Development and Evaluation of 

Numerical Sediment Quality 

Assessment Guidelines for Florida 

Inland Waters 

Technical Report 

Prepared for: 

Florida Department of Environmental Protection 

Twin Towers Office Building 

2600 Blair Stone Road 

Tallahassee, Florida 32399-2400 

Prepared – January 2003 – by: 

MacDonald Environmental Sciences Ltd. United States Geological Survey 

#24 - 4800 Island Highway North 4200 New Haven Road 

Nanaimo, British Columbia V9T 1W6 Columbia, Missouri 65201 
Development and Evaluation of 

Numerical Sediment Quality 

Assessment Guidelines for Florida 

Inland Waters 

Technical Report 

Prepared for: 

Florida Department of Environmental Protection 

Twin Towers Office Building 

2600 Blair Stone Road 

Tallahassee, Florida 32399-2400 

Prepared - January 2003 - by: 

D.D. MacDonald1, C.G. Ingersoll2, D.E. Smorong1, R.A. Lindskoog1, G. Sloane3 

and T. Biernacki3 

1

 MacDonald Environmental Sciences Ltd.

#24 - 4800 Island Highway North

Nanaimo, British Columbia V9T 1W6

2

 United States Geological Survey

4200 New Haven Road

Columbia, Missouri 65201

3

 Florida Department of Environmental Protection

Twin Towers Office Building

2600 Blair Stone Road

Tallahassee, Florida 32399-2400
TABLE OF CONTENTS 

Table of Contents 

Table of Contents ....................................................... i

List of Appendices ..................................................... iv

List of Tables .......................................................... v

List of Figures ........................................................ vii

List of Acronyms ..................................................... viii

Executive Summary .................................................... x

Acknowledgments .................................................... xiv

Chapter 1 Introduction ................................................ 1

1.0 Background ............................................. 1

1.1 Formulation of an Ecosystem-Based Framework for Assessing

Contaminated Sediments ............................... .... 2

1.2 Development of a Metals Interpretive Tool ..................... 4

1.3 Establishment of Sediment Quality Assessment Guidelines ........ 5

Chapter 2 Interests and Needs Related to the Assessment of Contaminated

Sediments in Florida Inland Waters ........................ .... 7

2.0 Introduction ............................................. 7

2.1 Role of Sediments in Freshwater Ecosystems ................... 8

2.2 Sediment Quality Issues and Concerns ....................... 10

2.3 Reasons for Collecting Information on Sediment Quality

Conditions .......................................... ... 11

2.4 Chemicals of Potential Concern ............................. 13

Chapter 3 Approaches for Establishing Numerical Sediment Quality

Assessment Guidelines for Freshwater Ecosystems ............. .. 15

3.0 Introduction ............................................ 15

3.1 Review and Evaluation of Existing Approaches to the Derivation

of Numerical Sediment Quality Guidelines ................. ... 16

3.1.1 Screening Level Concentration Approach ............... 17

3.1.2 Effects Range Approach ............................ 18

3.1.3 Effects Level Approach ............................. 20

3.1.4 Apparent Effects Threshold Approach ................. 20

3.1.5 Equilibrium Partitioning Approach .................... 21

3.1.6 Logistic Regression Modeling Approach ................ 23

3.1.7 Consensus Approach ............................... 24

3.1.8 Tissue Residue Approach ........................... 26

i 
TABLE OF CONTENTS 

3.2 Recommended Strategy for Establishing Sediment Quality

Assessment Guidelines for Florida Inland Waters ............. .. 27

3.2.1 Recommended Approach for Establishing Effects-Based

Sediment Quality Assessment Guidelines ........... ... 27

3.2.2 Recommended Approach for Establishing

Bioaccumulation-Based Sediment Quality Assessment

Guidelines ................................... .... 30

Chapter 4 Evaluation of the Predictive Ability of Effects-Based Sediment

Quality Assessment Guidelines ........................... .... 32

4.0 Introduction ............................................ 32

4.1 Acquisition of Candidate Data Sets .......................... 33

4.2 Review and Evaluation of Candidate Data Sets ................. 34

4.3 Development of a Regional Sediment Toxicity Database ......... 35

4.4 Evaluation of the Effects-Based Sediment Quality Assessment

Guidelines .......................................... ... 37

4.5 Predictive Ability of the Effects-Based Sediment Quality

Assessment Guidelines ............................... .... 39

Chapter 5 Recommended Sediment Quality Assessment Guidelines for

Florida Inland Waters .................................... ... 43

5.0 Introduction ............................................ 43

5.1 Narrative Sediment Quality Assessment Guidelines ............. 43

5.1.1 Toxic Substances .................................. 44

5.1.2 Bioaccumulative Substances ......................... 45

5.2 Numerical Sediment Quality Assessment Guidelines ............ 46

5.2.1 Effects-Based Sediment Quality Assessment Guidelines ... 46

5.2.2 Bioaccumulation-Based Sediment Quality Assessment

Guidelines ................................... .... 48

Chapter 6 Applications of the Numerical Sediment Quality Assessment

Guidelines .............................................. ... 49

6.0 Introduction ............................................ 49

6.1 Monitoring and Assessment Initiatives ....................... 50

6.1.1 Designing Environmental Monitoring Programs .......... 50

6.1.2 Interpreting Environmental Monitoring Data ............ 51

6.1.3 Identifying Chemicals of Potential Concern ............. 52

6.1.4 Identifying Areas of Concern ......................... 53

6.1.5 Identifying Sources of Chemicals of Potential Concern .... 54

6.1.6 Supporting Watershed Assessments ................... 54

6.1.7 Evaluating Stormwater Ponds ........................ 55

6.2 Assessment and Management of Contaminated Sites ............ 55

6.2.1 Undertaking Enforcement Actions and Clean-ups ......... 56

6.2.2 Reclaiming Phosphate Mines ......................... 57

ii 
TABLE OF CONTENTS 

6.3 Restoration of Wetland Habitats ............................ 57

6.3.1 Restoring Agricultural Land ......................... 57

6.3.2 Assessing State Liability ............................ 58

6.3.3 Restoring the Everglades ............................ 58

6.4 Assessment of Risks to Ecological Receptors .................. 58

6.5 Environmental Regulation ................................. 60

6.5.1 Evaluating Dredged Materials ........................ 60

6.5.2 Evaluating Solid Wastes ............................ 61

6.5.3 Evaluating Total Maximum Daily Loadings ............. 61

6.5.4 Evaluating National Pollutant Discharge Elimination

System Permits ................................ .... 62

6.5.5 Assessing the Effects of Aquatic Weed Control

Programs ..................................... ... 62

Chapter 7 Summary and Recommendations ............................. 63

7.0 Introduction ............................................ 63

7.1 Summary .............................................. 64

7.2 Recommendations ....................................... 66

7.2.1 Refinement of the Tools for Assessing Sediment Quality

Conditions .................................... ... 67

7.2.2 Evaluation of the Ecosystem-Based Framework for

Assessing and Managing Sediment Quality Conditions . ... 68

7.2.3 Improvement of Monitoring and Assessment Initiatives .... 68

7.2.4 Development of Strategies for Managing Contaminated

Sediments ..................................... ... 69

7.2.5 Development of Outreach and Partnership Building

Programs .................................... .... 69

Chapter 8 References ................................................ 71

iii 
TABLE OF CONTENTS 

List of Appendices 

Appendix 1 Freshwater Sediment Quality Assessment Initiative: Project

Overview ............................................... . A-1

A1.0 Introduction and Background .......................... A-1

A1.1 Freshwater Sediment Quality Assessment Initiative ......... A-2

A1.2 Implementation Plan ................................. A-3

A1.3 Development of a Metals Interpretive Tool ............... A-4

A1.4 Derivation and Evaluation of Sediment Quality Assessment

Guidelines ........................................ . A-5

A1.5 Formulation of an Integrated Framework for Assessing

Freshwater Sediments ............................... . A-5

Appendix 2 Criteria for Evaluating Candidate Data Sets .................. A-7

A2.0 Introduction ........................................ A-7

A2.1 Criteria for Evaluating Whole-sediment, Pore-water, and

Tissue Chemistry ................................... . A-8

A2.2 Criteria for Evaluating Biological Effects Data ............. A-9

Appendix 3 Appendices References ................................... A-11

iv 
TABLE OF CONTENTS 

List of Tables 

Table 3.1 Summary of the strengths and limitations of existing approaches for

deriving numerical sediment quality assessment guidelines (adapted

from Crane et al. 2000) ................................... ... 82

Table 3.2 Evaluation of candidate approaches for deriving sediment quality

assessment guidelines for Florida inland waters (adapted from

MacDonald 1994) ....................................... ... 85

Table 4.1 Listing of matching sediment chemistry and toxicity data sets

compiled in the regional database .......................... .... 87

Table 4.2 Summary of the whole-sediment toxicity data used to evaluate the

predictive ability of the preliminary sediment quality assessment

guidelines for Florida inland waters .......................... ... 92

Table 4.3 Descriptions of the published freshwater SQGs that were used to 

derive numerical sediment effect concentration (from MacDonald et 

al. 2000a) .............................................. ... 93

Table 4.4 Sediment quality guidelines that reflect threshold effect

concentrations (TECs; i.e., below which harmful effects are unlikely

to be observed; from MacDonald et al. 2000a) ................. ... 95

Table 4.5 Sediment quality guidelines that reflect probable effect concentrations

(PECs; i.e., above which harmful effects are likely to be observed;

from MacDonald et al. 2000a) .............................. ... 97

Table 4.6 Reliability of the consensus-based threshold effect concentrations

(TECs) in freshwater sediments (from MacDonald et al. 2000a) ... ... 99

Table 4.7 Reliability of the consensus-based probable effect concentrations

(PECs) in freshwater sediments (from MacDonald et al. 2000a) ... . . 100

Table 4.8 Incidence of toxicity within ranges of contaminant concentrations

defined by the sediment quality guidelines (SQGs; from MacDonald

et al. 2000a) ............................................ . . 101

Table 4.9 Incidence of sediment toxicity within ranges of mean PEC-Qs for

sediments collected throughout the United States (from USEPA

2000a) ............................................... ... 102

Table 4.10 Incidence of sediment toxicity within ranges of mean PEC-Qs for

sediments from Florida and elsewhere in the southeastern portion of

the United States ........................................ . . 103

v 
TABLE OF CONTENTS 

Table 4.11 Summary of sediment quality targets generated using matching

sediment chemistry and biological effects data Florida and elsewhere

in the southeastern portion of the United States ............... ... 104

Table 5.1 Sediment quality assessment guidelines for the protection of

sediment-dwelling organisms in Florida ...................... . . 105

Table 5.2 Sediment quality assessment guidelines for the protection of aquaticdependent wildlife and human health in Florida ............... ... 108

vi 
TABLE OF CONTENTS 

List of Figures 

Figure 4.1 Relationship between the geometric mean of mean PEC-Qs and the 

incidence of acute toxicity to amphipods (endpoints: survival only) 

in the national (10- to 14-day toxicity tests) and regional (10-day 

toxicity tests) databases .................................... . 112 

Figure 4.2 Relationship between the geometric mean of mean PEC-Qs and the 

incidence of acute toxicity to amphipods (endpoints: survival or 

growth) in the national (10- to 14-day toxicity tests) and regional 

(10-day toxicity tests) databases ........................... ... 113 

Figure 4.3 Relationship between the geometric mean of mean PEC-Qs and the 

incidence of chronic toxicity to amphipods(endpoints:survival only) 

in the national (28- to 42-day toxicity tests) and regional (28- to 

42-day toxicity tests; n = 174, grouped by 15) databases ......... .. 114 

Figure 4.4 Relationship between the geometric mean of mean PEC-Qs and the 

incidence of chronic toxicity to amphipods (endpoints: survival or 

growth) in the national (28- to 42 day toxicity tests) and regional (28-

to 42-day toxicity tests) databases ........................... . . 115 

Figure 4.5 Relationship between the geometric mean of mean PEC-Qs and the 

incidence of acute toxicity to midges (endpoints: survival or growth), 

in the national (10- to 14-d Chironomus spp. toxicity tests) and 

regional (10-day toxicity tests) databases ..................... . . 116 

vii 
TABLE OF CONTENTS 

List of Acronyms 

:g/kg OC

%OC

AETA

AVS

BEDS

BEHP

BSAFs

CA

COPCs

CWA

-d 

DQOs

DW

ELA

EqPA

ERA

ERL

ERM

ESGs

FCVs

FDEP

FGS

foc 

HCB 

HCBC 

HCH 

Koc 

Kow 

Kp

LELs

LRMA

“Mean-MPP (or)”

MESL

METs

NECs

NPDES

OC pesticides 

PAETs

PAHs

PCBs

PCDDs

PCDFs

micrograms per kilogram organic carbon

percent organic carbon

Apparent Effects Threshold Approach

acid volatile sulfide

Biological Effects Database for Sediments

bis(2-ethyl hexyl)phthalate

sediment-to-biota bioaccumulation factors

Consensus Approach

chemicals of potential concern

Clean Water Act

- day

data quality objectives

dry weight

Effects Level Approach

Equilibrium Partitioning Approach

Effects Range Approach

effects range-low

effects range-median

equilibrium-based sediment guidelines

final chronic values

Florida Department of Environmental Protection

Florida Geological Survey

fraction organic carbon

hexachlorobenzene

hexachlorobutadiene

hexachlorocyclohexane

partition coefficient for sediment organic carbon

octanol-water partition coefficient

partition coefficients

Lowest effects levels

Logistic Regression Modeling Approach

mean-metals or PAHs or PCBs

MacDonald Environmental Sciences Ltd.

moderate effects threshold

no effect concentrations or

National Pollutant Discharge Elimination System

organochlorine pesticides

probable AETs

polycyclic aromatic hydrocarbons

polychlorinated biphenyls

polychlorinated dibenzo-p-dioxins

polychlorinated dibenzofurans

viii 
TABLE OF CONTENTS 

PEC-Qs PEC-quotients

PECs probable effect concentrations

PEL probable effects level

PEL-HA probable effects level-Hyalella azteca

SECs sediment effect concentrations

SELs severe effects levels

SEM simultaneously extracted metals

SLC screening level concentration

SLCA Screening Level Concentration Approach

SQAG-Qs SQAG-quotients

SQAGs sediment quality guidelines

SQALs sediment quality advisory levels

SQGs sediment quality guidelines

SQROs Sediment quality remediation objectives

SSLC species screening level concentration

SVOCs semi-volatile organic chemicals

T10 10 percent probability of observing sediment toxicity

T50 50 percent probability of observing sediment toxicity

T90 90 percent probability of observing sediment toxicity

TECs threshold effect concentrations

TEL threshold effects level

TEL-HA threshold effects level-Hyalella azteca

TETs toxic effects threshold

TMDL total maximum daily load

TOC total organic carbon

TRA tissue residue approach

TRA Tissue residue approach

TRGs tissue residue guidelines

TRGs tissue residue guidelines

USEPA United States Environmental Protection Agency

USFDA Action Levels United States Food and Drug Administration Action Levels

USGS United States Geological Survey

WS whole sediment

ix 
EXECUTIVE SUMMARY 

Executive Summary 

In response to the need for guidance on the assessment of sediment quality conditions in 

freshwater ecosystems, Florida Department of Environmental Protection (FDEP) and its 

partners launched the Freshwater Sediment Quality Assessment Initiative in early 2000. 

This initiative, which is being implemented cooperatively by FDEP, United States 

Geological Survey (USGS), United States Environmental Protection Agency (USEPA), 

county governments, and water management districts (see Acknowledgments for a list of 

cooperators), consists of three main elements, including: 

• Formulation of an integrated framework for planning, designing, implementing, 

and interpreting the results of sediment quality investigations; 

• Development of an interpretive tool for assessing metal enrichment in freshwater 

sediments; and, 

• Establishment of numerical,sediment quality assessment guidelines (SQAGs) for 

assessing the potential for adverse biological effects associated with exposure to 

contaminated sediments. 

Together, these three elements of the overall Freshwater Sediment Quality Assessment 

Initiative are intended to provide FDEP staff and others with the guidance needed to conduct 

sediment quality assessments and to support defensible sediment management decisions. 

This report, which addresses the third element of the initiative, describes the development 

and evaluation of numerical SQAGsthat are intended to support the assessments ofsediment 

quality conditions in Florida inland waters, including effects-based SQAGs and 

bioaccumulation-based SQAGs. The effects-based SQAGs are intended to provide a means 

of determining the concentrations of sediment-associated contaminants that are unlikely to 

be associated with adverse biological effects and those that are likely to be associated with 

sediment toxicity or other adverse effects on sediment-dwelling organisms. By comparison, 

the bioaccumulation-based SQAGs are intended to identify the concentrations of sedimentassociated contaminants that are unlikely to be associated with adverse effects on aquaticdependent wildlife and/or human health. 

x 
EXECUTIVE SUMMARY 

To support the identification of interests and needsrelated to the assessment of contaminated 

sedimentsin Florida inland waters, FDEP convened a workshop in 2000 (MacDonald 2000). 

Based on input provided by workshop participants, the potential for adverse effects on 

sediment-dwelling organisms, aquatic-dependent wildlife, and human health represent the 

principal concern relative to contaminated sediments. In addition to identifying sediment 

quality issues and concerns, workshop participants also identified the toxic and 

bioaccumulative chemicals of potential concern (COPCs) for which numerical SQAGs are 

required to support sediment quality assessments in the state. Metals, polycyclic aromatic 

hydrocarbons (PAHs), polychlorinated biphenyls (PCBs), chlorinated benzenes, phthalates, 

triazine herbicides, organophosphate pesticides, organochlorine pesticides (OC pesticides), 

and toxaphene were identified as the highest priority toxic substances that partition into 

sediments. The bioaccumulative substances of greatest concern included mercury, PAHs, 

PCBs, chlorinated benzenes, polychlorinated dibenzo-p-dioxins (PCDDs) and 

polychlorinated dibenzofurans (PCDFs), and OC pesticides. 

A total of eight distinct approaches were reviewed and evaluated to support the establishment 

of numerical SQAGs for Florida inland waters. Both empirical and theoretical approaches 

were considered to support the derivation of numerical SQAGs for the protection of 

sediment-dwelling organisms, including: screening level concentration approach (SLCA); 

effects range approach (ERA); effects level approach (ELA); apparent effects threshold 

approach (AETA); equilibrium partitioning approach (EqPA); logistic regression modeling 

approach (LRMA); and, consensus approach (CA). Based on the results of this evaluation, 

it wasrecommended that guidelines developed using the consensus-based approach [i.e., the 

threshold effect concentrations (TECs) and probable effect concentrations (PECs)] be 

adopted as preliminary effects-based SQAGs for Florida inland waters (MacDonald et al. 

2000a). For those substances for which consensus-based guidelines were not available, it 

wasrecommended that guidelines derived using other effects-based approaches be evaluated 

to select SQAGs that could be used on an interim basis in Florida. The tissue residue 

approach (TRA) was considered to be the most relevant method for deriving numerical 

SQAGs for the protection of wildlife and human health (i.e., for substances that 

bioaccumulate in the food web). 

The evaluations that have been conducted to date demonstrate that the consensus-based 

guidelines provide reliable and predictive tools for assessing sediment quality conditions 

xi 
EXECUTIVE SUMMARY 

(MacDonald et al. 2000a; Crane et al. 2000; USEPA 2000a; Ingersoll et al. 2001). While 

these results generate a high level of confidence in the consensus-based guidelines, a further 

evaluation of the predictive ability of these guidelines was conducted to assess their 

relevance in the southeastern portion of the United States. To support this evaluation, 

matching sediment chemistry and sediment toxicity data were assembled from diverse 

studies conducted throughout USEPA Regions III, IV, and VI. For each of the samples 

represented in the project database, mean PEC-quotients (PEC-Qs) were calculated. 

Subsequently, the incidence of toxicity (i.e., to amphipods, Hyalella azteca, and midges, 

Chironomus tentans and Chironomus riparius) within ranges of mean PEC-Qs was 

calculated and compared to the results obtained using the information contained in the 

national database (USEPA 2000a). Additionally, concentration-response relationships were 

developed using the regional database and compared to the relationships developed for the 

same test organisms and endpoints using the data contained in the national database. The 

results of these evaluations showed that systematic differences in the toxicity of sedimentassociated COPCs (as expressed using mean PEC-Qs) do not exist between the regional and 

national data sets. Therefore, it was concluded that consensus-based guidelines are likely to 

represent relevant tools for assessing sediment quality conditions in Florida and should be 

adopted as the effects-based SQAGs. 

Together, the effects-based and bioaccumulation-based SQAGs describe the conditions that 

need to be maintained in freshwater ecosystems to protect sediment-dwelling organisms, 

aquatic-dependent wildlife, and human health against the adverse effects associated with 

exposure to contaminated sediments. Using the recommended approach, effects-based 

SQAGs were recommended for a total of 29 COPCs in Florida inland waters. Interim 

SQAGs were recommended for another 20 COPCs, based on the effects-based guidelines 

that have been promulgated in other jurisdictions. Bioaccumulation-based SQAGs for the 

protection of aquatic-dependent wildlife were recommended for 11 COPCs, while SQAGs 

for the protection of human health were recommended for 52 COPCs in the state. Because 

it was not possible to establish SQAGs for all of the COPCs that were identified by 

workshop participants, narrative SQAGs were also recommended to support assessments of 

sediment quality conditions. 

The numerical SQAGs are intended to provide science-based tools for assessing sediment 

quality conditions in Florida’s freshwater ecosystems. To assist potential users of these 

xii 
EXECUTIVE SUMMARY 

tools, the recommended applications of the SQAGs were also described in this report. In 

total, five principal program applications were identified for the SQAGs, including: 

supporting monitoring and assessment initiatives; assessing and managing contaminated 

sites; restoring wetland habitats; assessing ecological risks; and, supporting environmental 

regulation programs. Although the potential uses of the SQAGs were explicitly described, 

it is important to note that the SQAGs should be used together with other assessment tools 

to support comprehensive assessments of sediment quality conditions. MacDonald and 

Ingersoll(2002a; 2002b) and Ingersoll and MacDonald (2002) describe the ecosystem-based 

framework for designing, conducting, and interpreting the results of sediment quality 

investigations. 

xiii 
ACKNOWLEDGMENTS 

Acknowledgments 

The authors would like to acknowledge the efforts of a number of individuals who 

contributed to the preparation of ‘Development and Evaluation of Numerical Sediment 

Quality Assessment Guidelinesfor Florida Inland Waters’. First, we would like to thank the 

members of the Science Advisory Group on Sediment Quality Assessment for their insight 

and guidance on the development of sediment quality assessment guidelines and associated 

analyses of their predictive ability. In addition, we would like to thank the many 

investigators who provided relevant data for inclusion in the regional sediment toxicity 

database and fielded our numerous requests for additional information. These individuals 

include, but are not limited to: 

Beth McGee (United States Fish and Wildlife Service) 

Chris Ingersoll (United States Geological Survey) 

Parley Winger (United States Geological Survey) 

Peter Lasier (United States Geological Survey) 

Betty Beshoar (Kentucky Division of Water) 

Phyllis Fuchsman (ARCADIS G&M) 

Debra Rossi (United States Environmental Protection Agency) 

Jim Houston (CleanTech) 

Albert Westerman (Kentucky Department for Environmental Protection)

Bob Suedel (Entrix, Inc.)

Corlis West (United States Environmental Protection Agency)

David Velinsky (Patrick Center for Environmental Research)

Don Cherry (Virginia Polytechnic Institute and State University)

Michael Lewis (EPA Gulf Ecology Division)

Joel Lusk (United States Fish and Wildlife Service)

Kurt Olinger (Deleware Department of Natural Resources and Environmental Control)

Melissa Hughes (United States Environmental Protection Agency)

Ron Gouguet (National Oceanic and Atmospheric Administration)

Sharon Thoms (United States Environmental Protection Agency)

Robert Frakes (United States Fish and Wildlife Service)

David Hornsby (Suwannee River Water Management District)

Robert A. Hoke (E.I. Dupont deNemours Company, Haskell Laboratory)

Randy Sturgeon (United States Environmental Protection Agency)

Douglas Dawson (Ashland University)

Steven Twidwell (Texas Natural Resources Conservation Commission)

Jack Davis (Texas Natural Resources Conservation Commission)

Gerald A. LeBlanc (North Carolina State University)

Andrea H. Baird & Jennifer Osterhoudt (Mote Marine Laboratory)

Jerry F. Hall (Alto Technology Resources, Inc.)

Ian Hartwell (National Oceanic and Atmospheric Administration)

Charles Demas (United States Geological Survey)

xiv 
ACKNOWLEDGMENTS 

Tyler Baker (Tennessee Valley Authority)

Harriette L. Phelps (University of D.C.)

Tim Knight (Ouachita Baptist University)

David Burke (University of Southern Mississippi)

Jay Field (National Oceanic and Atmospheric Administration)

Doyle Brittain (United States Environmental Protection Agency)

James J. Feeney (United States Environmental Protection Agency)

David J. Soucek (Virginia Polytechnic Institute and State University)

Giezelle Bennett (United States Environmental Protection Agency)

Donald S. Cherry (Virginia Polytechnic Institute and State University)

Donald C. Wade (Tennessee Valley Authority)

Arthur J. Stewart (Oak Ridge National Laboratory)

Jack Q. Word (Batelle Marine Sciences Lab)

Claire O'Neill (United States Army Corps of Engineers)

W. Gregory Cope (North Carolina State University)

Lisa Noble (Keesler Air Force Base)

Joel Baker (Chesapeake Biological Laboratory, University of Maryland)

Edward Furlong (United States Geological Survey)

Charlie Howell (United States Environmental Protection Agency)

Lynn Adams Kszos (Oak Ridge National Laboratory)

Duane Chapman (United States Geological Survey)

Mike Buchman (National Oceanic and Atmospheric Administration)

Christian E. Schlekat (United States Geological Survey)

Charlie Strobel (United States Environmental Protection Agency)

William T. Waller (University of North Texas, Institute of Applied Sciences)

Furthermore, we would like to express our sincerest appreciation to the members of the 

project Steering Committee for providing oversight and excellent review comments on 

previous drafts of this report. The Steering Committee consisted of the following 

individuals: 

Scott Ireland (United States Environmental Protection Agency)

Ed Long (Long and Associates)

Herb Windom (Skidaway Institute of Oceanography)

Thomas Biernacki (Florida Department of Environmental Protection Agency)

Asia Ceric (St. Johns River Water Management District)

Larry Fink (South Florida Water Management District)

Tim Fitzpatrick (Florida Department of Environmental Protection Agency)

Russ Frydenborg (Florida Department of Environmental Protection Agency)

Steve Grabe (Hillsborough County Environmental Protection Commission)

Lee Hefty (Miami-Dade County Environmental Resource Management)

John Higman (St. Johns River Water Management District)

Thomas Seal (Florida Department of Environmental Protection Agency)

xv 
ACKNOWLEDGMENTS 

Gail Sloane (Florida Department of Environmental Protection Agency) 

Steve Wolfe (Florida Department of Environmental Protection Agency) 

Finally, timely review comments on the final draft of this report were provided by Tom Seal. 

Funding to support the preparation of this report was provided by the Florida Department of 

Environmental Protection. This report has been reviewed in accordance with United States 

Geological Survey policies. 

xvi 
INTRODUCTION – PAGE 1 

Chapter 1 Introduction 

1.0 Background 

Traditionally, management of aquatic resources in Florida has focused primarily on water 

quality. However, the importance of sediments in terms of determining the fate and effects 

of a wide variety of chemicals of potential concerns (COPCs) has become more apparent in 

recent years(MacDonald et al. 1996; Ingersoll et al. 1997). In addition to providing habitats 

for many organisms, sediments are important because many toxic substances that are found 

at only trace levels in water can accumulate to elevated levels in sediments. As such, 

sediments serve both as reservoirs and potential sources of COPCs to the water column. 

Sediment-associated COPCs have the potential to cause direct effects on sediment-dwelling 

organisms and to adversely affect wildlife and human health when these substances 

accumulate in the food web. Therefore, information on sediment quality conditions is 

essential for evaluating the overall status of freshwater ecosystems. 

Florida Department of Environmental Protection (FDEP) plays a lead role in the assessment 

and management of aquatic resources in the state. To meet its responsibilities in terms of 

managing Florida’s unique freshwater ecosystems, FDEP has developed a number of 

programs that enable it to effectively protect water quality and ensure proper waste 

management. Many of these programs have components that necessitate the assessment and 

management of sediment quality conditions, including: 

• Watershed Monitoring; 

• Environmental Resource Permitting; 

• Everglades Ecosystem Restoration; 

• Industrial Wastewater; 

• Mine Reclamation; 

• Nonpoint Source/Stormwater; 

• Solid and Hazardous Waste; 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
INTRODUCTION – PAGE 2 

• State Lands; 

• Surface Water; 

• Total Maximum Daily Loads; and, 

• Waste Cleanup. 

In response to the need for guidance on the assessment of sediment quality conditions in 

freshwater ecosystems, FDEP and its partners launched the Freshwater Sediment Quality 

Assessment Initiative in early 2000 (Appendix 1). This initiative, which is being 

implemented cooperatively by FDEP, United States Geological Survey (USGS), United 

States Environmental Protection Agency (USEPA), county governments, and water 

management districts, consists of three main elements, including: 

• Formulation of an integrated framework for planning, designing, implementing, 

and interpreting the results of sediment quality investigations; 

• Development of an interpretive tool for assessing metal enrichment in freshwater 

sediments; and, 

• Establishment of numericalsediment qualityassessment guidelines(SQAGs) for 

assessing the potential for adverse biological effects associated with exposure to 

contaminated sediments. 

Together, these three elements of the overall Freshwater Sediment Quality Assessment 

Initiative are intended to provide FDEP staff and others with the guidance that is needed to 

conduct sediment quality assessments and to support defensible sediment management 

decisions. 

1.1 Formulation of an Ecosystem-Based Framework for 

Assessing Contaminated Sediments 

The first element of the Freshwater Sediment Quality Assessment Initiative involves the 

development of an integrated framework for assessing sediment qualityconditionsin Florida 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
INTRODUCTION – PAGE 3 

inland waters. In response to the need for such a framework, FDEP has formulated detailed 

guidance of the assessment of contaminated sediments. The resultant three-volume guidance 

manual provides: 

• An ecosystem-based framework for assessing and managing contaminated 

sediments (Volume I; MacDonald and Ingersoll 2002a); 

• Recommended procedures for designing and implementing sediment quality 

investigations (Volume II; MacDonald and Ingersoll 2002b); and, 

• Recommended procedures for interpreting the results of sediment quality 

investigations (Volume III; Ingersoll and MacDonald 2002). 

The first volume ofthe guidancemanual, AnEcosystem-basedFramework forAssessing and 

Managing Contaminated Sediments in Freshwater Ecosystems (MacDonald and Ingersoll 

2002a), describes the five step process that is recommended to support the assessment and 

management of sediment quality conditions (i.e., relative to sediment-dwelling organisms, 

aquatic-dependent wildlife, and human health). Importantly, the document provides an 

overview of the framework for ecosystem-based sediment quality assessment and 

management. The recommended procedures for identifying sediment quality issues and 

concerns and compiling the existing knowledge base are also described. Furthermore, the 

recommended proceduresfor establishing ecosystemgoals, ecosystemhealth objectives, and 

sediment management objectives are presented. Finally, methods for selecting ecosystem 

health indicators, metrics, and targets for assessing contaminated sediments are described. 

Together, this guidance is intended to support planning activities related to contaminated 

sediment assessments,such that the resultant data are likelyto support sediment management 

decisions at the site under investigation. 

The second volume of the series, Design and Implementation of Sediment Quality 

Investigations (MacDonald and Ingersoll 2002b), describes the recommended procedures for 

designing and implementing sediment quality assessment programs. More specifically, 

Volume II provides an overview ofthe recommended framework for assessing and managing 

sediment quality conditions. In addition, Volume II presents the recommended procedures 

for conducting preliminary and detailed site investigations to assess sediment quality 

conditions. Furthermore, the factors that need to be considered in the development of 

sampling and analysis plans for assessing contaminated sediments are described. 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
INTRODUCTION – PAGE 4 

Supplemental guidance on the design of sediment sampling programs, on the evaluation of 

sediment quality data, and on the management of contaminated sediments is provided. The 

types and objectives of sediment quality assessments that are commonly conducted in 

freshwater ecosystems are also described. 

The third volume in the series, Interpretation of the Results of Sediment Quality 

Investigations (Ingersoll and MacDonald 2002), describes the four types of information that 

are commonly used to assess contaminated sediments, including whole-sediment and porewater chemistrydata, whole-sediment toxicity data, benthic invertebrate community structure 

data, and bioaccumulation data. Some of the other tools that can be used to support 

assessments ofsediment quality conditions are also described (e.g., fish health assessments). 

The information compiled on each of the tools includes: descriptions of its applications, 

advantages, and limitations; discussions on the availability ofstandard methods, evaluations 

of data quality and methodological uncertainty; interpretation of the associated data; and, 

recommendations to guide its use. Furthermore, guidance is provided on the interpretation 

of data on multiple indicators of sediment quality conditions. Together, the information 

provided in the three volume series is intended to further support the design and 

implementation of focused sediment quality assessment programs. 

1.2 Development of a Metals Interpretive Tool 

The development of an interpretive toolfor assessingmetal enrichment in Florida freshwater 

sediments was identified as a high priority element of the Freshwater Sediment Quality 

Assessment Initiative. The metals interpretive tool is intended to provide users with a 

simple way to account for the natural variability of metal concentrations in Florida’s 

freshwater ecosystems and to determine whether a sediment is enriched by metals. To 

support the development of such a tool, FDEP and its partners collected samples of lake, 

stream, and spring sediments at numerous uncontaminated sitesthroughout north and central 

Florida. In each of these sediment samples, the concentrations of metals were determined. 

Subsequently, the resultant data were evaluated and used to develop a metals interpretive tool 

for freshwater sediments. 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
INTRODUCTION – PAGE 5 

The data on the concentrations of trace metals and candidate reference elements (i.e., 

aluminum, iron, magnesium) in uncontaminated lake, stream, and spring sediments were 

analyzed to support the development of a metals interpretive tool. A simple statistical 

approach was used to evaluate the data on metals concentrations, including assessment ofthe 

normality of the metals concentration data, identification and removal of outliers, and 

determination of relationships between each metal and candidate normalizers. More 

specifically, linear regressions and 95% prediction limits were used to describe the 

relationships between the concentrations of trace metals and candidate normalizers. The 

resultant 95% prediction limits establish the expected range of natural variation of metal 

concentrations in uncontaminated freshwater sediments (Carvalho and Schropp 2002). 

Application of the freshwater metals interpretive tool is relatively straightforward. 

Specifically, users can compare the concentrations of metals in freshwater sediments at a new 

site (i.e., one that was not included in the database that was compiled to develop the metals 

interpretive tool) to the metal-reference element relationships that were established for 

uncontaminated sediments to determine if measured levels fall within the expected natural 

ranges. Metal enrichment is suspected when the measured concentrations of trace metals 

exceed the upper 95% prediction limits for uncontaminated sediments. The development and 

applications of the metals interpretive tool is described in a technical report prepared by 

Carvalho and Schropp (2002). 

1.3 Establishment of Sediment Quality Assessment Guidelines 

The third element of the Freshwater Sediment Quality Assessment Initiative involves the 

development and evaluation of numerical SQAGs for Florida inland waters, including 

effects-based SQAGs and bioaccumulation-based SQAGs. The effects-based SQAGs are 

intended to provide a means of determining the concentrations of sediment-associated 

contaminants that are unlikely to be associated with adverse biological effects and those that 

are likely to be associated with sediment toxicity or other adverse effects on sedimentdwelling organisms. By comparison, the bioaccumulation-based SQAGs are intended to 

identify the concentrations of sediment-associated contaminants that are unlikely to be 

associated with adverse effects on aquatic-dependent wildlife or human health. 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
INTRODUCTION – PAGE 6 

The purpose of this report is to describe the process that was used to develop and evaluate 

SQAGs for freshwater ecosystems in Florida. More specifically, this report was prepared to 

provide background information on the assessment of contaminated sediments, to describe 

the approach to the establishment of numerical SQAGs, to evaluate the predictive ability of 

the SQAGs, and to recommend effects-based and bioaccumulation-based SQAGs for 

assessing sediment quality conditions in freshwater ecosystems. This report is also intended 

to provide a summary of program applications for the SQAGs and a series of 

recommendations for supporting assessments of sediment quality conditions in Florida 

[Note: In this report, the tools that have been developed in other jurisdictions for assessing 

the effects of contaminated sediments on sediment-dwelling organisms, aquatic-dependent 

wildlife, and human health are termed sediment quality guidelines (SQGs), while those that 

have been developed or recommended for use in Florida are termed SQAGs]. 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
INTERESTS AND NEEDS – PAGE 7 

Chapter 2 Interests and Needs Related to the 

Assessment of Contaminated Sediments in 

Florida Inland Waters 

2.0 Introduction 

Concerns relative to the management of aquatic resources in freshwater systems have 

traditionallyfocused primarilyon water quality. As such, early aquatic resource management 

efforts were often directed at assuring the potability ofsurface water or groundwatersources. 

Subsequently (i.e., with the authorization of the Clean Water Act; CWA), the scope of these 

management initiatives expanded to include protection of instream (i.e., fish and aquatic 

life), agricultural, industrial, and recreational water uses. While initiatives undertaken 

pursuant to the CWA have unquestionably improved the quality of the nation’s waters, a 

growing body of evidence indicatesthat management efforts directed solely at the attainment 

of goals for surface water quality are unlikely to provide adequate protection for the 

designated uses of aquatic ecosystems. 

In recent years, concerns relative to the health and vitality of aquatic ecosystems have begun 

to reemerge. One of the principal reasons for this is that many toxic and bioaccumulative 

chemicals (such as metals, polycyclic aromatic hydrocarbons - PAHs, polychlorinated 

biphenyls - PCBs, chlorophenols, and organochlorine pesticides - OC pesticides), which are 

found in only trace amounts in water, can accumulate to elevated levels in sediments. Some 

of these pollutants, such as OC pesticides and PCBs, were released into the environment 

some time ago. Although the use of many of these substances has been banned in the United 

States for nearly 30 years, these chemicals continue to persist in the environment. Other 

COPCs continue to enter our waters from industrial and municipal discharges, urban and 

agricultural runoff, and atmospheric deposition from remote sources. Due to their physical 

and chemical properties, many of these substances tend to accumulate in sediments. In 

addition to providing sinksformany chemicals,sediments can also serve as potentialsources 

of pollutantsto the water column (i.e., when conditions change in the receiving watersystem; 

such as during periods of anoxia or after severe storms). 

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INTERESTS AND NEEDS – PAGE 8 

This chapter of the report is intended to provide background information relevant to the 

assessment of contaminated sediments in Florida inland waters. More specifically, this 

chapter includes discussions on the role of sediments in freshwater ecosystems and on the 

principal sediment quality issues and concerns in the state. Additionally, the main reasons 

that information on sediment quality conditions are being collected in Florida are described 

(i.e., based on the input that was provided by stakeholders at a workshop that was convened 

by FDEP in 2000; MacDonald 2000). Furthermore, the principal COPCs in Florida inland 

waters are identified. 

2.1 Role of Sediments in Freshwater Ecosystems 

The particulatematerialsthat lie below the waterin ponds, lakes,springs,streams,rivers, and 

other aquatic systems are called sediments (ASTM 2001a). Sediments represent essential 

elements of aquatic ecosystems because they support both autotrophic and heterotrophic 

organisms. Autotrophic (which means self-nourishing) organisms are those that are able to 

synthesize food from simple inorganic substances (e.g., carbon dioxide, nitrogen, and 

phosphorus) and the sun's energy. Green plants, such as algae, bryophytes (e.g., mosses and 

liverworts), and aquatic macrophytes (e.g., sedges, reeds, and pond weed), are the main 

autotrophic organisms in freshwater ecosystems. In contrast, heterotrophic (which means 

other-nourishing) organisms utilize, transform, and decompose the materials that are 

synthesized by autotrophic organisms (i.e., by consuming or decomposing autotrophic and 

other heterotrophic organisms). Some of the important heterotrophic organisms that can be 

present in aquatic ecosystems include bacteria, epibenthic and infaunal invertebrates, fish, 

amphibians, and reptiles. Birds and mammals can also represent important heterotrophic 

components of aquatic and aquatic-dependent food webs (i.e., through the consumption of 

aquatic organisms). 

Sediments support the production of aquatic organisms in several ways. For example, hardbottom sediments, which are characteristic of faster-flowing streams and are comprised 

largely of gravels, cobbles, and boulders, provide stable substrates to which periphyton (i.e., 

the algae that grows on rocks) can attach and grow. Soft sediments, which are common in 

ponds, lakes, and slower-flowing sections of rivers and streams, are comprised largely of 

sand, silt, and clay (i.e., fine sediment). Such sediments provide substrates in which aquatic 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
INTERESTS AND NEEDS – PAGE 9 

macrophytes can root and grow. The nutrients that are present in such sediments can also 

nourish aquatic macrophytes. By providing habitats and nutrients for aquatic plants, 

sediments support autotrophic production (i.e., the production of green plants) in aquatic 

systems. Sediments can also support prolific bacterial and meiobenthic communities, the 

latter including protozoans, nematodes, rotifers, benthic cladocerans, copepods, and other 

organisms. Bacteria represent important elements of aquatic ecosystems because they 

decompose organic matter (e.g., the organisms that die and accumulate on the surface of the 

sediment, as well as anthropogenically-derived organic chemicals) and, in so doing, release 

nutrients to the water column and increase bacterial biomass. Bacteria represent the primary 

heterotrophic producers in aquatic ecosystems, upon which many meiobenthic organisms 

depend. The role that sediments play in supporting primary productivity (both autotrophic 

and heterotrophic) is essential because green plants and bacteria represent the foundation of 

food webs upon which all other aquatic organisms depend (i.e., they are consumed by many 

other aquatic species). 

In addition to their role in supporting primary productivity, sediments also provide essential 

habitats for many sediment-dwelling invertebrates and benthic fish. Some of these 

invertebrate species live on the sediments (termed epibenthic species), while others live in 

the sediments (termed infaunal species). Both epibenthic and infaunal invertebrate species 

consume the plants, bacteria, and other organisms that are associated with the sediments. 

Invertebratesrepresent important elements of aquatic ecosystems because they are consumed 

bya wide range of wildlife species, including amphibians,reptiles,fish, birds, andmammals. 

For example, virtually all fish species consume aquatic invertebrates during all or a portion 

of their life cycle. In addition, many birds (e.g., dippers, sand pipers, and swallows) consume 

aquatic invertebrates. Similarly, aquatic invertebrates represent important food sources for 

both amphibians (e.g., frogs and salamanders) and reptiles (e.g., turtles and snakes). 

Therefore, sediments are of critical importance to many wildlife species due to the role that 

they play in terms of the production of aquatic invertebrates. 

Importantly, sediments can also provide habitats for many wildlife species during portions 

of their life cycle. For example, a variety of fish species utilize sediments for spawning and 

incubation of their eggs and larvae. In addition, juvenile fish often find refuge from 

predators in sediments and/or in the aquatic vegetation that is supported by the sediments. 

Furthermore, many amphibian species burrow into the sedimentsin the fall and remain there 

throughout the wintermonths,such that sediments provide important overwintering habitats. 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
INTERESTS AND NEEDS – PAGE 10 

Therefore, sediments play a variety of essential roles in terms of maintaining the structure 

(i.e., assemblage of organisms in the system) and function (i.e., the processes that occur in 

the system) of aquatic ecosystems. 

2.2 Sediment Quality Issues and Concerns 

Considering the important roles that they play, it is apparent that sediments represent 

essential elements of freshwater ecosystems. Yet, the available information on sediment 

quality conditions indicate that sediments throughout the United States, including Florida, 

are contaminated by a wide range oftoxic and bioaccumulative substances, includingmetals, 

PAHs, PCBs, OC pesticides, a variety of semi-volatile organic chemicals (SVOCs), 

polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans (PCDFs; 

USEPA 1997). The nature and extent of such sediment contamination depends on a variety 

of factors, such as the types of sources of COPCs that are present in the system under 

investigation, the loadings of COPCsfrom the varioussources, proximity to sources, and the 

fate of the COPCs once they are released into the aquatic system. 

Contaminated sediments represent an important environmental concern for several reasons. 

First, contaminated sediments have frequently been demonstrated to be toxic to sedimentdwelling organisms and fish. As such, exposure to contaminated sediments can result in 

decreased survival, reduced growth or impaired reproduction in benthic invertebrates and 

fish. Additionally, certain COPCs in the sediments are taken up by benthic organisms 

through a process called bioaccumulation. When larger animals feed on these contaminated 

prey species, the pollutants are taken into their bodies and are passed along to other animals 

in the food web in a process called biomagnification. As a result of the effects of toxic and 

bioaccumulative substances, benthic organisms, fish, birds, and mammals can be adversely 

affected by contaminated sediments (Ingersoll et al. 1997; MacDonald et al. 2002a; 2002b). 

Contaminated sediments can also adversely affect human health and the human uses of 

aquatic ecosystems. First, human health can be adversely affected due to direct exposure to 

contaminated sediments during wading or swimming in affected waterbodies. Consumption 

of contaminated fish and shellfish also poses a risk to human health. Human use of aquatic 

ecosystems can also be compromised by the presence of contaminated sediments through 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
INTERESTS AND NEEDS – PAGE 11 

reductions in the abundance of food or sportfish species or due to the imposition of fish 

consumption advisories(i.e., when fish orshellfish tissues are found to contain unacceptable 

levels of bioaccumulative substances). As such, contaminated sediments in freshwater 

ecosystems pose potential hazards to sediment-dwelling organisms (i.e., epibenthic and 

infaunal invertebrate species), aquatic-dependent wildlife species (i.e., fish, amphibians, 

reptiles, birds, and mammals), and human health (Ingersoll et al. 1997). 

2.3 Reasons for Collecting Information on Sediment Quality 

Conditions 

Information on sediment qualityconditionsis offundamental importance in themanagement 

of natural resources. To help focus the Freshwater Sediment QualityAssessmentInitiative, 

FDEP conducted a multi-stakeholder workshop in early 2000 to identify interests and needs 

related to sediment quality assessment and management (MacDonald 2000). Workshop 

participants were asked to describe why sediment quality data are currently being collected 

in Florida. In addition, information was solicited on how such data are currently being used 

to support management decisions in the state. Based on the responses that were provided by 

workshop participants, it is apparent that the primary reasons for conducting sediment quality 

assessments in Florida include: 

• To support broad assessments of environment conditions. The watershed 

assessments that are currently being conducted throughout the state provide a 

good example of such broad environmental assessments. Information on 

sediment quality conditions is needed to evaluate the effects of contaminated 

sediments on aquatic organisms, wildlife, and human health; 

• To support the identification and assessment of sites with contaminated 

sediments. In this context, information on sediment quality conditions is needed 

to determine if a site is contaminated, to identify COPCs, and to assess the areal 

extent of contamination; 

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INTERESTS AND NEEDS – PAGE 12 

• To evaluate the status and trends in environmental conditions. Information on 

sediment quality conditions is needed to determine if water bodies are currently 

supporting designated uses and to determine if conditions are improving or 

worsening over time; 

• To support ecological risk assessments. Information on sediment quality 

conditions is needed to evaluate the risks posed by contaminated sediments to 

aquatic and terrestrial receptors. Such information is also required to evaluate 

various risk management options; 

• To assess the efficacy of point or non-point source pollution control efforts. 

Information on sediment quality conditions is needed to determine if 

environmental conditions are improving as a result ofthe management initiatives 

that are being implemented to reduce inputs of COPCs into aquatic ecosystems; 

• To assess the cumulative environmental effects of multiple facilities in an area. 

Information on sediment quality conditions is needed to determine if sufficient 

assimilative capacity exists to support additional facilities in a particular water 

body and to evaluate various options for siting new facilities; 

• To evaluate the feasibility of restoring wetland habitats. Information on sediment 

quality conditions is needed to determine if wetland sediments, post-restoration, 

are likely to support the designated uses of the aquatic ecosystem. This 

information is also needed to support the design of wetland restoration projects; 

and, 

• To assess the environmental impacts of various anthropogenic activities. 

Information on sediment quality conditions is needed to conduct comprehensive 

assessments of the effects of anthropogenic activities, particularly those that 

result in releases of toxic or bioaccumulative substances to surface waters. 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
INTERESTS AND NEEDS – PAGE 13 

2.4 Chemicals of Potential Concern 

Identification of COPCs represents an essential element of the overall SQAGs derivation 

process. In the context of this report, COPCs are defined as those substances that are 

released in freshwater ecosystems as a result of human activities(including those originating 

from both point and non-point sources) and have the potential to adversely affect the uses of 

aquatic ecosystems (e.g., aquatic life, recreation and aesthetics). It is important to establish 

the COPCs in Florida inland waters because such information, when considered in 

conjunction with data on the environmental fate and persistence ofthese chemicals, provides 

a basis for identifying the substances that are likely to partition into sediments (i.e., the 

sediment-associated COPCs). The toxic and bioaccumulative COPCs that are likely to occur 

in Florida freshwater sediments are considered to be the highest priority for establishing 

numerical SQAGs. 

A variety of methods could be used to identify the sediment-associated COPCs in Florida 

inland waters. To expedite this process, FDEP convened a multi-stakeholder workshop in 

early 2000 to identify the substances that were most likely to occur at levels that could 

compromise the beneficial uses of freshwater ecosystems (MacDonald 2000). Based on the 

input that was provided by workshop participants, the highest priority substances for 

establishing numerical SQAGs included: 

Toxic Substances that Partition into Sediments: 

• Metals (arsenic, barium, beryllium, boron, cadmium, chromium, cobalt, copper, 

lead, mercury, nickel, silver, strontium, titanium, and zinc); 

• Polycyclic aromatic hydrocarbons (PAHs; acenaphthene, acenaphthylene, 

anthracene, fluorene, 2-methylnaphthalene, naphthalene, phenanthrene, 

benz[a]anthracene, benzo(a)pyrene, chrysene, dibenz[a,h]anthracene, 

fluoranthene, pyrene, total PAHs, and other PAHs); 

• Polychlorinated biphenyls (PCBs); 

• Chlorinated benzenes [hexachlorobenzene (HCB), hexachlorobutadienes 

(HCBD), and degradation products]; 

• Phthalates [e.g., bis(2-ethyl hexyl)phthalate (BEHP)]; 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
INTERESTS AND NEEDS – PAGE 14 

• Triazine herbicides (e.g., atrazine); 

• Organophosphate pesticides (e.g., diazinon); 

• Organochlorine pesticides [(OC pesticides) aldrin, chlordane; dieldrin, DDTs, 

endrin, heptachlor, heptachlor epoxide, lindane]; and, 

• Toxaphene. 

Bioaccumulative Substances that Partition into Sediments: 

• Metals (mercury); 

• PAHs (acenaphthene, acenaphthylene, anthracene, fluorene, 2-

methylnaphthalene, naphthalene, phenanthrene, benz[a]anthracene, 

benzo(a)pyrene, chrysene, dibenz[a,h]anthracene, fluoranthene, pyrene, total 

PAHs, and other PAHs); 

• PCBs; 

• Polychlorinated dibenzo-p-dioxins (PCDDs) and polychlorinated dibenzofurans 

(PCDFs); 

• Chlorinated benzenes (HCB, HCBD, and degradation products); and, 

• OC pesticides (aldrin, chlordane; dieldrin, DDTs, endrin, heptachlor, heptachlor 

epoxide, lindane). 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
APPROACHES FOR ESTABLISHING NUMERICAL SQAGS – PAGE 15 

Chapter 3 Approaches for Establishing Numerical 

Sediment Quality Assessment Guidelines for 

Freshwater Ecosystems 

3.0 Introduction 

Numericalsediment quality guidelines(including sediment quality criteria,sediment quality 

objectives, and sediment quality standards) have been developed by various jurisdictions in 

North America for both freshwater and marine ecosystems. Such guidelines have been used 

in numerous applications, including designing monitoring programs, interpreting historical 

data, evaluating the need for detailed sediment quality assessments, assessing the quality of 

prospective dredged materials, conducting remedial investigations and ecological risk 

assessments, and developing sediment quality remediation objectives (SQROs; Long and 

MacDonald 1998). Numerical SQGs have also been used by many scientists and 

administrators to identify COPCs in aquatic ecosystems and to rank areas of concern on a 

regional or national basis (e.g., USEPA 1997). It is apparent, therefore, that numerical SQGs 

represent useful tools for assessing the quality of freshwater and marine sediments 

(MacDonald et al. 1992; USEPA 1992; Adams et al. 1992; USEPA 1996; Ingersoll et al. 

1996; Smith et al. 1996; USEPA 1997; Ingersoll et al. 1997). 

Florida has been a leader in the development and implementation of numerical SQGs. In 

1994, the FDEP published sediment quality assessment guidelines (SQAGs; so termed to 

distinguish them from the SQGs that have been developed in other jurisdictions) for Florida 

coastal waters (MacDonald 1994; MacDonald et al. 1996). These SQAGs were derived 

using the effects level approach, which represents a modification of the weight-of-evidence 

approach that was developed under NOAA’s National Status and Trends Program for 

deriving empirically-based SQGs (Long and Morgan 1991). Using the effects level 

approach, two SQAGs were derived for each chemical substance, including a threshold 

effects level (TEL) and a probable effects level (PEL). These SQAGs defined three ranges 

of contaminant concentrations, including a minimal effects range, a possible effects range, 

and a probable effects range. Numerical SQAGs were established for 34 priority substances 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
APPROACHES FOR ESTABLISHING NUMERICAL SQAGS – PAGE 16 

in marine and estuarine waters, including trace metals, PAHs, PCBs, and OC pesticides. 

These SQAGs have provided useful tools for assessing sediment quality conditions in marine 

and estuarine ecosystems within the state and elsewhere in North America. 

In recent years, FDEP, USGS, Florida Geological Survey, USEPA, Dade County, South 

Florida Management District, and several other organizations have been collecting sediment 

chemistry data in freshwater ecosystems throughout the state. The results of these 

monitoring programs will provide valuable information on the concentrations of sedimentassociated contaminants throughout the state. However, interpretation of these data will 

require reliable tools for determining if measured concentrations of COPCs exceed 

background levels and/or if such levels are likely to be associated with adverse biological 

effects. The interpretive tool that was recently developed for assessing metal enrichment in 

Florida freshwater sediments provides a basis for identifying sediments in which metal 

concentrations exceed background levels (Carvalho and Schropp 2002). However, numerical 

SQAGs are still required to support assessments of the potential for biological effects 

associated with sediment contamination. 

This chapter is intended to provide the information needed to support the selection of the 

most relevant approach or approaches for establishing numerical SQAGs for Florida inland 

waters. To that end, the existing approaches to the derivation of numerical SQGs and their 

uses are described. Additionally, each of these approaches are critically evaluated to 

determine their strengths and limitations. Based on the results of that evaluation, an 

approach for establishing effects-based SQAGs for Florida inland waters is recommended. 

Similarly, an approach for establishing SQAGs for bioaccumulative substances is selected. 

3.1 Review and Evaluation of Existing Approaches to the 

Derivation of Numerical Sediment Quality Guidelines 

A number of jurisdictions throughout North America have developed numerical SQGs for 

freshwater and/or marine ecosystems. The SQGs that are currently being used in North 

America have been developed using a variety of approaches, including both empirical and 

theoretical approaches. Both empirical and theoretical approaches were considered to 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
APPROACHES FOR ESTABLISHING NUMERICAL SQAGS – PAGE 17 

support the derivation of numerical SQAGs for the protection of sediment-dwelling 

organisms, including: 

• Screening Level Concentration Approach (SLCA); 

• Effects Range Approach (ERA); 

• Effects Level Approach (ELA); 

• Apparent Effects Threshold Approach (AETA); 

• Equilibrium Partitioning Approach (EqPA); 

• Logistic Regression Modeling Approach (LRMA); and, 

• Consensus Approach (CA). 

The tissue residue approach (TRA) was considered to be the primary method for deriving 

numerical sediment quality objectives for the protection of wildlife and human health (i.e., 

for substances that bioaccumulate in the food web). The following sections of this report 

provide brief descriptions of each of these approaches. The strengths and limitations of these 

approaches are summarized in Table 3.1. 

3.1.1 Screening Level Concentration Approach 

The SLCA is a biological effects-based approach for deriving SQGs for the protection of 

benthic organisms. This approach utilizes matching biological and chemical data collected 

in field surveys to calculate a screening level concentration (SLC; Neff et al. 1986). The 

SLC is an estimate of the highest concentration of a substance that can be tolerated by a predefined proportion of benthic infaunal species. 

The SLC is calculated using a database that contains information on the concentrations of 

COPCs in sediments and on the co-occurrence of benthic organisms in the same sediments. 

For each benthic organism for which adequate data are available, a species screening level 

concentration (SSLC) is calculated. The SSLC is determined by plotting the frequency 

distribution of the COPC concentrations over all of the sites at which the species occurs 

(information from at least ten sites is required to calculate a SSLC). The 90th percentile of 

this distribution is taken as the SSLC for the species being investigated. The SSLCs for all 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
APPROACHES FOR ESTABLISHING NUMERICAL SQAGS – PAGE 18 

of the species for which adequate data are available are then compiled as a frequency 

distribution to determine the concentration that can be tolerated by a specific proportion of 

the species (i.e., the 5th percentile of the distribution would provide a SLC that should be 

tolerated by 95% of the species). This concentration is termed the SLC of the contaminant. 

A number of jurisdictions have used the SLCA to derive numerical SQGs. For example, 

Neff et al. (1986) developed freshwater SLCs for a variety of chemical substances, primarily 

using data from the Great Lakes. Similarly, the Quebec Ministry of the Environment used 

the SLCA for deriving two SQGs for each COPC in the St. Lawrence River, including a 

minimal effect threshold (MET) and a toxic effect threshold (TET; EC and MENVIQ 1992). 

The MET was calculated as the 15th percentile of the SSLCs, while the TET was calculated 

as the 90th percentile of the SSLC distribution for each substance. Therefore, the MET and 

TET are considered to provide protection for 85% and 10% of the species represented in the 

database, respectively. Furthermore, Environment Ontario developed a lowest effect level 

(LEL) and severe effect level (SEL) for various chemical substances using this approach 

(Persaud et al. 1993). 

3.1.2 Effects Range Approach 

The ERA to the derivation of SQGs was formulated to provide informal tools for assessing 

the potential for various COPCs tested in the National Status and Trends Program (NSTP) 

to be associated with adverse effects on sediment-dwelling organisms (Long and Morgan 

1991). The SQGs derivation process involves several steps, including acquisition of 

candidate data sets, review and evaluation of data sets, compilation of acceptable data into 

a project database, and data analysis (including guideline derivation). 

In the first step of the process, candidate data sets were identified using bibliographic 

database searches and communications with investigators active in the sediment assessment 

field. Following their retrieval, candidate data sets were reviewed and evaluated to 

determine their applicability for incorporation into the database (MacDonald et al. 1996). 

This evaluation was designed to determine the overall applicability of the data set, the 

methods that were used, the endpoints that were measured, and the degree of concordance 

between the chemical and biological data. The data which met the evaluation criteria were 

incorporated into the project database. 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
APPROACHES FOR ESTABLISHING NUMERICAL SQAGS – PAGE 19 

Information from several types of investigations were incorporated into the project database, 

including spiked-sediment toxicity tests, field studies conducted in the United States, and 

initiatives directed at the formulation of numerical SQGs. All of the information contained 

in the database was weighted equally, regardless of the method that was used in the 

investigation. Individual entries in the database consisted of the concentration of the COPC, 

the location of the study, the species tested and endpoint measured, and an indication of 

whether or not there was concordance between the observed effect and the concentrations 

of a specific chemical [i.e., no effect (NE), no or small gradient (NG or SG), no concordance 

(NC), or a "hit" (*), which indicated that an effect was measured in association with elevated 

sediment chemistry]. Data from non-toxic or unaffected samples were assumed to represent 

background conditions. Data which showed no concordance between chemical and 

biological variables were included in the database, but were not used to calculate the SQGs 

[i.e., only the effects data (i.e., hits) were used to calculate the SQGs]. 

Simple analytical procedures were used to derive numerical SQGs using the information that 

was compiled in the database. First, the data for which a biological effect was observed in 

association with elevated chemical concentrations (i.e., hits) were sorted in ascending order 

of concentration. Next, the 10th and 50th percentile concentrations for each compound were 

determined. The effects range-low (ERL; 10th percentile value) represents a lower threshold 

value, below which adverse effects on sensitive life stages and/or species occurred only 

infrequently. The effects range-median (ERM; 50th percentile value) represents a second 

threshold value, above which adverse effects were frequently observed. 

Using the ERA, Long and Morgan (1991) and Long et al. (1995) derived two types of 

informal SQGs (i.e., ERL and ERM) for use in the NSTP. The database that was used by 

Long and Morgan (1991) to derive the SQGs consisted of data from freshwater, estuarine, 

and marine ecosystems. Ingersoll et al. (1996) used a similar approach to derive ERLs (15th 

percentile of the effects data set) and ERMs (50th percentile of the effects data set) for 

assessing sediments from various freshwater locations in the United States. Similarly, 

MacDonald (1997) applied the ERA to regionally-collected field data to derive site-specific 

sediment effect concentrations(SECs) for PCBs and DDTsin the SouthernCaliforniaBight. 

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3.1.3 Effects Level Approach 

The ELA is closely related to the ERA described above. However, the ELA is supported by 

an expanded version of the database that was used to derive the effects ranges (Long and 

Morgan 1991). The expanded database contains matching sediment chemistry and biological 

effects data from spiked-sediment toxicity tests and from field studies conducted throughout 

North America (including both effects and no effects data). The expanded database also 

contains SQGs derived using various approaches. The information contained in the 

expanded database was evaluated and classified using the same selection criteria that were 

used to compile the original NSTP database. 

In the ELA, the underlying information in the database was used to derive two types of 

SQGs, including threshold effect levels (TELs) and probable effect levels (PELs). The TEL, 

which is calculated as the geometric mean of the 15th percentile of the effects data set and the 

50th percentile of the no effects data set, represents the chemical concentration below which 

adverse effects are expected to occur infrequently. The PEL represents a second threshold 

value, above which adverse effects are expected to be frequently observed. The PEL is 

calculated as the geometric mean of the 50th percentile of the effects data set and the 85th 

percentile of the no effects data set. 

The ELA was applied to the expanded database [i.e., Biological Effects Database for 

Sediments (BEDS)] to derive numerical SQGs (i.e., TELs and PELs) for Florida coastal 

waters (MacDonald et al. 1996). Similarly, Ingersoll et al. (1996) applied this approach to 

the results of freshwater toxicity tests on amphipods and midges to derive SQGs for 

assessing sediment quality conditions in freshwater systems. Furthermore, Smith et al. 

(1996) and CCME (1999) used the ELA to derive TELs and PELs for freshwater and marine 

systems in Canada. 

3.1.4 Apparent Effects Threshold Approach 

The AETA to the development of SQGs was developed for use in the Puget Sound area of 

Washington State (Tetra Tech Inc. 1986). The AETA is based on empirically-defined 

relationships between measured concentrations of COPCs in sediments and observed 

biological effects. This approach is intended to define the concentration of a COPC in 

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sediment above which significant (p < 0.05) biological effects are always observed. These 

biological effects include, but are not limited to, toxicity to benthic and/or water column 

species (as measured using sediment toxicity tests), changes in the abundance of various 

benthic species, and changes in benthic community structure. The AET values can be based 

on dry weight-normalized COPC concentrations or total organic carbon (TOC)-normalized 

concentrations for organic substances (Barrick et al. 1988; WDOE 1990). The guidance 

manual to support the assessment of contaminated sediments in freshwater ecosystems 

provides more information on normalizing procedures (MacDonald and Ingersoll 2002a; 

2002b; Ingersoll and MacDonald 2002). 

The state of Washington has used AET values to establish sediment quality standards and 

minimum clean-up levels for a variety of COPCs in the state (WDOE 1990). Cubbage et al. 

(1997) refined this approach to support the development of probable AETs (PAETs) using 

matching sediment chemistry and toxicity data for freshwater sediments from the state of 

Washington. Ingersoll et al. (1996) utilized a similar approach to develop freshwater AETs 

(termed no effect concentrations or NECs in that study) using the results of toxicity tests and 

chemical analyses conducted on sediments from various freshwater locations in the United 

States. 

3.1.5 Equilibrium Partitioning Approach 

The water-sediment EqPA is based on the premise that the distribution of COPCs among the 

two principal compartments in the sediment matrix (i.e., sediment solids and interstitial 

water) is predictable based on their physical and chemical properties, assuming that 

continuous equilibrium exchange between sediment and interstitial water occurs. This 

approach has been supported by the results of spiked-sediment toxicity tests, which indicate 

that positive correlations exist between the biological effects observed and the concentrations 

of COPCs measured in the interstitial water (Di Toro et al. 1991; Berry et al. 1996; Hansen 

et al. 1996). 

In the EqPA, water quality criteria developed for the protection of freshwater or marine 

organisms are used to support the SQGs derivation process. As such, the water quality 

criteria formulated for the protection of water column species are assumed to be applicable 

to benthic organisms (Di Toro et al. 1991). The SQGs are calculated using the appropriate 

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water quality criteria [usually the final chronic values (FCVs) or equivalent values; USEPA 

1998; 1999a] in conjunction with the sediment/water partition coefficients (Kp) for the 

specific COPCs. The FCV is derived from the species mean chronic values that have been 

calculated from published toxicity data and is intended to protect 95% of aquatic species. 

The calculation procedure for non-ionic organic substances is as follows: 

SQG = Kp • FCV 

where: 

SQG = Sediment quality guideline (in :g/kg); 

Kp = Partition coefficient for the chemical (in L/kg); and, 

FCV = Final chronic value (in :g/L). 

The Kp is a function of the partition coefficient for sediment organic carbon (Koc) of the 

substance under consideration and the amount of organic carbon in the sediment under 

investigation (foc; where Kp = Koc • foc; Di Toro et al. 1991). The Koc for non-ionic 

substances can be calculated from its octanol-water partition coefficient (Kow; Di Toro et al. 

1991). The foc is the decimal equivalent of the percent organic carbon in the sediment (i.e., 

foc = 0.01 if TOC = 1%). 

The EqPA has been used to derive numerical SQGs in several jurisdictions. For example, 

USEPA (1997) reported organic carbon-normalized SQGs (termed equilibrium-based 

sediment guidelines; ESGs) for a variety of non-polar organic substances. In addition, draft 

ESGs have been developed for endrin, dieldrin, and metal mixtures(S.Ireland. United States 

Environmental Protection Agency. Washington, District of Columbia. Personal 

communication). The SQGs for divalent cationic metals [i.e., simultaneously extracted 

metals (SEM)] are applied using data on the levels of acid volatile sulfide (AVS) in 

sediments (i.e., metals are thought to contribute to sediment toxicity only when SEM 

concentrations exceed AVS concentrations by a factor of five or more; Hansen et al. 1996; 

USEPA 1997). New York State Department of Environmental Conservation also developed 

SQGs for the protection of aquatic life using the EqPA (NYSDEC 1999). 

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3.1.6 Logistic Regression Modeling Approach 

In the LRMA, numerical SQGs are derived from the results of field studies conducted to 

assess sediment quality conditions. The first step of the SQGs derivation process involves 

the collection, evaluation, and compilation of matching sediment chemistry and toxicity data 

from a wide variety of sites in North America. Next, the information compiled in the project 

database is retrieved on a substance-by-substance basis, with the data from individual 

sediment samples sorted in order of ascending concentration. For each sediment sample, the 

ascending data table provides information on the concentration of the COPC under 

consideration (on either a dry weight- or organic carbon-normalized basis) and the results of 

the toxicity test (i.e., toxic or not toxic) for each endpoint (e.g., 10-d survival of amphipods; 

Field et al. 1999). 

In the next step of the process, the data contained in the ascending data tables are screened 

to minimize the potential for including samples in which the selected COPC did not 

contribute substantially to the observed toxicity. In this analysis, the chemical concentration 

in each toxic sample is compared to the mean concentration in the non-toxic samples from 

the same study and geographic area. The toxic samples with concentrations of the selected 

COPC that are less than or equal to the average concentration of that chemical in the nontoxic samples are not used in further analyses of the data (i.e., it was highly unlikely that the 

COPC substantially contributed to sediment toxicity in such samples; Field et al. 2002). 

In the final step of the analysis, the screened data are used to develop logistic regression 

models, which express the relationship between the concentration of the selected COPC and 

the probability of observing toxicity. In its simplest form, logistic models can be described 

using the following equation (Field et al. 1999): 

p = eB0 +B1(x) / (1 + eB0 +B1(x)) 

where: 

p = probability of observing a toxic effect; 

B0 = intercept parameter; 

B1 = slope parameter; and, 

x = concentration or log concentration of the chemical. 

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Using a preliminary database consisting of the results of 10-d toxicity tests with marine 

amphipods, Field et al. (1999) derived logistic regression models for seven chemical 

substances to illustrate the methodology. More specifically, these investigators calculated 

T10, T50, and T90 values for four metals (lead, mercury, nickel and zinc), two PAHs 

(fluoranthene and phenanthrene), and total PCBs. These values represent the chemical 

concentrations that correspond to a 10%, 50%, and 90% probability of observing sediment 

toxicity. In addition to supporting the derivation of specific T-values, this method can be 

used to determine the concentration of a COPC that corresponds to any probability of 

observing toxicity. Therefore, a sediment manager can identify an acceptable probability of 

observing sediment toxicity at a site (e.g., 25%) and determine the corresponding chemical 

concentrations (e.g., T25 value). The calculated value can then be used as the SQG for the 

site. While the existing data from 10-d toxicity tests with marine amphipods (endpoint: 

survival) support the development of logistic models for 37 substances (Field et al. 2002), 

insufficient data are currently available to derive reliable logistic models for any freshwater 

invertebrate species or toxicity test endpoint (Crane et al. 2000). 

3.1.7 Consensus Approach 

In the CA, consensus-based SQGs are derived from the existing SQGs that have been 

established for the protection of sediment-dwelling organisms. Derivation of numerical 

SQGs using the CA involves a four-step process. In a first step, the SQGs that have been 

derived by various investigators for assessing the quality of freshwater sediments are 

collected and collated. Next, the SQGs obtained from all sources are evaluated to determine 

their applicability to the derivation of consensus-based SQGs. The selection criteria that are 

applied are intended to evaluate the transparency of the derivation methods, the degree to 

which the SQGs are effects-based, and the uniqueness of the SQGs. 

The effects-based SQGs that meet these selection criteria are then grouped to facilitate the 

derivation of consensus-based sediment effect concentrations (SECs; Swartz 1999). 

Specifically, the SQGs for the protection of sediment-dwelling organisms are grouped into 

two categories according to their original narrative intent, including threshold effect 

concentrations (TECs) and probable effect concentrations (PECs). The TECs are intended 

to identify COPC concentrations below which harmful effects on sediment-dwelling 

organisms are unlikely to be observed. Examples of TECs include threshold effect levels 

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(TELs; Smith et al. 1996; Ingersoll et al. 1996), effect range low values (ERLs; Long and 

Morgan 1991; Ingersoll et al. 1996), and lowest effect levels (LELs; Persaud et al. 1993). 

The PECs are intended to identify COPC concentrations above which harmful effects on 

sediment-dwelling organisms are likely to be frequently or always observed (MacDonald et 

al. 1996; Swartz 1999). Examples of PECs include probable effect levels (PELs; Smith et 

al. 1996; Ingersoll et al. 1996), effect range median values (ERMs; Long and Morgan 1991; 

Ingersoll et al. 1996); and severe effect levels (SELs; Persaud et al. 1993). 

Following classification of the existing SQGs, consensus-based TECs are calculated by 

determining the geometric mean of the SQGs that are included in this category. Likewise, 

consensus-based PECs are calculated by determining the geometric mean of the PEC-type 

values. The geometric mean, rather than the arithmetic mean, is calculated because it 

provides an estimate of central tendency that is not unduly affected by outliers and because 

the SQGs may not be normally distributed. Consensus-based TECs or PECs are calculated 

only if three or more published SQGs are available for a chemical substance or group of 

substances (MacDonald et al. 2000a). 

The CA has been used to derive numerical SQGs for a variety of chemical substances and 

media types. For example, Swartz (1999) derived consensus-based SQGs for PAHs in 

marine ecosystems. Using a similar approach, MacDonald et al. (2000b) derived SQGs for 

total PCBs in freshwater and marine sediments. Ingersoll and MacDonald (1999) and 

MacDonald et al. (2000a) developed consensus-based SQGs for metals, PAHs, PCBs, and 

several pesticides in freshwater sediments. As the term implies, consensus-based SECs are 

intended to reflect the agreement among the various SQGs by providing an estimate of their 

central tendency. Consensus-based SECs are, therefore, considered to provide a unifying 

synthesis of the existing SQGs, reflect causal rather than correlative effects, and account for 

the effects of contaminant mixtures in sediment (Swartz 1999; MacDonald et al. 2000a; 

MacDonald et al. 2000b). The predictive ability of the consensus-based SECs were 

evaluated byMacDonald et al. (2000a; 2000b; 2001), Kemble et al. (2000), USEPA (2000a), 

and Ingersoll et al. (2001). 

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3.1.8 Tissue Residue Approach 

The TRA (which is also known as the biota-water-sediment EqPA) for deriving numerical 

SQGs was developed to address concerns regarding the bioaccumulation of sedimentassociated COPCs in aquatic and aquatic-dependent food webs. The TRA is used to estimate 

the levels of individual chemicals or classes of chemicals in sediments that are unlikely to 

result in unacceptable tissue residues (i.e., levels in excess of the concentrations 

recommended to protect aquatic-dependent wildlife and/or human health; Cook et al. 1992). 

Derivation of numerical SQGs using the TRA involves several steps. As a first step, the 

COPCs for which SQGs are to be derived are selected based on their potential to accumulate 

in aquatic food webs (e.g., based on their Kow). Next, numerical tissue residue guidelines 

(TRGs) are identified for these COPCs. While most of the available TRGs are intended to 

provide protection for human health (e.g., Food and Drug Administration Action Levels; 

USEPA 1989), it is also important to obtain TRGs that are explicitly designed to protect 

piscivorous wildlife species. Following the selection of TRGs, sediment-to-biota 

bioaccumulation factors (BSAFs) are determined for each COPC. Such BSAFs can be 

determined from the results of bioaccumulation assessments, from matching sediment 

chemistry and tissue residue data (i.e., from the results of field studies), or from the results 

of bioaccumulation models. Numerical SQGs are subsequently derived using the equation 

(WDOH 1995): 

SQG = TRG ÷ BSAF 

Numerical SQGs can also be developed using information on the Kow of a substance and its 

corresponding bioaccumulation-based WQC (NYSDEC 1999). 

The applicability of the TRA is supported by data which demonstrate that declines in DDT 

residues in fish and birds (since its use was banned) are strongly correlated with declining 

concentrations of this substance in surficial sediments in the Great Lakes and Southern 

California Bight. This approach has been used in Lake Ontario to derive numerical SQGs 

for 2,3,7,8 tetrachlorodibenzo-p-dioxin on the basis of fish tissue residues (Endicott et al. 

1989; Cook et al. 1989). In addition, the New York State Department of Environmental 

Conservation has developed numerical SQGsforthe protection of wildlife and human health 

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using this approach (NYSDEC 1999). Human health-based SQGs have also been established 

in Washington State by the Washington State Department of Health (WDOH 1995; 1996). 

3.2 Recommended Strategy for Establishing Sediment Quality 

Assessment Guidelines for Florida Inland Waters 

A total of seven approaches to the derivation of numerical SQGs for the protection of 

sediment-dwelling organisms were described in the preceding sections of this chapter. Crane 

et al. (2000) evaluated these approaches and determined that each approach has certain 

strengths and limitations that influence their applicability for deriving numerical SQGs 

(Table 3.1). Based on the results of that review, it is apparent that no single approach can 

be used to establish numerical SQGs for all water uses. Therefore, it may be necessary to 

employ a strategy for establishing SQAGs for Florida coastal waters that involves the use of 

multiple approaches. 

3.2.1 Recommended Approach for Establishing Effects-Based 

Sediment Quality Assessment Guidelines 

To help guide the selection of an approach for deriving effects-based SQAGs for Florida 

coastal waters, MacDonald (1994) identified a number of criteria for evaluating individual 

approaches. At that time, the primary factors that needed to be considered in the selection 

of an approach for deriving SQAGs included practicality, cost-effectiveness, scientific 

defensibility, and broad applicability to assessments of sediment quality conditions. In the 

context of that evaluation, an approach was considered to be practical if it supported the 

development of numerical SQAGs and was feasible to implement in the near-term. Costeffectiveness was evaluated based on the estimated costs associated with implementation of 

the approach and the requirement for new data to support the approach. The scientific 

defensibility of each candidate approach was determined by evaluating its potential to: 

consider the bioavailability of COPCs; establish cause and effect relationships; incorporate 

biological effects data, especially from the southeast; and, apply to the classes of COPCs and 

chemical mixtures that occur in Florida. Amenability to field validation was also considered 

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to be a key factor for evaluating scientific defensibility. Finally, candidate approaches were 

considered to be broadly applicable if the resultant SQAGs could be used in the sediment 

quality assessment and management initiatives that are being conducted in the state. 

Although these selection criteria were established some time ago, they are still relevant for 

evaluating candidate approaches for deriving numerical SQAGs for Florida inland waters. 

Among the candidate approachesto the derivation of effects-based SQAGs, the SLCA isthe 

least amenable to application in Florida. One of the principal impediments to its application 

is the dearth of matching sediment chemistry and benthic invertebrate community structure 

data for freshwater ecosystems. Additionally, this approach does not consider the 

bioavailability of sediment-associated COPCs, cannot be used to establish dose-response 

relationships, and does not provide a weight of evidence for assessing sediment quality 

conditions (i.e., because it utilizes benthos data only; Table 3.2). Because benthic 

invertebrate community structure can be affected by factors other than the concentrations of 

sediment-associated COPCs, the SLCA is likely to be of little assistance in conducting 

ecological risk assessments or supporting regulatory decisions at contaminated sites. 

The ERA, ELA, and AETA are all empirically-based approaches that rely on analyses of 

matching sediment chemistry and biological effects data to support the derivation of 

numerical SQAGs. All three approaches scored highly in the evaluation (Table 3.2); 

however, all three were limited by their inability to define dose-response relationships and 

by the extent to which the existing guidelines derived using these approaches incorporate 

data from the southeast. The AETA was further limited because insufficient regional data 

are currently available to support the derivation of SQAGs. None of the three approaches 

fully account for the factors that can influence the bioavailability of sediment-associated 

COPCs. 

The EqPA scored highly for many of the selection criteria that were used to evaluate 

candidate approaches for deriving numerical SQAGs. In terms of practicality, costeffectiveness, and applicability, the EqPA was the highest rated approach (Table 3.2). 

However, this approach does not consider data from the southeast, does not yield SQGs for 

individual metals, does not provide a weight of evidence for assessing sediment quality 

conditions, does not consider the effects of mixtures of COPCs (with the exception of the 

E PAH model; Swartz et al. 1995), and the approach is not particularly amenable to field 

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validation (i.e., data from sites which contain complex mixtures of COPCs cannot be used 

to field validate the resultant SQAGs). 

Among the seven effects-based approaches that were evaluated, the LRMA had the second 

highest overall assessment score (Table 3.2). More specifically, the LRMA scored highly 

in the cost-effectiveness, scientific defensibility, and applicability categories. The principal 

limitation of this approach is that insufficient data are currently available to support the 

development of reliable logistic models for most COPCs in freshwater sediments (Crane et 

al. 2000). In addition, the approach does not support the development of dose-response 

relationships. Furthermore, insufficient data from the southeast are available to support the 

development of reliable regional logistic models. 

Of the approaches that were evaluated, the CA appears to be the most applicable for 

establishing effects-based SQAGs for Florida inland waters. Based on the results of the 

evaluation, the CA is both practical and cost-effective for deriving numerical SQAGs. While 

it does not consider the factors thought to influence the bioavailability of sediment-associated 

contaminants, the results of several investigations demonstrate that dry weight-normalized 

guidelines predict the presence and absence of sediment toxicity as well or better than 

guidelines that are normalized to TOC or account for binding of metals by AVS (Ingersoll 

et al. 1996; Long et al. 1998a). Although regional data were not used in the derivation of the 

guidelines, such data have been assembled to the extent possible to support an evaluation of 

the predictive ability of the guidelinesin freshwatersedimentsfrom the southeastern portion 

of the United States. Hence, the two principal limitations of the approach have been 

mitigated. Furthermore, the consensus-based SECs are considered to provide a unifying 

synthesis of the existing guidelines,reflect causal rather than correlative effects, and account 

for the effects of COPC mixtures (Swartz 1999; MacDonald et al. 2000a; 2000b; 2001). 

Therefore, the consensus-based SECs are likely to provide powerful tools for assessing 

sediment quality conditions in Florida inland waters and are recommended for establishing 

effects-based SQAGs. The results of the evaluation of the predictive ability of the SECs will 

provide a basis for identifying any refinements that are need to increase their applicability 

to the southeastern portion of the United States. 

Consensus-based guidelines are not available for all of the COPCs that occur in Florida 

inland waters (MacDonald 2000). Nevertheless, sediment quality assessors in the state 

require science-based tools to support the assessment and management of sediments that 

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have been contaminated by substances for which consensus-based guidelines are not 

available. For this reason, it is recommended that the guidelines from other jurisdictions be 

reviewed and evaluated to identify SQAGs that can be used on an interim basis in Florida. 

More specifically, it is recommended that the effects-based guidelines that are most 

consistent with the narrative intent of the SQAGs be adopted for use as interim SQAGs in 

Florida. 

3.2.2 Recommended Approach for Establishing BioaccumulationBased Sediment Quality Assessment Guidelines 

Sediment-associatedCOPCs have the potential to adversely affect wildlife speciesin several 

ways. First, certain wildlife species can be exposed directly to contaminated sediments 

through dermal contact (e.g., demersal fish species, such as catfish) or through ingestion 

(e.g., bottom-feeding fish species or birds that consume sediment-dwelling organisms), 

potentially resulting in direct toxicity. In addition, many wildlife species may be exposed 

to sediment-associated COPCs as a result of food web transfers and associated 

bioaccumulation. The accumulation of toxic substances in the tissues of these species can 

result in decreased growth, impaired reproduction, reduced survival, or other harmful effects. 

Finally, sediment-associated COPCs can be toxic to sediment-dwelling organisms and, in so 

doing, result in decreased abundance of food organisms. 

Bioaccumulation-based guidelines represent important tools for conducting sediment quality 

assessments for several reasons. First and foremost, unlike the effects-based SQAGs 

described in the previous section, the bioaccumulation-based guidelines explicitly consider 

the potential for bioaccumulation and effects on higher trophic levels in the food web. That 

is, the bioaccumulation-based guidelines provide a basisfor interpreting sediment chemistry 

data in terms of the potential for harmful effects on wildlife. Because there were a limited 

number of bioaccumulation-based guidelines and the methods for evaluating the reliability 

of these guidelines are not readily available, it is recommended that the existing guidelines 

for the protection of wildlife (NYSDEC 1999; MacDonald 1994) be adopted directly as 

interim bioaccumulation-based SQAGs for Florida inland waters (Table 5.2). Importantly, 

these interim SQAGs should be used in conjunction with tissue chemistry data and 

applicable tissue residue guidelines (TRGs; such as Newell et al. 1987; USEPA 1989) to 

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confirm that contaminated sediments pose a hazard to mammalian and/or avian wildlife 

species. 

Bioaccumulation-based SQAGs are also needed to evaluate the potential effects of 

contaminated sediments on human health. For the same reasons that were cited for the 

bioaccumulation-based guidelines for protecting aquatic-dependent wildlife, it is 

recommended that the existing guidelinesfor the protection of human health (e.g., NYSDEC 

1999; WDOH 1995; 1996) be adopted directly as interim SQAGs for Florida inland waters. 

For those substances for which guidelines are available from two or more jurisdictions, the 

lower of the applicable guidelines should be adopted as the interim SQAGs. These interim 

SQAGsshould be applied in conjunction with tissue residue data and applicable TRGs(e.g., 

USFDA Action Levels; USEPA 1989) to confirm that contaminated sediments are posing 

an unacceptable risk to human health. 

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EVALUATION OF THE PREDICTIVE ABILITY OF EFFECTS-BASED SQAGS – PAGE 32 

Chapter 4 Evaluation of the Predictive Ability of 

Effects-Based Sediment Quality Assessment 

Guidelines 

4.0 Introduction 

Effects-based SQAGs are required to support the assessment and management of 

contaminated sediments in Florida inland waters. The approaches recommended in 

Chapter 3 provide a basisfor cost-effectivelyestablishing such effects-based SQAGs. Based 

on the results of a preliminary evaluation, MacDonald et al. (2000a) concluded that the 

consensus-based sediment effect concentrations (SECs; which were derived using the 

approach recommended for establishing effects-based SQAGs for freshwater ecosystems in 

Florida) provide a reliable basis for assessing sediment quality conditions in freshwater 

ecosystems. Subsequently, USEPA (2000a) and Ingersoll et al. (2001) conducted a further 

evaluation of these assessment tools using a more robust database and concluded the 

consensus-based SECs can be used to accurately predict the presence and absence of 

sediment toxicity on both regional and national bases. The results of these evaluations 

suggest that the consensus-based SECs are likely to be applicable for assessing sediment 

quality conditions in Florida inland waters. 

Despite the results of the earlier evaluations, the relevance of these SQAGs for assessing 

sediment quality conditions in the southeast needs to be demonstrated to provide users with 

a high level of confidence in these tools. For this reason, the consensus-based SECs that 

were derived by MacDonald et al. (2000a) were further evaluated to determine their 

applicability in Florida and elsewhere in the southeastern portion of the United States. More 

specifically, the ability of the SQAGs to correctly predict the presence and absence of 

sediment toxicity, based on sediment chemistrydata alone, was evaluated (i.e., the predictive 

ability of the SQAGs). 

This chapter describes the strategy that was used to evaluate the predictive ability of the 

freshwater SQAGs. More specifically, this chapter describes the efforts that were made to 

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EVALUATION OF THE PREDICTIVE ABILITY OF EFFECTS-BASED SQAGS – PAGE 33 

acquire matching sediment chemistry and toxicity data from Florida and elsewhere in the 

southeastern portion of the United States. In addition, the methods that were used to review 

and evaluate each of the candidate data sets are described. Furthermore, the procedures that 

were used to compile the highest quality data sets into a regional sediment toxicity database 

are described. Finally, the methods that were used to evaluate the predictive ability of the 

SQAGs and the results of that evaluation are presented. 

4.1 Acquisition of Candidate Data Sets 

An extensive search of the scientific literature was conducted by the FDEP and MacDonald 

Environmental Sciences Ltd. (MESL) to acquire matching sediment chemistry and bioeffects 

data from the southeastern portion of the United States. In the context of this report, the 

southeast is considered to be comprised of the geographic area within USEPA Region IV 

(i.e., Florida, Georgia, Alabama, Mississippi, NorthCarolina, SouthCarolina, Kentucky and 

Tennessee). To support the predictive ability evaluation, an effort was made to acquire all 

of the relevant information on the concentrations of COPCs (i.e., trace metals, PCBs, PAHs, 

certain OC pesticides, such as chlordane and DDTs, and several other classes of organic 

COPCs,such as PCDDs and PCDFs)in sedimentsfrom the southeast and the associated data 

on the effects of those sediments to sediment-dwelling organisms (i.e., including the results 

ofsediment toxicitytests and benthic invertebrate community assessments). The process that 

was used to identify and acquire candidate data sets included: 

• Accessing the information contained in MESL’s database on the effects of 

sediment-sorbed COPCs on aquatic organisms (i.e., BEDS); 

• Conducting on-line searches of a number of bibliographic databases to obtain 

recently published articles from peer-reviewed journals; 

• Reviewing recent volumes of peer-reviewed journals that routinely publish 

papers on the effects ofsediment-associated COPCsto accessrecently published 

data (e.g., Chemosphere, Environmental Toxicology and Chemistry; Water, Air, 

and Soil Pollution; Archives of Environmental Contamination and Toxicology; 

Environmental Science and Technology; Ecotoxicology, etc.); and, 

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• Contacting various practitioners in the sediment quality assessment field, by 

either letter or phone, to obtain published and unpublished data sets relevant to 

this project. 

Although data acquisition efforts were initially focused exclusively on the southeast, early 

results indicated that it was unlikely that the required information would be obtained from 

USEPA Region IV alone. For this reason, the geographic scope of the target area was 

expanded to include USEPA Region III and VI. The second challenge that arose during the 

data acquisition process was the lack of consistency among benthic invertebrate community 

assessments (e.g., a variety of indices had been used to assess the status of benthic 

invertebrate communities). As such, it was difficult to identify sediment quality metrics 

relative to the benthic invertebrate community that could be applied consistently across a 

number of data sets. For this reason, data acquisition efforts were further focused on 

obtaining matching sediment chemistry and sediment toxicity data. By making these 

adjustments to the data acquisition strategy, it was possible to obtain sufficient data (i.e., >50 

samples for each toxicity test considered: e.g., 28- to 42-d survival or growth of amphipods) 

to support evaluation of the preliminary SQAGs (i.e., the consensus-based SECs). 

4.2 Review and Evaluation of Candidate Data Sets 

All data sets and associated documents retrieved during the course of this study were 

critically evaluated to determine their scientific and technical validity. To support this 

evaluation, a set of selection criteria were developed in cooperation with the Science 

Advisory Group on Sediment Quality Assessment (Appendix 2). These selection criteria 

provided a means of consistently evaluating methods used in each study, including 

procedures used to collect, handle, and transport sediment samples, protocols that were 

applied to conduct sediment toxicity tests, methods that were used to determine the 

concentrations of COPCs in sediments, and the statistical tests that were applied to the study 

results. In many cases, additional communications with investigators and/or professional 

judgement were needed to determine if the selection criteria had been satisfied. 

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4.3 Development of a Regional Sediment Toxicity Database 

The data setsthat met the selection criteria were incorporated into spreadsheets(in MS Excel 

format) or directly into the project database (in MS Access format), printed, and verified 

against the original data sources (i.e., number-for-number). Overall, application of these 

quality assurance procedures were intended to ensure that only high quality and fully verified 

data were incorporated into the project database. Additional quality assurance procedures 

were undertaken to verify that translation problems had not occurred when data were 

incorporated into the project database (i.e., roughly 10% of the data entries were compared 

to the original data sources). Finally, the project manager conducted a quality assurance 

review of the database. 

All matching sediment chemistry and toxicity data that met the screening criteria were 

incorporated into the project database on a per sample basis. Each record in the resultant 

database included the citation, a brief description of the study area (i.e., by waterbody and 

reach), a description of the sampling locations (including georeferencing data, if available), 

information on the toxicity tests that were conducted (including species tested, endpoint 

measured, test duration, etc.), type of material tested (i.e., whole sediment, pore water, or 

elutriate), the TOC concentrations (if reported), and the chemical concentrations (expressed 

on a dry weight basis). Other supporting data, such as SEM concentrations, AVS, particle 

size distributions, and water temperature, were also included in the individual data records, 

as available. 

Using the selection criteria identified in Appendix 2, a total of 38 freshwater data sets from 

USEPA Regions III, IV, and VI were incorporated into the regional database. The assembled 

database includes data on a large number of samples with a broad range of concentrations 

and many different bioassay endpoints. A list of the data sets that were incorporated into the 

project database, including geographic area sampled, number of samples, and bibliographic 

citation, is provided in Table 4.1. These data sets provided information on the toxicity of 

whole-sediment samples to the following species: the amphipod, Hyalella azteca or 

Leptocheirus plumulosus (endpoints: survival, growth, and reproduction); the midge, 

Chironomus tentans (endpoints: survival and growth); the cladocerans (i.e., water fleas), 

Daphnia magna or Ceriodaphnia dubia (endpoints: survival and reproduction); the clam, 

Corbicula fluminea (endpoint:survival);flathead minnow, Pimephales promelas (endpoint: 

survival); and the bacterium, Vibrio fisheri (Microtox; endpoint: bioluminescence). 

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Additionally, the results of pore-water toxicity tests on the following species were 

incorporated into the regional database: the amphipod, Hyalella azteca (endpoint:survival); 

the cladoceran, Daphnia magna (endpoint: survival); steelhead trout, Oncorhynchus mykiss 

(endpoint: survival); and the bacterium, Vibrio fisheri (endpoint: bioluminescence). 

Although matching sediment chemistry and toxicity data were available on various species 

and toxicity test endpoints, only a subset of these data were selected for evaluating the 

predictive ability of the preliminary SQAGs. More specifically, the results of the following 

toxicity tests were used in the predictive ability evaluation (Table 4.2): 

• 10-d whole-sediment toxicity tests with the amphipod, Hyalella azteca 

(endpoints: survival; and, survival or growth); 

• 28- to 42-d whole-sediment toxicity tests with the amphipod, Hyalella azteca 

(endpoints: survival; and, survival or growth); 

• 10-d whole-sediment toxicity tests with the midge, Chironomus tentans 

(endpoints: survival or growth); and, 

• Overall toxicity (i.e., the results of any of the above whole-sediment toxicity 

tests). 

These toxicity test results were selected for use in the evaluation of the preliminary SQAGs 

for several reasons. First, 10-d and 28- to 42-d tests with amphipods and 10-d tests with 

midges are standard toxicity tests, for which a large quantity of data are currently available 

nationally. As such, the results of tests conducted with sediment samples from Florida and 

elsewhere in the southeast can be readily compared to the results of tests conducted 

elsewhere in the United States. In this respect, the results of tests compiled in the regional 

database can be compared to the concentration (i.e., mean PEC-Q) - response (i.e., percent 

incidence of toxicity) relationships that were developed using a larger database (USEPA 

2000a; Ingersoll et al. 2001). Importantly, the results of these whole-sediment toxicity tests 

represent the most robust data sets in the regional database. Individual samples were 

designated as toxic or not toxic based on a statistically significant reduction in survival or 

growth relative to a control or reference sediment. 

To supportsubsequent interpretation of the sediment chemistry data, the total concentrations 

of several chemical classes were determined for each sediment sample. Specifically, the 

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concentrations of total PAHs were calculated by summing the concentrations of up to 13 

individual PAHs, including acenaphthene, acenaphthylene, anthracene, fluorene, 2-

methylnaphthalene, naphthalene, phenanthrene, benz[a]anthracene, dibenz[a,h]anthracene, 

benzo(a)pyrene, chrysene, fluoranthene, and pyrene. For PCBs, the concentrations of total 

PCBs were determined using various procedures, depending on how the data were reported 

in the original study. If only the concentrations of total PCBs was reported in the study, then 

those values were used directly. If the concentrations of various Aroclors (e.g., 

Aroclor 1242, Aroclor 1248) were reported, then the concentrations of the various Aroclors 

were summed to determine the concentration of total PCBs. When the concentrations of 

individual congeners were reported, these values were summed to determine total PCB 

concentrations. An evaluation conducted by the CCME (1999) indicated that all three 

procedures for estimating the concentration of tPCB yielded roughly equivalent results. For 

DDTs, the concentrations of p,p’-DDD and o,p’-DDD, p,p’-DDE and o,p’-DDE, and p,p’-

DDT and o,p’-DDT were summed to calculate the concentrations of sum DDD, sum DDE, 

and sum DDT, respectively. Total DDTs was calculated by summing the concentrations of 

sum DDD, sum DDE, and sum DDT. Finally, the concentrations of chlordane were 

determined by summing the concentrations of alpha- and gamma-chlordane isomers. If only 

the concentrations of total chlordane were reported in the study, then those values were used 

directly. In calculating the total concentrations of the various chemical classes, less than 

detection limit values were assigned a value of one-half of the detection, except when the 

detection limit was greater than the consensus-based PEC (or an alternate sediment quality 

guideline if a PEC was not available; MacDonald et al. 2000a). In this latter case, the less 

than detection limit value was not used in the calculation of the total concentration of the 

substance or in the calculation of mean PEC-Qs. 

4.4 Evaluation of the Effects-Based Sediment Quality 

Assessment Guidelines 

Based on the results ofthe evaluation presented inChapter 3, the consensus-based SECs(i.e., 

TECs and PECs) that were derived by MacDonald et al. (2000a) are recommended as 

preliminary SQAGs for Florida inland waters. The underlying guidelines that were used to 

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derive the consensus-based TECs and PECs are described in Table 4.3, and listed in Tables 

4.4 and 4.5, respectively (MacDonald et al. 2000a). 

Previous evaluations of numerical SQGs have typically focused on determining their 

reliability and predictive ability. The results of evaluations of reliability provide the 

information needed to determine if the SQAGs for individual substances are consistent with 

their stated narrative intent. For example, the consensus-based TECs are intended to define 

the concentrations of sediment-associated contaminants below which adverse effects on 

sediment-dwelling organisms are likely to occur only infrequently. By determining the 

incidence of toxicity (i.e., number of toxic samples divided by the total number of samples) 

in sediment samples in which the concentrations of the selected substance (e.g., cadmium) 

is below the TEC, it is possible to determine the reliability of the associated SQAG. 

MacDonald et al. (2000a; 2000b; 2001) applied these procedures to evaluate the reliability 

of the consensus-based TECs and PECs for freshwater ecosystems and concluded that the 

SECs for most chemicals provided a reliable basis for classifying sediment samples as toxic 

and not toxic (Tables 4.6, 4.7, and 4.8; MacDonald et al. 2000a). The matching sediment 

chemistry and toxicity data that were used in this evaluation were largely independent of the 

underlying guidelines that were used to develop the SECs [i.e., a portion of the data used to 

evaluate predictive ability had been used to derive the TELs/PELs and TEL-Hyalella azteca 

(HAs)/PEL-HAs; however, none of these data had been used to derive the lowest effects 

level/severe effects level (LELs/SELs), moderate effects threshold/toxic effects threshold 

(METs/TETs), ERLs/ERMs, or sediment quality advisory levels (SQALs); Table 4.3]. 

While the SECs for the individual chemical substances provide reliable tools for assessing 

sediment quality conditions (MacDonald et al. 2000a), the predictive ability of these SQGs 

should be enhanced when the SQAGs are used together in assessments of sediment quality 

(i.e., because in-place sediments usually contain complete mixtures of COPCs; MacDonald 

et al. 2000a). In addition, it would be helpful to consider the magnitude of the exceedances 

of the SQAGs in such assessments. In response to the need for enhanced assessment tools, 

Long et al. (1998b) developed a procedure for evaluating the biological significance of 

COPC mixtures in marine and estuarine sediments through the application of mean SQAGquotients(SQAG-Qs; which were calculated asthe arithmeticmean ofthe SQAG-Q that was 

calculated for each measured substance, where SQAG-Q = concentration of a substance 

divided by the SQAG for that substance). Subsequently, USEPA (2000a) and Ingersoll et 

al. (2001) evaluated 11 difference procedures for calculated mean SQAG-Qs and concluded 

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that the “Mean-MPP (or)” procedure for calculating mean PEC-Qs yielded the most robust 

(i.e., included the largest number of samples) and reliable (i.e., concordance between 

sediment chemistry and toxicity) results for freshwater sediments. Therefore, the analyses 

of the predictive ability were conducted for mean PEC-Qs that were calculated using the 

“Mean-MPP (or)” procedure (USEPA 2000a; Ingersoll et al. (2001). Using this procedure, 

mean PEC-Qs were determined for each sediment sample in the database by calculating the 

arithmetic mean of the mean PEC-Q for metals, the PEC-Q for total PAHs, and/or the PECQ for total PCBs. 

4.5 Predictive Ability of the Effects-Based Sediment Quality 

Assessment Guidelines 

In this evaluation, the predictive ability of the preliminary SQAGs was evaluated in two 

ways. First, the incidence of sediment toxicity within relevant ranges of mean PEC-Qs was 

calculated using the information contained in the regional database and compared to the 

incidence of biological effects that was observed for sediments collected at sites located 

throughout the United States (Table 4.9; USEPA 2000a and Ingersoll et al. 2001). More 

specifically, the incidence of toxicity for each of the selected toxicity tests was determined 

for the following categories of mean PEC-Qs: <0.1, 0.1 to <0.5, 0.5 to <1.0, 1.0 to <5.0, 

>1.0, and >5.0. These ranges are the same as those used in the USEPA (2000a) evaluation 

of the predictive ability of the consensus-based PECs. The regional data were considered to 

be consistent with the national data if the incidence of toxicity within ranges of mean PECQs was within 10% of that determined for the national database. 

The predictive ability of the preliminary SQAGs was also evaluated by deriving 

concentration-response relationships from the information contained in the regional database. 

More specifically, the relationship between mean PEC-Qs (concentration) and incidence of 

toxicity (response) was evaluated by fitting logistic regression models to summarized data 

for each toxicity test endpoint (i.e., using SigmaPlot 2000, Version 6.00). More specifically, 

the underlying sediment chemistry and toxicity data were sorted by increasing mean PEC-Q 

and compiled in groups of 10 to 50 samples, depending on the number of samples available 

for each endpoint (i.e., to yield a minimum of 10 groups of samples). For each group of 

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samples, which are termed concentration intervals, the geometric mean of the mean PEC-Q 

and the incidence of toxicity were calculated. These summarized data were then plotted and 

used to generate the logistic regression models for each toxicity test endpoint. The 

correlation coefficient(r2

) and level ofsignificance (p) were then determined for each model. 

Subsequently, the regional concentration-response relationships were compared to the 

concentration-response curves generated by USEPA (2000a) using the results of 10- to 14-d 

toxicity tests with Hyalella azteca, 28- to 42-d toxicity tests with Hyalella azteca, and 10-

to 14-d toxicity tests with Chironomus spp. The regional data were considered to be 

consistent with the national data if the regional dose-response curve generally fell within the 

95% prediction limitsforthe relationship that was generated using the information contained 

in the national database. 

The results of this evaluation of predictive ability indicate that the preliminary SQAGs are 

likely to provide a reliable basis for assessing effects on sediment-dwelling organisms in 

Florida and elsewhere in the southeast portion of the United States. For the 10-d wholesediment toxicity tests with Hyalella azteca (n=522 samples), the incidence of sediment 

toxicity (i.e., as measured using data on amphipod survival or amphipod survival or growth; 

Table 4.10) increased consistently and markedly with increasing COPC concentrations (i.e., 

as indicated by mean PEC-Qs). At mean PEC-Qs of <0.1, the incidence of acute toxicity 

(i.e., survival or growth) to amphipods was low (i.e., 13%; n=116). The incidence of 

sediment toxicity increased to 18% (n=385) at mean PEC-Qs of 0.1 to 1.0. Higher mean 

PEC-Qs were associated with a higher incidence of acute toxicity to amphipods (i.e., 48% 

for mean PEC-Qs of >1.0, n=21; and, 100% for mean PEC-Qs of >5.0, n=3). By 

comparison, the incidence of acute toxicity to amphipods (i.e., based on the results of 10- to 

14-d whole-sediment toxicity tests with Hyalella azteca) in the national database was 18% 

for mean PEC-Qs of <0.1 (n=147), 20% for mean PEC-Qs of 0.1 to <1.0 (n=361), 54% for 

mean PEC-Qs of >1.0 (n=162), and 71% for mean PEC-Qs of >5.0 (n=70; USEPA 2000a). 

Hence, the incidence of acute toxicity to amphipods in the regional and national databases 

generally agreed within 10% within the various concentration intervals (i.e., for 5 of 6 

concentration intervals; Tables 4.9 and 4.10). Importantly, the concentration-response curve 

generated using the matching sediment chemistry and toxicity data from the regional 

database fell within the 95% prediction limits for the dose-response relationship that was 

generated using the information contained in the national database (Figures 4.1 and 4.2). 

Therefore, it is concluded that systematic differences between the regional and national 

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databases are not apparent when data on the acute toxicity of freshwater sediments to 

amphipods is evaluated. 

A substantial quantity of data from 28- to 42-d whole-sediment toxicity tests with the 

amphipod, Hyalella azteca, are available to evaluate the predictive ability of the preliminary 

SQAGs (n = 174 samples). Considering either survival or growth, the incidence of chronic 

sediment toxicity was low (i.e., 13%; n=53) at low mean PEC-Qs (i.e., <0.1; Table 4.10). 

The incidence of chronic toxicity was higher (i.e., 30%; n=110) at mean PEC-Qs of 0.1 to 

<1.0. Amphipod survival or growth was significantly reduced in 45% of the sediment 

samples with mean PEC-Qs of >1.0 (n=11). By comparison, the incidence of chronic 

toxicity to amphipods in the national database was 10% (n=63), 30% (n=66), and 97% 

(n=31) at mean PEC-Qs of <0.1, 0.1 to 1.0, and >1.0, respectively (Table 4.9). These results, 

combined with the concentration-response curves for survival and survival or growth of 

amphipods (Figures 4.3 and 4.4), suggest that there may be differences between the regional 

and national data sets. Specifically, amphipod survival appears to be reduced at lower levels 

of contamination in sediments from the southeast than is the case for sediments from 

elsewhere in the United States (Figure 4.3; Table 4.11). However, when survival or growth 

is considered, the reverse may be true, particularly at elevated mean PEC-Qs (i.e., >1.0; 

Figure 4.4). Therefore, it is not unreasonable to conclude that the differences between the 

national and regional concentration-response relationships are minor when chronic toxicity 

to amphipods is considered. 

The results of acute toxicity tests (i.e., 10-d) with midges were also used to evaluate the 

predictive ability of the preliminary SQAGs. The results of this evaluation indicated that the 

incidence of toxicity (i.e., survival or growth) to midges was relatively low (i.e., 23%; n=26) 

in sediments with mean PEC-Qs of <0.1 (Table 4.10). At mean PEC-Qs of 0.1 to 1.0, the 

incidence of sediment toxicity decreased to 11% (n=103). The incidence of toxicity was 

higher (i.e., 75%; n=4) in sediments with mean PEC-Qs of >1.0. By comparison, the 

incidence of acute toxicity to midges(i.e., based on the results of 10- to 14-d whole-sediment 

toxicity tests with the survival and growth endpoints) in the national database was 20% for 

mean PEC-Qs of <0.1 (n=121), 21% for mean PEC-Qs of 0.1 to <1.0 (n=376), and 52% for 

mean PEC-Qs of >1.0 (n=132; USEPA 2000a). Hence, the incidence of toxicity to midges 

in the regional and national databases generally agreed within 10% for the three 

concentration intervals, with the largest differences observed for the highest concentration 

interval (Table 4.10). The incidence of acute toxicity was not well correlated with COPC 

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concentrations (as indicated by mean PEC-Qs) in the regional database, as evidenced by the 

lower correlation coefficient (r2 = 0.42; p=0.07) compared to the national database (r2 = 0.56; 

p=<0.0001; Table 4.11; Figure 4.5). Therefore, it would be difficult to conclude that 

systematic differences in the toxicity of freshwater sediments to midges exist between the 

regional and national databases. 

Overall toxicity can be evaluated by considering the results of the selected toxicity tests 

conducted on a sediment sample. In this analysis, sediment samples found to be toxic in one 

or more of the toxicity tests were designated as toxic for overall toxicity. Using this 

designation, 18% (n=150) of the sediment samples with mean PEC-Qs of <0.1 were toxic 

to one or more of the organisms tested and endpoints measured (Table 4.10). By 

comparison, the incidence of sediment toxicity was 21% (n=467) in the samples with mean 

PEC-Qs of 0.1 to <1.0. The incidence of toxicity was higher in sediment samples in which 

the mean PEC-Q was >1.0 (i.e., 42%; n=26) and >5.0 (75%; n=4). As such, the overall 

toxicity of sediment samples generally increases with increasing levels of sediment 

contamination (as indicated by mean PEC-Qs). 

In summary, the available data on the toxicity of sediment samples from Florida and 

elsewhere in the southeast portion of the United States indicate that the preliminary SQAGs 

can be used to accurately classify sediment samples as toxic and not toxic using sediment 

chemistry data alone. Because systematic differences were not observed in the toxicity of 

regionally-collected or nationally-collected sediment samples to amphipods or midges, it is 

reasonable to conclude that the concentration-response relationships that were developed 

using the national database apply to Florida. Based on those nationally-derived 

concentration-response relationships, the probability of observing chronic toxicity to 

amphipods is 50% at a mean PEC-Q of 0.63 (USEPA 2000a). Because sediment-dwelling 

organisms are likely to be exposed to contaminated sediments for extended periods of time 

(i.e., >28-d), benthic invertebrate communities are likely to be adversely affected when 

exposed to sediments in which the chronic toxicity threshold is exceeded. Therefore, it is 

likely that adverse effects on sediment-dwelling organisms would occur frequently in 

sediments from Florida inland waters when this level of sediment contamination (i.e., mean 

PEC-Q of 0.63) is exceeded. In contrast, the probability of observing chronic toxicity is low 

(i.e., <10%) at mean PEC-Qs of <0.1. Sediment-dwelling organisms would be provided with 

a high level of protection in sediments with these chemical characteristics. 

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Chapter 5 Recommended Sediment Quality Assessment 

Guidelines for Florida Inland Waters 

5.0 Introduction 

Through theWaterResource Management Program, FDEP hasthe primary responsibility for 

protecting the quality of Florida’s rivers, lakes, and wetlands. To support water management 

initiatives within the state, FDEP has identified designated water uses, promulgated 

numerical water quality standards to protect those uses, and established an antidegradation 

policy to protect high quality waters. Such water quality standards provide an effective basis 

for managing water quality conditions in Florida. 

In addition to water qualitystandards, integratedmanagement of aquatic ecosystemsrequires 

a basis for assessing and managing aquatic-dependant resources, including sediment quality 

condition. For this reason, FDEP has identified SQAGs as an important tool for assessing 

the quality of aquatic habitats. This chapter presents the SQAGs that are recommended for 

assessing sediment quality conditions in Florida inland waters. The SQAGs describe the 

conditions that need to be maintained to ensure that sediment-dwelling organisms, aquaticdependent wildlife, or human health are not adversely affected by the presence of toxic 

and/or bioaccumulative substances in sediments. Numerical SQAGs have been 

recommended for COPCs when sufficient information was available to do so. Because it 

was not possible to recommend numerical SQAGs for many of the COPCs in Florida inland 

waters (see Chapter 2), narrative SQAGs have also been recommended to support 

assessments of sediment quality conditions. 

5.1 Narrative Sediment Quality Assessment Guidelines 

Although it is desirable to establish numerical SQAGs for all of the COPCs that occur or are 

likely to occur in Florida inland waters, recommendation of such SQAGs is limited by the 

availability of guidelines from other jurisdictions and/or by the availability of suitable 

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toxicological information for certain substances. For this reason, it is necessary to 

recommend narrative SQAGs that can be used to assess sediment quality conditions within 

the state. In addition, procedures for evaluating compliance with the narrative SQAGs are 

needed. 

5.1.1 Toxic Substances 

A number of toxic substances have been identified as COPCs in Florida inland waters. For 

many of these substances, sufficient toxicological data exist to recommend numerical 

SQAGs (see Section 5.2.1). However, limitations on the availability of information preclude 

the derivation of numerical SQAGs for other COPCs. For this reason, the following 

narrative SQAG is recommended to support the assessment of sediment quality conditions 

in the state: 

Toxic substances should not occur in shoreline or bottom sediments, either singly or 

in combination, at concentrations that adversely affect, or can reasonably be 

expected to adversely affect, biological resources (i.e., sediment-dwelling organisms, 

fish, amphibians, and reptiles). 

In the context of this report, an adverse effect on a biological resource is considered to have 

occurred if one or more of the following adverse changes in viability have been observed, 

or are likely to occur, in response to exposure to one or more COPCs: death, disease, 

behavior abnormalities, cancer, genetic mutations, physiological malformations, or physical 

deformities (USDOI 1996). 

Compliance with the above narrative SQAG cannot be measured directly. For this reason, 

it is necessary to establish a number of indicators of sediment quality conditions. The 

following are recommended as the primary indicators for assessing adverse effects on 

sediment dwelling organisms: sediment chemistry and sediment toxicity (MacDonald et al. 

2002a). Secondary indicators of sediment quality conditions include benthic invertebrate 

community structure, tissue chemistry, and physical habitat characteristics. Relative to 

sediment chemistry, the recommended numerical SQAGs presented in Section 5.2.1 identify 

the concentrations of COPCs that are unlikely to cause or substantially contribute to sediment 

toxicity (i.e., TECs) and those that are sufficient to cause or substantially contribute to 

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sediment toxicity (i.e., PECs). The chemical mixture model (i.e., as expressed in terms of 

mean PEC-Qs) provides a means of estimating the probability of observing chronic toxicity 

to amphipods in sediments with various chemical characteristics. 

In addition to applying sediment chemistry data, compliance with the narrative SQAG can 

also be evaluated using sediment toxicity data. In this context, the 28-d whole-sediment 

toxicity tests with the amphipod, Hyalella azteca (endpoints: survival and growth) is 

recommended as the primary basis for assessing compliance with the narrative SQAG 

relative to sediment-dwelling organisms. Using this test, sediments are considered to be 

toxic to sediment-dwelling organisms if the measured response of the test organisms exposed 

to sediments from an assessment area is significantly different from the response that is 

observed in an appropriately selected control or reference sediment (ASTM 2001a; Ingersoll 

et al. 2002). 

5.1.2 Bioaccumulative Substances 

In addition to causing toxicity to sediment-dwelling organisms, many of the COPCs in 

Florida can accumulate in the tissues of aquatic organisms and, in so doing, pose a hazard 

to aquatic-dependent wildlife and/or human health. While numerical SQAGs have been 

recommended for a number of these substances (see Section 5.2.2), such SQAGs are not 

available for several other bioaccumulative COPCs. For this reason, the following narrative 

SQAG isrecommended to support the assessment ofsediment quality conditionsin the state: 

Bioaccumulative substances should not occur in shoreline or bottom sediments, 

either singly or in combination, at concentrations that adversely affect, or can 

reasonably be expected to adversely affect, aquatic-dependent wildlife or human 

health. 

In the context of this report, adverse effects on aquatic-dependent wildlife and/or human 

health are considered to have occurred if one or more of the following adverse changes in 

viability have been observed, or are likely to occur, in response to exposure to one or more 

COPCs: death, disease, behavior abnormalities, cancer, genetic mutations, physiological 

malformations, or physical deformities (USDOI 1996). Issuance of fish consumption 

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advisories is also considered to represent an adverse effect on human health (i.e., an 

impairment of the beneficial uses of the aquatic ecosystem). 

Compliance with the above narrative SQAG cannot be measured directly. For this reason, 

it is necessary to establish a number of indicators of injury to biological resources. The 

following indicators are recommended for assessing injury to sediment dwelling organisms: 

sediment chemistry and tissue chemistry (MacDonald et al. 2002b). With respect to 

sediment chemistry, the recommended numerical SQAGs presented in Section 5.2.2 identify 

the concentrations of COPCs in sediments that are sufficient to cause or substantially 

contribute to adverse effects on aquatic-dependent wildlife and human health. 

While sediment chemistry data provide relevant information for assessing the potential for 

bioaccumulation of sediment-associated contaminants in the tissues of aquatic organisms, 

confirmation of risks to aquatic-dependent wildlife and human health necessitates the 

collection of tissue residue data. More specifically, compliance with the narrative SQAG 

should be evaluated by comparing the levels of bioaccumulative COPCs in the tissues of 

aquatic organisms to numerical TRGs for the protection of piscivorus wildlife (Newell et al. 

1987) and/or for the protection of human health (e.g., Food and Drug Administration action 

levels and tolerance levels; USEPA 1989). 

5.2 Numerical Sediment Quality Assessment Guidelines 

The narrative statements presented in Section 5.1 describe the level of protection that FDEP 

intends to afford ecological and human receptors through the application of SQAGs. While 

such narrative SQAGs clearly define the use protection goals for freshwater ecosystems in 

Florida, numerical SQAGs are also needed to support sediment management initiatives in 

the state. 

5.2.1 Effects-Based Sediment Quality Assessment Guidelines 

In accordance with the recommended approach (Section 3.2), the consensus-basedTECs and 

PECs were identified as preliminary SQAGs for Florida inland waters. In total, preliminary 

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effects-based SQAGs were recommended for 29 COPCs in the state (MacDonald et al. 

2000a). The results of the reliability evaluations indicate that the consensus-based TECs and 

PECs can be used to establish reliable, effects-based SQAGs for Florida inland waters. More 

specifically, the TECs identify the concentrations of sediment-associated COPCs below 

which adverse effects on sediment-dwelling organisms are unlikely to occur (i.e., false 

negative rates are typically < 25% using the TECs; i.e., incorrectly identifying sediment 

samples as not toxic when they are actually toxic to one or more species; MacDonald et al. 

2000a). In addition, the PECs identify the concentrations of sediment-associated COPCs 

above which adverse effects on sediment-dwelling organisms are likely to occur (i.e., false 

positive rates are typically < 25% using the PECs; i.e., incorrectly identifying sediment 

samples as toxic when they are actually not toxic; MacDonald et al. 2000a). A lower 

incidence of toxicity was reported at concentrations above the PEC for heptachlor epoxide, 

while no data were available for evaluating the reliability of the PEC for endrin. Because the 

preliminary SQAGs provide a reliable basis to classifying sediments as toxic to sedimentdwelling organisms, they are recommended as effects-based SQAGs for assessing sediment 

quality conditions in Florida. The TEC-type and PEC-type guidelines from other 

jurisdictions that are recommended as interim SQAGs are also included in Table 5.1. 

While the preliminary effects-based SQAGs for individual COPCs provide reliable tools for 

assessing sediment quality conditions, predictive ability is enhanced when the SQAGs are 

used together to assess sediment quality conditions. USEPA (2000a) recommended the use 

of mean PEC-Qs to facilitate the assessment of sediments with mixtures of COPCs (i.e., 

metals, PCBs, and/or PAHs). Based on the results of the USEPA (2000a) evaluation, the 

probability of observing sediment toxicity is 10% and 50% at mean PEC-Qs of 0.12 and 

0.63, respectively. The results of the predictive ability evaluation conducted in this study 

indicated that the relationships between concentration (i.e., mean PEC-Qs) and response (i.e., 

incidence of toxicity) generated using the national database and the regional database are 

similar (i.e., the logistic regression curve for the regional database largely falls within the 

95% prediction limits for the national database). 

The results of the predictive ability evaluations indicate that the chemical mixture models 

that utilize the consensus-based PECs can be used to accurately assess the presence and 

absence of sediment toxicity in Florida inland waters and elsewhere in the southeast. In 

sediments that contain mixtures of contaminants, mean PEC-Qs of 0.12 and 0.63 are 

recommended as SQAGs for assessing sediments with mixtures of COPCs. The probability 

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of observing chronic toxicity to sediment-dwelling organisms (i.e., the amphipod, Hyalella 

azteca) is <10% below a mean PEC-Q of 0.12 and >50% above a mean PEC-Q of 0.63. 

5.2.2 Bioaccumulation-Based Sediment Quality Assessment 

Guidelines 

The bioaccumulation-based SQGs that were derived by New York State Department of 

Environmental Conservation (NYSDEC 1999) are recommended as interim 

bioaccumulation-based SQAGsfor the protection of aquatic-dependent wildlife (Table 5.2). 

As insufficient data are available to evaluate the reliability of these SQAGs in Florida or 

elsewhere in the southeastern portion of the United States, it is recommended that collection 

ofthe requisite data to evaluate the bioaccumulation-based SQAGs be identified as a priority. 

The types of information that would support such an evaluation include the results of 

standard 28-d bioaccumulation tests with the oligochaete, Lumbriculus variegatus (i.e., 

ASTM 2001b), matching sediment chemistry and tissues residue data for field-collected 

sediments and infaunal invertebrate species, and relevant bioaccumulation/food web models 

(i.e., to estimate the transfer of COPCs to aquatic-dependent wildlife). 

The bioaccumulation-based SQGs that were derived by New York State Department of 

Environmental Conservation (NYSDEC 1999) and the Washington State Department of 

Health (WDOH 1995; 1996) are recommended as interim bioaccumulation-based SQAGs 

for the protection of human health (Table 5.2). For each bioaccumulative COPC, the lower 

of the guidelines reported by these two jurisdictions was selected as the interim SQAG for 

the protection of human health. 

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Chapter 6 Applications of the Numerical Sediment 

Quality Assessment Guidelines 

6.0 Introduction 

In Florida, there are a variety of environmental programs and program activities that 

necessitate the collection and interpretation of information on sediment quality conditions. 

The numerical SQAGs that were recommended in Chapter 5 of this report are likely to 

support many ofthese activities by providing a basisforinterpreting sediment chemistry data 

relative to the potential for observing adverse effects on sediment-dwelling organisms, 

aquatic-dependent wildlife, and/or human health. This chapter provides an overview of the 

potential uses of effects-based and bioaccumulation-based SQAGs in a variety of program 

applications in Florida. More specifically, the following sections of this report briefly 

discuss how the SQAGs can be used in: 

• Monitoring and assessment initiatives; 

• Assessment and management of contaminated sites; 

• Restoration of wetland habitats; 

• Assessment of ecological risks; and, 

• Environmental regulation programs. 

Although the potential uses of SQAGs are explicitly described, it is important to note that 

the SQAGs should be used along with other sediment quality assessment tools, such as the 

Florida metals interpretative tool (Carvalho and Schropp 2002) and sediment toxicity tests 

(ASTM 2001a; USEPA 2000b), within an integrated framework to support decisions 

regarding the management of contaminated sediments. Such a framework for assessing 

contaminated sedimentsis provided in the companion documentsto thisreport (MacDonald 

and Ingersoll 2002a; 2002b; Ingersoll and MacDonald 2002). 

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6.1 Monitoring and Assessment Initiatives 

Ambient environmental monitoring represents an essential element of virtually all programs 

that are focused on the assessment and management of environmental conditions. Without 

the data that are generated in such monitoring programs, the information needed to support 

environmental management decisions would be unavailable. Some of the specific 

applications of the SQAGs in monitoring and assessment initiatives in Florida include: 

supporting the design of monitoring programs; interpreting the results of monitoring 

programs; identifying COPCs and areas of concern; and, evaluating sediment quality 

conditions in stormwater ponds. 

6.1.1 Designing Environmental Monitoring Programs 

Monitoring is an integral component of environmental surveillance programs. While such 

programs may be undertaken for a number of reasons (e.g., trend assessment, impact 

assessment, compliance monitoring, etc.), limitations on available resources dictate that they 

must be conducted in an effective and efficient manner. For this reason, it is important for 

sediment quality monitoring programs to be well-focused and to provide the type of 

information that is necessary to manage contaminated sediments. 

The numerical SQAGs contribute to the design of environmental monitoring programs in 

several ways. First, comparison of existing sediment chemistry data to the SQAGs provides 

a systematic basis for identifying high priority areas for implementing monitoring activities. 

Second, when used in conjunction with existing sediment chemistry data, the SQAGs may 

be utilized to identify COPCs within an area of concern. By considering the potential 

sources of these substances, it may be possible to further identify priority sites for 

investigation. The SQAGs can also assist in monitoring program design by establishing 

target detection limits for each substance (e.g., <0.5 x TEC; MacDonald and Ingersoll 

2002b). Determination of the detection limits that are needed to support further 

interpretations of sediment chemistry data should help to avoid many of the difficulties that 

have resulted from the use of standard, yet inappropriate, analytical methods. 

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6.1.2 Interpreting Environmental Monitoring Data 

Ambient monitoring of freshwater ecosystems in Florida is primarily focused on the 

assessment of water quality conditions. However, it is likely that sediment quality 

monitoring activities will intensify in the future. Numerical SQAGs are likely to support 

ambient monitoring initiatives by assisting in identification of issues and concerns relative 

to sediment quality conditions, the design of sampling programs, and interpretation of the 

resultant data. 

The numerical SQAGs provide consistent tools for evaluating spatial patterns in chemical 

contamination. More specifically, the SQAGs can be used to compare and rank sediment 

quality conditions among sites located within an area of concern (Long and MacDonald 

1998). If a stratified random sampling design is used in the monitoring program, then the 

SQAGs provide a basis for calculating the spatial extent of potentially toxic sediments. In 

the areas of greatest concern, further investigations would typically be implemented to 

explicitly identify the sources of COPCs, assess the areal extent and severity of sediment 

toxicity, evaluate the potential for bioaccumulation, and/or determine the need for source 

control measures or other remedial measures. The SQAGs can also be used to evaluate the 

success of any regulatory actions that are implemented at the site (Macfarlane and 

MacDonald 2002). 

While previous guidance has cautioned against using the SQAGs as stand alone decisionmaking tools, the results of recent evaluations of reliability and predictive ability 

substantially increase the level of confidence that can be placed in the SQAGs. In the 

national database, for example, there is a low probability (i.e., 8%) of observing sediment 

toxicity in sediments with mean PEC-Qs below 0.1 (i.e., based on the results of 28-to 42-day 

toxicity tests with amphipods; USEPA 2000a). In contrast, the probability of observing 

sediment toxicity is relatively higher at mean PEC-Qs of 0.5 to 1.0 (56%) and >1.0 (97%; 

USEPA 2000a). Therefore, the PECs can also be used directly to support certain sediment 

management decisions (e.g., to implement source control measures, to conduct sediment 

remediation, etc.). These tools are particularly efficient for evaluating sediment quality 

conditions at relatively small sites, where the costs of further investigations could approach 

or exceed the costs ofimplementing the remedial measures (MacDonald and Ingersoll 2002a; 

2002b; Ingersoll and MacDonald 2002). 

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6.1.3 Identifying Chemicals of Potential Concern 

As previously discussed, many substances that are present at only trace levels in water can 

accumulate to elevated levels in sediments. The effects-based and bioaccumulation-based 

SQAGs provide a basis for identifying the substances that occur in sediments at 

concentrations that pose a potential hazard to sediment-dwelling organisms, aquaticdependent wildlife, and/or human health. More specifically, the numerical SQAGs can be 

used to identify, rank, and prioritize COPCs in freshwater sediments. In this application, the 

concentration of each chemical substance can be compared to the corresponding SQAG. 

Those substances that occur at concentrations below the TECs should be considered to be 

of low priority relative to the potential for effects on sediment-dwelling organisms. Those 

substances that occur at concentrations above the TEC but below the PEC should be 

considered to be of moderate concern, while those that are present at concentrationsin excess 

of the PECs should be considered to be of relatively high concern (Long and MacDonald 

1998). 

The relative priority that should be assigned to each chemical can be determined by 

evaluating the magnitude and frequency of exceedance of the SQAGs. Chemicals that 

frequently exceed the PECs and/or those that exceed the PECs by a large margin should be 

viewed as the chemicals of greatest concern (Long and MacDonald 1998). In conducting 

such assessments, it is also important to remember that certain chemicals can be present in 

relatively unavailable forms (such as slag, paint chips, tar, etc.). Therefore, it is not a 100% 

certainty that samples with chemical concentrations in excess of the PECs will actually be 

toxic to sediment-dwelling organisms. Additionally, the reliability of the SQAGs should be 

considered when conducting evaluations of chemicals of concern, with the greatest weight 

assigned to those SQAGs which have been shown to be highly or moderately reliable 

(MacDonald et al. 2000a; Ingersoll et al. 1996; 2001) 

The degree of confidence that can be placed in determinations of COPCs can be increased 

by collecting ancillary sediment quality information. Specifically, data on regional 

background concentrations of sediment-associated COPCs (e.g., metals) can be used to 

identify substances of relatively low concern with respect to anthropogenic activities (i.e., 

those that occur at or below background levels). In Florida, an interpretive tool has been 

developed for assessing metal enrichment in freshwater sediments (Carvalho and Schropp 

2002). Using this tool, the metals that exceed the SQAGs and the upper limit of background 

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conditions (i.e., 95% prediction limit) should be considered to be the highest priority for 

further investigations. Data from toxicity tests can also be used to support the identification 

of COPCs. In particular, matching sediment chemistry and sediment toxicity data provide 

a basis for evaluating the degree of concordance between the concentrations of specific 

COPCs and measured adverse effects (i.e., using correlation analyses and regression plots; 

Carr et al. 1996). Those substances that are present at elevated concentrations (i.e., as 

indicated by exceedances ofthe PECs)in toxic samplesshould be identified asthe chemicals 

of greatest concern (Long and MacDonald 1998). Those chemicals that are not positively 

correlated to the results of the toxicity tests should be viewed as relatively lower priority. 

For bioaccumulative substances, the SQAGs also provide an important basis for identifying 

COPCs. In this case, the results of laboratory bioaccumulation tests (e.g., using the 

oligochaete, Lumbriculus variegatus) and/or tissue residue analyses conducted on fieldcollected samples of benthic organisms can be used to validate that bioaccumulative COPCs 

are present in bioavailable forms. 

6.1.4 Identifying Areas of Concern 

The numerical SQAGs can be used to identify areas of potential concern with respect to the 

potential for observing adverse biological effects. In this application, the concentrations of 

sediment-associated COPCs should be compared to the corresponding SQAGs. Sediments 

in which none of the measured chemical concentrations exceed the TECs should be 

considered to have the lowest potential for adversely affecting sediment-dwelling organisms 

and could be considered as reference areas (Long and Wilson 1997). However, the potential 

for unmeasured substances to be present at levels of toxicological concern can not be 

dismissed without evaluating detailed information on land and water uses within the water 

body or the results of toxicity tests. Those sediments which have concentrations of one of 

more COPCs between the TECs and PECs should be considered to be of moderate priority, 

while those sediments with COPC concentrations in excess of one or more PECs should be 

considered to be of relatively high concern (Long and MacDonald 1998). Once again, the 

magnitude and frequency of exceedances of the PECs provide a basis for assigned relative 

priority to areas of concern with respect to contaminated sediments. The bioaccumulationbased SQAGs can also be used in this way to help identify areas of potential concern. 

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Sediment chemistry and associated data from sediment coring and profiling studies can be 

used to determine the timing and progression of sediment contamination within a site. The 

metalsinterpretive tool(Carvalho and Schropp 2002)islikely to be particularly useful in this 

application because it provides a means of identifying sediments in which metals have been 

enriched as a result of human activities. Data from such studies can also be used to identify 

natural background levels. In turn, the SQAGs can be used to determine the levels of 

sediment-associated contaminants that pose a potential hazard to ecological receptors. 

6.1.5 Identifying Sources of Chemicals of Potential Concern 

In addition to assessing status and trends in sediment quality conditions, environmental 

monitoring programs can provide important information for identifying sources of COPCs. 

In this context, the SQAGs can be used to identify areasin which sediment quality conditions 

have degraded to such a point that contaminated sediments pose hazards to sedimentdwelling organisms, aquatic-dependent wildlife, and/or human health. By applying overlay 

mapping techniques, it is possible to identify the sources of COPCs that are most likely 

affecting sediment qualityconditions. In addition, the significance of atmospheric deposition 

ofCOPCs can be evaluated byapplying the metalsinterpretive tools and the SQAGstogether 

to identify areas (i.e., that are not influenced by point sources or other non-point sources of 

COPCs) in which anthropogenic enrichment has occurred and sediment quality conditions 

pose a potential hazard to ecological receptors or human health. 

6.1.6 Supporting Watershed Assessments 

In Florida, watershed assessments are conducted periodically to evaluate the status and trends 

of freshwater ecosystems. Such assessments, which are conducted in five year cycles, are 

currently focused on evaluating water quality conditions (i.e., primarily conventional 

variables, bacteriological characteristics conditions, and nutrient levels) in groundwater, 

streams, and lakes in the state, as well as the status of various biological indicators of 

ecosystem health. In the future, the scope of such assessments could be expanded to include 

evaluations of sediment quality conditions. Numerical SQAGs are likely to support such 

assessments by providing a basis for assessing the potential for contaminated sediments to 

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be adversely affecting sediment-dwelling organisms, aquatic-dependent wildlife, and/or 

human health. 

6.1.7 Evaluating Stormwater Ponds 

Stormwater ponds represent important elements of the overall water management program 

in Florida. These facilities support water quality management initiatives by collecting 

stormwater during precipitation events and promoting the settling of suspended sediments. 

In this way, stormwater ponds reduce loadings of COPCs to surface waters from non-point 

sources. However, such ponds tend to fill-in as sediments and other materials are deposited 

in the ponds. The numerical SQAGs can support assessments of stormwater ponds by 

providing effects-based and bioaccumulation-based tools for evaluating the hazards posed 

by contaminated sediments to sediment-dwelling organisms, aquatic-dependent wildlife, 

and/or human health. In addition, the SQAGs can be used in the selection of disposal options 

for materials that are removed from such ponds. 

6.2 Assessment and Management of Contaminated Sites 

Historic land and water use activities have resulted in releases of toxic and/or 

bioaccumulative substances at a number of sites in the state. In some cases, the nature, 

magnitude, and extent of such releases have resulted in significant contamination of 

environmental media, including water, sediment, and biota. At such sites, it is often 

necessary to evaluate hazards posed by contaminated sediments to ecological receptors 

and/or human health. The results of such assessments provide a basis for evaluating the 

various options for managing these sites. Some of the specific activities that are conducted 

to assess and manage contaminated sites in Florida are briefly described in the following 

sections. 

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6.2.1 Undertaking Enforcement Actions and Clean-ups 

In Florida, sediment quality assessment tools are needed to support a variety of enforcement 

actions and clean-ups at contaminated sites. Such actions may be initiated by the Hazardous 

Waste Sections of County governments, the FDEP’s Bureau of Waste Clean-up (as 

coordinated through FDEP’s district offices), or by natural resource trustees (i.e., FDEP, 

NOAA, USFWS). In such actions, the numerical SQAGs are needed to determine if 

sediments are contaminated, to identify COPCs, to assess the areal extent of contamination, 

and to support the establishment of target clean-up levels (i.e., sediment quality remediation 

objectives; sediment quality remediation objectives; SQROs). 

Sediment quality remediation objectives represent an essential component of the 

contaminated sediment remediation process because they establish target clean-up levels for 

a site. Sediment quality issues are rarely entirely the responsibility of one agency or one 

level of government. For this reason, it may be necessary to establish agreements between 

various levels of government to define their respective responsibilities with respect to the 

prevention, assessment, and remediation of sediment contamination. Multi-jurisdictional 

agreements may include accords on a number of issues; however, establishment of sitespecific SQROs is important because they provide a common yardstick against which the 

success of a range of sediment management initiatives can be measured. 

Numerical SQAGs can be used in several ways to support the derivation of SQROs. 

Specifically, SQAGs are useful because they provide a means of establishing SQROs that 

fulfill the narrative use protection or use restoration goals for the site. For example, SQROs 

could be set at the TECs and/or mean PEC-Q of 0.1 if the site management goal is to provide 

a high level of protection for sediment-dwelling organisms. Alternatively, the SQROs could 

be set at the PECs or a mean PEC-Q of 0.6 if the immediate goal for the site is to reduce the 

potential for acute toxicity and permit natural recovery processes to further reduce COPC 

concentrations and associated risks to ecological receptors. In addition, the SQAGs and 

associated evaluations of predictive ability provide information that may be used to evaluate 

the costs and benefits associated with various remediation options. 

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6.2.2 Reclaiming Phosphate Mines 

In both northern and central Florida, phosphate mining has affected large tracts of land. In 

recent years, substantial effort has been directed at the development and implementation of 

strategies for reclaiming affected lands following the completion of mining activities. 

Because phosphate-bearing rock contains a number of metals (i.e., at levels that are elevated 

relative to other soils in Florida), there is a potential for wetlands that are constructed as part 

of mine reclamation initiatives to be contaminated by metals. The numerical SQAGs can be 

used to evaluate the significance ofsediment-associated metals and establishing target cleanup levels at phosphate mines, should remedial measures be required. 

6.3 Restoration of Wetland Habitats 

In Florida, wetland habitats represent an essential components of freshwater ecosystems. 

Wetlands provide a number of ecological services in the state. For example, wetlands 

perform a number of functions which contribute to the enhancement of the quality of water 

and provide "safety" functions (e.g., flood control) which have substantial economic value. 

Wetland habitats support numerous wildlife species (such as fish, birds, and mammals) by 

providing food sources, protective cover, and habitats for reproduction. Wetlands also 

support recreational and aesthetic water uses, and in so doing generate a range of economic 

benefits for the state. Because wetland restoration initiatives provide a basis for restoring 

these beneficial water uses, a number of state programs rely of the restoration of wetland 

habitats to achieve their long-term environmental management objectives. Some of the 

potential uses of the SQAGs in wetland restoration activities are described in the following 

sections. 

6.3.1 Restoring Agricultural Land 

In recent years, restoration of agricultural lands has been initiated at a number of locations 

in the state. Such restoration projects commonly involve the flooding of agricultural land to 

restore native wetland habitats. In this application, the SQAGs can be used to determine if 

adverse effects on sediment-dwelling organisms are likely to occur after the land has been 

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flooded. In addition, bioaccumulation-based SQAGs can be used to assess the potential for 

effects on wildlife and/or human health that could occur after reclamation activities have 

been completed. As such, the SQAGs support assessments of the costs and benefits of 

candidate agricultural land restoration projects. 

6.3.2 Assessing State Liability 

In Florida, private lands are periodically purchased to support a number of state program 

objectives, such as habitat protection and habitat restoration. Some of these private lands 

have been contaminated as a result of variousland use activities(e.g., agricultural operations, 

industrial activities, land filling, etc.). In this application, the numerical SQAGs can be used 

to identify the presence of contaminated sediments and, in so doing, assist in the assessment 

of the state’s potential liability (i.e., clean-up costs) if the lands are purchased. 

6.3.3 Restoring the Everglades 

Restoring water flows has been a central component of the Everglades restoration initiative. 

In certain locations, however, successful restoration of aquatic habitats will also necessitate 

restoration of sediment quality conditions (e.g., in agricultural areas in which historic 

pesticide use may be a concern). In this case, the numerical SQAGs can be used to identify 

contaminated sediments. In addition, the SQAGs can be used to establish restoration 

objectives in terms of sediment quality conditions. 

6.4 Assessment of Risks to Ecological Receptors 

Risk assessment is the process of assigning magnitudes and probabilities to the adverse 

effects that may be associated with environmental contamination or other hazards. 

Ecological risk assessment (ERA) is an evolving process that is designed to provide sciencebased guidance for managing environmental quality, particularly at contaminated sites. Until 

recently, appropriate scientific information was not available for assessing the ecological 

risks that were associated with contaminated sediments. However, a panel of environmental 

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chemists and toxicologists recently concluded that there is sufficient certainty associated with 

SQAGs to recommend their use in ecological risk assessments (Ingersoll et al. 1997). 

The numerical SQAGs can contribute directly to several stages of the ecological risk 

assessment process, including problem formulation, effects assessment, and risk 

characterization. During problem formulation, background information and preliminary 

sampling data are used to identify the problem and define issues that need to be addressed 

at sediment contaminated sites (Chapman et al. 1997). At the problem formulation stage, 

SQAGs can be used in conjunction with existing sediment chemistry data to identify the 

COPCs and areas of concern with respect to sediment contamination (Long and MacDonald 

1998; MacDonald et al. 2001). In turn, this information can be used to scope out the nature 

and extent of the problem and to identify probable sources of sediment contamination at the 

site. In addition, the SQAGs provide a consistent basis for identifying appropriate reference 

areas that can be used in subsequent assessments of the sediment contaminated site (Menzie 

1997). Furthermore, the underlying data used to derive the SQAGs provide a scientific basis 

for identifying appropriate assessment endpoints (i.e., receptors and ecosystem functions to 

be protected) and measurement endpoints (i.e., metrics for the assessment endpoints) that can 

be used at subsequent stages of the assessment. 

Numerical SQAGs represent effective tools that can be used to assess the effects of 

sediment-associated contaminants (i.e., during the effects assessment of the ERA). The goal 

of the effects assessment is to provide information on the toxicity or other effects that are 

likely to occur as a result of the sediment contamination. In this application, the SQAGs and 

associated chemical mixture models provide an effective basis for describing how sediment 

toxicity is likely to change with changing COPC concentrations (MacDonald et al. 1996; 

Ingersoll et al. 1996; MacDonald et al. 2000a; Ingersoll et al. 2001). The applicability of the 

SQAGs in effects assessments is increased when used in conjunction with other tools that 

facilitate determinations of background concentrations of contaminants, sediment toxicity, 

bioaccumulation, and effects on in situ benthic macroinvertebrates (Chapman et al. 1997). 

The primary purpose of the risk characterization stage of an ERA is to estimate the nature 

and extent of the risks associated with exposure to contaminated sediment and to evaluate 

the level of uncertainty associated with that estimate (Chapman et al. 1997). The SQAGs 

are particularly useful at this stage of the process because they provide a quantitative basis 

for evaluating the potential for observing adverse effects associated with exposure to 

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contaminated sediments, for determining the spatial extent of unacceptable levels of 

sediment contamination (i.e., sediments that exceed prescribed limits of risk to sedimentdwelling organisms), and for estimating the uncertainty in the risk determinations (i.e., the 

potential for Type I and Type II errors). Importantly, calculation of the frequency of 

exceedance of the PECs and mean PEC-Qs for individual sediment samples enables risk 

assessors to estimate the probability that contaminated sediments will be toxic to sedimentdwelling organisms (Long and MacDonald 1998; USEPA 2000a; Ingersoll et al. 2001). 

These procedures facilitate determination of the cumulative effects of COPCs arising from 

multiple sources(i.e., in addition to the contaminated site) and evaluation of the potential for 

off-site impacts when appropriate sediment chemistry data are available. The uncertainty 

associated with the application of the SQAGs at this stage of the ERA can be effectively 

reduced by using the SQAGs in conjunction with other assessment tools, such as results of 

toxicity tests and/or benthic invertebrate community assessments. 

6.5 Environmental Regulation 

In Florida, asin other jurisdictions, decisionsregarding the management of natural resources 

are intended to assure their long-term sustainability and to optimize the benefits that accrue 

to the residents of the state. Achieving these goals is dependent on development and 

implementation of environmental regulations that effectively manage human activities that 

have the potential to adversely affect aquatic resources. While regulations are in place to 

regulate the discharge of industrial and municipal effluents and the disposal of solid wastes, 

hazardous wastes, and dredged materials, such regulations are not necessarily protective of 

sediment quality conditions (i.e., they are usually focused on protecting water quality 

conditions). Some potential uses of the SQAGs in these environmental regulation processes 

are described in the following sections. 

6.5.1 Evaluating Dredged Materials 

A variety of dredge and fill activities are undertaken in the state to support the beneficial uses 

of Florida inland waters (e.g., navigational dredging, beach nourishment). Such activities 

are typically authorized under FDEP’s Environmental Resource Permitting Program. 

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PROGRAM APPLICATIONS OF THE NUMERICAL SQAGS – PAGE 61 

Although the inland testing manual provides explicit guidance on the assessment of dredged 

materials for open water disposal (USEPA and USACE 1998), the numerical SQAGs 

complement this guidance by providing relevant tools to support such tiered assessments. 

In this application, the numerical SQAGs can be used to determine if dredged materials are 

likely to be toxic to sediment-dwelling organisms and, hence, support the evaluation of 

various disposal options. More specifically, these tools can be used to identify dredged 

materials that require special handling and careful disposal. Conversely, the numerical 

SQAGs and the metals interpretive tool can be used to identify sediments that are unlikely 

to pose significant hazards to aquatic organisms and, hence, could be used for a variety of 

beneficial uses (e.g., beach nourishment, etc.). 

6.5.2 Evaluating Solid Wastes 

There are a variety of solids wastes (e.g., sewage sludge, wood wastes, composted materials, 

and other debris) that require evaluation prior to selecting appropriate disposal or re-use 

options. However, the SQAGs recommended in this report are intended to apply directly to 

aqueous sediments. As such, their application for assessing other materials is uncertain. 

Therefore, the SQAGs should be used with caution in these types of applications. 

6.5.3 Evaluating Total Maximum Daily Loadings 

Under direction from USEPA, FDEP is now required to conduct total maximum daily 

loading (TMDL) assessments for all water bodies in the state. For each substance of 

concern, a TMDL must be determined that specifies the total amount of the substance that 

can be discharged into a water body from all sources without adversely affecting designated 

uses. As contaminated sediments can adversely affect the designated uses of surface waters, 

sediment contamination must be considered in the development of TMDLs. Desorption from 

sediments also represents a potential source of certain COPCs to overlying waters, which 

must be considered in the TMDL calculations. The numerical SQAGs can be used to help 

identifythe locations where beneficial uses are not beingmaintained due to the accumulation 

of COPCs in sediments. In addition, the SQAGs could be used to assist in the establishment 

of TMDLs for these water bodies. 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
PROGRAM APPLICATIONS OF THE NUMERICAL SQAGS – PAGE 62 

6.5.4 Evaluating National Pollutant Discharge Elimination 

System Permits 

In Florida, the discharge of water and wastewater to receiving water systems is authorized 

byFDEP through the issuance of permits under the National Pollutant Discharge Elimination 

System (NPDES). Historically, the discharge limits for various COPCs that are specified in 

such permits have been established using ambient water quality criteria, in conjunction with 

other related information. The water quality criteria identify the concentrations of waterborne COPCs that should not be exceeded in receiving waters, post-mixing, to protect the 

designated uses of the water body. In this application, the numerical SQAGs can be used to 

determine if sediments have been contaminated as a result of permitted discharges (and/or 

other inputs of contaminants). In this way, it may be possible to evaluate the efficacy of 

NPDES permits in terms of protecting the uses of receiving water systems. 

6.5.5 Assessing the Effects of Aquatic Weed Control Programs 

Proliferation of aquatic weeds is a serious problem in many water bodies in Florida. 

Frequently, copper-based compounds are applied to these systems to control such nuisance 

organisms. The numerical SQAGs can be used, in conjunction with ambient monitoring 

data, to identify the herbicide application rates that are likely to result in acceptable or 

problematic levels of copper in freshwater sediments. This information could then be 

utilized to refine aquatic weed control strategies in the state. 

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SUMMARY AND RECOMMENDATIONS – PAGE 63 

Chapter 7 Summary and Recommendations 

7.0 Introduction 

In response to the need for guidance on the assessment of sediment quality conditions in 

freshwater ecosystems, FDEP and its partners launched the Freshwater Sediment Quality 

Assessment Initiative in early 2000. This initiative, which is being implemented 

cooperatively by FDEP, USGS, USEPA, county governments, and water management 

districts (see Acknowledgments for a list of cooperators), consists of three main elements, 

including: 

• Formulation of an integrated framework for planning, designing, implementing, 

and interpreting the results of sediment quality investigations; 

• Development of an interpretive tool for assessing metal enrichment in freshwater 

sediments; and, 

• Establishment of numerical SQAGs for assessing the potential for adverse 

biological effects associated with exposure to contaminated sediments. 

Together, these three elements of the overall Freshwater Sediment Quality Assessment 

Initiative are intended to provide FDEP staff and others with the guidance needed to conduct 

sediment quality assessment, and to support defensible sediment management decisions. 

This report, which addresses the third element of the initiative, describes the development 

and evaluation of numerical SQAGs that are intended to support assessments of sediment 

quality conditions in Florida inland waters. This chapter of the report provides a summary 

of the results of the project and offers a series of recommendationsto support the assessment 

and management of contaminated sediments in the state. 

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SUMMARY AND RECOMMENDATIONS – PAGE 64 

7.1 Summary 

The third element of the Freshwater Sediment Quality Assessment Initiative involves the 

development and evaluation of numerical SQAGs for Florida inland waters, including 

effects-based SQAGs and bioaccumulation-based SQAGs. The effects-based SQAGs are 

intended to provide a basis for determining the concentrations of sediment-associated COPCs 

that are unlikely to be associated with adverse biological effects and those that are likely to 

be associated with sediment toxicity or other adverse effects on sediment-dwelling 

organisms. By comparison, the bioaccumulation-based SQAGs are intended to identify the 

concentrations ofsediment-associatedCOPCsthat are unlikelyto be associated with adverse 

effects on aquatic-dependent wildlife or human health. 

To support the identification ofinterests and needsrelated to the assessment of contaminated 

sedimentsin Florida inland waters, FDEP convened a workshop in 2000 (MacDonald 2000). 

Based on input provided by workshop participants, the potential for adverse effects on 

sediment-dwelling organisms, aquatic-dependent wildlife, and human health represents the 

principal concern relative to contaminated sediments. In addition to identifying sediment 

quality issues and concerns, workshop participants also identified the toxic and 

bioaccumulative COPCs for which numerical SQAGs are required to support sediment 

quality assessments in the state. Metals, PAHs, PCBs, chlorinated benzenes, phthalates, 

triazine herbicides, organophosphate pesticides, OC pesticides, and toxaphene were 

identified as the highest priority toxic substances that partition into sediments. The 

bioaccumulative substances of greatest concern included mercury, PAHs, PCBs, chlorinated 

benzenes, PCDDs and PCDFs, and OC pesticides. 

A total of eight distinct approaches were reviewed and evaluated to support the establishment 

of numerical SQAGs for Florida inland waters. Both empirical and theoretical approaches 

were considered to support the derivation of numerical SQAGs for the protection of 

sediment-dwelling organisms, including SLCA,ERA,ELA,AETA,EqPA,LRMA, andCA. 

Based on the results of this evaluation, it was recommended that guidelines developed using 

theCA (i.e., theTECs and PECs) be adopted as preliminaryeffects-based SQAGsfor Florida 

inland waters (MacDonald et al. 2000a). For those substances for which consensus-based 

guidelines were not available, it was recommended that guidelines derived using other 

effects-based approaches be evaluated to select SQAGs that could be used on an interim 

basis in Florida. The TRA was considered to be the most relevant method for deriving 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
SUMMARY AND RECOMMENDATIONS – PAGE 65 

numerical SQAGs for the protection of wildlife and human health (i.e., for substances that 

bioaccumulate in the food web). 

The evaluations that have been conducted to date demonstrate that the consensus-based 

guidelines provide reliable and predictive tools for assessing sediment quality conditions 

(MacDonald et al. 2000a; Crane et al. 2000; USEPA 2000a; Ingersoll et al. 2001). While 

these results generate a high level of confidence in the consensus-based guidelines, a further 

evaluation of the predictive ability of these guidelines was conducted to assess their 

relevance in the southeastern portion of the United States. To support this evaluation, 

matching sediment chemistry and sediment toxicity data were assembled from diverse 

studies conducted throughout USEPA Regions III, IV, and VI. For each of the samples 

represented in the project database, mean PEC-Qs were calculated. Subsequently, the 

incidence of toxicity (i.e., to amphipods, Hyalella azteca, and midges, Chironomus tentans 

and Chironomus riparius) within ranges of mean PEC-Qs was calculated and compared to 

the results obtained using the information contained in the national database (USEPA 

2000a). Additionally, concentration-response relationships were developed using the 

regional database and compared to the relationships developed for the same test organisms 

and endpoints using the data contained in the national database. The results of these 

evaluationsshowed thatsystematic differences in the toxicity of sediment-associated COPCs 

(as expressed using mean PEC-Qs) do not exist between the regional and national data sets. 

Therefore, it was concluded that consensus-based guidelines are likely to represent relevant 

tools for assessing sediment quality conditions in Florida and should be adopted as the 

effects-based SQAGs. 

Together, the effects-based and bioaccumulation-based SQAGs describe the conditions that 

need to be maintained in freshwater ecosystems to protect sediment-dwelling organisms, 

aquatic-dependent wildlife, and human health against the adverse effects associated with 

exposure to contaminated sediments. Using the recommended approach, effects-based 

SQAGs were recommended for a total of 29 COPCs in Florida inland waters. Interim 

SQAGs were recommended for another 20 COPCs, based on the effects-based guidelines 

that have been promulgated in other jurisdictions. Bioaccumulation-based SQAGs for the 

protection of aquatic-dependent wildlife were recommended for 11 COPCs, while SQAGs 

for the protection of human health were recommended for 52 COPCs in the state. Because 

it was not possible to establish SQAGs for all of the COPCs that were identified by 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
SUMMARY AND RECOMMENDATIONS – PAGE 66 

workshop participants, narrative SQAGs were also recommended to support assessments of 

sediment quality conditions. 

The numerical SQAGs are intended to provide science-based tools for assessing sediment 

quality conditions in Florida’s freshwater ecosystems. To assist potential users of these 

tools, the recommended applications of the SQAGs were also described in this report. In 

total, five principal program applications were identified for the SQAGs, including: 

supporting monitoring and assessment initiatives; assessing and managing contaminated 

sites; restoring wetland habitats; assessing ecological risks; and, supporting environmental 

regulation programs. Although the potential uses of the SQAGs were explicitly described, 

it is important to note that the SQAGs should be used together with other assessment tools 

to support comprehensive assessments of sediment quality conditions. MacDonald and 

Ingersoll(2002a; 2002b) and Ingersoll and MacDonald (2002) describe the ecosystem-based 

framework for designing, conducting, and interpreting the results of sediment quality 

investigations. 

7.2 Recommendations 

This report was prepared to provide background information on the assessment of 

contaminated sediments, to describe the recommended approach to the establishment of 

numerical SQAGs, to evaluate the predictive ability of the SQAGs, and to present the 

recommended effects-based and bioaccumulation-based SQAGs for assessing sediment 

quality conditions in freshwater ecosystems. Additionally, a summary of the recommended 

program applications of the SQAGs was provided in this report. The following 

recommendations are offered to identify the strategic actionsthatshould be taken to improve 

the assessment and management of contaminated sediments in Florida inland waters. 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
SUMMARY AND RECOMMENDATIONS – PAGE 67 

7.2.1 Refinement of the Tools for Assessing Sediment Quality 

Conditions 

The Freshwater Sediment Quality Assessment Initiative was undertaken to develop tools 

to support assessments of sediment quality conditions in freshwater ecosystems. In response 

to the need for science-based assessment tools, FDEP developed an interpretive tool for 

assessing metal enrichment in Florida freshwater sediments (Carvalho and Schropp 2002). 

In addition, effects-based and bioaccumulation-based SQAGs have been developed to 

support evaluations of the potential for effects on sediment-dwelling organisms, aquaticdependent wildlife, and human health associated with exposure to contaminated sediments 

(this report). While these tools are likely to meet the state’s immediate requirements, further 

development of such tools is recommended to ensure that FDEP and its partners can meet 

emerging challenges associated with the assessment and management of contaminated 

sediments. More specifically, the following activities are recommended: 

• Develop SQAGs for the protection of sediment-dwelling organisms for those 

substances for which neither consensus-based guidelines nor guidelines from 

other jurisdictions are currently available; 

• Refine the chemical mixture model (i.e., mean PEC-Qs) such that it better 

incorporates the substances of greatest concern in Florida inland waters; 

• Evaluate the extent to which the effects-based SQAGs provide the desired level 

of protection for in situ benthic macroinvertebrate communities; 

• Develop bioaccumulation-based SQAGs for the protection of aquatic-dependent 

wildlife forthose substancesfor which guidelinesfromotherjurisdictions are not 

currently available; 

• Develop bioaccumulation-based SQAGs for the protection of human health for 

those substances for which guidelines from other jurisdictions are not currently 

available; and, 

• Conduct an evaluation of the reliability of the bioaccumulation-based SQAGs in 

Florida and elsewhere in the southeastern portion of the United States. 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
SUMMARY AND RECOMMENDATIONS – PAGE 68 

7.2.2 Evaluation of the Ecosystem-Based Framework for 

Assessing and Managing Sediment Quality Conditions 

In response to the need for guidance on the assessment and management of contaminated 

sediments, FDEP developed an integrated framework for assessing sediment quality 

conditions in Florida inland waters. The three volume guidance manual provides an 

ecosystem-based framework for assessing and managing contaminated sediments, detailed 

guidance on the design and implementation of sediment quality investigations, and advice 

on the interpretation of the results of sediment quality investigations (MacDonald and 

Ingersoll 2002a; 2002b; Ingersoll and MacDonald 2002). Although the guidance manual was 

designed tomeet the needsthat were identified byworkshop participants(MacDonald 2000), 

it would be helpful to have users identify any refinements needed to better enable them to 

address their program requirements. Therefore, it is recommended that the guidance manual 

be broadly distributed to potential users within the state. The recipients should be asked to 

review and evaluate the guidance manual relative to their needs and identify any refinements 

that would increase its applicability. 

7.2.3 Improvement of Monitoring and Assessment Initiatives 

Participants at the workshop that was convened in 2000 developed a number of 

recommendations that would improve the monitoring and assessment of sediment quality 

conditions in the state (MacDonald 2000). As these recommendations were not addressed 

in the first three elements of the Freshwater Sediment Quality Assessment Initiative, the 

recommendations that were offered by workshop participants are reproduced here to make 

sure that they are considered in the next phase of the initiative: 

• Identify potential sources of existing sediment quality data; 

• Compile the existing data on sediment quality conditions on a watershed by 

watershed basis and evaluate the resultant data using appropriate assessment 

tools; 

• Develop an understanding of the importance of the microbial community to 

ecological health and the fate of sediment-associated COPCs; 

• Document the levels of metals in phosphate rock and phosphatic sediments; and, 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
SUMMARY AND RECOMMENDATIONS – PAGE 69 

• Evaluate sediment quality conditions in areas where fish consumption advisories 

(e.g., due to mercury contamination) have been issued to determine if there are 

sediment-related issues that need to be addressed. 

7.2.4 Development of Strategies for Managing Contaminated 

Sediments 

Sediment management initiatives are currently being conducted under a number of federal, 

state, county, and local government programs in Florida. Participants at the interests and 

needs workshop that was convened in 2000 identified several high priority activities that 

should be undertaken to support the management of contaminated sediments, including 

remedial action planning (MacDonald 2000). These recommendations are reproduced here 

to ensure that they are considered in the next phase of the initiative: 

• Conduct a review of disposal options for contaminated sediments (including 

those that contain metals and organic contaminants), focusing on lessons learned 

in other jurisdictions; 

• Develop a strategy for disposing of contaminated sediments from stormwater 

ponds; and, 

• Investigate the possibility of establishing sediment quality standards for the state. 

7.2.5 Development of Outreach and Partnership Building 

Programs 

In the southeastern portion of the United States, there are a relatively large number of 

initiatives that are directed at the assessment and management of contaminated sediments. 

Development of a regional strategy for assessing and managing contaminated sediments is 

likely to increase the effectiveness of government programs and encourage greater support 

for sediment management initiatives (i.e., to coordinate the various initiatives). Some of the 

specific recommendations for outreach and partnership building that were offered by 

participants at the interests and needs workshop (MacDonald 2000) include: 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
SUMMARY AND RECOMMENDATIONS – PAGE 70 

• Develop partnerships with other organizations that are actively involved in the 

assessment and management of contaminated sediments, including the U.S. 

ArmyCorps of Engineers, water management districts, county governments, and 

other natural resource trustees; 

• Highlight key sediment-related issues to help people understand them and to 

increase their priority relative to other environmental management issues; 

• Explore the potential for securing funding under Section 319 of the CWA to 

conduct a statewide assessment of sediment quality conditions; 

• Evaluate the potential for conducting monitoring programs under Section 305b 

of the CWA and encourage USEPA to get more involved in this area; 

• Encourage other USEPA Region IV states to cooperate in the refinement of 

frameworks and tools for assessing sediment quality conditions; and, 

• Report the progress that is being made on sediment-related initiatives to senior 

management in FDEP on a regular basis. 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
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DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
Tables
Table 3.1. Summary of the strengths and limitations of existing approaches for deriving numerical sediment quality 

assessment guidelines (adapted from Crane et al. 2000). 

Approach Strengths Limitations 

Screening Level * Based on biological effects data. * Not possible to establish cause and effect relationships. 

Concentration Approach * Sufficient data to derive SQGs are generally available for * Large database of matching sediment chemistry and benthic 

many chemicals. data is required. 

* Suitable for all classes of chemicals and most types of * Chemistry and benthic data are rarely strictly matching (i.e., 

sediments. generated from splits of a homogenized sediment sample). 

* Accounts for the effects of mixtures of contaminants. * Bioavailability is not considered. 

Effects Range Approach * Based on biological effects data. * Large database of matching sediment chemistry and 

* Many types of biological effects data are considered. biological effects data is required. 

* Suitable for all classes of chemicals and most types * Not possible to establish cause and effect relationships. 

of sediments. * Bioavailability is not considered. 

* Provides a weight of evidence. * Does not consider the potential for bioaccumulation. 

* Provides data summaries for evaluating sediment quality. 

* Accounts for the effects of mixtures of contaminants. 

Effects Level Approach * Based on biological effects data. * Large database of matching sediment chemistry and 

* Many types of biological effects data are considered. biological effects data is required. 

* Suitable for all classes of chemicals and most types * Not possible to establish cause and effect relationships. 

of sediments. * Bioavailability is not considered. 

* Provides a weight of evidence. * Does not consider the potential for bioaccumulation. 

* Provides data summaries for evaluating sediment quality. 

* Accounts for the effects of mixtures of contaminants. 

82 
Table 3.1. Summary of the strengths and limitations of existing approaches for deriving numerical sediment quality 

assessment guidelines (adapted from Crane et al. 2000). 

Approach Strengths Limitations 

Apparent Effects * Based on biological effects data. * Extensive site-specific database is required. 

Threshold Approach * Several types of biological effects data are considered. * Not possible to establish cause and effect relationships. 

* Considers effects on benthic invertebrate community * Risk of under-protection of resource. 

structure. * Bioavailability is not considered. 

* Suitable for all classes of chemicals and most types * Does not consider the potential for bioaccumulation. 

of sediments. 

* Accounts for the effects of mixtures of contaminants 

Equilibrium Partitioning * Based on biological effects. * Water quality criteria are not available for certain 

Approach * Suitable for many classes of chemicals and most types of * In situ sediments are rarely at equilibrium. 

sediments. * Further field validation is needed. 

* Bioavailability is considered. * Guidelines for single chemicals do not account for effects. 

* Supports cause and effect evaluations. of mixtures of contaminants. 

* Risk of under-protection of resource. 

* Does not consider the potential for bioaccumulation. 

Logistic Regression * Based on sediment toxicity test results. * Large database of matching sediment chemistry and 

Modelling Approach * Suitable for all classes of chemicals and most types biological effects data is required. 

of sediments. * Insufficient data are available for most freshwater 

* Provides SQGs that are associated with a specific receptors. 

probability of observing sediment toxicity. * Not possible to establish cause and effect relationships. 

* Provides SQGs that are species and endpoint specific. * Bioavailability is not considered. 

* Factors that influence bioavailability can be considered. * Does not consider the potential for bioaccumulation. 

* SQGs can be derived that correspond to specific 

management goals (e.g., 20% probability of observing 

sediment toxicity). 

83 
Table 3.1. Summary of the strengths and limitations of existing approaches for deriving numerical sediment quality 

assessment guidelines (adapted from Crane et al. 2000). 

Approach Strengths Limitations 

Consensus-Based 

Sediment Quality 

* Provides a unifying synthesis of the existing sediment 

quality guidelines. 

* 

* 

Bioavailability is not considered.

Does not consider the potential for bioaccumulation.

Guidelines Approach * Reflects causal rather than correlative effects. 

* Accounts for the effects of contaminant mixtures 

in sediments. 

* Predictive ability in freshwater sediments has 

been demonstrated. 

Tissue Residue Approach * Bioaccumulation is considered. * Tissue residue guidelines for wildlife are not yet available 

* A protocol for the derivation of tissue residue for most chemicals. 

guidelines is available. * Wildlife may be exposed to contaminants from multiple 

* Numerical SQGs can be derived if biota-sediment sites. 

accumulation factors are available. 

SQGs = sediment quality guidelines. 

84 
Table 3.2. Evaluation of candidate approaches for deriving sediment quality assessment guidelines for Florida inland waters 

(adapted from MacDonald 1994). 

Evaluation Criteria SLCA ERA ELA AETA EqPA LRMA CA 

Practicality 

Supports development of numerical SQAGs? 2 2 2 2 2 2 2 

Feasible to implement in the near term? 0 2 2 0 2 0 2 

Cost Effectiveness 

Inexpensive to implement? 2 2 2 2 2 2 2 

Does not requires generation of new data? 0 2 2 0 2 1 2 

Scientific Defensibility 

Considers bioavailability? 0 0 0 1 2 2 0 

Provides cause and effect relationships? 0 0 0 0 2 0 1 

Based on biological effects data? 2 2 2 2 2 2 2 

Considers data from southeast? 0 0 0 0 0 0 0 

Provides weight of evidence? 0 2 2 2 0 1 2 

Supports definition of ranges of concentrations 

rather than absolute assessment values 2 2 2 2 1 2 2 

Considers effects of mixtures of contaminants? 2 2 2 2 0 2 2 

Amenable to field validation? 2 2 2 2 0 2 2 

Applicable to all classes of chemicals? 2 2 2 2 1 2 2 

Applicability 

Supports monitoring programs? 2 2 2 2 2 2 2 

Supports identification of COPCs? 2 2 2 2 2 2 2 

Supports identification of sites of potential concern? 2 2 2 2 2 2 2 

Supports ecological risk assessments? 0 1 1 1 2 2 2 

Supports pollution control efforts? 2 2 2 2 2 2 2 

85 
Table 3.2. Evaluation of candidate approaches for deriving sediment quality assessment guidelines for Florida inland waters 

(adapted from MacDonald 1994). 

Evaluation Criteria SLCA ERA ELA AETA EqPA LRMA CA 

Applicability (continued) 

Supports wetland restoration projects? 1 1 1 1 2 1 1 

Supports hazardous waste site clean-ups? 0 1 1 1 2 2 2 

Supports regulatory decisions? 0 1 1 2 2 2 2 

Overall assessment score 23 32 32 30 32 33 36 

Note: Scores of 2, 1, or 0 were assigned if the approach fully, somewhat, or doesn't satisfy the criterion, respectively.

SQAGs = sediment quality assessment guidelines; COPCs = contaminants of potential concern.

SLCA = screening level concentration approach; ERA = effects range approach; ELA = effects level approach; AETA = apparent effects threshold approach;

EqPA = equilibrium partitioning approach; LRMA = logistic regression modelling approach; CA = consensus-based approach.

86 
Table 4.1. Listing of matching sediment chemistry and toxicity data sets compiled in the regional database. 

Location Sampling Whole Sediment Toxicity Sediment Chemistry n Reference Date Tests Conducted Analyses Conducted 

USEPA Region 3 

Chesapeake Bay, Delaware Bay, Anacostia 

River, DE, MD, NJ, PA, VA, DC 

Chester-Sassafras watershed (Bohemia River, 

Corsica River), MD 

Middle Potomac-Anacostia-Occoquan 

watershed (Anacostia River, Potomac 

River), DC 

Middle Potomac-Anacostia-Occoquan 

watershed (Anacostia River, Kingman 

Lake, Potomac River), DC 

Chester-Sassafras, Gunpowder-Patapsco 

watersheds (Corsica River, Curtis Creek), 

MD 

Middle Potomac-Anacostia-Occoquan 

watershed (Anacostia River, Kingman Lake, 

Potomac River), DC 

Brandywine-Christina watershed (Christina 

River, Churchmans Marsh, Newport Marsh, 

Nonesuch Creek) , DE 

1990 34 10-d Hyalella azteca (S) Butyltins, TOC, grainsize, metals, PAHs Weisberg et al. (1990) 

1991 10 28-d Hyalella azteca (S, G) Butyltins, TOC, grainsize, metals, PAHs, McGee et al. (1995) 

AVS, SEM 

1993 11 10-d Hyalella azteca Chlorinated benzenes, AVS, grainsize, USFWS (1997) 

TOC, metals, PAHs, PCBs, pesticides 

1993 5 10-d Hyalella azteca (S) TOC, grainsize, metals, PCBs, OC Eignor (1994) 

pesticides 

19931 5 10-d Hyalella azteca (S) Grainsize, metals McGee et al. (1993) 

19941 15 28-d Hyalella azteca (S, G) AVS, grainsize, TOC, metals, PAHs, Velinsky et al. (1994) 

PCBs, OC pesticides 

1995 39 10-d Hyalella azteca (S) AVS, SEM, grainsize, TOC, metals, Olinger (1996) 

PAHs, PCBs, pesticides 

87 
Table 4.1. Listing of matching sediment chemistry and toxicity data sets compiled in the regional database. 

Location Sampling Whole Sediment Toxicity Sediment Chemistry n Reference Date Tests Conducted Analyses Conducted 

USEPA Region 3 (cont.) 

Powell watershed (Ely Creek) , VA 

Brandywine-Christina watershed (Army 

Creek), DE 

Middle Potomac-Anacostia-Occoquan 

watershed (Anacostia River Estuary), 

DC 

USEPA Region 4 

Lower Mississippi River, Ogeechee River, IL, 

LA, MS, TN, GA 

Everglades watershed (Homestead Air Force 

Base), FL 

Pensacola Bay watershed (Lagoon 

between Santa Rosa Island and the 

Santa Rosa Sound), FL 

Lower Savannah watershed (Lower Savannah 

River), GA, SC 

1997 18 10-d Chironomus tentans (S, G) 

1999, 12 10-d Chironomus tentans (S, G) 

2000 12 10-d Hyalella azteca (S, G) 

2000 20 10-d Chironomus tentans (S, G) 

20 10-d Hyalella azteca (S, G) 

1994, 45 10-d Hyalella azteca (S) 

1995 

1995, 88 10-d Hyalella azteca (S) 

1996 

1996 4 10-d Hyalella azteca (S) 

1996, 48 10-d Hyalella azteca (S) 

1997 

Metals Cherry et al. (2001) 

Phthalates, TOC, metals, PAHs, USEPA (1999b) 

pesticides 

TOC, grainsize, metals, PAHs, PCBs, OC Fisher et al. (2001) 

pesticides 

AVS, TOC, metals, PAHs, PCBs, 

pesticides 

Butyltins, chlorinated benzenes, TOC, 

metals, PAHs, PCBs, pesticides 

Chlorinated benzenes, metals, PCBs, 

pesticides 

AVS, SEM, TOC, grainsize, metals 

Winger and Lasier 

(1998) 

Hefty (1998) 

Lewis et al. (2000) 

Winger et al. (2000) 

88 
Table 4.1. Listing of matching sediment chemistry and toxicity data sets compiled in the regional database. 

Location Sampling Whole Sediment Toxicity Sediment Chemistry n Reference Date Tests Conducted Analyses Conducted 

USEPA Region 4 (cont.) 

Bayou De Chien-Mayfield, Highland-Pigeon, 

Lower Green, Pond, Tradewater watersheds 

(Bayou de Chien, Casey Creek, Highland 

Creek, Panther Creek, Pond River, Tradewater 

River), KY 

Barren, Tradewater watersheds (Gasper River, 

Greasy Creek), KY 

Chipola watershed (Sapp Battery Site), FL 

Upper Cumberland watershed (Cane Creek), 

KY 

Lower Oconee watershed (Oconee River), GA 

Rolling Fork, Upper Green watersheds (Salt 

Lick Creek, Billy Creek), KY 

1997 6 10-d Hyalella azteca (S) Chlorinated benzenes, TOC, metals, Roth et al. (1998a) 

PCBs, pesticides 

1998 4 10-d Hyalella azteca (S) Chlorinated benzenes, phthalates, Roth et al. (1998b) 

phenols, ethers, metals, PAHs, PCBs, 

pesticides 

1998 11 10-d Chironomus tentans (S, G) Metals, grainsize, TOC ARCADIS Geraghty & 

11 10-d Hyalella azteca (S, G) Miller (1998a; 1998b); 

1998 2 10-d Hyalella azteca (S) Chlorinated benzenes, chlorophenols, 

metals, PCBs, pesticides 

1998 12 28-d Hyalella azteca (S, G) Chlorinated benzenes, TOC, grainsize, 

metals, PAHs, PCBs, pesticides, AVS, 

SEM 

1998, 4 10-d Hyalella azteca (S) Chlorinated benzenes, TOC, metals, 

1999 PCBs, pesticides 

New England 

Bioassay, Inc. (1998) 

Commonwealth of 

Kentucky (1999a) 

Lasier et al. (2001) 

Commonwealth of 

Kentucky (2000c) 

89 
Table 4.1. Listing of matching sediment chemistry and toxicity data sets compiled in the regional database. 

Location Sampling Whole Sediment Toxicity Sediment Chemistry n Reference Date Tests Conducted Analyses Conducted 

USEPA Region 4 (cont.) 

Lower Kentucky, Silver-Little Kentucky 1999 5 10-d WS Hyalella azteca (S) Chlorinated benzenes, phthalates, Commonwealth of 

watersheds, KY phenols, ethers, PAHs, PCBs, pesticides Kentucky (1999b) 

Upper Cumberland watershed, KY 2000 5 10-d Hyalella azteca (S) Chlorinated benzenes, phthalates, 

phenols, ethers, AVS, SEM, metals, 

PAHs, PCBs, pesticides 

Upper Cumberland watershed, KY 2000 4 10-d Hyalella azteca (S) Chlorinated benzenes, phthalates, 

phenols, ethers, AVS, SEM, metals, 

PAHs, PCBs, pesticides 

USEPA Region 6 

Trinity River Basin (East Fork, Elm Fork, 19891 72 10-d Chironomus tentans (S) TOC, metals, pesticides 

Trinity River), TX 36 10-d Hyalella azteca (S) 

Trinity River, TX, Mobile Bay, AL, Tabbs Bay, 19961 5 10-d Hyalella azteca (S) TOC, grainsize, AVS, 

TX 10 28-d Hyalella azteca (S) SEM, metals, PAHs 

4 28-d Hyalella azteca (G) 

5 32-d Hyalella azteca (S) 

Lower Calcasieu watershed (Calcasieu River), 1996, 15 10-d Hyalella azteca (S, G) Chlorinated benzenes, phthalates, 

Commonwealth of 

Kentucky (2000a) 

Commonwealth of 

Kentucky (2000b) 

Dickson et al. (1989) 

USEPA (1996) 

McLaren/Hart 

LA 1997 phenols, ethers, TOC, grainsize, metals, Environmental 

PAHs, OC pesticides, Engineering (1997) 

AVS, SEM 

90 
Table 4.1. Listing of matching sediment chemistry and toxicity data sets compiled in the regional database. 

Location Sampling Whole Sediment Toxicity Sediment Chemistry n Reference Date Tests Conducted Analyses Conducted 

USEPA Region 6 (cont.) 

West Galveston Bay watershed (Swan Lake salt 

marsh), TX 

1997 2 10-d Hyalella azteca (S, G) Chlorinated benzenes, phthalates, 

phenols, ethers, grainsize, TOC, metals, 

PAHs, PCBs, pesticides 

Charters et al. (1998) 

Austin-Travis Lakes, Gunpowder-Patapsco, Rio 

Grande watersheds (Eliza Pool, Canal Creek, 

Rio Grande River), TX 

19981 13 

13 

13 

28-d Hyalella azteca (S, G) 

35-d Hyalella azteca (S) 

42-d Hyalella azteca (S, G) 

TOC, grainsize, AVS, SEM, PAHs Ingersoll et al. (1998) 

Lower Calcasieu watershed (Calcasieu 2000 100 10-d Hyalella azteca (S) Chlorinated benzenes, CDM and MESL 

River), LA 99 10-d Hyalella azteca (G) phthalates, phenols, ethers, (2002) 

100 28-d Hyalella azteca (S) metals, PAHs, PCBs, 

99 28-d Hyalella azteca (G) OC pesticides, AVS, 

SEM, TOC, dioxins, furans 

Lower Calcasieu watershed (Calcasieu River), 2000 12 10-d Hyalella azteca (S) Chlorinated benzenes, phthalates, Entrix, Inc. (2001)

phenols, ethers, metals, PAHs, PCBs, 

pesticides 

LA

Austin-Travis Lakes watershed (Barton Creek, 

Wells Branch Creek), TX 

2000 9 28-d Hyalella azteca (S, G) Grainsize, metals, PAHs Ingersoll et al. (2001) 

d = day; n = number of samples; S = survival; G = growth; TOC = total organic carbon; PAHs = polycyclic aromatic hydrocarbons; 

PCBs = polychlorinated biphenyls; AVS = acid volatile sulfides; SEM = simultaneously extracted metals; OC = organochlorine. 1

Sampling date unknown, report date used. 

91 
Table 4.2. Summary of the whole-sediment toxicity data used to evaluate the predictive ability of the preliminary sediment quality 

assessment guidelines for Florida inland waters. 

Common Duration of Endpoint Number of Number of Toxic 

Species Tested Name Exposure (WS) Measured Samples Samples (%) 

Hyalella azteca Amphipod 10-d Growth 159 16 (10%) 

Hyalella azteca Amphipod 10-d Survival 522 88 (17%) 

10-d Survival or Growth 522 96 (18%) 

Hyalella azteca Amphipod 28-d Growth 162 18 (11%) 

Hyalella azteca Amphipod 28-d Survival 169 30 (18%) 

Hyalella azteca Amphipod 32-d Survival 5 0 (0%) 

Hyalella azteca Amphipod 35-d Survival 13 0 (0%) 

Hyalella azteca Amphipod 42-d Growth 13 1 (8%) 

Hyalella azteca Amphipod 42-d Survival 13 0 (0%) 

28- to 42-d Survival or Growth 174 45 (26%) 

Chironomus tentans Midge 10-d Growth 61 8 (13%) 

Chironomus tentans Midge 10-d Survival 133 12 (9%) 

10-d Survival or Growth 133 20 (15%) 

All tests combined Amphipod or Midge 10- to 42-d Survival or Growth 643 137 (21%) 

WS = whole sediment; -d = -day. 

92 
Table 4.3. Descriptions of the published freshwater SQGs that were used to derive numerical sediment effect concentration 

(from MacDonald et al. 2000a). 

Type of SQG Acronym Approach Description Reference 

Threshold Effect Concentration - SQGs 

Lowest Effect Level LEL SLCA Sediments are considered to be clean to marginally polluted at 

concentrations below the LELs. Adverse effects on the 

majority of sediment-dwelling organisms are not expected 

below this concentration. 

Threshold Effect Level TEL WEA Represents the concentration below which adverse effects are 

expected to occur only rarely. 

Effects Range - Low ERL WEA Represents the chemical concentration below which adverse 

effects would be only rarely observed. 

Threshold Effect Level for TEL-HA28 WEA Represents the concentration below which adverse effects on 

Hyalella azteca in 28-day tests survival or growth of the amphipod, Hyalella azteca , are 

expected to occur only rarely (in 28-day tests). 

Minimal Effect Threshold MET SLCA Sediments are considered to be clean to marginally polluted at 

concentrations below the METs. Adverse effects on the 

majority of sediment-dwelling organisms are not expected 

below this concentration. 

Chronic Equilibrium SQAL EqPA Represents the concentration in sediments that is predicted to be 

Partitioning Threshold associated with concentrations in the interstitial water below a 

chronic water quality criterion. Adverse effects on sedimentdwelling organisms are predicted to occur only rarely below 

this concentration. 

Persaud et al. 1993 

Smith et al. 1996 

Long and Morgan 1991 

USEPA 1996; 

Ingersoll et al. 1996

EC and MENVIQ 1992

Bolton et al. 1985;

Zarba 1992; USEPA 1997

93 
Table 4.3. Descriptions of the published freshwater SQGs that were used to derive numerical sediment effect concentration 

(from MacDonald et al. 2000a). 

Type of SQG Acronym Approach Description Reference 

Probable Effect Concentration - SQGs 

Severe Effect Level SEL SLCA Sediments are considered to be heavily polluted at 

concentrations above the SELs. Adverse effects on the majority 

of sediment-dwelling organisms are expected when this 

concentration is exceeded. 

Probable Effects Level PEL WEA Represents the concentration above which adverse effects are 

expected to occur frequently. 

Effects Range - Median ERM WEA Represents the chemical concentration above which adverse 

effects would frequently occur. 

Probable Effects Level for PEL-HA28 WEA Represents the concentration above which adverse effects on 

Hyalella azteca in 28-day tests survival or growth of the amphipod, Hyalella azteca, are 

expected to occur frequently in 28-day tests. 

Toxic Effect Threshold TET SLCA Sediments are considered to be heavily polluted at 

concentrations above the TETs. Adverse effects on sedimentdwelling organisms are expected when this concentration is 

exceeded. 

Persaud et al. 1993 

Smith et al. 1996 

Long and Morgan 1991 

USEPA 1996; 

Ingersoll et al. 1996 

EC and MENVIQ 1992 

SQGs = sediment quality guidelines; LEL = lowest observed effect level; SLCA = screening level concentration approach; WEA = weight of evidence approach;

ERL = effects range low; TEL = threshold effect level; MET = minimal effects threshold; SQAL = sediment quality advisory level; 

EqPA = equilibrium partitioning approach; SEL = severe effect level; PEL = probable effect level; ERM = effects range median; TET = toxic effect threshold.

HA28 = Hyalella azteca 28 day test.

94 
Table 4.4. Sediment quality guidelines that reflect threshold effect concentrations (TECs; i.e., below which harmful effects are 

unlikely to be observed; from MacDonald et al. 2000a). 

Threshold Effect Concentrations Substance TEL LEL MET ERL TEL-HA28 SQAL Consensus-Based TEC 

Metals (in mg/kg DW) 

Arsenic 

Cadmium 

Chromium 

Copper 

Lead 

Mercury 

Nickel 

Zinc 

5.9 6 7 33 11 NG 9.79 

0.596 0.6 0.9 5 0.58 NG 0.99 

37.3 26 55 80 36 NG 43.4 

35.7 16 28 70 28 NG 31.6 

35 31 42 35 37 NG 35.8 

0.174 0.2 0.2 0.15 NG NG 0.18 

18 16 35 30 20 NG 22.7 

123 120 150 120 98 NG 121 

Polycyclic Aromatic Hydrocarbons (PAHs; in μg/kg DW) 

Anthracene

Fluorene

Naphthalene

Phenanthrene

Benz[a]anthracene

Benzo(a)pyrene

Chrysene

Dibenz[a,h]anthracene

Fluoranthene

Pyrene

Total PAHs

NG 220 NG 85 10 NG 57.2 

NG 190 NG 35 10 540 77.4 

NG NG 400 340 15 470 176 

41.9 560 400 225 19 1800 204 

31.7 320 400 230 16 NG 108 

31.9 370 500 400 32 NG 150 

57.1 340 600 400 27 NG 166 

NG 60 NG 60 10 NG 33.0 

111 750 600 600 31 6200 423 

53 490 700 350 44 NG 195 

NG 4000 NG 4000 260 NG 1610 

95 
Table 4.4. Sediment quality guidelines that reflect threshold effect concentrations (TECs; i.e., below which harmful effects are 

unlikely to be observed; from MacDonald et al. 2000a). 

Threshold Effect Concentrations Substance TEL LEL MET ERL TEL-HA28 SQAL Consensus-Based TEC 

Polychlorinated Biphenyls (PCBs; in μg/kg DW) 

Total PCBs 34.1 70 200 50 32 NG 59.8 

Organochlorine Pesticides (in μg/kg DW) 

Chlordane

Dieldrin

Sum DDD

Sum DDE

Sum DDT

Total DDTs

Endrin

Heptachlor epoxide

Lindane (gamma-BHC)

4.5 7 7 0.5 NG NG 3.24 

2.85 2 2 0.02 NG 110 1.90 

3.54 8 10 2 NG NG 4.88 

1.42 5 7 2 NG NG 3.16 

NG 8 9 1 NG NG 4.16 

7 7 NG 3 NG NG 5.28 

2.67 3 8 0.02 NG 42 2.22 

0.6 5 5 NG NG NG 2.47 

0.94 3 3 NG NG 3.7 2.37 

TEC = Threshold effect concentration (from MacDonald et al. 2000a).

TEL = Threshold effect level; dry weight (Smith et al. 1996).

LEL = Lowest effect level, dry weight (Persaud et al. 1993).

MET = Minimal effect threshold; dry weight (EC and MENVIQ 1992).

ERL = Effects range low; dry weight (Long and Morgan 1991).

TEL-HA28 = Threshold effect level for Hyalella azteca ; 28 day test; dry weight (USEPA 1996).

SQAL = Sediment quality advisory levels; dry weight at 1% OC (USEPA 1997).

NG = No guideline; DW = dry weight.

96 
Table 4.5. Sediment quality guidelines that reflect probable effect concentrations (PECs; i.e., above which harmful effects are 

likely to be observed; from MacDonald et al. 2000a). 

Probable Effect Concentrations Substance PEL SEL TET ERM PEL-HA28 Consensus-Based PEC 

Metals (in mg/kg DW) 

Arsenic 

Cadmium 

Chromium 

Copper 

Lead 

Mercury 

Nickel 

Zinc 

17 33 17 85 48 33.0 

3.53 10 3 9 3.2 4.98 

90 110 100 145 120 111 

197 110 86 390 100 149 

91.3 250 170 110 82 128 

0.486 2 1 1.3 NG 1.06 

36 75 61 50 33 48.6 

315 820 540 270 540 459 

Polycyclic Aromatic Hydrocarbons (PAHs; in μg/kg DW) 

Anthracene NG 3700 NG 960 170 845 

Fluorene NG 1600 NG 640 150 536 

Naphthalene NG NG 600 2100 140 561 

Phenanthrene 515 9500 800 1380 410 1170 

Benz[a]anthracene 385 14800 500 1600 280 1050 

Benzo(a)pyrene 782 14400 700 2500 320 1450 

Chrysene 862 4600 800 2800 410 1290 

Fluoranthene 2355 10200 2000 3600 320 2230 

Pyrene 875 8500 1000 2200 490 1520 

Total PAHs NG 100000 NG 35000 3400 22800 

Polychlorinated Biphenyls (PCBs; in μg/kg DW) 

Total PCBs 277 5300 1000 400 240 676 

97 
Table 4.5. Sediment quality guidelines that reflect probable effect concentrations (PECs; i.e., above which harmful effects are 

likely to be observed; from MacDonald et al. 2000a). 

Probable Effect Concentrations Substance PEL SEL TET ERM PEL-HA28 Consensus-Based PEC 

Organochlorine Pesticides (in μg/kg DW) 

Chlordane

Dieldrin

Sum DDD

Sum DDE

Sum DDT

Total DDTs

Endrin

Heptachlor Epoxide

Lindane (gamma-BHC)

8.9 60 30 6 NG 17.6 

6.67 910 300 8 NG 61.8 

8.51 60 60 20 NG 28.0 

6.75 190 50 15 NG 31.3 

NG 710 50 7 NG 62.9 

4450 120 NG 350 NG 572 

62.4 1300 500 45 NG 207 

2.74 50 30 NG NG 16.0 

1.38 10 9 NG NG 4.99 

PECs = probable effect concentrations (from MacDonald et al. 2000a)

PEL = Probable effect level; dry weight (Smith et al. 1996).

SEL = Severe effect level, dry weight (Persaud et al. 1993).

TET = Toxic effect threshold; dry weight (EC and MENVIQ 1992).

ERM = Effects range median; dry weight (Long and Morgan 1991).

PEL-HA28 = Probable effect level for Hyalella azteca ; 28-day test; dry weight (USEPA 1996).

NG = No guideline; DW = dry weight.

98 
Table 4.6. Reliability of the consensus-based threshold effect concentrations (TECs) in freshwater 

sediments (from MacDonald et al. 2000a). 

Number Number of Samples Number of Samples Percentage of Samples 

Substance of Predicted to be Not Observed Correctly Predicted 

Samples Toxic to be Not Toxic to be Not Toxic 

Metals 

Arsenic 150 58 43 74.1 

Cadmium 347 102 82 80.4 

Chromium 347 132 95 72.0 

Copper 347 158 130 82.3 

Lead 347 152 124 81.6 

Mercury 79 35 12 34.3 

Nickel 347 184 133 72.3 

Zinc 347 163 133 81.6 

Polycyclic Aromatic Hydrocarbons (PAHs) 

Anthracene

Fluorene

Naphthalene

Phenanthrene

Benz[a]anthracene

Benzo(a)pyrene

Chrysene

Dibenz[a,h]anthracene

Fluoranthene

Pyrene

Total PAHs

129 

129 

139 

139 

139 

139 

139 

98 

139 

139 

167 

Polychlorinated Biphenyls (PCBs) 

Total PCBs 120 

Organochlorine Pesticides 

Chlordane

Dieldrin

Sum DDD

Sum DDE

Sum DDT

Total DDT

Endrin

Heptachlor Epoxide

Lindane

193 

180 

168 

180 

96 

110 

170 

138 

180 

75 62 82.7 

93 66 71.0 

85 64 75.3 

79 65 82.3 

76 63 82.9 

81 66 81.5 

80 64 80.0 

77 56 72.7 

96 72 75.0 

78 62 79.5 

81 66 81.5 

27 24 88.9 

101 86 85.1 

109 91 83.5 

101 81 80.2 

105 86 81.9 

100 77 77.0 

92 76 82.6 

126 89 70.6 

90 74 82.2 

121 87 71.9 

99 
Table 4.7. Reliability of the consensus-based probable effect concentrations (PECs) in 

freshwater sediments (from MacDonald et al. 2000a). 

Number Number of Samples Number of Samples Percentage of Samples 

Substance of Predicted Observed Correctly Predicted 

Samples to be Toxic to be Toxic to be Toxic 

Metals 

Arsenic 

Cadmium 

Chromium 

Copper 

Lead 

Mercury 

Nickel 

Zinc 

150 26 20 76.9 

347 126 118 93.7 

347 109 100 91.7 

347 110 101 91.8 

347 125 112 89.6 

79 4 4 100 

347 96 87 90.6 

347 120 108 90.0 

Polycyclic Aromatic Hydrocarbons (PAHs) 

Anthracene

Fluorene

Naphthalene

Phenanthrene

Benz[a]anthracene

Benzo(a)pyrene

Chrysene

Fluoranthene

Pyrene

Total PAHs

129 13 13 100 

129 13 13 100 

139 26 24 92.3 

139 25 25 100 

139 20 20 100 

139 24 24 100 

139 24 23 95.8 

139 15 15 100 

139 28 27 96.4 

167 20 20 100 

Polychlorinated Biphenyls (PCBs) 

Total PCBs 

Organochlorine Pesticides 

Chlordane

Dieldrin

Sum DDD

Sum DDE

Sum DDT

Total DDT

Endrin

Heptachlor Epoxide

Lindane

120 51 42 82.3

193 37 27 73.0 

180 10 10 100 

168 6 5 83.3 

180 30 29 96.7 

96 12 11 91.7 

110 10 10 100 

170 0 0 NA 

138 8 3 37.5 

180 17 14 82.4 

NA = Not applicable 

100 
Table 4.8. Incidence of toxicity within ranges of contaminant concentrations defined by the 

sediment quality guidelines (SQGs; from MacDonald et al. 2000a) 

Substance Number of Incidence of Toxicity 

Samples Evaluated (number of samples in parenthesis) 

<TEC TEC-PEC >PEC

Metals 

Arsenic 150 25.9% (15 of 58) 

Cadmium 347 19.6% (20 of 102) 

Chromium 347 28% (37 of 132) 

Copper 347 17.7% (28 of 158) 

Lead 347 18.4% (28 of 152) 

Mercury 79 65.7% (23 of 35) 

Nickel 347 27.7% (51 of 184) 

Zinc 347 18.4% (30 of 163) 

Polycyclic Aromatic Hydrocarbons (PAHs) 

Anthracene 129 

Fluorene 129 

Naphthalene 139 

Phenanthrene 139 

Benz[a]anthracene 139 

Benzo(a)pyrene 139 

Chrysene 139 

Fluoranthene 139 

Pyrene 139 

Total PAHs 167 

Polychlorinated Biphenyls (PCBs) 

Total PCBs 

Organochlorine Pesticides 

Chlordane

Dieldrin

Sum DDD

Sum DDE

Sum DDT

Total DDT

Endrin

Heptachlor Epoxide

Lindane

120 

193 

180 

168 

180 

96 

110 

170 

138 

180 

17.3% (13 of 75) 

29% (27 of 93) 

24.7% (21 of 85) 

17.7% (14 of 79) 

17.1% (13 of 76) 

18.5% (15 of 81) 

20% (16 of 80) 

25% (24 of 96) 

20.5% (16 of 78) 

18.5% (15 of 81) 

11.1% (3 of 27) 

14.9% (15 of 101) 

16.5% (18 of 109) 

19.8% (20 of 101) 

18.1% (19 of 105) 

23% (23 of 100) 

17.4% (16 of 92) 

29.4% (37 of 126) 

17.8% (16 of 90) 

28.1% (34 of 121) 

57.6% (38 of 66) 

44.6% (29 of 65) 

64.4% (38 of 59) 

64.0% (48 of 75) 

53.6% (37 of 69) 

70.0% (28 of 40) 

62.7% (32 of 51) 

60.9% (39 of 64) 

92.9% (26 of 28) 

85.7% (12 of 14) 

94.1% (16 of 17) 

88.2% (30 of 34) 

70% (14 of 20) 

75.7% (28 of 37) 

68.1% (32 of 47) 

82.5% (33 of 40) 

63.0% (29 of 46) 

65.1% (43 of 66) 

31.0% (9 of 29) 

75.0% (15 of 20) 

95.2% (20 of 21) 

33.3% (1 of 3) 

33.3% (1 of 3) 

0.0% (0 of 1) 

100% (23 of 23) 

40.0% (4 of 10) 

85.0% (17 of 20) 

65.9% (29 of 44) 

76.9% (20 of 26) 

93.7% (118 of 126) 

91.7% (100 of 109) 

91.8% (101 of 110) 

89.6% (112 of 125) 

100% (4 of 4) 

90.6% (87 of 96) 

90.0% (108 of 120) 

100% (13 of 13) 

100% (13 of 13) 

92.3% (24 of 26) 

100% (25 of 25) 

100% (20 of 20) 

100% (24 of 24) 

95.8% (23 of 24) 

100% (15 of 15) 

96.4% (27 of 28) 

100% (20 of 20) 

82.3% (42 of 51) 

73.0% (27 of 37) 

100% (10 of 10) 

83.3% (5 of 6) 

96.7% (29 of 30) 

91.7% (11 of 12) 

100% (10 of 10) 

NA% (0 of 0) 

37.5% (3 of 8) 

82.4% (14 of 17) 

NA = not applicable; TEC = threshold effect concentration; PEC = probable effect concentration. 

101 
Table 4.9. Incidence of sediment toxicity within ranges of mean PEC-Qs for sediments collected throughout the United States 

(from USEPA 2000a). 

Toxicity Test Endpoint n Incidence of Toxicity (number of samples in parentheses) 

<0.1 0.1 to <0.5 0.5 to <1.0 1.0 to <5.0 >1.0 >5.0 

10- to 14-day tests with amphipods Survival or growth 670 18% 16% 37% 41% 54% 71% 

(Hyalella azteca) (26 of 147) (46 of 288) (27 of 73) (38 of 92) (87 of 162) (50 of 70) 

28- to 42-day tests with amphipods Survival or growth 160 10% 13% 56% NC 97% NC 

(Hyalella azteca) (6 of 63) (5 of 39) (15 of 27) (30 of 31) 

10- to 14-day tests with midges Survival or growth 629 20% 17% 43% 43% 52% 68% 

(Chironomus tentans or (24 of 121) (53 of 313) (27 of 63) (38 of 88) (69 of 132) (30 of 44) 

Chironomus riparius) 

n = number of samples; NC = not calculated. 

102 
Table 4.10. Incidence of sediment toxicity within ranges of mean PEC-Qs for sediments from Florida and elsewhere in the southeastern 

portion of the United States. 

Toxicity Test - Endpoint n Avg Incidence of Toxicity (number of samples in parentheses) 

mean Q <0.1 0.1 to <0.5 0.5 to <1.0 1.0 to <5.0 >1.0 >5.0 

10-d Hyalella azteca survival 522 0.379 13% (15 of 116) 15% (51 of 339) 30% (14 of 46) 33% (6 of 18) 38% (8 of 21) 67% (2 of 3) 

10-d Hyalella azteca survival or growth 522 0.379 13% (15 of 116) 16% (54 of 339) 37% (17 of 46) 39% (7 of 18) 48% (10 of 21) 100% (3 of 3) 

28-42-d Hyalella azteca survival 174 0.549 8% (4 of 53) 13% (11 of 87) 43% (10 of 23) 38% (3 of 8) 45% (5 of 11) 67% (2 of 3) 

28-42-d Hyalella azteca survival or growth 174 0.549 13% (7 of 53) 24% (21 of 87) 52% (12 of 23) 38% (3 of 8) 45% (5 of 11) 67% (2 of 3) 

10-d Chironomus tentans survival 133 0.391 19% (5 of 26) 7% (7 of 94) 0% (0 of 9) 0% (0 of 3) 0% (0 of 4) 0% (0 of 1) 

10-d Chironomus tentans survival or growth 133 0.391 23% (6 of 26) 9% (8 of 94) 33% (3 of 9) 67% (2 of 3) 75% (3 of 4) 100% (1 of 1) 

Overall Toxicity 643 0.381 18% (27 of 150) 18% (73 of 406) 43% (26 of 61) 36% (8 of 22) 42% (11 of 26) 75% (3 of 4) 

n = number of samples; PEC-Q = probable effects concentration quotient. 

103 
Table 4.11. Comparison of concentration-response relationships using matching sediment chemistry and biological effects data 

from the regional and national databases. 

Sediment Quality Targets (expressed as mean PEC-Qs1) Endpoint Measured n 

P20 P50 Logistic Model Parameters2 

Chronic toxicity to amphipods (endpoint: survival) 

Regional database 174 0.299 1.82 a = 76.9819; b = -0.9205; x0 = 0.9310 (r2 = 0.79; p = <0.001) 

National database3 160 0.647 3.03 a = 309.0814; b = -0.6643; x0 = 36.0700 (r2

 = 0.79; p = <0.0001) 

Chronic toxicity to amphipods (endpoint: survival or growth) 

Regional database 174 0.136 0.781 a = 61.7734; b = -1.2463; x0 = 0.2450 (r2 = 0.78; p = <0.05) 

National database3 160 0.220 0.628 a = 111.7462; b = -1.2496; x0 = 0.7438 (r2

 = 0.93; p = <0.0001) 

Acute toxicity to amphipods (endpoint: survival) 

Regional database 522 0.362 NA4 a = 633.7739; b = -0.4810; x0 = 447.2264 (r2 = 0.71; p = <0.05) 

National database3 670 0.336 4.46 a = 122.2927; b = -0.4890; x0 = 9.4722 (r2

 = 0.77; p = <0.0001) 

Acute toxicity to amphipods (endpoint: survival or growth) 

Regional database 174 0.302 NA4 a = 1020.4246; b = -0.5518; x0 = 361.9784 (r2 = 0.82; p = <0.005) 

National database3 670 0.225 3.38 a = 113.4909; b = -0.4811; x0 = 5.5553 (r2

 = 0.71; p = <0.0001) 

Chronic toxicity to midges (endpoint: survival or growth) 

Regional database 133 0.496 1.12 a = 8404.0068; b = -1.1309; x0 = 103.2892 (r2 = 0.42; p = 0.07) 

National database3 632 0.187 3.52 a = 99.4883; b = -0.4736; x0 = 3.4422 (r2

 = 0.56; p = <0.0001) 

1

PEL-Q = probable effect concentration quotient from MacDonald et al. (2000a).

2

Logistic Model Equation: y = a/[1+(x/x0)

b

]

3

From USEPA (2000a) and Ingersoll et al. (2001).

4

NA = not applicable; concentration-response data did not support calculation of the P value. 104
Table 5.1. Sediment quality assessment guidelines for the protection of sediment-dwelling 

organisms in Florida. 

Sediment Quality 

Substance Assessment Guideline Source 

TEC PEC

Metals (in mg/kg DW) 

Arsenic 

Barium 

Beryllium 

Boron 

Cadmium 

Chromium 

Cobalt 

Copper 

Lead 

Mercury 

Nickel 

Silver 

Strontium 

Titanium 

Zinc 

Zircon 

9.8 33 

20 60 

NG NG 

NG NG 

1.0 5.0 

43 110 

50 NG 

32 150 

36 130 

0.18 1.1 

23 49 

1.0 2.2 

NG NG 

NG NG 

120 460 

NG NG 

Polycyclic Aromatic Hydrocarbons (PAHs; in μg/kg DW) 

Acenaphthene 6.7 89 

Acenaphthylene 5.9 130 

Anthracene 57 850 

Fluorene 77 540 

Naphthalene 180 560 

Phenanthrene 200 1200 

Benz[a]anthracene 110 1100 

Benzo(a)pyrene 150 1500 

Chrysene 170 1300 

Dibenz[a,h]anthracene 33 140 

Fluoranthene 420 2200 

Pyrene 200 1500 

Total PAHs 1600 23000 

MacDonald et al. (2000a)

USEPA (1977)

MacDonald et al. (2000a)

MacDonald et al. (2000a)

Persaud et al . (1993)

MacDonald et al. (2000a)

MacDonald et al. (2000a)

MacDonald et al. (2000a)

MacDonald et al. (2000a)

NYSDEC (1999)

MacDonald et al. (2000a)

CCME (1999)

CCME (1999)

MacDonald et al. (2000a)

MacDonald et al. (2000a)

MacDonald et al. (2000a)

MacDonald et al. (2000a)

MacDonald et al. (2000a)

MacDonald et al. (2000a)

MacDonald et al. (2000a)

MacDonald et al. (2000a)/CCME (1999)

MacDonald et al. (2000a)

MacDonald et al. (2000a)

MacDonald et al. (2000a)

105 
Table 5.1. Sediment quality assessment guidelines for the protection of sediment-dwelling 

organisms in Florida. 

Sediment Quality 

Substance Assessment Guideline Source 

TEC PEC

Polychlorinated Biphenyls (PCBs; in μg/kg DW) 

Total PCBs 60 680 

Chlorinated Benzenes (in μg/kg DW) 

Hexachlorobenzene (HCB) 20 240 

Hexachlorobutadiene (HCBD) 55 550 

Phthalates (in μg/kg DW) 

Bis(2-ethylhexyl)phthalate 180 2600 

Dimethyl Phthalate NG NG 

Diethyl Phthalate 630 NG 

Di-n-butyl Phthalate NG 43 

Organochlorine Pesticides (in μg/kg DW) 

Chlordane 3.2 18 

Dieldrin 1.9 62 

Sum DDD 4.9 28 

Sum DDE 3.2 31 

Sum DDT 4.2 63 

Total DDTs 5.3 570 

Endrin 2.2 210 

Heptachlor Epoxide 2.5 16 

Lindane (gamma-BHC) 2.4 5.0 

Organophosphate Pesticides (in μg/kg DW) 

Azinphos-ethyl 0.018 NG 

Azinphos-methyl 0.062 NG 

Diazinon 0.38 NG 

Ethion NG NG 

Malathion 0.67 NG 

Methidathion NG NG 

Phosmet NG NG 

Phosphamidon NG NG 

Phoxim 0.060 NG 

Pyrazophos 0.015 NG 

MacDonald et al. (2000a) 

Persaud et al . (1993) 

NYSDEC (1999) 

MacDonald et al. (1996) 

USEPA (1997) 

Cubbage et al. (1997) 

MacDonald et al. (2000a) 

MacDonald et al. (2000a) 

MacDonald et al. (2000a) 

MacDonald et al. (2000a) 

MacDonald et al. (2000a) 

MacDonald et al. (2000a) 

MacDonald et al. (2000a) 

MacDonald et al. (2000a) 

MacDonald et al. (2000a) 

Stortelder et al. (1989) 

Stortelder et al. (1989) 

Stortelder et al. (1989) 

USEPA (1997) 

Stortelder et al. (1989) 

Stortelder et al. (1989) 

106 
Table 5.1. Sediment quality assessment guidelines for the protection of sediment-dwelling 

organisms in Florida. 

Sediment Quality 

Substance Assessment Guideline Source 

TEC PEC

Other Pesticides (in μg/kg DW) 

Toxaphene 0.10 32 NYSDEC (1999) 

Triazine Herbicides (in μg/kg DW) 

Atrazine 0.30 NG Stortelder et al. (1989) 

Cyanazine NG NG 

Simazine 0.34 NG Stortelder et al. (1989) 

DW = dry weight; NG = no guideline. 

107 
Table 5.2. Sediment quality assessment guidelines for the protection of aquatic-dependent wildlife and human health 

in Florida. 

Wildlife-Based Human Health-Based 

Chemicals of Concern SQAGs1 Source SQAGs2 Source 

Metals (mg/kg DW) 

Lead 

Mercury 

Polycyclic Aromatic Hydrocarbons (μg/kg OC) 

Acenapthene

Acenaphthylene

Anthracene

Fluorene

2-methylnaphthalene

Naphthalene

Phenanthrene

Benz[a]anthracene

Benzo(b)fluoranthene

Benzo(k)fluoranthene

Benzo(a)pyrene

Chrysene

Dibenz[a,h]anthracene

Fluoranthene

Indeno(1,2,3-cd)pyrene

Pyrene

Total PAHs

NG NG 

NG NG 

NG NG 

NG NG 

NG NG 

NG NG 

NG NG 

NG NG 

NG NG 

NG 69 

NG 69 

NG 69 

NG 69 

NG 44 

NG 69 

NG NG 

NG 69 

NG NG 

NG NG 

WDOH (1995; 1996) 

WDOH (1995; 1996) 

WDOH (1995; 1996) 

WDOH (1995; 1996) 

WDOH (1995; 1996) 

WDOH (1995; 1996) 

WDOH (1995; 1996) 

108 
Table 5.2. Sediment quality assessment guidelines for the protection of aquatic-dependent wildlife and human health 

in Florida. 

Wildlife-Based Human Health-Based 

Chemicals of Concern SQAGs1 Source SQAGs2 Source 

Polychlorinated Biphenyls (μg/kg OC) 

Aroclor 1016 NG 4.9 WDOH (1995; 1996) 

Aroclor 1242 NG 1.7 WDOH (1995; 1996) 

Aroclor 1248 NG 1.7 WDOH (1995; 1996) 

Aroclor 1254 NG 1.7 WDOH (1995; 1996) 

Aroclor 1260 NG 1.7 WDOH (1995; 1996) 

Total PCBs 1400 NYSDEC (1999) NG 

Chlorinated Benzenes (μg/kg OC) 

Hexachlorobenzene (HCB) 12000 NYSDEC (1999) 310 WDOH (1995; 1996) 

Hexachlorobutadiene (HCBD) 4000 NYSDEC (1999) 8100 WDOH (1995; 1996) 

Phthalates (μg/kg OC) 

Bis(2-ethyl hexyl)phthalate NG 36000 WDOH (1995; 1996) 

Chlorophenols (μg/kg OC) 

Pentachlorophenol NG 4200 WDOH (1995; 1996) 

Pesticides (μg/kg OC) 

Aldrin NG 0.13 WDOH (1995; 1996) 

Aldrin + Dieldrin 770 NYSDEC (1999) NG NYSDEC (1999) 

Chlordane 6 NYSDEC (1999) 1.7 WDOH (1995; 1996) 

Dieldrin NG 0.14 WDOH (1995; 1996) 

p,p-DDD NG 9.1 WDOH (1995; 1996) 

p,p-DDE NG 5.5 WDOH (1995; 1996) 

109 
Table 5.2. Sediment quality assessment guidelines for the protection of aquatic-dependent wildlife and human health 

in Florida. 

Wildlife-Based Human Health-Based 

Chemicals of Concern SQAGs1 Source SQAGs2 Source 

Pesticides (μg/kg OC; con't.) 

p,p-DDT NG 6.5 WDOH (1995; 1996) 

Total DDT 1000 NYSDEC (1999) 10 NYSDEC (1999) 

Endosulfan NG 36000 WDOH (1995; 1996) 

Endrin 800 NYSDEC (1999) 550 WDOH (1995; 1996) 

Heptachlor NG 1.3 WDOH (1995; 1996) 

Heptachlor epoxide NG 0.65 WDOH (1995; 1996) 

Heptachlor + heptachlor epoxide 30 NYSDEC (1999) 0.80 NYSDEC (1999) 

Alpha-hexachlorocyclohexane (HCH)3 NG 0.94 WDOH (1995; 1996) 

Beta-HCH3 NG 3.2 WDOH (1995; 1996) 

Technical-HCH3 1500 NYSDEC (1999) 3.3 WDOH (1995; 1996) 

Lindane (gamma-HCH)3 NG 4.6 WDOH (1995; 1996) 

Mirex 3700 NYSDEC (1999) 70 NYSDEC (1999) 

Toxaphene NG 20 NYSDEC (1999) 

Dioxins (μg/kg OC) 

1,2,3,4,6,7,8-Heptachlorodibenzo-p-dioxin NG 12 WDOH (1995; 1996) 

1,2,3,4,6,7,8-Heptachlorodibenzofuran NG 12 WDOH (1995; 1996) 

1,2,3,4,7,8,9-Heptachlorodibenzofuran NG 12 WDOH (1995; 1996) 

1,2,3,4,7,8-Hexachlorodibenzo-p-dioxin NG 0.046 WDOH (1995; 1996) 

1,2,3,4,7,8-Hexachlorodibenzofuran NG 0.046 WDOH (1995; 1996) 

1,2,3,6,7,8-Hexachlorodibenzo-p-dioxin NG 0.046 WDOH (1995; 1996) 

1,2,3,6,7,8-Hexachlorodibenzofuran NG 0.046 WDOH (1995; 1996) 

1,2,3,7,8,9-Hexachlorodibenzo-p-dioxin NG 0.046 WDOH (1995; 1996) 

110 
Table 5.2. Sediment quality assessment guidelines for the protection of aquatic-dependent wildlife and human health 

in Florida. 

Wildlife-Based Human Health-Based 

Chemicals of Concern SQAGs1 Source SQAGs2 Source 

Dioxins (μg/kg OC; con't.) 

1,2,3,7,8,9-Hexachlorodibenzofuran NG 0.046 WDOH (1995; 1996) 

1,2,3,7,8-Pentachlorodibenzo-p-dioxin NG 0.0092 WDOH (1995; 1996) 

1,2,3,7,8-Pentachlorodibenzofuran NG 0.026 WDOH (1995; 1996) 

2,3,4,6,7,8-Hexachlorodibenzofuran NG 0.046 WDOH (1995; 1996) 

2,3,4,7,8-Pentachlorodibenzofuran NG 0.0031 WDOH (1995; 1996) 

2,3,7,8-Tetrachlorodibenzo-p-dioxin 0.2 NYSDEC (1999) 0.00015 WDOH (1995; 1996) 

2,3,7,8-Tetrachlorodibenzofuran NG 0.013 WDOH (1995; 1996) 

Octachlorodibenzodioxin NG 120 WDOH (1995; 1996) 

Octachlorodibenzofuran NG 120 WDOH (1995; 1996) 

OC = organic carbon; NG = no guideline is available; SQGs = sediment quality guidelines; DW = dry weight; OC = organic carbon.

1

Source: NYSDEC 1999

2

Source: WDOH 1995; 1996 (*if no guideline was available from this source, the NYSDEC 1999 guidelines were used)

3

The wildlife-based SQGs for hexachlorocyclohexane (HCH) are for the sum of all HCH isomers, including alpha - HCH, beta-HCH and gamma-HCH.

111 
 Figures
0.01 0.1 1 10 100 

0 

20 

40 

60 

80 

100 

Figure 4.1. Relationship between the geometric mean of mean PEC-Qs and the 

incidence of acute toxicity to amphipods (endpoints: survival only) 

in the national (10- to 14-day toxicity tests) and regional (10-day 

toxicity tests) databases. 

100

90

80

National database 

National database 

95% prediciton limits 

Regional database 

Regional database 

r 

2

 = 0.77 

r 

2

 = 0.71 

Incidence of t

o

xicity (%) 

70

60

50

40

30

20

10

0

0.01 0.1 1 10 100 

Geomean of mean PEC-Q 

112

0.01 0.1 1 10 100 

0 

20 

40 

60 

80 

100 

Figure 4.2. Relationship between the geometric mean of mean PEC-Qs and the 

incidence of acute toxicity to amphipods (endpoints: survival or growth) 

in the national (10- to 14-day toxicity tests) and regional (10-day 

toxicity tests) databases. 

100

90

80 National database 

National database 

95% prediction limits 

Regional database 

Regional database 

r

2

 = 0.71 

r

2

 = 0.82 

Incidence of t

o

xicity (%) 

70

60

50

40

30

20

10

0

0.01 0.1 1 10 100 

Geometric mean of mean PEC-Q 

113

0.01 0.1 1 10 

0 

20 

40 

60 

80 

100 

Figure 4.3. Relationship between the geometric mean of mean PEC-Qs and the 

incidence of chronic toxicity to amphipods (endpoints: survival only) 

in the national (28- to 42-day toxicity tests) and regional (28- to 42-day 

toxicity tests; n = 174, grouped by 15) databases. 

100 

90 

80 

70 

60 

50 

40 

30 

20 

10 

0 

Regional database 

Regional database 

National database 

National database 

95% prediction limits 

r 

2

 = 0.79 

0.01 0.1 1 10 

Geometric mean of mean PEC-Q 

% incidence of t

o

xicity 

114

0.01 0.1 1 10 

0 

20 

40 

60 

80 

100 

Figure 4.4. Relationship between the geometric mean of mean PEC-Qs and the 

incidence of chronic toxicity to amphipods (endpoints: survival or growth) 

in the national (28- to 42 day toxicity tests) and regional (28- to 42-day 

toxicity tests) databases. 

100

90

80

Incidence of t

o

xicity (%) 

70

60

50

40

30

National database 

National database 

95% prediction limits 

Regional database 

Regional database 

r

2

 = 0.78 

r

2

 = 0.93 

20

10

0

0.01 0.1 1 10 

Geometric mean of mean PEC-Q 

115

0.01 0.1 1 10 100 

0 

20 

40 

60 

80 

100 

Figure 4.5. Relationship between the geometric mean of mean PEC-Qs and the 

incidence of acute toxicity to midges (endpoints: survival or growth), 

in the national (10- to 14-d Chironomus spp. toxicity tests) and regional 

(10-day toxicity tests) databases. 

100

90

80

National database 

National database 

95% prediction limits 

Regional database 

Regional database 

r

2

 = 0.42 

r

2

 = 0.56 

% incidence of t

o

xicity 

70

60

50

40

30

20

10

0

0.01 0.1 1 10 100 

Geometric mean of mean PEC-Q 

116

 Appendices
APPENDIX 1 – PAGE A-1 

Appendix 1 Freshwater Sediment Quality Assessment 

Initiative: Project Overview 

A1.0 Introduction and Background 

Historic and, to a lesser extent, ongoing land and water use activities, have caused aquatic 

sediments in many locations throughout Florida to become contaminated with a variety of 

toxic and bioaccumulative substances. These contaminants include trace metals, PAHs, 

PCBs, PCDDs and PCDFs, chlorinated pesticides (e.g., DDTs and toxaphene), and other 

industrial and agricultural chemicals. The presence of contaminated sediments in freshwater, 

estuarine, and marine ecosystems has the potential to adversely affect aquatic organisms, 

aquatic-dependent wildlife species, and human health. For this reason, the assessment, 

management, and remediation of contaminated sediments has been identified as a priority 

for the water assessment initiative and waste management sections of the FDEP. 

In recognition of the need to support sediment management activities throughout the state, 

FDEP initiated its first major sediment-related initiative in the early 1980's. This initiative, 

which was implemented under the Coastal Zone Management Program, consisted of four 

main elements. First, FDEP conducted a broad survey of sediment quality conditions in 

near-shore marine and estuarine habitats along the Atlantic and Gulf coasts. Next, the 

resultant data fromrelativelyuncontaminated sites were used to develop a practical approach 

for assessing metals contamination in coastal sediments which relied on the normalization 

of metal concentrationsto a reference element (i.e., the metalsinterpretive tool; Schropp and 

Windom 1988; Schropp et al. 1990). Subsequently, effects-based SQAGs were developed 

which provide a scientifically-defensible basis for evaluating the potential effects of 

sediment-associated contaminants on aquatic organisms (MacDonald 1994; MacDonald et 

al. 1996). Finally, a framework for assessing sediment quality conditions in marine and 

estuarine ecosystems was developed to provide agencystaff and others with guidance on how 

the various tools should be applied together to support sediment management decisions 

(MacDonald 1994). These assessment tools and the assessment framework are currently 

being used in a wide variety of applications, both in Florida and elsewhere in North America. 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
APPENDIX 1 – PAGE A-2 

While the existing guidance documents provide administrators, managers, and scientists with 

the tools that are needed to effectively manage marine and estuarine sediments in Florida, 

companion tools for assessing freshwater sediments are not currently available in the state. 

For this reason, FDEP has identified the development of guidance on the assessment of 

freshwater sediments as a high priority. This guidance has been developed as part of the 

Freshwater Sediment Quality Assessment Initiative. 

A1.1 Freshwater Sediment Quality Assessment Initiative 

Traditionally, themanagement of aquatic resourcesin Florida has focused primarily on water 

quality. However, the importance of sediments in terms of determining the fate and effects 

of a wide variety of contaminants has become more apparent in recent years. In addition to 

providing habitat for many organisms, sediments are important because many toxic 

substancesfound at only trace levelsin water can accumulate to elevated levelsin sediments. 

As such, sediments serve both as reservoirs and potential sources of contaminants to the 

water column. Sediment-associated contaminants have the potential to cause direct effects 

on sediment-dwelling organisms and to adversely affect wildlife and human health when 

these substances accumulate in the food web. Therefore, information on sediment quality 

conditions is essential for evaluating the overall status of freshwater ecosystems. 

The FDEP plays a lead role in the assessment and management of aquatic resources in the 

state. To meet its responsibilities in terms of managing Florida’s unique freshwater 

ecosystems, FDEP has developed a number of programs that enable it to effectively protect 

water quality and ensure proper waste management. Many of these programs have 

componentsthat necessitate the assessment and management ofsediment quality conditions, 

including: 

• Watershed Monitoring; 

• Environmental Resource Permitting; 

• Everglades Ecosystem Restoration; 

• Domestic and Industrial Wastewater; 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
APPENDIX 1 – PAGE A-3 

• Mine Reclamation; 

• Nonpoint Source/Stormwater; 

• Solid and Hazardous Waste; 

• State Lands; and, 

• Waste Cleanup. 

A1.2 Implementation Plan 

Successful completion of the Freshwater Sediment Quality Assessment Initiative 

necessitated the development and implementation of an effective project management 

strategy. In recognition of the need for broad stakeholder involvement and inter-agency 

cooperation, FDEP developed a detailed implementation plan that consists of the following 

elements: 

• Identify the project components and develop a preliminary implementation plan; 

• Convene an interests and needs workshop on the assessment of freshwater 

sediments; 

• Prepare and distribute a workshop summary report to workshop participants; 

• Build an effective inter-agency Steering Committee to guide the project through 

the implementation phase; 

• Solicit additional advice from stakeholders on an as needed basis; 

• Prepare periodic progress reports for FDEP’s senior managers and stakeholders; 

• Prepare and distribute draft guidance documents to stakeholders; 

• Incorporate comments and finalize guidance documents; and, 

• Convene a series a workshops for FDEP district staff and others to explain the 

applications of the tools that are described in the guidance documents. 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
APPENDIX 1 – PAGE A-4 

A1.3 Development of a Metals Interpretive Tool 

Sediment chemistry data are essential for evaluating sediment quality conditions in 

freshwater ecosystems. However, interpretation of data on the concentrations of sedimentassociated metals is challenging because such measurements are influenced by a variety of 

factors, including sediment mineralogy, grain size, organic content, and anthropogenic 

enrichment. This combination of factors results in metals levels that can vary two to three 

orders of magnitude at uncontaminated sites in Florida. Therefore, it is important to consider 

the natural background levels of sediment-associated metals when conducting sediment 

quality assessments. 

In Florida, assessment of the probable origin of metals in freshwater sediments is supported 

by a metals interpretive tool. Development of the metals interpretive tool for freshwater 

sediments followed the same procedures that were used to formulate the companion tool for 

marine and estuarine sediments (Schropp et al. 1990). In the first step of this process, 

existing data on the concentrations of sediment-associated metals at several hundred 

uncontaminated sites in the state were obtained, evaluated, and compiled in electronic 

database format. Florida Department of Environmental Protection, Florida Geological 

Survey (FGS), and USEPA represented the primary sources of these data. Next, a statistical 

test were applied to the data for each metal to determine if the data were normally 

distributed. For those metals that had normally distributed data, simple linear regressions 

of each metal and an appropriate geochemical normalizer were performed (using logtransformed data) and the 95% prediction limits were calculated for each regression equation. 

The regression plots provide the basis for interpreting new data on the concentrations of 

metals in sediments, such that anthropogenic enrichment of metal levels is indicated at sites 

with metals concentrations exceeding the upper 95% prediction limit (for one or more 

substances). 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
APPENDIX 1 – PAGE A-5 

A1.4 Derivation and Evaluation of Sediment Quality Assessment 

Guidelines 

Sediment chemistry data alone do not provide an adequate basis for assessing the hazards 

posed by sediment-associated contaminants to aquatic organisms. In addition, interpretive 

tools are required to determine if sediment-associated contaminants are present at 

concentrations which could, potentially, impair the designated uses of the aquatic 

environment. In this respect, effects-based SQAGs are needed to provide a scientifically 

defensible basis for evaluating the potential effects of sediment-associated contaminants on 

aquatic organisms. 

Numerical SQAGs for freshwater ecosystems were developed using the same general 

approach that was used to derive the SQAGsfor Florida’s coastal waters(MacDonald 1994). 

First, matching sediment chemistry and biological effects data from Florida and elsewhere 

in the southeast (i.e., Region IV) were acquired from a variety of sources. Next, each 

candidate data set were reviewed and critically evaluated to determine its scientific and 

technical validity. Data sets that were deemed to be acceptable were compiled in electronic 

database format and verified against the original data source. Subsequently, numerical 

SQAGs for each chemical of concern were developed using the consensus approach 

(MacDonald et al. 2000a). Finally, the SQAGs were evaluated to determine if they provide 

a reliable basis for predicting the presence and absence of adverse biological effects in 

Florida and the southeastern portion of the United States. 

A1.5 Formulation of an Integrated Framework for Assessing 

Freshwater Sediments 

Numerical SQAGs provide benchmarks for evaluating the potential effects of sedimentassociated contaminants on aquatic organisms. While numerical SQAGs provide essential 

tools for assessing the quality of freshwater sediments, decisions regarding the management 

of contaminated sediments should not be made based on exceedances of the SQAGs alone. 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
APPENDIX 1 – PAGE A-6 

Instead, the SQAGs should be used within an integrated framework which supports a more 

comprehensive assessment of sediment quality conditions. 

The integrated framework identifiesthe stepsthatshould be taken to conduct comprehensive 

assessments of sediment quality conditions in freshwater ecosystems. In addition, the 

integrated framework provides detailed guidance on each of the steps in the assessment 

process, including the following: 

• Collection of historical land and water use information; 

• Identification of contaminants and areas of concern; 

• Collection and evaluation of existing sediment chemistry data; 

• Collection of supplemental sediment chemistry data; 

• Assessment of the potential for biological effects of sediment-associated 

contaminants; 

• Evaluation of the probable origin of sediment-associated contaminants; 

• Collection of additional biological effects data; 

• Evaluation of the nature, severity, and areal extent of contamination; 

• Development and implementation of a remedial action plan; and, 

• Evaluation of the efficacy of remedial measures. 

The recommended framework will be designed to provide a consistent approach to assessing 

sediment quality in freshwater ecosystems. However, the framework will not replace 

accepted sediment testing protocols, such as developed for the ocean disposal of dredged 

material. Instead, it is intended to provide general guidance to support the sediment quality 

assessment process. 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
APPENDIX 2 – PAGE A-7 

Appendix 2 Criteria for Evaluating Candidate Data Sets 

A2.0 Introduction 

In recent years, the Great Lakes National Program Office (USEPA), United States Geological 

Survey, National Oceanic and Administration, Minnesota PollutionControl Agency, Florida 

Department ofEnvironmental Protection,BritishColumbia Ministry of Water, Air, and Land 

Protection, MacDonald Environmental Sciences Ltd., and EVS Consultants have been 

developing a database of matching sediment chemistry and sediment toxicity data to support 

evaluations of the predictive ability of numerical SQAGs in the Great Lakes Basin and 

elsewhere in North America (Field et al. 1999; USEPA 2000a; Crane et al. 2000). In 

addition, various project-specific databases have been developed to facilitate access to and 

analysis of data sets to support natural resource damage assessments and ecological risk 

assessments at sites with contaminated sediments (MacDonald and Ingersoll 2000; 

MacDonald et al. 2000a; Crane et al. 2000; MacDonald et al. 2001b; 2001c; Ingersoll et al. 

2001). The goal of these initiatives was to collect and collate the highest quality data sets 

for assessing sediment quality conditions at contaminated sites and evaluating numerical 

SQAGs. To assure that the data used in these assessments met the associated data quality 

objectives (DQOs), all of the candidate data sets were critically evaluated before inclusion 

in the database. However, the screening process was also designed to be flexible to assure 

that professional judgement could also be used when necessary in the evaluation process. 

In this way, it was possible to include as many data sets as possible and, subsequently, use 

them to the extent that the data quality and quantity dictate. 

The following criteria for evaluating candidate data sets were established in consultation with 

an ad hoc Science Advisory Group on Sediment Quality Assessment (which is comprised 

of representatives of federal, provincial, and state government agencies, consulting firms, and 

non-governmental organizations located throughout North America and elsewhere 

worldwide). These criteria are reproduced here because they provide useful guidance on the 

evaluation of data that have been generated to support sediment quality assessments. In 

addition, these criteria can be used to support the design of sediment sampling and analysis 

plans, and associated quality assurance project plans (see Volume II). 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
APPENDIX 2 – PAGE A-8 

A2.1 Criteria for Evaluating Whole-sediment, Pore-water, and 

Tissue Chemistry 

Data on the chemical composition of whole sediments, pore water, and biological tissues are 

of fundamental importance in assessments of sediment quality conditions. For this reason, 

it is essential to ensure that high quality data are generated and used to supportsuch sediment 

quality assessments. In this respect, data from individual studies are considered to be 

acceptable if: 

• Samples were collected from any sediment horizon (samples representing 

surficial sediments are most appropriate for assessing effects on sedimentdwelling organisms and other receptors, while samples of sub-surface sediments 

are appropriate for assessing potential effects on sediment-dwelling organisms 

and other receptors, should these sediments become exposed; ASTM 2001a; 

ASTM 2001d; USEPA 2000b); 

• Appropriate procedures were used for collecting, handling, and storing sediments 

(e.g., ASTM 2001b; 2001c; USEPA 2001) and samples of other media types; 

• The concentrations of a variety of all COPCs were measured in samples; 

• Appropriate analytical methods were used to generate chemistry data. The 

methods that are considered to be appropriate included USEPA approved 

methods, other standardized methods (e.g., ASTM methods, SW-846 methods), 

or methods that have been demonstrated to be equivalent or superior to standard 

methods; and, 

• Data quality objectives were met. The criteria that are used to evaluate data 

quality included: 

(i) the investigator indicated that DQOs had been met; 

(ii) analytical detection limits were reported and lower than the PECs 

(however, detection limits < TEC are preferred); 

(iii) accuracy and precision of the chemistry data were reported and within 

acceptable ranges for the method; 

(iv) sample contamination was not noted (i.e., analytes were not detected 

at unacceptable concentrations in method blanks); and, 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
APPENDIX 2 – PAGE A-9 

(v) the results of a detailed independent review indicated that the data 

were acceptable and/or professional judgement indicated that the data 

set was likely to be of sufficient quality to be used in the assessment 

(i.e., in conjunction with author communications and/or other 

investigations). 

A2.2 Criteria for Evaluating Biological Effects Data 

Data on the effects of contaminated sediments on sediment-dwelling organisms and other 

aquatic species provide important information for evaluating the severity and extent of 

sediment contamination. Data from individual studies are considered to be acceptable for 

this purpose if: 

• Appropriate procedures were used for collecting, handling, and storing sediments 

(e.g., ASTM 2001b; USEPA 2000b; 2001); Sediments were not frozen before 

toxicity tests were initiated (ASTM 2001a; 2001e); 

• The responses in the negative control and/or reference groups were within 

accepted limits(i.e., ASTM 2001a; 2001c; 2001d; 2001e; 2001f; 2001g; USEPA 

2000a); 

• Adequate environmental conditions were maintained in the test chambers during 

toxicity testing (i.e., ASTM 2001a; 2001d; USEPA 2000a); 

• The endpoint(s) measured were ecologically-relevant (i.e., likely to influence the 

organism's viability in the field) or indicative of ecologically-relevant endpoints; 

and, 

• Appropriate procedures were used to conduct bioaccumulation tests (ASTM 

2001c). 

Additional guidance is presented in USEPA (1994) for evaluating the quality of benthic 

community data generated as part of a sediment quality assessment. These criteria include 

collection ofreplicate samples,resorting at least 10% ofthe samples, and independent checks 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
APPENDIX 2 – PAGE A-10 

of taxonomic identification of specimens. Guidance is presented in USEPA (2000c) and in 

Schmidt et al. (2000) for evaluating the quality of fish health and fish community data. 

DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS 
APPENDIX 2 – PAGE A-11 

Appendix 3 Appendices References 

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ASTM (American Society for Testing and Materials). 2001b. Standard guide for collection, 

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ASTM (American Society for Testing and Materials). 2001c. Standard guide for 

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ASTM (American Society for Testing and Materials). 2001d. Standard guide for conducting 

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ASTM (American Society for Testing and Materials). 2001e. Standard guide for conducting 

acute toxicity tests on test materials with fishes, macroinvertebrates, and amphibians. 

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ASTM (American Society for Testing and Materials). 2001f. Standard guide for conducting 

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ASTM (American Society for Testing and Materials). 2001g. Standard guide for conducting 

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2001 Annual Book of Standards Volume 11.05. Philadelphia, Pennsylvania. 

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APPENDIX 2 – PAGE A-12 

Ingersoll C.G., D.D. MacDonald, N. Wang, J.L. Crane, L.J. Field, P.S. Haverland, N.E. 

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MacDonald, D.D., D.R. Moore, A. Pawlisz, D.E. Smorong, R.L. Breton, D.B. MacDonald, 

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DEVELOPMENT AND EVALUATION OF NUMERICAL SQAGS FOR FLORIDA INLAND WATERS