page 1 of 165
r _ **
&
United States Environmental Protection Agency
Office of Water
Washington, DC
EPA No. 841-F-19-003
National Coastal
Condition Assessment
2020
Quality Assurance
Project Plan
Version 1.2 February 2021
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Approval Page
Management Approvals: Signature indicates approval for the National Coastal Condition Assessment
2020 Quality Assurance Project Plan (QAPP), related Field Operations Manual (FOM) and Laboratory
Operations Manual (LOM).
ill i/-* m Digitally signed by HUGH
nuvjn SULLIVAN
SULLIVAN _Date2021.02.2211:57:54
Hugh Sullivan Date
NCCA Project Manager
n a M|C| I C Digitally signed by DANIELLE
UMINICLLC GRUNZKE
GRUNZKE ^2021.02.22 10:39:06
Danielle Grunzke Date
Project Quality Assurance Coordinator
Digitally signed by SARAH
SARAH LEHMANN LEHMANN
Date: 2021.02.22 1 5:04:32 -05'00'
Sarah Lehmann Date
National Aquatic Resource Surveys (NARS) Team Leader
Q[ | o AM Digitally signed by SUSAN
oUoAN HOLDSWORTH
HOLDSWORTH D0a5te002021 0Z23 17:32:10
Susan Holdsworth Date
Chief, Monitoring Branch
Digitally
SMITH
Date: 2(
-05'00'
|q^ Digitally signed by BERNICE
SM |TH Date: 2021.03.04 09:40:57
Bernice Smith Date
Division Quality Assurance Coordinator
PYMTHI A Digitally signed by
O 1 I V I ril/A CYNTHIA SHIMANSKI
SHIMANSKI Dn"1 03 08 13:37:57
Cynthia Johnson Date
OWOW Quality Assurance Coordinator
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QUALITY ASSURANCE PROJECT PLAN
REVIEW & DISTRIBUTION ACKNOWLEDGMENT AND
COMMITMENT TO IMPLEMENT
for
National Coastal Condition Assessment 2020
I/We have read the QAPP and the methods manuals for the National Coastal Condition
Assessment listed below. Our agency/organization agrees to abide by its requirements for
work performed under the National Coastal Condition Assessment. Please check the
appropriate documents.
Quality Assurance Project Plan ~
Field Operations Manual ~
Site Evaluation Guidelines ~
Laboratory Methods Manual ~
Field Crew leads: I also certify that I attended an NCCA 2020 training and that all members of
my crew have received training in NCCA protocols
Print Name
Title
(Cooperator's Principal Investigator)
Organization
Signature Date
Field Crews: Please return this signed "QAPP Review & Distribution Acknowledgment and Commitment
to Implement" form and return to the Contractor Field Logistics Coordinator, Chris Turner, Great Lakes
Environmental Center, Inc.; 739 Hastings Street; Traverse City, Ml 49686. cturner(5)glec.com.
Labs and others: Please return the signed original to Kendra Forde who will ensure all parties have
signed the QA forms, compile them, and submit them to the EPA QA Coordinator. Send your forms to:
Kendra Forde atforde.kendra@epa.gov; or by US Postal Service at EPA, 1200 Pennsylvania Ave, NW
(4503T); Washington, DC 20460. Please retain a copy for your files.
Please save the QAPP locally upon completing this page, and then print this page only to PDF. Use the
following naming convention for the file:
NCCA_2020_QAPPvl.l_ACK_[Lastname. Firstname_organization_YYYYMMDDJ.pdf"
* Handwritten or digital signatures are acceptable.
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Version History
QAPP Version
Date Approved
Changes Made
1.0
April 10, 2020
Not Applicable
1.1
April 22, 2020
Section 3.4 Revisit Sites, text chaneed to indicate that revisits should
occur at least two weeks after the first visit and preferably lonser.
Pase 53.
Section 5.1.4.3 Instrumentation. Corrected Table 5.3 so that
Dissolved Oxveen calibration Acceptance Criteria reads "ฑ0.5
me/L or 10% of 100% saturation", to alien with the DO data
accuracy objective in Table 5.2, which is correct, p. 79.
Section 5.10 Human Health Fish Tissue (HTIS) (Great Lakes
Nearshore and Lake Michigan Enhancement Sites Only). Corrected
name of indicator to "Great Lakes Human Health Fish Tissue
Studv". Corrected compounds to be analyzed for (removed "PFCs"
and "PBDEs". and added "PFAS"). Pases 139-140. 142-144.
Table 0.1 Description of NCCA 2020 Indicators and
location where indicators are collected undated to clarify
the sites at which Human Health fish specimens will be
collected. P. 73
1.2
March 9, 2021
Table 5.13 changed Average absorbance value, AO, for SO to >0.80
from > 0.80.
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Notices
The National Coastal Condition Assessment (NCCA) 2020 Quality Assurance Project Plan (QAPP) and
related documents are based on the previous Environmental Monitoring and Assessment Program's
(EMAP) National Coastal Assessment (NCA) conducted in 2001 - 2004 as well as the National Coastal
Condtion Assessments in 2010 and 2015.
The complete documentation of overall NCCA project management, design, methods, and standards is
contained in four companion documents, including:
National Coastal Condition Assessment: Quality Assurance Project Plan (EPA # 841-F-19-003)
National Coastal Condition Assessment: Field Operations Manual (EPA # 841-F-19-005)
National Coastal Condition Assessment: Laboratory Methods Manual (EPA # 841-F-19-004)
National Coastal Condition Assessment: Site Evaluation Guidelines (EPA # 841-B-20-001)
This document (QAPP) contains elements of the overall project management, data quality objectives,
measurement and data acquisition, and information management for the NCCA 2020. Methods
described in this document are to be used specifically in work relating to the NCCA 2020 and related
projects. All Project Cooperators should follow these guidelines. Mention of trade names or
commercial products in this document does not constitute endorsement or recommendation for use.
More details on specific methods for site evaluation, field sampling, and laboratory processing can be
found in the appropriate companion document(s).
The citation for this document is:
U.S. EPA. National Coastal Condition Assessment Quality Assurance Project Plan. United States
Environmental Protection Agency, Office of Water, Office of Wetlands, Oceans and Watersheds.
Washington, D.C.EPA# 841-F-19-003. 2020.
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Table of Contents
Approval Page 3
Version History 5
Notices 6
Table of Contents 7
List of Tables 13
List of Figures 16
Acronyms 17
Distribution List 20
NCCA Executive Summary 22
1 Project Planning and Management 25
1.1 Introduction 25
1.2 Scope of the Quality Assurance Project Plan 26
1.3 Project Organization 27
1.4 Project Design 31
1.5 Project Schedule 34
1.6 Overview of Field Operations 34
1.7 Overview of Laboratory Operations 38
1.7.1 Chemistry Lab Quality Evaluation 40
1.7.2 Biological Laboratory Quality Evaluation 40
1.8 Data Analysis 41
1.9 Peer Review 41
2 Data Quality Objectives 43
2.1 Data Quality Objectives for the National Coastal Condition Assessment 43
2.2 Measurement Quality Objectives 43
2.2.1 Method Detection Limits (Laboratory Reporting Level (Sensitivity)) 44
2.2.2 Sampling Precision and Bias 45
2.2.3 Sampling Accuracy 47
2.2.4 Taxonomic Precision and Accuracy 47
2.2.5 Completeness 48
2.2.6 Comparability 49
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2.2.7 Representativeness 49
3 Site Selection Design 51
3.1 Probability Based Sampling Design and Site Selection 51
3.2 Survey Design for the Estuarine Waters 51
3.3 Survey Design for the Great Lakes Nearshore Waters 52
3.3.1 Great Lakes Enhancement Study Designs 53
3.4 Revisit Sites 53
4 Information Management 54
4.1 Roles and Responsibilities 54
4.1.1 State/ Tribe-Based Data Management 57
4.2 Overview of System Structure 58
4.2.1 Data Flow 58
4.2.2 Simplified Description of Data Flow 58
4.2.3 Core Information Management Standards 60
4.2.4 Data Formats 60
4.2.5 Public Accessibility 61
4.3 Data Transfer Protocols 61
4.4 Data Quality and Results Validation 63
4.4.1 Design and Site Status Data Files 63
4.4.2 Sample Collection and Field Data 63
4.4.3 Laboratory Analyses and Data Recording 65
4.4.4 Data Review, Verification, and Validation Activities 67
4.5 Data Transfer 69
4.5.1 Database Changes 69
4.6 Metadata 70
4.6.1 Parameter Formats 70
4.6.2 Standard Coding Systems 70
4.7 Information Management Operations 70
4.7.1 Computing Infrastructure 70
4.7.2 Data Security and Accessibility 71
4.7.3 Life Cycle 71
4.7.4 Data Recovery and Emergency Backup Procedures 71
4.7.5 Long-Term Data Accessibility and Archive 71
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4.8
Records Management
72
Indicators__
73
5.1
In Situ Measurements
75
5.1.1
Introduction
75
5.1.2
Sample Design and Methods
75
5.1.3
Pertinent Laboratory QA/QC Procedures
75
5.1.4
Pertinent Field QA/QC Procedures
75
5.1.5
Data Review
81
5.2
Water
Chemistry Measurements (Including chlorophyll-a)
81
5.2.1
Introduction
81
5.2.2
Sample Design and Methods
81
5.2.3
Pertinent Laboratory QA/QC Procedures
81
5.2.4
Pertinent Field QA/QC Procedures
89
5.2.5
Data Review
91
5.3
Cylindrospermopsin
92
5.3.1
Introduction
92
5.3.2
Sample Design and Methods
92
5.3.3
Pertinent Laboratory QA/QC Procedures
92
5.3.4
Pertinent Field QA/QC Procedures
95
5.3.5
Data Review
96
5.4
Microcystins
96
5.4.1
Introduction
96
5.4.2
Sample Design and Methods
97
5.4.3
Pertinent Laboratory QA/QC Procedures
97
5.4.4
Pertinent Field QA/QC Procedures
100
5.4.5
Data Review
101
5.5
Benthic Invertebrates
101
5.5.1
Introduction
101
5.5.2
Sample Design and Methods
101
5.5.3
Pertinent Laboratory QA/QC Procedures
101
5.5.4
Pertinent Field QA/QC Procedures
105
5.5.5
Data Review
106
5.6
Sediment Contaminants, Total Organic Carbon (TOC) and Grain Size
106
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5.6.1 Introduction 106
5.6.2 Sample Design and Methods 106
5.6.3 Pertinent Laboratory QA/QC Procedures 106
5.6.4 Pertinent Field QA/QC Procedures 120
5.6.5 Data Review 121
5.7 Sediment Toxicity 122
5.7.1 Introduction 122
5.7.2 Sample Design and Methods 122
5.7.3 Pertinent Laboratory QA/QC Procedures 122
5.7.4 Pertinent Field QA/QC Procedures 126
5.7.5 Data Review 127
5.8 Fecal Indicator: Enterococci 127
5.8.1 Introduction 127
5.8.2 Sampling Design and Methods 128
5.8.3 Pertinent Laboratory QA/QC Procedures 128
5.8.4 Pertinent Field QA/QC Procedures 128
5.9 Whole Fish Tissue Samples for Ecological Analysis 129
5.9.1 Introduction 129
5.9.2 Sample Design and Methods 130
5.9.3 Pertinent Laboratory QA/QC Procedures 130
5.9.4 Pertinent Field QA/QC Procedures 137
5.9.5 Data Review 139
5.10 Fish Tissue Filets (Great Lakes) Error! Bookmark not defined.
5.10.1 Introduction 139
5.10.2 Sampling Design and Methods 140
5.10.3 Sampling and Analytical Methodologies 142
5.10.4 Pertinent Laboratory QA/QC Procedures 142
5.10.5 Pertinent Field QA/QC Procedures 142
5.10.6 Data Management, Review and Validation 143
5.11 Fish Tissue Plugs 144
5.11.1 Introduction 144
5.11.2 Sample Design and Methods 144
5.11.3 Pertinent Laboratory QA/QC Procedures 144
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5.11.4 Pertinent Field QA/QC Procedures 145
5.11.5 Data Review 147
5.12 Microplastics in Sediment 147
5.13 Total Alkalinity 147
5.13.1 Introduction 147
5.14 5N15 Isotope in Benthic Organic Matter 148
6 Field and Biological Quality Evaluation & Assistance 149
6.1 National Coastal Condition Assessment Field Quality Evaluation and Assistance
Visit Plan 149
6.1.1 Preparation Activities 150
6.1.2 Field Day Activities 150
6.1.3 Post Field Day Activities 151
6.1.4 Summary 151
6.2 National coastal condition assessment laboratory quality evaluation and
assistance visit plan 152
6.2.1 Remote Evaluation/Technical Assessment 153
6.2.2 Water Chemistry Laboratories 154
6.2.3 Inter-laboratory Comparison 154
6.2.4 Assistance Visits 155
6.2.5 NCCA 2020 Document Request Form Chemistry Laboratories 155
6.2.6 NCCA 2020 Document Request Form Biology Labs 156
7 Data Analysis Plan 158
7.1 Data Interpretation Background 158
7.1.1 Scale of Assessment 158
7.1.2 Selecting Indicators 159
7.2 Datasets to be used for the Report 159
7.3 Indicators for the Coastal Assessment 159
7.3.1 Water Chemistry and Chlorophyll 159
7.3.2 Benthic Invertebrates 159
7.3.3 Sediment Chemistry/Characteristics 159
7.3.4 Enterococci Data Analysis 160
7.3.5 Fish Chemistry 160
7.3.6 Algal toxins 160
7.4 NCCR Index Development Approach 160
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7.5 Calculation of Population Estimates 160
7.6 Other Change Analyses 160
7.7 Index Precision and Interpretation 161
8 References 162
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List of Tables
Table 1.1 Proposed schedule 42
Table 4.1 Summary of IM responsibilities 54
Table 4.2 Summary of software 61
Table 4.3 Summary sample and field data quality control activities: sample tracking 64
Table 4.4 Summary laboratory data quality control activities 65
Table 4.5 Data review, verification, and validation quality control activities 68
Table 5.1 Description of NCCA 2020 Indicators and location where indicators are collected ....73
Table 5.2 Measurement data quality objectives: water indicators 76
Table 5.3 Field quality control: multiparameter indicator 79
Table 5.4 Data reporting criteria: field measurements 80
Table 5.5 Data Validation Quality Control for In-Situ Indicator 81
Table 5.6 Measurement data quality objectives: water chemistry indicator and chlorophyll a. ...83
Table 5.7 Laboratory Quality Control Samples: Water Chemistry Indicator 84
Table 5.8 Data Reporting Criteria: Water Chemistry Indicator 89
Table 5.9 Sample field processing quality control activities: water chemistry indicator (CHEM).90
Table 5.10 Sample field processing quality control: chlorophyll-a (CHLA) and dissolved nutrient
(NUTS) indicators 90
Table 5.11 Data Validation Quality Control for Water Chemistry Indicator 91
Table 5.12 Measurement Quality Objectives for Cylindrospermopsin 92
Table 5.13 Sample analysis quality control activities and objectives for Cylindrospermopsin ....92
Table 5.14 Sample receipt and processing quality control: Cylindrospermopsin indicator
indicator 94
Table 5.15 Data Reporting Criteria: Cylindrospermopsin Indicator 95
Table 5.16 Sample field processing quality control: Cylindrospermopsin indicator 96
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Table 5.17 Data Validation Quality Control for Cylindrospermopsin Indicator 96
Table 5.18 Measurement Quality Objectives for Microcystins 97
Table 5.19 Sample analysis quality control activities and objectives for microcystins 97
Table 5.20 Sample receipt and processing quality control: microcystins indicator indicator 99
Table 5.21 Data Reporting Criteria: Microcystins Indicator 99
Table 5.22 Sample field processing quality control: microcystins indicator 100
Table 5.23 Data Validation Quality Control for Microcystins Indicator 101
Table 5.24 Benthic Macroinvertebrates: Measurement Data Quality Objectives 103
Table 5.25 Benthic Macroinvertebrates: Laboratory quality control 103
Table 5.26 Sample receipt and processing quality control: benthic invertebrate indicator 104
Table 5.27 Sample Collection and Field Processing Quality Control: Benthic Invertebrate
Indicator 105
Table 5.28 Data Validation Quality Control for Benthic Macroinvetebrates 106
Table 5.29 Sediment Contaminants, Grain size and TOC: Precision and Accuracy Objectives
107
Table 5.30 Sediment Contaminants, Grain Size, and TOC: Analytical Methods 108
Table 5.31 Sediment Contaminants, Grain Size, and TOC: Required Parameters 109
Table 5.32 Sediment Chemistry, Grain Size, and TOC: Quality control activities for samples. 116
Table 5.33 Data Reporting Criteria: Sediment Contaminants, TOC and Grain Size indicators. 120
Table 5.34 Sample collection and field processing quality control: sediment contaminant
indicator 121
Table 5.35 Sample collection and field processing quality control: sediment TOC and grain size
indicator 121
Table 5.36 Data Validation Quality Control for Sediment Contaminants, TOC and Grain Size
Indicators 122
Table 5.37 Quality control activities for sediment toxicity samples
Table 5.38 Data Reporting Review Critera: Sediment Toxicity....
124
126
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Table 5.39 Sample collection and field processing quality control: sediment toxicity indicator. 127
Table 5.40 Data validation quality control: sediment toxicity 127
Table 5.41 Data Validation Quality Control: Fecal Indicator 128
Table 5.42 Sample Collection and Field Processing Quality Control: Fecal Indicator 129
Table 5.43 Whole Fish Tissue: Precision and Accuracy Objectives 130
Table 5.44 Whole Body Fish: Required Contaminants 130
Table 5.45 Whole Body Fish: Quality control activities 134
Table 5.46 Data Reporting Criteria: Eco-Fish Tissue Chemistry 137
Table 5.47 Method quality objectives for field measurement for eco-fish indicator 138
Table 5.48 Field Quality Control: Whole Fish Tissue Samples for Ecological Analysis 138
Table 5.49 Data validation quality control: eco-fish 139
Table 5.50 Data validation quality control: eco-fish tissue indicator 139
Table 5.51 Recommended target species: whole fish tissue collection 141
Table 5.52 Field data types: whole fish tissue samples for fillet analysis 142
Table 5.53 Field quality control: whole fish tissue samples for fillet analysis 142
Table 5.54 Data validation quality control: whole fish tissue samples for fillet analysis 143
Table 5.55 Measurement data quality objectives for mercury in fish tissue plugs 144
Table 5.56 Quality Control for mercury in fish tissue plugs 144
Table 5.57 Data Reporting Criteria: Fish Tissue Plugs 145
Table 5.58 Method quality objectives for field measurement for the fish tissue plug indicator.. 146
Table 5.59 Field Quality Control: Fish Tissue Plug 146
Table 5.60 Data validation quality control: Fish Tissue Plugs 147
Table 6.1 Equipment and Supplies - Field Evaluation and Assistance Visits 150
Table 6.2 Summary of Field Evaluation and Assistance Visit Information 151
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List of Figures
Figure 1.1 NCCA Project Organization and Flow 28
Figure 1.2 NCCA Estuarine Base Sites 32
Figure 1.3 NCCA Great Lakes Coastal Base Sites 33
Figure 1.4 Schedule for the NCCA 2020 34
Figure 1.5 Site Evaluation Diagram 37
Figure 4.1 Conceptual model of data flow into and out of the master SQL 59
Figure 5.1 Field Measurement Process for Water Chemistry Samples 78
Figure 5.2 Analysis Activities for Water Chemistry Samples 82
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Acronyms
ACESD
APHA
ASCII
BOM
CAS
CRM
CSDGM
CV
DDT
DO
DQOs
EMAP
FGDC
FOIA
GC
GEMMD
GLEC
GLTED
GPS
GRTS
ICP
IDL
IM
ITIS
LDR
LRL
LT-MDL
MDLs
MQOs
NARSIMS
NARS
NCA
NCCA
NCCRs
NELAC
NEP
Atlantic Coastal Environmental Sciences Division
American Public Health Association
American Standard Code for Information Interchange
Benthic Organic Matter
Chemical Abstracts Service
Certified Reference Material
Content Standards for Digital Geospatial Metadata
Coefficient of Variation
dichlorodiphenyltrichloroethane
Dissolved Oxygen
Data Quality Objectives
Environmental Monitoring and Assessment Program
Federal Geographic Data Committee
Freedom of Information Act
Gas Chromatograph
Gulf Ecosystem Measurement and Modeling Division Division
Great Lakes Environmental Center, Inc.
Great Lakes Toxicology and Ecology Division
Global Positioning System
Generalized Random Tessellation Stratified
Inductively Coupled Plasma
Instrument Detection Limit
Information Management
Integrated Taxonomic Information System
Linear Dynamic Range
Laboratory Reporting Level
Long-term Method Detection Limit
Method Detection Limits
Measurement Quality Objectives
National Aquatic Resource Surveys Information Management System
National Aquatic Resource Surveys
National Coastal Assessment (past surveys)
National Coastal Condition Assessment (current survey)
National Coastal Condition Reports
National Environmental Laboratory Accreditation Conference
National Estuary Programs
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NHD
NIST
NOAA
NRCC
NWQL
OARM
ORD
OST
OW
OWCD
OWOW
PAHs
PAR
PBDE
PCBs
PE
PESD
PFC
PPT, ppt
PSU
PTD
PTL
QAPP
QA/QC
qPCR
R-EMAP
RSD
SAS
SDTS
SQL
SRM
STORET
SWIMS
TKN
TOC
TSA
US EPA
USGS
National Hydrography Dataset
National Institute of Standards and Technology
National Oceanic and Atmospheric Administration
National Research Council of Canada
National Water Quality Laboratory
Office of Administrative Resource Management
Office of Research and Development
Office of Science and Technology
Office of Water
Oceans, Wetlands and Communities Division
Office of Wetlands, Oceans and Watersheds
Polycyclic Aromatic Hydrocarbons
Photosynthetically Active Radiation
Polybrominated Diphenyl Ethers
Polychlorinated biphenyl
Performance Evaluation
Pacific Ecological Systems Divsion
Perfluorinated compound
parts per thousand
Practical Salinity Unit
Percent Taxonomic Disagreement
Phosphorus, total
Quality Assurance Project Plan
Quality Assurance/Quality Control
quantitative Polymerase Chain Reaction
Regional Environmental Monitoring and Assessment Program
Relative Standard Deviation
Statistical Analysis System
Spatial Data Transfer Standard
Structure Query Language
Standard Reference Material
Storage and Retrieval Data Warehouse
Surface Water Information Management System
Total Kjeldahl Nitrogen
Total Organic Carbon
Technical Systems Audits
United States Environmental Protection Agency
United Stated Geological Survey
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WED Western Ecology Division
WoRMS World Register of Marine Species
WQX Water Quality Exchange
WRAPD Watershed Restoration, Assessment and Protection Division
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Distribution List
This Quality Assurance Protection Plan (QAPP) and associated manuals or guidelines will be distributed
to the following EPA and contractor staff participating in the NCCA and to State Water Quality Agencies
or cooperators who will perform the field sampling operations. The NCCA Project Quality Assurance
(QA) Coordinator will distribute the QA Project Plan and associated documents to participating project
staff at their respective facilities and to the project contacts at participating states, EPA offices,
laboratories and any others, as they are determined.
NCCA
Hugh Sullivan
NCCA Project Leader
sullivan.hughPepa.gov
202-564-1763
U.S. EPA Office of Water
Office of Wetlands, Oceans, and Watersheds
Washington, DC
Danielle Grunzke
NCCA Project QA Coordinator
Grunzke.DaniellePepa.gov
202-566-2876
U.S. EPA Office of Water
Office of Wetlands, Oceans, and Watersheds
Washington, DC
Brian Hasty
NCCA Logistics Coordinator
hastv.brianPepa.gov
202-564-2236
U.S. EPA Office of Water
Office of Wetlands, Oceans, and Watersheds
Washington, DC
Sarah Lehmann
NARS Team Leader
lehmann.sarahPepa.gov
202-566-1379
U.S. EPA Office of Water
Office of Wetlands, Oceans, and Watersheds
Washington, DC
Bern ice Smith
Division Quality Assurance
Coordinator
smith.bernicelPepa.gov
202-566-1244
U.S. EPA Office of Water
Office of Wetlands, Oceans, and Watersheds
Washington, DC
Cynthia Johnson Shimanski,
OWOW
Quality Assurance Officer
iohnson.cvnthiaNfSeoa.gov
202-566-1679
U.S. EPA Office of Water
Office of Wetlands, Oceans, and Watersheds
Washington, DC
Steven G. Paulsen
EPA ORD Technical Advisor
Daulsen.stevefSeoa.gov
541-754-4428
U.S EPA, ORD
Pacific Ecological Systems Division
Corvallis, OR
Lareina Guenzel, Endangered
Species Act (ESA) Lead
Guenzel.lareinafSeoa.gov
202-566-0455
U.S. EPA Office of Water
Office of Wetlands, Oceans, and Watersheds
Washington, DC
Michelle Gover
NARS Information Management
Coordinator
gover.michelle(5)eDa.gov
541-754-4793
Computer Science Corporation
Corvallis, OR 9733
Chris Turner
Contract Logistics Coordinator
cturner(5)glec.com
715-829-3737
Great Lakes Environmental Center
Traverse City, Ml
Leanne Stahl
OST Fish Tissue Coordinator
stahl.leannePepa.gov
202-566-0404
U.S. EPA Office of Water
Office of Science and Technology
Washington, DC
John Healey
OST Fish Tissue QA Coordinator
healev.iohnfSeoa.gov
202-566-0176
U.S. EPA Office of Water
Office of Science and Technology
Washington, DC
David Bolgrien
Great Lakes Enhancements
Coordinator
bolgrien.davidPepa.gov
218-529-5216
U.S. EPA, ORD
Great Lakes Toxicology and Ecology Divsion
Duluth, MN
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Regional Monitoring Coordinators
Tom Faber, Region 1
faber.tomPepa.gov
617-918-8672
U.S. EPA - Region 1
North Chelmsford, MA
Emily Nering, Region 2
nering.emilv (5Jeoa.gov
732-321-6764
USEPA- Region II
Edison, NJ
Bill Richardson, Region 3
richardson.william(5)eDa.gov
215-814-5675
U.S. EPA-Region III
Philadelphia, PA
Chris McArthur, Region 4
mcarthur.christopherPepa.gov
404-562-9391
U.S.EPA- Region IV
Atlanta, GA
Mari Nord, Region 5
nord. marifSeoa. gov
312-353-3017
U.S. EPA-Region V
Chicago, IL
Rob Cook, Region 6
cook.robert(a)eDa.gov
214-665-7141
U.S. EPA-Region VI
Dallas, TX
Terry Fleming, Region 9
fleming.terrencefSeoa.gov
415-972-3452
U.S.EPA - Region IX
San Francisco, CA
Lil Herger, Region 10
herger. lillianfSeoa. gov
206-553-1074
U.S. EPA - Region X,
Seattle, WA
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NCCA Executive Summary
Background
Several recent reports have identified the need for improved water quality monitoring and analysis at
multiple scales. In response, the U.S. EPA Office of Water, in partnership with EPA's Office of Research
and Development (ORD), EPA regional offices, states, tribes and other partners, has begun a program to
assess the condition of the nation's waters using a statistically valid design approach. Often referred to
as probability-based surveys, these assessments, known as the National Aquatic Resource Surveys
(NARS), report on core indicators of water condition using standardized field and lab methods and utilize
integrated information management plans, such as described in this Quality Assurance Project Plan, to
ensure confidence in the results at national and ecoregional scales. NARS is made up of four
assessments: coastal, lakes, rivers and streams, and wetlands.
NCCA, which builds upon previous National Coastal Assessments led by ORD and the National Coastal
Condition Assessment in 2010 and 2015, aims to address three key questions about the quality of the
Nation's coastal waters:
What percent of the Nation's coastal waters are in good, fair, and poor condition for key indicators
of water quality, ecological health, and recreation?
What is the relative extent of key stressors such as nutrients and pathogens?
How are conditions in coastal waters changing over time?
NCCA is also designed to help expand and enhance state monitoring programs. Through these surveys,
states and tribes have the opportunity to collect data which can be used to supplement their existing
monitoring programs or to begin development of new NCCA programs.
NCCA Project Organization
Overall project coordination is conducted by EPA's Office of Water (OW) in Washington, DC, with
technical support from EPA's ORD. Each of the coastal EPA Regional Offices has identified regional
coordinators to assist in implementing the survey and coordinate with the state crews who collect the
water and sediment samples following NCCA protocols. As in 2010 and 2015, the Office of Science and
Technology (OST) within OW is conducting the human health fish tissue study in the Great Lakes in
partnership with the Great Lakes National Program Office. Region 5, ORD Great Lakes Toxicology and
Ecology Division, and the Great Lakes National Program Office are collaborating with the Office of Water
on enhancement studies of Green Bay, Great Lakes Islands and National Parks, and a Lake Erie Special
Sudy.
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Quality Assurance Project Plan
The purpose of this QAPP is to document the project data quality objectives and quality
assurance/quality control measures that will be implemented in order to ensure that the data collected
meets those needs. The plan contains elements of the overall project management, data quality
objectives, measurement and data acquisition, and information management for the NCCA.
Information Management Plan
Environmental monitoring efforts that amass large quantities of information from various sources
present unique and challenging data management opportunities. To meet these challenges, the NCCA
employs a variety of well-tested information management (IM) strategies to aid in the functional
organization and ensured integrity of stored electronic data. IM is integral to all aspects of the NCCA
from initial selection of sampling sites through the dissemination and reporting of final, validated data.
A technical workgroup convened by the EPA Project Leader is responsible for development of a data
analysis plan that includes a verification and validation strategy. General processes are summarized in
the indicator-specific sections of this QAPP. Validated data are transferred to the central data base
managed by EMAP information management support staff located at the Pacific Ecological Systems
Division facilities in Corvallis. This database is known as the National Aquatic Resource Surveys
Information Management (NARS IM) system. All validated measurement and indicator data from the
NCCA are eventually transferred to EPA's Water Quality Exchange (WQX) for storage in EPA's STORET
warehouse for public accessibility. NARS IM staff provides support and guidance to all program
operations in addition to maintaining NARS IM.
Overview of NCCA Design
The NCCA is designed to be completed during the index period of June through the end of September
2020. EPA used an unequal probability design to select 725 estuarine sites along the coasts of the
continental United States and 225 freshwater sites from the shores of the Great Lakes. As in previous
NCCA surveys, enhancement studies will occur in the Great Lakes. The enhancement studies planned for
2020 are: Green Bay/Lake Michigan enhancement, a Lake Erie Basin Special Study, and a combined
National Park Service and Great Lakes Islands enhancement. Additionally, related sampling will occur on
reef flat (coastal areas) of American Samoa, Guam and the Northern Mariana Islands. More information
can be found in Section 1.4 (Project Design) and Section 3.3 (Site Selection) of this QAPP.
Overview of Field Operations
Field data acquisition activities are implemented in a consistent manner across the entire country. Each
site is given a unique ID which identifies it throughout the pre-field, field, lab, analysis, and data
management phases of the project. Specific procedures for evaluating each sampling location and for
replacing non-sampleable sites are documented in NCCA 2020: Site Evaluation Guidelines.
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NCCA indicators include nutrients, light attenuation, sediment chemistry, sediment toxicitybenthic
communities, fish tissue contaminants, algal toxins (microcystins and cylindrospermopsin), mercury in
fish fillet tissue and pathogens. Research indicators for the NCCA 2020 are nitrogen isotopes in benthic
organic matter, microplastics in sediment, and total alkalinity. Field measurements and samples are
collected by trained teams following sampling methods described in the NCCA 2020: Field Operations
Manual.. The field team leaders must be trained at an EPA-sponsored training session. Field sampling
assisstance visits will be completed for each field team.
Overview of Laboratory Operations
NCCA laboratory analyses are conducted either by state-selected labs or "National Laboratories"
contracted by EPA to conduct analyses for any state which so elects. All laboratories must comply with
the QA/QC requirements described in this document. Any laboratory selected to conduct analyses with
NCCA samples must demonstrate that they can meet the quality standards presented in this QAPP and
the NCCA 2020: Laboratory Methods Manual.
Peer Review
The NARS program, including the NCCA, utilizes a three-tiered approach for peer review of the Survey.
ฆ internal and external review by USEPA, states, other cooperators and partners;
ฆ external scientific peer review (when applicable); and
ฆ public review (when applicable).
Additioanlly, cooperators have been actively involved in the development of the overall project
management, design, indicator selection, and methods. Outside scientific experts from universities,
research centers, and other federal agencies have been instrumental in indicator development and will
continue to play an important role in data analysis.
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1 Project Planning and Management
1.1 Introduction
Several recent reports have identified the need for improved water quality monitoring and analysis at
multiple scales. In 2000, the General Accounting Office (USGAO 2000) reported that EPA, states, and
tribes collectively cannot make statistically valid inferences about water quality (via 305[b] reporting)
and lack data to support key management decisions. In 2001, the National Research Council (NRC 2000)
recommended EPA, states, and tribes promote a uniform, consistent approach to ambient monitoring
and data collection to support core water quality programs. In 2002, the H. John Heinz III Center for
Science, Economics, and the Environment (Heinz Center 2002) found there is inadequate data for
national reporting on fresh water, coastal and ocean water quality indicators. The National Association
of Public Administrators (NAPA 2002) stated that improved water quality monitoring is necessary to help
states and tribes make more effective use of limited resources. EPA's Report on the Environment 2003
(USEPA 2003) said that there is not sufficient information to provide a national answer, with confidence
and scientific credibility, to the question, 'What is the condition of U.S. waters and watersheds?'
In response to this need, the Office of Water (OW), in partnership with states and tribes, initiated a
program to assess the condition of the nation's waters via a statistically valid approach. The current
assessment, the National Coastal Condition Assessment 2020 (referred to as NCCA 2020 throughout this
document), builds upon the National Coastal Condition Assessment 2010 and the original National
Coastal Assessments implemented by EPA's Office of Research and Development, state and other
partners. It also builds on other National Aquatic Resource Surveys (NARS) surveys such as the National
Lakes Assessment (NLA), the National Rivers and Streams Assessment (NRSA) and the National Wetland
Condition Assessment (NWCA). The NCCA 2020 effort will provide important information to states and
the public about the condition of the nation's coastal waters and key stressors on a national and
regional scale. It will also provide a trends assessment between five time periods: 2000-2001; 2005-
2006; 2010; 2015 and 2020.
EPA developed this QAPP to support project participants and to ensure that the final assessment is
based on high quality data and known quality for its intended use, and information. The QAPP contains
elements of the overall project management, data quality objectives, measurement and data
acquisition, and information management for NCCA 2020. EPA recognizes that states and tribes may add
elements to the survey, such as supplemental indicators, that are not covered in the scope of this
integrated QAPP. EPA requires that any supplemental elements are addressed by the states, tribes, or
their designees, in a separate approved QAPP. This document covers all core NCCA QA activities. The
NCCA 2020 participants have agreed to follow this QAPP and the protocols and design laid out in this
document, and its associated documents - the NCCA 2020 Field Operations Manual (FOM), Lab
Operations Manual (LOM), and Site Evaluation Guidelines (SEG).
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This cooperative effort between states, tribes, and federal agencies makes it possible to produce a
broad-scale assessment of the condition of the Nation's coastal waters with both a known confidence
and scientific credibility. Through this survey, states and tribes have the opportunity to collect data that
can be used to supplement their existing monitoring programs or to begin development of new
programs.
The NCCA 2020 has three main objectives:
ฆ Estimate the current status, trends, and changes in selected trophic, ecological, and
recreational indicators of the condition of the nation's coastal waters with known
statistical confidence;
ฆ Identify the relative importance of key stressors; and
ฆ Assess changes and trends from the earlier National Coastal Assessments and the NCCA
2010 and 2015.
Indicators for the 2020 survey will remain basically the same as those used in the past surveys, with a
few modifications. This is critical so that EPA and partners can track not only condition but changes over
time in the quality of coastal water resources. Modifications include expanding the area in which crews
can collect samples to reduce the amount of missing data. In 2020, EPA and partneres are adding the
algal toxin cylindropsermopsin, as well as three research indicators: nitrogen isotopes in benthic organic
matter at all estuarine sites, total alkalinity at all estuarine sites, and microplastics in sediments at select
estuarine sites in the northeast.
In the Great Lakes, The Office of Science and Technology (OST), in partnership with the Great Lakes
National Program Office (GLNPO) is conducting an human health fish tissue study for the third time.
Region 5, GLNPO and ORD's Great Lakes Toxicology and Ecology Division are teaming up to conduct
enhanced assessments in the Great Lakes that add sites to the overall number of sites within the Great
Lakes, but will otherwise follow procedures as outlined in the QAPP and other NCCA documents. See
section 1.4 for more information.
1.2 Scope of the Quality Assurance Project Plan
This QAPP addresses the data acquisition efforts of NCCA, which focuses on the 2020 sampling of coasts
across the United States. Data from approximately 950 coastal sites (selected with a probability design)
located along the contiguous coastal marine and Great Lakes states will provide a comprehensive
assessment of the Nation's coastal waters. Additionally, EPA is conducting special studies as described
above. Companion documents to this QAPP that are relevant to the overall project include:
National Coastal Condition Assessment 2020: Field Operations Manual (EPA 841-F-19-005)
National Coastal Condition Assessment 2020: Laboratory Methods Manual (EPA 841-F-19-004)
National Coastal Condition Assessment 2020: Site Evaluation Guidelines (EPA 841-F-20-
001)
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1.3 Project Organization
The responsibilities and accountability of the various principals and cooperators are described here and
illustrated in Figure 1.1. Overall, the project will be coordinated by the Office of Water (OW) in
Washington, DC, with support from EPA Office of Research and Development (ORD.) Specifically, OW is
working with ORD's Pacific Ecological Systems Divsion (PESD), the EPA Gulf Ecolosystem Measurement
and Modeling Division (GEMMD), the EPA Atlantic Coastal Environmental Sciences Division (ACESD) and
the Great Lakes Toxicology and Ecology Division (GLTED). Each EPA Regional Office has identified a
Regional EPA Coordinator who is part of the EPA team providing a critical link with state and tribal
partners. Cooperators will work with their Regional EPA Coordinator to address any technical issues. A
comprehensive quality assurance (QA) program has been established to ensure data integrity and
provide support for the reliable interpretation of the findings from this project.
Contractor support is provided for all aspects of this project. Contractors will provide support ranging
from implementing the survey, sampling and laboratory processing, data management, data analysis,
and report writing. Cooperators will interact with their Regional EPA Coordinator and the EPA Project
Leader regarding contractual services.
The primary responsibilities of the principals and cooperators are as follows:
Project Leader: Hugh Sullivan, EPA Office of Water
Provides overall coordination of the project and makes decisions regarding the proper functioning of
all aspects of the project.
Makes assignments and delegates authority, as needed to other parts of the project organization.
Leads the NCCA Steering Committee and establishes needed technical workgroups.
Interacts with EPA Project Team on technical, logistical, and organizational issues on a regular basis.
EPA Field Logistics Coordinator: Brian Hasty, EPA Office of Water
EPA employee who functions to support implementation of the project based on technical guidance
established by the EPA Project Leader and serves as point-of-contact. for questions from field crews
and cooperators for all activities.
Tracks progress of field sampling activities.
EPA Project OA Coordinator: Danielle Grunzke, EPA Office of Water
Provides leadership, development, and oversight of project-level quality assurance for NARS.
Assembles and provides leadership for a NCCA 2020 Quality Team.
Maintains official, approved QAPP.
Maintains all training materials and documentation.
Maintains all laboratory accreditation files.
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Project Management
Project Lead: Hugh Sullivan, EPA-OW
Project QA Coordinator: Danielle Grunzke. EPA-OW
Technical Advisor: Steve Paulsen, EPA-ORD
Study Design
Tony Olsen EPA-ORD
Field Logistics
Implementation C oordinator
Training
EPA OW, ORD and Regions,
Contractors
OWOWQA
Oversight/Review
Cynthia Simanski
Field Protocols/Indicator
Selection
EPA OW and ORD
State/Tribal
Steering Committee
Field Implementation
State/Tribal Water Quality Agencies,
EPA ORD/Regions, Contractors
Select Indicator Leads
HH Fish Tissue - Learine Stalil. EPA-OW
GL Enhancements - David Bolgrien, EPA-ORD
Sample Flow
Nutrients Lab
Macroinvertebrate
Lab
Sediment Toxicity
Lab
Ecological fish
Lab
Sediment Chem
Lab
Pathogens
Lab
Algal Toxin
Lab
Fish Plug
Lab
Pliytoplakton
Lab (GL only)
Research
Indicator
Labs
Human Health
Lab (Subset of
GLsites only)
NCCA Project and Quality
Team
I
Information Management
PESD/SRA-Michelle Gover
Final Data
STORET/WQX - OW
Assessment
EPA-OW Lead
EPA ORD and Regions,
States, Tribes,
Cooperators and other partners
HH Fish Tissue
QAPP
Learme Stahl Lead
Figure 1.1 NCCA Project Organization and Flow
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EPA Technical Advisor: Steven Paulsen, EPA Office of Research and Development
Advises the Project Leader on the relevant experiences and technology developed within the Office
of Research and Development (ORD) that may be used in this project.
Facilitates consultations between NCCA personnel and ORD scientists.
Laboratory Review Coordinator: Kendra Forde, EPA Office of Water
Ensures participating laboratories complete sample analysis following LOM.
Ensures participating laboratories follow QA activities.
Ensures data submitted within the specified timelines.
Coordinates activities of individual lab Task Order Project Officers to ensure methods are followed
and QA activities take place.
QA Assistance Visit Coordinator: Brian Hasty, EPA Office of Water
The EPA employee who will supervise the implementation of the QA audit program; and
Directs the field and laboratory audits and ensures the field and lab auditors are adequately trained
to correct errors immediately to avoid erroneous data and the eventual discarding of information
from the assessment.
Human Health Fish Tissue Indicator Lead: Leanne Stahl, EPA Office of Water
The EPA Employee who will coordinate implementation of the human health fish tissue effort on the
Great Lakes;
Interacts with the EPA Project Leads, EPA regional coordinators, contractors and cooperators to
provide information and respond to questions related to the human health fish tissue indicator; and
Responsible for lab analysis phase of the project.
Great Lakes Enhancement Coordinator: Dave Bolgrien, EPA Office of Research and
Development
The EPA Employee who will coordinate the embayment enhancement component of the Great
Lakes NCCA; and
Interacts with the EPA Project Leads, EPA regional coordinators, contractors and cooperators to
provide information and respond to questions related to embayment enhancement effort.
Information Management Coordinator Michelle Gover, SRA International, Inc.
A contractor who functions to support implementation of the project based on technical guidance
established by the EPA Project Leader and Alternate EPA Project Leader.
Under scope of the contract, oversees the NARS Information Management team.
Oversees all sample shipments and receives data forms from the Cooperators.
Oversees all aspects of data entry and data management for the project.
OWOW QA Officer: Cynthia Simanski, EPA Office of Water
Functions as an independent officer overseeing all quality assurance (QA) and quality control (QC)
activities.
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Responsible for ensuring that the QA program is implemented thoroughly and adequately to
document the performance of all activities.
Endangered Species Act (ESA) Lead: Lareina Guenzel, EPA Office of Water
Primary ESA contact for the U.S. Fish and Wildlife Service (FWS) and National Oceanic and
Atmospheric Administration, National Marine Fisheries Service (NOAA/NMFS).
Works with the EPA Project Lead to ensure that survey manuals and protocols include appropriate
responses and reporting requirements in the event that a crew encounters federally listed species
when conducting field work.
Prepares the Biological Evaluation to support Section 7 consultations.
Works with the survey logistics lead to implement the conservation measures, reasonable and
prudent measures, and reporting requirements identified in the Biological Opinion.
Maintains library of NCCA ESA documents.
Regional EPA Coordinators
Assists EPA Project Leader with regional coordination activities.
Serves on the Technical Experts Workgroup and interacts with Project Facilitator on technical,
logistical, and organizational issues on a regular basis.
Serves as primary point-of-contact for the Cooperators.
Steering Committee (Technical Experts Workgroup): States, EPA, academics, other federal
agencies
Provides expert consultation on key technical issues as identified by the EPA Coordination crew and
works with Project Facilitator to resolve approaches and strategies to enable data analysis and
interpretation to be scientifically valid.
Cooperator(s): States, Tribes, USGS, others
Under the scope of their assistance agreements, plans and executes their individual studies as part
of the cross jurisdictional NCCA 2013/14 and adheres to all QA requirements and standard operating
procedures (SOPs).
Interacts with the Grant Coordinator, Project Facilitator and EPA Project Leader regarding technical,
logistical, organizational issues.
Field Sampling Crew Leaders
Functions as the senior member of each Cooperator's field sampling crew and the point of contact
for the Field Logistics Coordinator.
Responsible for overseeing all activities of the field sampling crew and ensuring that the Project field
method protocols are followed during all sampling activities.
National Laboratory Task Order Managers: EPA Office of Water
EPA staff responsible for managing activities of the national contract laboratories.
Provide direction to national and State labs on methods, timelines and QA activities to ensure all
actions are followed.
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Provide updates to EPA Laboratory Review Coordinator, the EPA QA Project Lead, and the Project
Leader on the sample processing status of labs and any questions or concerns raised by participating
labs in regards to timelines and deliverables.
Field Logistics Coordinator: Chris Turner, Great Lakes Environmental Center
A contractor who functions to support implementation of the project based on technical guidance
established by the EPA Field Logistics Coordinator and the Project Leader.
Serves as point-of-contact for questions from field crews and cooperators for all activities.
Tracks progress of field sampling activities.
1.4 Project Design
The NCCA 2020 is designed to be completed during the index period of June through the end of
September 2020. Field crews will collect a variety of measurements and samples from predetermined
sampling locations (located with an assigned set of coordinates).
With input from the states and other partners, EPA used an unequal probability design to select 725
estuarine sites along the coasts of the continental United States. The design for the Great Lakes has 225
nearshore sites. See maps of estuarine and Great Lakes sites in Figure 1.2 and Figure 1.3, respectively.
Other EPA programs are conducting special studies in the Great Lakes in partnership with the NCCA:
The Office of Science and Technology (OST) within OW is conducting a human health fish tissue
study in partnership with the Great Lakes National Program Office at all 225 sites in the Great
Lakes NCCA. A brief description of the study is provided in Section Error! Reference source not
found..
Region 5, GLNPO and ORD's Great Lakes Toxicology and Ecology Division in Duluth, MN are
teaming up to conduct enhanced assessments in the Great Lakes that add sites to the overall
number of sites within the Great Lakes but will otherwise follow procedures as outlined in the
QAPP and other NCCA documents.
o Green Bay and Lake Michigan Enhancement
o Lake Erie Basin Special Study, which adds sites to be sampled (for water only) so that 30
total sites are sampled in each of the Lake Erie Basins
o a combined National Park Service and Great Lakes Islands enhancement, which samples
an additional Great Lakes Island and National Park Service Sites.
Additionally, NCCA-related sampling will occur in reef flat (coastal areas) of American Samoa, Guam and
the Northern Mariana Islands, during the 2020 field season.
For more information about the primary and enhancement survey designs, please see Section 3.
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1.5 Project Schedule
Training and field sampling will be conducted in spring and summer of 2020. Sample processing and data
analysis are planned for 2021 to support publication of results in 2022 (planned). Figure 1.4 gives an
overview of the major tasks leading up to the final report.
2018 2019 2020 2021 2022
research
design
Field
lab / data
report
survey planning
-
pilot studies
-
select indicators
-
-
design frame
-
select sites
-
implementation
manuals
-
-
field training
-
sampling season
-
sample processing
data analysis
"
draft results and/or
report
peer review
-
final results and/or
report
Figure 1.4 Schedule for the NCCA 2020
1.6 Overview of Field Operations
Field data acquisition activities are implemented for the NCCA, based on guidance originally developed
for the NCA and for the NCCA 2010 and 2015 surveys. Funding for states and tribes to conduct field
data collection activities are provided by EPA under Section 106 of the Clean Water Act. Survey
preparation is initiated with selection of the sampling locations by the Design Team (ORD in Corvallis).
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The Design Team gives each site a unique ID which identifies it throughout the pre-field, field, lab,
analysis, and data management phases of the project. The Project Lead distributes the list of sampling
locations to the EPA Regional Coordinators, states, and tribes. With the sampling location list, state and
tribal field crews can begin site reconnaissance on the primary sites and alternate replacement sites and
begin work on obtaining access permission to each site. EPA provides specific procedures for evaluating
each sampling location and for replacing non-sampleable sites in NCCA: Site Evaluation Guidelines. Each
crew is responsible for procuring, as needed, scientific collecting permits from State/Tribal and Federal
agencies, and if necessary, permission from landowners. The field teams will use standard field
equipment and supplies as identified in the Equipment and Supplies List (Appendix A of the Field
Operations Manual). Field crews will work with Field Logistics Coordinators to coordinate equipment
and supply requests. This helps to ensure comparability of protocols across all crews. EPA has
documented detailed lists of equipment required for each field protocol, as well as guidance on
equipment inspection and maintenance, in the Field Operations Manual.
Field measurements and samples are collected by trained teams/crews. The field crews leaders must be
trained at an EPA-sponsored training session. Ideally, all members of each field crews should attend one
EPA-sponsored training session before the field season. The training program stresses hands-on
practice of methods, consistency among crews, collection of high quality data and samples, and safety.
Training documentation will be maintained by the Project QA Coordinator. Field Crew leaders will
maintain records indicating that members of their team that did not attend and EPA training were
properly trained to follow the NCCA protocols. Field crew leaders will provide EPA with this
documentation if requested by the NCCA Project Leader or QA Coordinator. EPA or other designated
personnel (e.g. contractors) will conduct field sampling assistance visits for each field crew early in the
sampling season.
For each site, crews prepare a dossier that contains the following applicable information: road maps;
copies of written access permissions to boat launches; scientific collection permits; per field crew's
standard operating procedures, information on federally listed species that may occur at the site, how
to avoid them, and actions to be taken if they are encountered; coordinates of the coastal site;
information brochures on the program for interested parties; and local area emergency numbers.
Whenever possible, field crews leaders attempt to contact owners of private marinas or boat launches
(as appropriate) approximately two days before the planned sampling date. As the design requires
repeat visits to select sampling locations, it is important for the field crews to do everything possible to
maintain good relationships with launch owners. This includes prior contacts, respect of special
requests, closing gates, minimal site disturbance, and removal of all materials, including trash,
associated with the sampling visit.
The site verification process is shown in Figure 1.5. Upon arrival at a site, crews verify the location by a
Global Positioning System (GPS) receiver, landmark references, and/or local residents. Crews collect
samples and measurements for various parameters in a specified order (See the Field Operations
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Manual). This order has been set up to minimize the impact of sampling for one parameter upon
subsequent parameters. All methods are fully documented in step-by-step procedures in the NCCA Field
Operations Manual. The manual also contains detailed instructions for completing documentation,
labeling samples, any field processing requirements, and sample storage and shipping. Field
communications will be through Field Logistics Coordinator and may involve regularly scheduled
conference calls or contacts.
After field sampling is complete (and wifi available), crews will submit all completed data forms in the
NCCA App. If still reviewing data forms, the Site Verification and Tracking Forms (for any shipped
samples) must be submitted if samples are shipped. All submitted data will be sent back to the field
crew in a summary email from the database to the field crew's iPad.
Crews store and package samples for shipment in accordance with instructions contained in the Field
Operations Manual. EPA developed the NCCA shipping instructions so that sample holding times are not
exceeded. Samples which must be shipped are delivered to a commercial carrier; copies of bills of
lading or other documentation are maintained by the team. Crews notify the Information Management
Coordinator, as outlined in the FOM, that shipment has occured; thus, tracing procedures can be
initiated quickly in the event samples are not received. Crews complete chain-of-custody forms for all
transfers of samples, with copies maintained by the field team.
The field operations phase is completed with collection of all samples or expiration of the sampling
window. Following the field seasons, EPA and the contractor field logisitcs coordinator will hold
debriefings with crews and other project staff which cover all aspects of the field program and solicit
suggestions for improvements.
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Figure 1.5 Site Evaluation Diagram
* If you need access to the SharePoint site, please send an email to Brian Hasty (hasty.brian@epa.gov),Kendra Forde
(forde.kendraPepa.gov) and cc: Hugh Sullivan (sullivan.hughPepa.gov). If you are having trouble with the SharePoint site, you
may email interim and final spreadsheets to the Contract Logistics Coordinator and your P.egional Coordinator (see page 19 for
contact information).
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1.7 Overview of Laboratory Operations
Holding times for surface water samples vary with the sample types and analyte. Field crews begin some
analytical measurements during sampling (e.g., in situ measurements) while other analytical
measurements are not initiated until sampling has been completed (e.g., water chemistry, microcystins,
fecal indicators (Enterococci)). Analytical methods are summarized in the NCCA 2020 Laboratory
Operations Manual (LOM). When available, standard methods are used and are referenced in the LOM.
Where experimental methods are used or standard methods are modified by the laboratory, these
methods are documented in the laboratory methods manual by EPA or in internal documentation by the
appropriate laboratory. The laboratory coordinator will work with appropriate experts to describe them
in Standard Operating Procedures (SOPs) developed by the analytical laboratories.
Contractor and/or cooperator laboratories will perform chemical, physical, and biological
analyses. National contract labs will process most samples. Where those labs are currently in place,
EPA has identified the prime contractor here.
Dynamac, a lab managed by the ORD Western Ecology Division, will analyze water chemistry and
chlorophyll-a samples.
Great Lakes Environmental Center, a national contractor,will analyze benthic invertebrates.
Great Lakes Environmental Center, a national contractor, will analyze sediment chemistry.
Avanti, a national contractor will analyze sediment toxicity.
Great Lakes Environmental Center, a national contractor, will analyze whole fish tissue samples.
ESS Group, Inc., a national contractor, will analyze fish tissue plugs.
Great Lakes Environmental Center, a national contractor, will analyze algal toxin samples.
EPA's Office of Research and Development lab in Cincinnati, OH will analyze samples for
enterococci.
Tetratech and CSRA, national contractors, will prepare and analyze fish tissue fillet samples for
the Great Lakes Human Health Fish Sillet Tissue Study for the Office of Science and Technology.
EPA anticipates that a few pre-approved state labs may opt to analyze samples for various non-
research indicators.
Labs analyzing research indicator samples:
ORD-AESCD, Narragansett, Rl: microplastics in sediment; nitrogen isotope in benthic organic
matter; and approximately half of the total alkalinity samples.
ORD-PESC, Newport, OR: The remaining half of the total alkalinity samples.
Laboratories providing analytical support must have the appropriate facilities to properly store and
prepare samples and appropriate instrumentation and staff to provide data of the required quality
within the time period dictated by the project. Laboratories are expected to conduct operations using
good laboratory practices. The following are general guidelines for analytical support laboratories:
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A program of scheduled maintenance of analytical balances, water purification systems,
microscopes, laboratory equipment, and instrumentation.
Verification of the calibration of analytical balances using class "S" weights which are
certified by the National Institute of Standards and Technology (NIST)
(http://www.nist.gov/).
Verification of the calibration of top-loading balances using NIST-certified class "P"
weights.
Checking and recording the composition of fresh calibration standards against the
previous lot of calibration standards. Participating laboratories will keep a percentage of
the previous lot of calibration standard to check against the next batch of samples
processed. This will ensure that a comparison between lots can occur. Acceptable
comparisons are less than or equal to two percent of the theoretical value. (This
acceptance is tighter than the method calibration criteria.)
Recording all analytical data in bound logbooks in ink, or on standardized recording
forms.
Verification of the calibration of uniquely identified daily use thermometers using NIST-
certified thermometers.
Monitoring and recording (in a logbook or on a recording form) temperatures and
performance of cold storage areas and freezer units (where samples, reagents, and
standards may be stored). During periods of sample collection operations, monitoring
must be done on a daily basis.
An overall program of laboratory health and safety including periodic inspection and
verification of presence and adequacy of first aid and spill kits; verification of presence
and performance of safety showers, eyewash stations, and fume hoods; sufficiently
exhausted reagent storage units, where applicable; available chemical and hazardous
materials inventory; and accessible material safety data sheets for all required
materials.
An overall program of hazardous waste management and minimization, and evidence of
proper waste handling and disposal procedures (90-day storage, manifested waste
streams, etc.).
If needed, having a source of reagent water meeting American Society of Testing and
Materials (ASTM) Type I specifications for conductivity (< 1 piS/cm at 25 ฐC; ASTM 2011)
available in sufficient quantity to support analytical operations.
Appropriate microscopes or other magnification for biological sample sorting and
organism identification.
Approved biological identification and taxonomic keys/guides for use in biological
identification (benthic macroinvertebrates) as appropriate.
Labeling all containers used in the laboratory with date prepared contents, and initials
of the individual who prepared the contents.
Dating and storing all chemicals safely upon receipt. Chemicals are disposed of properly
when the expiration date has expired.
Using a laboratory information management system to track the location and status of
any sample received for analysis.
Reporting results electronically using standard formats and units compatible with NARS
IM (see LOM for data templates). These files will be labeled properly by referencing the
indicator and/or analyte and date (see the LOM for file naming convention).
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All laboratories providing analytical support to NCCA 2020 must adhere to the provisions of this
integrated QAPP and LOM. Laboratories will provide information documenting their ability to conduct
the analyses with the required level of data quality prior to data analysis. Different requirements will be
provided based on the type of analysis being completed by the laboratory (i.e. chemistry vs. biological
analyses).
Laboratories will send the documentation to the Project Quality Assurance Coordinator and the
Laboratory Review Coordinator at EPA Headquarters (or other such designated parties). The Project QA
Coordinator will maintain these files in NCCA QA files. Such information may include the following:
ฆ Signed Quality Assurance Project Plan by the laboratory performing analysis;
ฆ Signed Laboratory Form;
ฆ Valid Accreditation or Certification;
ฆ Laboratory's Quality Manual and/or Data Management Plan;
ฆ Method Detection Limits (MDL);
ฆ Demonstration of Capability;
ฆ Results from inter-laboratory comparison studies;
ฆ Analysis of performance evaluation samples; and
ฆ Control charts and results of internal QC sample or internal reference sample analyses
to Document achieved precision, bias, accuracy.
ฆ Participation in calls regarding laboratory procedures and processes with participating
laboratories;
ฆ Participation in a laboratory technical assessment or audit;
ฆ Participation in performance evaluation studies; and
ฆ Participation in inter-laboratory sample exchange.
1.7.1 Chemistry Lab Quality Evaluation
Participating laboratories will send requested documentation to the NCCA 2020 QA Team for evaluation
of qualifications. The NCCA 2020 QA Team will maintain these records in the project QA file.
1.7.2 Biological Laboratory Quality Evaluation
The NCCA 2020 Quality Team will review the past performance of biological laboratories. The biological
laboratories shall adhere to the quality assurance objectives and requirements as specified for the
pertinent indicators in the LOM.
See Section 6 of this QAPP and Appendix A of the LOM for additional information related to laboratory
certification. All qualified laboratories shall work with the NARS IM Center to track samples as specified
by the NARS Information Managment Lead.
Other requirements may include:
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1.8 Data Analysis
A technical workgroup convened by the EPA Project Leader is responsible for development of a data
analysis plan that includes a verification and validation strategy. General processes are summarized in
the indicator-specific sections of this QAPP. The NCCA Quality team transfers validated data to the
central data base managed by EMAP information management support staff located at WED in Corvallis.
Information management activities are discussed further in Section 4. Data in the WED data base are
available to Cooperators for use in development of indicator metrics. EPA will transfer all validated
measurement and indicator data from the NCCA to EPA's Water Quality Exchange (WQX) for storage in
EPA's STORET warehouse for public accessibility. Additionally, the NCCA team maintains data files on
the internal project SharePoint site for partners and on the NCCA website for public accessibility. The
Data Analysis plan is described in Section 7 of this QAPP.
1.9 Peer Review
The USEPA NARS program, including the NCCA 2020, utilizes a three-tiered approach for peer review of
the Survey: (1) internal and external review by EPA, states, other cooperators and partners, (2) external
scientific peer review, when applicable, and (3) public review, when applicable.
Once data analysis has been completed, cooperators examine the results. The NCCA team reviews
comments and feedback from the cooperators and incorporate such feedback into the draft report,
when appropriate. The NCCA Team follows Agency and OMB requirements for public and peer
review. External scientific peer review and public review is initiated for new analyses or approaches as
appropriate. Additionally, following applicable guidance, other aspects of the NCCA may undergo public
and scientific peer review.
ฆ Follow the Agency's Information Quality Guidelines (IQG) and complete the IQG checklist.
ฆ Develop and maintain a public website with links to standard operating procedures, quality
assurance documents, fact sheets, scientific peer review feedback, and final report.
ฆ Conduct technical workgroup meetings composed of scientific experts, cooperators, and
EPA to evaluate and recommend data analysis options and indicators.
ฆ Complete data validation on all chemical, physical and biological data.
ฆ Conduct final data analysis with workgroup to generate assessment results.
ฆ Engage peer review contractor to identify external peer review panel (if applicable).
ฆ Develop draft report presenting assessment results.
ฆ Develop final draft report incorporating input from cooperators and results from data
analysis group to be distributed for peer a review.
ฆ Issue Federal Register (FR) Notice announcing document availability and hold public
comment (30-45 days) (if applicable).
ฆ Consider public comments and produce a final report (if applicable).
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The proposed peer review schedule is provided below in Table 1.1 and is contingent upon timeliness of
data validation and schedule availability for regional meetings and experts for data analysis workshop.
Table 1.1 Proposed schedule
Proposed Schedule
Activity
May 2020-November 2021
Data validation
November 2021-June 2022
Internal data analysis and review meetings (e.g., web conferences)
Summer 2022
Draft released for external peer review (if applicable)
December 2022
Draft released for public review (if applicable)
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2 Data Quality Objectives
It is a policy of the U.S. EPA that Data Quality Objectives (DQOs) be developed for all environmental data
collection activities following the prescribed DQO Process. DQOs are qualitative and quantitative
statements that clarify study objectives, define the appropriate types of data, and specify the tolerable
levels of potential decision errors that will be used as the basis for establishing the quality and quantity
of data needed to support decisions (EPA 2006B). Data quality objectives thus provide the criteria to
design a sampling program within cost and resource constraints or technology limitations imposed upon
a project or study. DQOs are typically expressed in terms of acceptable uncertainty (e.g., width of an
uncertainty band or interval) associated with a point estimate at a desired level of statistical confidence.
The DQO Process is used to establish performance or acceptance criteria, which serve as the basis for
designing a plan for collecting data of sufficient quality and quantity to support the goals of a study. As
a rule, performance criteria represent the full set of specifications that are needed to design a data or
information collection effort such that, when implemented, generate newly-collected data that are of
sufficient quality and quantity to address the project's goals. Acceptance criteria are specifications
intended to evaluate the adequacy of one or more existing sources of information or data as being
acceptable to support the project's intended use (EPA 2006B).
2.1 Data Quality Objectives for the National Coastal Condition Assessment
NCCA has established target DQOs for assessing the current status of selected indicators of condition
for the conterminous U.S.coastal resources as follows:
For each indicator of condition, estimate the proportion of the nation's estuaries and
combined area of the Great Lakes in degraded condition within a ฑ 5% margin of error and
with 95% confidence.
For each indicator of condition, estimate the proportion of regional estuarine (Northeast,
Southeast, Gulf of Mexico, and West Coast) or Great Lake resources in degraded condition
within a ฑ 15% margin of error and with 95% confidence.
For estimates of change, the DQOs are: Estimate the proportion of the nation's estuaries and
combined area of the Great Lakes (ฑ 7%) that have changed condition classes for selected
measures with 95% confidence.
2.2 Measurement Quality Objectives
For each parameter, performance objectives (associated primarily with measurement error) are
established for several different data quality indicators (following USEPA Guidance for Quality
Assurance Plans EPA240/R-02/009). Specific measurement quality objectives (MQOs) for each
parameter are shown in chapter 5 of this QAPP and in the LOM. The following sections define the
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data quality indicators and present approaches for evaluating them against acceptance criteria
established for the program.
2.2.1 Method Detection Limits (Laboratory Reporting Level (Sensitivity))
For chemical measurements, requirements for the MDL are typically established (see indicators in
Section 5). The MDL is defined as the lowest level of analyte that can be distinguished from zero with
99 percent confidence based on a single measurement (Glaser et al., 1981). United State Geologic
Survey (USGS) NWQL has developed a variant of the MDL called the long-term MDL (LT-MDL) to
capture greater method variability (Oblinger Childress et al. 1999). Unlike MDL, it is designed to
incorporate more of the measurement variability that is typical for routine analyses in a production
laboratory, such as multiple instruments, operators, calibrations, and sample preparation events
(Oblinger Childress et al. 1999). The LT-MDL determination ideally employs at least 24 spiked
samples prepared and analyzed by multiple analysts on multiple instruments over a 6-to 12-month
period at a frequency of about two samples per month (EPA 2004B). The LT-MDL uses "F-
pseudosigma" (Fc) in place of s, the sample standard deviation, used in the EPA MDL calculation. F-
pseudosigma is a non-parametric measure of variability that is based on the interquartile range of
the data (EPA 2004B). The LT-MDL may be calculated using either the mean or median of a set of
long-term blanks, or from long-term spiked sample results (depending o the analyte and specific
analytical method). The LT-MDL for an individual analyte is calculated as:
Equation la IT-MM* = M + j X FJ
Where M is the mean or median of blank results; n is the number of spiked sample results; and
Fa is F-pseudosigma, a nonparametric estimate of variability calculated as:
r- 1 u r* *53 ""
Equation lb F = - -
Where: Q3 and Ql are the 75th percentile and 25th percentile of spiked sample results, respectively.
LT-MDL is designed to be used in conjunction with a laboratory reporting level (LRL; Oblinger Childress
et al. 1999). The LRL is designed to achieve a risk of <1% for both false negatives and false positives
(Oblinger Childress et al. 1999). The LRL is set as a multiple of the LT-MDL, and is calculated as follows:
LRL = 2 x LT-MDL
Therefore, multiple measurements of a sample having a true concentration at the LRL should result in
the concentration being detected and reported 99 percent of the time (Oblinger Childress et al. 1999).
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All laboratories will develop calibration curves for each batch of samples that include a calibration
standard with an analyte concentration equal to the LRL. Estimates of LRLs (and how they are
determined) are required to be submitted with analytical results. Analytical results associated with LRLs
that exceed the objectives are flagged as being associated with unacceptable LRLs. Analytical data that
are below the estimated LRLs are reported, but are flagged as being below the LRLs.
2.2.2 Sampling Precision and Bias
Precision and bias are estimates of random and systematic error in a measurement process (Kirchmer,
1983; Hunt and Wilson, 1986, USEPA 2002). Collectively, precision and bias provide an estimate of the
total error or uncertainty associated with an individual measurement or set of measurements.
Systematic errors are minimized by using validated methods and standardized procedures across all
laboratories. Precision is estimated from repeated measurements of samples. Net bias is determined
from repeated measurements of solutions of known composition, or from the analysis of samples that
have been fortified by the addition of a known quantity of analyte. For analytes with large ranges of
expected concentrations, MQOs for precision and bias are established in both absolute and relative
terms, following the approach outlined in Hunt and Wilson (1986). At lower concentrations, MQOs are
specified in absolute terms. At higher concentrations, MQOs are stated in relative terms. The point of
transition between an absolute and relative MQO is calculated as the quotient of the absolute objective
divided by the relative objective (expressed as a proportion, e.g., 0.10 rather than as a percentage, e.g.,
10%). Precision and bias within each laboratory are monitored for every sample batch by the analysis of
internal QC samples. Samples associated with unacceptable QC sample results are reviewed and re-
analyzed if necessary. For selected analyses, precision and bias across all laboratories will be evaluated
by EPA (or an EPA contractor) sending performance evaluation samples to each lab. For more
information, see section 5 of this QAPP and the LOM. Equations used to calculate precision, bias and
accuracy follow.
Equation 1 Standard Deviation. Precision in absolute terms is estimated as the sample standard
deviation when the number of measurements is greater than two:
where x, is the value of the replicate, x is the mean of repeated sample measurements, and n is the
number of replicates.
n
n 1
Equation 2 Relative Standard Deviation or Coefficient of Variation. Relative precision for such
measurements is estimated as the relative standard deviation (RSD, or coefficient of variation, [CV]):
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RSD = CV = x 100
X
value for the set of measurements. Here s is the sample standard deviation of the set of measurements,
and x equals the mean.
Equation 3 Relative Percent Difference.Precision based on duplicate measurements is estimated based
on the range of measured values (which equals the difference for two measurements). The relative
percent difference (RPD) is calculated as:
(
RPD =
(A + B)/2
x 100
where A is the first measured value, B is the second measured value.
Equation 4 Net Bias. For repeated measurements of samples of known composition, net bias (B) is
estimated in absolute terms as:
B = X-T
where x equals the mean value for the set of measurements, and T equals the theoretical or
target value of a performance evaluation sample.
Equation 5 Relative Bias. Bias in relative terms (B[%]) is calculated as:
T7
B(%) = ^ x 100
where x equals the mean value for the set of measurements, and T equals the theoretical or target
value of a performance evaluation sample.
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2.2.3 Sampling Accuracy
Accuracy is generally a qualitative description rather than a quantitative description. Therefore, accuracy
is estimated for some analytes by calculating the percent recovery of a known quantity of an analyte
from fortified or spiked samples. For example, for water chemistry and chlorophyll a, accuracy is
estimated as the difference between the measured (across batches) and target values of performance
evaluation and/or internal reference samples at the lower concentration range, and as the percent
difference at the higher concentration range. See specific indicator sections in Chapter 5 for which
analytes include accuracy calculations.
Equation 6 Percent Recovery. Percent recovery is calculated as:
%re cov ery = ( ( x 100
Cs
where Cis is the measured concentration of the spiked sample, Q is the concentration of the unspiked
sample, and Cs is the concentration of the spike.
2.2.4 Taxonomic Precision and Accuracy
For the NCCA, taxonomic precision will be quantified by comparing whole-sample identifications
completed by independent taxonomists or laboratories. Accuracy of taxonomy will be qualitatively
evaluated through specification of target hierarchical levels (e.g., family, genus, or species); and the
specification of appropriate technical taxonomic literature or other references (e.g., identification keys,
voucher specimens). To calculate taxonomic precision, 10 percent of the samples will be randomly-
selected for re-identification by an independent, outside taxonomist or laboratory.
Equation 7 Percent Taxonomic Disagreement. Comparison of the results of whole sample re-
identifications will provide a Percent Taxonomic Disagreement (PTD) calculated as:
PTD =
1-
( comppp^
N
x 100
where comppos is the number of agreements, and N is the total number of individuals in the larger of the
two counts. The lower the PTD, the more similar are taxonomic results and the overall taxonomic
precision is better. A MQO of 15% is recommended for taxonomic difference (overall mean <15% is
acceptable). Individual samples exceeding 15% are examined for taxonomic areas of substantial
disagreement, and the reasons for disagreement investigated.
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Sample enumeration is another component of taxonomic precision. Final specimen counts for samples
are dependent on the taxonomist, not the rough counts obtained during the sorting activity.
Equation 8 Percent Difference in Enumeration. Comparison of counts is quantified by calculation of
percent difference in enumeration (PDE), calculated as:
An MQO of 5% is recommended (overall mean of <5% is acceptable) for PDE values. Individual samples
exceeding 5% are examined to determine reasons for the exceedance.
Corrective actions for samples exceeding these MQOs can include defining the taxa for which re-
identification may be necessary (potentially even by third party), for which samples (even outside of the
10% lot of QC samples) it is necessary, and where there may be issues of nomenclatural or enumeration
problems.
Taxonomic accuracy is evaluated by having individual specimens representative of selected taxa
identified by recognized experts. Samples will be identified using the most appropriate technical
literature that is accepted by the taxonomic discipline and reflects the accepted nomenclature. Where
necessary, the Integrated Taxonomic Information System (ITIS, http://www.itis.usda.gov/) and the
World Register of Marine Species (WoRMS, https://marinespecies.org/) will be used to verify
nomenclatural validity and spelling. A reference collection will be compiled as the samples are
identified. It is maintained by the contractor. Specialists in several taxonomic groups will verify selected
individuals of different taxa, as determined by the NCCA workgroup.
2.2.5 Completeness
Completeness is defined as "a measure of the amount of data collected from a measurement process
compared to the amount that was expected to be obtained under the conditions of measurement"
(Stanley and Vener, 1985).
Completeness requirements are established and evaluated from two perspectives. First, valid data for
individual parameters must be acquired from a minimum number of sampling locations in order to make
subpopulation estimates with a specified level of confidence or sampling precision. The objective of this
study is to complete sampling at 95% or more of the 1000 initial sampling sites. Percent completeness is
calculated as:
Equation 9 Percent Completeness.
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%C = V/Tx 100
where V is the number of measurements/samples judged valid, and T is the total number of planned
measurements/samples.
Within each indicator, completeness objectives are also established for individual samples or individual
measurement variables or analytes. These objectives are estimated as the percentage of valid data
obtained versus the amount of data expected based on the number of samples collected or number of
measurements conducted. Where necessary, supplementary objectives for completeness are presented
in the indicator-specific sections of this QAPP.
The completeness objectives are established for each measurement per site type (e.g., probability sites,
revisit sites, etc.). Failure to achieve the minimum requirements for a particular site type results in
regional population estimates having wider confidence intervals and may impact the ability to make
some subnational assessments. Failure to achieve requirements for repeat sampling (10% of samples
collected) and revisit samples (10% of sites visited) reduces the precision of estimates of index period
and annual variance components, and may impact the representativeness of these estimates because of
possible bias in the set of measurements obtained.
2.2.6 Comparability
Comparability is defined as "the confidence with which one data set can be compared to another"
(Stanley and Vener, 1985). A performance-based methods approach is being utilized for water
chemistry and chlorophyll-a analyses that defines a set of laboratory method performance requirements
for data quality. Following this approach, participating laboratories may choose which analytical
methods they will use for each target analyte as long as they are able to achieve the performance
requirements as listed in the Quality Control section of each Indicator section. For all parameters,
comparability is addressed by the use of standardized sampling procedures and analytical methods by
all sampling crews and laboratories. Comparability of data within and among parameters is also
facilitated by the implementation of standardized quality assurance and quality control techniques and
standardized performance and acceptance criteria. For all measurements, reporting units and format
are specified, incorporated into standardized data recording forms, and documented in the information
management system. Comparability is also addressed by providing results of QA sample data, such as
estimates of precision and bias, and conducting performance evaluation studies such as providing
performance evaluation samples to all appropriate labs and implementing an independent verification
of taxonomic identifications for 10% of samples processed at laboratories.
2.2.7 Representativeness
Representativeness is defined as "the degree to which the data accurately and precisely represent a
characteristic of a population parameter, variation of a property, a process characteristic, or an
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operational condition" (USEPA 2002). At one level, representativeness is affected by problems in any or
all of the other data quality indicators.
At another level, representativeness is affected by the selection of the target surface water bodies, the
location of sampling sites within that body, the time period when samples are collected, and the time
period when samples are analyzed. The probability-based sampling design should provide estimates of
condition of surface water resource populations that are representative of the region. The individual
sampling programs defined for each indicator attempt to address representativeness within the
constraints of the response design, (which includes when, where, and how to collect a sample at each
site). Holding time requirements for analyses ensure analytical results are representative of conditions
at the time of sampling. Use of duplicate (repeat) samples which are similar in composition to samples
being measured provides estimates of precision and bias that are applicable to sample measurements.
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3 Site Selection Design
The overall sampling program for the NCCA project requires a randomized, probability-based approach
for selecting coastal sites where sampling activities are to be conducted. Details regarding the specific
application of the probability design to surface waters resources are described in Paulsen et al. (1991)
and Stevens (1994). The specific details for the collection of samples associated with different indicators
are described in the indicator-specific sections of this QAPP.
3.1 Probability Based Sampling Design and Site Selection
Target Populations:
Estuarine waters of the United States from the head-of-salt to confluence with ocean including
inland waterways and major embayments river mouths, open and semi-enclosed estuaries,
bays, embayments, and the more open shallow waters adjacent to East Coast and Gulf Coast
shorelines. Excluded are the very deep waters adjacent to steep shorelines along the West
Coast. For the purposes of this study the head of salt is generally defined as < 0.5 psu (ppt) and
represents the landward/upstream boundary. The seaward boundary extends out to where an
imaginary straight-line intersecting two land features would fully enclose a body of coastal
water. All waters within the enclosed area are defined as estuarine, regardless of depth or
salinity.
Near shore waters of the Great Lakes of the United States and Canada. Near shore zone is
defined as region from shoreline to 30m depth constrained to a maximum of 5 km from
shoreline. Great Lakes include Lake Superior, Lake Michigan, Lake Huron, Lake Erie, and Lake
Ontario. The NARS Great Lakes survey will be restricted to the United States portion.
3.2 Survey Design for the Estuarine Waters
Sample Frame: The sample frame was derived from the prior National Coastal Assessment sample
frame developed by ORD Gulf Ecosystem Measurement and Modeling Division (GEMMD, Formerly the
Gulf Ecology Division (GED)). The sample frame was derived from prior National Coastal Assessment
sample frame developed by ORD Gulf Breeze Ecology Division. The prior GEMMD sample frame was
enhanced as part of the National Coastal Monitoring Network design by including information from
NOAA's Coastal Assessment Framework, boundaries of National Estuary Programs and identification of
major coastal systems. For NCA 2010 information on salinity zones was obtained from NOAA. For
Delaware Bay, Chesapeake Bay, Puget Sound and state of South Carolina, the prior NCA sample frames
were replaced by GIS layers provided by those organizations, ensuring that no prior areas in NCA were
excluded and any differences clearly identified in the new NCA 2010 sample frame. For the Californian
Province excluding San Francisco Bay, the GED sample frame was changed to match 2004 sample frame
used for NCA 2004 study. In 2013, the sample frame was updated to include information related to
1999-2001 and 2005-2006 NCA sample frames. This is necessary to provide the information required to
estimate change between these periods, 2010 and 2015.
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Survey Design: The NCCA 2020 survey design is a stratified probability design that is constructed from
two independent designs. The first design consists of sites sampled in 2010 and again to 2015. It also
includes sites that were evaluated but could not be sampled due to safety, too shallow or other reasons.
A total of 305 sites (269 to be sampled once in 2020 and 36 sites to be sampled twice in 2020) are
planned to be sampled from this design. The second design selects new sites and consists of 420 sites
planned to be sampled (414 to be sampled once in 2020 and 6 to be sampled twice in 2020). A
Generalized Random Tessellation Stratified (GRTS) survey design for an area resource was used for the
second design. The first design uses all the sites evaluated in the 2015 panel of sites sampled from 2010.
The details are given below.
Stratification: Stratification is based on a combination of states and a categorization of estuaries as
small or large. The categorization was completed by ORD estuarine scientists and is based on
classification used by EMAP estuaries and NCCA studies from 1999 to 2006. This results in 40 strata as
two states, Georgia and New Hampshire do not have large estuaries. Note that the above directly
applies to the selection of new sites for 2020. For sites to be sampled again from sites evaluated in both
2010 and 2015, the same stratification was used but the prior design was stratified by major estuary
group within a state. Massachusetts has a state-level design that is stratified by their six regions. Texas
has a state-level design that is stratified by their three regions and small/large estuaries; five extra sites
will be sampled in Texas as part of a state level intensification. The South Carolina design combines 10
revisit sites from previous NCCA Surveys and 11 sites from the South Carolina Estuarine and Cosatal
Assessment Program (SCECAP).
Multi-density categories: The design for the selection of new sites is equal probability within each
stratum. Sites to be re-sampled from 2010/2015 were selected with unequal probability categories
based on area of polygons within each major estuary group. The number of categories with a major
estuary group ranged from 1 to 4. The categories were used to ensure that sites were selected in the
smaller polygons.
3.3 Survey Design for the Great Lakes Nearshore Waters
Sample Frame: The sample frame was developed by the ORD Great Lakes Toxicology and Ecology
Division (GLTED, formerly Mid-Continent Ecology Division) by Jonathon Launspach under the direction of
David Bolgrien. The expected sample size is 225 Near Shore sites with 45 sites in each of the five Great
Lakes. Five sites in each Great Lake will be sampled twice in 2020 for a total of 250 site visits. All sites
that will be sampled twice in 2020 are sites that were sampled in 2010 and in 2015. Sample sizes were
allocated proportional to shoreline length by state within each Great Lake.
Survey Design: The survey design consists of two independent designs. One design re-samples sites
sampled during NCCA 2015 Great Lakes assessment, which were also sampled in 2010. The other design
selects new sites using the same survey design used for NCCA 2015. Both designs use a Generalized
Random Tessellation Stratified (GRTS) survey design for an area resource.
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Stratification: Both designs are stratified by Great Lake.
Multi-Density Categories: Both designs use unequal probability categories where the categories are
based on states within each Great Lake and the expected sample size is proportional to state shoreline
length within each stratum.
3.3.1 Great Lakes Enhancement Study Designs
3.3.1.1 Lake Erie Special Study.
The Lake Erie Special Study follows on a similar study conducted in 2015. The goal of the special study is
to collect water samples at enough additional sites drawn to have water quality at 30 sites per basin in
each of the Lake Erie basins (East, Central and West). The existing design has 45 base sites in Lake Erie
with 13 in East, 21 in Central and 11 in West basins. The enhanced design requires an additional 17 in
the East, 9 in the Central and 19 in the West basin.
3.3.1.2 Green Bay Enhancement.
The goal of the Green Bay enhancement is to develop an assessment of the nearshore and offshore
waters of Green Bay in Lake Michigan. The near shore zone is defined as region from shoreline to 30m
depth constrained to a maximum of 5 km from shoreline. Offshore waters are all remaining water within
Green Bay. The enhancement design incorporates existing NCCA 2020 sites in Green Bay (eight) sites
plus over sample sites (five). The NCCA 2020 design was supplemented with a new design for Green Bay
that includes 17 additional nearshore sites (for a total of 25 nearshore sites) and 25 offshore sites.
3.3.1.3 Great Lakes Islands and National Park Service Enhancement.
The goals of the Great Lakes Islands and National Park Service Enhancement are to create a reasonably-
sized and coherently-defined population assessment of the nearshore areas of the large islands of Lake
Michigan and to add data to the Lake Michigan nearshore assessment that will give
NPS/stakeholders enough site-based data for analysis and comparisons with 2010 results. The
Enhancement adds 50 additional sites, of which twelve are National Park Service sites.
3.4 Revisit Sites
Two NCCA estuarine sites in each state and five sites in each Great Lake Great Lakes nearshore site will
be revisited, that is they will be sampled once, and then at least two weeks later, and preferably
longer, will be visited a second time. The primary purpose of this revisit set of sites is to allow variance
estimates that would provide information on the extent to which the population estimates might vary
if they were sampled at a different time.
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4 Information Management
Environmental monitoring efforts that amass large quantities of information from various sources
present unique and challenging data management opportunities. To meet these challenges, the NCCA
employs a variety of well-tested information management (IM) strategies to aid in the functional
organization and ensured integrity of stored electronic data. IM is integral to all aspects of the NCCA
from initial selection of sampling sites through the dissemination and reporting of final, validated data.
And, by extension, all participants in the NCCA have certain responsibilities and obligations which also
make them a part of the IM system. This "inclusive" approach to managing information helps to:
Strengthen relationships among NCCA cooperators;
Increase the quality and relevancy of accumulated data; and
Ensure the flexibility and sustainability of the NARS IM structure.
This IM strategy provides a congruent and scientifically meaningful approach for maintaining
environmental monitoring data that will satisfy both scientific and technological requirements of the
NCCA 2020.
4.1 Roles and Responsibilities
At each point where data and information are generated, compiled, or stored, the NCCA 2020 IM team
must manage the information (Table 4.1). Thus, the IM system includes all of the data-generating
activities, all of the means of recording and storing information, and all of the processes which use data.
The IM system also includes both hardcopy and electronic means of generating, storing, organizing and
archiving data and the efforts to achieve a functional IM process is all encompassing. To that end, all
participants in the NCCA 2020 play an integral part within the IM system. The following table provides a
summary of the IM responsibilities identified by NCCA 2020 group. Specific information on the field
crew responsibilities for tracking and sending information is found in the FOM.
Table 4.1 Summary of IM responsibilities.
NCCA 2020
Contact
Primary Role
Responsibility
Group
Field Crews
State/tribal
Acquire in-situ
Complete and review field data forms and sample tracking forms
partners and
measurements and
for accuracy, completeness, and legibility.
contractor or
prescribed list of
other field
biotic/abiotic
Email/Ship/fax field and sample tracking forms to NARS IM Center
crews (regional
samples at each site
so information can be integrated into the central database
EPA, etc.)
targeted for the
survey
Work with the NARS IM Center staff to develop acceptable file
structures and electronic data transfer protocols should there be
a need to transfer and integrate data into the central database
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Analytical
Laboratories
State/tribal
partners and
contractors
j Provide all data as specified in FOM, SEG or as negotiated with
! the NCCA Project Leader.
j Maintain open communications with NARS IM Center regarding
any data issues
Analyze samples
received from field
crews in the
manner appropriate
to acquire
biotic/abiotic
indicators/measure
ments requested.
Review all electronic data transmittal files for completeness and
accuracy (as identified in the QAPP).
Work with the NARS IM Center staff to develop file structures and
electronic data transfer protocols for electronically-based data.
Submit completed sample tracking forms to NCCA 2020 IM Center
so information can be updated in the central database
Provide all data and metadata as specified in the laboratory
transmittal guidance section of the LOM, with specific templates
for each indicator or as negotiated with the NCCA Project Leader.
Maintain open communications with NCCA 2020 IM Center
regarding any data issues.
Whole fish tissue fillet responsibilities are specified in a separate
QAPP developed by U.S EPA Office of Science and Technology
IM Center staff
USEPAORD
NHEERL
Western
Ecology
Division-
Co rvallis,
Contractors
Provides support
and guidance for all
IM operations
related to
maintaining a
central data
management
system for NCCA
2020
Develop/update field data forms (electronic and paper versions).
Plan and implement electronic data flow and management
processes.
Manage the centralized database and implement related
administration duties.
Receive, scan, and conduct error checking of field data forms.
Monitor and track samples from field collection, through
shipment to appropriate laboratory.
Receive data submission packages (analytical results and
metadata) from each laboratory.
Run automated error checking, e.g., formatting differences, field
edits, range checks, logic checks, etc.
Receive verified, validated, and final indicator data files (including
record changes and reason for change) from QA reviewers.
Maintain history of all changes to data records from inception
through delivery to WQX.
Organize data in preparation for data verification and validation
analysis and public dissemination.
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Project Quality
Assurance
Coordinator
Steering
Committee
Data Analysis
and Reporting
Team
USEPA Office
Of Water
NCCA Project
Lead and other
team
members, EPA
Regional and
ORD staff,
States, tribes,
other federal
agencies
USEPA Office
of Water, ORD
WED, Partners
Review and
evaluate the
relevancy and
quality of
information/data
collected and
generated through
the NCCA 2020
surveys.
Provide technical
recommendations
related to data
analysis, reporting
and overall
implementation
Provide the data
analysis and
technical support
for NCCA 2020
reporting
requirements
Implement backup and recovery support for central database.
Implement data version control as appropriate.
Monitor quality control information.
Evaluate results stemming from field and laboratory audits.
Investigate and take corrective action, as necessary, to mitigate
any data quality issues.
Issue guidance to NCCA 2020 Project Leader and IM Center staff
for qualifying data when quality standards are not met or when
protocols deviate from plan.
Provide feedback and recommendations related to QA, data
management, analysis, reporting and data distribution issues
Review and comment on QA and information management
documentation (QAPP, data templates, etc.).
Provide data integration, aggregation and transformation support
as needed for data analysis.
Provide supporting information necessary to create metadata.
Investigate and follow-up on data anomalies using identified data
analysis activities.
Produce estimates of extent and ecological condition of the target
population of the resource.
Provide written background information and data analysis
interpretation for report(s).
Document in-depth data analysis procedures used.
Provide mapping/graphical support.
Document formatting and version control.
Develops QA report for management.
Data
Finalization
Team
TBD
Provides data ! Prepare NCCA 2020 data for transfer to USEPA public web-
librarian support j server(s).
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Generate data inventory catalog record (Science Inventory
Record).
Ensure all metadata is consistent, complete, and compliant with
USEPA standards.
4.1.1 State/ Tribe-Based Data Management
Some state and tribal partners will be managing activities for both field sampling and laboratory
analyses and may prefer to handle data management activities in-house. While the NARS program
encourages states and tribes to use these in-house capabilities, it is imperative that NCCA 2020 partners
understand their particular role and responsibilities for executing these functions within the context of
the national program. If a state or tribe chooses to do IM in-house, the state or tribe must perform all of
the functions associated with the following roles:
ฆ Field Crewincluding shipping/faxing of field data forms to the IM Coordinator (NCCA 2020)
paper or electronic field forms must be used and the original field forms must be sent to the
NARS IM Center as outlined in the NCCA 2020 FOM).
ฆ Quality Control Team for laboratory data.
ฆ NCCA QA Project Coordinator for ensuring that laboratory results meet specified QA
requirements.
ฆ All data will flow from the state or tribe to the NARS IM Center. Typically, the state or tribe
will provide a single point of contact for all things related to NCCA 2020 data. However, it
may be advantageous for the NARS IM Center staff to have direct communication with the
state or tribe participating laboratories to facilitate the transfer of data, a point that may be
negotiated between the primary state or tribal contact, the regional coordinator and the
NCCA 2020 Project Leader (with input from the NARS IM Center staff).
ฆ Data transfers to the NARS IM Center must be timely. States and tribes must submit all
initial laboratory results (i.e., those that have been verified by the laboratory and have
passed all internal laboratory QA/QC criteria) in the appropriate format to NARS IM Center
by May 2020, in order to meet NCCA 2020 product deadlines.
ฆ Data transfers must be complete. For example, laboratory analysis results submitted by a
state or tribe must be accompanied by related quality control and quality assurance data,
qualifiers code definitions, contaminant/parameter code cross-references/descriptions, test
methods, instrumentation information and any other relevant laboratory-based
assessments or documentation related to specific analytical batch runs.
ฆ The state or Tribe will ensure that data meet minimum quality standards and that data
transfer files meet negotiated content and file structure standards.
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The NARS IM Center will provide the necessary guidance for IM requirements. Each group that will
perform in-house IM functions will incorporate these guidelines as is practicable or as previously
negotiated.
4.2 Overview of System Structure
In its entirety, the NARS IM system includes site selection and logistics information, sample labels and
field data forms, tracking records, mapping and analytical data, data validation and analysis processes,
reports, and archives. NARS IM staff provides support and guidance to all program operations in
addition to maintaining a central database management system for the NCCA data.
The central repository for data and associated information collected for use by NCCA 2020 is a secure,
access-controlled server located at WED-Corvallis. This database is known as the NARS IM. Data are
stored and managed on this system using the Structured Query Language (SQL). Data review (e.g.,
verification and validation) and data analysis (e.g., estimates of status and extent) are accomplished
primarily using programs developed in either Statistical Analysis System (SAS) or 'R' language software
packages.
4.2.1 Data Flow
The NCCA 2020 will accumulate large quantities of observational and laboratory analysis data. To
manage this information appropriately, it is essential to have a well-defined data flow model and
documented approach for acquiring, storing, and summarizing the data. This conceptual model (Figure
4.1) helps focus efforts on maintaining organizational and custodial integrity, ensuring that data
available for analyses are of the highest possible quality.
4.2.2 Simplified Description of Data Flow
There are several components associated with the flow of information, these are:
ฆ Communication between the NARS IM Center and the various data contributors (e.g., field
crews, laboratories and the data analysis and reporting team) is vital for maintaining an
organized, timely, and successful flow of information and data.
ฆ Data are captured or acquired from four basic sources; field data transcription, laboratory
analysis reporting, automated data capture, and submission of external data files (e.g.,
Geographic Information Systems (GIS) data) encompassing an array of data types (site
characterization, biotic assessment, sediment and tissue contaminants, and water quality
analysis). Data capture generally relies on the transference of electronic data, e.g., optical
character readers and email, to a central data repository. However, some data must be
transcribed by hand in order to complete a record.
ฆ Data repository or storage provides the computing platform where raw data are archived,
partially processed data are staged, and the "final" data, assimilated into a final, user-ready
data file structure, are stored. The raw data archive is maintained in a manner consistent
with providing an audit trail of all incoming records. The staging area provides the IM Center
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staff with a platform for running the data through all of its QA/QC paces as well as providing
data analysts a first look at the incoming data. This area of the data system evolves as new
data are gathered and user-requirements are updated. The final data format becomes the
primary source for all statistical analysis and data distribution.
* Metadataa descriptive document that contains information compliant with the Content
Standards for Digital Geospatial Metadata (CSDGM) developed by the Federal Geographic
Data Committee (FGDC).
ECOLOGICAL INDICATOR FIELD AND LABORATORY DATA FLOW
LABORATORY
LABORATORY
INFORMATION
MANAGEMENT
SYSTEM
RAW DATA yS-t
SUBMISSION PACKAS
INFORMATION
MANAGEMENTCENTER
(WED-Corvallis)
Relational-
1 record per datum
Data
Table
1
Data
Table
2
Data
Table
3
Data
Table
4
ฆ ฆ ฆ
Data
Table
n
ASSESSMENT DATA FILES
(Extent and status estimates)
FINAL DATA
RECORDS
(EPA WATER
QUALITY
EXCHANGE
[WQX])
Permanent
Archival
Figure 4.1 Conceptual model of data flow into and out of the master SQL
The following sections describe core information management standards, data transfer protocols, and
data quality and results validation. Additionally, Section 4.4 describes the major data inputs to the
central database and the associated QA/QC processes used to record, enter, and validate measurement
and analytical data collected.
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4.2.3 Core Information Management Standards
The development and organization of the NARS IM system is compliant with current EPA guidelines and
standards. Areas addressed by these policies and guidelines include, but are not limited to, the
following:
ฆ Taxonomic nomenclature and coding;
ฆ Locational data;
ฆ Sampling unit identification and reference;
ฆ Hardware and software; and
ฆ Data catalog documentation.
NCCA 2020 is committed to compliance with all applicable regulations and guidance concerning
hardware and software procurement, maintenance, configuration control, and QA/QC. To that end, the
NCCA 2020 team has adopted several IM standards that help maximize the ability to exchange data
within the study and with other aquatic resource surveys or similar large-scale monitoring and
assessment studies (e.g. NARS, past EMAP and R-EMAP studies). Specific information follows.
4.2.4 Data Formats
4.2.4.1 Attribute Data
ฆ SQL Tables;
ฆ SAS Data Sets;
ฆ R Data Sets1; and
ฆ American Standard Code for Information Interchange (Ascii) Files: Comma-Separated values,
or space-delimited, or fixed column.
4.2.4.2 GIS Data
ฆ ARC/INFO native and export files; compressed .tar file of ARC/INFO workspace; and
ฆ Spatial Data Transfer Standard (SDTS; FGDC 1999) (format available upon request).
4.2.4.3 Standard Coding Systems
ฆ Sampling Site: (EPA Locational Data Policy; EPA 1991);
ฆ Coordinates: Latitude and Longitude in decimal degrees (ฑ0.002);
ฆ Datum: NAD83;
ฆ Chemical Compounds: Chemical Abstracts Service (CAS 1999) (http://www.cas.org/) ;
ฆ Species Codes: Integrated Taxonomic Information System when possible; and
ฆ Land cover/land use codes: Multi-Resolution Land Characteristics; National Hydrography
Dataset Plus Version 2.0.
1 R is a free software programming language and a software environment for statistical computing and graphics.
The R language is widely used among statisticians and data miners for developing statistical software and data
analysis.
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4.2.5 Public Accessibility
While any data created using public funds are subject to the Freedom of Information Act (FOIA), some
basic rules apply for general public accessibility and use. Briefly, those rules are:
ฆ Program must comply with Data Quality Act before making any data available to the public
and person generating data must fill out and have a signed Information Quality Guidelines
package before any posting to the Web or distribution of any kind.
ฆ Data and metadata files are made available to the contributor or participating group for
review or other project-related use from NARS IM or in flat files before moving to an EPA-
approved public website.
ฆ Data to be placed on a public website will undergo QA/QC review according to the approved
QAPP.
ฆ Only "final" data (those used to prepare the final project report) are readily available
through an EPA-approved public website.
As new guidance and requirements are issued, the NARS IM staff will assess the impact upon the IM
system and develop plans for ensuring timely compliance.
4.3 Data Transfer Protocols
Field crews are expected to send in hard copies of field forms or use the provided electronic field forms
containing in situ measurement and event information to the NARS IM Center defined in the FOM for
submission. Laboratories will submit electronic data files. Field crews and laboratories must submit all
sample tracking and analytical results data to the NARS IM Center in electronic form using a standard
software package to export and format data. Data submission templates for laboratories are included in
the LOM. Examples of software and the associated formats are:
Table 4.2 Summary of software
Software Export Options (file extensions)
Microsoft Excel"
xls, xlsx, csv, formatted txt delimited
Microsoft Access"
mdb, csv, formatted txt delimited
SAS"
csv, formatted txt delimited
R
csv, formatted txt delimited
All electronic files must be accompanied by appropriate documentation (e.g., metadata, laboratory
reports, QA/QC data and review results). This documentation must contain sufficient information to
identify field contents, field formats, qualifier codes, etc. It is very important to keep EPA informed of
the completeness of the analyses. Labs may send files periodically, before all samples are analyzed, but
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EPA must be informed that more data are pending if a partial file is submitted. All data files sent by the
labs must be accompanied by text documentation describing the status of the analyses, any QA/QC
problems encountered during processing, and any other information pertaining to the quality of the
data. Following is a list of general transmittal requirements each laboratory, state, or tribal based IM
group should consider when packaging data for electronic transfer to the IM Center:
ฆ Provide data in row/column data file/table structure - see data templates. All cooperators
and contractors should further consider the following:
a. Include NCCA site and sample ID provided on the sample container label in a field
for each record (row) to ensure that each data file/table record can be related to a
site visit.
b. Use a consistent set of column labels.
c. Use file structures consistently.
d. Use a consistent set of data qualifiers.
e. Use a consistent set of units.
f. Include method detection limit (MDL) as part of each result record.
g. Include reporting limit (RL) as part of each result record for water chemistry.
h. Provide a description of each result/QC/QA qualifier.
i. Provide results/measurements/MDL/RL in numeric form.
j. Maintain result qualifiers (e.g., <, Not Detected (ND)) in a separate column.
k. Use a separate column to identify record-type. For example, if QA or QC data are
included in a data file, there should be a column that allows the IM staff to readily
identify the different result types.
I. Include laboratory sample identifier.
m. Include batch numbers/information so results can be paired with appropriate
QA/QC information.
n. Include "true value" concentrations, if appropriate, in QA/QC records.
o. Include a short description of preparation and analytical methods used to analyze
samples (where appropriate) either as part of the record or as a separate
description for the test(s) performed on the sample. For example, EPAxxxx.x,
ASTMxxx.x, etc. Provide a broader description (e.g., citation) if a non-standard
method is used.
p. Include a short description of instrumentation used to acquire the test result (where
appropriate). This may be reported either as part of the record or as a separate
description for each test performed on the sample. For example, GC/MS-ECD, ICP-
MS, etc.
q. Ensure that data ready for transfer to NARS IM are verified and validated, and
results are qualified to the extent possible (final verification and validation are
conducted by EPA).
r. Data results must meet the specified requirements for each indicator found in the
LOM as specified by contract or agreement.
s. Identify and qualify missing data (why are the data missing?).
t. Submit any other associated quality assurance assessments and relevant data
related to laboratory results (i.e., chemistry, nutrients). Examples include summaries
of QC sample analyses (blanks, duplicates, check standards, matrix spikes) standard
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or certified reference materials, etc.), results for external performance evaluation or
proficiency testing samples, and any internal consistency checks conducted by the
laboratory. For requirements, please see specific indicator sections of this QAPP and
LOM.
Laboratories will work with the NARS IM Coordinator to establish a data load process into NARS IM.
4.4 Data Quality and Results Validation
Data quality is integrated throughout the life cycle of the data. This includes development of appropriate
forms, labels etc. for capturing data as well as verifying data entry, results, and other assessments.
Indicator workgroup experts, the data analysis and reporting team submit any recommended changes to
the Project QA Coordinator who recommends and submits any changes (deletions, additions,
corrections) to the NARS IM data center for inclusion in the validated data repository. All explanation for
data changes is included in the record history.
4.4.1 Design and Site Status Data Files
The site selection process described in Section 3 produces a list of candidate sampling locations,
inclusion probabilities, and associated site classification data (e.g., target status, ecoregion, etc.). The
Design Team provides this file to the NCCA 2020 Project Leader, who in turn distributes to the IM staff,
and field coordinators. Field coordinators determine ownership and contacts for acquiring permission to
access each site, and conduct site evaluation and reconnaissance activities. Field Crews document
information from site evaluation and reconnaissance activities following the SEG and the FOM. The site
evaluation spreadsheets are submitted to the Project Lead by the field crews. The NARS IM Center
compiles all information such as ownership, site evaluation, and reconnaissance information for each
site into a "site status" data file. Any missing information from the site status data file is identified and a
request is made by the NARS IM Center to the field crew (or site evaluator) to complete the record.
4.4.2 Sample Collection and Field Data
Field crews record sampling event observational data in a standard and consistent manner using field
data collection forms (see the NCCA 2020 FOM). Prior to initiation of field activities, the NARS IM staff
works with the indicator leads and analytical support laboratories to develop standardized field data
forms and sample labels. Adhesive labels, completed by the field crews, have a standard recording
format and are affixed to each sample container. Field protocols include precautions to ensure that label
information remains legible and the label remains attached to the sample.
The NCCA App is the required format for field data submission. Paper field forms are only to be used if
the App fails. A few copies will be provided to crews prior to the field season. In the event that the App
fails, the crew lead must continue sampling and record field data on paper forms and contact the EPA
Contractor Logistics Coordinator as quickly as possible. Paper forms are printed for field crews on water
resistant paper. Copies of the field data forms and instructions for completing each form are
documented in the NCCA 2020 FOM. Recorded data whether through the NCCA App or on paper are
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reviewed upon completion of data collection and recording activities by the Field Crew Leader. Field
crews check completed data forms and sample labels before leaving a sampling site to ensure
information and data were recorded legibly and completely. Errors are corrected by field crews if
possible, and data considered as suspect are qualified using a flag variable. The field sampling crew
enters explanations for all flagged data in a comments section. Field crews transmit forms to the NARS
IM Staff by selecting the "submit" button as described in the FOM. Alternately, field crews, ship
completed paper field data forms to the NARS IM staff for entry into the central database management
system.
All samples are tracked from the point of collection. Tracking of samples refers to the documentation of
the specified location of each sample in the centralized NARS IM Center database. This is done by
requiring that field crews ensure that copies of the shipping and custody record accompany all sample
transfers; other copies are transmitted to the IM Center. Each sample has a custody record that
laboratory manager is required to enter into NARS IM Center upon receipt of sample. The IM Center
tracks samples to ensure that they are delivered to the appropriate laboratory, that lost shipments can
be quickly identified and traced, and that any problems with samples observed when received at the
laboratory are reported promptly so that corrective action can be taken, if necessary. Detailed
procedures on shipping and sample tracking can be found in the FOMs.
Procedures for completion of sample labels and field data forms and use of personal computers (PCs)
are covered extensively in training sessions. General QC checks and procedures associated with sample
collection and transfer, field measurements, and field data form completion for most indicators are
listed in Table 4.3. Additional QA/QC checks or procedures specific to individual indicators are described
in the LOM.
Table 4.3 Summary sample and field data quality control activities: sample tracking
Quality Control Activity Description and/or Requirements
Contamination
Prevention
All containers for individual site sealed in plastic bags until use; specific contamination
avoidance measures covered in training
Sample Identification
Pre-printed labels with unique ID number on each sample
Data Recording
Data recorded on pre-printed forms of water-resistant paper; field sampling crew
reviews data forms for accuracy, completeness, and legibility
Data Qualifiers
Defined qualifier codes used on data form; qualifiers explained in comments section on
data form
Sample Custody
Records
Unique sample ID and tracking form information entered in LIMS; sample shipment
and receipt confirmed
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Quality Control Activity Description and/or Requirements
Sample Tracking
Sample condition inspected upon receipt and noted on tracking form with copies sent
to NCCA Field Logistics Coordinator and/or IM
Data Entry
Data entered using customized entry screens that resemble the data forms; entries
reviewed manually or by automated comparison of double entry
Data Submission
Standard format defined for each measurement including units, significant figures, and
decimal places, accepted code values, and required field width
Data Archival
All data records, including raw data, archived in an organized manner. For example,
following verification/validation of the last submission into the NARS database, it is
copied to a terabit external hard drive and sent to the Project Leader for inclusion in
his project file, scheduled as 501, permanent records.
Processed samples and reference collections of taxonomic specimens submitted for
cataloging and curing at an appropriate museum facility
4.4.3 Laboratory Analyses and Data Recording
Upon receipt of a sample shipment, analytical laboratory receiving personnel check the condition and
identification of each sample against the sample tracking record. Each sample is identified by
information written on the sample label. The lab reports any discrepancies, damaged samples, or
missing samples to the NARS IM staff and N NCCA 2020 Project Lead electronically.
Most of the laboratory analyses for the NCCA 2020 indicators, particularly chemical and physical
analyses, follow or are based on standard methods. Standard methods generally include requirements
for QC checks and procedures. General laboratory QA/QC procedures applicable to most NCCA 2020
indicators are described in Section 5. Additional QA/QC procedures specific to individual indicator and
parameter analyses are described in the LOM and the QAPP. Biological sample analyses are generally
based on current acceptable practices within the particular biological discipline. Some QC checks and
procedures applicable to most NCCA 2020 biological samples are described in the LOM and the QAPP.
Table 4.4 provides a summary of the lab data QC activities for NCCA 2020.
Table 4.4 Summary laboratory data quality control activities
Quality Control Activity
Description and/or Requirements
Instrument Maintenance
Follow manufacturer's recommendations and specific guidelines in methods;
maintain logbook of maintenance/repair activities
Calibration
Calibrate instruments according to manufacturer's recommendations for each
specific indicator; recalibrate or replace before analyzing any samples
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Quality Control Activity Description and/or Requirements
QC Data
Maintain control charts, determine LT-MDLs and achieved data attributes; include
QC data summary (narrative and compatible electronic format) in submission
package
Data Recording
Use software compatible with NARS IM system. Check all data entered against the
original bench sheet to identify and correct entry errors.
Review other QA data (e.g., condition upon receipt, etc.) for possible problems
with sample or specimen.
Data Qualifiers
Use defined qualifier codes; explain all qualifiers
Data Entry
Automated comparison of double entry or 100% manual check against original
data form
Submission Package
Includes:
ฆ Letter by laboratory manager
ฆ Data
ฆ Data qualifiers and explanations
ฆ Electronic format compatible with NARS IM
ฆ Documentation of file and database structures
ฆ Metadata: variable descriptions and formats
ฆ Summary report of any problems and corrective actions implemented
A laboratory's IM system may consist of only hardcopy records such as bench sheets and logbooks, an
electronic laboratory information management system (LIMS), or some combination of hardcopy and
electronic records. Laboratory data records are reviewed at the end of each analysis day by the
designated laboratory onsite QA coordinator or by supervisory personnel. Errors are corrected by
laboratory personnel if possible, and data considered as suspect by laboratory analysts are qualified
with a flag variable. All flagged data are explained in a comments section. Private contract laboratories
generally have a laboratory Quality Assurance Project Plan and established procedures for recording,
reviewing, and validating analysis data.
Once analytical data have passed all of the laboratory's internal review procedures, the lab prepares and
transfers a submission package using the prescribed templates in the LOM. The contents of the
submission package are largely dictated by the type of analysis (physical, chemical, or biological).
Remaining sample material and voucher specimens may be transferred to EPA's designated laboratory
or facilities as directed by the NCCA 2020 Project Lead. All samples and raw data files (including
logbooks, bench sheets, and instrument tracings) are to be retained by the laboratory for 3 years or until
authorized for disposal, in writing, by the EPA Project Leader. Deliverables from contractors and
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cooperators, including raw data, are permanent as per EPA Record Schedule 258
(http://www.epa.gov/records/policy/schedule/sched/258.htm). EPA's project records are scheduled 501
(http://www.epa.gov/records/policy/schedule/sched/501.htm) and are also permanent.
4.4.4 Data Review, Verification, and Validation Activities
Raw data files are created from entry of field and analytical data, including data for QA/QC samples and
any data qualifiers noted on the field forms or analytical data package.
4.4.4.1 Paper Forms
The NARS IM Center either optically scans or transcribes information from field collection forms into an
electronic format (sometimes using a combination of both processes). During the scanning process,
incoming data are subjected to a number of automated error checking routines. Obvious errors are
corrected immediately at the time of scanning. Suspected errors that cannot be confirmed at the time of
scanning are qualified for later review by someone with the appropriate background and experience
(e.g., a chemist or aquatic ecologist). The process continues until the transcribed data are 100% verified
or no corrections are required.
4.4.4.2 Electronic Forms
The NARS IM Center directly uploads information from the electronic field collection forms into their
database. During the upload process, incoming data are subjected to a number of automated error
checking routines. Omissions and errors are automatically noted in an email message to the field crew
lead.
4.4.4.3 Additional Review
Additional validation is accomplished by the NARS IM Center staff using a specific set of guidelines and
executing a series of programs (computer code) to check for: correct file structure and variable naming
and formats, outliers, missing data, typographical errors and illogical or inconsistent data based on
expected relationships to other variables. Data that fail any check routine are identified in an "exception
report" that is reviewed by an appropriate scientist for resolution.
The NARS IM Center brings any remaining questionable data to the attention of the EPA Project QA
Coordinator and individuals responsible for collecting the data for resolution. The EPA Project QA
Coordinator reviews all data to determine completeness and validity. Additionally, the data are run
through a rigorous inspection using SQL queries or other computer programs such as SAS or R to check
for anomalous data values that are especially large or small, or are noteworthy in other ways. Focus is
on rare, extreme values since outliers may affect statistical quantities such as averages and standard
deviations.
The EPA Project QA Coordinator examines all laboratory quality assurance (QA) information to
determine if the laboratory met the predefined data quality objectives - available through the QAPP.
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Some of the typical checks made in the processes of verification and validation are described in Table
4.5.
Automated review procedures may be used. The primary purpose of the initial checks is to confirm that
each data value present in an electronic data file is accurate with respect to the value that was initially
recorded on a data form or obtained from an analytical instrument. In general, these activities focus on
individual variables in the raw data file and may include range checks for numeric variables, frequency
tabulations of coded or alphanumeric variables to identify erroneous codes or misspelled entries, and
summations of variables reported in terms of percent or percentiles. In addition, associated QA
information (e.g., sample holding time) and QC sample data are reviewed to determine if they meet
acceptance criteria. Suspect values are assigned a data qualifier. They will either be corrected, replaced
with a new acceptable value from sample reanalysis, or confirmed suspect after sample reanalysis. For
biological samples, species identifications are corrected for entry errors associated with incorrect or
misspelled codes. Errors associated with misidentification of specimens are corrected after voucher
specimens have been confirmed and the results are available. Files corrected for entry errors are
considered to be raw data files. Copies of all raw data files are maintained in the centralized NARS IM
System. Any suspect data will be flagged for data qualification.
The NARS IM staff, with the support of the NCCA 2020 Quality Team, correct and qualify all questionable
data. Copies of the raw data files are maintained in NARS IM, generally in active files until completion of
reporting and then in archive files. Redundant copies of all data files are maintained and all files are
periodically backed up to the EPA HQ shared G drive system.
Table 4.5 Data review, verification, and validation quality control activities
Quality Control Activity Description and/or Requirements
Review any qualifiers associated with variable
Determine if value is suspect or invalid; assign
validation qualifiers as appropriate
Determine if Measurement Quality Objective (MQOs) and
project DQOs have been achieved
Determine potential impact on achieving research
and/or program objectives
Exploratory data analyses (univariate, bivariate,
multivariate) utilizing all data
Identify outlier values and determine if analytical
error or site-specific phenomenon is responsible
Confirm assumptions regarding specific types of statistical
techniques being utilized in development of metrics and
indicators
Determine potential impact on achieving research
and/or program objectives
In the final stage of data verification and validation, exploratory data analysis techniques may be used to
identify extreme data points or statistical outliers in the data set. Examples of univariate analysis
techniques include the generation and examination of box-and-whisker plots and subsequent statistical
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tests of any outlying data points. Bivariate techniques include calculation of Spearman correlation
coefficients for all pairs of variables in the data set with subsequent examination of bivariate plots of
variables having high correlation coefficients. Multivariate techniques have also been used in detecting
extreme or outlying values in environmental data sets (Meglen, 1985; Garner et al., 1991; Stapanian et
al., 1993).
The Quality Team reviews suspect data to determine the source of error, if possible. If the error is
correctable, the data set is edited to incorporate the correct data. If the source of the error cannot be
determined, the Quality Team qualifies the data as questionable or invalid. Data qualified as
questionable may be acceptable for certain types of data analyses and interpretation activities. The
decision to use questionable data must be made by the individual data users. Data qualified as invalid
are considered to be unacceptable for use in any analysis or interpretation activities and will generally
be removed from the data file and replaced with a missing value code and explanatory comment or flag
code. After completion of verification and validation activities, a final data file is created, with copies
transmitted for archival and for uploading to the centralized IM system.
Once verified and validated, data files are made available for use in various types of interpretation
activities; each activity may require additional restructuring of the data files. These restructuring
activities are collectively referred to as "data enhancement." In order to develop indicator metrics from
one or more variables, data files may be restructured so as to provide a single record per site.
4.5 Data Transfer
Field crews may transmit data electronically; hardcopies of completed data and sample tracking forms
are sent via express courier service. Copies of raw, verified, and validated data files are transferred from
the Project QA Coordinator to the IM staff for inclusion in the central IM system. All transfers of data are
conducted using a means of transfer, file structure, and file format that has been approved by the EPA
IM Project lead. Data files that do not meet the required specifications will not be incorporated into the
centralized data access and management system.
4.5.1 Database Changes
The NARS IM Center staff complete data corrections at the lowest level to ensure that any subsequent
updates will contain only the most correct data. The NARS IM Center sends back laboratory results
found to be in error to the originator (e.g., analysis laboratory) for correction. After the originator makes
any corrections, the entire batch or file is resubmitted to the NARS IM Center. The NARS IM Center uses
these resubmissions to replace any previous versions of the same data.
The NARS IM Center uses a version control methodology when receiving files. This methodology is
explained in the following sentences. Incoming data are not always immediately transportable into a
format compatible with the desired file structures. When this situation occurs, the IM staff creates a
copy of the original data file, which then becomes the working file in which any formatting changes will
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take place. The original raw data will remain unchanged. This practice further ensures the integrity of
the data and provides an additional data recovery avenue, should the need arise.
All significant changes are documented by the NARS IM Center staff. The NARS IM Center includes this
information in the final summary documentation for the database (metadata).
After corrections have been applied to the data, the NARS IM Center will rerun the validation programs
to re-inspect the data.
If requested by the NARS Project QA Coordinator and funds are available, the NARS IM Center will
implement database auditing features to track changes.
4.6 Metadata
All metadata will be kept according to the Federal Geographic Data Committee, Content standard for
digital geospatial metadata, version 2.0. FGDC-STD-001-1998 (FGDC 1998).
4.6.1 Parameter Formats
The following parameter formats will be used:
Sampling Site (EPA Locational Data Policy (USEPA 1991)
Latitude and Longitude in decimal degrees {+/- 7.4), Negative longitude values (west of the
prime meridian),
Datum: NAD83;
Date: YYYYMMDD (year, month, day)
Hour: HHMMSS (hour, minute, second), Greenwich mean time, Local time
Data loaded to STORET will take on the STORET formats upon loading.
4.6.2 Standard Coding Systems
The following standard coding systems will be used:
Chemical Compounds: Chemical Abstracts Service (CAS 1999)
Taxonomic Names: USGS BioData (https://aquatic.biodata.usgs.gov/landing.action)
Land cover/land use codes: Multi-Resolution Land Characteristics (MRLC 1999)
4.7 Information Management Operations
4.7.1 Computing Infrastructure
Electronic data are collected and maintained within a central server housed at WED using a Windows
Server (current configuration) or higher computing platform in SQL native tables for the primary data
repository and SASฎ native data sets or R datasets for data analysis. Official IM functions are conducted
in a centralized environment.
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4.7.2 Data Security and Accessibility
The NARS IM Center ensures that all data files in NARS IM are protected from corruption by computer
viruses, unauthorized access, and hardware and software failures. Guidance and policy documents of
EPA and management policies established by the IM Technical Coordination Group for data access and
data confidentiality are followed. Raw and verified data files are accessible only to the NCCA 2020
collaborators. Validated data files are accessible only to users specifically authorized by the NCCA 2020
Project Leader. Data files in the central repository used for access and dissemination are marked as
read-only to prevent corruption by inadvertent editing, additions, or deletions.
Data generated, processed, and incorporated into the IM system are routinely stored as well as archived
on redundant systems by the NARS IM Center. This ensures that if one system is destroyed or
incapacitated, IM staff can reconstruct the databases. Procedures developed to archive the data,
monitor the process, and recover the data are described in IM documentation.
Data security and accessibility standards implemented for NCCA 2020 IM meet EPA's standard security
authentication (i.e., username, password) process in accordance to EPA's Information Management
Security Manual (1999; EPA Directive 2195 Al) and EPA Order 2195.1 A4 (2001D). Any data sharing
requiring file transfer protocol (FTP) or internet protocol is provided through an authenticated site.
4.7.3 Life Cycle
Data may be retrieved electronically by the NCCA 2020 team, partners and others throughout the
records retention and disposition lifecycle or as practicable (Section 4.4).
4.7.4 Data Recovery and Emergency Backup Procedures
The NARS IM Center maintains several backup copies of all data files and of the programs used for
processing the data. Backups of the entire system are maintained off-site by the NARS IM Center. The
IM process used by the NARS IM Center for NCCA 2020 uses system backup procedures. The NARS IM
Center backs up and archives the central database according to procedures already established for EPA
Western Ecology Division and NARS IM. All laboratories generating data and developing data files are
expected to establish procedures for backing up and archiving computerized data.
4.7.5 Long-Term Data Accessibility and Archive
All data are transferred by OW's Water Quality Exchange (WQX) team working with the NARS IM Team
to U.S. EPA's agency-wide WQX data management system for archival purposes. WQX is a repository for
water quality, biological, and physical data and is used by state environmental agencies, EPA and other
federal agencies, universities, and private citizens. Data from the NCCA 2020 project will be run through
an Interface Module in an Excel format and uploaded to WQX by the WQX team. Once uploaded, states
and tribes and the public will be able to download data (using Oracle software) from their region. Data
will also be provided in flat files on the NARS website.
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4.8 Records Management
Removable storage media (i.e., CDs, USB Drives) and paper records are maintained in a centrally located
area at the NARS IM Center. Paper records will be returned to OW once the assessment is complete. The
IM Team identifies and maintains files using standard divisional procedures as established by EPA
Western Ecology Division. Records retention and disposition comply with U.S. EPA directive 2160
Records Management Manual (July, 1984) in accordance with the Federal Records Act of 1950.
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5 Indicators
This section of the QAPP provides summary information on laboratory and field performance and quality
control measures for the NCCA 2020 indicators. Additional details are described in the NCCA 2020 Field
Operations Manual and Laboratory Operations Manual. A description of the NCCA indicators are found
in Table 5.1.
Table 5.1 Description of NCCA 2020 Indicators and location where indicators are collected
Indicator Description Location of sample collection
In Situ measurements
[Salinity (estuarine),
temperature, DO
Depth,
Conductivity (freshwater),
pH]
Measurements taken to detect
extremes in condition that
might indicate impairment and
depth at location
One set of measurements taken at the
index site; readings are taken on a
profile through the water column at
the index site
Secchi/light measurements
PAR
Measurements to look at
clarity
Measured at the index site
Water chemistry filtered
sample for dissolved
inorganic N02 N03, NH4,
P04; Unfiltered sample for
Total N and P
Water chemistry
measurements will be used to
determine nutrient
enrichment/eutrophication
Collected from a depth of 0.5 m at the
index site
Chlorophyll-a
Chlorophyll-a is used to
determine algal biomass in the
water
Collected as part of water chemistry
sample
Microcystes,
Cylindrospermopsin
Measurement used to
determine the presence of
algal toxins in the water
Collected from a depth of 0.5 m at the
index site
Benthic invertebrate
assemblage
Benthic invertebrate
community information is used
to assess the biological health
of estuarine and Great lake
waters. The NCCA will measure
attributes of the overall
structure and function of the
Collected from a sediment grab at the
index site
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benthic community, diversity,
abundances, etc to evaluate
biological integrity
Sediment Chemistry Measurement to determine Collected from a sediment grab at the
contaminant levels in sediment index site
Sediment toxicity Measurement to determine
level of toxicity of sediment
Collected from a sediment grab at the
index site
Nitrogen Isotopes
(Research Indicator)
Research indicator to
determine the utility of
nitrogen isotope for tracking of
waste sources in estuaries
Collected from a sediment grab at the
index site in estuaries only
Microplastics in sediment
(research indicator)
Research indicator to help Collected from a sediment grab at the
develop methods for index site from select sites in the
microplastics detection, Northeast only
separation and quantification
in estuarine sediments
Whole fish tissue Measurement to determine Target species collected within 500
contaminant levels in whole meter radius of the X-site (may expand
body fish for ecological to 1000 meters if needed)
assessment
Fecal indicator (Enterococci) Enterococci are bacteria that
are endemic to the guts of
warm blooded creatures.
These bacteria, by themselves,
are not considered harmful to
humans but often occur in the
presence of potential human
pathogens (the definition of an
indicator organism)
Collected from a depth of 0.5 m at the
index site
Fish Tissue Plug
Fish Tissue plugs will provide
information on the national
distribution of Hg, a
Target species collected within a 500
meter radius of the X-site (may expand
to 1000 meters if needed)
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bioaccumulative and toxic
chemical in fish species
Great Lakes Human Health
Fish Tissue Samples
Fish Tissue fillet samples will
be analyzed for mercury,
PCBs, and PFAS because of
associated human health risk
implications
Target species collected at a subset of
Great Lakes sites within a 500 meter
radius of the X-site, if possible, and up
to a 1500 meter radius, if needed
5.1 In Situ Measurements
The first activities that should be conducted by crews upon arriving onsite are those that involve water
column measurements; these data need to be collected before disturbing bottom sediments.
5.1.1 Introduction
Crews make in situ measurements using field meters, and data are recorded utilizing the NCCA App.
Field crews will measure dissolved oxygen (DO), pH, conductivity (fresh water) or salinity (marine), and
temperature using a multi-parameter water quality meter. Crews use a meter to read photosynthetically
active radiation (PAR) throughout the photic zone. Crews measure secchi disk depth as well. At Great
Lakes sites, crews will also take underwater video at each site.
5.1.2 Sample Design and Methods
Detailed sample collection and handling procedures are described in NCCA 2020 Field Operation
Manual.
5.1.3 Pertinent Laboratory QA/QC Procedures
Not applicable for in situ measurements.
5.1.4 Pertinent Field QA/QC Procedures
Several pieces of equipment that may be utilized by crews to collect or analyze environmental data for
NCCA should have periodic maintenance and calibration verification performed by manufacturer's
representatives or service consultants. These procedures should be documented by date and the
signature of the person performing the inspection. Examples include:
CTDs or multiparameter probes - annual (or as needed) maintenance and calibration check by
manufacturer or certified service center;
Light (PAR) Meters - biannual verification of calibration coefficient by manufacturer;
Video cameras- as needed maintenance as described in the manufacturer information.
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Crews will maintain all other sampling gear and laboratory instrumentation in good repair as per
manufacturer's recommendations to ensure proper function.
5.1.4.1 Field Performance Requirements
Measurement data quality objectives (measurement DQOs or MQOs) are given in Table 5.2. General
requirements for comparability and representativeness are addressed in Section 2.
Table 5.2 Measurement data quality objectives: water indicators.
Variable or Measurement
Maximum allowable
Accuracy Goal (Bias)
Maximum
Allowable
Precision Goal
(%RSD)
Completeness
Oxygen, dissolved
ฑ0.5 mg/L
10%
95%
Temperature
ฑ1 ฑC
10%
95%
Conductivity
ฑ1 piS/cm
10%
95%
Salinity
ฑlppt
10%
95%
Depth
ฑ0.5 m
10%
95%
PH
ฑ0.3 SU
10%
95%
PAR
0.01 pimol s 1 m"2*
5%
95%
Secchi Depth
ฑ0.5 m
10%
95%
*Determined by biannual manu'
:acturer calibration.
5.1.4.2 Field Quality Control Requirements
For in situ measurements, each field instrument (e.g., multi-probe) used by the crews must be
calibrated, inspected prior to use, and operated according to manufacturer specifications. Figure 5.1
illustrates the general scheme for field chemistry measurement procedures.
5.1.4.3 Instrumentation
Seabird CTDs and Multiparameter Probes: SeaBird CTDs and multiparameter probes are routinely used
in estuarine, Great Lakes, deep water or oceanographic surveys to measure and electronically log
various water column parameters. When properly maintained and serviced, they have an established
history of dependable utilization. The units can be configured with different arrays of probes; for the
purposes of the NCCA, when used, crews will equip them to measure DO, temperature,
salinity/conductivity, pH, and depth. Crews will follow the NCCA Field Operations Manual and
manufacturer's instructions for use of these instruments.
For instruments that are factory calibrated and checked (e.g. Sea-Bird Electronics meters, etc.), crews
must ensure that factory-certified diagnostics have been completed according to manufacturer
specifications (preferably conducted immediately prior to the sampling season) and provide
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documentation copies during assistance visits. Meters such as these do not require the daily calibration
steps or the weekly diagnostic/QCS (Quality Check Solution) checks. Table 5.3 includes field quality
control measures for multiparameter probes.
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FIELD MEASUREMENT PROCESS: WATER CHEMISTRY INDICATOR
Figure 5.1 Field Measurement Process for Water Chemistry Samples.
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Table 5.3 Field quality control: multiparameter indicator.
Check Description
Frequency
Acceptance Criteria
Corrective
Actions
Verify performance of
temperature probe using
wet ice
Prior to initial
sampling, daily
thereafter
Functionality = ฑ 0.5ฐC
See manufacturer's
directions
Verify depth against
markings on cable
Daily
ฑ 0.2 m
Re-calibrate
pH - Internal electronic
check if equipped; if not
check against Quality
Check Solution
At the beginning and
end of each day
Alignment with
instrument
manufacturer's
specifications; or QCS
measurement in range
AM: Re-calibrate
PM: Flag day's data. pH
probe may need
maintenance
Conductivity (Great Lakes
only) - internal electronic
check if equipped; if not
check against Quality
Check Solution
At the beginning and
end of each day
Alignment with
intrument
manufacturer's
specifications or within
ฑ2 piS/cm or ฑ10% of QCS
value
AM: Re-calibrate
PM: Flag day's data.
Instrument may need repair
Salinity (marine only) -
internal electronic check if
equipped; if not check
against Quality Check
Solution
At the beginning and
end of each day
Alignment with
instrument
manufacturer's
specifications or within ฑ
0.2 ppt of QCS value
AM: Re-calibrate
PM: Flag day's data.
Instrument may need
reapair
Check DO calibration in
field against atmospheric
standard (ambient air
saturated with water)
At the beginning and
end of each day
ฑ0.5 mg/L or 10% of
100% saturation
AM: Re-calibrate
PM: Flag day's data. Change
membrane and re-check
LICOR PAR meter: No daily field calibration procedures are required for the LICOR light meter; however,
the manufacturer recommends that the instrument be returned to the factory for bi-annual calibration
check and resetting of the calibration coefficient. Calibration kits are available from LICOR and this
procedure can be performed at the laboratory (see LICOR operation manual). There are several field QC
measures that crews will take to help ensure taking accurate measurements of light penetration.
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1. The "deck" sensor must be situated in full sunlight (i.e., out of any shadows).
2. Likewise, the submerged sensor must be deployed from the sunny side of the vessel and care should
be taken to avoid positioning the sensor in the shadow of the vessel.
3. For the comparative light readings of deck and submerged sensors, (ratio of ambient vs.
submerged), the time interval between readings should be minimized (approximately 1 sec).
Secchi Disk: No field calibration procedures are required for the Secchi disk. QC procedures that crews
will implement when using the Secchi disk to make water clarity measurements include designating a
specific crew member as the Secchi depth reader; taking all measurements from the shady side of the
boat (unlike LICOR measurements which are taken from the sunny side); and not wearing sunglasses or
hats while taking Secchi readings.
Underwater Video (Great Lakes only): No field calibration of camera is required but crews should check
the equipment prior to each field day to assure that it is operational. Crews will charge the battery
regularly.
5.1.4.4 Data Reporting
Data reporting units and significant figures are summarized in Table 5.4.
Table 5.4 Data reporting criteria: field measurements.
No.
Significant
Maximum No.
Measurement
Units
Figures
Decimal Places
Dissolved Oxygen
mg/L
2
1
Temperature
ฐC
2
1
PH
pH units
3
Conductivity
|a,S/cm at 25 ฐC
3
1
Salinity
ppt
2
1
PAR
mE/m /s
2
1
Depth
meters
3
1
Secchi Depth
meters
3
1
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Table 5.5 Data Validation Quality Control for In-Situ Indicator.
Activity or Procedure Requirements and Corrective Action
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Range checks, summary statistics, and/or
exploratory data analysis (e.g., box and whisker
plots)
Correct reporting errors or qualify as suspect or
invalid
Review data from calibration and field notes
Determine impact and possible limitations on
overall usability of data
5.2 Water Chemistry Measurements (Including chlorophyll-a)
5.2.1 Introduction
Water chemistry indicators based on field and laboratory methods evaluate estuarine and Great Lake
condition with respect to nutrient over-enrichment and eutrophication. Data are collected for a variety
of physical and chemical constituents to provide information on the water clarity, primary productivity,
and nutrient status. Data are collected for chlorophyll-a to provide information on the algal loading and
gross biomass of blue-greens and other algae.
5.2.2 Sample Design and Methods
Detailed sample collection and handling procedures are described in NCCA 2020 Field Operation
Manual. Detailed laboratory methods are in the NCCA 2020 Laboratory Operations Manual.
5.2.3 Pertinent Laboratory QA/QC Procedures
A single central laboratory and some state laboratories will analyze the water chemistry samples. The
specific quality control procedures used by each laboratory are implemented to ensure that:
ฆ Objectives established for various data quality indicators being met.
ฆ Results are consistent and comparable among all participating laboratories.
The central laboratory demonstrated in previous studies that it can meet the required Laboratory
Reporting Levels( RLs) (USEPA 2004). All laboratories will follow the QA/QC procedures outlined in the
NCCA 2020 QAPP and the LOM. A summary and diagram of the QA processes related to water chemistry
samples for the NCCA 2020 are found in Figure 5.2.
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Figure 5.2 Analysis Activities for Water Chemistry Samples
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5.2.3.1 Laboratory Performance Requirements
Table 5.6 summarizes the pertinent laboratory measurement data quality objectives for the water
chemistry indicators.
Table 5.6 Measurement data quality objectives: water chemistry indicator and chlorophyll a.
Parameter
Units
Potential
Range
of Samples1
Method
Detection
Limit Objective2
Transition
Value3
Precision
Objective4
Accuracy
Objective5
Ammonia (Nhb)
mg N/L
Oto 17
marine
(0.7 jjeq/L)
0.02 freshwater
0.10
ฑ 0.01 or
ฑ10%
ฑ 0.01 or
ฑ10%
Chloride (CI)
(Great Lakes
only)
mg Cl/L
Oto 5,000
0.20 (6 jjeq/L)
1
ฑ 0.10 or
ฑ10%
ฑ 0.10 or
ฑ10%
Conductivity
l_iS/cm
at 25ฐC
1-66,000
1.0
20
ฑ2 or ฑ10%
ฑ2 or ฑ 5%
Nitrate-Nitrite
(NO3-NO2)
mg N/L
0 to 360
(as nitrate)
marine
0.02 freshwater
0.10
ฑ 0.01 or
ฑ10%
ฑ 0.01 or
ฑ10%
pH (Laboratory)
Std
Units
3.5-10
N/A
5.75, 8.25
<5.75 or
> 8.25 =
ฑ0.07;
5.75-8.25 =
ฑ0.15
<5.75 or
>8.25
=ฑ0.15;
5.75-8.25
= ฑ0.05
Total Nitrogen
(TN)
mg N/L
0.1 to 90
0.01
0.10
ฑ 0.01 or
ฑ10%
ฑ 0.01 or
ฑ10%
Total
Phosphorous (TP)
and
ortho-Phosphate
mg P/L
Oto 22
(as TP)
0.002
0.02
ฑ 0.002 or
ฑ10%
ฑ 0.002 or
ฑ10%
Nitrate (NO3)
mg N/L
0. to 360
marine
(10.1 jjeq/L)
0.03 freshwater
0.1
ฑ 0.01 or
ฑ5%
ฑ 0.01 or
ฑ5%
Sulfate (SO4)
mg/L
0 to 5000
0.5 freshwater
(10.4 ueq/L)
2.5
ฑ0.25 or
ฑ10%
ฑ0.25 or
ฑ10%
Chlorophyll-a
jug/L in
extract
0.7 to 11,000
1.5
15
ฑ 1.5 or
ฑ10%
ฑ 1.5 or
ฑ10%
1 Estimated from samples analyzed at the EPA Western Ecological Division-Corvallis laboratory between
1999 and 2005
2 The method detection limit is determined as a one-sided 99% confidence interval from repeated
measurements of a low-level standard across several calibration curves.
3 Value for which absolute (lower concentrations) vs. relative (higher concentrations) objectives for
precision and accuracy are used.
4 For duplicate samples, precision is estimated as the pooled standard deviation (calculated as the root-
mean square) of all samples at the lower concentration range, and as the pooled percent relative
standard deviation of all samples at the higher concentration range. For standard samples, precision is
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estimated as the standard deviation of repeated measurements across batches at the lower concentration
range, and as percent relative standard deviation of repeated measurements across batches at the higher
concentration range.
5 Accuracy is estimated as the difference between the measured (across batches) and target values of
performance evaluation and/or internal reference samples at the lower concentration range, and as the
percent difference at the higher concentration range.
5.2.3.2 Laboratory Quality Control Requirements
Table 5.7 summarizes the pertinent laboratory quality control samples for the water chemistry
indicators.
Table 5.7 Laboratory Quality Control Samples: Water Chemistry Indicator.
QC Sample
Indicators
Description
Frequency
Acceptance
Corrective
Type and
Criteria
Action
Description
Demonstrate
All
Demonstration
Once
See LOM
EPA will not
competency
of past
approve any
for analyzing
experience
laboratory for
water
with water
NCCA sample
samples to
samples in
processing if
meet the
achieving the
the laboratory
performance
method
cannot
measures
detection
demonstrate
limits
competency. In
other words,
EPA will select
another
laboratory that
can
demonstrate
competency for
its NCCA
samples
Check
All
Sample issues
Once
No sample
Lab determines
condition of
such as
issues or
if the sample
sample when
cracked
determination
can be
it arrives.
container;
that sample
analyzed or
missing label;
can still be
has been too
temperature;
analyzed
severely
adherence to
compromised
holding time
(e.g.,
requirements;
contamination).
sufficient
Assign
volume for
appropriate
test.
condition code
identified in the
LOM
Store sample
All
Check the
Record
While stored
If at any time
appropriately.
temperature of
temperature of
at the
samples are
the
sample upon
laboratory, the
warmer than
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QC Sample
Indicators
Description
Frequency
Acceptance
Corrective
Type and
Criteria
Action
Description
refrigerator
arrival at the
sample must
required, note
per
laboratory.
be kept at a
temperature
laboratory's
Check
maximum
and duration
standard
temperature of the
temperature of
(either from the
operating
refrigerator/freezer
4ฐ C. (for
continuous
procedures
where samples
aliquots
temperature log
are stored at least
except
or from the last
daily if using a
chlorophyll a)
manual
continuous
and -20ฐ C for
reading) in
temperature
the chlorophyll
comment
logger and twice
a sample
field. Lab will
daily (once at
still perform
beginning of the
test. EPA
day and once at
expects that
the end) not using
the laboratory
a continuous
will exercise
logger
every effort to
maintain
samples at the
correct
temperature
Analyze
All
The test must
Perform test in
sample within
be completed
all cases, but
holding time
within the
note reason for
holding time
performing test
specified in
outside holding
the analytical
time. EPA
method
expects that
the laboratory
will exercise
every effort to
perform tests
before the
holding time
expires
Analyze
All
Once per day prior
Control limits
Prepare and
Laboratory/
to sample analysis
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QC Sample
Indicators
Description
Frequency
Acceptance
Corrective
Type and
Criteria
Action
Description
any sample
analyses.
Reestablish
statistical
control by
analyzing three
blank samples
Analyze
All dissolved
ASTM Type II
Prepare once per
Measured
Measure
Filtration
analytes
reagent water
week and archive
concentrations
archived
Blank
processed
Prepare filter
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QC Sample
Indicators
Description
Frequency
Acceptance
Corrective
Type and
Criteria
Action
Description
sample
(volume
permitting).
Review
precision of
QCCS
measurements
for batch.
Check
preparation of
split sample.
Qualify all
samples in
batch for
possible
reanalysis
Analyze
When
One analysis in a
Manufacturers
Analyze
Standard
available for
minimum of five
certified range
standard in
Reference
a particular
separate batches
next batch to
Material
indicator
confirm
(SRM)
suspected
inaccuracy.
Evaluate
calibration and
QCCS
solutions and
standards for
contamination
and preparation
error. Correct
before any
further
analyses of
routine
samples are
conducted.
Reestablish
control by three
successive
reference
standard
measurements
that are
acceptable.
Qualify all
sample batches
analyzed since
the last
acceptable
reference
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QC Sample
Indicators
Description
Frequency
Acceptance
Corrective
Type and
Criteria
Action
Description
standard
measurement
for possible
reanalysis
Analyze
Only
One per batch
Control limits
Select two
Matrix Spike
prepared
for recovery
additional
Samples
when
cannot exceed
samples and
samples with
100ฑ20%
prepare fortified
potential for
subsamples.
matrix
Reanalyze all
interferences
suspected
are
samples in
encountered
batch by the
method of
standard
additions.
Prepare three
subsamples
(unfortified,
fortified with
solution
approximately
equal to the
endogenous
concentration,
and fortified
with solution
approximately
twice the
endogenous
concentration)
Use
All
Verify that all
Data reporting
For each
If it is not
consistent
units are
indicator, all
possible to
units for QC
provided
field and QC
provide the
samples and
consistently
samples are
results in
field samples
within each
reported with
consistent
indicator
the same
units, then
measurement
assign a QC
units
code and
describe the
reason for
different units
in the
comments field
of the database
Maintain
All
Determine
Data reporting
Completeness
Contact EPA
completeness
completeness
objective is
HQ NCCA
95% for all
Laboratory
indicators
Review
(useable with
Coordinator*
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QC Sample
Type and
Description
Indicators
Description
Frequency
Acceptance
Criteria
Corrective
Action
or without
flags)
immediately if
issues affect
laboratory's
ability to meet
completeness
objective
"Chapter 2 of the LOM provides contact information for the EPA HQ NCCA Laboratory Review
Coordinator. Laboratories under contract to EPA must contact the Task Order's Contracting Officer's
Representative (TOCOR) instead of the Laboratory Review Coordinator.
5.2.3.3 Data Reporting
Data reporting units and significant figures are summarized in Table 5.8
Table 5.8 Data Reporting Criteria: Water Chemistry Indicator
No. Significant
Maximum No.
Measurement
Units
Figures
Decimal Places
Total phosphorus
mg P/L
3
3
Total nitrogen
Mg N/L
3
2
Nitrate-Nitrite
mg/L as N
3
2
Ammonia
mg/L as N
3
2
Chlorophyll-a
Hg/L
2
1
pH (laboratory)
pH units
3
2
Conductivity (Laboratory)
|jS/cm at 25 ฐC
3
1
5.2.4 Pertinent Field QA/QC Procedures
Field data quality is addressed, in part, by application and consistent performance of valid procedures
documented in the standard operating procedures detailed in the NCCA FOM. That quality is enhanced
by the training and experience of project staff and documentation of sampling activities. Field crews will
verify that all sample containers are uncontaminated and intact, and that all sample labels are legible
and intact.
Before leaving the field, the crews will:
ฆ Check all labels to ensure that all written information is complete and legible.
ฆ Place a strip of clear packing tape over the labels, covering the label completely.
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ฆ Enter a flag code and provide comments on the Sample Collection Form in the App if
there are any problems in collecting the sample or if conditions occur that may affect
sample integrity.
ฆ Store the CHEM and NUTS indicators on wet ice in a cooler. Maintain CHLA filters frozen
until shipping on wet ice.
ฆ Recheck all forms and labels for completeness and legibility.
5.2.4.1 Field Performance Requirements
Not Applicable
5.2.4.2 Field Quality Control Requirements
See Table 5.9 and Table 5.10 for quality control activities and corrective actions.
Table 5.9 Sample field processing quality control activities: water chemistry indicator (CHEM).
Quality Control
Activity
Description and Requirements
Corrective Action
Water Chemistry
Rinse collection bottles 3x with ambient water
Discard sample. Rinse bottle
Container and
before collecting water samples.
and refill.
Preparation
Sample Storage
Store samples in darkness at 4ฐC.
Qualify sample as suspect for
all analyses.
Ship on wet ice within 24 hours of collection.
Table 5.10 Sample field processing quality control: chlorophyll-a (CHLA) and dissolved nutrient (NUTS) indicators
Quality Control
Activity
Description and Requirements
Corrective Action
Chlorophyll-a
Rinse collection bottles 3x with ambient water
Discard sample. Rinse bottle
Containers and
before collecting water samples.
and refill.
Preparation
Holding Time
Complete filtration of chlorophyll-a after all water
samples are collected.
Qualify samples
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Filtration (done
in field)
Use Whatman 0.7 |a,m GF/F filter. Filtration
pressure should not exceed 3.4 psig to avoid
rupture of fragile algal cells.
Rinse sample bottle for dissolved nutrient (NUTS)
3x with 10-20 mL of filtrate before collecting 250
mL of filtrate for analysis.
Discard and refilter
Sample Storage
CHLA: Filters are placed in centrifuge tube
wrapped in foil square and stored on dry ice in
field.
NUTS: Filtrate is stored on wet ice in field.
CHLA and NUTS are shipped within 24 hours of
collection on wet ice along with water chemistry
(CHEM).
Qualify sample as suspect for
all analyses.
5.2.5 Data Review
Checks made of the data in the process of review and verification are summarized in Table 5.11. The
NCCA Project QA Coordinator is ultimately responsible for ensuring the validity of the data, although
performance of the specific checks may be delegated to other staff members.
Table 5.11 Data Validation Quality Control for Water Chemistry Indicator.
Activity or Procedure Requirements and Corrective Action
Range checks, summary statistics, and/or
exploratory data analysis (e.g., box and whisker
plots)
Correct reporting errors or qualify as suspect or
invalid.
Review holding times
Qualify value for additional review
Review data from QA samples (laboratory PE
samples, and interlaboratory comparison samples)
Determine impact and possible limitations on
overall usability of data
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5.3 Cylindrospermopsin
5.3.1 Introduction
Crews will collect a water sample at the index site to measure concentrations of total
Cylindrospermopsin, an algal toxin.
5.3.2 Sample Design and Methods
Detailed sample collection and handling procedures are found in the NCCA 2020 Field Operations
Manual. Detailed laboratory methods are in the NCCA 2020 Laboratory Operations Manual.
5.3.3 Pertinent Laboratory QA/QC Procedures
A single central laboratory and some State laboratories will analyze the Cylindrospermopsin samples.
The specific quality control procedures used by each laboratory are implemented to ensure that:
ฆ Objectives established for various data quality indicators are being met.
ฆ Results are consistent and comparable among all participating laboratories.
All laboratories will follow the procedures outlined in the NCCA 2020 QAPP and the LOM.
5.3.3.1 Laboratory Performance Requirements
Performance requirements for the Cylindrospermopsin indicator are listed in Table 5.12.
Table 5.12 Measurement Quality Objectives for Cylindrospermopsin.
Parameter
Units
Method Detection
Limit Objective
Reporting Limit Objective
Cylindrospermopsin, undiluted
samples with salinities <8 part
pg/L
0.05
0.10
per thousand (ppt)
Cylindrospermopsin, undiluted
samples with salinity >8 ppt
must dilute 1:5 prior to
running the kit
pg/L
0.05
Will vary
5.3.3.2 Laboratory Quality Control Requirements
Quality control requirements for the Cylindrospermopsin indicator are listed in Table 5.13. Sample
receipt and other processing requirements are listed in Table 5.14.
Table 5.13 Sample analysis quality control activities and objectives for Cylindrospermopsin
Quality Control Activity
Description and Requirements
Corrective Action
Kit - Shelf Life
Is within its expiration date
listed on kit box.
If kit has expired, then discard or set
aside for training activities.
Kit - Contents
All required contents must be
present and in acceptable
condition. This is important
If any bottles are missing or
damaged, discard the kit.
Quality Assurance Project Plan
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because Abraxis has
calibrated the standards and
reagents separately for each
kit.
Calibration
All of the following must be
If any requirement fails:
met:
Results from the analytical run are
not reported.
Standard curve must have a
All samples in the analytical run are
reanalyzed until calibration provides
correlation coefficient of
acceptable results. At its discretion,
>0.99;
the laboratory may consult with
USEPA for guidance on persistent
Average absorbance value,
difficulties with calibration.
Ao, for SO must be >0.80; and
Standards S0-S6 must have
decreasing average
absorbance values. That is, if
Ai is the average of the
absorbance values for Si,
then the absorbance average
values must be: Ao > Ai > A2 >
A3 > A4 >A5>A6
Kit Control
The average concentration
If either requirement fails:
value of the duplicates (or
triplicate) must be within the
Results from the analytical run are
range of 0.75 +/- 0.15 pg/L.
That is, results must be
not reported
between 0.60 and 0.90.
Negative Control
The values for the negative
The laboratory evaluates its
control replicates must meet
processes, and if appropriate,
the following requirements:
modifies its processes to correct
possible contamination or other
All concentration values must
problems.
be < 0.1 ng/L (i.e., the
reporting limit); and
The laboratory reanalyzes all
samples in the analytical run until the
One or more concentration
controls meet the requirements.
results must be
nondetectable (i.e., <0.05
Mfl/L)
Sample Evaluations
All samples are run in
If %CV of the absorbance for the
duplicate. Each duplicate pair
sample>15%, then:
must have %CV<15%
Record the results for both
between its absorbance
duplicates using different start dates
values.
and/or start times to distinguish
between the runs.
Report the data for both duplicate
results using Quality Control Failure
flag "QCF"; and
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Re-analyze the sample in a new
analytical run. No samples are to
be run more than twice.
If the second run passes, then the
data analyst will exclude the data
from the first run (which will have
been flagged with "QCF"). If both
runs fail, the data analyst will
determine if either value should be
used in the analysis (e.g., it might be
acceptable to use data if the CV is
just slightly over 15%).
Results Within Calibration
Range
All samples are run in
duplicate. If both of the values
are less than the upper
calibration range (i.e., 2.0
|jg/L for undiluted samples),
then the requirement is met.
If a result registers as "HIGH", then
record the result with a data flag of
"HI." If one or both duplicates
register as 'HIGH,' then the sample
must be diluted and re-run. No
samples are to be run more than
twice. If samples are re-run, do not
enter concentration information of
the first run.
External Quality Control
Sample
External QC Coordinator,
supported by QC contractor,
provides 1-2 sets of identical
samples to all laboratories
and compares results.
Based upon the evaluation, the
External QC Coordinator may
request additional information from
one or more laboratories about any
deviations from the method or
unique laboratory practices that
might account for differences
between the laboratory and others.
With this additional information, the
External QC Coordinator will
determine an appropriate course of
action, including no action, flagging
the data, or excluding some or all of
the laboratory's data.
Table 5.14 Sample receipt and processing quality control: Cylindrospermopsin indicator indicator.
Quality Control
Activity
Description and Requirements
Corrective Action
Sample Log-in
Upon receipt of a sample shipment, record receipt
of samples in the NARS IM system (within 24 clock
hours) and the laboratory's Information
Management System (LIMS).
Discrepancies, damaged, or
missing samples are reported to
the EPA HQs Laboratory QA
Coordinator
Sample condition
upon receipt
Sample issues such as cracked container; missing
label; temperature (frozen); adherence to holding
time requirements; sufficient volume for test.
Qualify samples
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Sample Storage
Store sample frozen
Qualify samples
Holding time
Frozen samples can be stored for several months.
Qualify samples
5.3.3.3 Data Reporting
Data reporting units and significant figures are summarized in Table 5.15.
Table 5.15 Data Reporting Criteria: Cylindrospermopsin Indicator.
Measurement
Units
No.
Maximum No.
Significant
Decimal Places
Figures
Cylindrospermopsin
ug/L
3
3
5.3.4 Pertinent Field QA/QC Procedures
Field data quality is addressed, in part, by application and consistent performance of valid procedures
documented in the standard operating procedures detailed in the NCCA 2020 FOM. That quality is
enhanced by the training and experience of project staff and documentation of sampling activities.
Crews will collect a single water sample for Cylindrospermopsin analyses. Field crews will verify that all
sample containers are uncontaminated and intact, and that all sample labels are legible and intact.
While in the field, the crew will store samples in a cooler on ice and will then freeze the sample upon
returning to the base site (hotel, lab, office). Before leaving the field, the crews will:
ฆ Check all labels to ensure that all written information is complete and legible.
ฆ Place a strip of clear packing tape over the labels, covering the label completely.
ฆ Enter a flag code and provide comments on the Sample Collection Form in the App if
there are any problems in collecting the sample or if conditions occur that may affect
sample integrity.
ฆ Store the sample on ice in field.
ฆ Recheck all forms and labels for completeness and legibility.
5.3.4.1 Field Performance Requirements
Not Applicable.
5.3.4.2 Field Quality Control Requirements
See Table 5.16 for quality control activities and corrective actions.
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Table 5.16 Sample field processing quality control: Cylindrospermopsin indicator.
Quality Control
Activity
Description and Requirements
Corrective Action
Holding time
Hold sample on wet ice and freeze immediately
upon return to the base site (hotel, lab, office) and
keep frozen until shipping
Qualify samples
Sample Storage
Store samples in darkness and frozen (-20 ฐC)
Monitor temperature daily
Qualify sample as suspect
5.3.5 Data Review
Checks made of the data in the process of review and verification are summarized in Table 5.17. The
NCCA Project QA Coordinator is ultimately responsible for ensuring the validity of the data, although
performance of the specific checks may be delegated to other staff members.
Table 5.17 Data Validation Quality Control for Cylindrospermopsin Indicator.
Activity or Procedure Requirements and Corrective Action
Range checks, summary statistics, and/or
exploratory data analysis (e.g., box and
whisker plots)
Correct reporting errors or qualify as
suspect or invalid.
Review holding times
Qualify value for additional review
Review data from QA samples (laboratory
PE samples, and interlaboratory
comparison samples)
Determine impact and possible
limitations on overall usability of data
5.4 Microcystins
5.4.1 Introduction
Crews will collect a water sample at the index site to measure concentrations of total microcystins, an
algal toxin.
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5.4.2 Sample Design and Methods
Detailed sample collection and handling procedures are found in the NCCA 2020 Field Operations
Manual. Detailed laboratory methods are in the NCCA 2020 Laboratory Operations Manual.
5.4.3 Pertinent Laboratory QA/QC Procedures
A single central laboratory and some State laboratories will analyze the microcystins samples. The
specific quality control procedures used by each laboratory are implemented to ensure that:
ฆ Objectives established for various data quality indicators are being met.
ฆ Results are consistent and comparable among all participating laboratories.
All laboratories will follow the procedures outlined in the NCCA 2020 QAPP and the LOM.
5.4.3.1 Laboratory Performance Requirements
Performance requirements for the microcystins indicator are listed in Table 5.18.
Table 5.18 Measurement Quality Objectives for Microcystins.
Parameter
Units
Method Detection
Limit Objective
Reporting Limit Objective
Microcystins, undiluted
samples with salinities <3.5
part per thousand (ppt)
ijg/L
0.1
0.15
Microcystins, undiluted
samples with salinity greater
than or equal to 3.5 ppt
|jg/i
0.175
0.263
Microcystins, diluted samples
with salinities <3.5 ppt
|jg/i
0.1 times the dilution
factor
Will vary
Microcystins, diluted samples
with salinity greater than or
equal to 3.5 ppt
|jg/i
1.75 times the dilution
factor
Will vary
5.4.3.2 Laboratory Quality Control Requirements
Quality control requirements for the microcystins indicator are listed in Table 5.19. Sample receipt and
other processing requirements are listed in Table 5.20.
Table 5.19 Sample analysis quality control activities and objectives for microcystins
Quality Control
Activity
Description and Requirements
Corrective Action
Kit - Shelf Life
Is within its expiration date listed on kit box.
If kit has expired, then discard or
clearly label as expired and set
aside for training activities.
Kit - Contents
All required contents must be present and in
acceptable condition. This is important
because Abraxis has calibrated the standards
and reagents separately for each kit.
If any bottles are missing or
damaged, discard the kit.
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Calibration
All of the following must be met:
Standard curve must have a correlation
coefficient of >0.99;
Average absorbance value, Ao, for SO must be
>0.80; and
Standards S0-S5 must have decreasing
average absorbance values. That is, if Ai is the
average of the absorbance values for Si, then
the absorbance average values must be: Ao>
Ai > A2 > A3 > A4 >A5
If any requirement fails:
Results from the analytical run are
not reported.
All samples in the analytical run
are reanalyzed until calibration
provides acceptable results.
Kit Control The average concentration value of the
duplicates must be within the range of 0.75 +/-
( 0.185 |jg/L. That is, the average must be
between 0.565 |jg/L and 0.935 |jg/L.
If either requirement fails:
Results from the analytical run are
not reported
The lab evaluates its processes,
and if appropriate, modifies its
processes to correct possible
contamination or other problems.
The lab reanalyzes all samples in
the analytical run until the controls
meet the requirements. At its
discretion, the lab may consult with
EPA for guidance on persistent
difficulties with calibration.
Negative Control
The values for the negative control replicates
must meet the following requirements:
All concentration values must be < 0.15 |jg/L
(i.e., the reporting limit; and
one or more concentration results must be
nondetectable (i.e., <0.10 jjg/L)
Sample
Evaluations
All samples are run in duplicate. Each
duplicate pair must have %CV<15% between
its absorbance values.
If %CV of the absorbances for the
sample>15%, then:
Record the results for both
duplicates using different start
dates and/or start times to
distinguish between the runs.
Report the data for both duplicate
results using the Quality Control
Failure flag "QCF"; and
re-analyze the sample in a new
analytical run. No samples are to
be run more than twice.
If the second run passes, then the
data analyst will exclude the data
from the first run (which will have
been flagged with "QCF"). If both
runs fail, the data analyst will
determine if either value should be
used in the analysis (e.g., it might
be acceptable to use data if the CV
is just slightly over 15%).
Results Within
Calibration
Range
All samples are run in duplicate. If both of the
values are less than the upper calibration
range (i.e., < 5.0 |jg/L for undiluted samples
with salinity <3.5 ppt; < 8.75 |jg/L for undiluted
samples with salinity >3.5 ppt), then the
requirement is met.
If a result registers as 'HIGH', then
record the result with a data flag of
"HI." If one or both duplicates
register as 'HIGH,' then the sample
must be diluted and re-run until
both results are within the
calibration range. No samples are
to be run more than twice. The lab
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reports both the original and
diluted sample results.
External Quality
Control Sample
External QC Coordinator, supported by QC
contractor, provides 1-2 sets of identical
performance testing samples to all laboratories
and compares results.
Based upon the evaluation, the
External QC Coordinator may
request additional information from
one or more laboratories about any
deviations from the method or
unique laboratory practices that
might account for differences
between the laboratory and others.
With this additional information, the
External QC Coordinator will
determine an appropriate course of
action, including no action, flagging
the data, or excluding some or all
of the laboratory's data.
Table 5.20 Sample receipt and processing quality control: microcystins indicator indicator.
Quality Control
Activity
Description and Requirements
Corrective Action
Sample Log-in
Upon receipt of a sample shipment, record receipt
of samples in the NARS IM system (within 24 clock
hours) and the laboratory's Information
Management System (LIMS).
Discrepancies, damaged, or
missing samples are reported to
the EPA HQs Laboratory QA
Coordinator
Sample condition
upon receipt
Sample issues such as cracked container; missing
label; temperature (frozen); adherence to holding
time requirements; sufficient volume for test.
Qualify samples
Sample Storage
Store sample frozen
Qualify samples
Holding time
Frozen samples can be stored for several months.
Qualify samples
5.4.3.3 Data Reporting
Data reporting units and significant figures are summarized in Table 5.21.
Table 5.21 Data Reporting Criteria: Microcystins Indicator.
Measurement
Units
No.
Maximum No.
Significant
Decimal Places
Figures
Microcystins
ug/L
3
3
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5.4.4 Pertinent Field QA/QC Procedures
Field data quality is addressed, in part, by application and consistent performance of valid procedures
documented in the standard operating procedures detailed in the NCCA 2020 FOM. That quality is
enhanced by the training and experience of project staff and documentation of sampling activities.
Crews will collect a single water sample for microcystins analyses. Field crews will verify that all sample
containers are uncontaminated and intact, and that all sample labels are legible and intact. While in the
field, the crew will store samples in a cooler on ice and will then freeze the sample upon returning to the
base site (hotel, lab, office). Before leaving the field, the crews will:
ฆ Check all labels to ensure that all written information is complete and legible.
ฆ Place a strip of clear packing tape over the labels, covering the labels completely.
ฆ Enter a flag code and provide comments on the Sample Collection Form in the App if
there are any problems in collecting the sample or if conditions occur that may affect
sample integrity.
ฆ Store the sample on ice in field.
ฆ Recheck all forms and labels for completeness and legibility.
5.4.4.1 Field Performance Requirements
Not Applicable.
5.4.4.2 Field Quality Control Requirements
See Table 5.22 for quality control activities and corrective actions.
Table 5.22 Sample field processing quality control: microcystins indicator.
Quality Control
Activity
Description and Requirements
Corrective Action
Holding time
Hold sample on wet ice and freeze immediately
upon return to the base site (hotel, lab, office) and
keep frozen until shipping
Qualify samples
Sample Storage
Store samples in darkness and frozen (-20 ฐC)
Monitor temperature daily
Qualify sample as suspect
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5.4.5 Data Review
Checks made of the data in the process of review and verification are summarized in Table 5.23. The
NCCA Project QA Coordinator is ultimately responsible for ensuring the validity of the data, although
performance of the specific checks may be delegated to other staff members.
Table 5.23 Data Validation Quality Control for Microcystins Indicator.
Activity or Procedure Requirements and Corrective Action
Range checks, summary statistics, and/or
exploratory data analysis (e.g., box and
whisker plots)
Correct reporting errors or qualify as
suspect or invalid.
Review holding times
Qualify value for additional review
Review data from QA samples (laboratory
PE samples, and interlaboratory
comparison samples)
Determine impact and possible
limitations on overall usability of data
5.5 Benthic Invertebrates
5.5.1 Introduction
The Benthic invertebrates inhabit the sediment (infauna) or live on the bottom substrates or aquatic
vegetation (epifauna) of coastal areas. The response of benthic communities to various stressors can
often be used to determine types of stressors and to monitor trends (Klemm et al., 1990). The overall
objectives of the benthic invertebrate indicators are to detect stresses on community structure in
National coastal waters and to assess and monitor the relative severity of those stresses. The benthic
invertebrate indicator procedures are based on various recent bioassessment litrature (Barbour et al.
1999, Hawkins et al. 2000, Klemm et al. 2003), previous coastal surveys (US EPA 2001C, US EPA 2004A,
US EPA 2008,), and the procedures used in NCCA 2010, and 2015.
5.5.2 Sample Design and Methods
Detailed sample collection and handling procedures are described in the NCCA 2020 Field Operations
Manuals. Detailed information on the benthic processing procedure are described in the NCCA 2020
Laboratory Operations Manual.
5.5.3 Pertinent Laboratory QA/QC Procedures
A single central laboratory and some State laboratories will analyze the benthic invertebrate samples.
The specific quality control procedures used by each laboratory are implemented to ensure that:
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ฆ Objectives established for various data quality indicators are being met.
ฆ Results are consistent and comparable among all participating laboratories.
All laboratories will follow the procedures outlined in the NCCA 2020 QAPP and the LOM.
For the NCCA 2020, laboratories and EPA will implement quality control in three primary ways. First,
laboratories will conduct internal QC for sorters as described in the LOM (10% of all samples [minimum
of 1] completed per sorter). Second, laboratories will conduct internal QC for taxonomists identifying
benthic invertebrates as described in the LOM (1 in 10 samples per taxonomist). Finally, EPA will
randomly select 10% of samples for identification by an independent, external taxonomist as described
in the LOM (10% of all samples completed by each laboratory).
5.5.3.1 Laboratory Performance Requirements
Measurement quality objectives (MQOs) are given in Table 5.24. General requirements for
comparability and representativeness are addressed in Section 2. Precision is calculated as percent
efficiency, estimated from examination of randomly selected sample residuals by a second analyst and
independent identifications of organisms in randomly selected samples. The MQO for sorting and
picking accuracy is estimated from examinations (repicks) of randomly selected residues by an
experienced QC Sorter.
Equation 5.1 Percent sorting efficiency (PSE)
Number of organisms found by the sorter (A) compared to the combined (total) number of organisms
found by the sorter (A) and the number recovered by the QC Officer (B) from Sorter A's pickate for a
sample. PSE should be >90%.
A
PSE = x 100
A + B
Equation 5.2 Percent disagreement in enumeration (PDE)
Measure of taxonomic precision comparing the number of organisms, rii, counted in a sample by the
primary taxonomist with the number of organisms, n2, counted by the internal or external QC
taxonomist. PDE should be <5%.
\n,
pde = ' x 100
nx + n2
Equation 5.3 Percent taxonomic disagreement (PTD)
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Measure of taxonomic precision comparing the number of agreements (positive comparisons, comppos)
of the primary taxonomist and internal or external QC taxonomists. In the following equation, N is the
total number of organisms in the larger of the two counts. PTD should be <15%.
PTD
r comp ^
pos
N
x 100
Table 5.24 Benthic Macroinvertebrates: Measurement Data Quality Objectives
Variable or Measurement
Precision
Accuracy
Sort and Pick
90% a
90% a
Identification
85% b
95% c
NA = not applicable;a As measured by PSE; b As measured by (100%-PTD);c As measured by (100%-PDE)
5.5.3.2 Laboratory Quality Control Requirements
Quality Control Requirements for the benthic invertebrate indicator are provided in Table 5.25 and
Table 5.26.
Table 5.25 Benthic Macroinvertebrates: Laboratory quality control
Check or Sample
Frequency
Acceptance Criteria
Corrective Action
Description
SAMPLE PROCESSING AND SORTING
Sample pickate
examined by another
sorter
10% of all
samples
(minimum of 1)
completed per
sorter
PSE > 90%
If < 90%, examine all residuals
of samples by that sorter and
retrain sorter
IDENTIFICATION
Duplicate
identification by
Internal Taxonomy
QC Officer
1 in 10 samples
per taxonomist,
PTD <15%
If PTD >15%, reidentify all
samples completed by that
taxonomist since last meeting
the acceptance criteria,
focusing on taxa of concern
Independent
identification by
outside, expert,
taxonomist
All uncertain taxa
Uncertain identifications
to be confirmed by
expert in particular taxa
Record both tentative and
independent IDs
External QC
10% of all
samples
completed per
laboratory
PDE < 5%
PTD< 15%
If PDE > 5%, implement
recommended corrective
actions.
If PTD > 15%, implement
recommended corrective
actions.
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Use of
widely/commonly
accepted taxonomic
references by all
NCCA labs
For all
identifications
All keys and references
used by each lab must
be on bibliography
prepared by one or
more additional NCCA
labs. This requirement
demonstrates the
general acceptance of
the references by the
scientific community.
If a lab proposes to use other
references, the lab must
obtain prior permission from
External QC Officer before
submitting the data with the
identifications based upon the
references.
Prepare reference
collection2
Each new taxon
per laboratory
Complete reference
collection to be
maintained by each
individual laboratory
Internal Taxonomy QC Officer
periodically reviews data and
reference collection to ensure
reference collection is
complete and identifications
are accurate
DATA VALIDATION
Taxonomic
"reasonableness"
checks
All data sheets
Taxa known to occur for
coastal waters or Great
Lakes.
Second or third identification
by expert in that taxon
Table 5.26 Sample receipt and processing quality control: benthic invertebrate indicator.
Quality Control
Description and Requirements
Corrective Action
Activity
Sample Log-in
Upon receipt of a sample shipment, record
receipt of samples in the NARS IM system (within
24 clock hours) and the laboratory's Information
Management System (LIMS).
Discrepancies, damaged, or
missing samples are reported to
the EPA HQs Laboratory QA
Coordinator
Sample
condition upon
receipt
Sample issues such as cracked container; missing
label; preservation.
Qualify samples
Sample Storage
Store benthic samples in a cool, dark place.
Qualify sample as suspect for all
analyses
Preservation
Transfer storage to 70% ethanol for long term
storage
Qualify samples
Holding time
Preserved samples can be stored indefinitely;
periodically check jars and change the ethanol if
sample material appears to be degrading.
Qualify samples
2 If requested, EPA can return reference collection materials and/or other sample materials.
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5.5.4 Pertinent Field QA/QC Procedures
Field data quality is addressed, in part, by application and consistent performance of valid procedures
documented in the standard operating procedures detailed in the NCCA 2020 Field Operations Manuals.
That quality is enhanced by the training and experience of project staff and documentation of sampling
activities. Field Crews enter a flag code and provide comments on the Sample Collection Form in the App
if there are any problems in collecting the sample or if conditions occur that may affect sample integrity.
Before leaving the field, the crews will:
ฆ Check the labels to ensure that all written information is complete and legible.
ฆ Ensure the waterproof benthic infauna labels placed inside the jar contain the pertinent
information (including the sample ID and jar number).
ฆ Place a strip of clear packing tape over the labels, covering the labels completely.
ฆ Enter a flag code and provide comments on the Sample Collection Form in the App if
there are any problems in collecting the sample or if conditions occur that may affect
sample integrity.
ฆ Preserve the sample with formalin.
ฆ Recheck all forms and labels for completeness and legibility.
5.5.4.1 Field Performance Requirements
Not Applicable
5.5.4.2 Field Quality Control Requirements
Specific quality control measures are listed in Table 5.27 for field quality control requirements.
Table 5.27 Sample Collection and Field Processing Quality Control: Benthic Invertebrate Indicator.
Quality Control Activity Description and Requirements Corrective Action
Check integrity of sample
containers and labels
Clean, intact containers and labels
Obtain replacement
supplies
Sample Processing (field)
Use 0.5 mm mesh sieve. Preserve with ten percent
buffered formalin. Fill jars no more than 1/2 full of
material to reduce the chance of organisms being
damaged.
Discard and recollect
sample
Sample Storage (field)
Store benthic samples in a cool, dark place until
shipment to analytical lab
Discard and recollect
sample
Holding time
Preserved samples can be stored indefinitely;
periodically check jars and change the ethanol
(change from formalin to ethanol for long term
Change ethanol
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storage) if sample material appears to be
degrading.3
Preservation
Transfer storage to 70% ethanol for long term
storage
Qualify samples
5.5.5 Data Review
Checks made of the data in the process of review and verification is summarized in Table 5.28. The NCCA
Project QA Coordinator is ultimately responsible for ensuring the validity of the data, although
performance of the specific checks may be delegated to other staff members.
Table 5.28 Data Validation Quality Control for Benthic Macroinvetebrates.
Activity or Procedure Requirements and Corrective Action
Review data and reports from Laboratories
Determine impact and possible limitations on
overall usability of data
Review data and reports from External QC
Coordinator
Determine impact and possible limitations on
overall usability of data
Review taxonomic names and spellings
Correct and qualify
5.6 Sediment Contaminants, Total Organic Carbon (TOC) and Grain Size
5.6.1 Introduction
Field crews will collect sediment grabs for chemical contaminant analyses (organics/metals), TOC and
grain size determination.
5.6.2 Sample Design and Methods
Detailed sample collection and handling procedures are described in the NCCA 2020 Field Operations
Manual. Detailed laboratory methods are in the NCCA 2020 Laboratory Operations Manual.
5.6.3 Pertinent Laboratory QA/QC Procedures
A single central laboratory and some State laboratories will analyze the sediment contaminants, TOC
and grain size samples. The specific quality control procedures used by each laboratory are implemented
to ensure that:
3 In most cases, crews will ship samples to the batch lab within 2 weeks, so long-term storage will not be an issue for
field crews.
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ฆ Objectives established for various data quality indicators being met.
ฆ Results are consistent and comparable among all participating laboratories.
All laboratories will follow the QA/QC procedures outlined in the NCCA QAPP and the LOM.
5.6.3.1 Laboratory Performance Requirements
The laboratory shall perform analysis of the sediment samples to determine the moisture content, grain
size, and concentrations of TOC, metals, pesticides, PAHs, and PCBs.
To demonstrate its competency in analysis of sediment samples, the laboratory shall provide analyte
and matrix specific information to EPA. EPA will accept one or more of the following as a demonstration
of competency:
Memorandum that identifies the relevant services that the laboratory provided for the National
Aquatic Resource Surveys in the past five years.
Documentation detailing the competency of the organization, including professional
certifications for water-related analyses, membership in professional societies, and experience
with analyses that are the same or similar to the requirements of this method.
Demonstration of competency with sediment samples in achieving the method detection limits,
accuracy, and precision targets.
To demonstrate its competency in quality assurance and quality control procedures, the organization
shall provide EPA with copies of the quality-related documents relevant to the procedure. Examples
include Quality Management Plans (QMP), QAPPs, and applicable Standard Operating Procedures
(SOPs). To demonstrate its ongoing commitment to quality assurance, the person in charge of quality
issues for the organization shall sign the NCCA QAPP Certification Page.
Precision and accuracy objectives are identified in Table 5.29. Table 5.30 identifies the storage
requirements. Laboratories may choose to use any analysis method, including those in Table 5.30, which
measures the parameters to the levels of the method detection limits identified in Table 5.31.
Table 5.29 Sediment Contaminants, Grain size and TOC: Precision and Accuracy Objectives
Parameter
Precision
Objective
(measured by)
Accuracy
Objective
(measured by)
All Contaminants
30% (RPD between
MS and MSD)
20% (average %Rs
between MS and MSD)
TOC
10% (RPD between
duplicates)
10% (CRM)
Grain Size
10% (LCS)
Not Applicable
* RPD=Relative Percent Difference; %Rs=%Recovery; MS=Matrix Spike; MSD=Matrix Spike Duplicate;
CRM=Certified Reference Material; LCS=Lab Control Sample.
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Table 5.30 Sediment Contaminants, Grain Size, and TOC: Analytical Methods
Storage Requirements
Type
Methods that Meet the QA/QC
Requirements (any method that
meets the QA/QC requirements is
acceptable)
Freeze samples to a
Metals (except Mercury)
Extraction: EPA Method 3051A
temperature < -20ฐ C
Analysis: EPA Method 6020A4
Mercury
EPA Method 245.7s
PCBs, Pesticides, PAHs
Extraction: EPA Method 3540C
Analysis: EPA Method 8270D6
TOC
USEPA Method 9060
Refrigerate at 4ฐ C
(do not freeze)
Grain Size
Any method that reports the
determination as percent silt, sand
and clay and meets QA/QC
requirements
4 For example, see:
Method 3051A "Microwave Assisted Acid Digestion of Sediments, Sludges, Soils, And Oils" retrieved
November 13, 2018 from https://www.epa.gov/sites/production/files/2015-12/documents/3051a.pdf; and
Method 6020A "Inductively Coupled Plasma-Mass Spectrometry" retrieved April 28, 2018 from
https://www.epa.gov/sites/production/files/2015-07/documents/epa-6Q20a.pdf.
5 For example, see Method 245.7 "Mercury in Water by Cold Vapor Atomic Fluorescence Spectrometry, Revision
2.0" (EPA-821-R-05-001, February 2005), retrieved March 13, 2019 from
https://www.nemi.gov/methods/method summarv/9629/.
6 For example, see:
Method 3540C "Soxhlet Extraction" retrieved June 27, 2014 from
https://www.epa. gov/sites/production/files/2015-12/documents/3 540c.pdf: and
Method 8270D "Semivolatile Organic Compounds by Gas Chromatography/Mass Spectrometry (GC/MS)
retrieved March 13, 2019 from https://www.epa.gov/sites/production/files/2015-07/documents/epa-
8270d.pdf
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Table 5.31 Sediment Contaminants, Grain Size, and TOC: Required Parameters.
PCB NUMBER
TYPE UNITS PARAMETER (WHERE
APPLICABLE)
CAS
NUMBER
MAX CONC BASED UPON MDL
2010 AND 2015 DATA TARGET*
REPORTING
LIMIT
TARGET**
TARGET
ACCURACY
TARGE
PRECISIC
% silt,
% sand,
% clay
Grain Size
0.05%
0.05
10% (LCS)
mg/kg
or %
Total Organic Carbon
54.5
0.01%
0.02%
10%
10%
METAL
dry
weight
Mg/g,
(ppm)
7429-90-5
Aluminum
162000
1500
5
20
30
7440-36-0
Antimony
38.1
0.2
0.05
20
30
7440-38-2
Arsenic
147.61
1.5
0.05
20
30
7440-43-9
Cadmium
9.9
0.05
0.005
20
30
7440-47-3
Chromium
1078.78
5
0.005
20
30
7440-50-8
Copper
2290
5
0.005
20
30
7439-89-6
Iron
169000
500
5
20
30
7439-92-1
Lead
461
1
0.005
20
30
7439-96-5
Manganese
6587.02
1
0.01
20
30
7439-97-6
Mercury
3.12
0.01
0.00002
20
30
7440-02-0
Nickel
360.17
1
0.02
20
30
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TYPE UNITS
CAS
NUMBER
PARAMETER
11
PCB NUMBER
(WHERE
APPLICABLE)
MAX CONC BASED UPON
2010 AND 2015 DATA
MDL
TARGET*
REPORTING
TARGET
LIMIT
ACCURACY
TARGET"
PRECISION
7782-49-2
Selenium
121.019
0.1
0.05
20
30
7440-22-4
Silver
35.34
0.3
0.02
20
30
7440-31-5
Tin
258
0.1
0.05
20
30
7440-62-2
Vanadium
4734
1
0.05
20
30
7440-66-6
Zinc
1750
2
0.05
20
30
2051-24-3
2,2',3,3',4,4',5,5',6,6'-
Decachlorobiphenyl
209
22.4
1
5
20
30
34883-43-7
2,4'-Dichlorobiphenyl
8
10.7
1
5
20
30
35065-30-6
2,2',3,3',4,4',5-
Heptachlorobiphenyl
170
115.4
1
5
20
30
| dry
I weight
PCB I
| ng/g,
(ppb)
52663-68-0
2,2',3,4',5,5',6-
Heptachlorobiphenyl
187
56.8
1
5
20
30
35065-29-3
2,2',3,4',5,5',6-
Heptachlorobiphenyl
180
249.4
1
5
20
30
38380-07-3
2,2',3,3',4,4'-
Hexachlorobiphenyl
128
61.3
1
5
20
30
35065-28-2
2,2',3,4,4',5'-
Hexachlorobiphenyl
138
362
1
5
20
30
35065-27-1
2,2',4,4',5,5'-
Hexachlorobiphenyl
153
168.7
1
5
20
30
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TYPE UNITS
CAS
NUMBER
PARAMETER
PCB NUMBER
(WHERE
APPLICABLE)
MAX CONC BASED UPON
2010 AND 2015 DATA
MDL
TARGET*
REPORTING
LIMIT
TARGET**
TARGET
ACCURACY
PRECISION
40186-72-9
2,2',3,3',4,4',5,5',6-
Nonachlorobiphenyl
206
75.5
1
5
20
30
52663-78-2
2,2',3,3',4,4',5,6-
Octachlorobiphenyl
195
40
1
5
20
30
32598-14-4
2,3,3',4,4'-
Pentachlorobiphenyl
105
78.2
1
5
20
30
37680-73-2
2,2',4,5,5'-
Pentachlorobiphenyl
101
256
1
5
20
30
31508-00-6
2,3,4,4',5-
Pentachlorobiphenyl
118
201
1
5
20
30
38380-03-9
2,3,3',4,6'-
Pentachlorobiphenyl
110
249
1
5
20
30
57465-28-8
3,3',4,4',5-
Pentachlorobiphenyl
126
3.5
1
5
20
30
41464-39-5
2,2',3,5'-
Tetrachlorobiphenyl
44
54.3
1
5
20
30
32598-13-3
3,3',4,4'-
Tetrachlorobiphenyl
77
8.8
1
5
20
30
35693-99-3
2,2',5,5'-
Tetrachlorobiphenyl
52
123
1
5
20
30
32598-10-0
2,3',4,4'-
Tetrachlorobiphenyl
66
36.6
1
5
20
30
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i||ggtai
TYPE
UNITS
CAS
NUMBER
PARAMETER
PCB NUMBER
(WHERE
APPLICABLE)
MAX CONC BASED UPON
2010 AND 2015 DATA
MDL
TARGET*
REPORTING
LIMIT
TARGET**
TARGET
ACCURACY
PRECISION
37680-65-2
2,2',5-Trichlorobiphenyl
18
18.4
1
5
20
30
7012-37-5
2,4,4'-Trichlorobiphenyl
28
39.5 | 1
5
20
30
53-19-0
2,4'-DDD
10.2
1
5
20
30
3424-82-6
2,4'-DDE
6.4
1
5
20
30
789-02-6
2,4'-DDT
114.1
1
5
20
30
72-54-8
4,4'-DDD
100.6
1
5
20
30
72-55-9
4,4'-DDE
29.5
1
5
20
30
50-29-3
4,4'-DDT
59.3
1
5
20
30
dry
309-00-2
Aldrin
13.3
1
5
20
30
weight
ng/g,
(ppb)
PEST
319-84-6
Alpha-BHC
#N/A
1
5
20
30
319-85-7
Beta-BHC
510.4
1
5
20
30
319-86-8
Delta-BHC
7.2
1
5
20
30
5103-71-9
Alpha-Chlordane
3.7
1
5
20
30
5566-34-7
Gamma-Chlordane
5.1
1
5
20
30
60-57-1
Dieldrin
2.3
1
5
20
30
959-98-8
Endosulfan 1
#N/A
1
5
20
30
33213-65-9
Endosulfan II
21.2
1
5
20
30
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TYPE UNITS
CAS
NUMBER
PARAMETER
PCB NUMBER
(WHERE
APPLICABLE)
MAX CONC BASED UPON
2010 AND 2015 DATA
MDL
TARGET*
REPORTING
LIMIT
TARGET**
TARGET
ACCURACY
PRECISION
1031-07-8
Endosulfan Sulfate
8.1
1
5
20
30
72-20-8
Endrin
13.2
1
5
20
30
7421-93-4
Endrin Aldehyde
#N/A
1
5
20
30
53494-70-5
Endrin Ketone
#N/A
1
5
20
30
76-44-8
Heptachlor
5.3
1
5
20
30
1024-57-3
Heptachlor Epoxide
3.5
1
5
20
30
118-74-1
Hexachlorobenzene
173.7
1
5
20
30
58-89-9
Lindane
163.3
1
5
20
30
2385-85-5
Mi rex
9.1
1
5
20
30
5103-73-1
Cis-Nonachlor
1.9
1
5
20
30
26880-48-8
Oxychlordane
13.4
1
5
20
30
39765-80-5
Trans-Nonachlor
3.6
1
5
20
30
83-32-9
Acenaphthene
1437.9
1
5
20
30
! dry
208-96-8
Acenaphthylene
1530
1
5
20
30
I weight
PAH I
| ng/g,
(ppb)
120-12-7
Anthracene
4343
1
5
20
30
56-55-3
Benz(a)anthracene
#N/A
1
5
20
30
205-99-2
Benzo(b)fluoranthene
11125.6
1
5
20
30
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TYPE UNITS
CAS
NUMBER
PARAMETER
PCB NUMBER
(WHERE
APPLICABLE)
MAX CONC BASED UPON
2010 AND 2015 DATA
MDL
TARGET*
REPORTING
LIMIT
TARGET**
TARGET
ACCURACY
PRECISION
207-08-9
Benzo(k)fluoranthene
8530.9
1
5
20
30
191-24-2
Benzo(g,h,i)perylene
#N/A
1
5
20
30
50-32-8
Benzo(a)pyrene
10158.6
1
5
20
30
192-97-2
Benzo(e)pyrene
#N/A
1
5
20
30
92-52-4
Biphenyl
#N/A
1
5
20
30
218-01-9
Chrysene
13600
1
5
20
30
53-70-3
Dibenz(a,h)anthracene
1513.5
1
5
20
30
132-65-0
Dibenzothiophene
1000
1
5
20
30
581-42-0
2,6-Dimethylnaphthalene
283.7
1
5
20
30
206-44-0
Fluoranthene
38970
1
5
20
30
86-73-7
Fluorene
1594.8
1
5
20
30
193-39-5
lndeno(l,2,3-c,d)pyrene
6615.5
1
5
20
30
90-12-0
1-Methylnaphthalene
487
1
5
20
30
91-57-6
2-Methylnaphthalene
430.5
1
5
20
30
832-69-9
1-Methylphenanthrene
903
1
5
20
30
91-20-3
Naphthalene
694
1
5
20
30
198-55-0
Perylene
2157
1
5
20
30
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TYPE UNITS
CAS
NUMBER
PARAMETER
PCB NUMBER
(WHERE
APPLICABLE)
MAX CONC BASED UPON MDL
2010 AND 2015 DATA TARGET*
REPORTING
LIMIT
TARGET**
TARGET
ACCURACY
TARGE
PRECISIC
85-01-8
Phenanthrene
20000
1
5
20
30
129-00-0
Pyrene
30000
1
5
20
30
2245-38-7
2,3,5-
Trimethylnaphthalene
411
1
5
20
30
*For samples requiring dilution, the lowest possible dilution factor should be used to achieve a valid
measurement. Labs must report the dilution factor for any diluted sample, and the MDL/RL may be
adjusted by the dilution factor used to achieve a valid measurement.
**The reporting limits (RL) listed are those reported by the National Contract Lab in the NCCA 2015 data.
The RLs are targets only. Inability to achieve the listed RL for any parameters will not be considered a QA
failure. However, please contact the EPA Task Order Contracting Officer's Representative if you have any
questions.
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5.6.3.2 Laboratory Quality Control Requirements
The laboratory must conduct QC analyses for each batch of samples. Each batch shall consist of no more
than 20 samples. Unique laboratory quality control lot numbers must be assigned to each batch of
samples. The lot number must associate each batch of field samples to the appropriate measures such
as laboratory control sample, matrix spike, laboratory duplicate, and method blank samples. Also, each
laboratory QC samples (i.e., preparation and instrument blanks, laboratory control sample (LCS),
spike/duplicate, etc.) must be given a unique sample identification. Table 5.32 provides a summary of
the quality control requirements including sample receipt and processing.
Table 5.32 Sediment Chemistry, Grain Size, and TOC: Quality control activities for samples.
Activity
Evaluation
Corrective Action
Demonstrate competency for
analyzing sediment samples to
meet the performance measures
Demonstration of competency
with sediment samples in
achieving the method detection
limits, accuracy, and precision
targets
EPA will not approve any
laboratory for NCCA sample
processing if the laboratory
cannot demonstrate
competency. In other words, EPA
will select another laboratory
that can demonstrate
competency for its NCCA
samples.
Check condition of sample when
it arrives.
Sample issues such as cracked
container; missing label;
sufficient volume for test.
Assign appropriate condition
code identified in Table 7.4. of
the LOM
Store sample appropriately.
While stored at the laboratory,
the sample must be kept at a
temperature <-20ฐ C except jars
for grain analyses are
refrigerated at 4ฐC.
Check the temperature of the
freezer and refrigerator per
laboratory's standard operating
procedures.
Record temperature of sample
upon arrival at the laboratory. If
at any other time, samples are
warmer than required, note
temperature and duration in
comment field.
Data analyst will consider
temperature deviations in
evaluating the data. He/she will
flag the deviations and
determine whether the data
appear to be affected and/or the
data should be excluded from
the analyses.
Analyze sample within holding
time
The test must be completed
within the holding time of 1
year. If the original test fails,
then the retest also must be
Perform test but note reason for
performing test outside holding
time. EPA expects that the
laboratory will exercise every
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conducted within the holding effort to perform tests before
time. the holding time expires.
Perform once at the start of each
batch to evaluate the labeled
compound recovery (LCR) in a
Laboratory Control Sample (LCS).
This tests the performance of
the equipment.
Control limits for recovery First, prepare and analyze one
cannot exceed 100ฑ20%. additional LCS. If the second
blank meets the requirement,
then no further action is
required. If the second LCS fails,
then determine and correct the
problem before proceeding with
any sample analyses.
Perform once at the start of each
batch to evaluate the entire
extraction and analysis process
using a Method Blank
Control limits cannot exceed the First, prepare and analyze one
laboratory reporting level (LRL). additional blank. If the second
blank meets the requirement,
then no further action is
required. If the second blank
fails, then determine and correct
the problem (e.g.,
contamination, instrument
calibration) before proceeding
with any sample analyses.
Reestablish statistical control by
analyzing three blank samples.
Report values of all blanks
analyzed.
Check calibration immediately
before and immediately after
the sample batch (abbreviated
as QCCS for quality control check
sample)
Results must be ฑ10% of each If calibration fails before
other or as specified in method analysis, recalibrate and
criteria reanalyze QCCS until it passes. If
check fails after all samples the
batch have been analyzed, verify
the QCCS reading. If the QCCS
reading fails a second time, then
reanalyze all samples in the
batch and report only the set of
results associated with the
acceptable QCCS reading. Also
report all QCCS readings for the
batch.
Compare results of one
laboratory duplicate sample (for
TOC) or matrix spike duplicate
(for contaminant) sample for
each batch (not required for
grain size)
Results must be within the target If both results are below LRL,
and precision goals in Table 7.3 then conclude that the test has
of the LOM passed. Otherwise, prepare and
analyze a split from different
sample in the batch. If the
second result is within the target
precision goal of the original
sample, then report the data and
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findings for both QC samples.
However, if the two results differ
by more than the target
precision goal, review precision
of QCCS measurements for
batch; check preparation of split
sample; etc. and report
evaluation and findings in the
case narrative. Consult with the
EPA HQ NCCA Laboratory Review
Coordinator to determine if
reanalysis of the entire batch (at
the laboratory's expense) is
necessary. If no reanalysis is
necessary, report and quantify
all samples in batch. If reanalysis
is necessary, then report all QC
sample and the 2nd analysis of
the batch. If the second set also
is unacceptable, then assign a
data code to each sample in the
batch.
Compare results of one matrix
Evaluate performance after the If both the original and duplicate
spike sample per batch to
first 3 batches; and then every results are below LRL, then
evaluate performance in matrix
subsequent batch. Ideally, conclude that the test has
(not required for TOC and grain
control limits for recovery will passed for the batch. Otherwise,
size)
not exceed the target accuracy if any results are not within the
goal, but this may not be realistic target accuracy goal for the first
for all parameters with this 3 batches, within 2 working days,
matrix. contact the EPA HQ NCCA
Laboratory Review Coordinator
to discuss method performance
and potential improvements.
After achieving acceptable
results or EPA's permission to
continue, perform the test for
every subsequent batch. For
each batch, report the results
from the original analysis and its
duplicate and their RPD for TOC;
the matrix spike, matrix spike
duplicate, RPD and %recovery
for contaminants.
Compare results of TOC Certified
Value must be within 10% of the If value is outside the acceptable
Reference Material once per
certified value. range, analyze a second CRM. If
each batch
the second CRM also is
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measured outside the
acceptable range, then
determine and correct the
problem (e.g., contamination,
instrument calibration) before
reanalyzing all samples in the
batch.
Maintain the required MDL
Evaluate for each sample If MDL could not be achieved,
, then provide dilution factor or
j | QC code and explanation in the
comment field.
Participate in External Quality
Evaluate QC samples provided by Based upon the evaluation, the
Control
the External QC Coordinator External QC Coordinator may
request additional information
from one or more laboratories
about any deviations from the
Method or unique laboratory
practices that might account for
differences between the
laboratory and others. With this
additional information, the
External QC Coordinator will
determine an appropriate course
of action, including no action,
flagging the data, or excluding
some or all of the laboratory's
data.
Maintain completeness
Completeness objective is 95% Contact EPA HQ NCCA
for all parameters. Laboratory Review Coordinator
immediately if issues affect
laboratory's ability to meet
completeness objective.
"Chapter 2 of the LOM provides contact information for the EPA HQ NCCA Laboratory Review
Coordinator. Laboratories under contract to EPA must contact the Task Order's Contracting Officer's
Representative (TOCOR) instead of the Laboratory Review Coordinator.
5.6.3.3 Data Reporting
Data reporting units and significant figures are summarized in Table 5.33.
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Table 5.33 Data Reporting Criteria: Sediment Contaminants, TOC and Grain Size indicators.
Measurement
Units
Expressed to the
Nearest
Sediment
Pesticides and PCBs
ng/g; PPb (sediment: dry wt)
0.01
Metals
ug/g; PPm (sediment: dry wt)
0.01
Hg
ug/g; ppm (sediment: dry wt)
0.001
PAHs
ng/g; ppb (dry wt)
0.01
TOC
%
0.01
Grain Size
%
0.01
5.6.4 Pertinent Field QA/QC Procedures
Field data quality is addressed, in part, by application and consistent performance of valid procedures
documented in the standard operating procedures detailed in the NCCA 2020 FOM. That quality is
enhanced by the training and experience of project staff and documentation of sampling activities.
Crews will collect a sediment sample for sediment contamination, TOC and grain size analyses. Field
crews will verify that all sample containers are uncontaminated and intact, and that all sample labels are
legible and intact.
Before leaving the field, the crews will:
ฆ Check the label to ensure that all written information is complete and legible.
ฆ Place a strip of clear packing tape over the label, covering the label completely.
ฆ Enter a flag code and provide comments on the Sample Collection Form in the App if
there are any problems in collecting the sample or if conditions occur that may affect
sample integrity.
ฆ Store the sediment contaminants and TOC samples on dry ice. Store grain size samples
on wet ice.
ฆ Recheck all forms and labels for completeness and legibility.
5.6.4.1 Field Performance Requirements
Not Applicable
5.6.4.2 Field Quality Performance Requirements
Any contamination of the samples can produce significant errors in the resulting interpretation. Crews
must take care not to contaminate the sediment with the tools used to collect the sample (i.e., the
sampler, spoons, mixing bowl or bucket) and not to mix the surface layer with the deeper sediments.
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Prior to sampling at each site, crews must clean the sampler and collection tools that will come into
contact with the sediment with Alconox and rinse them with ambient water at the site. Field processing
quality control requirements can be found in Table 5.34 and Table 5.35.
Table 5.34 Sample collection and field processing quality control: sediment contaminant indicator.
Quality Control Activity Description and Requirements Corrective Action
Check integrity of sample
containers and labels
Clean, intact containers and labels.
Obtain replacement
supplies
Sample Storage (field)
Store sediment samples on dry ice and in
a dark place (cooler).
Discard and recollect
sample
Shipping time
Frozen samples must be shipped on dry
ice within 2 weeks of collection.
Logistics coordinator
contacts crew and
requests samples be
shipped every week
Table 5.35 Sample collection and field processing quality control: sediment TOCand grain size indicator.
Quality Control Activity Description and Requirements Corrective Action
Check for homogeneity
Sample must be homogeneous.
Mix sample for a longer
period of time
Sample Storage (field)
Store sediment (TOC) samples on dry ice and
grain size indicators on wet ice. Store all
samples in a dark place (cooler).
Discard and recollect
sample
Holding time
TOC samples must be shipped on dry ice within
2 weeks of collection.
Grain size indicators must be shipped on wet
ice every week.
Qualify samples
Check integrity of
sample containers and
labels
Clean, intact containers and labels.
Obtain replacement
supplies
5.6.5 Data Review
Checks made of the data in the process of review and verification is summarized in Table 5.36. The NCCA
Project QA Coordinator is ultimately responsible for ensuring the validity of the data, although
performance of the specific checks may be delegated to other staff members.
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Table 5.36 Data Validation Quality Control for Sediment Contaminants, TOC and Grain Size Indicators.
Activity or Procedure Requirements and Corrective Action
Range checks, summary statistics, and/or
exploratory data analysis (e.g., box and whisker
plots)
Correct reporting errors or qualify as suspect
or invalid.
Review holding times
Qualify value for additional review
Review data from QA samples (laboratory PE
samples, and interlaboratory comparison
samples)
Determine impact and possible limitations on
overall usability of data
5.7 Sediment Toxicity
5.7.1 Introduction
Toxicity tests will be completed on sediments from both marine/estuarine and freshwater
environments. Both tests determine toxicity, in terms of survival rate of amphipod crustaceans, in
whole sediment samples.
5.7.2 Sample Design and Methods
Detailed sample collection and handling procedures are described in the NCCA 2020 Field Operations
Manual. Laboratory methods are in the NCCA 2020 Laboratory Operations Manual.
5.7.3 Pertinent Laboratory QA/QC Procedures
A single central laboratory and some State laboratories will analyze the sediment toxicity. The specific
quality control procedures used by each laboratory are implemented to ensure that:
ฆ Objectives established for various data quality indicators being met.
ฆ Results are consistent and comparable among all participating laboratories.
All laboratories will follow the QA/QC procedures outlined in the NCCA QAPP and the LOM.
5.7.3.1 Laboratory Performance Requirements
Laboratories may choose to use any analysis method using the required organisms of Hyalella azteca
(freshwater) or Leptocheirus plumulosus (estuarine). The laboratory's method must meet the quality
requirements in Section 9.7 of the LOM, including mean survival of the control's freshwater and
estuarine treatments must remain greater than or equal to 80% and 90%, respectively. It is essential
that the contractor require that all of its laboratory technicians use the same procedures and meet the
required quality elements. At a minimum, the laboratory must:
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1. Perform the procedures using the 10-day tests. Possible methods include those described in the
following documents:
a. Estuarine: Test Method 100.4 in EPA 600/R-94/0257 or ASTM E1367-038
b. Freshwater: Test Method 100.1 in EPA 600/R-99/0649 or ASTM E170610
2. Test the following number of replicates for each sample and control:
a. Estuarine: 5 replicates with 20 organisms per replicate
b. Freshwater: 4 replicates with 10 organisms per replicate
3. Test no more than 10 samples and one control within each batch.
4. Use the following organisms for the tests:
a. Estuarine: Leptocheirus plumulosus
b. Freshwater: Hyalella azteca
5. Select organisms for each batch of tests that are:
a. From the same culture;
b. Cultured at the same temperature as will be used for the tests;
c. (optional) EPA would prefer but does not require that the organisms are cultured in the
same water as that used for testing.
6. Use a water source (for the overlying water) demonstrated to support survival, growth, and
reproduction of the test organisms.
a. For estuarine sediments, 175 mL of sediment and 800 mL of overlying seawater
b. For freshwater sediments, lOOmL of sediment and 175mL of overlying freshwater
7. Use clean sediment for control tests.
8. Implement the following for exposure/feeding
a. For estuarine sediments, exposure is static (i.e., water is not renewed), and the animals
are not fed over the 10 d exposure period
b. For freshwater, exposure is renewed (i.e., 2 volumes a day) and the animals are fed over
the 10 day exposure period
7 Chapter 11 in Methods for Assessing the Toxicity of Sediment-associated Contaminants with Estuarine and Marine
Amphipods, June 1994, retrieved May 22, 2019 from
https://nepis.epa. gov/Exe/ZvPDF.cgi/300032A9.PDF?Dockev=300032A9.PDF
8 American Society for Testing and Materials (ASTM). 2008. E1367-03 "Standard Guide for Conducting 10-Day
Static Sediment Toxicity Tests With Marine and Estuarine Amphipods." Annual Book of Standards, Water and
Environmental Technology, Vol. 11.05, West Conshohocken, PA.
9 Section 11 in Methods for Measuring the Toxicity and Bioaccumulation of Sediment-associated Contaminants with
Freshwater Invertebrates, Second Edition, March 2000, retrieved from
https://pdfs.semanticscholar.org/6876/ca3e48ad5ecdefd46b6600f9346d5be845b6.pdf
10 ASTM 2009 E1706. "Standard Test Method for Measuring the Toxicity of Sediment-Associated Contaminants
with Freshwater Invertebrates."
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5.7.3.2 Follow the following procedure for homogenization/sieving:
Water above the sediment is not discarded, but is mixed back into the sediment during homogenization.
Sediments should be sieved for estuarine samples (following the 10 day method) and the sieve size
should be noted. For freshwater samples, they should not be sieved to remove indigenous organisms
unless there is a good reason to believe indigenous organisms may influence the response of the test
organism. Large indigenous organisms and large debris can be removed using forceps
Laboratory Quality Control Requirements
The laboratory must conduct QC analyses for each batch of samples. Each batch shall consist of no more
than 10 samples. Unique laboratory quality control lot numbers must be assigned to each batch of
samples. The lot number must associate each batch of field samples to the appropriate measures such
as laboratory control samples. Table 5.37 provides a summary of the quality control requirements
including sample receipt and processing.
Table 5.37 Quality control activities for sediment toxicity samples.
Activity Evaluation Corrective Action
Laboratory demonstrates
competency for conducting
sediment toxicity analyses
EPA will review SOPs, lab
certifications, past performance
results, etc. as part of the lab
verification process.
EPA will not approve any
laboratory for NCCA sample
processing if the laboratory
cannot demonstrate
competency. In other words,
EPA will select another
laboratory that can
demonstrate competency for its
NCCA samples.
Check condition of sample
when it arrives.
Sample issues, such as cracked
or leaking container; missing
label; temperature; adherence
to holding time requirements;
insufficient volume for test.
Assign appropriate condition
code identified in Table 9.1 of
the LOM
Sample storage
All samples: 4 ฐC at arrival at the
laboratory (temperature
recorded at arrival) and while
stored at the laboratory.
Record temperature upon
arrival at the laboratory. Check
temperature of the refrigerator
where samples are stored at
least daily if using a continuous
temperature logger and twice
daily (beginning and end of day)
if the lab does not have a
continuous logger. If
refrigerator is warmer than
required, note temperature and
duration (either from the
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Holding Time
continuous temperature log or
from the last manual reading) in
comment field. Lab will still
perform test. EPA expects that
the laboratory will exercise
every effort to maintain
samples at the correct
temperature.
The test must be completed
within 8 weeks after sample
collection. If the original test
fails, then the retest also must
be conducted within the 8
weeks after sample collection.
Perform test but note reason
for performing test outside
holding time. EPA expects that
the laboratory will exercise
every effort to perform tests
before the holding time expires.
Check that the organisms are Unhealthy organisms may Don't start test using unhealthy
healthy before starting the test appear to be discolored, or organisms.
otherwise stressed (for
| example, greater than 20
percent mortality for the 48
hours before the start of a test).
Maintain conditions as required Check conditions (e.g.,
in Section 9.3 of the LOM temperature, DO) each test day.
| Record conditions in bench
sheet or in laboratory database.
Note any deviations in
comments field. In extreme
cases, conduct a new toxicity
test for all samples affected by
the adverse conditions.
Control survival rates
For a test of a batch of samples Data template includes a field
to be considered valid, the to record if a test passed or
control's mean survival in failed the control requirements.
hyalella and leptocheirus If a test fails, retest all samples
treatments must remain >80% in the batch. Report both the
and >90%, respectively. original and retest results. If
both tests fail, submit data to
EPA for further consideration.
Include comments in the data
template noting any particular
factors that may have caused
the test to fail twice.
"Chapter 2 of the LOM provides contact information for the EPA HQ NCCA Laboratory Review
Coordinator. Laboratories under contract to EPA must contact the Task Order's Contracting Officer's
Representative (TOCOR) instead of the Laboratory Review Coordinator.
5.7.3.3 Data Reporting
Data reporting units and significant figures are given in Table 5.38.
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Table 5.38 Data Reporting Review Critera: Sediment Toxicity.
Sediment toxicity
%
Survival integer
5.7.4 Pertinent Field QA/QC Procedures
Field data quality is addressed, in part, by application and consistent performance of valid procedures
documented in the standard operating procedures detailed in the NCCA 2020 FOM. That quality is
enhanced by the training and experience of project staff and documentation of sampling activities.
Crews will collect a sediment sample for sediment toxicity. Field crews will verify that all sample
containers are uncontaminated and intact, and that all sample labels are legible and intact.
Before leaving the field, the crews will:
ฆ Check the label to ensure that all written information is complete and legible.
ฆ Place a strip of clear packing tape over the label, covering the label completely.
ฆ Enter a flag code and provide comments on the Sample Collection Form in the App if
there are any problems in collecting the sample or if conditions occur that may affect
sample integrity.
ฆ Store the sample on wet ice.
ฆ Recheck all forms and labels for completeness and legibility.
5.7.4.1 Field Performance Requirements
Not Applicable
5.7.4.2 Field Quality Control Requirements
Any contamination of the samples can produce significant errors in the resulting interpretation. Crews
must take care not to contaminate the sediment with the tools used to collect the sample (i.e., the
sampler, spoons, mixing bucket) and not to mix the surface layer with the deeper sediments. Prior to
sampling at each site, crews must clean the sampler and collection tools that will come into contact with
the sediment with Alconox and rinse them with ambient water at the site. Field processing quality
control requirements are summarized in Table 5.39.
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Table 5.39 Sample collection and field processing quality control: sediment toxicity indicator.
Quality Control Activity Description and Requirements Corrective Action
Check integrity of
sample containers and
labels
Clean, intact containers and labels.
Obtain replacement
supplies
Sample Volume
Preferred maximum volume 2000 mL;
minimum volume 900 mL (estuarine); For Great
Lakes sites, preferred volume is 900 mL,
minimum is 400 mL.
Qualify samples if less
than 900 mL available to
submit to lab (less than
400 mL for GL sites.
Sample Storage (field)
Store sediment samples on wet ice and in a
dark place (cooler).
Discard and recollect
sample
Holding time
Refrigerated samples must be shipped on wet
ice within 1 week of collection.
Qualify samples
5.7.5 Data Review
Checks made of the data in the process of review, verification, and validation are summarized in Table
5.40. The NCCA Project QA Coordinator is ultimately responsible for ensuring the validity of the data,
although performance of the specific checks may be delegated to other staff members.
Table 5.40 Data validation quality control: sediment toxicity.
Activity or Procedure
Requirements and Corrective Action
Summary statistics, and/or exploratory data
analysis (e.g., box and whisker plots)
Correct reporting errors or qualify as suspect
or invalid.
Review data from reference toxicity samples
Determine impact and possible limitations on
overall usability of data
5.8 Fecal Indicator: Enterococci
5.8.1 Introduction
The primary function of collecting water samples for Pathogen Indicator Testing is to provide a relative
comparison of fecal pollution indicators for coastal waters. The concentration of Enterococci (the
current bacterial indicator for fresh and estuarine waters) in a water body correlates with the level of
more infectious gastrointestinal pathogens present in the water body. While some Enterococci are
opportunistic pathogens among immuno-compromised human individuals, the presence of Enterococci
is more importantly an indicator of the presence of more pathogenic microbes (bacteria, viruses and
protozoa) associated with human or animal fecal waste.
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5.8.2 Sampling Design and Methods
Detailed sample collection and handling procedures are described in the NCCA 2020 Field Operations
Manual.
5.8.3 Pertinent Laboratory QA/QC Procedures
Pertinent laboratory QA/QC procedures are in the EPA ORD manuals/QAPP.
5.8.3.1 Data Reporting, Review and Management
Checks made of the data in the process of review, verification, and validations are summarized in Table
5.41. All raw data (including all standardized forms and logbooks) are retained in an organized fashion
for seven years or until written authorization for disposition has been received from the NCCA Project
Lead. Once data have passed all acceptance requirements, data is submitted to the NARS Project Lead
and then to the NARS IM processing center.
Table 5.41 Data Validation Quality Control: Fecal Indicator.
Check Description Frequency Acceptance Criteria Corrective Action
Duplicate
sampling
Duplicate composite
samples collected at
10% of sites
Measurements should be
within 10 percent
Review data for reasonableness;
determine if acceptance criteria
need to be modified
Field filter blanks
Field blanks filtered
at 10% of sites
Measurements should be
within 10 percent
Review data for reasonableness;
determine if acceptance criteria
need to be modified
DATA PROCESSING & REVIEW
100% verification
and review of
qPCR data
All qPCR
amplification traces,
raw and processed
data sheets
All final data will be
checked against raw
data, exported data, and
calculated data printouts
before entry into LIMS
and upload to NARS IM.
Second tier review by
contractor and third tier review
by EPA.
5.8.4 Pertinent Field QA/QC Procedures
5.8.4.1 Field Performance Requirements
Not Applicable
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5.8.4.2 Field Quality Control Requirements
Field data quality is addressed, in part, by application and consistent performance of valid procedures
documented in the standard operating procedures detailed in the NCCA 2020 Field Operations Manual.
That quality is enhanced by the training and experience of project staff and documentation of sampling
activities. Specific quality control measures are listed in Table 5.42 for field measurements and
observations.
Table 5.42 Sample Collection and Field Processing Quality Control: Fecal Indicator
Quality Control Activity Description and Requirements Corrective Action
Check integrity of sample
containers and labels
Clean, intact containers and labels
Obtain replacement
supplies
Sterility of sample
containers
Sample collection bottle and filtering apparatus are
sterile and must be unopened prior to sampling.
Nitrile gloves must be worn during sampling and
filtering
Discard sample and
recollect in the field.
Sample Collection
Collect sample at the last transect to minimize
holding time before filtering and freezing
Discard sample and
recollect in the field.
Sample holding
Sample is held in a cooler on wet ice until filtering.
Discard sample and
recollect in the field.
Field Processing
Sample is filtered within 6 hours of collection and
filters are frozen on dry ice.
Discard sample and
recollect in the field
Field Blanks
Field blanks must be filtered at 10% of sites.
Review blank data and
flag sample data.
5.9 Whole Fish Tissue Samples for Ecological Analysis
5.9.1 Introduction
Fish collected as indicators of ecological contamination (Eco-fish) will be collected at all sites to be
analyzed for whole body concentrations of organic and inorganic contaminants. This will also include
the analysis and reporting of lipid content, sample weight and percent moisture. Results from these
analyses will be used to help determine the ecological integrity of U.S. coastal resources.
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5.9.2 Sample Design and Methods
Detailed sample collection and handling procedures are described in the NCCA 2020 Field Operations
Manual. Laboratory methods are in the NCCA 2020 Laboratory Operations Manual..
5.9.3 Pertinent Laboratory QA/QC Procedures
5.9.3.1 Laboratory Performance Requirements
A single central laboratory shall perform analysis of the homogenized composites to determine the lipid
content, concentrations of metals, mercury, pesticides, and PCBs. EPA also may require the national
contract laboratory to analyze the samples for PAHs; however, EPA will not require the State
laboratories to analyze for them. With the exception of sea urchins, NCCA does not provide support
for analyses of any other invertebrates such as crustaceans (e.g., lobster, crabs).
Laboratories may choose to use any analysis method that measures contaminants to the levels of the
method detection limits identified in Table 5.43. In addition, the method must meet the target precision
of 30% and the target accuracy identified in Table 5.44.
Table 5.43 Whole Fish Tissue: Precision and Accuracy Objectives.
Parameter
Precision
Objective
Accuracy
Objective
Metals
30%
20%
Organics (PCBs, pesticides, and PAHs)
30%
35%
Table 5.44 Whole Body Fish: Required Contaminants.
Type
Units
Parameter
CAS Number PCB Number
MDL
Reporting
(where
Target**
Limit
applicable)
Target***
LIPID
% Wet
Weight
% LIPID
0.05
METAL
jjg/wet g
Aluminum
7429-90-5
10.0
5
(mg/L)
Arsenic
7440-38-2
2.0
0.05
Cadmium
7440-43-9
0.2
0.05
Chromium
7440-47-3
0.1
0.05
Copper
7440-50-8
5.0
0.05
Iron
7439-89-6
50.0
5
Lead
7439-92-1
0.1
0.05
Mercury
7439-97-6
0.01
0.00002
Nickel
7440-02-0
0.5
0.05
Selenium
7782-49-2
1.0
0.05
Silver
7440-22-4
0.3
0.05
Tin
7440-31-5
0.05
0.05
Vanadium
7440-62-2
1.0
0.05
Zinc
7440-66-6
50.0
0.05
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Type
Units
Parameter
CAS Number PCB Number
MDL
Reporting
(where
Target**
Limit
applicable)
Target***
PCB
ng/wet g
(mq/l)
2,2',3,3',4,4',5,5',6,6'
-Decachlorobiphenyl
2051-24-3
209
2.0
5
2,4'-
34883-43-7
8
2.0
5
Dichlorobiphenyl
2,2',3,4',5,5',6-
35065-29-3
180
2.0
5
Heptachlorobiphenyl
2,2',3,3'4,4',5,6-
52663-78-2
195
2.0
5
Octachlorobiphenyl
2,2',3,4 ,5,5',6-
52663-68-0
187
2.0
5
Heptachlorobiphenyl
2,2',3,3',4,4'-
38380-07-3
128
2.0
5
Hexachlorobiphenyl
2,2',3,3'4,4',5-
35065-30-6
170
2.0
5
Heptachlorobiphenyl
2,2',3,4,4',5'-
35065-28-2
138
2.0
5
Hexachlorobiphenyl
2,2',4,4',5,5'-
35065-27-1
153
2.0
5
Hexachlorobiphenyl
2,2',3,3',4,4',5,5',6-
40186-72-9
206
2.0
5
Nonachlorobiphenyl
2,3,3',4,4'-
32598-14-4
105
2.0
5
Pentachlorobiphenyl
2,2',4,5,5'-
37680-73-2
101
2.0
5
Pentachlorobiphenyl
2,3',4,4',5-
31508-00-6
118
2.0
5
Pentachlorobiphenyl
2,3,3',4,6'-
38380-03-9
110
2.0
5
Pentachlorobiphenyl
3,3',4,4',5-
57465-28-8
126
2.0
5
Pentachlorobiphenyl
2,2',3,5'-
41464-39-5
44
2.0
5
Tetrachlorobiphenyl
3,3',4,4'-
32598-13-3
77
2.0
5
Tetrachlorobiphenyl
2,2',5,5'-
35693-99-3
52
2.0
5
Tetrachlorobiphenyl
2,3',4,4'-
32598-10-0
66
2.0
5
Tetrachlorobiphenyl
2,2',5-
37680-65-2
18
2.0
5
Trichlorobiphenyl
2,4,4'-
7012-37-5
28
2.0
5
Trichlorobiphenyl
PEST
ng/wet g
2,4'-DDD
53-19-0
2.0
5
(mq/l)
2,4'-DDE
3424-82-6
2.0
5
2,4'-DDT
789-02-6
2.0
5
4,4'-DDD
72-54-8
2.0
5
4,4'-DDE
72-55-9
2.0
5
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Type
Units
Parameter
CAS Number
PCB Number
(where
applicable)
MDL
Target**
Reporting
Limit
Target***
4,4'-DDT
50-29-3
2.0
5
Aldrin
309-00-2
2.0
5
Alpha-BHC
319-84-6
2.0
5
Beta-BHC
319-85-7
2.0
5
Delta-BHC
319-86-8
2.0
5
Alpha-Chlordane
5103-71-9
2.0
5
Gamma-Chlordane
5566-34-7
2.0
5
Dieldrin
60-57-1
2.0
5
Endosulfan I
959-98-8
2.0
5
Endosulfan II
33213-65-9
2.0
5
Endosulfan Sulfate
1031-07-8
2.0
5
Endrin
72-20-8
2.0
5
Endrin Aldehyde
7421-93-4
2.0
5
Endrin Ketone
53494-70-5
2.0
5
Heptachlor
76-44-8
2.0
5
Heptachlor Epoxide
1024-57-3
2.0
5
Hexachlorobenzene
118-74-1
2.0
5
Lindane
58-89-9
2.0
5
Mi rex
2385-85-5
2.0
5
Cis-Nonachlor
5103-73-1
2.0
5
Oxychlordane
26880-48-8
2.0
5
Trans-Nonachlor
39765-80-5
2.0
5
PAHs*
Acenaphthene
83-32-9
2.0
Acenaphthylene
208-96-8
2.0
Anthracene
120-12-7
2.0
Benz(a)anthracene
200-280-6
2.0
Benzo(b)fluoranthen
e
205-99-2
2.0
Benzo(k)fluoranthen
e
207-08-9
2.0
Benzo(g,h,i)perylen
e
191-24-27-2
2.0
Benzo(a)pyrene
50-32-8
2.0
Benzo(e)pyrene
192-97-2
2.0
Biphenyl
92-54-4
2.0
Chrysene
218-01-9
2.0
Dibenz(a,h)anthrace
ne
53-70-3
2.0
Dibenzothiophene
132-65-0
2.0
2,6-
Dimethylnaphthalen
e
581-42-0
2.0
Fluoranthene
205-99-2
2.0
Fluorene
86-73-7
2.0
lndeno(1,2,3-
c,d)pyrene
193-39-5
2.0
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Type
Units
Parameter
CAS Number
PCB Number
(where
applicable)
MDL
Target**
Reporting
Limit
Target***
1-
Methylnaphthalene
90-12-0
2.0
2-
Methylnaphthalene
91-57-6
2.0
1-
Methylphenanthrene
832-69-9
2.0
Naphthalene
91-20-3
2.0
Perylene
198-55-0
2.0
Phenanthrene
85-01-8
2.0
Pyrene
129-00-0
2.0
2,3,5-
Trimethylnaphthalen
e
2245-38-7
2.0
* EPA also may require the national contract laboratory to analyze the samples for PAHs; however, EPA
will not require the State laboratories to analyze for them.
** For samples requiring dilution, the lowest possible dilution factor should be used to achieve a valid
measurement. Labs must report the dilution factor for any diluted sample, and the MDL/RL may be
adjusted by the dilution factor used to achieve a valid measurement.
*** The reporting limits (RL) listed are those reported by the National Contract Lab in the NCCA 2015
data. The RLs are targets only. Inability to achieve the listed RL for any parameters will not be considered
a QA failure. However, please contact the EPA Task Order Contracting Officer's Representative if you
have any questions.
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5.9.3.2 Laboratory Quality Control Requirements
The laboratory must conduct QC analyses for each batch of samples. Each batch shall consist of no more
than 20 samples. Unique laboratory quality control lot numbers must be assigned to each batch of
samples. The lot number must associate each batch of field samples to the appropriate measures such
as laboratory control sample, matrix spike, laboratory duplicate, and method blank samples. Also, each
laboratory QC samples (i.e., preparation and instrument blanks, laboratory control sample (LCS),
spike/duplicate, etc.) must be give a unique sample identification. Table 5.45 provides a summary of the
quality control requirements, including sample receipt and processing.
Table 5.45 Whole Body Fish: Quality control activities.
Quality Control
Description and Requirements
Corrective Action
Activity
Demonstrate
competency for
analyzing fish
samples with the
required methods
Demonstration of competency with fish
samples in achieving the method detection
limits, accuracy, and precision targets.
EPA will not approve any
laboratory for NCCA sample
processing if the laboratory cannot
demonstrate competency. In other
words, EPA will select another
laboratory that can demonstrate
competency for its NCCA samples.
Check condition
of sample when it
arrives
Sample issues, such as punctures or rips in
wrapping; missing label; temperature;
adherence to holding time requirements;
sufficient volume for test. All samples should
arrive at the laboratory in a frozen state.
Assign appropriate condition code
identified in Table 6.1 of the LOM.
Store sample
appropriately.
While stored at
the laboratory,
the sample must
be kept at a
maximum
temperature of
-20ฐ C
Check the temperature of the freezer per
laboratory's standard operating procedures.
Record temperature of sample
upon arrival at the laboratory. If at
any other time, samples are
warmer than required, note
temperature and duration in
comment field.
Determine if all
fish meet the
criteria
Evaluate if the sample contains fish of the
same species and are similar in size (within
75%) and provides enough material to run the
analysis.
Contact the EPA HQ NCCA
Laboratory Review Coordinator*
for a decision on fish selection
and/or chemical analysis.
Analyze sample
within holding
time
The test must be completed within the holding
time (i.e., 28 days for mercury; 6 months for
other metals; and 1 year for all others). If the
original test fails, then the retest also must be
conducted within the holding time.
Perform test but note reason for
performing test outside holding
time. EPA expects that the
laboratory will exercise every effort
to perform tests before the holding
time expires.
Perform once at
the start of each
batch to evaluate
Control limits for recovery cannot exceed
100ฑ20%.
First, prepare and analyze one
additional LCS. If the second blank
meets the requirement, then no
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the labeled
compound
recovery (LCR) in
a Laboratory
Control Sample
(LCS). This tests
the performance
of the equipment
Control limits cannot exceed the laboratory
reporting level (LRL).
further action is required. If the
second LCS fails, then determine
and correct the problem before
proceeding with any sample
analyses.
Perform once at
the start of each
batch to evaluate
the entire
extraction and
analysis process
using a Method
Blank
First, prepare and analyze one
additional blank. If the second
blank meets the requirement, then
no further action is required. If the
second blank fails, then determine
and correct the problem (e.g.,
homogenization, reagent
contamination, instrument
calibration, or contamination
introduced during filtration) before
proceeding with any sample
analyses. Reestablish statistical
control by analyzing three blank
samples. Report values of all
blanks analyzed.
Check calibration
immediately
before and
immediately after
the sample batch
is run
(abbreviated as
QCCS for quality
control check
sample)
Results must be ฑ10% of each other or as
specified in method criteria
If calibration fails before analysis,
recalibrate and reanalyze QCCS
until it passes. If check fails after
all samples in the batch have been
analyzed, verify the QCCS
reading. If the QCCS reading fails
a second time, then reanalyze all
samples in the batch and report
both sets of results. For the first
run, include a data qualifier that
indicates that the QCCS reading
taken immediately following the
first run failed. For the second run,
include a data qualifier that
indicates that it is the second set
and whether the QCCS reading
immediately following that second
run passed. No sample is to be
analyzed more than twice.
Evaluate rinsate
for first sample in
each batch. This
evaluation is a
surrogate for
assessing cross-
contamination
Results must be below laboratory's LRL.
If original rinsate was above LRL,
analyze rinsate from a second
sample. If second rinsate sample
also has results above the LRL,
then assign a data qualifier to all
samples in the batch for the
parameters with results above the
LRL in the rinsates. Also, improve
procedures for cleaning all
surfaces, knives, and
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Compare lipids in
triplicate for the
first sample in
each batch. This
evaluation is a
surrogate for
assessing
homogenization
Substitute the LRL for any value below the LRL
before calculating the RSD. If the RSD of the
triplicate results is <20%, then the
homogenization effort is judged to be sufficient
for all samples in the batch.
homogenization equipment
between samples.
If the RSD could not be achieved,
then regrind all samples in the
batch one or more times as
described in Section 6.5 of the
LOM.
Compare results
of one laboratory
duplicate sample
or matrix spike
duplicate sample
for each batch
Results must be within the target precision goal
in Table 5.44 (30% for all analytes).
If both results are below LRL, then
conclude that the test has passed.
Otherwise, prepare and analyze a
split from different sample in the
batch. If the second result is within
the target precision goal (see
Table 5.44) of the original sample,
then report the data and findings
for both QC samples. However, if
the two results differ by more than
the target precision goal, review
precision of QCCS measurements
for batch; check preparation of split
sample; etc. and report evaluation
and findings in the case narrative.
Consult with the EPA HQ NCCA
Laboratory Review Coordinator* to
determine if reanalysis of the entire
batch (at the laboratory's expense)
is necessary. If no reanalysis is
necessary, report and quantify all
samples in batch. If reanalysis is
necessary, then report all QC
sample and the 2nd analysis of the
batch. If the second set also is
unacceptable, then assign a data
code to each sample in the batch.
Compare results
of one matrix
spike sample per
batch to evaluate
performance in
matrix
Evaluate performance after the first 3 batches.
Ideally, control limits for recovery will not
exceed the target accuracy goal (Table 5.44),
but this may not be realistic for all parameters
with this matrix.
If both results are below LRL, then
conclude that the test has passed
for the batch. Otherwise, if any
results are not within the target
accuracy goal for the 3 batches,
within 2 working days, contact the
EPA HQ NCCA Laboratory Review
Coordinator* to discuss method
performance and potential
improvements. Continue to
perform the test for every batch.
Report the results from the original
analysis, the matrix spike, matrix
spike duplicate, and %recovery.
Maintain the Evaluate for each sample If MDL could not be achieved, then
required MDL provide dilution factor or QC code
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identified in Table
5.44.
and explanation in the comment
field.
Use consistent
units for QC
samples and field
samples
Verify that all units are provided in wet weight
units and consistently within each indicator
type as follows:
Metals in pg/g or ppm.
PCBs, pesticides, and PAHs in ng/g or pg/L.
If dry units are reported for any
sample (QC or field), reanalyze the
sample and report only the
reanalysis results. If it is not
possible to provide the results in
wet units, then assign a QC code
and describe the reason for dry
units in the comments field of the
database.
Maintain
completeness
Completeness objective is 95% for all
parameters.
Contact EPA HQ NCCA
Laboratory Review Coordinator*
immediately if issues affect
laboratory's ability to meet
completeness objective.
"Chapter 2 of the LOM provides contact information for the EPA HQ NCCA Laboratory Review
Coordinator. Laboratories under contract to EPA must contact the Task Order's Contracting Officer's
Representative (TOCOR) instead of the Laboratory Review Coordinator.
5.9.3.3 Data Reporting
Data reporting units and significant figures are given in Table 5.46.
Table 5.46 Data Reporting Criteria: Eco-Fish Tissue Chemistry.
Measurement
Units
Expressed to the
Nearest
Pesticides and PCBs
dry wt and fish tissue wet weight)
0.01
Metals
dry wt and fish tissue wet weight)
0.01
Hg
dry wt and fish tissue wet weight)
0.001
PAHs
ng/g; ppb (dry wt)
0.01
5.9.4 Pertinent Field QA/QC Procedures
Field data quality is addressed, in part, by application and consistent performance of valid procedures
documented in the standard operating procedures detailed in the NCCA 2020 FOM. That quality is
enhanced by the training and experience of project staff and documentation of sampling activities.
Crews will collect whole fish samples for analysis of organic and inorganic contaminants. Field crews
will verify that all sample containers are uncontaminated and intact, and that all sample labels are
legible and intact.
Before leaving the field, the crews will:
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ฆ Check the label to ensure that all written information is complete and legible.
ฆ Place a strip of clear packing tape over the label, covering the label completely.
ฆ Enter a flag code and provide comments on the Sample Collection Form in the App if
there are any problems in collecting the sample or if conditions occur that may affect
sample integrity.
ฆ Store the sample frozen.
ฆ Recheck all forms and labels for completeness and legibility.
5.9.4.1 Field Performance Requirements
Specific field performance requirements/checks are listed in Table 5.47.
Table 5.47 Method quality objectives for field measurement for eco-fish indicator.
Quality Control
Description and Requirements
Corrective Action
Activity
75% rule
Length of smallest fish in the composite must
Indicator lead will review
be at least 75% of the length of the longest
composite data and advise the
fish.
lab before processing begins
5.9.4.2 Field Quality Control Requirements
Specific quality control measures are listed in Table 5.48 for field measurements and observations.
Table 5.48 Field Quality Control: Whole Fish Tissue Samples for Ecological Analysis.
Quality Control Activity Description and Requirements Corrective Action
Check integrity of sample
containers and labels
Clean, intact containers and labels.
Obtain replacement
supplies
Set up fishing equipment
An experienced fisheries biologist sets up the
equipment. If results are poor, a different
method may be necessary.
Note on field data sheet
Field Processing
The fisheries biologist will identify specimens in
the field using a standardized list of common
and scientific names. A re-check will be
performed during processing.
Attempt to catch more
fish of the species of
interest.
Holding time
Frozen samples must be shipped on dry ice
within 2 weeks of collection
Qualify samples
Sample Storage (field)
Keep frozen and check integrity of sample
packaging.
Qualify sample as suspect
for all analyses
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5.9.5 Data Review
Checks made of the data in the process of review, verification, and validation are summarized in Table
5.49 and Table 5.50. The NCCA Project QA Coordinator is ultimately responsible for ensuring the validity
of the data, although performance of the specific checks may be delegated to other staff members.
Table 5.49 Data validation quality control: eco-fish.
Activity or Procedure Requirements and Corrective Action
Summary statistics, and/or exploratory data
analysis (e.g., box and whisker plots)
Correct reporting errors or qualify as suspect
or invalid.
Review data from reference toxicity samples
Determine impact and possible limitations on
overall usability of data
Table 5.50 Data validation quality control: eco-fish tissue indicator.
Check Description Frequency Acceptance Criteria Corrective Action
Taxonomic
"reasonableness"
checks
All data sheets
Generally known to occur
in coastal waters or
geographic area
Second or third identification by
expert in that taxon
Composite validity
check
All composites
Each composite sample
must have 5 fish of the
same species
Indicator lead will review
composite data and advise the
lab before processing begins
75% rule
All composites
Length of smallest fish in
the composite must be at
least 75% of the length of
the longest fish.
Indicator lead will review
composite data and advise the
lab before processing begins
5.10 Human Health Fish Tissue (HTIS) (Great Lakes Nearshore and Lake Michigan
Enhancement Sites Only)
5.10.1 Introduction
Fish are time-integrating indicators of persistent pollutants, and contaminant bioaccumulation in fish
tissue has important human and ecological health implications. The NCCA Great Lakes human health fish
tissue collection will provide information on the prevalence of selected chemicals (mercury,
polychlorinated biphenyls (PCBs), and per- and polyfluoroalkyl substances (PFAS) and fatty acidsin fish
commonly consumed by humans from the Great Lakes.
The human health fish tissue indicator procedures are based on EPA's National Study of Chemical
Residues in Lake Fish Tissue (USEPA 2000a) and EPA's Guidance for Assessing Chemical Contaminant
Data for Use in Fish Advisories, Volume 1 (Third Edition) (USEPA 2000b).
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5.10.2 Sampling Design and Methods
Field crews collect human health fish tissue composites at all 225 of the Great Lakes nearshore
sites (i.e., sites whose prefix begins with NGL20), all 38 Great Lakes island sites (sites whose prefix
begins with ISA20), and all 12 Great Lakes National Park sites (sites whose prefix begins with
NPA20). This will result in human health fish tissue being targeted at 45 sites per lake, plus the 38
island sites and 12 park sites in Lake Michigan. Human health fish tissue samples should consist of
a composite of fish (i.e., five individuals of one target or alternate species) from each site. Field
crews should make every effort to consistently obtain five fish for the human health fish composite
sample; however, a sample of fewer than five fish is acceptable. Conversely, for the exceptions
where field crews collect five fish that are small, they should collect up to five additional fish (for an
overall composite of up to 10 fish) to provide adequate tissue for analysis.
As with the ecological fish tissue samples, crews collect human health fish tissue samples using any
reasonable method that represents the most efficient or best use of the available time on station (e.g.,
hook and line, gill net, or otter trawl) to obtain the recommended target species (Table 5.51). Five fish
will be collected per composite at each site, all of which must be large enough to provide sufficient
tissue for analysis. Fish in each composite must all be of the same species, satisfy legal requirements of
harvestable size (or be of consumable size if there are no harvest limits), and be of similar size so that
the smallest individual in the composite is no less than 75% of the total length of the largest individual. If
the recommended primary or secondary target species are unavailable, the on-site fisheries biologist
will select an alternative species (i.e., a species that is commonly consumed in the study area, with
specimens of harvestable or consumable size, and in sufficient numbers to yield a composite).
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Table 5.51 Recommended target species: whole fish tissue collection
PRIMARY HUMAN HEALTH FISH TISSUE TARGET SPECIES
FAMILY
SCIENTIFIC NAME
COMMON NAME
Centrarchidae
Ambloplites rupestris
Rock bass
Micropterus dolomieu
Smallmouth bass
Micropterus salmoides
Largemouth bass
Pomoxis annularis
White crappie
Pomoxis nigromaculatus
Black crappie
Cyprinidae
Cyprinus carpio
Common carp
Esocidae
Esox lucius
Northern pike
Esox masquinongy
Muskellunge
Esox niger
Chain pickerel
Ictaluridae
Ictalurus punctatus
Channel catfish
Gadidae
Lota lota
Burbot
Moronidae
Morone americana
White perch
Morone chrysops
White bass
Percidae
Percaflavescens
Yellow perch
Sander canadensis
Sauger
Sander vitreus
Walleye
Salmonidae
Coregonus clupeaformis
Lake whitefish
Oncorhynchus gorbuscha
Pink salmon
Oncorhynchus kisutch
Coho salmon
Oncorhynchus tshawytscha
Chinook salmon
Oncorhynchus mykiss
Rainbow trout
Salmo salar
Atlantic salmon
Salmo trutta
Brown trout
Sa/ve/inus namaycush
Lake trout
Sciaenidae
Aplodinotus grunniens
Freshwater drum
SECONDARY HUMAN HEALTH FISH TISSUE TARGET SPECIES
FAMILY
SCIENTIFIC NAME
COMMON NAME
Catostomidae
Carpiodes cyprinus
Quillback
Catostomus catostomus
Longnose sucker
Catostomus commersonii
White sucker
Hypentelium nigracans
Northern hogsucker
Ictiobus cyprinellus
Bigmouth buffalo
Ictiobus niger
Black buffalo
Centrarchidae
Lepomis cyanellus
Green Sunfish
Lepomis gibbosus
Pumpkinseed
Lepomis gulosus
Warmouth
Lepomis macrochirus
Bluegill
Lepomis megalotis
Longear Sunfish
Ictaluridae
Ameiurus melas
Black bullhead
Ameiurus natal is
Yellow bullhead
Ameiurus nebulosus
Brown bullhead
Salmonidae
Coregonus artedi
Cisco/ lake herring
Coregonus hoyi
Bloater
Prosopium cylindraceum
Round whitefish
Salvelin us fon tin alis
Brook trout
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5.10.3 Sampling and Analytical Methodologies
Detailed methods and handling for samples are found in the NCCA 2020 FOM.
5.10.4 Pertinent Laboratory QA/QC Procedures
Detailed methods and handling for samples are in the EPA OST Manuals/QAPP.
5.10.5 Pertinent Field QA/QC Procedures
5.10.5.1 Quality Assurance Objectives
The relevant quality objectives for Great Lakes human health fish tissue sample collection activities are
primarily related to sample handling issues. Types of field sampling data needed for the fish tissue
indicator are listed in Table 5.52. Methods and procedures described in this QAPP and the FOM are
intended to reduce the magnitude of the sources of uncertainty (and their frequency of occurrence) by
applying:
ฆ standardized sample collection and handling procedures, and
ฆ use of trained scientists to perform the sample collection and handling activities.
Table 5.52 Field data types: Great Lakes human health whole fish tissue samples for fillet analysis
Variable or Measurement Measurement Endpoint or Unit
Fish specimen
Species-level taxonomic identification
Fish length
Millimeters (mm), total length
Composite classification
Sample identification number
Specimen count classification
Specimen number
5.10.5.2 Quality Control Procedures: Field Operations
Field data quality is addressed, in part, by application and consistent performance of valid procedures
documented in the standard operating procedures detailed in the FOM. That quality is enhanced by the
training and experience of project staff and documentation of sampling activities. Specific quality control
measures are listed in Table 5.53 for field measurements and observations.
Table 5.53 Field quality control: Great Lakes human health whole fish tissue samples for fillet analysis
Quality Control Activity
Description and Requirements
Corrective Action
Check integrity of sample
containers and labels
Clean, intact human health fish coolers, solvent-
rinsed foil, food-grade polyethylene tubing, and
labels
Obtain replacement
supplies
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Quality Control Activity Description and Requirements Corrective Action
Field Processing
The crew will identify specimens to species in the field
Labs verify. If not same
species, different species
eliminated from sample
Sample Collection
The crew will retain 5 specimens (if available) of the
same species to form the composite sample.
Labs verify. If not same
species EPA makes
compositing decisions. If
fewer than 5 specimens,
EPA determines composite
suitability.
Sample Collection
The length of the smallest fish must be at least 75% of
the length of the longest fish.
If fish out of length range
requirement, EPA OST Fish
Tissue Coordinator
contacted for instructions
5.10.6 Data Management, Review and Validation
Checks made of the data in the process of review, verification, and validation are summarized in
Table 5.54. For the whole fish tissue fillet data, the OST Fish Tissue Coordinator is ultimately responsible
for ensuring the validity of the data, although performance of the specific checks may be delegated to
other EPA OST staff members. All raw data (including all standardized forms and logbooks) are retained
in an organized fashion for seven years or until written authorization for disposition has been received
from the NCCA Project Manager.
Table 5.54 Data validation quality control: Great Lakes human health whole fish tissue samples for fillet
analysis
Check Description Frequency
Acceptance Criteria Corrective Action
Composite validity
check
All composites
Each routine composite
sample must have 5 fish of
the same species
For non-routine composite samples,
EPA OST Fish Tissue Coordinator
contacted for instructions before
processing begins
75% rule
All composites
Length of smallest fish in
the composite must be at
least 75% of the length of
the longest fish.
For non-routine composite samples,
EPA OST Fish Tissue Coordinator
contacted for instructions before
processing begins
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5.11 Fish Tissue Plugs
5.11.1 Introduction
Fish are time-integrating indicators of persistent pollutants, and contaminant bioaccumulation in fish
tissue has important human and ecological health implications. The NCCA 2020 tissue plug will provide
information on the national distribution of mercury in fish species from all coastal waters.
5.11.2 Sample Design and Methods
Detailed methods and handling for samples are found in the NCCA 2020 Field Operations manual. The
laboratory method for fish tissue is performance based. Example standard operating procedures are
provided in Appendix C of the LOM.
5.11.3 Pertinent Laboratory QA/QC Procedures
5.11.3.1 Laboratory Performance Requirements
Specific laboratory performance requirements are listed in Table 5.55.
Table 5.55 Measurement data quality objectives for mercury in fish tissue plugs.
1 Variable or Measurement
MDL
Quantitation Limit 1
Mercury
0.47 ng/g
5.0 ng/g
5.11.3.2 Laboratory Quality Control Requirements
Specific laboratory quality control requirements are listed in Table 5.56.
Table 5.56 Quality Control for mercury in fish tissue plugs.
Activity
Evaluation/Acceptance Criteria
Corrective Action
Demonstrate competency
for analyzing fish samples
to meet the performance
measures
Demonstration of past experience
with fish tissue samples in
applying the laboratory SOP in
achieving the method detection
limit
EPA will not approve any
laboratory for NCCA sample
processing if the laboratory
cannot demonstrate competency.
In other words, EPA will select
another laboratory that can
demonstrate competency for its
NCCA samples.
Check condition of sample
when it arrives.
Sample issues, such as
punctures or rips in wrapping;
missing label; temperature;
adherence to holding time
requirements; sufficient volume
for test. All samples should arrive
at the laboratory frozen.
Assign an appropriate condition
code.
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Store sample
appropriately. While
stored at the laboratory,
the sample must be kept
at a maximum
temperature of -20ฐ C.
Check the temperature of the
freezer per laboratory's standard
operating procedures.
Record temperature of sample
upon arrival at the laboratory. If
at any other time, samples are
warmer than required, note
temperature and duration in
comment field.
Analyze sample within
holding time
The test must be completed
within the holding time (i.e., 1
year). If the original test fails,
then the retest also must be
conducted within the holding
time.
Perform test but note reason for
performing test outside holding
time. EPA expects that the
laboratory will exercise every
effort to perform tests before the
holding time expires.
Maintain quality control
specifications from
selected method/SOP
(that meets the
measurement data quality
objectives)
Data meet all QC specifications
in the selected method/SOP.
If data do not meet all QC
requirements, rerun sample or
qualify data. If the lab believes
the data are to be qualified
without rerunning sample, the lab
must consult with the EPA
Survey QA Lead before
proceeding.
Maintain the required
MDL/RL and denote the
dilution factor
Evaluate for each sample.
Samples should not be diluted
more than necessary. Labs must
report the dilution factor and
adjusted MDL/RL
If MDL could not be achieved,
then provide dilution factor or QC
code and explanation in the
comment field.
Use consistent units for
QC samples and field
samples
Verify that all units are provided
in wet weight units and
consistently
If it is not possible to provide the
results in the same units as most
other analyses, then assign a QC
code and describe the reason for
different units in the comments
field of the database.
Maintain completeness
Completeness objective is 95%
for all parameters.
Contact the EPA Survey QA
Lead immediately if issues affect
laboratory's ability to meet
completeness objective.
5.11.3.3 Data Reporting
Table 5.57 Data Reporting Criteria: Fish Tissue Plugs
Measurement
Units
Expressed to the
Nearest
Metals
fish tissue wet weight
0.01
5.11.4 Pertinent Field QA/QC Procedures
Field data quality is addressed, in part, by application and consistent performance of valid procedures
documented in the standard operating procedures detailed in the NCCA 2020 FOM. That quality is
enhanced by the training and experience of project staff and documentation of sampling activities.
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Crews will collect fish plugs for mercury. Field crews will verify that all sample containers are
uncontaminated and intact, and that all sample labels are legible and intact.
Before leaving the field, the crews will:
ฆ Check the label to ensure that all written information is complete and legible.
ฆ Place a strip of clear packing tape over the label, covering the label completely.
ฆ Enter a flag code and provide comments on the Sample Collection Form in the App if
there are any problems in collecting the sample or if conditions occur that may affect
sample integrity.
ฆ Store the sample frozen.
ฆ Recheck all forms and labels for completeness and legibility.
5.11.4.1 Field Performance Requirements
Specific field performance requirements are listed in Table 5.58.
Table 5.58 Method quality objectives for field measurement for the fish tissue plug indicator.
Quality Control
Description and Requirements
Corrective Action
Activity
Minimum
Acceptable Fish
Length
Fish plugs should not be collected from fish
smaller than 190 mm in length.
If unable to collect plug sample
from fish longer than 190 mm,
do not collect plug and flag
sample.
75% rule
Length of smaller of the two fish from which
plug samples were collected must be no less
than 190 mm and at least 75% of the length of
the longest fish.
Collect fish plug and flag sample
as not meeting 75% rule.
5.11.4.2 Field Quality Control Requirements
Specific quality control measures are listed in Table 5.59 for field measurements and observations.
Table 5.59 Field Quality Control: Fish Tissue Plug.
Quality Control Activity Description and Requirements Corrective Action
Check integrity of sample
containers and labels
Clean, intact containers and labels.
Obtain replacement
supplies
Set up fishing equipment
An experienced fisheries biologist sets up the
equipment. If results are poor, a different
method may be necessary.
Note on field data sheet
Field Processing
The fisheries biologist will identify specimens in
the field using a standardized list of common
and scientific names. A re-check will be
performed during processing.
Attempt to catch more
fish of the species of
interest.
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Holding time
Frozen samples must be shipped on dry ice
within 2 weeks of collection.
Qualify samples
Sample Storage (field)
Keep frozen and check integrity of sample
packaging.
Qualify sample as suspect
for all analyses
5.11.5 Data Review
Checks made of the data in the process of review, verification, and validation are summarized in Table
5.60. The Project QA Coordinator is ultimately responsible for ensuring the validity of the data, although
performance of the specific checks may be delegated to other staff members.
Table 5.60 Data validation quality control: Fish Tissue Plugs.
Activity or Procedure Requirements and Corrective Action
Range checks, summary statistics, and/or
exploratory data analysis (e.g., box and whisker
plots)
Correct reporting errors or qualify as suspect
or invalid.
Review holding times
Qualify value for additional review
Review data from QA samples (laboratory PE
samples, and interlaboratory comparison
samples)
Determine impact and possible limitations on
overall usability of data
5.12 Microplastics in Sediment
The laboratory SOP for Microplastics in Sediment will be under the Quality Assurance protocol by the
Office of Research and Development (ORD) laboratory processing the sample. Detailed sample
collection and handling procedures are found in the NCCA 2020 Field Operations Manual. Example SOPs
are provided in Appendix D: Microplastics in Sediment in the LOM.
5.13 Total Alkalinity
5.13.1 Introduction
Total alkalinity (TA) is a characteristic of seawater that, in combination with other measurements, can be
used to calculate total pH (i.e., coastal acidification) and the availability of carbonate ions used by
marine organisms to produce structural materials such as corals and shells. TA is also used to calculate
the fate of carbon that enters coastal waters in various forms and is useful as a direct indicator of
seawater buffering capacity. TA is defined differently from the alkalinity measurements typically used in
freshwater monitoring. In addition, the above seawater calculations are sensitive to tiny errors in TA
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determination, so monitoring programs aim for extreme care in the collection, handling, and analysis of
TA samples.
The laboratory SOP for Total Alkalinity will be under the Quality Assurance protocol by the Office of
Research and Developmemt (ORD) laboratory processing the sample. Detailed sample collection and
handling procedures are found in the NCCA 2020 Field Operations Manual. Example SOPs are provided
in Appendix E: Total Alkalinity in the LOM.
5.14 SN15 Isotope in Benthic Organic Matter
The laboratory SOP Delta N15 Isotope in Benthic Organic Matter will be under the Quality Assurance
protocol by the Office of Research and Development (ORD) laboratory processing the sample. Detailed
sample collection and handling procedures are found in the NCCA 2020 Field Operations Manual.
Example SOPs are provided in Appendix F: Research Indicator- A N15 Isotope in Benthic Organic Matter
in the LOM.
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6 Field and Biological Quality Evaluation & Assistance
6.1 National Coastal Condition Assessment Field Quality Evaluation and Assistance Visit
Plan
EPA, contractor and other qualified staff will conduct evaluation and assistance visits with each field
crew early in the sampling and data collection process, if possible, and corrective actions will be
conducted in real time. These visits provide both a quality check for the uniform evaluation of the data
collection methods and an opportunity to conduct procedural reviews, as required, minimizing data loss
due to improper technique or interpretation of field procedures and guidance. Through uniform training
of field crews and review cycles conducted early in the data collection process, sampling variability
associated with specific implementation or interpretation of the protocols will be significantly reduced.
The visit also provides the field crews with an opportunity to clarify procedures and offer suggestions for
future improvements based on their sampling experience preceding the visit. The field evaluations,
while performed by a number of different supporting collaborator agencies and participants, will be
based on the uniform training, plans, and checklists. The field evaluations will be based on the
evaluation plan and field evaluation checklist. EPA has scheduled this review and assistance task for
each unique field crew collecting and contributing data under this program. If unforeseen events
prevent the EPA from evaluating every crew, the NCCA Quality Assurance Coordinator (QAC) will rely on
the data review and validation process to identify unacceptable data that will not be included in the final
database. If inconsistencies cannot be resolved, the QAC may contact the Field Crew Leader for
clarification..
One or more designated EPA, contractor or other staff who are qualified (i.e. have completed training)
in the procedures of the NCCA 2020 field sampling operations will visit trained state, contractor, federal
agency and EPA field sampling crews during sampling operations on site. If membership of a field crew
changes, and at least two of the members have not been evaluated previously, the field crew must be
evaluated again during sampling operations as soon as possible to ensure that all members of the field
crew understand and can perform the procedures. If a deviation is needed from the process described
here, the staff member conducting the assistance visit (AV) must contact the Assistance Visit
Coordinator who will contact the NCCA Project Lead and the NCCA Project QA Coordinator to determine
an acceptable course of action.
The purpose of this on-site visit will be to identify and correct deficiencies during field sampling
operations. The process will involve preparation activities, field day activities and post field day activities
as described in the following sections. Additionally, conference calls with crews may be held
approximately every two weeks to discuss issues as they come up throughout the sampling season.
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6.1.1 Preparation Activities
ฆ Each Field Crew Evaluator will schedule an assistance visit with their designated crews in
consultation with the Contractor Field Logistics Coordinator, Regional NCCA
Coordinator, and respective Field Sampling Crew Leader. Ideally, each Field Crew will be
evaluated within the first two weeks of beginning sampling operations, so that
procedures can be corrected or additional training provided, if needed.
ฆ Each Evaluator is responsible for providing their own field gear sufficient to accompany
the Field Sampling Crews during a complete sampling cycle. Schedule of the Field visits
will be made by the Evaluator in consultation with the respective Field Crew Leader.
Evaluators should be prepared to spend additional time in the field if needed (see
below).
ฆ Each Field Crew Evaluator will ensure that field crews are aware of their visit plans and
all capacity and safety equipment will be provided for the Field Crew Evaluator.
ฆ Each Field Crew Evaluator will need to bring the items listed in Table 6.1.
Table 6.1 Equipment and Supplies - Field Evaluation and Assistance Visits
Assistance Visit
Checklist
Appendix D (see FOM)
1
Documentation
NCCA 2020 Field Operations Manuals
NCCA 2020 Quality Assurance Project Plan
Clipboard
Pencils (#2, for data forms)/Pen (or computer for electronic versions)
Field notebook (optional)
1
1
1
1
1
Gear
Field gear (e.g., protective clothing, sunscreen, insect repellent, hat, water,
food, backpack, cell phone)
As
needed
6.1.2 Field Day Activities
ฆ The Field Crew Evaluator will review the Field Evaluation & Assistance Visit Checklist
with each crew during the field sampling day and establish and plan and schedule for
their evaluation activities for the day.
ฆ The Field Crew Evaluator will view the performance of a field crew through one
complete set of sampling activities as detailed on the checklist.
ฆ Scheduling might necessitate starting the evaluation midway on the list of tasks at a site,
instead of at the beginning. In that case, the Field Crew Evaluator will follow the crew to
the next site to complete the evaluation of the first activities on the list.
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ฆ If the field crew misses or incorrectly performs a procedure, the Field Crew Evaluator
will note this on the checklist and immediately point this out so the mistake can be
corrected on the spot. The role of the Field Crew Evaluator is to provide additional
training and guidance so that the procedures are being performed consistent with the
FOM, all data are recorded correctly, and paperwork, if applicable, is properly
completed at the site.
ฆ When the sampling operation has been completed, the Field Crew Evaluator will review
the results of the evaluation with the field crew before leaving the site (if practicable),
noting positive practices and problems (i.e., weaknesses [might affect data quality];
deficiencies [would adversely affect data quality]). The Field Crew Evaluator will ensure
that the field crew understands the findings and will be able to perform the procedures
properly in the future.
ฆ The Field Crew Evaluator will review the list and record responses or concerns from the
field crew, if any; on the checklist (this may happen throughout the field day).
ฆ The Field Crew Leader will sign the checklist after this review.
ฆ The Field Crew Evaluator will review the checklist that evening and provide a summary
of findings, including lessons learned and concerns.
ฆ If the Field Crew Evaluator finds major deficiencies in the field crew operations (e.g., less
than two members, equipment, or performance problems) the Field Crew Evaluator
must contact the EPA NCCA Project QA Coordinator. The EPA NCCA Project QA
Coordinator will work with the EPA NCCA Program Manager to determine the
appropriate course of action. Data records from sampling sites previously visited by this
Field Crew will be checked to determine whether any sampling sites must be redone.
ฆ The Field Crew Evaluator will retain a copy of the checklist and submit to the EPA
Logistics Coordinator either via Fed-Ex or electronically.
ฆ The EPA Logistics Coordinator and the NCCA Project QA Coordinator or authorized
designee (member of the NCCA 2020 quality team) will review the returned Field
Evaluation and Assistance Visit Checklist, note any issues, and check off the completion
of the evaluation for each field crew.
6.1.3 Post Field Day Activities
6.1.4 Summary
Table 6.2 summarizes the plan, checklist, and corrective action procedures.
Table 6.2 Summary of Field Evaluation and Assistance Visit Information
Field
Evaluation
Plan
The Field Crew Evaluator:
Arranges the field evaluation visit in consultation with the Project QA Coordinator, Regional
NCCA Coordinator, and respective Field Sampling Crew Leader, ideally within the first two
weeks of sampling
Observes the performance of a crew through one complete set of sampling activities
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Field
Evaluation
Checklist
Takes note of errors the field crew makes on the checklist and immediately point these out to
correct the mistake
Reviews the results of the evaluation with the field crew before leaving the site, noting positive
practices, lessons learned, and concern
The Field Crew Evaluator:
Observes all pre-sampling activities and verifies that equipment is properly calibrated and in
good working order, and protocols are followed
Checks the sample containers to verify that they are the correct type and size, and checks the
labels to be sure they are correctly and completely filled out
Confirms that the field crew has followed NCCA protocols for locating the X -site
Observes the index site sampling, confirming that all protocols are followed
Observes the littoral sampling and habitat characterization, confirming that all protocols are
followed
Records responses or concerns, if any, on the Field Evaluation and Assistance Checklist
Corrective
Action
Procedures
If the Field Crew Evaluator's findings indicate that the Field Crew is not performing the
procedures correctly, safely, or thoroughly, the Evaluator must continue working with this Field
Crew until certain of the crew's ability to conduct the sampling properly so that data quality is
not adversely affected
If the Field Crew Evaluator finds major deficiencies in the Field Crew operations the Evaluator
must contact the EPA NCCA Project QA Coordinator
6.2 National coastal condition assessment laboratory quality evaluation and assistance visit
plan
As part of the NCCA 2020, field samples will be collected at each assessment site. These samples will be
sent to laboratories cooperating in the assessment. To ensure quality, each Project Cooperator
laboratory analyzing samples from the NCCA 2020 will receive an evaluation from an NCCA Lab
Evaluator. All Project Cooperator laboratories will follow these guidelines.
No national program of accreditation for laboratory processing for many of our indicators currently
exists. For this reason, a rigorous program of laboratory evaluation has been developed to support the
NCCA 2020.
Given the large number of laboratories participating in the NCCA 2020, it is not feasible to perform an
assistance visit11 (AV) on each of these laboratories. An AV would include an on-site visit to the
laboratory lasting at least a day. As a result, the EPA Headquarters Project Management Team will
conduct remote review of laboratory certifications and accreditations of all laboratories. Additionally,
EPA will include an inter-laboratory comparison between some laboratories (mainly for biological
indicators). If issues arise from the remote review or inter-laboratory comparison that cannot be
resolved remotely, the EPA Quality Team and/or contractors will perform an on-site visit to the
11 The evaluation of the labs is being considered an Assistance Visit rather than an audit because the evaluation is
designed to provide guidance to the labs rather than as "inspection" as in a traditional audit.
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laboratory. This process is in keeping with EPA's Policy to Assure Competency of Laboratories, Field
Sampling, and Other Organizations Generating Environmental Measurement Data under Agency-Funded
Acquisitions.
6.2.1 Remote Evaluation/Technical Assessment
A remote evaluation procedure has been developed for performing assessment of all laboratories
participating in the NCCA 2020.
The Laboratory Review Coordinator, the NCCA Project QA Coordinator and other members of the NCCA
QA Team will conduct laboratory evaluation prior to data analysis to ensure that the laboratories are
qualified and that techniques are implemented consistently across the multiple laboratories generating
data for the program. The EPA National Aquatic Resource Surveys team has developed laboratory
evaluation plans to ensure uniform interpretation and guidance in the procedural reviews.
The NCCA Quality Team is using a procedure that requests the laboratory to provide documentation of
its policies and procedures. For the NCCA 2020 project, the Quality Team is requesting that each
participating laboratory provide the following documentation:
ฆ The laboratory's Quality Manual, Quality Management Plan or similar document.
ฆ Standard Operating Procedures (SOPs) for each analysis to be performed.
ฆ Long term Method Detection Limits (MDLs) for each instrument used and
Demonstration of Capability for each analysis to be performed.
ฆ A list of the laboratory's accreditations and certifications, if any.
ฆ Results from Proficiency Tests for each analyte to be analyzed under the NCCA 2020
project.
If a laboratory has clearly documented procedures for sample receiving, storage, preservation,
preparation, analysis, and data reporting; has successfully analyzed Proficiency Test samples (if required
by EPA, EPA will provide the PT samples); has a Quality Manual that thoroughly addresses laboratory
quality including standard and sample preparation, record keeping and QA non-conformance;
participates in a nationally recognized or state certification program; and has demonstrated ability to
perform the testing for which program/project the audit is intended, then the length of an on-site visit
will be minimum, if not waived entirely. The QA Team will make a final decision on the need for an
actual on-site visit after the review and evaluation of the documentation requested.
If a laboratory meets or exceeds all of the major requirements and is deficient in an area that can be
corrected remotely by the lab, suggestions will be offered and the laboratory will be given an
opportunity to correct the issue. The QA Team will then verify the correction of the deficiency remotely.
The on-site visit by EPA and/or a contractor should only be necessary if the laboratory fails to meet the
major requirements and is in need of help or fails to produce the requested documentation.
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In addition, all labs must sign a Lab Signature Form (see NCCA 2020 LOM) indicating that they will abide
by the following:
ฆ Utilize procedures identified in the NCCA 2020 Lab Operations Manual (or equivalent). If
using equivalent procedures, please provide procedures manual to demonstrate ability
to meet the required MQOs.
ฆ Read and abide by the NCCA 2020 Quality Assurance Project Plan (QAPP) and related
Standard Operating Procedures (SOPs).
ฆ Have an organized IT system in place for recording sample tracking and analysis data.
ฆ Provide data using the template provided in the Lab Operations Manual.
ฆ Provide data results in a timely manner. This will vary with the type of analysis and the
number of samples to be processed. Sample data must be received no later than May 1,
2016 or as otherwise negotiated with EPA.
ฆ Participate in a lab technical assessment or audit if requested by EPA NCCA Quality
Team staff (this may be a conference call or on-site audit).
If a lab is participating in biology analyses, they must, in addition, abide by the following:
ฆ Use taxonomic standards outlined in the NCCA 2020 Lab Manual.
ฆ Participate in taxonomic reconciliation exercises during the field and data analysis
season, which include conference calls and other lab reviews (see more below on Inter-
laboratory comparison).
6.2.2 Water Chemistry Laboratories
The water chemistry laboratory approval process which is outlined on in the previous paragraphs of this
section is deemed appropriate because many laboratories participate in one or more national laboratory
accreditation programs such as the National Environmental Laboratory Accreditation Program (NELAP),
International Organization for Standardization (ISO-17025) as well as various state certification
programs which include strict requirements around documentation and procedures as well as site visits
by the accrediting authority. It is built off of the process s used by the NLA 2012 and NRSA 2013/14. The
laboratories participating in NCCA 2020 meet these qualifications and as such have demonstrated their
ability to function independently. This process is one that has been utilized in Region 3 for many years
and is designed around the national accrediting programs listed above.
6.2.3 Inter-laboratory Comparison
The NCCA QA plan includes an inter-laboratory investigation for the laboratories performing analysis on
benthic invertebrates for the NCCA 2020. This process is defined as an inter-laboratory comparison since
the same protocols and method will be used by both laboratories as described in this manual. The QA
plan also includes an independent taxonomist (EPA Contractor) to re-identify 10% of the samples from
each laboratory. No site visit is envisioned for these laboratories unless the data submitted and
reviewed by EPA does not meet the requirements of the inter-laboratory comparison described.
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6.2.4 Assistance Visits
Assistance Visits will be used to:
ฆ Confirm the NCCA 2020 Laboratory Operations Manual (LOM) methods are being
properly implemented by cooperator laboratories.
ฆ Assist with questions from laboratory personnel.
ฆ Suggest corrections if any errors are made in implementing the lab methods.
Evaluation of the laboratories will take the form of administration of checklists which have been
developed from the LOM to ensure that laboratories are following the methods and protocols outlined
therein. The checklist will be administered on-site by a qualified EPA scientist or contractor.
Below are examples of the Document Request form used for both the Biological laboratories and the
Chemical laboratories.
6.2.5 NCCA 2020 Document Request Form Chemistry Laboratories
EPA and its state and tribal partners will conduct a survey of the nation's coastal waters. This National
Coastal Condition Assessment (NCCA), is designed to provide statistically valid regional and national
estimates of the condition of coastal waters. Consistent sampling and analytical procedures ensure that
the results can be compared across the country. As part of the NCCA 2020, the Quality Assurance Team
will conduct a technical assessment to verify quality control practices in your laboratory and its ability to
perform chemistry analyses under this project. Our review will assess your laboratory's ability to receive,
store, prepare, analyze, and report sample data generated under EPA's NCCA 2020.
The first step of this assessment process will involve the review of your laboratory's certification and/or
documentation. Subsequent actions may include (if needed): reconciliation exercises and/or a site visit.
All laboratories will need to complete the following forms:
If your lab has been previously approved within the last 5 years for the specific parameters:
ฆ A signature on the attached Laboratory Signature Form indicates that your laboratory
will follow the quality assurance protocols required for chemistry laboratories
conducting analyses for the NCCA 2020. A signature on the QAPP and the LOM
Signature Form indicates that you will follow both the QAPP and the LOM.
If you have not been approved within the last 5 years for the specific parameters in order for us to
determine your ability to participate as a laboratory in the NCCA, we are requesting that you submit
the following documents (if available) for review:
ฆ Documentation of a successful quality assurance audit from a prior National Aquatic
Resource Survey (NARS) that occurred within the last 5 years (if you need assistance
with this please contact the individual listed below).
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ฆ Documentation showing participation in a previous NARS for Water Chemistry for the
same parameters/methods.
Additionally, we request that all laboratories provide the following information in support of your
capabilities, (these materials are required if neither of the two items above are provided):
ฆ A copy of your Laboratory's accreditations and certifications if applicable (i.e. NELAC,
ISO, state certifications, North American Benthological Society (NABS), etc.).
ฆ An updated copy of your Laboratory's QAPP.
ฆ Standard Operating Procedures (SOPs) for your laboratory for each analysis to be
performed (if not covered in NCCA 2020 LOM).
ฆ Documentation attesting to experience running all analytes for the NCCA 2020,
including chlorophyll a.
This documentation may be submitted electronically via e-mail to forde.kendraffiepa.gov. Questions
concerning this request can be submitted forde.kendra@epa.gov (202-566-0417) or
sullivan.hugh@epa.gov.
6.2.6 NCCA 2020 Document Request Form Biology Labs
EPA and its state and tribal partners will conduct a survey of the nation's coastal waters . This National
Coastal Condition Assessment (NCCA), is designed to provide statistically valid regional and national
estimates of the condition of coastal waters. Consistent sampling and analytical procedures ensure that
the results can be compared across the country. As part of the NCCA 2020, the Quality Assurance Team
will conduct a technical assessment to verify quality control practices in your laboratory and its ability to
perform biology analyses under this project. Our review will assess your laboratory's ability to receive,
store, prepare, analyze, and report sample data generated under EPA's NCCA 2020.
The first step of this assessment process will involve the review of your laboratory's certification and/or
documentation. Subsequent actions may include (if needed): reconciliation exercises and/or a site visit.
All laboratories will need to complete the following forms:
ฆ If your laboratory has been previously approved within the last 5 years for the specific
parameters: A signature on the attached Laboratory Signature Form indicates that your
laboratory will follow the quality assurance protocols required for biology laboratories
conducting analyses for the NCCA 2020. A signature on the QAPP and the LOM
Signature Form indicates you will follow both the QAPP and the LOM.
If you have not been approved within the last 5 years for the specific parameters, in order for us to
determine your ability to participate as a laboratory in the NCCA, we are requesting that you submit
the following documents (if available) for review:
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ฆ Documentation of a successful quality assurance audit from a prior National Aquatic
Resource Survey (NARS) that occurred within the last 5 years (if you need assistance
with this please contact the individual listed below).
ฆ Documentation showing participation in previous NARS for this particular indicator.
Additionally, we request that all laboratories provide the following information in support of your
capabilities, (these materials are required if neither of the two items above are provided):
ฆ A copy of your Laboratory's accreditations and certifications if applicable (i.e. NELAC,
ISO, state certifications, NABS, etc.).
ฆ Documentation of NABS (or other) certification for the taxonomists performing analyses
(if applicable).
ฆ An updated copy of your Laboratory's QAPP.
ฆ Standard Operating Procedures (SOPs) for your lab for each analysis to be performed (if
not covered in NCCA 2020 LOM).
This documentation may be submitted electronically via e-mail to forde.kendra@epa.gov. Questions
concerning this request can be submitted forde.kendra@epa.gov (202-566-0417) or
sullivan.hugh@epa.gov.
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7 Data Analysis Plan
The goal of the NCCA is to address three key questions about the quality of the Nation's coastal
waters:
What percent of the Nation's coastal waters are in good, fair, and poor condition for key
indicators of chemical water quality, ecological condition, and suitability for recreation?
How are conditions changing over time?
What is the relative importance of key stressors (e.g., nutrients and pathogens) in
impacting the biota?
The Data Analysis Plan describes the approach used to process the data generated during the field
survey to answer these three questions. Results from the analysis will be included in the final report and
used in future analysis.
7.1 Data Interpretation Background
The intent of data analyses is to describe the occurrence and distribution of selected indicators
throughout the estuaries and coastal waters of the United States within the context of regionally
relevant expectations. The analyses will culminate by categorizing and reporting the condition of coastal
waters as being good, fair, or poor condition. Statistical analysis techniques appropriate for using data
collected using probabilistic survey designs, will serve as the primary method for interpreting survey
results. However, other data analyses will be used for further assessment investigations as described
below.
Because of the large-scale and multijurisdictional nature of this effort, the key issues for data
interpretation are: the scale of assessment, selecting the effective indicators across the range of systems
included in the survey, and determining thresholds for judging condition. An NCCA Data Analysis work
group will be created to address these points and to help strengthen NCCA assessments.
7.1.1 Scale of Assessment
EPA selected the sampling locations for the NCCA survey using a probability based design, and
developed rules for selection to meet certain distribution criteria, while ensuring that the design yielded
a set of coastal areas that would provide for statistically valid conclusions about the condition of the
population of coastal areas across the nation.
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7.1.2 Selecting Indicators
Indicators for the 2020 survey will basically remain the same as those used in the previous National
Coastal Condition Assessment12, with a few modifications. The indicators for NCCA 2020 include
nutrients in water, light attenuation, sediment chemistry, sediment toxicity, benthic communities,
whole body fish tissue, fish tissue plugs for mercury analysis, microcystins, and enterococci.
Supplemental and research indicators also include algal toxins, fish tissue filets (Great Lakes only),
phytoplankton (Great Lakes only), and under water vide (Great Lakes only). Of these, fish tissue plugs,
microcystins and algal toxins are new indicators.
7.2 Datasets to be used for the Report
The Dataset used for the 2020 assessment consists of data collected during NCCA 2020, the NCCA
2010, and data from historic National Coastal Condition Reports (NCCRs) for tracking changes in water
quality data. Other data may be added as appropriate.
7.3 Indicators for the Coastal Assessment
7.3.1 Water Chemistry and Chlorophyll
A wide array of water chemistry parameters will be measured. Water chemistry analysis is critical for
interpreting the biological indicators. Chlorophyll-a, Secchi depth, light attenuation and nutrient
measurements will be used to create a water quality index and identify stressors.
7.3.2 Benthic Invertebrates
To distinguish degraded benthic habitats from undegraded benthic habitats, EMAP and NCA have
developed regional (Southeast, Northeast, and Gulf coasts) benthic indices of environmental condition
(Engle et al., 1994; Weisberg et al., 1997; Engle and Summers, 1999; Van Dolah et al., 1999; Hale and
Heltshe, 2008). A new Multi-metric approach (M-AMBI) is also being developed and peer reviewed for
potential use in the NCCA 2020 report.
7.3.3 Sediment Chemistry/Characteristics
The NCCA is collecting sediment samples, measuring the concentrations of chemical constituents and
percent TOC in the sediments, and evaluating sediment toxicity as described in the QAPP, field
operations manual and laboratory operations manual. The results of these evaluations will be used to
identify the percent of coastal waters with sediment contamination. The sediment quality index is
based on measurements of three component indicators of sediment condition: sediment toxicity,
sediment contaminants, and sediment TOC. This information will also be used in identifying stressors to
ecological/biological condition.
12 For more information visit the NCCA website at: https://www.epa.gov/national-aquatic-resource-surveys/ncca
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7.3.4 Enterococci Data Analysis
The presence of certain levels of enterococci is associated with pathogenic bacterial contamination of
the resource. A single enterococci water sample will be collected at each site, then filtered, processed,
and analyzed using qPCR. Bacterial occurrence and distribution will be reported. Data interpretation will
be enhanced by comparison to USEPA thresholds13. In 2012, EPA released new recreational water
quality criteria recommendations for protecting human health in all coastal and non-coastal waters
designated for primary contact recreation use. NCCA will use the enterococci statistical threshold values
for marine and freshwaters to assess the percent of coastal waters above and below human health
levels of concern.
7.3.5 Fish Chemistry
For the NCCA, both juvenile and adult target fish species will be collected from all monitoring stations
where fish were available, and whole-body contaminant burdens will be determined. The target species
typically included demersal (bottom dwelling) and pelagic (water column-dwelling) species that are
representative of each of the geographic regions. The EPA recommended values for fish advisories will
serve as the threshold against which to evaluate risk.
7.3.6 Algal toxins
The presence of algal toxins can be an indicator of human and/or ecological risk. Microcystin and other
algal toxins will be collected at each site. Occurrence and distribution will be reported. Where
thresholds are available (such as World Health Organization or other applicable thresholds)
concentrations will be reported against those values.
7.4 NCCR Index Development Approach
EPA intends to calculate the indices used in previous NCCR reports. Information on this approach, the
indices and related thresholds can be found in the National Coastal Condition Report III (EPA 2008.)
7.5 Calculation of Population Estimates
Once the individual indicator values are calculated for each sampling location, population estimates will
be generated using the procedures outlined by EMAP and found on the Aquatic Resource Monitoring
website (https://archive.epa.gov/nheerl/arm/web/html/index.html). The population estimates will
include estimates of uncertainty for each indicator. The output of these analyses are the specific results
that will appear in the coastal assessment report.
7.6 Other Change Analyses
Biological and stressor/chemical data from the NCCA and previous reports will be analyzed to see what
13 For more information visit EPA's website at https://www.epa.gov/wqc/2012-recreational-water-quality-criteria-
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changes have occurred overtime.
7.7 Index Precision and Interpretation
NCCA indicators will be repeated at 10% of the sites during the summer index sampling period. These
repeat samples allow an assessment of the within-season repeatability of these indicators and metrics.
The NCCA will calculate the precision of select site condition indicators using a basic measure of
repeatability - the RMSrep or the Root Mean Square of repeat visits.
The RMSrep is a measure of the absolute (unsealed) precision of the whole measurement and analytical
process as well as short-term temporal variability within the summer sampling period. The RMSrep for a
metric is an estimate of its average standard deviation if it were measured repeatedly at all sites, and
then standard deviations for each site were averaged. For Log transformed data, the antilog of the
RMSrep represents a proportional standard deviation. For example, if theRMSrep of the unsealed total
phosphorus data is 0.179, the antilog is 1.51. Therefore, the RMSrep of 0.179 for Logl0(PTL+l) means
that the error bound on a measurement at a site is +/-1.51. Because the data are LoglO transformed,
the measured value times 1.51 gives the upper ("+") error bound and divided by 1.51 gives the lower ("-
") error bound. So, the +/-1 StdDev error bounds on a PTL measurement of 10 ug/L during the index
period is (10 4-1.51) to (10 xl.51) or 6.6 to 15.1.
Another way of scaling the precision of metrics is to examine their components of variance. The NCCA
calculates signal to noise ratios for each indicator to determine whether the amount of variance is
acceptable for it to be used in the data analysis described above. The ratio of variance among sites to
measurement (or temporal) variation within individual sites has been termed a "Signal-to-noise" ratio.
The S/N ratio assesses the ability of the metric to discern differences among sites in this survey context.
If the among-site variance in condition in the region, large estuary, Great Lake or nation is high, then the
S/N is high and the metric is ble to adequately discern differences in site condition. The NCCA uses a
variance-partitioning explained in Kaufmann et al. (1999) and Faustini and Kaufmann (2007), in which
the authors referred to RMSrep as RMSE and evaluated S/N in stream physical habitat variables. In those
publications, the authors generally interpreted precision to be high relative to regional variation if S/N
>10, low if S/N <2.0, and moderate if in-between. When S/N is over about 10, the effect of
measurement error on most interpretations is nearly insignificant within the national context; when S/N
is between 6 and 10, measurement effects are minor. When S/N ratios are between 2 and 5, the effects
of imprecision should be acknowledged, examined and evaluated. Ratios between 2 and 4 are usually
adequate to make good-fair-poor classifications in the NCCA, but there is some distortion of cumulative
distribution functions () and a significant limitation to ability of a multiple linear regression to explain the
amount of among-site variance using single visit data.
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