Procedures for the 

Derivation of Equilibrium 

Partitioning Sediment 

Benchmarks (ESBs) for the 

Protection of Benthic 

Organisms

Compendium of Tier 2 

Values for Nonionic Organics
 
 Recycled/Recyclable 

Printed with vegetable-based ink on 

paper that contains a minimum of 

50% post-consumer fiber content 

processed chlorine free 

EPA/600/R-02/016 

PB2008-107282 

March 2008 

 

Procedures for the Derivation of 

Equilibrium Partitioning Sediment Benchmarks (ESBs) 

for the Protection of Benthic Organisms: 

Compendium of Tier 2 Values for Nonionic Organics

Robert M. Burgess 

Walter J. Berry 

National Health and Environmental Effects Research Laboratory 

Atlantic Ecology Division 

Narragansett, RI 

David R. Mount 

Gerald T. Ankley 

National Health and Environmental Effects Research Laboratory 

Mid-Continent Ecology Division 

Duluth, MN 

D. Scott Ireland 

Great Lakes National Program Office 

Chicago, IL 

Dominic M. Di Toro 

University of Delaware, Newark, DE; HydroQual, Inc., 

Mahwah, NJ 

David J. Hansen 

 (formerly with U.S. EPA) 

Joy A. McGrath 

Laurie D. DeRosa 

HydroQual, Inc., Mahwah, NJ 

Heidi E. Bell 

F. James Keating 

Mary C. Reiley 

Office of Water, Washington, DC 

Christopher S. Zarba 

Office of Research and Development, Washington, DC 

U.S. Environmental Protection Agency 

Office of Research and Development 

National Health and Environmental Effects Research Laboratory 

Atlantic Ecology Division, Narragansett, RI

Mid-Continent Ecology Division, Duluth, MN
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

ii 

Notice

The Office of Research and Development (ORD) has produced this compendium document to provide 

procedures for the derivation of equilibrium partitioning sediment benchmarks (ESBs) for several 

nonionic organic chemicals. ESBs may be useful as a complement to existing sediment assessment tools. 

This document should be cited as: 

U.S. EPA. 2008. Procedures for the Derivation of Equilibrium Partitioning Sediment Benchmarks 

(ESBs) for the Protection of Benthic Organisms: Compendium of Tier 2 Values for Nonionic 

Organics. EPA-600-R-02-016. Office of Research and Development. Washington, DC 20460 

This document, and the other ESB documents, can also be found in electronic format at the following web 

address: 

http://www.epa.gov/nheerl/publications/ 

The information in this document has been funded wholly by the U.S. Environmental Protection Agency. 

It has been subject to the Agency’s peer and administrative review, and it has been approved for 

publication as an EPA document. Mention of trade names or commercial products does not constitute 

endorsement or recommendation for use. 

Abstract

This equilibrium partitioning sediment benchmark (ESB) document describes procedures to derive 

concentrations for 32 nonionic organic chemicals in sediment which are protective of the presence of 

freshwater and marine benthic organisms. The equilibrium partitioning (EqP) approach was chosen 

because it accounts for the varying biological availability of chemicals in different sediments and allows 

for the incorporation of the appropriate biological effects concentration. This provides for the derivation 

of benchmarks that are causally linked to the specific chemical, applicable across sediments, and 

appropriately protective of benthic organisms. 

EqP can be used to calculate ESBs for any toxicity endpoint for which there are water-only toxicity data; 

it is not limited to any single effect endpoint. For the purposes of this document, ESBs for 32 nonionic 

organic chemicals, including several low molecular weight aliphatic and aromatic compounds, pesticides, 

and phthalates, were derived using Final Chronic Values (FCV) from Water Quality Criteria (WQC) or 

Secondary Chronic Values (SCV) derived from existing toxicological data using the Great Lakes Water 

Quality Initiative (GLI) or narcosis theory approaches. These values are intended to be the concentration 

of each chemical in water that is protective of the presence of aquatic life. For nonionic organic 

chemicals demonstrating a narcotic mode of action, ESBs derived using the GLI approach specifically for 

freshwater organisms were assumed to also be protective of marine organisms. This assumption is based 

on the similar sensitivity of freshwater and marine organisms to narcotic chemicals like some of the 

nonionic organics in this document. For this reason, SCVs derived using narcosis theory are protective of 

both freshwater and marine organisms. For chemicals with more specific modes of action, freshwater and 

marine organisms were not assumed to be similar in sensitivity, and separate freshwater and marine ESBs 

were derived as the available data allowed. Because of the lack of a comprehensive toxicity data set and 

other reasons discussed in this document in detail, values derived here are considered Tier 2 ESBs 

(ESBTier2). The presentation of these ESBs is such that updated values could be calculated as new toxicity 

data become available. 
Abstract 

iii 

The ESBTier2 is derived by multiplying the FCV or SCV by a chemical’s KOC, yielding the concentration 

in sediment that should provide the same level of protection that the FCV or SCV provides in water. The 

ESBTier2 should be interpreted as a chemical concentration below which adverse effects are not expected. 

At concentrations above the ESBTier2, and assuming equilibrium between phases, effects may occur with 

increasing severity as the degree of exceedance increases. The document also includes examples 

demonstrating the calculation of conventionally-derived and narcosis-based ESBs that discuss an 

approach for addressing mixtures of narcotic chemicals. 

ESB documents have also been developed for two pesticides (endrin, dieldrin), polycyclic aromatic 

hydrocarbon (PAH) mixtures, and metal mixtures. 

The ESBs do not intrinsically consider the antagonistic, additive or synergistic effects of other sediment 

contaminants in combination with the individual nonionic organic chemicals discussed in this document 

or the potential for bioaccumulation and trophic transfer of these chemicals to aquatic life, wildlife or 

humans. However, for narcotic chemicals, an approach for considering the toxicity of mixtures is 

presented. Important assumptions and considerations for applying and interpreting the ESBs are also 

discussed.
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

iv 

Foreword 

Under the Clean Water Act (CWA), the U.S. Environmental Protection Agency (EPA) and the States 

develop programs for protecting the chemical, physical, and biological integrity of the Nation’s waters. 

To support the scientific and technical foundations of the programs, EPA’s Office of Research and 

Development has conducted efforts to develop and publish equilibrium partitioning sediment benchmarks 

(ESBs) for some of the 65 toxic pollutants or toxic pollutant categories. Toxic contaminants in bottom 

sediments of the Nation’s lakes, rivers, wetlands, and coastal waters create the potential for continued 

environmental degradation even where water column contaminant levels meet applicable water quality 

standards. In addition, contaminated sediments can lead to water quality impacts, even when direct 

discharges to the receiving water have ceased. 

The ESBs and associated methodology presented in this document provide a means to estimate the 

concentrations of a substance that may be present in sediment while still protecting benthic organisms 

from the effects of that substance. These benchmarks are applicable to a variety of freshwater and marine 

sediments because they are based on the biologically available concentration of the substance in the 

sediments. These ESBs are intended to provide protection to benthic organisms from direct toxicity due 

to this substance. In some cases, the additive toxicity for specific classes of toxicants (e.g., metal 

mixtures or polycyclic aromatic hydrocarbon mixtures) is addressed. The ESBs do not intrinsically 

consider the antagonistic, additive or synergistic effects of other sediment contaminants in combination 

with the individual nonionic organic chemicals discussed in this document or the potential for 

bioaccumulation and trophic transfer of these chemicals to aquatic life, wildlife or humans. However, for 

narcotic chemicals, the ESBs can be used in a framework to evaluate the toxicity of mixtures. 

ESBs may be useful as a complement to existing sediment assessment tools, to help evaluate the extent of 

sediment contamination, to identify chemicals causing toxicity, and to serve as targets for pollutant 

loading control measures. Both types of ESBs, Tier 1 and Tier 2, are intended for similar applications 

with the user’s understanding that, because of limited data availability, Tier 2 ESBs are likely to have 

greater uncertainty associated with them as compared to Tier 1 ESBs. As new, high quality toxicological 

and geochemical data becomes available, it is encouraged that the ESB values are revised and updated. 

This document provides technical information to EPA Program Offices, including Superfund, Regions, 

States, the regulated community, and the public. Decisions about risk management are the purview of 

individual regulatory programs, and may vary across programs depending upon the regulatory authority 

and goals of the program. For this reason, each program will have to decide whether the ESB approach is 

appropriate to that program and, if so, how best to incorporate this technical information into that 

program's assessment process. While it was necessary to choose specific parameters for the purposes of 

this document, it is important to realize that the basic science underlying this document can be adapted to 

a range of risk management goals by adjusting the input parameters. At the same time, the ESBs do not 

substitute for the CWA or other EPA regulations, nor are they regulation. Thus, they cannot impose 

legally binding requirements on EPA, States, or the regulated community. EPA and State decision 

makers retain the discretion to adopt approaches on a case-by-case basis that differ from this technical 

information where appropriate. It is recommended that the ESBs not be used alone but with other 

sediment assessment methods to make informed management decisions. EPA may change this technical 

information in the future. This document has been reviewed by EPA’s Office of Research and 

Development (Atlantic Ecology Division, Narragansett, RI), undergone an external peer review, and 

approved for publication.

This is contribution AED-02-052 of the Office of Research and Development National Health and 

Environmental Effects Research Laboratory’s Atlantic Ecology Division. 

Front cover image provided by Wayne R. Davis and Virginia Lee.
Contents 

v 

Contents

Notice ...................................................................................................................................... ii 

Abstract ................................................................................................................................... ii 

Foreword ................................................................................................................................iv 

Acknowledgements ............................................................................................................... vii 

Executive Summary ............................................................................................................. viii 

Glossary of Abbreviations........................................................................................................x 

Section 1 

Introduction .......................................................................................................................... 1-1 

1.1 General Information.................................................................................................................1-1 

1.2 Development of Tier 2 Sediment Benchmarks ........................................................................1-2 

1.3 Application of Sediment Benchmarks .....................................................................................1-5 

1.4 Data Quality Assurance ...........................................................................................................1-5 

1.5 Overview..................................................................................................................................1-6 

Section 2 

Derivation of Equilibrium Partitioning Sediment Benchmark Effects Concentrations....... 2-1 

2.1 General Introduction................................................................................................................2-1 

2.2 Determination of KOW Values..................................................................................................2-1 

2.3 Selection and Determination of Aquatic Toxicity Values.......................................................2-2 

 2.3.1 Derivation of Conventional Chronic Toxicity Values................................................2-2 

 2.3.2 Derivation of Narcotic Chronic Toxicity Values........................................................2-3 

2.4 Comparison of Narcosis and Conventional Chronic Toxicity Values .....................................2-4 

2.5 Selection of New and Alternate Aquatic Toxicity Values .......................................................2-6 

Section 3 

Calculation of Equilibrium Partitioning Sediment Benchmarks.......................................... 3-1 

3.1 Overview of EqP Methodology ...............................................................................................3-1 

3.2 Derivation of Tier 2 Equilibrium Partitioning Sediment Benchmarks.....................................3-1 

3.3 Effects of Low KOW on Derivation of ESBTier2 ........................................................................3-7 

3.4 Conversion to Dry Weight Concentration .............................................................................3-11

Section 4 

Sediment Benchmark Values: Application and Interpretation ............................................ 4-1

4.1 Benchmarks .............................................................................................................................4-1 

4.2 Considerations in the Application and Interpretation of ESBs................................................4-1 

4.2.1 Relationship of ESBTier2 to Expected Effects.............................................................4-1 

4.2.2 Use of EqP to Develop Alternative Benchmarks.......................................................4-2 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

vi 

4.2.3 Influence of Unusual Forms of Sediment Organic Carbon .......................................4-2 

4.2.4 Relationship to Risks Mediated through Bioaccumulation and Trophic Transfer ....4-2 

4.2.5 Exposures to Chemical Mixtures...............................................................................4-3 

4.2.6 Interpreting ESBTier2s in Combination with Toxicity Tests.......................................4-4 

4.2.7 Effects of Disequilibrium Conditions........................................................................4-5 

 4.3 Example Application of ESBTier2s Using Conventional and Narcosis 

Approaches and EqP-based Interpretation........................................................................4- 7 

Section 5 

References............................................................................................................................ 5-1 

Appendix A......................................................................................................................... A-1 

Tables 

Table 3-1 Chronic toxicity values (μg/L), SCVs and FCVs, used to derive Tier 2 

 ESBs based on conventional and narcotic approaches.....................................................3-3 

Table 3-2 Tier 2 ESBs (μg/gOC) based on toxicity values derived using conventional 

 and narcosis approaches (from Table 3-1). ......................................................................3-4 

Table 3-3 Example calculations of conventional freshwater standard and modified 

ESBTier2DRY WT values (μg/g dry weight) for four chemicals under 

different fOC and fSolids conditions ...................................................................................3-10 

Table 3-4 Example Tier 2 ESBs (μg/g dry weight) using freshwater conventional (C) 

and narcosis (N) approaches normalized to various total organic 

carbon (TOC) concentrations.........................................................................................3-12 

Table 4-1 Example application of ESBTier2 values with several nonionic organic chemicals using 

 conventional and narcosis approaches..................................................................... 4-9 

Figures 

Figure 2-1 Comparison of narcosis-based and conventionally-derived chronic toxicity values.. .....2-7 

Figure 2-2 Comparison of observed LC50 values used in the calculation of secondary chronic 

 values and LC50 values predicted using narcosis theory as described by 

 Di Toro et al. (2000) ........................................................................................................2-8 

Figure 2-3 Comparison of observed LC50 values used in the calculation of secondary chronic 

 values and LC50 values predicted using narcosis theory as described by 

 Di Toro et al. (2000).. ......................................................................................................2-9 

Figure 2-4 Comparison of observed LC50 values used in the calculation of secondary chronic 

 values and LC50 values predicted using narcosis theory as described by 

 Di Toro et al. (2000)..... ................................................................................................2-10 

Figure 2-5 Comparison of observed LC50 values used in the calculation of secondary chronic 

 values and LC50 values predicted using narcosis theory as described by 

 Di Toro et al. (2000) ......................................................................................................2-11 

Figure 3-1 Comparison of ESBs calculated using the standard equation 

 (Equation 3-3) and modified equations which include the effects of low KOW 

(Equations 3-5 and 3-6) ............................................................................................. 3-9 
Acknowledgements 

vii 

Acknowledgements

Coauthors

Robert M. Burgess*,

** U.S. EPA, NHEERL, Atlantic Ecology Division, Narragansett, RI 

Walter J. Berry U.S. EPA, NHEERL, Atlantic Ecology Division, Narragansett, RI 

David R. Mount* U.S. EPA, NHEERL, Mid-Continent Ecology Division, Duluth, MN 

Gerald T. Ankley U.S. EPA, NHEERL, Mid-Continent Ecology Division, Duluth, MN 

D. Scott Ireland* U.S. EPA, Great Lakes National Program Office, Chicago, IL 

Dominic M. Di Toro University of Delaware, Newark, DE; HydroQual, Inc., Mahwah, NJ 

David J. Hansen formerly with U.S. EPA 

Joy A. McGrath HydroQual, Inc., Mahwah, NJ 

Laurie D. De Rosa HydroQual, Inc., Mahwah, NJ 

Heidi E. Bell U.S. EPA, Office of Water, Washington, DC 

F. James Keating U.S. EPA, Office of Water, Washington, DC 

Mary C. Reiley U.S. EPA, Office of Water, Washington, DC 

Christopher S. Zarba U.S. EPA, Office of Research and Development, Washington, DC 

Significant Contributors to the Development of the Approach and Supporting Science

Gerald T. Ankley U.S. EPA, NHEERL, Mid-Continent Ecology Division, Duluth, MN 

Dominic M. Di Toro University of Delaware, Newark, DE; HydroQual, Inc., Mahwah, NJ 

David J. Hansen formerly with U.S. EPA 

David R. Mount U.S. EPA, NHEERL, Mid-Continent Ecology Division, Duluth, MN 

Richard C. Swartz formerly with U.S. EPA 

Christopher S. Zarba U.S. EPA, Office of Research and Development, Washington, DC 

Technical Support and Document Review

Patricia A. DeCastro Computer Sciences Corporation, Narragansett, RI 

Phyllis Fuchsman ARCADIS, Cleveland, OH 

Christopher Ingersoll U.S. Geological Survey, Columbia, MO 

Susan Kane-Driscoll Exponent, Inc., Maynard, MA 

Guilherme Lotufo U.S. Army Corps of Engineers, Vicksburg, MS 

James Meador NOAA, Seattle, WA 

Monique M. Perron Harvard School of Public Health, Boston, MA 

Christine L. Russom U.S. EPA, NHEERL, Mid-Continent Ecology Division, Duluth, MN 

*Principal U.S. EPA contacts 

**Series Editor 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

viii 

Executive Summary

This equilibrium partitioning sediment benchmark (ESB) document describes procedures to derive 

concentrations of 32 nonionic organic chemicals in sediment which are protective of the presence of 

freshwater and marine benthic organisms. The equilibrium partitioning (EqP) approach was chosen 

because it accounts for the varying biological availability of chemicals in different sediments and allows 

for the incorporation of the appropriate biological effects concentration (U.S. EPA 2003a). This provides 

for the derivation of benchmarks that are causally linked to the specific chemical, applicable across 

sediments, and appropriately protective of benthic organisms. 

EqP theory holds that a nonionic chemical in sediment partitions between sediment organic carbon, 

interstitial (pore) water and benthic organisms. At equilibrium, if the concentration in any one phase is 

known, then the concentrations in the others can be predicted. The ratio of the concentration in water to 

the concentration in organic carbon is termed the organic carbon-water partition coefficient (KOC), which 

is a constant for each chemical. The ESB Technical Basis Document (U.S. EPA 2003a) demonstrates that 

biological responses of benthic organisms to nonionic organic chemicals in sediments are different across 

sediments when the sediment concentrations are expressed on a dry weight basis, but similar when 

expressed on a μg chemical/g organic carbon basis (μg/gOC). Similar responses were also observed across 

sediments when interstitial water concentrations were used to normalize biological availability. The 

Technical Basis Document (U.S. EPA 2003a) further demonstrates that if the effect concentration in 

water is known, the effect concentration in sediments on a μg/gOC basis can be accurately predicted by 

multiplying the effect concentration in water by the chemical’s KOC. 

EqP can be used to calculate ESBs for any toxicity endpoint for which there are water-only toxicity data; 

it is not limited to any single effect endpoint. For the purposes of this document, ESBs for 32 nonionic 

organic chemicals, including several low molecular weight aliphatic and aromatic compounds, pesticides, 

and phthalates, were derived using Final Chronic Values (FCV) from Water Quality Criteria (WQC) or 

Secondary Chronic Values (SCV) derived from existing toxicological data using the Great Lakes Water 

Quality Initiative (GLI) or narcosis theory approaches. These values are intended to be the concentration 

of each chemical in water that is protective of the presence of aquatic life. For nonionic organic 

chemicals demonstrating a narcotic mode of action, ESBs derived using the GLI approach specifically for 

freshwater organisms were assumed to also be protective of marine organisms. This assumption is based 

on the similar sensitivity of freshwater and marine organisms to narcotic chemicals like some of the 

nonionic organics in this document. For this reason, SCVs derived using narcosis theory are presumed to 

be protective of both freshwater and marine organisms. For chemicals with other specific modes of 

action, freshwater and marine organisms were not assumed to have similar sensitivity and separate 

freshwater and marine ESBs were derived as the available data allowed. For pesticides, only freshwaterand marine-specific FCVs or SCVs were used to derive ESBs because of likely differences between 

freshwater and marine organism sensitivities. Similarly, for the phthalates, which are not thought to be 

narcotic, SCVs were derived using the GLI approach and considered protective of freshwater species 

only. Because of the lack of a comprehensive toxicity data set and other reasons discussed in this 

document in detail, values derived here are considered Tier 2 ESBs (ESBTier2). Ancillary analyses 

conducted as part of this derivation suggest that the sensitivity of benthic/epibenthic organisms is not 

significantly different from pelagic organisms; for this reason, the FCV or SCV and the resulting ESBTier2

should be fully applicable to benthic organisms. The ESBTier2 is derived by multiplying the FCV or SCV 

by a chemical’s KOC, yielding the concentration in sediment that should provide the same level of 

protection that the FCV or SCV provides in water. The ESBTier2 should be interpreted as a chemical 

concentration below which adverse effects are not expected. At concentrations above the ESBTier2, 

assuming equilibrium between phases, effects may occur with increasing severity as the degree of 
Executive Summary 

ix 

exceedance increases. A sediment-specific site assessment (e.g., toxicity testing) would provide further 

information on chemical bioavailability and the expectation of toxicity relative to the ESB Tier2 along with 

associated uncertainties. The document also includes examples demonstrating the calculation of 

conventionally-derived and narcosis-based ESBs that discuss an approach for addressing mixtures of 

narcotic chemicals. 

As discussed, while this document uses the FCV or SCV, the EqP methodology can be used by 

environmental managers to derive a benchmark with any desired level of protection, so long as the wateronly concentration affording that level of protection is known. Therefore, the resulting benchmark can be 

species or site-specific if the corresponding water-only information is available. For example, if a wateronly effects concentration is known for an economically important benthic species, that value could be 

used to derive a sediment benchmark commensurate with the protection of that species and endpoint. 

Another way to increase the site-specificity of an ESB would be to incorporate information on sedimentspecific partitioning of chemicals, particularly for sites where the composition and partitioning behavior 

of the sediment organic carbon may be substantially different than for typical diagenic organic matter (see 

U.S. EPA 2003b). However, it should also be noted that the ability to predict partitioning based on 

additional partitioning factors like black carbon is still evolving and may serve to decrease partitioningrelated uncertainties in future applications. 

The ESBs do not intrinsically consider the antagonistic, additive or synergistic effects of other sediment 

contaminants in combination with the individual nonionic organic chemicals discussed in this document 

or the potential for bioaccumulation and trophic transfer of these chemicals to aquatic life, wildlife or 

humans. However, for narcotic chemicals, ESB values may be used in a framework to evaluate the 

potential effects of chemical mixtures. Consistent with the recommendations of EPA’s Science Advisory 

Board, publication of these documents does not imply the use of ESBs as stand-alone, pass-fail criteria for 

all applications; rather, ESB exceedances could be used to trigger the collection of additional assessment 

data. Similarly, ESBs are supportive of recent recommendations by Wenning et al. (2005), to apply a 

weight of evidence approach when evaluating contaminated sediments. These ESBs apply only to 

sediments having ≥ 0.2% total organic carbon by dry weight and nonionic organic chemicals with log 

KOWs ≥ 2. 

Tier 1 and Tier 2 ESB values were developed to reflect differing degrees of data availability and 

uncertainty. Tier 1 ESBs have been derived for the nonionic organic pesticides endrin and dieldrin (U.S. 

EPA 2003c,d), polycyclic aromatic hydrocarbon (PAH) mixtures (U.S. EPA 2003e), and metal mixtures 

(U.S. EPA 2005a). Tier 2 ESBs for several nonionic organic chemicals for freshwater and marine 

sediments are reported in this document. Both types of ESBs are intended for similar applications with 

the user’s understanding that Tier 2 ESBs are likely to have greater uncertainty associated with them as 

compared to Tier 1 ESBs. As new, high quality toxicological and geochemical data becomes available, 

recalculation of the Tier 2 ESB values is encouraged. 

 

Uncertainties associated with ESBTier2 values are discussed in detail through-out this document. They 

include unknown effects of antagonism, synergism and additivity, occurrence of chemical disequilibria, 

and presence of unusual types of sedimentary carbon, like black carbon, and large particles. Uncertainties 

for the ESBTier2 values can be reduced by conducting additional acute and chronic water-only and spiked 

sediment toxicity tests to refine water-only effect concentrations and confirm predictions of sediment 

toxicity, respectively.
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

x 

Glossary of Abbreviations 

ACR Acute–chronic ratio 

AQUIRE Aquatic Toxicity Information Retrieval 

ASTER ASsessment Tools for the Evaluation of Risk 

ASTM American Society for Testing and Materials 

CL* Critical lipid concentration 

CAS Chemical Abstracts Service 

CWA Clean Water Act 

DOC Dissolved organic carbon 

EC50 Chemical concentration estimated to cause adverse effects to 50% of the test 

organisms within a specified time period 

ECOTOX ECOTOXicology databases 

EMAP Environmental Monitoring and Assessment Program 

EPA United States Environmental Protection Agency 

EqP Equilibrium partitioning 

ESB Equilibrium partitioning Sediment Benchmark; for nonionic organics, this term 

usually refers to a value that is organic carbon–normalized (more formally 

ESBOC) unless otherwise specified 

ESBDRY WT Equilibrium partitioning Sediment Benchmark; for nonionic organics, 

expressed on a sediment dry weight basis 

ESBOC Equilibrium partitioning Sediment Benchmark; for nonionic organics, 

expressed on an organic carbon basis 

ESBTier2 Equilibrium partitioning Sediment Benchmark; for nonionic organics, derived 

using Tier 2 data; specifically, the values in this document 

ESB Tier2DRY WT Equilibrium partitioning Sediment Benchmark; for nonionic organics, derived 

using Tier 2 data, expressed on a sediment dry weight basis 

ESBTier2OC Equilibrium partitioning Sediment Benchmark; for nonionic organics, derived 

using Tier 2 data; expressed on organic carbon basis 
Glossary 

xi 

ESBTU Equilibrium Partitioning Sediment Benchmark Toxic Units 

FACR Final acute–chronic ratio 

FAV Final acute value 

FCV Final chronic value 

fOC Fraction of organic carbon in sediment 

fSolids Fraction of solids in sediment 

GLI Great Lakes Water Quality Initiative 

GMAV Genus mean acute value 

GMCV Genus mean chronic value 

gOC Gram organic carbon 

HECD U.S. EPA, Health and Ecological Criteria Division 

IC50 Chemical concentration estimated to cause some form of inhibition to 50% 

of the test organisms within a specified time period 

KBC Black carbon-water partition coefficient 

KOC Organic carbon–water partition coefficient 

KOW Octanol–water partition coefficient 

KP Sediment–water partition coefficient 

LC50 Chemical concentration estimated to be lethal to 50% of test organisms within 

a specified time period 

MC Moisture content 

MDR Minimum data requirement 

NHEERL U.S. EPA, National Health and Environmental Effects Research Laboratory 

OECD Organization for Economic Cooperation and Development 

ORD U.S. EPA, Office of Research and Development 

OST U.S. EPA, Office of Science and Technology 

OSWER U.S. EPA, Office of Solid Waste and Emergency Response 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

xii 

PAH Polycyclic aromatic hydrocarbon 

PM Particulate matter 

QSAR Quantitative structure-activity relationship 

SACR Secondary acute-chronic ratio 

SAF Secondary acute factor 

SAV Secondary acute value 

SCV Secondary chronic value 

SCVN Secondary chronic value based on narcosis theory 

SMACR Species mean acute–chronic ratio 

SMAV Species mean acute value 

SPARC SPARC Performs Automated Reasoning in Chemistry 

STORET EPA’s computerized database for STOrage and RETrieval of water-related data 

TIE Toxicity Identification Evaluation 

TOC Total organic carbon 

WQC Water Quality Criteria 
Introduction 

1-1 

Section 1 

Introduction 

1.1 General Information 

 Toxic pollutants in bottom sediments of the 

Nation’s lakes, rivers, wetlands, estuaries, and 

marine coastal waters create the potential for 

continued environmental degradation even 

where water column concentrations comply with 

established WQC. In addition, contaminated 

sediments can be a significant pollutant source 

that may cause water quality degradation to 

persist, even when other pollutant sources are 

stopped (Larsson 1985, Salomons et al. 1987, 

Burgess and Scott 1992). The absence of 

defensible equilibrium partitioning sediment 

benchmarks (ESBs) make it difficult to 

accurately assess the extent of the ecological 

risks of contaminated sediments and to identify, 

prioritize, and implement appropriate cleanup 

activities and source controls (U.S. EPA 1997a, 

b, c, 2004). 

 As a result of the need for a procedure to 

assist regulatory agencies in making decisions 

concerning contaminated sediment problems, the 

U.S. Environmental Protection Agency (EPA) 

Office of Water Office of Science and 

Technology, Health and Ecological Criteria 

Division (OST/HECD) and Office of Research 

and Development National Health and 

Environmental Effects Research Laboratory 

(ORD/NHEERL) established a research team to 

review alternative approaches (Chapman 1987). 

 All of the approaches reviewed had both 

strengths and weaknesses, and no single 

approach was found to be applicable for the 

derivation of guidelines in all situations (U.S. 

EPA 1989, 1993). The equilibrium partitioning 

(EqP) approach was selected for nonionic 

organic chemicals because it presented the 

greatest promise for generating defensible, 

national, numeric chemical-specific benchmarks 

applicable across a broad range of sediment 

types. The three principal observations that 

underlie the EqP approach to establishing 

sediment benchmarks are as follows: 

1. The concentrations of nonionic organic 

chemicals in sediments, expressed on an 

organic carbon basis, and in interstitial 

waters correlate to observed biological 

effects on sediment-dwelling organisms 

across a range of sediments. 

2. Partitioning models can relate sediment 

concentrations for nonionic organic 

chemicals on an organic carbon basis to 

freely-dissolved concentrations in interstitial 

water. 

3. The distribution of sensitivities of benthic 

organisms to chemicals is similar to that of 

water column organisms; thus, the currently 

established water quality criteria (WQC) 

final chronic values (FCV) or secondary 

chronic values (SCV) can be used to define 

the acceptable effects concentration of a 

chemical freely-dissolved in interstitial 

water. 

 The EqP approach, therefore, assumes that 

(1) the partitioning of the chemical between 

sediment organic carbon and interstitial water is 

at or near equilibrium; (2) the concentration in 

either phase can be predicted using appropriate 

partition coefficients and the measured 

concentration in the other phase (assuming the 

freely-dissolved interstitial water concentration 

can be accurately measured); (3) organisms 

receive equivalent exposure from water-only 

exposures or from any equilibrated phase: either 

from interstitial water via respiration, from 

sediment via ingestion or other sedimentintegument exchange, or from a mixture of 

exposure routes; (4) for nonionic chemicals, 

effect concentrations in sediments on an organic 

carbon basis can be predicted using the organic 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

1-2 

carbon partition coefficient (KOC) and effects 

concentrations in water; (5) the FCV or SCV 

concentration is an appropriate effects 

concentration for freely-dissolved chemical in 

interstitial water; and (6) ESBs derived as the 

product of the KOC and FCV or SCV are 

protective of benthic organisms. ESB 

concentrations presented in this document are 

expressed as μg chemical/g sediment organic 

carbon (μg/gOC) and not on an interstitial water 

basis because (1) interstitial water is difficult to 

sample and (2) significant amounts of the 

dissolved chemical may be associated with 

dissolved organic carbon; thus, total 

concentrations in interstitial water may 

overestimate exposure. 

1.2 Development of Tier 2 Sediment 

 Benchmarks 

 Aquatic toxicity values used in this 

compendium (Table 3-1) were developed in two 

possible ways: (1) conventionally using Water 

Quality Criteria (WQC) (when available) and 

Great Lakes Water Quality Initiative (GLI) 

generated values, and (2) narcosis theory. This 

compendium consists of Tier 2 ESBs for 32 

chemicals including several low molecular 

weight aliphatic and aromatic compounds, 

pesticides and phthalates. Both types of ESBs, 

Tier 1 and Tier 2, are intended for similar 

applications with the user’s understanding that 

Tier 2 ESBs are likely to have greater 

uncertainty associated with them as compared to 

Tier 1 ESBs. See Section 1.3 for further 

discussion of Tier 1 and Tier 2 ESBs. 

 The ESB values are reported in Tables 3-2 

and 3-4. In the References section, along with 

the cited sources, the reference U.S. EPA 

(2001a) contains the sources and tables of data 

used to derive some of the Tier 2 ESBs. 

 For many of the chemicals in this document, 

the Tier 2 ESBs were developed using the GLI 

(1995) methodology for obtaining secondary 

chronic values (SCVs). As described in Section 

2 and Appendix A, this methodology uses 

adjustment factors to allow derivation of chronic 

values when fewer toxicity data are available 

than are required under the National Ambient 

Water Quality Criteria methodology (Stephan et 

al. 1985). Because of these adjustment factors, 

SCVs are generally expected to be lower than 

would be likely if a complete data set were 

available. Consequently, Tier 2 ESBs would 

tend to be lower (i.e., be more conservative) 

compared to the Tier 1 ESBs developed 

exclusively from FCVs. The degree of 

conservatism will be a function of the database 

used to derive the SCVs. Further, the presence 

of these chemicals in mixtures will also affect 

the conservatism (see Section 4.2.5). The SCVs 

used in calculating most Tier 2 ESBs were 

derived using toxicity data primarily for 

freshwater species. In the toxicity data 

evaluation for the PAH mixtures ESB (U.S. EPA 

2003e), there was no significant difference in 

sensitivity between freshwater and saltwater 

species when distributions of data for all species 

were compared using the approximate 

randomization (AR) method (Noreen 1989, U.S. 

EPA 2003e). Like PAHs, many of the Tier 2 

ESB chemicals are also narcotics; from this, it is 

reasonable to presume that these ESBs would be 

applicable to both freshwater and saltwater 

sediments. 

 For pesticides, there are likely to be 

differences between FCVs or SCVs developed 

for freshwater and saltwater organisms (e.g., 

Thursby 1990, U.S. EPA 1980a,b, 1986, 1996, 

2005b). Therefore, applying Tier 2 ESB values 

for pesticides derived using the GLI 

methodology to saltwater sediments is not 

recommended and would result in increased 

uncertainties. To address these uncertainties, 

Tier 2 ESBs are presented for pesticides for both 

freshwater and marine organisms based on FCVs 

from WQC (when available) or SCVs. 

Similarly, SCVs developed for phthalates in this 

document using the GLI approach were assumed 

to be protective only of freshwater species. 

Unlike the pesticides, WQC FCVs were not 

available for either freshwater or marine species 

for the phthalates. 

 

 As noted, many of the chemicals for which 

EPA has developed Tier 2 ESBs are known or 

suspected to affect aquatic organisms by a 
Introduction 

1-3 

narcotic mode of action (Russom et al. 1997). 

For these compounds, Tier 2 ESBs were also 

derived using the narcosis theory approach 

applied to develop ESBs for PAH mixtures (U.S. 

EPA 2003e). In contrast to the conventional 

GLI approach, the narcosis approach does not 

apply adjustment factors. As a consequence, 

narcosis-based values are often larger in 

magnitude compared to the GLI-derived values 

(discussed further in Section 2). In Table 3-1, 

narcosis-based SCVs are also reported for 

chemicals with other modes of actions in 

addition to narcosis (i.e., pesticides and 

phthalates). For these chemicals, potency via 

narcosis is generally small compared to the more 

specific mode(s) of action which would result in 

narcosis-based ESB values being considerably 

higher than the conventionally-derived values. 

Accepting these approaches for developing 

chronic toxicity values and the associated 

uncertainties, Tier 2 ESB values for narcotic 

chemicals, pesticides and phthalates should be 

meaningful interpretive tools for marine 

sediments as well as freshwater sediments 

(Tables 3-2 and 3-4). 

 With regard to using narcosis to derive ESB 

values, the approach applied in this document 

and U.S. EPA (2003e) uses narcosis theory to 

predict acute toxicity and then empirically based 

acute-chronic ratios (ACRs) to calculate chronic 

toxicity values. These chronic values (i.e., 

SCVs) are then used to calculate the ESBs. 

Strengthening our mechanistic understanding of 

the link between acute toxicity based on narcosis 

and chronic effects potentially caused by other 

forms of toxicity is an active area of research 

(e.g., Incardona et al. 2006). Users of this 

document should recognize deficiencies in our 

understanding of this link may introduce 

uncertainties into the narcosis based estimates of 

ESB values. 

 Regardless of the approach used to derive the 

Tier 2 toxicity values, these concentrations have 

been generated on a single chemical basis; that 

is, the benchmark addresses effects for that 

chemical only and does not consider additive 

effects from other chemicals that may be present 

in sediment. For that reason, as the number and 

concentration of other chemicals present 

increases, single chemical benchmarks would be 

expected to provide a lesser degree of protection 

than a mixtures-based approach. EPA has not 

yet recommended an approach for summing the 

particular chemicals in this document, but 

approaches for assessing the toxicity of narcotic 

mixtures in sediments have been published (Di 

Toro and McGrath 2000, DiToro et al. 2000), 

and the Agency has developed methodologies 

for deriving ESBs for mixtures of PAHs (U.S. 

EPA 2003e) and metals (U.S. EPA 2005a). The 

approach discussed in U.S. EPA (2003e) for 

addressing the toxicity of mixtures of PAHs may 

be useful for those interested in combining the 

toxic effects of narcotic chemicals in this 

compendium (see Section 4.3 for an example). 

 Values similar to some of those reported in 

this document were used to evaluate data for 

EPA’s 1997 and 2004 National Sediment 

Quality Survey reports to Congress (USEPA 

1997a,b,c, 2004). In those documents, the 

values were called sediment quality advisory 

levels (SQALs). These SQALs for nonionic 

organic chemicals were also included as “Ecotox 

Thresholds” in a 1996 ECO Update bulletin 

published by EPA’s Office of Solid Waste and 

Emergency Response (OSWER) (U.S. EPA 

1996). In some cases, the Tier 2 ESBs in this 

document may differ from the SQALs and 

Ecotox Thresholds because of different data 

sources. Further, the SQALs and Ecotox 

Thresholds did not include narcosis-based 

chronic toxicity values. 

 Sediment benchmarks generated using the 

EqP approach are suitable for use in providing 

technical information to regulatory agencies 

because they are: 

1. Numeric values 

2. Chemical specific 

3. Applicable to most sediments 

4. Predictive of biological effects 

5. Protective of benthic organisms 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

1-4 

 ESBs are derived using the available 

scientific data to assess the likelihood of 

significant environmental effects to benthic 

organisms from chemicals in sediments in the 

same way that the WQC are derived using the 

available scientific data to assess the likelihood 

of significant environmental effects to organisms 

in the water column. As such, ESBs are 

intended to protect benthic organisms from the 

effects of chemicals associated with sediments 

and, therefore, only apply to sediments 

permanently inundated with water, to intertidal 

sediment, and to sediments inundated 

periodically for durations sufficient to permit 

development of benthic assemblages. ESBs 

should not be applied to occasionally inundated 

soils containing terrestrial organisms, nor should 

they be used to address the question of possible 

contamination of upper trophic level organisms 

or the generic synergistic, additive, or 

antagonistic effects of multiple chemicals. The 

application of ESBs under these conditions may 

result in values lower or higher than those 

presented in this document. It should be noted 

that under certain conditions with narcotic 

chemicals, additivity may be considered. 

 ESB values presented herein are the 

concentrations of 32 nonionic organic chemicals 

in sediment that are not expected to adversely 

affect most benthic organisms. Just as values in 

this document can be seen as an update of the 

SQALs and Ecotox Thresholds, it is recognized 

(and encouraged) that these ESB values may 

need to be adjusted to account for new data as 

they become available. They may also need to 

be adjusted because of site-specific 

considerations. For example, in spill situations, 

where chemical equilibrium between water and 

sediment has not yet been reached, sediment 

chemical concentrations less than an ESB may 

pose risks to benthic organisms. This is because 

for spills, disequilibrium concentrations in 

interstitial and overlying water may be 

proportionally higher relative to sediment 

concentrations. In systems where biogenic 

organic carbon dominates, research has shown 

that the source or ‘quality’ of total organic 

carbon (TOC) in natural sediments does not 

affect chemical partitioning when sediment 

toxicity was measured as a function of TOC 

concentration (DeWitt et al. 1992). KOCs for 

several nonionic chemicals have also been 

shown to not vary significantly across estuarine 

sediments with differing organic carbon 

concentrations and quality (Burgess et al. 2000). 

However, in systems where other forms of 

carbon are present at elevated levels, the source 

or ‘quality’ of TOC may affect chemical binding 

despite expressing toxicity as a function of TOC 

concentration. At some sites, concentrations in 

excess of an ESB may not pose risks to benthic 

organisms because the compounds are 

partitioned to a component of a particulate phase 

such as black carbon or coal or exceed solubility 

such as in the case of undissolved oil or 

chemical (e.g., manufactured gas plant sites) 

(U.S. EPA 2003e, Cornelissen et al. 2005). In 

these situations, an ESB would be overly 

protective of benthic organisms and should not 

be used unless modified using the procedures 

outlined in “Procedures for the Derivation of 

Site-Specific Equilibrium Partitioning Sediment 

Benchmarks (ESBs) for the Protection of 

Benthic Organisms: Nonionic Organics” (U.S. 

EPA 2003b). It should also be noted that the 

ability to predict partitioning based on additional 

factors like black carbon is still evolving and 

may serve to decrease partitioning-related 

uncertainties in future applications. If the 

organic carbon has a low sorptive affinity (e.g., 

hair, wood chips, hide fragments), an ESB 

would be under protective. An ESB may also be 

under protective when the toxicity of other 

chemicals are additive with an ESB chemical or 

when species of unusual sensitivity occur at the 

site. 

 This document presents the derivation and 

calculation of Tier 2 ESBs for 32 nonionic 

organic chemicals. The data that support the 

EqP approach for deriving ESBs for nonionic 

organic chemicals are reviewed by Di Toro et al. 

(1991) and EPA (2003a). Before proceeding 

through the following text, tables, and 

calculations, the reader should also consider 

reviewing Stephan et al. (1985). 
Introduction 

1-5 

1.3 Application of Sediment Benchmarks 

 ESBs as presented in this document are 

meant to be used with direct toxicity testing of 

sediments as a method of sediment evaluation, 

assuming the toxicity testing species is sensitive 

to the chemical(s) of interest (e.g., ASTM 

1998a,b,c, U.S. EPA 1994, 2000, 2001b). In 

this way, ESBs are supportive of recent 

recommendations by Wenning et al. (2005), to 

apply a weight of evidence approach when 

evaluating contaminated sediments. 

Specifically, the ESBs provide a chemical-bychemical specification of sediment 

concentrations protective of benthic aquatic life 

(see Section 4.2.6 for more discussion). The 

EqP method should be most applicable to 

nonionic organic chemicals with a log KOW ≥ 2. 

However, for chemicals with log KOW between 2 

and 3, EqP will function but sedimentary 

conditions (i.e., fOC and fSolids) should be 

considered and adjustments to the derivation of 

the ESB maybe advisable (see Section 3.3). 

Examples of other chemicals to which the 

methodology applies include the pesticides 

endrin and dieldrin (U.S. EPA 2003c,d), metal 

mixtures (U.S. EPA 2005a), and PAH mixtures 

(U.S. EPA 2003e). 

 For the toxic chemicals addressed by the ESB 

documents, Tier 1 (U.S. EPA, 2003c, d, e, and 

2005a) and Tier 2 (this document) values were 

developed to reflect the differing degrees of data 

availability and uncertainty. Tier 1 ESBs are 

more scientifically rigorous and data intensive 

than Tier 2 ESBs. The minimum requirements 

to derive a Tier 1 ESB include: (1) each 

chemical‘s organic carbon-water partition 

coefficient (KOC) is derived from the octanolwater partition coefficient (KOW) obtained using 

the SPARC model (Karickhoff et al. 1991) and 

the KOW-KOC relationship from Di Toro et al. 

(1991). This KOC has been demonstrated to 

predict the toxic sediment concentration from 

the toxic water concentration with less 

uncertainty than KOC values derived using other 

methods, (2) the FCV is updated using the most 

recent toxicological information and is based on 

the National WQC guidelines (Stephan et al. 

1985), and (3) EqP-confirmation tests are 

conducted to demonstrate the accuracy of the 

EqP prediction that the KOC multiplied by the 

effect concentration from a water-only toxicity 

test predicts the effect concentration from 

sediment tests (Swartz 1991, DeWitt et al. 1992, 

Hoke et al. 1994). Using these specifications, 

Tier 1 ESBs have been derived for the nonionic 

organic pesticides endrin and dieldrin (U.S. EPA 

2003c,d), PAH mixtures (U.S. EPA 2003e), and 

metals mixtures (U.S. EPA 2005a). In 

comparison, the minimum requirements for a 

Tier 2 ESB (this document) are less rigorous: (1) 

the KOW for the chemical that is used to derive 

the KOC can be from slow-stir, generator column, 

shake flask, SPARC or other sources (e.g., Site 

2001), (2) FCVs can be from published or draft 

WQC documents, the Great Lakes Water 

Quality Initiative (GLI 1995), or developed from 

AQUIRE (now ECOTOX). Secondary chronic 

values (SCV) from narcosis theory (Di Toro and 

McGrath 2000, Di Toro et al. 2000, U.S. EPA 

2003e), Suter and Tsao (1996), or other effects 

concentrations from water-only toxicity tests can 

also be used. The U.S. EPA methodology for 

deriving water quality criteria SCVs required for 

the computation of Tier 2 ESBs is described in 

Water Quality Guidance for the Great Lakes 

System: Supplementary Information Document 

(SID) (U.S. EPA 1995a), and (3) EqP 

confirmation tests are recommended, but are not 

required for the development of Tier 2 ESBs. 

Because of these lesser requirements, there is 

greater uncertainty in the EqP prediction of the 

sediment effect concentration from the wateronly effect concentration, and in the level of 

protection afforded by Tier 2 ESBs. This 

uncertainty can be decreased by conducting 

additional acute and chronic water-only and 

spiked sediment toxicity tests to evaluate effect 

concentrations and confirm predicted sediment 

concentrations, respectively. 

1.4 Data Quality Assurance 

 Data sources, selections and manipulations 

used to generate KOWs or KOCs and SCV or 

FCVs are discussed in detail in Section 2. 

Toxicological data were selected from final and 

draft Water Quality Criteria, Suter and Tsao 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

1-6 

(1996), U.S. EPA (1996), GLI (1995) and U.S. 

EPA (2001a) or derived using the approach 

described by Di Toro and McGrath (2000), Di 

Toro et al. (2000) and U.S. EPA (2003e). KOW

values were taken from Karickhoff and Long 

(1995) as well as other sources. Toxicity data 

were evaluated for acceptability using the 

procedures in Stephan et al. (1985), the Great 

Lakes Water Quality Initiative (GLI 1995), and 

the approach for deriving narcotic chronic 

toxicity values (Di Toro and McGrath 2000, Di 

Toro et al. 2000, U.S. EPA 2003e). Data not 

meeting criteria for acceptability were rejected. 

In general, three or four significant figures were 

used in intermediate calculations to limit the 

effect of rounding errors, and are not intended to 

indicate the true level of precision. The time 

periods covered in the literature searches 

associated with data in this document can be 

found in the cited source literature. 

 Literature searches supporting Suter and 

Tsao (1996), U.S. EPA (1996), GLI (1995) and 

U.S. EPA (2001a) were conducted in the mid1990s. In order to capture more recent data, 

EPA’s ECOTOX database 

(www.epa.gov/ecotox) was searched for any 

data pertaining to the chemicals evaluated in 

this document published after 1995. These data 

were then sorted to identify sources of acute 

toxicity data for North American species tested 

for a period appropriate to the species (Stephan 

et al. 1985) and for which test concentrations of 

chemical were measured. In addition, literature 

sources suggested by peer reviewers of this 

document were also consulted for data meeting 

minimum requirements. Fewer than 30 

additional data points were identified, and only 

one of these affected the calculation of an SCV 

(see footnote in Table 3-1). As new, high 

quality toxicological and geochemical data 

becomes available, it is encouraged that the 

ESB values are revised and updated. See 

Section 2.5 for further discussion. 

 The document was reviewed as part of a 

formal external peer review coordinated at the 

U.S. EPA National Health and Environmental 

Effects Research Laboratory, Research Triangle 

Park, North Carolina and Atlantic Ecology 

Division, Narragansett, Rhode Island. Any 

errors of omission or calculation discovered 

during the peer review process were corrected. 

1.5 Overview 

 This document presents the derivation and 

calculation of ESBs for 32 nonionic organic 

chemicals. 

 Section 2 reviews the toxicological and 

chemical data used to derive the ESBTier2s. 

Section 3 discusses the calculation of the 

ESBTier2s. Section 4 “Sediment Benchmark 

Values: Application and Interpretation” 

discusses the sediment benchmark values and 

lists several factors to consider when applying 

and interpreting these values. Section 5 lists 

references cited in all sections of this document. 

 Appendix A discusses, in detail, the GLI 

approach for calculating chronic toxicity values. 
Derivation of Equilibrium Partitioning Sediment Benchmarks 

2-1 

Section 2 

Derivation of Equilibrium Partitioning 

Sediment Benchmark Effects 

Concentrations

2.1 General Introduction 

 This section outlines the compilation of data 

used in the derivation of the Tier 2 ESBs 

presented in this compendium. The section 

follows the format for calculating the ESB 

values by first describing the derivation of the 

KOW values, and then the derivation of the 

appropriate aquatic toxicity values. The 

derivation of the KOW values follows procedures 

outlined in Karickhoff and Long (1996) and in 

many cases uses values summarized in 

Karickhoff and Long (1995). Because of the 

diversity of chemicals discussed in this 

compendium (i.e., narcotics, pesticides, 

phthalates), aquatic toxicity values were derived 

in two possible ways. Conventional aquatic 

toxicity values were derived either using the 

procedures detailed in the Great Lakes Water 

Quality Initiative (GLI, 1995) or taken from 

existing or draft WQC. For example, marine 

ESBs for pesticides were based only on FCVs 

from existing or draft WQC while freshwater 

ESBs for pesticides were derived using both 

WQC and GLI toxicity values. Similarly, ESBs 

for phthalates were derived only for freshwater 

species using the GLI approach as WQC values 

were not available. For chemicals designated as 

being narcotic, toxicity values were also derived 

using the narcosis theory used to develop ESBs 

for PAH mixtures (Di Toro et al. 2000, U.S. 

EPA 2003e). As discussed in Section 1, ESBs 

derived using either conventional or narcotic 

approaches, for narcotic chemicals in this 

document are applicable to both freshwater and 

marine species based on the concept that these 

organisms show similar sensitivity to narcotic 

chemicals. This concept was not exercised for 

pesticides and phthalates. 

2.2 Determination of KOW Values

 The determination of Kow values was based 

on experimental measurements taken primarily 

by the slow-stir, generator-column, and shakeflask methodologies. The SPARC properties 

calculator model (Karickhoff and Long 1995) 

was also used to generate Kow values, when 

appropriate, for comparison with the measured 

values. Values that appeared to be considerably 

different from the rest were classified as outliers 

and were not used in the calculation. For each 

chemical, the available log Kow value, based on 

one of the above mentioned methods, was given 

preference. If more than one such value was 

available, the log Kow value was calculated as 

the arithmetic mean of those values (U.S. EPA 

1995b). Most of the log Kow values used in this 

document are summarized in an internal EPA 

report (Karickhoff and Long 1995). Subsequent 

to that evaluation, EPA has published a 

recommended procedure for selecting Kow 

values, which can be seen in Karickhoff and 

Long (1996). 

 Log Kow values were initially identified in 

summary texts on physical-chemical properties, 

such as Howard (1990) and Mackay et al. 

(1992a,b), and accompanying volumes. 

Additional compendia of log Kow values were 

also evaluated including de Bruijn et al. (1989), 

De Kock and Lord (1987), Doucette and Andren 

(1988), Isnard and Lambert (1989), Klein et al. 

(1988), Leo (1993), Noble (1993), and Stephan 

(1993). To supplement these sources, on-line 

database searches were conducted in ChemFate, 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

2-2 

TOXLINE, and Hazardous Substances Data 

Bank (HSDB) (National Library of Medicine); 

Internet databases such as EPA’s ASsessment 

Tools for the Evaluation of Risk (ASTER) were 

also reviewed. Original references were located 

for the values, and additional values identified. 

In cases where log Kow values varied over 

several orders of magnitude or measured values 

could not be identified, detailed on-line searches 

were conducted using TOXLIT, Chemical 

Abstracts, and DIALOG. 

2.3 Selection and Determination of 

Aquatic Toxicity Values 

 For this discussion, all sources of 

toxicological information are considered 

‘conventionally-derived’ approaches except for 

the narcosis source which will be referred to 

separately as the ‘narcosis-based’ approach. 

 A variety of sources were used for selecting 

conventional chronic toxicity values to be used 

in the derivation of the ESBs. The following 

were identified as possible sources to be used for 

determining chronic toxicity values: 

2. Final Chronic Values from National 

Ambient Water Quality Criteria documents 

3. Final Chronic Values from draft freshwater 

and marine National Ambient Water Quality 

Criteria documents 

4. Final Chronic Values developed from data 

in AQUIRE (now ECOTOX) and other 

sources 

5. Secondary Chronic Values from Suter and 

Tsao (1996) 

6. Secondary Chronic Values developed from 

data in AQUIRE (now ECOTOX) and other 

sources (U.S. EPA 1996, 2001a) 

2.3.1 Derivation of Conventional Chronic 

Toxicity Values

 For the nine pesticides discussed in this 

document, values for freshwater ESBs for the 

following chemicals: 

 gamma-BHC/Lindane 

 diazinon 

endosulfan (mixed isomers and alpha and 

beta forms) 

toxaphene 

were based on the FCVs from existing or draft 

National Ambient Water Quality Criteria 

documents (U.S. EPA 1980a,b, 1986, 2005b). 

Exceptions were the ESBs for BHCs other than 

Lindane, malathion and methoxychlor which 

were derived using SCVs with the GLI approach 

(GLI 1995, Suter and Tsao 1996, U.S. EPA 

1996, 2001a). Marine ESBs for pesticides, in 

this document, were based only on WQCderived FCVs. Consequently, marine ESBs for 

the following chemicals: 

 diazinon 

endosulfan (mixed isomers and alpha and 

beta forms) 

 malathion 

 toxaphene 

were derived from FCVs in existing or draft 

National Ambient Water Quality Criteria 

documents (Thursby 1990, U.S. EPA 1980b, 

1986, 2005b). Similar FCVs for the pesticides 

BHCs other than Lindane, gammaBHC/Lindane, and methoxychlor were 

unavailable and marine ESBs were not derived. 

 

 Twelve aquatic toxicity values, including 

three phthalates, used to develop freshwater 

SCVs were based on work conducted by Oak 

Ridge National Laboratories (Suter and Tsao 

1996) using the GLI (1995) methodology. This 

methodology was developed to obtain wholeeffluent toxicity screening values based on all 

available data, but the methodology can also be 

used to calculate SCVs with fewer toxicity data 

than are required for the WQC methodology. 

The SCVs are generally lower than values that 

are produced by the FCV methodology, 

1. Final Chronic Values from the Great Lakes 

Water Quality Initiative (GLI 1995, U.S. 

EPA 2001a) 
Derivation of Equilibrium Partitioning Sediment Benchmarks 

2-3 

reflecting greater uncertainty and use of 

protective adjustment factors in the absence of 

additional toxicity data (see Section 2.4). 

According to GLI (1995), the minimum 

requirement for deriving an SCV is toxicity data 

from a single taxonomic family (Daphnidae), 

provided the data are acceptable. In general, 

those values from Suter and Tsao (1996), which 

included at least one daphnid test result in the 

calculation of the SCV, were included for the 

derivation of Tier 2 ESBs with the exception of 

ethylbenzene, toluene, 1,1,1-trichloroethane and 

trichloroethene. For these four chemicals, 

daphnids were not used for calculating the 

SCVs. SCVs from Suter and Tsao (1996) were 

used to develop Tier 2 ESBs for the following 

chemicals: 

 benzene 

 BHC (other than Lindane)

 chlorobenzene 

 dibenzofuran 

 diethyl phthalate 

 di-n-butyl phthalate 

 ethylbenzene 

 tetrachloroethane, 1,1,2,2- 

 tetrachloroethene 

 toluene 

 trichloroethane, 1,1,1- 

 trichloroethene 

 A preliminary search of data records in the 

AQUIRE (now ECOTOX) database indicated 

that the following chemicals, which includes one 

phthalate, might have sufficient toxicity data for 

the development of SCVs using the GLI (1995) 

methodology: 

biphenyl 

4-bromophenyl phenyl ether 

 butyl benzyl phthalate 

dichlorobenzene, 1,2- 

dichlorobenzene, 1,3- 

 dichlorobenzene, 1,4- 

hexachlorethane 

malathion 

methoxychlor 

pentachlorobenzene 

tetrachloromethane 

tribromomethane 

trichlorobenzene, 1,2,4- 

m-xylene 

The procedure used for deriving SCVs for other 

chemicals of concern using the GLI (1995) 

methodology and data from ACQUIRE (now 

ECOTOX) and other sources is described in 

detail in Appendix A and U.S. EPA (1996, 

2001a). 

2.3.2 Derivation of Narcotic Chronic Toxicity 

 Values 

 Along with the derivation of aquatic toxicity 

values using conventional techniques (see 

discussion above), narcosis theory was used to 

derive SCVs for chemicals determined to be 

primarily narcotic in their mode of action by 

ASsessment Tools for the Evaluation of Risk 

(ASTER) (Russom et al. 1997). These 

chemicals include: 

 benzene 

 biphenyl 

 4-bromophenyl phenyl ether 

 chlorobenzene 

 dibenzofuran 

 1,2-dichlorobenzene 

 1,3-dichlorobenzene 

 1,4-dichlorobenzene 

 ethylbenzene 

 hexachloroethane 

 pentachlorobenzene 

 1,1,2,2-tetrachloroethane 

 tetrachloroethene 

 tetrachloromethane 

 toluene 

 tribromomethane 

 1,2,4-trichlorobenzene 

 1,1,1-trichloroethane 

 trichloroethene 

 m-xylene 

It should be noted that for a given chemical 

multiple modes of action can affect an organism. 

Therefore, despite the categorization of these 

chemicals as primarily narcotics, other modes of 

action may be active. Section 4.3 discusses 

some of the implications of this issue. 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

2-4 

 Narcosis-based SCVs were derived using the 

approach discussed in the Procedures for the

Derivation of Equilibrium Partitioning Sediment 

Benchmarks (ESBs) for the Protection of 

Benthic Organisms: PAH Mixtures (U.S. EPA 

2003e) and Di Toro et al. (2000). In this 

approach, the SCV for these narcotic chemicals 

is derived using Equation 2-1: 

log (SCVN) = log[CL*∆cl ÷ ACR] – 0.945 · log 

 (KOW) (2-1) 

where, SCVN is the narcosis-based SCV for a 

given chemical (mmol/L), CL* is the critical 

lipid concentration predicted to cause 50% 

mortality equaling 35.3 μmol/g octanol, ∆cl 

is the chemical class specific correction, ACR is 

the acute-chronic ratio equaling 5.09, -0.945 the 

universal narcosis slope, and KOW is specific to 

the chemical being investigated (Di Toro et al. 

2000). This equation can be simplified to: 

log (SCVN) = log (6.94) + ∆cl - 0.945 · log 

 (KOW) (2-2) 

 For the narcotic chemicals in this document, 

the chemical class specific correction value (∆cl) 

for halogenated compounds was -0.244. For all 

other compounds, a correction was not necessary 

(Di Toro et al. 2000). 

 Narcosis values were also calculated for 

chemicals with other toxicological modes of 

action; specifically, the pesticides and 

phthalates. In every instance, the narcosis SCVN

was larger in magnitude than the conventional 

FCV or SCV. For example, the range of the 

ratio of narcosis to conventional values was 2.4 

for di-n-butyl phthalate to nearly 50,000 for 

alpha-endosulfan. In general, the ratio of 

narcosis to conventional values was greater than 

1000 and thus the pesticides and phthalates 

contribute only a small amount of narcotic 

potency. Despite the utility of knowing the 

contribution of narcosis to the overall toxicity of 

the pesticides and phthalates, the narcosis values 

should be used with caution. The narcosis 

equation above (Equation 2-2) provides 

chemical class specific corrections (i.e., ∆cl ) for 

halogenated functional groups. However, 

several of the pesticides and phthalates contain 

other functional groups not directly addressed in 

Equation 2-2 including ester and sulfur groups. 

At this time, the effects of these types of groups 

on predictions by Equation 2-2 are unknown. 

2.4 Comparison of Narcosis and 

Conventional Chronic Toxicity 

Values 

For every narcotic chemical in this 

document, the narcosis-based SCV is greater 

than the conventionally-derived SCV, although 

the magnitude of the difference varies among 

chemicals (also see Table 3-1). Figure 2-1 

shows the ratio of the two values, which ranges 

from 1.1 (1,2,4-trichlorobenzene) to 220 (1,1,1-

trichloroethane). Of the 20 chemicals evaluated, 

four chemicals had ratios below 10, 13 

chemicals had ratios between 10 and 50, and 

three chemicals had ratios greater than 100. To 

interpret these differences, one must consider the 

differences in how the two values are derived. 

There are two features of the conventional SCV 

derivation that create discrepancies. The first is 

the use of secondary acute factors (SAFs) to 

estimate a SAV from existing data (see Section 

A.5 of Appendix A for more discussion of 

SAFs). The SAFs applied to the chemicals in 

question here range from 4 up to 242, depending 

on the number of minimum data requirements 

met by the available toxicity data, and is applied 

to the lowest reported mean acute value 

available (see Suter and Tsao (1996) and U.S. 

EPA (2001) for a description of how the 

conventional SCVs were calculated). 

 The SAFs were derived based on an analysis 

of a wide range of chemicals. However, 

narcotics tend to show a much narrower range in 

species sensitivity than do many other 

chemicals; in fact, the total range in species 

sensitivity reported by Di Toro et al. (2000) is 

only a factor of 8.3 across a total of 33 species. 

More importantly, the conventional GLI SCV 

methodology requires that data for Daphnia 

magna be included in the data set. As shown by 

Di Toro et al. (2000), the ratio of the estimated 

SMAV for Daphnia magna and the FAV for all 

species is only a factor 3.1. In the case of 
Derivation of Equilibrium Partitioning Sediment Benchmarks 

2-5 

rainbow trout, a species for which data were 

frequently available for the present analysis, that 

ratio is only 1.7. What this means in terms of 

SCV derivation for narcotic chemicals is that the 

generic SAFs are larger than is appropriate for 

narcotic chemicals in particular; while values of 

4 to 242 were used, one would expect the true 

value to have never been higher than 3.1, and 

commonly 1.7 or less. This difference in 

extrapolation therefore accounts for as much as a 

factor of >10 difference between the 

conventionally-derived and narcosis-based 

SAVs, which is directly translated into 

differences in the SCVs (Figure 2-1). 

 The second major factor lies in the acutechronic ratios (ACRs) used to translate the SAV 

into a SCV. In the conventional approach, 

calculation of the ACR was based on the 

geometric mean of at least three ACRs. 

However, wherever there were less than three 

species-specific ACRs available, a value of 18 

was used to replace the missing data (see 

Section A.5 of Appendix A for more discussion 

of ACRs); this value was derived through an 

analysis of ACRs for a variety of chemicals. For 

the narcotic chemicals shown in Figure 2-1, 

availability of chronic toxicity data varied from 

no measured ACRs to three measured ACRs. 

Where there were no measured ACRs, the 

conventionally-derived secondary ACR (SACR) 

was 18. 

 In their analysis, Di Toro et al. (2000) 

calculated a much lower mean ACR of 5.09 for 

narcotic chemicals specifically. Because 

narcosis appears to result in a lower ACR than 

the default value of 18 used in the conventional 

Tier 2 SCV derivation, one can expect additional 

conservatism in the conventionally-derived Tier 

2 SCVs for those chemicals where little or no 

chronic data were available. Examples include 

chemicals like 1,2 dichlorobenzene and 

pentachlorobenzene, both of which were derived 

using SACRs of 18 and have correspondingly 

high ratios of the narcosis-based and 

conventionally-derived SCV values (Figure 2-

1). In contrast, 1,2,4 – trichlorobenzene had 

enough acute toxicity data to meet all 8 

minimum data requirements (MDRs) (so no SAF 

was applied) and the SACR (with two measured 

ACRs) was only 6.7, very close to the 5.09 

estimated for narcotic chemicals (Di Toro et al. 

2000). As a result, the conventionally-derived 

SCV and the narcosis-based SCVs are very close 

(Figure 2-1). 

 The applicability of narcosis theory to the 

compounds designated here as narcotics can be 

evaluated by comparing the individual species 

mean acute values (SMAVs) for each of the 

compounds to the SMAV one would predict 

based on narcosis theory. To do this, the 

individual SMAV values were extracted from 

the SCV derivation for the 20 narcotic chemicals 

listed in Section 2.3.2. For those species which 

also appeared in the dataset compiled by Di 

Toro et al. (2000), the mean species sensitivity 

was used along with the KOW of each chemical 

to predict an LC50 for that species and chemical. 

 These predicted LC50s for all 20 chemicals 

were compared to the observed SMAVs as 

shown in Figure 2-2. To allow better 

discrimination of data for individual chemicals, 

this same data set was segregated into three 

groups of chemicals, and replotted as Figures 2-

3 through 2-5. 

 The strong agreement between observed and 

predicted values, shown by alignment along the 

one to one line, clearly indicates that the 

observed toxicity of these chemicals is 

consistent with a narcosis mode of action. Most 

of the measured values fall within a factor of 

two of the predicted value (shown by the dashed 

lines in Figures 2-2 through 2-5) with no 

consistent bias from a 1:1 relationship. This in 

turn suggests that deriving SCVs for these 

chemicals using narcosis theory is appropriate, 

and that the differences in the conventionallyderived and narcosis-based SCVs is primarily 

due to conservatism in the SAFs and default 

SACRs as discussed above. 

 Finally, for the three phthalates discussed 

in this document, ‘FCVs’ derived using the 

quantitative structure-activity relationship 

(QSAR) described by Parkerton and Konkel 

(2000) were compared to conventional SCVs in 

Table 3-1. ASTER does not classify phthalates 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

2-6 

as narcotics but there is some evidence they may 

demonstrate narcotic-like behavior. The QSAR 

values derived by Parkerton and Konkel (2000) 

were 60, 62 and 1173 μg/L for butyl benzyl 

phthalate, di-n-butyl phthalate and diethyl 

phthalate, respectively. These values compare 

relatively well to the conventional SCVs of 19, 

35 and 270 μg/L for butyl benzyl phthalate, 

di-n-butyl phthalate and diethyl phthalate, 

respectively. From this comparison, the 

conventional values for phthalates in this 

document appear to be slightly more 

conservative than the QSAR based numbers but 

not tremendously different with ratios ranging 

from 2 to 4. See Adams et al. (1995), Rhodes et 

al. (1995), Staples et al. (1997), Parkerton and 

Konkel (2000), and Call et al. (2001) for further 

discussion of phthalate aquatic toxicity. 

2.5 Selection of New and Alternate 

Aquatic Toxicity Values 

 As discussed in the Foreword, the ESBs are 

intended primarily as technical information, not 

as formal guidelines. As such, the aquatic 

toxicity values used to derive the Tier 2 ESBs 

reported in this document are principally 

recommendations. The conventional (based on 

WQC and GLI) and narcosis approaches were 

selected to generate aquatic toxicity values for 

the 32 chemicals in this document because of 

their wide usage and acceptance by the 

scientific, regulatory and regulated communities. 

 As new high quality aquatic toxicity data 

becomes available, it is encouraged that these 

Tier 2 ESBs be updated and revised. The GLI 

approach, as discussed in Appendix A, is one 

method for performing these updates and 

revisions. Periodic review of aquatic toxicity 

databases like ECOTOX may provide new high 

quality aquatic toxicity values for some of the 

chemicals discussed in this ESB, especially 

those for which a limited data base was initially 

available (see Section 2.3.1). 
Derivation of Equilibrium Partitioning Sediment Benchmarks 

2-7 

1 10 100 1000

Benzene

Biphenyl

4-Bromophenyl phenyl ether

Chlorobenzene

Dibenzofuran

1,2-Dichlorobenzene

1,3-Dichlorobenzene

1,4-Dichlorobenzene

Ethylbenzene

Hexachloroethane

Pentachlorobenzene

1,1,2,2-Tetrachloroethane

Tetrachloroethene

Tetrachloromethane

Toluene

Tribromomethane

1,2,4-Trichlorobenzene

1,1,1-Trichloroethane

Trichloroethene

m-Xylene

Compound

Narcosis-based SCV/Conventionally-derived SCV

Figure 2-1 Comparison of narcosis-based and conventionally-derived chronic toxicity values. 

Chemicals with modes of action in addition to narcosis (i.e., pesticides and 

 phthalates) are not shown. 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

2-8 

Predicted LC50 (ug/L)

100 1000 10000 100000 1000000

Observed LC50 (ug/L)

100

1000

10000

100000

1000000

Figure 2-2 Comparison of observed LC50 values used in the calculation of secondary chronic 

values and LC50 values predicted using narcosis theory as described by Di Toro et 

al. (2000) for all 20 narcotic chemicals discussed in this document (including data 

from Chaisuksant et al. (1998)). Plot shows data for all species that had both 

measured LC50 values in the SCV derivation and have species-specific sensitivity 

data as calculated by Di Toro et al. (2000). See discussion in text for more details. 

 The solid line is the one to one line and the dashed lines show ± a factor of two. 

Chemicals potentially having more specific modes of action (e.g., pesticides and 

phthalates) are not shown. 
Derivation of Equilibrium Partitioning Sediment Benchmarks 

2-9 

Predicted LC50 (ug/L)

100 1000 10000 100000 1000000

Observed LC50 (ug/L)

100

1000

10000

100000

1000000

Benzene

Biphenyl

Dibenzofuran

Ethylbenzene

Toluene

m-xylene

Figure 2-3 Comparison of observed LC50 values used in the calculation of secondary 

chronic values and LC50 values predicted using narcosis theory as described by 

Di Toro et al. (2000) for non-halogenated aromatic narcotic chemicals 

discussed in this document. Plot shows data for all species that had both 

measured LC50 data in the SCV derivation and have species-specific sensitivity 

data as calculated by Di Toro et al. (2000). See discussion in text for more 

details. The solid line is the one to one line and the dashed lines show ± a factor 

of two. 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

2-10 

Predicted LC50 (ug/L)

100 1000 10000 100000 1000000

Observed LC50 (ug/L)

100

1000

10000

100000

1000000

Chlorobenzene

1,2-Dichlorobenzene

1,3-Dichlorobenzene

1,4-Dichlorobenzene

Pentachlorobenzene

1,2,4 Trichlorobenzene

Figure 2-4 Comparison of observed LC50 values used in the calculation of secondary chronic 

values and LC50 values predicted using narcosis theory as described by Di Toro et 

al. (2000) for chlorobenzenes (including Chaisuksant et al. (1998)). Plot shows 

data for all species that had both measured LC50 data in the SCV derivation and 

have species-specific sensitivity data as calculated by Di Toro et al. (2000). See 

discussion in text for more details. The solid line is the one to one line and the 

dashed lines show ± a factor of two. 
Derivation of Equilibrium Partitioning Sediment Benchmarks 

2-11 

Predicted LC50 (ug/L)

100 1000 10000 100000 1000000

Observed LC50 (ug/L)

100

1000

10000

100000

1000000

4-Bromophenyl phenyl ether

Hexachloroethane

1,1,2,2 Tetrachloroethane

Tetrachloroethene

Tetrochloromethane

Tribromomethane

1,1,1-Trichloroethane

Trichloroethene

Figure 2-5 Comparison of observed LC50 values used in the calculation of secondary chronic 

values and LC50 values predicted using narcosis theory as described by Di Toro et 

al. (2000) for narcotic chemicals not shown in Figures 2-3 or 2-4, primarily 

halogenated hydrocarbons. Plot shows data for all species that had both 

measured LC50 data in the SCV derivation and have species-specific sensitivity 

data as calculated by Di Toro et al. (2000). See discussion in text for more details. 

The solid line is the one to one line and the dashed lines show ± a factor of two. 

Calculation of Equilibrium Partitioning Sediment Benchmarks 

3-1 

Section 3 

Calculation of Equilibrium 

Partitioning Sediment Benchmarks 

3.1 Overview of EqP Methodology 

 ESBs are the numeric concentrations of 

individual chemicals that are intended, based on 

the assumptions discussed in Section 1, to be 

predictive of biological effects, protective of the 

presence of benthic organisms, and applicable to 

the range of natural sediments from lakes, 

streams, estuaries, and near-coastal marine 

waters. For nonionic organic chemicals, ESBs 

are expressed as μg chemical/gOC and apply to 

sediments having ≥ 0.2% organic carbon by dry 

weight. A brief overview follows of the 

concepts that underlie the EqP methodology for 

deriving ESBs. The methodology is discussed in 

detail in “Technical Basis for the Derivation of 

Equilibrium Partitioning Sediment Benchmarks 

(ESBs) for the Protection of Benthic Organisms: 

Nonionic Organics” (U.S. EPA 2003a), hereafter 

referred to as the ESB Technical Basis 

Document.

 Bioavailability of a chemical at a particular 

sediment concentration often differs from one 

sediment type to another. Therefore, a method 

is necessary to determine ESBs based on the 

bioavailable chemical fraction in a sediment. 

For nonionic organic chemicals, the 

concentration–response relationship for the 

biological effect of concern can most often be 

correlated with the interstitial water (i.e., pore 

water) concentration (μg chemical/L interstitial 

water) and not with the sediment chemical 

concentration (μg chemical/g sediment) (Di 

Toro et al. 1991). This does not mean that all of 

the exposure is from the interstitial waters but 

from a purely practical point of view, this 

correlation suggests that if it were possible to 

measure the interstitial water chemical 

concentration, or predict it from the total 

sediment concentration and the relevant 

sediment properties, then that concentration 

could be used to quantify the exposure 

concentration for an organism. Thus, 

knowledge of the partitioning of chemicals 

between the solid and liquid phases in a 

sediment is a necessary component for 

establishing ESBs. For this reason, the 

methodology described below is called the EqP 

method. As stated above, an ESB can be 

derived using any given level of protection, in 

the following discussion the SCVs or FCVs for 

several nonionic organic chemicals are applied. 

The EqP approach used here to derive ESBs 

functions most effectively for nonionic organic 

chemicals with log KOWs ≥ 2. However, for 

chemicals with log KOW between 2 and 3, EqP 

will function but sedimentary conditions (i.e., 

fOC and fSolids) should be considered and 

adjustments to the derivation of the ESB maybe 

advisable (see Section 3.3). 

3.2 Derivation of Tier 2 Equilibrium 

 Partitioning Sediment Benchmarks 

The ESB Technical Basis Document (U.S. 

EPA 2003a) demonstrates that benthic species, 

as a group, have sensitivities similar to all 

benthic and water column species tested (taken 

as a group) to derive the WQC concentration for 

a wide range of chemicals. Thus, an ESB can be 

established using the FCV, calculated based on 

the WQC guidelines (Stephan et al. 1985), or a 

SCV calculated based on other sources like the 

water quality guidance originally derived for the 

Great Lakes Water Quality Initiative (GLI 

1995), as the acceptable effect concentration in 

interstitial or overlying water. The appropriate 

partition coefficient can then be used to relate 

the interstitial water concentration (i.e., the 

calculated FCV or SCV) to the sediment 

concentration via the partitioning equation. 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

3-2 

For chemicals discussed in this document, this 

acceptable concentration in sediment is termed 

an ESBTier2. 

 The methodology for deriving FCVs and 

SCVs used in the development of these ESBs 

were taken from existing or draft WQC, the 

approach developed for the Great Lakes Water 

Quality Initiative (Tier 1 and 2) and, when 

necessary, available data were obtained from 

EPA's AQUIRE database (now ECOTOX 

accessible at www.epa.gov/ecotox) and other 

literature (see Section 2). 

 In addition to deriving FCVs or SCVs based 

on chemical-specific toxicity data, the likelihood 

that each chemical would act as a narcotic 

toxicant (as opposed to a more specific mode of 

action) was evaluated using the ASTER model 

(Russom et al. 1997) which predicts mode of 

toxic action based on chemical structure. For 

chemicals in this document that were flagged by 

the ASTER model as acting through a narcotic 

mode of action, SCVs were also derived using 

the narcosis model described in U.S. EPA 

(2003e), Di Toro and McGrath (2000) and Di 

Toro et al. (2000). 

 For chemicals evaluated using 

conventionally-derived SCVs, separate ESB 

values were calculated for freshwater and marine 

organisms according to data availability. For 

chemicals flagged as narcotic toxicants, only 

single values were calculated, as it is believed 

that there is little difference in sensitivity 

between freshwater and marine organisms under 

this mode of action (U.S. EPA 2003e). A listing 

of SCVs and FCVs using conventional and 

narcosis approaches are shown in Table 3-1. 

 An ESB is calculated as follows. 

Establishing the SCV or FCV (μg/L) as the 

acceptable concentration in water for the 

chemical of interest, the ESB is computed using 

the partition coefficient, KP (L/Kg), between 

sediment and water: 

ESBTier2 = KP · SCV (3-1) 

This is the fundamental equation used to 

generate an ESBTier2. Its’ utility depends on the 

existence of a methodology for quantifying KP. 

 Organic carbon appears to be the dominant 

sorption phase for most nonionic organic 

chemicals in naturally occurring sediments and, 

thus, controls the bioavailability of these 

compounds in sediments. Evidence for this can 

be found in numerous toxicity tests, 

bioaccumulation studies, and chemical analyses 

of interstitial water and sediments (Di Toro et al. 

1991, U.S. EPA 2003a). The organic carbon 

binding of a chemical in sediment is a function 

of that chemical’s KOC and the weight fraction of 

organic carbon (fOC) in the sediment. The 

relationship is as follows: 

KP = fOC · KOC (3-2) 

It follows that: 

ESBTier2OC = KOC · SCV (3-3) 

where ESB Tier2OC is an ESB Tier2 expressed on a 

sediment organic carbon normalized basis. For 

nonionic organics, normalization of the “ESB

Tier2” to organic carbon is assumed (more 

formally ESBTier2OC) unless otherwise specified. 

 Although KOC is not usually measured, it is 

closely related to the octanol-water partition 

coefficient (KOW), which has been measured for 

many compounds, and can be measured very 

precisely. A chemical’s KOC is related to the 

KOW by the following equation (Di Toro et al. 

1991): 

Log KOC = 0.00028 + 0.983 · (log KOW) (3-4) 

Karickhoff and Long (1996) established a 

protocol for recommending KOW values for 

nonionic organic chemicals based on the best 

available measured, calculated, and estimated 

data. The recommended log10KOW values from 

Karickhoff and Long (1995) were used to derive 

many of the KOC values for ESB calculation in 

this document (Table 3-2). 

 Based on this derivation, ESBTier2 values for 

32 nonionic organic chemicals using 

conventional and narcosis approaches are listed 

in Table 3-2. 
Calculation of Equilibrium Partitioning Sediment Benchmarks 

3-3 

Table 3-1. Chronic toxicity values (μg/L), SCVs and FCVs, used to derive Tier 2 ESBs based on 

conventional and narcosis approaches. Narcosis values for chemicals with a toxicological mode 

of action in addition to narcosis are italicized and bolded (e.g., pesticides and phthalates) and 

are provided for comparison not for use. Values presented with two significant figures except 

FCVs. 

Conventional* 

CAS FCV or SCV (μg/L) 

Number Chemical log Kow

Freshwater Marine 

Narcosis* SCV 

(μg/L) 

71432 Benzene 2.13 SCV = 130 SCV = 130 5300 

319868 BHC other than Lindane 3.78 SCV = 2.2 - 310 

58899 Gamma-BHC, Lindane 3.73 FCV = 0.080 - 340 

92524 Biphenyl 3.96 SCV = 14 SCV = 14 190 

101553 4-Bromophenyl phenyl 

ether 5.00 SCV = 1.5 SCV = 1.5 19 

85687 Butyl benzyl phthalate 4.84 SCV = 19 - 58 

108907 Chlorobenzene 2.86 SCV = 64 SCV = 64 880 

333415 Diazinon 3.70 FCV = 0.1699 FCV = 0.8185 670 

132649 Dibenzofuran 4.07 SCV = 3.7 SCV = 3.7 170 

95501 1,2-Dichlorobenzene 3.43 SCV = 14 SCV = 14 330 

541731 1,3-Dichlorobenzene 3.43 SCV = 71 SCV = 71 330 

106467 1,4-Dichlorobenzene 3.42 SCV = 15 SCV = 15 340 

84742 Di-n-butyl phthalate 4.61 SCV = 35 - 85 

84662 Diethyl phthalate 2.50 SCV = 270** - 6700 

115297 Endosulfan mixed isomers 4.10 FCV = 0.056 FCV = 0.0087 210 

959988 Alpha-Endosulfan 3.83 FCV = 0.056 FCV = 0.0087 390 

332136

59 Beta-Endosulfan 4.52 FCV = 0.056 FCV = 0.0087 86 

100414 Ethylbenzene 3.14 SCV = 7.3 SCV = 7.3 790 

67721 Hexachloroethane 4.00 SCV = 12 SCV = 12 160 

121755 Malathion 2.89 SCV = 0.097 FCV = 0.1603 4300 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

3-4 

Conventional* 

CAS FCV or SCV (μg/L) 

Number Chemical log Kow

Freshwater Marine 

Narcosis* SCV 

(μg/L) 

72435 Methoxychlor 5.08 SCV = 0.019 - 22 

608935 Pentachlorobenzene 5.26 SCV = 0.47 SCV = 0.47 11 

79345 1,1,2,2-Tetrachloroethane 2.39 SCV = 610 SCV = 610 3700 

127184 Tetrachloroethene 2.67 SCV = 98 SCV = 98 2000 

56235 Tetrachloromethane 2.73 SCV = 240 SCV = 240 1600 

108883 Toluene 2.75 SCV = 9.8 SCV = 9.8 1600 

800135

2 Toxaphene 5.50 FCV = 0.039 FCV = 0.2098 10 

75252 Tribromomethane 

(Bromoform) 2.35 SCV = 320 SCV = 320 6000 

120821 1, 2, 4-Trichlorobenzene 4.01 SCV = 110 SCV = 110 120 

71556 1, 1, 1-Trichloroethane 2.48 SCV = 11 SCV = 11 2400 

79016 Trichloroethene 2.71 SCV = 47 SCV = 47 1400 

108383 m-Xylene 3.20 SCV = 67*** SCV = 67*** 700 

- = Not Available. 

* = See Section 2.3 for definition. 

** = Data summary in Suter and Tsao (1996) did not include a 96-hour LC50 of 131,000 ug/L from 

Adams et al. (1995). Inclusion of this LC50 in the SCV calculation increased the SCV from 210 to 270 

μg/L (Mount 2008). 

*** = Value changed from original GLI SCV (Suter and Tsao 1996, U.S. EPA 1996), see Mount (2006). 

Table 3-2. Tier 2 ESBs (μg/goc) based on toxicity values derived using conventional and narcosis 

approaches (from Table 3-1). KOC based on Equation 3-4. Values presented with two significant 

figures. 

Conventional* 

CAS ESB (μg/gOC) 

Number Chemical Log KOC

Freshwater Marine 

Narcosis* ESB 

(μg/gOC) 

71432 Benzene 2.09 16 16 660 

319868 BHC other than Lindane 3.72 11 - ^ 
Calculation of Equilibrium Partitioning Sediment Benchmarks 

3-5 

Conventional* 

CAS ESB (μg/gOC) 

Number Chemical Log KOC

Freshwater Marine 

Narcosis* ESB 

(μg/gOC) 

58899 Gamma-BHC, Lindane 3.67 0.37 - ^ 

92524 Biphenyl 3.89 110 110 1500 

101553 4-Bromophenyl phenyl 

ether 4.92 120 120 1600 

85687 Butyl benzyl phthalate 4.76 1100 - ^ 

108907 Chlorobenzene 2.81 41 41 570 

333415 Diazinon 3.64 0.74 3.6 ^ 

132649 Dibenzofuran 4.00 37 37 1700 

95501 1,2-Dichlorobenzene 3.37 33 33 780 

541731 1,3-Dichlorobenzene 3.37 170 170 780 

106467 1,4-Dichlorobenzene 3.36 34 34 780 

84742 Di-n-butyl phthalate 4.53 1200 - ^ 

84662 Diethyl phthalate 2.46 77 - ^ 

115297 Endosulfan mixed isomers 4.03 0.60 0.093 ^ 

959988 Alpha-Endosulfan 3.77 0.33 0.051 ^ 

3321365

9 Beta-Endosulfan 4.44 1.6 0.24 ^ 

100414 Ethylbenzene 3.09 8.9 8.9 970 

67721 Hexachloroethane 3.93 100 100 1400 

121755 Malathion 2.84 0.067 0.11 ^ 

72435 Methoxychlor 4.99 1.9 - ^ 

608935 Pentachlorobenzene 5.17 70 70 1600 

79345 1,1,2,2-Tetrachloroethane 2.35 140 140 830 

127184 Tetrachloroethene 2.62 41 41 840 

56235 Tetrachloromethane 2.68 120 120 770 

108883 Toluene 2.70 5.0 5.0 810 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

3-6 

Conventional* 

CAS ESB (μg/gOC) 

Number Chemical Log KOC

Freshwater Marine 

Narcosis* ESB 

(μg/gOC) 

8001352 Toxaphene 5.41 10 54 ^ 

75252 Tribromomethane 

(Bromoform) 2.31 65 65 1200 

120821 1, 2, 4-Trichlorobenzene 3.94 960 960 1100 

71556 1, 1, 1-Trichloroethane 2.44 3.0 3.0 660 

79016 Trichloroethene 2.66 22 22 650 

108383 m-Xylene 3.15 94 94 980 

* = See Section 2.3 for definition. 

- = Not Available. 

^ = Not Calculated. 
Calculation of Equilibrium Partitioning Sediment Benchmarks 

3-7 

3.3 Effects of Low KOW on Derivation of 

ESBTier2

 As noted above, the EqP approach used 

here to derive ESBs functions most effectively 

for nonionic organic chemicals with log KOWs ≥

2. However, Fuchsman (2003) demonstrated 

recently that equilibrium partitioning may 

inaccurately predict the bioavailable 

concentration of organic compounds with low 

log KOWs (i.e., approximately 3). This is because 

the basic equilibrium partitioning equation 

(Equation 3-3) assumes that the measured 

contaminant is associated overwhelmingly with 

sediment organic carbon and that the amount in 

the dissolved phase is negligible. However, for 

chemicals with comparatively low KOW a more 

substantial fraction of total chemical may be 

present in the dissolved phase. As a result, the 

ESB calculation as shown in Equation 3-3, may 

result in overly protective ESBs. 

 A modification of the equilibrium 

partitioning equation (Equation 3-3) can be 

determined (Fuchsman 2003): 

ESBTier2DRY WT = SCV [(fOC KOC) + ((1 – fSolids) ÷ 

 fSolids)] (3-5) 

In which, ESBTier2DRY WT is in units of μg 

chemical/g dry weight sediment and fSolids is the 

fraction of sediment present as solids. In the 

U.S. EPA Environmental Monitoring and 

Assessment Program (EMAP) data set discussed 

below, fSolids values for 1024 sediment samples 

ranged from 0.085 to 0.938 with an average 

value of 0.553 (U.S. EPA 2007a). In Equation 

3-5, the proportion ((1 – fSolids) ÷ fSolids), is used 

to adjust the magnitude of the ESBTier2DRY WT as a 

function of the amount of solids in the sediment. 

As KOC increases; that is, the chemical becomes 

more hydrophobic, the proportion becomes less 

important and has little effect on the ESBTier2DRY 

WT. Conversely, for low KOC chemicals, the 

proportion may have a substantial effect on the 

magnitude of ESBTier2DRY WT. The ESBTier2DRY WT

is converted to ESBTier2OC by the following: 

ESBTier2OC = ESBTier2DRY WT ÷ fOC (3-6) 

 It should be noted that in aquatic 

environments, fSolids and fOC are often inversely 

correlated. For example, in depositional areas, 

where contaminants discussed in this document 

frequently accumulate, fSolids is often low and fOC 

elevated because of the abundance of carbonrich small particles with large surface area to 

volume ratios. Conversely, sediments in 

dynamic areas tend to have low fOC and 

elevated fSolids because of the dominance of large 

mineral particles with low surface area to 

volume ratios and comparatively low carbon 

content. 

 An analysis of the effects of low KOW on the 

ESB calculation is shown in Figure 3-1. The 

departure of the standard ESB (Equation 3-3) 

from the modified ESB (Equations 3-5 and 3-6) 

occurs most substantially at low fOC and low 

fSolids conditions, starting at a log KOW of 

approximately 4. Conversely, at high fSolids and 

high fOC conditions, there is little difference 

between the calculated values (Figure 3-1a). 

When high fOC is combined with low fSolids as 

well as low fOC combined high fSolids, departure 

between the two approaches for calculating 

ESBs are observed but at log KOWs of about 2.50 

(Figure 3-1b). 

 Table 3-3 provides examples of the specific 

effects of fSolid on the derivation of ESBs for four 

chemicals with a range of KOWs. For this 

exercise, fSolids was calculated using paired sand 

and moisture content data from sediment 

samples collected in several U.S. EPA EMAP 

estuarine provinces (i.e., Acadian, Carolinian, 

Virginian) (U.S. EPA 2007a). From the 

moisture content (MC) data (as %), fSolids was 

calculated as: 

fSolids = (100 – MC) ÷ 100 (3-7) 

and regressed against the sand content (%) to 

derive the relationship: 

fSolids = 0.264 + 0.00487 · Sand Content (3-8) 

For this example, fOC values were set to the 

environmentally relevant range of 0.002 to 0.05. 

Examining the extremes, in a sandy sediment 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

3-8 

(80% sand), the ESB for low KOW benzene is 

shown to increase by a factor of three between 

the standard equation (Equation 3-3) and the 

modified equation (Equation 3-5) calculations. 

 Conversely, for high KOW toxaphene, there is 

no difference between the ways of calculating 

ESBs in the same sandy sediment. For a low 

sand content sediment (20% sand), benzene 

ESBs are different by only 20% and again no 

difference was observed between toxaphene 

ESBs. The other two chemicals, malathion and 

1,2,4-trichlorobenzene with KOWs between 

benzene and toxaphene, follow similar trends. 

 Of the 32 chemicals discussed in this 

document, only four have log KOWs less than 2.5 

while 22 have log KOWs that are equal to or less 

than log 4. In situations where low fOC and low 

fSolids are known to occur, it is recommended that 

Equation 3-5 be used to modify the predicted 

ESB. However, it is most likely chemicals in 

this document will occur in environments at 

concentrations of concern when fSolids are low 

and fOC is high, conditions where departure 

between the standard and modified ESBs takes 

place at log KOW of about 2.5, not affecting these 

chemicals too substantially. It maybe possible 

under conditions where a contaminated 

groundwater discharge is occurring into a 

sedimentary environment for fSolids to be 

elevated, fOC to be low, and for low KOW 

chemicals to be present. Under such conditions, 

the use of Equation 3-5 maybe warranted. 

 Finally, the value fSolids is not often reported 

in sediment investigations. In sediments 

suspected of contamination by low KOW

chemicals, it may be important to record this 

sediment characteris-tic (see Equation 3-8 for 

predicting fSolids based on sediment sand 

content). The fSolids values should be available 

from laboratories conducting chemical analyses 

on any contaminated sediment samples as part of 

the determination of moisture content (i.e., 

Percent Solids = 100% - moisture content 

(expressed as %)). 
Calculation of Equilibrium Partitioning Sediment Benchmarks 

3-9 

Figure 3-1 Comparison of ESBs calculated using the standard equation 

(Equation 3-3) and modified equations which include the effects of low KOW 

(Equations 3-5 and 3-6): (a) effects of low fSolids and fOC and high fSolids 

and fOC and (b) effects of high fSolids and low fOC and low fSolids and high fOC. 

In all cases, the FCV is 1000 ug/L. 

(a)

1.5

2

2.5

3

3.5

4

4.5

5

5.5

6

1.5 2.5 3.5 4.5 5.5

Log KOW

Log ESB (ug/g OC)

Modified ESB for fSolids = 0.2 and fOC = 0.002 

Standard ESB 

Modified ESB for fSolids = 0.8 and fOC = 0.1 

(b)

1.5

2

2.5

3

3.5

4

4.5

5

5.5

6

1.5 2.5 3.5 4.5 5.5

Log KOW

Log ESB (ug/g OC)

Modified ESB for fSolids = 0.8 and fOC = 0.002 

Standard ESB 

Modified ESB for fSolids = 0.2 and fOC = 0.1 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

3-10 

Table 3-3 Example calculations of conventional freshwater standard and modified ESBTier2DRY WT values 

(μg/g dry weight) for four chemicals under different fOC and fSolids conditions. See text for 

discussion of the calculation of fSolids. ESB values presented with two significant figures. 

Standard ESBTier2DRY WT : Modified ESBTier2DRY WT* 

(μg/g dry weight) 

Sediment Characteristics 

Chemical 

FCV or 

SCV 

(μg/L) 

Log 

KOW:KOC

Sand = 80% 

Silt-Clay = 20% 

fOC = 0.002 

fSolids = 0.65 

Sand = 50% 

Silt-Clay = 50% 

fOC = 0.025 

fSolids = 0.51 

Sand = 20% 

 Silt-Clay = 80% 

fOC = 0.05 

fSolids = 0.36 

Benzene 130 2.13:2.09 0.032:0.10 0.40:0.52 0.80:1.0 

Malathion 0.097 2.89:2.84 0.00013:0.00019 0.0017:0.0018 0.0034:0.0035 

1,2,4-

Trichlorobenzene 

110 4.01:3.94 1.9:2.0 24:24 48:48 

Toxaphene 0.039 5.50:5.41 0.02:0.02 0.25:0.25 0.50:0.50 

* = See Equation 3-5.
Calculation of Equilibrium Partitioning Sediment Benchmarks 

3-11 

3.4 Conversion to Dry Weight 

Concentration

μg Chemical/gOC = μg Chemical/gDRY WT ÷ 

 (% TOC ÷ 100) (3-9) 

or 

μg Chemical/gOC = μg Chemical/gDRY WT · 

 100 ÷ % TOC (3-10) 

 For example, sediment with a chemical 

concentration of 0.1 μg/gDRY WT and 0.5% TOC 

has an organic carbon-normalized concentration 

of 20 μg/gOC (0.1 μg/gDRY WT · 100 ÷ 0.5 = 20 

μg/gOC). Another sediment with the same dry 

weight concentration (0.1 μg/gDRY WT) but a TOC 

concentration of 5.0% would have an organic 

carbon-normalized concentration of 2.0 μg/gOC 

(0.1 μg/gDRY WT · 100 ÷ 5.0 = 2.0 μg/gOC). 

 In situations where TOC values for 

particular sediments are not available, a range of 

TOC values may be used in a ‘worst case’ or 

‘best case’ analysis. In this situation, the 

organic carbon-normalized ESB values 

(ESBTier2OC) may be ‘converted’ to dry weightnormalized ESB values (ESBTier2DRY WT). This 

‘conversion’ must be performed for each level of 

TOC of interest: 

ESBTier2DRY WT = ESBTier2OC (μg/gOC) · (% TOC 

 ÷ 100) (3-11) 

where ESBTier2DRY WT is the dry weight 

normalized ESB value. Examples of the Tier 2 

ESB values (ESBTier2DRY WT) using conventional 

and narcosis approaches normalized to various 

organic carbon concentrations can be seen in 

Table 3-4. 

 Since organic carbon is the major factor 

controlling the bioavailability of nonionic 

organic compounds in sediments, ESBs have 

been developed on an organic carbon 

normalized basis (e.g., ESBTier2OC) not on a dry 

weight basis. When the chemical concentrations 

in sediments are reported as dry weight 

concentration and organic carbon data are 

available, it is best to convert the sediment 

concentration to μg chemical/g organic carbon. 

These concentrations can then be directly 

compared to the ESB value. This facilitates 

comparisons between the ESB and field 

concentrations relative to identification of hot 

spots and the degree to which sediment 

concentrations do or do not exceed ESB values. 

Conversion from the dry weight to organic 

carbon-normalized concentration can be 

performed using the following equations: 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

3-12 

Table 3-4. Example Tier 2 ESBs (μg/g dry weight) using freshwater conventional (C) and narcosis 

(N) approaches normalized to various total organic carbon (TOC) concentrations. 

Narcosis values for chemicals with a toxicological mode of action in addition to narcosis 

(e.g., pesticides and phthalates) are not presented. Values presented with two 

significant figures. 

Chemical Name Approach 

Dry Weight 

Sediment 

Concentration 

(μg/gDRYWT) at 

0.2% TOC 

Dry Weight 

Sediment 

Concentration 

(μg/gDRYWT) at 

1.0% TOC 

Dry Weight 

Sediment 

Concentration 

(μg/gDRYWT) at 

5.0% TOC 

C 0.032 0.16 0.80 

Benzene 

N 1.3 6.6 33 

BHC other than Lindane C 0.022 0.11 0.55 

Gamma-BHC, Lindane C 0.00074 0.0037 0.019 

C 0.22 1.1 5.5 

Biphenyl 

N 3.0 15 75 

C 0.24 1.2 6.0 4-Bromophenyl phenyl 

ether N 3.2 16 80 

Butyl benzyl phthalate C 2.2 11 55 

C 0.082 0.41 2.1 

Chlorobenzene 

N 1.1 5.7 29 

Diazinon C 0.0015 0.0074 0.037 

C 0.074 0.37 1.9 

Dibenzofuran 

N 3.4 17 85 

1,2-Dichlorobenzene C 0.066 0.33 1.7 

 N 1.6 7.8 39 

1,3-Dichlorobenzene C 0.34 1.7 8.5 

 N 1.6 7.8 39 

1,4-Dichlorobenzene C 0.068 0.34 1.7 

 N 1.6 7.8 39 

Di-n-butyl phthalate C 2.4 12 60 
Calculation of Equilibrium Partitioning Sediment Benchmarks 

3-13 

Chemical Name Approach 

Dry Weight 

Sediment 

Concentration 

(μg/gDRYWT) at 

0.2% TOC 

Dry Weight 

Sediment 

Concentration 

(μg/gDRYWT) at 

1.0% TOC 

Dry Weight 

Sediment 

Concentration 

(μg/gDRYWT) at 

5.0% TOC 

Diethyl phthalate C 0.15 0.77 3.85 

Endosulfan mixed 

isomers C 0.0012 0.006 0.030 

Alpha-Endosulfan C 0.00066 0.0033 0.017 

Beta-Endosulfan C 0.0032 0.016 0.08 

C 0.018 0.089 0.45 

Ethylbenzene 

N 1.9 9.7 49 

C 0.20 1.0 5.0 

Hexachloroethane 

N 2.8 14 70 

Malathion C 0.00013 0.00067 0.0034 

Methoxychlor C 0.0038 0.019 0.095 

C 0.14 0.70 3.5 

Pentachlorobenzene 

N 3.2 16 80 

C 0.28 1.4 7.0 

1,1,2,2-Tetrachloroethane 

N 1.7 8.3 42 

C 0.082 0.41 2.1 

Tetrachloroethene 

N 1.7 8.4 42 

C 0.24 1.2 6.0 

Tetrachloromethane 

N 1.5 7.7 39 

C 0.01 0.05 0.25 

Toluene 

N 1.6 8.1 41 

Toxaphene C 0.02 0.10 0.50 

C 0.13 0.65 3.3 Tribromomethane 

(Bromoform) N 2.4 12 60 

1, 2, 4-Trichlorobenzene C 1.9 9.6 48 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

3-14 

Chemical Name Approach 

Dry Weight 

Sediment 

Concentration 

(μg/gDRYWT) at 

0.2% TOC 

Dry Weight 

Sediment 

Concentration 

(μg/gDRYWT) at 

1.0% TOC 

Dry Weight 

Sediment 

Concentration 

(μg/gDRYWT) at 

5.0% TOC 

N 2.2 11 55 

C 0.006 0.03 0.15 

1, 1, 1-Trichloroethane 

N 1.3 6.6 33 

C 0.044 0.22 1.1 

Trichloroethene 

N 1.3 6.5 33 

C 0.19 0.94 4.7 

m-Xylene 

N 2.0 9.8 49 
Sediment Benchmark Values 

4-1 

Section 4 

Sediment Benchmark Values: 

Application and Interpretation 

4.1 Benchmarks 

Based on the level of protection provided by 

FCVs or SCVs, the procedures described in this 

document indicate that benthic organisms should 

be comparably protected from the adverse 

effects of the 32 nonionic organic chemicals 

listed in Table 3-2, when their concentrations in 

sediment are below the ESBTier2 values. These 

values are appropriate for the protection of both 

freshwater and marine sediments based on the 

assumptions discussed in Section 1, except 

possibly where a locally important species is 

very sensitive or sediment organic carbon is 

<0.2% or the nonionic organic chemical’s log 

KOW is <2 (see Section 3.3 to modify ESBTier2

values). 

 The benchmarks presented in this document 

are the concentrations of a substance that may be 

present in sediment while still protecting benthic 

organisms from the effects of that substance. 

These benchmarks are applicable to a variety of 

freshwater and marine sediments because they 

are based on the biologically available 

concentration of the substance in those 

sediments. 

 The ESBs do not intrinsically consider the 

antagonistic, additive or synergistic effects of 

other sediment contaminants in combination 

with the individual nonionic organic chemicals 

discussed in this document or the potential for 

bioaccumulation and trophic transfer of these 

chemicals to aquatic life, wildlife or humans. 

However, for narcotic chemicals, the toxicity of 

mixtures can be considered (see discussion 

below). Consistent with the recommendations 

of EPA’s Science Advisory Board, publication 

of this document does not imply the use of ESBs 

as stand-alone, pass-fail criteria for all 

applications; rather, when used in a weight of 

evidence approach (Wenning et al. 2005), 

exceedances of ESBs could trigger collection of 

additional assessment data (e.g., benthic 

community composition, whole sediment 

toxicity testing, and other sediment quality 

guideline evaluations (e.g., Long et al. 1995, 

MacDonald et al. 1996, Long and MacDonald 

1998, Swartz 1999, MacDonald et al. 2000a,b, 

Leung et al. 2005). 

4.2 Considerations in the Application and 

Interpretation of ESBs 

4.2.1 Relationship of ESBTier2 to 

 Expected Effects

The ESBTier2 should be interpreted as a 

chemical concentration below which adverse 

effects are not expected. In contrast, at 

concentrations above the ESBTier2, assuming 

equilibrium between phases, effects may occur if 

the chemical is bioavailable as predicted by EqP 

theory. In general terms, the degree of effect 

expected increases with increasing exceedance 

of the ESBTier2. Because the FCV or SCV is 

derived as an estimate of the concentration 

causing chronic toxicity to sensitive organisms, 

effects of this type may be expected when 

sediment concentrations are near the ESBTier2. 

As sediment concentrations increase beyond the 

ESBTier2, one can expect chronic effects on less 

sensitive species and/or acute effects on 

sensitive species. See Section 4.2.6 for further 

discussion. 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

4-2 

4.2.2 Use of EqP to Develop Alternative 

 Benchmarks 

The FCV or SCV is used to define a 

threshold for unacceptable effects based on its 

precedence in establishing unacceptable effects 

in the development of WQC. However, the use 

of EqP to assess sediment contamination is not 

limited to the ESBTier2 and the associated level of 

protection discussed in this document. As 

discussed in earlier sections of this document, by 

substituting water-only effect values other than 

the FCV or SCV into the ESB equations, other 

benchmarks may be developed that are useful in 

evaluating specific types of biological effects, or 

that better represent the ecological protection 

goals for specific assessments. 

4.2.3 Influence of Unusual Forms of 

 Sediment Organic Carbon 

 Partition coefficients used for calculating 

these ESBs are based on estimated and measured 

partitioning from natural organic carbon in 

typical field sediments. Some sediments 

influenced heavily by anthropogenic activity 

may contain sources of organic carbon whose 

partitioning properties are not similar to natural 

organic carbon. The presence of rubber, animal 

or wood processing wastes, relatively 

undegraded woody debris or plant matter (e.g., 

roots, leaves) as well as black carbon (soot) and 

coal may alter contaminant partitioning and 

concentrations of chemicals in interstitial waters 

in unexpected ways (Iglesias-Jimenez et al. 

1997, Grathwohl 1990, Xing et al. 1994). 

Sediments with substantial amounts of these 

materials may exhibit higher concentrations of 

chemicals in interstitial water than would be 

predicted using generic KOC values, thereby 

making the ESBs under protective. If such a 

situation is encountered, the applicability of 

literature KOC values can be evaluated by 

analyzing for the chemical of interest in both 

sediment and interstitial water. If the measured 

concentration in interstitial water is markedly 

greater (e.g., more than twofold) than that 

predicted using the KOC values recommended 

herein (after accounting for dissolved organic 

carbon (DOC) partitioning in the interstitial 

water (U.S. EPA 2003b)), then the ESBs would 

be under protective and calculation of a sitespecific ESB should be considered (see U.S. 

EPA 2001c, 2003b). Conversely, the presence 

of black carbon or coal in a sediment may result 

in reduced chemical activity in sediment and 

correspondingly reduced concentrations of 

chemical in interstitial water. Under these 

conditions, the ESB is likely to be over 

protective and a site-specific ESB may be 

warranted (U.S. EPA 2001c, 2003b). However, 

it should also be noted that the ability to predict 

partitioning based on additional partitioning 

factors like black carbon is still evolving and 

may serve to decrease partitioning-related 

uncertainties in future applications.

 The presence of organic carbon in large 

particles may also influence the apparent 

partitioning. Large particles may artificially 

inflate the effect of the organic carbon because 

of their large mass, but comparatively small 

surface area; they may also increase variability 

in TOC measurements by causing sample 

heterogeneity. The effect of these particles on 

partitioning can be evaluated by analysis of 

interstitial water as described above (U.S. EPA 

2001c), and site-specific ESBs may be used if 

required (U.S. EPA 2003b). It may be possible 

to screen large particles from sediment prior to 

analysis to reduce their influence on the 

interpretation of sediment chemistry relative to 

ESBs. 

4.2.4 Relationship to Risks Mediated 

 through Bioaccumulation and 

 Trophic Transfer

 As indicated above, ESBs are designed to 

address direct toxicity to benthic organisms 

exposed directly to contaminated sediment. 

They are not designed to address risks that may 

occur through bioaccumulation and subsequent 

exposure of pelagic aquatic organisms (e.g., 

predatory fish), terrestrial or avian wildlife, or 

humans. No inference can be drawn between 

attainment of the ESBTier2 and the potential for 

risk via bioaccumulation and trophic transfer; 

the potential for those risks must be addressed 

by separate means.
Sediment Benchmark Values 

4-3 

4.2.5 Exposures to Chemical Mixtures 

 It is very important that users of this 

guidance are aware that the ESBTier2 values 

provided here reflect the expected toxicity of 

that specific chemical individually; they do not 

consider the potential interactive toxicity of that 

chemical with other chemicals in the mixture, 

whether antagonistic, additive or synergistic. 

Thus, a sediment may have concentrations of 

several chemicals at concentrations below the 

individual ESBTier2 values, but still cause toxicity 

because of the aggregate effects of the chemicals 

acting as a mixture. This potential is not 

explicitly incorporated into the derivation of the 

ESBTier2 values because the types and 

concentrations of co-occurring chemicals is 

infinitely variable, and the expected interaction 

of those chemicals is therefore not predictable in 

a general case.

 While the potential for mixture effects must 

be considered for all chemical mixtures, it is of 

special concern for the chemicals with a 

primarily narcotic mode of action discussed in 

this document. Published literature provides a 

convincing argument that narcotic chemicals do 

show additive toxicity with other narcotic 

chemicals (U.S. EPA 2003e). This is especially 

relevant for interpreting ESBTier2 values because 

many, if not most, narcotic chemicals tend to cooccur with other narcotic chemicals because 

they have common sources. For example, 

benzene, xylene, toluene, and ethylbenzene 

commonly co-occur in refined petroleum 

products. Sources of chlorobenzenes often 

include multiple chlorobenzene compounds with 

differing levels of chlorination. Also common 

in sediments is contamination with narcotic 

chemicals outside those with ESBTier2 values 

derived here, such as PAHs (see U.S. EPA 

2003e). 

 For these reasons, it is expected that 

narcosis-based ESBTier2 values will be under 

protective if applied as individual values in most 

sediments, because other narcotic chemicals are 

likely to co-occur. This issue can be addressed 

by using ESBTier2 values in the context of a 

mixture assessment similar to that used for the 

ESB for PAH mixtures (U.S. EPA 2003e). In 

this approach, as shown in the examples in 

Section 4.3, the contribution of each individual 

narcotic chemical to the toxicity of the overall 

mixture is assessed by taking the ratio of the 

measured concentration of that individual 

chemical in the mixture by the corresponding 

single chemical ESBTier2 value. This proportion 

is calculated individually for all narcotic 

chemicals in the mixture, then the proportions 

are summed. If the sum of these values is 

greater than one, then the expected toxicity of 

the mixture is greater than that associated with 

an ESB. If the sum of proportions is less than 

one, then the sediment would not be expected to 

be toxic to benthos as a result of that mixture of 

narcotic chemicals. If PAHs are present in the 

mixture, then the proportions calculated for 

PAHs according to the PAH mixture ESB (U.S. 

EPA 2003e) should be added to the proportions 

calculated for the narcotic ESBTier2 chemicals. 

In addition, if there are other narcotic chemicals 

present in the sediment beyond PAHs and the 

narcotic chemicals with ESBTier2 values given in 

this document, they can be incorporated into the 

analysis using parallel procedures as described 

by Di Toro and McGrath (2000) and Di Toro et 

al. (2000). Also, U.S. EPA (2003e), and the 

references within, provides information about 

narcotic chemicals. Finally, as discussed in 

Section 4.3, the narcotic contribution of 

chemicals with modes of action in addition to 

narcosis (i.e., the pesticides and phthalates) can 

be included. 

 While narcosis is generally discussed for 

chemicals without a more specific mode of 

action, theory would suggest that all nonionic 

organic chemicals would contribute to the 

overall narcotic potency of a mixture. While 

this is technically true, the impact of these other 

chemicals (e.g., pesticides) on the overall 

narcotic potency of a mixture would be 

dependent on the toxicity of the chemical acting 

through a specific mode of action compared to 

its narcotic potency. If a chemical has a very 

high conventional potency (low FCV/SCV) 

compared to its narcosis SCV, then it would 

exceed the conventional chemical-specific ESB 

before it was present in sufficient concentration 

to contribute significantly to the narcotic 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

4-4 

potency of a mixture. One can make this 

comparison by examining the ratios between 

conventionally-derived FCV/SCV values and 

the narcosis SCV as given in Table 3-1. Most of 

these comparisons show that the conventional 

FCV/SCV is generally 100-fold or more lower 

than the narcosis SCV; accordingly, these 

chemicals could not contribute more than 1% to 

an exceedance of a narcosis mixture ESB 

without simultaneously violating the 

conventionally-derived ESBTier2. For this 

reason, the contribution of most non-narcotic 

chemicals discussed in this document can be 

ignored in the calculation of the narcotic 

potency of mixtures without substantial error. 

The exceptions are some of the phthalates, for 

which the conventionally-derived ESBTier2

values are much higher relative to the narcosis 

SCV. Where these chemicals occur near their 

conventionally-derived ESBTier2 concentrations, 

it may be worth considering the potential for 

them to contribute to the narcotic potency of that 

mixture. 

4.2.6 Interpreting ESBTier2s in 

Combination with Toxicity Tests

 Sediment toxicity tests provide an important 

complement to ESBs in interpreting overall risk 

from contaminated sediments. Toxicity tests 

have different strengths and weaknesses 

compared to chemical-specific guidelines, and 

the most powerful inferences can be drawn when 

both are used together. 

 Unlike chemical-specific guidelines, toxicity 

tests are capable of detecting any toxic chemical, 

if it is bioavailable in toxic amounts; one does 

not need to know what chemicals of concern are 

present to monitor the toxicity of sediment. 

Toxicity tests are also useful for detecting the 

combined effects of chemical mixtures, if those 

effects are not considered in the formulation of 

the applicable chemical-specific guideline or 

benchmark. 

 On the other hand, toxicity tests also have 

weaknesses; they provide information only for 

the species tested, and only for the endpoints 

measured. This is particularly critical given that 

a majority of the sediment toxicity tests 

conducted at the time of this writing primarily 

measure short-term lethality (in some cases 

growth), although the use of chronic sediment 

toxicity tests is becoming more common. 

Chronic sediment toxicity test procedures have 

been developed and published for some species 

(e.g., U.S. EPA 2001b), but these procedures are 

more resource-intensive as compared to acute 

tests. In contrast, the ESBTier2 is intended to 

protect most species against both acute and 

chronic effects. 

 Many assessments may involve comparison 

of sediment chemistry (relative to ESBs or other 

sediment quality guidelines) and toxicity test 

results. In cases where results using these two 

methods agree (either both positive or both 

negative), the interpretation is clear. In cases 

where the two disagree, the interpretation is 

more complex and requires further evaluation. 

 Individual ESBs address only the effects of 

the chemical or group of chemicals for which 

they are derived. For this reason, if a sediment 

shows toxicity but does not exceed the ESBTier2

value for a chemical of interest, it is likely that 

the cause of toxicity is a different chemical or 

chemicals (although the chemical of interest 

maybe contributing to observed toxicity as a 

component of a mixture). This result might also 

occur if the partitioning of the chemical in a 

sediment is different from that assumed by the 

KOC value used (see Section 4.2.3 Influence of 

Unusual Forms of Sediment Organic Carbon

above). 

 In other instances, it may be that an ESBTier2

is exceeded but the sediment is not toxic. As 

explained above, these findings are not mutually 

exclusive, because the inherent sensitivity of the 

two measures is different. Four possible 

circumstances may account for this result. First, 

the ESBTier2 is intended to protect relatively 

sensitive species against both acute and chronic 

effects, whereas toxicity tests are performed 

with species that may or may not be sensitive to 

chemicals of concern, and often do not 

encompass the most sensitive endpoints (e.g., 

growth or reproduction). As such, one may not 

expect a nonionic organic chemical 

concentration near the ESBTier2 to cause lethality 
Sediment Benchmark Values 

4-5 

in a short-term toxicity test. Second, a GLIbased SCV, because of the use of SAFs, may 

overestimate a contaminant’s toxicity compared 

to the intended level of protection, as described 

in Section 2.4. Third, site-specific conditions 

may result in lower bioavailability than assumed 

based on equilibrium partitioning (see Section 

4.2.3). Finally, the organism may avoid the 

sediment or have other mechanisms to reduce 

exposure relative to that assumed by the EqP 

approach. To distinguish these potential 

explanations, species- and endpoint-specific 

toxicity information could be used to better 

interpret toxicity test results, and SCV 

derivation could be reviewed. Spiked sediment 

tests could also be used to verify the exposureresponse relationship for that particular 

organism and contaminant. If these lines of 

evidence do not account for the discrepancy 

between predicted and observed toxicity, then 

site-specific chemical partitioning could be 

investigated (U.S. EPA 2003b). 

 As discussed above, a good method for 

evaluating the results of toxicity tests is to 

calculate effect concentrations in sediment that 

are species and endpoint specific. For some 

species contained in the water-only toxicity data 

for the 32 nonionic organic chemicals discussed 

here, effect concentrations in sediment can be 

calculated that are specific for that organism 

(U.S. EPA 2003e). These values could then be 

used to directly judge whether the absence of 

toxicity in the test would be expected from the 

concentration of nonionic organics chemicals 

present. As noted above, the magnitude of error 

between toxicity test results and predicted 

effects is made larger because of the use of 

SCVs, and SAFs, to derive some ESBTier2 values 

(see discussion in Section 2.4). 

 If the exceedance of an ESB is sufficient that 

one would expect effects in a toxicity test but 

they are not observed, it is prudent to evaluate 

the partitioning behavior of the chemical in the 

sediment. This is performed by isolating 

interstitial water from the sediment and 

analyzing it for the chemicals of interest. 

Predicted chemical concentrations in the 

interstitial water can be calculated from the 

measured concentrations in the solid phase 

(normalized to organic carbon) as follows: 

μg chemical/L = (μg chemical/gOC) · 

 (103

gOC/KgOC ÷ KOC) (4-1) 

 For chemicals with log KOW greater than 5.5, 

corrections for DOC partitioning in the 

interstitial water will be necessary (see 

Gschwend and Wu 1985, Burkhard 2000, U.S. 

EPA 2003b). See U.S. EPA (2003b) for a 

discussion of the effects of DOC on ESB 

derivation. If the measured chemical in the 

interstitial water is substantially less (e.g., 2-3 

fold lower or more), it suggests organic carbon 

in that sediment may not partition similarly to 

more typical natural organic carbon, and 

derivation of site-specific ESBs based on 

interstitial water may be warranted (U.S. EPA 

2003b). 

 Finally, in addition to the use of sediment 

toxicity tests for interpreting ESBTier2 values, the 

generation of acute and chronic water-only data 

with benthic organisms for the nonionic organic 

chemicals discussed in this document would be 

very beneficial. Further, acute and chronic 

whole sediment toxicity data sets with these 

chemicals would also complement the 

interpretation of the ESBs. 

4.2.7 Effects of Disequilibrium 

Conditions

 As discussed throughout this document, the 

EqP is based on an assumption of chemical 

equilibrium between the solid phase of sediment 

and the interstitial water. In natural settings, 

equilibrium may not always exist or may be 

disturbed by episodic events. As such, the 

potential for disequilibrium and its impact on the 

interpretation of the equilibrium-based ESBs 

should be considered. For purposes of this 

discussion, two types of disequilibria are 

discussed: 1) disequilibrium between the solid 

phase sediment and interstitial water; and 2) 

disequilibrium between the sediment and 

overlying water column. 

 With regard to the first, ESBs are based on 

an assumption that nonionic organic chemicals 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

4-6 

are in equilibrium with the sediment and 

interstitial water and are associated with 

sediment primarily through absorption to 

sediment organic carbon. When new chemical 

is introduced to a sediment, time is required for 

the chemical to distribute itself between 

interstitial water and sediment organic carbon. 

The time required for equilibrium to be achieved 

is dependent on the characteristics and 

concentration of the chemical. Sediment spiking 

experiments suggest that this is typically in the 

range of weeks. 

 In areas where sediment erosion and 

deposition are highly dynamic, equilibrium may 

be frequently disturbed. The degree to which 

this would affect the applicability of ESBs 

depends on the degree and frequency of 

equilibrium disruption. As noted above, even 

high Kow nonionic organic compounds come to 

equilibrium in clean sediment in a period of 

days, weeks or months. Equilibrium times 

should be even shorter for mixtures of two 

sediments that each have previously been at 

equilibrium. This is particularly relevant in tidal 

situations where large volumes of sediments are 

eroded and deposited, even though near 

equilibrium conditions may predominate over 

large areas. While the potential for 

disequilibrium is recognized, it is probably 

unwise to deviate from the equilibrium 

assumption without strong evidence that 

disequilibrium exists over the long term to a 

sufficient degree to change the expected toxicity 

of sediment contamination. Recognize that even 

if there are short-term disturbances to 

equilibrium between sediment and interstitial 

water, conditions may quickly re-approach 

equilibrium between disturbances, such that an 

equilibrium-based approach is still reasonable, 

even if there are periods of 

disturbance/disequilibrium. If it is shown that 

disequilibrium exists to such an extent that 

equilibrium-based ESBs are inappropriate, sitespecific experimentation may be useful in 

developing a modified approach (U.S. EPA 

2003b). 

 Even where equilibrium exists between the 

solid phase sediment and interstitial water, there 

is often disequilibrium between the sediment 

and overlying water. This is particularly true for 

legacy pollution where input of new 

contamination to the water body has ceased or 

greatly decreased, and the sediment is now a 

source of contamination to the overlying water. 

Some have argued that such disequilibrium 

reduces exposure of sediment organisms, 

particularly for those that interact substantially 

with the overlying water. While the theoretical 

possibility is clear, the quantitative data from 

which an appropriate compensation could be 

calculated is lacking. Moreover, many toxicity 

test procedures used in the development and 

testing of EqP theory involve renewal of 

overlying water and thus include some degree of 

disequilibrium between the sediment and 

overlying water. Nonetheless, results from these 

tests are generally explicable through EqP 

predictions (e.g., Swartz et al. 1990, DeWitt et 

al. 1992, Hoke et al. 1994), suggesting that the 

degree to which this disequilibrium affects 

exposure is not exceptional, at least for those 

organisms. In instances where it is determined 

that EqP does not apply for a particular sediment 

because of the disequilibrium situations 

discussed above, site-specific experimentation 

may be useful in developing a modified 

approach (U.S. EPA 2003b). 

 A special case may be in spill situations, 

where there is a sudden, dramatic influx of new 

chemical into a system. Immediately following 

a spill, it can be expected that one or both types 

of disequilibrium might exist, that the overlying 

water might have higher chemical activity than 

in the sediment, and that the solid-phase 

sediment may not be in equilibrium with the 

interstitial water. In this situation there is a high 

potential for ESBs to be under protective. 

 In sediments where particles of undissolved 

chemical occur, disequilibrium exists and the 

benchmarks may be over protective in the sense 

that chemical concentrations in interstitial water 

may be lower than would be predicted based on 

chemical concentrations in sediment and foc. 

However, it is also true that in this situation 

basing an assessment solely on chemical 

concentrations in the interstitial water might 
Sediment Benchmark Values 

4-7 

under-represent the degree of contamination. 

This is because sufficient chemical exists to 

contaminate a larger mass of sediment if the 

sediment containing as yet undissolved chemical 

is later mixed with other, less contaminated 

sediment. 

 Clearly, situations where substantial 

disequilibrium exists can result in several 

complexities for interpreting sediment chemistry 

in the context of ESBs. While it is true that 

ESBs may be less accurate for such situations, it 

is also important that an alternate assessment 

approach be developed that adequately accounts 

for the site-specific conditions. Disequilibrium 

should not be used as an excuse to dismiss ESB 

values without developing an alternate 

conceptual model on which to base the 

assessment. 

4.3 Example Application of ESBTier2s 

 Using Conventional and Narcosis 

 Approaches and EqP-based 

 Interpretation 

 Table 4-1 shows sediment chemistry data (in 

ug/gOC) for four example marine sediments (i.e., 

A, B, C, D) along with the corresponding 

conventional and narcosis ESBTier2 values. The 

sediment concentrations have been normalized 

for a TOC of 4.5% using Equation 3-9. 

Assuming a fSolids of 0.20, ESBTier2 values for 

benzene, 1,1,2,2-tetrachloroethane, and 

tetrachloroethene were adjusted using Equations 

3-5 and 3-6. These values were compared to 

measured sediment chemistry. For each of the 

four sediments, Table 4-1 also shows the ratios 

of the measured concentration in sediment to the 

conventional and narcosis ESBTier2s. For the 

chemicals with modes of action in addition to 

narcosis (i.e., the pesticides in these examples), 

their narcosis contribution is not reported but 

was calculated to be very small and did not 

substantially affect the sum narcosis ESBTUs 

(see discussion in Section 2.3.2). 

 In sediment A (Table 4-1), all measured 

chemicals were below their conventional and 

narcosis ESBTier2 values. In addition, the sum of 

the ratios of the measured concentrations to their 

narcosis ESBTier2 (sum narcosis ESBTUs) was 

only 0.01, far below a value of 1 which would 

indicate concern for a narcotic effect caused by a 

mixture of chemicals. While these results 

themselves indicate no reason to suspect adverse 

effects to benthic organisms from these 

chemicals, it must be remembered that this 

conclusion is limited to the effects of these 

specific chemicals. It is, of course, still possible 

that other chemicals could be present in the 

sediment at concentrations that could cause 

adverse effects. Toxicity testing would be one 

way to address the potential for toxicity caused 

by unmeasured chemicals. 

 Sediment B (Table 4-1) has the same 

concentrations of all measured chemicals as in 

sediment A, except for diazinon and malathion, 

which exceed their conventional ESBTier2 by 

factors of 3.9 and 11, respectively. These 

exceedances suggest concern for adverse effects 

of these chemicals on benthic organisms, subject 

to the assumptions underlying the ESB approach 

as discussed elsewhere in this document. 

Toxicity testing, particularly with species 

sensitive to these chemicals, could be used to 

further evaluate the presence of toxicity, as well 

as assessing the potential presence of toxicity 

from unmeasured chemicals. In addition, spiked 

sediment tests with these chemicals and/or 

sediment Toxicity Identification Evaluation 

(TIE) studies (U.S. EPA 2007b) may also be 

useful in evaluating the expected contribution of 

these chemicals at these concentrations to 

sediment toxicity. 

 For sediment C (Table 4-1), concentrations of 

the pesticides diazinon, alpha endosulfan and 

malathion are all below their conventional 

ESBTier2 values, but three of the other measured 

chemicals, benzene, ethylbenzene and toluene, 

exceed their corresponding conventional 

ESBTier2 values by factors of 4.3, 5.1, and 7.6, 

respectively. In contrast, these same chemicals 

do not exceed their narcosis ESB values, nor 

does the sum of narcosis ESBTUs exceed 1. 

The exceedance of the conventional ESBTier2s 

suggests that the levels of benzene, 

ethylbenzene, and toluene are high enough to be 

of potential concern when evaluated by the GLI 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

4-8 

Tier 2 assessment approach (GLI 1995). 

However, the fact that the sum of narcosis 

ESBTUs does not exceed one raises the 

possibility that the exceedances for these 

chemicals may be influenced by conservatism in 

the GLI Tier 2 paradigm, particularly as it 

relates to narcotic chemicals (see Section 2.4 for 

additional discussion). Another issue to be 

considered relates to the likelihood that other 

narcotic chemicals, not listed in Table 4-1 may 

be present and contribute to an overall mixture 

toxicity. In particular, the elevated 

concentrations of benzene, ethylbenzene and 

toluene may suggest contamination with 

hydrocarbons such as refined petroleum 

products that may also contain PAHs or other 

hydrocarbons that could contribute to a narcotic 

mixture effect. Further analytical chemistry and 

toxicity testing would be logical supplements to 

the information in Table 4-1 for determining the 

overall likelihood of risk to benthic organisms. 

If PAHs are present, separate ESB guidance for 

PAH mixtures (U.S. EPA 2003e) can provide an 

approach to evaluate their potential contribution 

to narcotic toxicity. The theory underlying 

narcotic toxicity (Di Toro and McGrath 2000, Di 

Toro et al. 2000, U.S. EPA 2003e) suggests that 

the sum of ESBTUs for PAHs could be added to 

the sum of narcosis Tier 2 ESBTUs in Table 4.1 

to assess the combined potency of those 

chemicals. 

 Finally, in sediment D (Table 4-1), 

concentrations of measured pesticides are again 

low, but concentrations of both BTEX 

compounds (i.e., benzene, toluene, 

ethylbenzene, xylene) and the measured 

chlorinated compounds are higher than for 

sediment C. Conventional ESBTier2s are 

exceeded for several compounds; although no 

individual narcosis ESBTier2 values are exceeded, 

the sum of narcosis ESBTUs does exceed 1. In 

this case, both the conventional ESBTier2s and the 

narcosis mixture analysis suggests the potential 

for adverse effects to benthic organisms. Also, 

the finding that many compounds, including 

BTEX, chlorinated benzenes, and other 

chlorinated hydrocarbons are all present in 

concentrations approaching their narcosis 

ESBTier2s makes it likely that other, unmeasured 

chemicals in these families may also be present 

at toxicologically significant concentrations in 

this sediment, because typical sources of these 

chemicals to the environment often include 

many different related compounds (e.g., other 

di-, tri-, tetra-and hexachloro-benzenes). While 

this document does not address these additional 

compounds specifically, an approach for 

addressing their contribution in a way similar to 

that used in this document is provided by Di 

Toro and McGrath (2000) and Di Toro et al. 

(2000). 
Sediment Benchmark Values 

4-9 

Table 4-1 Example applications of ESBTier2 values with several nonionic organic chemicals using 

conventional and narcosis approaches. In this example, four marine sediments with 4.5% TOC and 

fSolids of 0.20 are assessed. Sediment concentrations are shown with organic carbon normalization 

using Equation 3-9. ESBTier2 values modified with Equations 3-5 and 3-6 to account for fSolids for 

benzene, 1,1,2,2-tetrachloroethane and tetrachloroethene are shown rather than ESBTier2 values in 

Table 3-1. 

Sediment A 

Conventional

* ESB 

(μg/gOC) 

Narcosis* 

ESB 

(μg/gOC) 

Sediment 

Concentration 

(μg/gOC) 

Sediment 

Concentration/ 

Conventional 

ESB 

Sediment 

Concentration/ 

Narcosis ESB 

Benzene 28 1100 0.95 0.0339 0.0009 

Ethylbenzene 8.9 970 0.23 0.0258 0.0002 

Toluene 5 810 0.32 0.0640 0.0004 

m-Xylene 94 980 0.42 0.0045 0.0004 

Chlorobenzene 41 570 0.67 0.0163 0.0012 

1,2-Dichlorobenzene 33 780 1.2 0.0364 0.0015 

Pentachlorobenzene 70 1600 2.3 0.0329 0.0014 

Tetrachloromethane 120 770 1.5 0.0125 0.0019 

1,1,2,2-

Tetrachloroethane 190 1200 1.3 0.0068 0.0011 

Hexachloroethane 100 1400 0.89 0.0089 0.0006 

Trichloroethene 22 650 0.51 0.0232 0.0008 

Tetrachloroethene 50 1000 0.53 0.0106 0.0005 

Diazinon 3.6 ^ 0.02 0.0056 ^ 

Alpha-Endosulfan 0.051 ^ 0.01 0.1961 ^ 

Malathion 0.11 ^ 0.01 0.0909 ^ 

 

Sum Narcosis 

ESBTUs 

 

0.0111 

Sediment B 

Conventional

* ESB 

(μg/gOC) 

Narcosis* 

ESB 

(μg/gOC) 

Sediment 

Concentration 

(μg/gOC) 

Sediment 

Concentration/ 

Conventional 

ESB 

Sediment 

Concentration/ 

Narcosis ESB 

Benzene 28 1100 0.95 0.0339 0.0009 

Ethylbenzene 8.9 970 0.23 0.0258 0.0002 

Toluene 5 810 0.32 0.0640 0.0004 

m-Xylene 94 980 0.42 0.0045 0.0004 

Chlorobenzene 41 570 0.67 0.0163 0.0012 

1,2-

Dichlorobenzene 33 780 1.2 0.0364 0.0015 

Pentachlorobenzene 70 1600 2.3 0.0329 0.0014 
 Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium 

4-10 

Tetrachloromethane 120 770 1.5 0.0125 0.0019 

1,1,2,2-

Tetrachloroethane 190 1200 1.3 0.0068 0.0011 

Hexachloroethane 100 1400 0.89 0.0089 0.0006 

Trichloroethene 22 650 0.51 0.0232 0.0008 

Tetrachloroethene 50 1000 0.53 0.0106 0.0005 

Diazinon 3.6 ^ 13.9 3.8611 ^ 

Alpha-Endosulfan 0.051 ^ 0.01 0.1961 ^ 

Malathion 0.11 ^ 1.2 10.9091 ^ 

 

Sum Narcosis 

ESBTUs 

 

0.0111 

Sediment C 

Conventional

* ESB 

(μg/gOC) 

Narcosis* 

ESB 

(μg/gOC) 

Sediment 

Concentration 

(μg/gOC) 

Sediment 

Concentration/ 

Conventional 

ESB 

Sediment 

Concentration/ 

Narcosis ESB 

Benzene 28 1100 120 4.2857 0.1091 

Ethylbenzene 8.9 970 45 5.0562 0.0464 

Toluene 5 810 38 7.6000 0.0469 

m-Xylene 94 980 31 0.3298 0.0316 

Chlorobenzene 41 570 1.3 0.0317 0.0023 

1,2-

Dichlorobenzene 33 780 3.7 0.1121 0.0047 

Pentachlorobenzene 70 1600 8.8 0.1257 0.0055 

Tetrachloromethane 120 770 1.1 0.0092 0.0014 

1,1,2,2-

Tetrachloroethane 190 1200 0.66 0.0035 0.0006 

Hexachloroethane 100 1400 0.43 0.0043 0.0003 

Trichloroethene 22 650 0.19 0.0086 0.0003 

Tetrachloroethene 50 1000 0.21 0.0042 0.0002 

Diazinon 3.6 ^ 0.02 0.0056 ^ 

Alpha-Endosulfan 0.051 ^ 0.01 0.1961 ^ 

Malathion 0.11 ^ 0.01 0.0909 ^ 

 

Sum Narcosis 

ESBTUs 

 

 0.2493 

Sediment D 

Conventional

* ESB 

(μg/gOC) 

Narcosis* 

ESB 

(μg/gOC) 

Sediment 

Concentration 

(μg/gOC) 

Sediment 

Concentration/ 

Conventional 

ESB 

Sediment 

Concentration/ 

Narcosis ESB 

Benzene 28 1100 410 14.6429 0.3727 

Ethylbenzene 8.9 970 320 35.9551 0.3299 

Toluene 5 810 290 58.0000 0.3580 
Sediment Benchmark Values 

4-11 

m-Xylene 94 980 360 3.8298 0.3673 

Chlorobenzene 41 570 250 6.0976 0.4386 

1,2-

Dichlorobenzene 33 780 140 4.2424 0.1795 

Pentachlorobenzene 70 1600 87 1.2429 0.0544 

Tetrachloromethane 120 770 12 0.1000 0.0156 

1,1,2,2-

Tetrachloroethane 190 1200 16 0.0842 0.0133 

Hexachloroethane 100 1400 31 0.3100 0.0221 

Trichloroethene 22 650 27 1.2273 0.0415 

Tetrachloroethene 50 1000 15 0.3000 0.0150 

Diazinon 3.6 ^ 0.02 0.0056 ^ 

Alpha-Endosulfan 0.051 ^ 0.01 0.1961 ^ 

Malathion 0.11 ^ 0.01 0.0909 ^ 

 

Sum Narcosis 

ESBTUs 

 

 2.2081 

* = See Section 2.3 for definition. 

^ = Not Reported. 

References 

5-1 

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410 chemicals and 66 species of freshwater 

animals. Resource Pub. 160. U.S. Dept. 

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phthalate esters to Daphnia magna and rainbow 

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criteria for the protection of aquatic organisms 

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human health and wildlife bioaccumulation 

factors for the Great Lakes Initiative. U.S. 

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Research and Development, Duluth, MN, USA. 

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benchmarks for screening potential 

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sediment-associated contaminants with 

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 EPA-820-B-95-005. Office of Water, 

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equilibrium partitioning sediment benchmarks 

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Appendix A 

Description of the Derivation of Conventional Freshwater Chronic Toxicity 

Values using the Great Lakes Water Quality Initiative 

(GLI 1995) Approach 
A-2 

A.1 Acquisition and Review of 

Conventional Aquatic Toxicity Data 

 As discussed above, when possible, 

conventional ESBs were based on FCVs for 

aquatic life (Stephan et al.1985). When FCVs 

could not be derived, the ESBs were calculated 

from SCVs for aquatic life using the GLI 

approach (Suter and Mabrey 1994, GLI 1995, 

Suter and Tsao 1996). The purpose of this 

section is to describe the procedure used to derive 

SCVs from data in AQUIRE (now ECOTOX) 

and other sources. 

The following restrictions on toxicity data and 

reference sources used were applied: 

1. Acute toxicity data for only freshwater species 

were used (GLI, 1995), whereas acute-chronic 

ratios (ACRs) for both freshwater and saltwater 

species were used in order to expand the number 

of available ACRs. 

2. Only the following were used as sources of 

references: 

a. U.S. Environmental Protection Agency's 

AQUIRE (now ECOTOX) database. 

b. Tables in existing documents from EPA's 

Office of Research and Development. 

 A preliminary review was conducted on test 

results obtained by means of a search of AQUIRE 

(now ECOTOX). Only information that could be 

retrieved from AQUIRE (now ECOTOX) was 

used in this review. Each test result was rejected 

if one or more of the reasons listed below 

applied. The first three reasons for rejection given 

below were addressed in the search strategy used 

to find test results in AQUIRE (now ECOTOX). 

All pertinent test results were printed and 

reviewed manually using the “Reasons for 

Rejection of a Test Result Based on Information 

in AQUIRE.” For each test result that was not 

rejected, a copy of the original report was 

reviewed as described in the next section of this 

report, “Data Rejection Checklist.” 

Reasons for Rejection of a Test Result Based on 

Information in AQUIRE (now ECOTOX): 

___ The test was not conducted in the 

laboratory (i.e., Site was not LAB). 

___ Poor documentation (the documentation 

code (Dc) was not 1 or 2). 

___ The endpoint was not reported (i.e., Endpt

was left blank or was “NR”). 

___ The purity of the test chemical was less 

than 80% (i.e., Chem_char < 80%). 

___ The test species (Latin, Species) was not 

an aquatic animal. 

___ The test species (Latin, Species) was not a 

resident North American species. 

___ The test species was Wyeomyia smithii (i.e., 

the pitcher plant mosquito) or was in the 

genus Artemia (i.e., it was a brine shrimp). 

The following reasons for rejection applied only 

to acute toxicity tests: 

___ The test exposure was not static, renewal, 

or flow-through (i.e., Extype was not S, R, 

or F). 

___ The test was not conducted in freshwater

(i.e., Media was not FW). 

___ If the test species was Cladoceran (CLAD, 

water flea), copepod (COPE), midge or 

phantom midge (insect, family 

Chironomidae, order Diptera, DIPT), the 

Duration was less than 2 days (48 hr). 

___ For all other animal species, the Duration

was less than 4 days (96 hrs). 

___ The endpoint was not LC50 or EC50 or IC50. 

___ The effect was not EQU, IMM, and/or 

MOR, except that SHD (incompletely 

developed shells, change in the ability to 

grow a shell) was acceptable for bivalve 

molluscs. 

The following reasons for rejection applied only 

to chronic toxicity tests: 

___ The concentrations of test material were not 

measured (i.e., Method was not M) in the 

test solution. 

___ The test exposure was not flow-through or 

renewal (i.e., Extype was not F or R). 
 

A-3 

If the test species was a Cladoceran (CLAD, 

water flea) or copepod (COPE): 

___ The Life stage was older than 24 hr. 

___ The Duration was less than 21 days 

 (except less than 7 days for Ceriodaphnia). 

___ For all other species, the Duration was 

 less than 24 days. 

 Stephan et al. (1985), references cited therein, 

and other pertinent publications (e.g., the 

American Fisheries Society guidebook series for 

North American fishes, molluscs, and crustacea) 

were used to determine whether a vertebrate or 

invertebrate aquatic species is resident in North 

America. Because of various constraints, some 

species listed below were assumed to be 

nonresident if a limited search did not 

demonstrate that they were resident. Any species 

that was said to have been field-collected in 

North America was considered resident. 

 Examples of resident species not in Stephan 

et al. (1985): 

Chironomus riparius midge 

Gila elegans bonytail 

Gillia attilis buffalo pebblesnail 

Lestes congener damselfly 

Sigara alternata water boatman 

Stenonema 

 interpunctatum mayfly 

Umbra pygmaea eastern mudminnow 

Examples of nonresident species not in Stephan 

et al. (1985): 

Anguilla anguilla common eel 

 (assumed nonresident) 

Anodonta anatina fresh-water mussel 

Anodonta cyanea swan mussel 

Barbus ticto two-spotted; 

 tic tac toe barb 

Carassius carassius Crucian carp 

Chana punctatus 

 or gachua snake-head catfish 

Cirrhinus mrigala carp, hawkfish 

Heteropneustes fossilis Indian catfish 

Macrobrachiu 

 rosenbergii giant freshwater prawn 

Mystus vittatus catfish 

Notopterus notopterus featherback 

Paratelphusa 

 jacquemontii crab (probably) 

Rasbora heteromorpha harlequinfish/red 

rasbora 

Spicodiaptomus 

chilospinus calanoid copepod 

(assumed nonresident) 

 Resident status of organisms for which only 

the genus and “sp.” were provided as the 

scientific name (e.g., Peltodytes sp.) was based 

on the location where the organisms were 

collected. 

 This checklist was used to review the 

acceptability of results of aquatic toxicity tests on 

nonionic organic chemicals including all 

references that were obtained from AQUIRE 

(now ECOTOX) and passed the “Preliminary 

Review of Records from AQUIRE.” Because 

this second review was performed on all test 

results regardless of whether the reference came 

from AQUIRE (now ECOTOX), all items on the 

AQUIRE (now ECOTOX) review were also 

included here. This review was performed using 

the original publication and sources of 

supplemental information; this review was not 

performed using only secondary sources. 

 This final review covered both the quality of 

the test result and whether it was the kind of 

result that had been specified for use in this 

document. A test result that was deemed 

unacceptable for use in this document might be 

acceptable for another use. A result that was 

deemed unacceptable was not necessarily an 

incorrect result; it just might have been too 

questionable to use. For example, an LC50

obtained using unacceptable methodology might 

have been the same as an LC50 using acceptable 

methodology. The LC50 from the test using the 

unacceptable methodology, however, was 

unacceptable because it was questionable. In 

many cases, some test results in a publication 

were acceptable, whereas others were 

unacceptable. Similarly, one result from a test 

(e.g., a 24-hr LC50) might not have been 

acceptable although another (e.g., a 48-hr LC50) 

was acceptable. 

 Each test result was placed in one of three 

categories for the purposes of this review: 
A-4 

1. A test result was assumed acceptable if the test 

was conducted at EPA laboratories in Corvallis 

(OR), Duluth (MN), Gulf Breeze (FL), or 

Narragansett (RI); was conducted at the U.S. 

Fish and Wildlife Service laboratory in La 

Crosse, Wisconsin; was contained in Mayer 

and Ellersieck (1986); was conducted at the 

U.S. Department of the Interior laboratory in 

Columbia, Missouri, after the period covered 

by the report published by Mayer and 

Ellersieck (1986); or was contained in the 

University of Wisconsin-Superior data 

summary volumes (Brooke et al.1984; Geiger 

et al.1985, 1986, 1988, 1990). Reports from 

these sources usually contained information 

concerning methodology, but the result was 

assumed acceptable even if little information 

was available concerning methodology. 

Results in this category were rejected only if a 

major problem was known to exist. 

2. A test result was assumed acceptable if the test 

was reported to have been conducted according 

to procedures described by such American 

Society for Testing and Materials (ASTM) 

standards as: 

ASTM Standard E 729, Guide for Conducting 

Acute Toxicity Tests with Fishes, 

Macroinvertebrates, and Amphibians 

ASTM Standard E 1241, Guide for Conducting 

Early Life-Stage Toxicity Tests with Fishes 

ASTM Standard E 1193, Guide for Conducting 

Renewal Life-Cycle Tests with Daphnia magna

ASTM Standard E 1295, Guide for Conducting 

Three-brood, Renewal Toxicity Tests with 

Ceriodaphnia dubia

Or procedures described by Standard Methods, 

the European Economic Community (EEC), the 

International Organization for Standardization, or 

the Organization for Economic Cooperation and 

Development (OECD), and if the description of 

the methodology at least mentioned such factors 

as acclimation, temperature control, controls, 

solvent and solvent control (if used), source of 

water, randomization, and duplication. Results in 

this category were, however, rejected if a single 

major problem was identified. 

3. All other test results were in a third category. 

Whether they were accepted or rejected 

depended on the information available 

concerning the methodology and results. The 

result was rejected if insufficient information 

was available to evaluate the test. 

Identification of a single major problem, or at 

least three minor problems, were grounds for 

rejection of a test result, and most results with 

this number of identified problems were 

rejected. Best professional judgment was; 

however, applied to determine whether 

identified problems warranted rejection of the 

result. 

 The review of test results required judgments, 

starting with decisions about what items to 

include on the following list, and whether each 

one was major or minor. Applying the list also 

required judgment. For example, a test result was 

always rejected if a surfactant was used in the 

preparation of a stock solution or the test 

solutions, even if the test was conducted by 

Mount and Stephan (1967). If no information 

was given concerning the use of surfactants, test 

results in the first category above were deemed 

acceptable, but it was identified as a problem for 

other test results. 

 Reasons for Rejection (Asterisks indicate 

major problems; all others are minor problems.) 

Report 

___ * The test results were not available for 

public distribution in a dated and signed 

hard copy (e.g., publication, manuscript, 

letter, memorandum, etc.). 

___ * The test results were from a secondary 

publication, except those results 

contained in the Manual of Acute 

Toxicity: Interpretation and Data Base 

for 410 Chemicals and 66 Species of 

Freshwater Animals (Mayer and 

Ellersieck 1986) were considered 

acceptable. 

___ * Methodology and/or results were not 

adequately and clearly described, except 

for category 1. In some cases, other 

papers by the same or different authors 

provided the necessary information. 
 

A-5 

Test chambers 

___ All test chambers and any compartments 

within the chambers were not identical. 

___ * The test result was from a microcosm or 

model ecosystem study. 

___ * The test chambers were made from or 

lined with PVC, except that the presence 

of PVC in chambers was acceptable if the 

test material was miscible with or very 

soluble in water or concentrations of the 

test material in solutions were measured. 

Test material 

___ The test material was not adequately 

described. 

___ * The organisms were exposed to the test 

material via food, sediment, injection, 

gavage, etc.; exposure was not via only 

the test solutions. 

___ * The test material was a component of a 

drilling mud, effluent, fly ash, mixture, 

formulation, sediment, or sludge. 

___ The purity of the test material was less 

than 80 percent (e.g., the test material 

contained less than 80 percent active 

 ingredient); analytical-grade, reagentgrade, or technical-grade materials were 

considered acceptable unless known to be 

unacceptable. 

Exception: The test material could contain less 

active ingredient if data were available to show 

that tests on the material produced the same 

results as tests on material that was at least 80 

percent pure. 

___ * The test material was an emulsifiable 

concentrate, a wettable powder, or a 

specially prepared mixture that contained 

a surfactant and/or an organic solvent 

that was not miscible with water. 

___ * A surfactant or an organic solvent that 

was not miscible with water was used in 

the preparation of a stock solution or the 

test solutions. 

___ If a water-miscible solvent was used to 

prepare the stock solution and/or test 

solutions, its concentration exceeded 0.5 

mL/L in the test solutions. 

___ * The test material was introduced into the 

test chamber by evaporating it onto the 

test chamber and adding dilution water. 

Exception: This procedure was acceptable if the 

concentrations of test material in the test 

solutions were measured. 

___ * Concentrations of test material in the test 

solutions were not measured for chronic 

toxicity tests (measurement was not 

necessary for acute tests). 

___ Measured concentrations of test material 

during a flow-through test varied too much. 

___ * For highly volatile, hydrolyzable, or 

degradable materials, the test was static 

or renewal (i.e., not flow-through) and/or 

concentrations of test material were not 

measured often enough using acceptable 

analytical methods. 

___ * Exposure to the test material was 

intermittent, not continuous. 

Test organisms 

___ * The test species was not an aquatic 

animal. 

___ * The test species was a single-celled 

organism. 

___ * The test species was not a resident North 

American species. 

___ * The test species was Wyeomyia smithii

(i.e., the pitcher plant mosquito) or was 

in the genus Artemia (i.e., it was a brine 

shrimp). 

___ * The test was not conducted using 

“whole” organisms; for example, the test 

was conducted using tissues or cell 

cultures. 

___ * The test result was calculated for a 

mixture of species, especially if the 

species were in different genera. 

___ * At least some of the test organisms were 

in a life stage that is not aquatic for at 

least part of the test. 

___ * The test organisms were cladocerans that 

were obtained from a stock culture in 

which ephippia were being produced. 

___ The test organisms showed signs of stress 

or disease before the test. 

___ * The test was begun with organisms 

within 10 days after they were treated to 

cure or prevent disease and/or the 

organisms were treated during the test. 

___ * Test organisms were previously exposed 

to substantial concentrations of the test 

material or other contaminants and were 

not held in clean water for at least 10 

days before the beginning of the test. 

___ * The test organisms were not acclimated 
A-6 

to or were not maintained in the dilution 

water at the test temperature for at least 

48 hours before the beginning of the test. 

___ The test organisms were mishandled or 

excessively disturbed before or during 

the test. 

___ * The test organisms were fed during an 

acute toxicity test. 

Exceptions: 

1. Saltwater annelids and mysids could be fed 

during acute tests. 

2. The test material does not sorb or complex 

readily with food. 

3. Data were available to show that the presence 

of food probably would not affect the results 

of the test. 

___ There were fewer than 10 test organisms 

per treatment. 

___ There were not two or more replicates 

(groups of individuals of a species) tested 

for each concentration for chronic tests. 

___ The test organisms were crowded in the 

test chambers. 

___ * The test organisms reproduced during the 

test and all of the new organisms could 

not be distinguished from the initial 

organisms at the end of the test. (This 

has been a problem in some tests with 

rotifers.) 

Controls 

___ * There was no control treatment. 

___ * There was a control treatment, but it was 

not comparable to the other treatments. 

___ No data were reported for the controls. 

___ * More than 10 percent of the control 

organisms died or showed signs of stress 

or disease or were otherwise adversely 

affected, except that a higher percentage 

was acceptable for a few species. 

___ * Survival, growth, or reproduction in the 

control treatment for chronic tests were 

unacceptably low. (The limits of 

acceptability depended on the species.) 

Dilution water 

___ * Distilled or deionized water was used 

without addition of appropriate salts. 

___ * Chlorinated water was used without 

adequate dechlorination. 

___ * River water was used as the dilution 

water without appropriate treatment. 

___ * The concentration of total organic carbon 

(TOC) or particulate matter (PM) in the 

dilution water exceeded 5 mg/L. 

 

Exceptions: 

1. TOC or PM could exceed 5 mg/L if a 

relationship was developed between toxicity 

and TOC or PM. 

2. Data were available to show that TOC or PM 

probably would not affect the results of the 

test. 

___ The dilution water contained unusual 

amounts or ratios of inorganic ions. 

Test conditions 

___ Turbulence in the test chamber, resulting 

from aeration, stirring, or design (of 

flow-through chambers), was excessive. 

___ The temperature, pH, etc., of the test 

solutions were not adequately controlled. 

___ * The pH of the dilution water was below 

6.5 or above 9.0. 

___ * The concentration of dissolved oxygen in 

a renewal or flow-through test was less 

than 60 percent of saturation. 

___ * The concentration of dissolved oxygen 

during a static test was less than 60 

percent saturation during the first 48 

hours, or less than 40 percent of 

saturation from 48 to 96 hours. 

___ Treatments, test organisms, and 

experimental units were not appropriately 

randomized. 

___ * The dilution factor was greater than 9. 

The toxicity tests that were not rejected were next 

evaluated to determine whether they provided the 

kinds of acute and chronic results that were to be 

used, as described in the next two sections. 

A.2 Compilation of Acute Values

 The following kinds of results of acute 

toxicity tests were used: 

1. For midges, phantom midges, daphnids, and 

other cladocerans, the result used was the 48-

hr EC50 based on percentage of organisms 

immobilized plus percentage of organisms 

killed. If such an EC50 was not available from 

a test, the 48-hr LC50 was used in place of the 

desired 48-hr EC50. An EC50 or LC50 of longer 
 

A-7 

than 48 hours was used as long as the animals 

were not fed and the control animals were 

acceptable at the end of the test. Tests with 

daphnids and other cladocerans should have 

been started with organisms less than 24 hours 

old, and tests with midges and phantom 

midges should have been started with secondor third-instar larvae. 

2. For embryos and larvae of barnacles, bivalve 

molluscs (clams, mussels, oysters, and 

scallops), sea urchins, lobsters, crabs, shrimp, 

and abalones, the result used was the 96-hr 

EC50 based on the percentage of organisms 

with incompletely developed shells plus the 

percentage of organisms killed. If such an 

EC50 was not available from a test, the lower 

of the 96-hr EC50 based on percentage of 

organisms with incompletely developed shells 

and the 96-hr LC50 was used in place of the 

desired 96-hr EC50. If the duration of the test 

was between 48 and 96 hours, the EC50 or 

LC50 at the end of the test was used. 

3. For all other freshwater and saltwater animal 

species and older life stages of barnacles, 

bivalve molluscs, sea urchins, lobsters, crabs, 

shrimp, and abalones, the result used was the 

96-hr EC50 based on the percentage of 

organisms exhibiting loss of equilibrium plus 

the percentage of organisms immobilized plus 

the percentage of organisms killed. If such an 

EC50 was not available from a test, the 96-hr 

LC50 was used in place of the desired 96-hr 

EC50. 

 Acceptable freshwater acute test results were 

entered in taxonomic order. If the tests were 

conducted properly, acute values reported as 

“greater than” values and those that were above 

the solubility of the test material were entered 

because rejection of such acute values would 

unnecessarily lower the Final Acute Value (FAV) 

by eliminating acute values for resistant species. 

Reported results were not rounded off to fewer 

than four significant digits. 

 In the case of a species for which at least one 

acceptable acute value was available, the species 

mean acute value (SMAV) was calculated as the 

geometric mean of the results of all flow-through 

tests in which the concentrations of test material 

were measured. In the case of a species for 

which no such result was available, the SMAV 

was calculated as the geometric mean of all 

available acute values (i.e., results of flowthrough tests in which the concentrations were 

not measured and results of static and renewal 

tests based on initial concentrations of test 

material). (Nominal concentrations were 

acceptable for most test materials if measured 

concentrations were not available.) If only one 

acceptable acute value was available for a 

species, the SMAV was that value. The 

following information was also considered: 

1. If the available data indicated that one or 

more life stages were more resistant than one 

or more other life stages of the same species 

by at least a factor of 2, the data for the more 

resistant life stages were not used in the 

calculation of the SMAV. This procedure 

was followed because a species can be 

considered protected from acute toxicity only 

if all life stages are protected. 

2. The agreement of the data within and 

between species was considered. Acute 

values that appeared to be questionable in 

comparison with other acute and chronic data 

for the same species and for other species in 

the same genus usually were not used in the 

calculation of a SMAV. For example, if the 

acute values available for a species or genus 

differed by more than a factor of 10, some or 

all of the values usually were not used in 

calculations. 

SMAVs were not rounded off to fewer than four 

significant digits. 

 The geometric mean of N numbers was 

calculated as the Nth root of the product of the N 

numbers. Alternatively, the geometric mean was 

calculated by adding the logarithms of the N 

numbers, dividing the sum by N, and taking the 

antilog of the quotient. Either natural (base e) or 

common (base 10) logarithms were used to 

calculate geometric means as long as they were 

used consistently within each set of data (i.e., the 

antilog used matched the logarithm used). The 

geometric mean of two numbers was usually 

calculated as the square root of the product of the 

two numbers. The geometric mean of one 

number was that number. 
A-8 

A.3 Compilation of Chronic Values 

 Results of three kinds of chronic toxicity tests 

were used: 

1. Life-cycle toxicity tests. These tests consist of 

exposures of each of two or more groups of 

individuals of a species to a different 

concentration of the test material throughout a 

life cycle. To ensure that all life stages and life 

processes are exposed, tests with fish begin 

with embryos or newly hatched young less than 

48 hours old, continue through maturation and 

reproduction, and end not less than 24 days (90 

days for salmonids) after the hatching of the 

next generation. Tests with daphnids begin 

with young less than 24 hours old and continue 

until 7 days past the median time of first brood 

release in the controls. 

 For fish, data are obtained and analyzed on 

survival and growth of adults and young, 

maturation of males and females, eggs spawned 

per female, embryo viability (salmonids only), 

and hatchability. For daphnids, data are obtained 

and analyzed on survival and young per female. 

For mysids, data are obtained and analyzed on 

survival, growth, and young per female. 

2. Partial life-cycle toxicity tests. These tests 

consist of exposures of each of two or more 

groups of individuals of a species of fish to 

different concentrations of the test material 

through most portions of a life cycle. Partial 

life-cycle tests are allowed with fish species 

that require more than a year to reach sexual 

maturity, so that all major life stages are 

exposed to the test material in less than 15 

months (i.e., the tests begin with immature 

juveniles at least 2 months prior to active gonad 

development and end not less than 24 days (90 

days for salmonids) after hatching of the next 

generation). 

Data are obtained and analyzed on survival and 

growth of adults and young, maturation of males 

and females, eggs spawned per female, embryo 

viability (salmonids only), and hatchability. 

3. Early life-stage toxicity tests. These tests 

consist of 28- to 32-day (60-days post hatch for 

salmonids) exposures of the early life stages of 

a species of fish from shortly after fertilization 

through embryonic, larval, and early juvenile 

development. Results of early life-stage tests in 

which the incidence of mortalities or 

abnormalities increased substantially near the 

end of the test are not used because the results 

of such tests are probably not good predictions 

of the results of comparable life-cycle or partial 

life-cycle tests. 

 Data are obtained and analyzed on survival 

and growth. Results of early life-stage tests were 

used as predictions of results of life-cycle and 

partial life-cycle tests with the same species. 

Therefore, when results of a life-cycle or partial 

life-cycle test were available, results of an early 

life-stage test with the same species were not 

used. 

 Acceptable freshwater and saltwater chronic 

test results were sorted by taxonomic order. 

Reported results were not rounded off to fewer 

than four significant digits. 

 A chronic value was obtained either by 

calculating the geometric mean of the lower and 

upper chronic limits from a chronic test or by 

analyzing chronic data using regression analysis. 

 A lower chronic limit was the highest tested 

concentration (a) in an acceptable chronic test, 

(b) that did not cause an unacceptable amount of 

adverse effect on any of the specified biological 

measurements, and (c) below which no tested 

concentration caused an unacceptable effect. An 

upper chronic limit was the lowest tested 

concentration (a) in an acceptable chronic test, 

(b) that did cause an unacceptable amount of 

adverse effect on one or more of the specified 

biological measurements, and (c) above which all 

tested concentrations also caused such an effect. 

 Because various authors have used a variety 

of terms and definitions to interpret and report 

results of chronic tests, reported results were 

reviewed carefully. The amount of effect that 

was considered unacceptable was based on a 

statistical hypothesis test and/or the percent 

reduction from the controls. For example, a small 

percent reduction (e.g., 3 percent) was considered 

acceptable even if it was statistically significantly 

different from the control, whereas a large 

percent reduction (e.g., 30 percent) was 

considered unacceptable even if it was not 

statistically significant. 
 

A-9 

A.4 Compilation of Acute-Chronic Ratios 

1. For each chronic value for which at least one 

corresponding appropriate acute value was 

available, an ACR was calculated, using for 

the numerator the geometric mean of the 

results of all acceptable flow-through acute 

tests in the same dilution water and in which 

the concentrations were measured. Static and 

renewal tests were acceptable for daphnids. 

Acute tests with fish should have been started 

with juveniles, whereas acute tests with 

daphnids should have been started with 

organisms less than 24 hr old. 

2. Acute test(s) that were part of the same study 

as the chronic test were used if available. If 

acute tests were not conducted as part of the 

same study, acute tests conducted in the same 

laboratory and dilution water, but in a 

different study, were used. If no such acute 

tests were available, results of acute tests 

conducted in the same dilution water in a 

different laboratory were used. If no such 

acute tests were available, an ACR was not 

calculated. 

3. For fish, if chronic test data for life-cycle or 

partial life-cycle tests were available for a 

species, they were used for the denominator 

instead of an early life-stage test for the same 

species. 

 For each species, the species mean acutechronic ratio (SMACR) was calculated as the 

geometric mean of all ACRs available for that 

species. 

A.5 Calculation Procedures 

 For each genus for which one or more 

SMAVs were available, the genus mean acute 

value (GMAV) was calculated as the geometric 

mean of the SMAVs available for the genus. The 

GMAVs were ranked from highest to lowest, 

with the lowest GMAV assigned rank 1. The 

associated SMAVs and freshwater SMACRs 

were also entered. 

1. The family Salmonidae in the Class 

Osteichthyes. 

2. A second family in the Class Osteichthyes, 

preferably a commercially or recreationally 

important warm-water species (e.g., bluegill, 

channel catfish). 

3. A third family in the phylum Chordata (may 

be in the class Osteichthyes or may be an 

amphibian, etc.). 

4. A planktonic crustacean (e.g., cladoceran, 

copepod). 

5. A benthic crustacean (e.g., ostracod, isopod, 

amphipod, crayfish). 

6. An insect (e.g., mayfly, dragonfly, damselfly, 

stonefly, caddisfly, mosquito, midge). 

7. A family in a phylum other than Arthropoda 

or Chordata (e.g., Rotifera, Annelida, 

Mollusca). 

8. A family in any order of insect or any 

phylum not already represented. 

 If all eight of the minimum data requirements 

(MDRs) were satisfied, the FAV was calculated 

using the computer program given on page 98 of 

Stephan et al. (1985), using the total number of 

GMAVs and the four lowest. The calculated FAV 

was compared with the low SMAVs to determine 

whether the FAV should be lowered to protect a 

commercially or recreationally important species. 

 If all eight of the acute freshwater MDRs 

were not met, a freshwater secondary acute value 

(SAV) was calculated. To derive a freshwater 

SAV, it was necessary to have at least one 

acceptable acute toxicity test with a species in 

one of three genera (Daphnia, Ceriodaphnia, or 

Simocephalus) in the Family Daphnidae. 

 The SAV was calculated using the lowest 

GMAV and the secondary acute factor (SAF) 

corresponding to the number of minimum data 

requirements that were satisfied: 

SAV = lowest Genus Mean Acute Value

 Secondary Acute Factor 

The SAFs from GLI (1995): 

 Acceptable freshwater and saltwater ACRs 

and the test results on which they were based 

were recorded. 

 To derive a freshwater FAV (Stephan et al., 

1985), it was necessary to have results of 

acceptable acute toxicity tests with at least one 

species of freshwater animal in eight different 

families, such that all of the following 

requirements were satisfied: 
A-10 

Number of MDRs Satisfied SAF 

 1 21.9 

 2 13.0 

 3 8.0 

 4 7.0 

 5 6.1 

 6 5.2 

 7 4.3 

 If sufficient data are available, chronic values 

can be calculated in the same manner as acute 

values, without the use of an ACR. Genus mean 

chronic values (GMCVs) were then calculated as 

the geometric mean of available chronic values. 

If the necessary data were available, the chronic 

value was calculated using the computer program 

used to calculate the FAV. (This option is rarely 

used because the chronic MDRs are rarely 

satisfied.) 

 If the data were not available to allow use of 

the computer program (e.g., Stephan et al. 1985), 

a final acute-chronic ratio (FACR) was calculated 

if acceptable ACRs were available for at least one 

species of aquatic animal in at least three 

different families, and of the three species: 

1. At least one was a fish. 

2. At least one was an invertebrate. 

3. At least one was an acutely sensitive 

freshwater species. (The other two could be 

saltwater species.) 

 If the MDRs for calculation of an FACR 

were satisfied, an FACR was calculated; 

otherwise an SACR was derived. 

 For some materials, the ACR seems to be the 

same for all species, but for other materials the 

ratio seems to increase or decrease as the SMAV 

increases. The FACR was obtained in one of 

four ways, depending on the data available: 

1. If the SMACR seemed to increase or 

decrease as the SMAVs increased, the FACR 

was calculated as the geometric mean of the 

ACRs for species whose SMAVs were close 

to the FAV or SAV. 

2. If no major trend was apparent and the ACRs 

for a number of species were within a factor 

of 10, the FACR was calculated as the 

geometric mean of the SMACRs that were 

within a factor of 10. 

3. For acute tests conducted on metals and 

possibly other substances with embryos and 

larvae of barnacles, bivalve molluscs, sea 

urchins, lobsters, crabs, shrimp, and abalones, 

the ACR was usually assumed to be 2. 

Chronic tests are very difficult to conduct 

with most such species, but it is likely that 

the sensitivities of embryos and larvae would 

determine the results of life-cycle tests. 

Thus, if the lowest available SMAVs were 

obtained with embryos and larvae of such 

species, the FACR was assumed to be 2. 

4. If the most appropriate SMACRs were less 

than 2.0, and especially if they were less than 

1.0, acclimation had probably occurred 

during the chronic test. Because continuous 

exposure and acclimation cannot be assured 

to provide adequate protection in field 

situations, the FACR was assumed to be 2. 

If the available SMACRs did not fit one of the 

above cases, an FACR could not be obtained and 

an SACR was derived if possible. 

 If the available ACRs did not satisfy the 

minimum data requirements for derivation of an 

FACR, sufficient ACRs of 18 were assumed so 

that the MDRs were satisfied. The SACR was 

then calculated as the geometric mean of the 

measured and assumed ACRs. If no 

experimentally determined ACRs were available, 

the SACR was 18 (GLI 1995). 
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