United States
Environmental Protection
Agency
Procedures for the
Derivation of Equilibrium
Partitioning Sediment
Benchmarks (ESBs) for the
Protection of Benthic
Organisms
Compendium of Tier 2
Values for Nonionic Organics
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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
Recycled/Recyclable
Printed with vegetable-based ink on
paper that contains a minimum of
50% post-consumer fiber content
processed chlorine free
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Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
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.
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Abstract
The ESBTier2 is derived by multiplying the FCV or SCV by a chemical's K0c, 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.
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Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
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.
iv
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Contents
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 K0w 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 K0w 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
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Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
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-l
Tables
Table 3-1 Chronic toxicity values (|ig/L), SCVs and FCVs, used to derive Tier 2
ESBs based on conventional and narcotic approaches 3-3
Table 3-2 Tier 2 ESBs ((ig/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
ESBTier2DRYWT values (ug/g dry weight) for four chemicals under
different foe and fsoiids conditions 3-10
Table 3-4 Example Tier 2 ESBs (ug/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 K0w
(Equations 3-5 and 3-6) 3-9
VI
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Acknowledgements
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
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Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
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 (K0c), 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 (ig chemical/g organic carbon basis ((ig/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 (ig/goc basis can be accurately predicted by
multiplying the effect concentration in water by the chemical's K0c.
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 freshwater-
and 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 K0c, 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
Vlll
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Executive Summary
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 water-
only 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 water-
only 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 sediment-
specific 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 partitioning-
related 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.
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Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
Glossary of Abbreviations
ACR
AQUIRE
ASTER
ASTM
CL*
CAS
CWA
DOC
ECOTOX
EMAP
EPA
EqP
ESB
RY WT
ESBoc
ESBxier2
ESB Tier2DRYWT
ESBxier2OC
Acute-chronic ratio
Aquatic Toxicity Information Retrieval
Assessment Tools for the Evaluation of Risk
American Society for Testing and Materials
Critical lipid concentration
Chemical Abstracts Service
Clean Water Act
Dissolved organic carbon
Chemical concentration estimated to cause adverse effects to 50% of the test
organisms within a specified time period
ECOTOXicology databases
Environmental Monitoring and Assessment Program
United States Environmental Protection Agency
Equilibrium partitioning
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
Equilibrium partitioning Sediment Benchmark; for nonionic organics,
expressed on a sediment dry weight basis
Equilibrium partitioning Sediment Benchmark; for nonionic organics,
expressed on an organic carbon basis
Equilibrium partitioning Sediment Benchmark; for nonionic organics, derived
using Tier 2 data; specifically, the values in this document
Equilibrium partitioning Sediment Benchmark; for nonionic organics, derived
using Tier 2 data, expressed on a sediment dry weight basis
Equilibrium partitioning Sediment Benchmark; for nonionic organics, derived
using Tier 2 data; expressed on organic carbon basis
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Glossary
ESBTU
FACR
FAV
FCV
foe
fsolids
GLI
GMAV
GMCV
goc
HECD
IC50
KBC
KOC
KOW
KP
MC
MDR
NHEERL
OECD
ORD
OST
OSWER
Equilibrium Partitioning Sediment Benchmark Toxic Units
Final acute-chronic ratio
Final acute value
Final chronic value
Fraction of organic carbon in sediment
Fraction of solids in sediment
Great Lakes Water Quality Initiative
Genus mean acute value
Genus mean chronic value
Gram organic carbon
U.S. EPA, Health and Ecological Criteria Division
Chemical concentration estimated to cause some form of inhibition to 50%
of the test organisms within a specified time period
Black carbon-water partition coefficient
Organic carbon-water partition coefficient
Octanol-water partition coefficient
Sediment-water partition coefficient
Chemical concentration estimated to be lethal to 50% of test organisms within
a specified time period
Moisture content
Minimum data requirement
U.S. EPA, National Health and Environmental Effects Research Laboratory
Organization for Economic Cooperation and Development
U.S. EPA, Office of Research and Development
U.S. EPA, Office of Science and Technology
U.S. EPA, Office of Solid Waste and Emergency Response
XI
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Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
PAH
PM
QSAR
SACK
SAP
SAV
scv
SCVN
SMACR
SMAV
SPARC
STORET
TIE
TOC
WQC
Polycyclic aromatic hydrocarbon
Particulate matter
Quantitative structure-activity relationship
Secondary acute-chronic ratio
Secondary acute factor
Secondary acute value
Secondary chronic value
Secondary chronic value based on narcosis theory
Species mean acute-chronic ratio
Species mean acute value
SPARC Performs Automated Reasoning in Chemistry
EPA's computerized database for STOrage and RETrieval of water-related data
Toxicity Identification Evaluation
Total organic carbon
Water Quality Criteria
xn
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Section 1
Introduction
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 sediment-
integument 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
1-1
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Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
carbon partition coefficient (K0c) 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 K0c and FCV or SCV are
protective of benthic organisms. ESB
concentrations presented in this document are
expressed as (ig chemical/g sediment organic
carbon ((ig/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
(200 la) 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
1-2
-------
Introduction
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 fornonionic
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
1-3
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Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
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).
1-4
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Introduction
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-by-
chemical 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 K0w > 2.
However, for chemicals with log K0w between 2
and 3, EqP will function but sedimentary
conditions (i.e., f0c and fSoiids) 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. EPA2003e).
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 (K0c) is derived from the octanol-
water partition coefficient (K0w) 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 K0c multiplied by the
effect concentration from a water-only toxicity
test predicts the effect concentration from
sediment tests (Swartz 1991, DeWittetal. 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 KQW 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 water-
only 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
1-5
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Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
(1996), U.S. EPA (1996), GLI (1995) and U.S.
EPA (200la) 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 mid-
1990s. 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.
1-6
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Derivation of Equilibrium Partitioning Sediment Benchmarks
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
KQW values, and then the derivation of the
appropriate aquatic toxicity values. The
derivation of the K0w 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 shake-
flask 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,
2-1
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Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
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:
1. Final Chronic Values from the Great Lakes
Water Quality Initiative (GLI 1995, U.S.
EPA 200la)
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, 200la). Marine ESBs for pesticides, in
this document, were based only on WQC-
derived 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, gamma-
BHC/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 whole-
effluent 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,
2-2
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Derivation of Equilibrium Partitioning Sediment Benchmarks
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,
200 la).
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.
2-3
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Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
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*Ac,- ACR] - 0.945 • log
(*ow) (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 (imol/g octanol, Ac/
is the chemical class specific correction, ACR is
the acute-chronic ratio equaling 5.09, -0.945 the
universal narcosis slope, and K0w is specific to
the chemical being investigated (Di Toro et al.
2000). This equation can be simplified to:
log (SCVN) = log (6.94)
-0.945 -log
(2-2)
For the narcotic chemicals in this document,
the chemical class specific correction value (Ac/)
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., Act) 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
2-4
-------
Derivation of Equilibrium Partitioning Sediment Benchmarks
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 acute-
chronic 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 SAP
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 K0w of each chemical
to predict an LC50 for that species and chemical.
These predicted LCSOs 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 conventionally-
derived 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
2-5
-------
Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
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 (ig/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 (ig/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).
2-6
-------
Derivation of Equilibrium Partitioning Sediment Benchmarks
Benzene
Biphenyl
Chlorobenzene
Dibenzofuran
1,2-Dichlorobenzene
1,3-Dichlorobenzene
1,4-Dichlorobenzene
^ Ethylbenzene
O Hexachloroethane
Q.
g Pentachlorobenzene
Q 1,1,2,2-Tetrachloroethane
Tetrachloroethene
Tetrachloromethane
Toluene
Tribromo methane
1, 2, 4-Trichloro benzene
1,1,1-Trichloroethane
Trichloroethene
m-Xylene
Narcosis-based SCV/Conventionally-derived SCV
10 100 1000
^^^—
I
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.
2-7
-------
Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
1000000
100000 -
O)
3
o
LO
O
_i
T3
CD
>
CD
co
.a
O
10000 -
1000 -
100
100
1000 10000 100000
Predicted LC50 (ug/L)
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.
2-8
-------
Derivation of Equilibrium Partitioning Sediment Benchmarks
1000000
100000 -
en
o
LO
O
CD
>
CD
CO
.a
O
10000 -
1000 -
100
• Benzene
O Biphenyl
T Dibenzofuran
A Ethylbenzene
• Toluene
D m-xylene
100
1000 10000 100000
Predicted LC50 (ug/L)
1000000
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.
2-9
-------
Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
1000000
100000 -
en
^
o
LO
O
_i
T3
CD
£
CD
co
.0
O
10000 -
1000 -
100
• Chlorobenzene
O 1,2-Dichlorobenzene
V 1,3-Dichlorobenzene
A 1,4-Dichlorobenzene
• Pentachlorobenzene
D 1,2,4Trichlorobenzene
X
X
X
X
X
100
1000 10000 100000
Predicted LC50 (ug/L)
1000000
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.
2-10
-------
Derivation of Equilibrium Partitioning Sediment Benchmarks
1000000
100000 -
en
^
o
LO
O
_i
T3
CD
£
CD
co
.0
O
10000 -
1000 -
100
• 4-Bromophenyl phenyl ether
O Hexachloroethane
V 1,1,2,2Tetrachloroethane
A Tetrachloroethene
• Tetrochloromethane
D Tribromomethane
^ 1,1,1-Trichloroethane
O Trichloroethene
100
1000 10000 100000
Predicted LC50 (ug/L)
1000000
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.
2-11
-------
-------
Calculation of Equilibrium Partitioning Sediment Benchmarks
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 (ig 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 (^g chemical/L interstitial
water) and not with the sediment chemical
concentration (fig 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 K0wS > 2. However, for
chemicals with log Kow between 2 and 3, EqP
will function but sedimentary conditions (i.e.,
foc and fSoiids) 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.
3-1
-------
Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
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 (ng/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:
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 K0c and the weight fraction of
organic carbon (foc) in the sediment. The
relationship is as follows:
Kp — f
oe
It follows that:
ESB
Tier2OC
= KOC ' SCV
(3-2)
(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 K0c 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 K0w values for
nonionic organic chemicals based on the best
available measured, calculated, and estimated
data. The recommended logi0Kow values from
Karickhoff and Long (1995) were used to derive
many of the K0c 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.
3-2
-------
Calculation of Equilibrium Partitioning Sediment Benchmarks
Table 3-1. Chronic toxicity values (jig/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.
CAS
Number
71432
319868
58899
92524
101553
85687
108907
333415
132649
95501
541731
106467
84742
84662
115297
959988
332136
59
100414
67721
121755
Chemical
Benzene
BHC other than Lindane
Gamma-BHC, Lindane
Biphenyl
4-Bromophenyl phenyl
ether
Butyl benzyl phthalate
Chlorobenzene
Diazinon
Dibenzofuran
1 ,2-Dichlorobenzene
1 , 3 -Dichlorobenzene
1 ,4-Dichlorobenzene
Di-n-butyl phthalate
Diethyl phthalate
Endosulfan mixed isomers
Alpha-Endosulfan
Beta-Endosulfan
Ethylbenzene
Hexachloroethane
Malathion
log Kow
2.13
3.78
3.73
3.96
5.00
4.84
2.86
3.70
4.07
3.43
3.43
3.42
4.61
2.50
4.10
3.83
4.52
3.14
4.00
2.89
Conventional*
FCV or SCV (|ig/L)
Freshwater
SCV= 130
SCV = 2.2
FCV = 0.080
SCV = 14
SCV =1.5
SCV = 19
SCV = 64
FCV = 0.1699
SCV = 3. 7
SCV = 14
SCV = 71
SCV =15
SCV = 35
SCV = 270**
FCV = 0.056
FCV = 0.056
FCV = 0.056
SCV = 7.3
SCV = 12
SCV = 0.097
Marine
SCV =130
-
-
SCV = 14
SCV =1.5
-
SCV = 64
FCV = 0.8185
SCV = 3. 7
SCV = 14
SCV = 71
SCV =15
-
-
FCV = 0.0087
FCV = 0.0087
FCV = 0.0087
SCV = 7.3
SCV = 12
FCV = 0.1603
Narcosis* SCV
(Hg/L)
5300
310
340
190
19
58
880
670
170
330
330
340
85
6700
210
390
86
790
160
4300
3-3
-------
Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
CAS
Number
72435
608935
79345
127184
56235
108883
800135
2
75252
120821
71556
79016
108383
Chemical
Methoxychlor
Pentachlorobenzene
1 , 1 ,2,2-Tetrachloroethane
Tetrachloroethene
Tetrachloromethane
Toluene
Toxaphene
Tribromomethane
(Bromoform)
1, 2, 4-Trichlorobenzene
1,1, 1-Trichloroethane
Trichloroethene
m-Xylene
log Kow
5.08
5.26
2.39
2.67
2.73
2.75
5.50
2.35
4.01
2.48
2.71
3.20
Conventional*
FCV or SCV (ng/L)
Freshwater
SCV = 0.019
SCV = 0.47
SCV = 610
SCV = 98
SCV = 240
SCV = 9.8
FCV = 0.039
SCV = 320
SCV =110
SCV =11
SCV = 47
SCV = 67***
Marine
-
SCV = 0.47
SCV = 610
SCV = 98
SCV = 240
SCV = 9.8
FCV = 0.2098
SCV = 320
SCV =110
SCV = 1 1
SCV = 47
SCV = 67***
Narcosis* SCV
(Hg/L)
22
11
3700
2000
1600
1600
10
6000
120
2400
1400
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
(ig/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 (jlg/goc) based on toxicity values derived using conventional and narcosis
approaches (from Table 3-1). K0c based on Equation 3-4. Values presented with two significant
figures.
CAS
Number
71432
319868
Chemical
Benzene
BHC other than Lindane
Log KOC
2.09
3.72
Conventional*
ESB (ng/goc)
Freshwater
16
11
Marine
16
-
Narcosis* ESB
((ig/goc)
660
A
3-4
-------
Calculation of Equilibrium Partitioning Sediment Benchmarks
CAS
Number
58899
92524
101553
85687
108907
333415
132649
95501
541731
106467
84742
84662
115297
959988
3321365
9
100414
67721
121755
72435
608935
79345
127184
56235
108883
Chemical
Gamma-BHC, Lindane
Biphenyl
4-Bromophenyl phenyl
ether
Butyl benzyl phthalate
Chlorobenzene
Diazinon
Dibenzofuran
1 ,2-Dichlorobenzene
1 ,3 -Dichlorobenzene
1 ,4-Dichlorobenzene
Di-n-butyl phthalate
Diethyl phthalate
Endosulfan mixed isomers
Alpha-Endosulfan
Beta-Endosulfan
Ethylbenzene
Hexachloroethane
Malathion
Methoxychlor
Pentachlorobenzene
1 , 1 ,2,2-Tetrachloroethane
Tetrachloroethene
Tetrachloromethane
Toluene
Log KOC
3.67
3.89
4.92
4.76
2.81
3.64
4.00
3.37
3.37
3.36
4.53
2.46
4.03
3.77
4.44
3.09
3.93
2.84
4.99
5.17
2.35
2.62
2.68
2.70
Conventional*
ESB (ng/goc)
Freshwater
0.37
110
120
1100
41
0.74
37
33
170
34
1200
77
0.60
0.33
1.6
8.9
100
0.067
1.9
70
140
41
120
5.0
Marine
-
110
120
-
41
3.6
37
33
170
34
-
-
0.093
0.051
0.24
8.9
100
0.11
-
70
140
41
120
5.0
Narcosis* ESB
(Hg/goc)
A
1500
1600
A
570
A
1700
780
780
780
A
A
A
A
A
970
1400
A
A
1600
830
840
770
810
3-5
-------
Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
CAS
Number
8001352
75252
120821
71556
79016
108383
Chemical
Toxaphene
Tribromomethane
(Bromoform)
1, 2, 4-Trichlorobenzene
1,1, 1-Trichloroethane
Trichloroethene
m-Xylene
Log KOC
5.41
2.31
3.94
2.44
2.66
3.15
Conventional*
ESB (ng/goc)
Freshwater
10
65
960
3.0
22
94
Marine
54
65
960
3.0
22
94
Narcosis* ESB
(Hg/goc)
A
1200
1100
660
650
980
* = See Section 2.3 for definition.
- = Not Available.
A = Not Calculated.
3-6
-------
Calculation of Equilibrium Partitioning Sediment Benchmarks
3.3 Effects of Low KOW on Derivation of
ESBxierl
As noted above, the EqP approach used
here to derive ESBs functions most effectively
for nonionic organic chemicals with log K0wS >
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 K0w 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):
ESBTler2DRY WT = SCV [(foe KOC) + ((1 - fsolids) -
fsoiid,)] (3-5)
In which, ESBTier2DRY WT is in units of (ig
chemical/g dry weight sediment and fsdids is the
fraction of sediment present as solids. In the
U.S. EPA Environmental Monitoring and
Assessment Program (EMAP) data set discussed
below, fsoiids 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 - fSoiids) - fsoiids), 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 K0c chemicals, the
proportion may have a substantial effect on the
magnitude of ESBTier2DRYwT. The ESBTier2DRY WT
is converted to ESBTier20c by the following:
It should be noted that in aquatic
environments, fSoiids and f0c are often inversely
correlated. For example, in depositional areas,
where contaminants discussed in this document
frequently accumulate, fs0udsis often low and f0c
elevated because of the abundance of carbon-
rich small particles with large surface area to
volume ratios. Conversely, sediments in
dynamic areas tend to have low f0c and
elevated fSoiids 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 K0w 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 f0c and low
fsoiids conditions, starting at a log K0w of
approximately 4. Conversely, at high fsoiids and
high foc conditions, there is little difference
between the calculated values (Figure 3-la).
When high foc is combined with low fSoiids as
well as low f0c combined high fsoiids, departure
between the two approaches for calculating
ESBs are observed but at log K0wS of about 2.50
(Figure 3-lb).
Table 3-3 provides examples of the specific
effects of fSoiid on the derivation of ESBs for four
chemicals with a range of K0wS. For this
exercise, fsoiids 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 %), fSoiids was
calculated as:
soiids = (100-MC)-100
(3-7)
ESBxier2OC ~~ ESBji
ier2DRY WT
OC
(3-6)
and regressed against the sand content (%) to
derive the relationship:
fsoiids = 0.264 + 0.00487 • Sand Content (3-8)
For this example, f0c values were set to the
environmentally relevant range of 0.002 to 0.05.
Examining the extremes, in a sandy sediment
3-7
-------
Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
(80% sand), the ESB for low K0w 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 K0w 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 K0wS between
benzene and toxaphene, follow similar trends.
Of the 32 chemicals discussed in this
document, only four have log K0wS less than 2.5
while 22 have log K0ws that are equal to or less
than log 4. In situations where low f0c and low
fsoiids 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 fsoiids are low
and foe is high, conditions where departure
between the standard and modified ESBs takes
place at log K0w 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 fSoilds to be
elevated, f0c to be low, and for low K0w
chemicals to be present. Under such conditions,
the use of Equation 3-5 maybe warranted.
Finally, the value fsoiids is not often reported
in sediment investigations. In sediments
suspected of contamination by low K0w
chemicals, it may be important to record this
sediment characteris-tic (see Equation 3-8 for
predicting fSoilds based on sediment sand
content). The fgohds 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 %)).
3-8
-------
Calculation of Equilibrium Partitioning Sediment Benchmarks
(a)
8
•5?
ro
m
W
LU
ro
o
6
5.5 -
5 -
4.5 -
4 -
3.5 -
3 -
2.5 -
2 -
1.5
1.5
Modified ESB for fsoiids = 0.2 and f0c = 0.002
Modified ESB for fsoiids = 0.8 and foc = 0.1
Standard ESB
2.5
3.5
Log KOW
4.5
5.5
(b)
!
6
5.5 -
5
4.5 -
4 -
3.5 -
3 -
2.5 -
2
1.5
Modified ESB for fsoiids = 0.8 and f0c = 0.002
Modified ESB for fsoiids = 0.2 and foc = 0.1
Standard ESB
1.5
2.5
3.5
Log
4.5
5.5
Figure 3-1 Comparison of ESBs calculated using the standard equation
(Equation 3-3) and modified equations which include the effects of low K0w
(Equations 3-5 and 3-6): (a) effects of low fSoiids and f0c and high fSolids
and f0c and (b) effects of high fSoiids and low f0c and low fSoiids and high f0c-
In all cases, the FCV is 1000 ug/L.
5-9
-------
Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
Table 3-3 Example calculations of conventional freshwater standard and modified ESBTier2DRY WT values
(jig/g dry weight) for four chemicals under different f0c and fSoiids conditions. See text for
discussion of the calculation of fSoiidS. ESB values presented with two significant figures.
Chemical
Benzene
Malathion
1,2,4-
Trichlorobenzene
Toxaphene
FCVor
SCV
(Hg/L)
130
0.097
110
0.039
Log
KQ^/'.KQC
2.13:2.09
2.89:2.84
4.01:3.94
5.50:5.41
Standard ESBTier2DRYWT : Modified ESBTier2DRYWT*
((ig/g dry weight)
Sediment Characteristics
Sand = 80%
Silt-Clay = 20%
foe = 0.002
fsoiids = 0.65
0.032:0.10
0.00013:0.00019
1.9:2.0
0.02:0.02
Sand = 50%
Silt-Clay = 50%
foc = 0.025
fsoiids = 0.51
0.40:0.52
0.0017:0.0018
24:24
0.25:0.25
Sand = 20%
Silt-Clay = 80%
foe = 0.05
fsoiids = 0.36
0.80:1.0
0.0034:0.0035
48:48
0.50:0.50
* = See Equation 3-5.
3-10
-------
Calculation of Equilibrium Partitioning Sediment Benchmarks
3.4 Conversion to Dry Weight
Concentration
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 (ig 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:
|lg Chemical/goc = M-g Chemical/gDRY WT +
(% TOO 100) (3-9)
or
Chemical/goc = |ig Chemical/gDRY WT
100 - % TOC
For example, sediment with a chemical
concentration of 0.1 |ig/gDRYwT and 0.5% TOC
has an organic carbon-normalized concentration
of 20 M.g/goc (0.1 ^g/gDRYwi ' 100 - 0.5 = 20
|lg/goc). Another sediment with the same dry
weight concentration (0.1 |ig/gDRY WT) but a TOC
concentration of 5.0% would have an organic
carbon-normalized concentration of 2.0 |lg/goc
(0.1 ^ig/gDRYWT ' 100 - 5.0 = 2.0 Mg/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 weight-
normalized ESB values (ESBTier2DRY WT). This
'conversion' must be performed for each level of
TOC of interest:
ESB
Tiei2DRY WT
= ESBTier20C(^g/goc)-(%TOC
-100) (3-11)
(3-10)
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.
3-11
-------
Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
Table 3-4. Example Tier 2 ESBs (ug/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
Benzene
BHC other than Lindane
Gamma-BHC, Lindane
Biphenyl
4-Bromophenyl phenyl
ether
Butyl benzyl phthalate
Chlorobenzene
Diazinon
Dibenzofuran
1 ,2-Dichlorobenzene
1 , 3 -Dichlorobenzene
1 ,4-Dichlorobenzene
Di-n-butyl phthalate
Approach
C
N
C
C
C
N
C
N
C
C
N
C
C
N
C
N
C
N
C
N
C
Dry Weight
Sediment
Concentration
((ig/gDRYwi) at
0.2% TOC
0.032
1.3
0.022
0.00074
0.22
3.0
0.24
3.2
2.2
0.082
1.1
0.0015
0.074
3.4
0.066
1.6
0.34
1.6
0.068
1.6
2.4
Dry Weight
Sediment
Concentration
((ig/gDRYwi) at
1.0% TOC
0.16
6.6
0.11
0.0037
1.1
15
1.2
16
11
0.41
5.7
0.0074
0.37
17
0.33
7.8
1.7
7.8
0.34
7.8
12
Dry Weight
Sediment
Concentration
((ig/gDRYwi) at
5.0% TOC
0.80
33
0.55
0.019
5.5
75
6.0
80
55
2.1
29
0.037
1.9
85
1.7
39
8.5
39
1.7
39
60
3-12
-------
Calculation of Equilibrium Partitioning Sediment Benchmarks
Chemical Name
Diethyl phthalate
Endosulfan mixed
isomers
Alpha-Endosulfan
Beta-Endosulfan
Ethylbenzene
Hexachloroethane
Malathion
Methoxychlor
Pentachlorobenzene
1 , 1 ,2,2-Tetrachloroethane
Tetrachloroethene
Tetrachloromethane
Toluene
Toxaphene
Tribromomethane
(Bromoform)
1, 2, 4-Trichlorobenzene
Approach
C
C
C
C
C
N
C
N
C
C
C
N
C
N
C
N
C
N
C
N
C
C
N
C
Dry Weight
Sediment
Concentration
((ig/gDRYwi) at
0.2% TOC
0.15
0.0012
0.00066
0.0032
0.018
1.9
0.20
2.8
0.00013
0.0038
0.14
3.2
0.28
1.7
0.082
1.7
0.24
1.5
0.01
1.6
0.02
0.13
2.4
1.9
Dry Weight
Sediment
Concentration
((ig/gDRYwi) at
1.0% TOC
0.77
0.006
0.0033
0.016
0.089
9.7
1.0
14
0.00067
0.019
0.70
16
1.4
8.3
0.41
8.4
1.2
7.7
0.05
8.1
0.10
0.65
12
9.6
Dry Weight
Sediment
Concentration
((ig/gDRYwi) at
5.0% TOC
3.85
0.030
0.017
0.08
0.45
49
5.0
70
0.0034
0.095
3.5
80
7.0
42
2.1
42
6.0
39
0.25
41
0.50
3.3
60
48
3-13
-------
Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
Chemical Name
1,1, 1-Trichloroethane
Trichloroethene
m-Xylene
Approach
N
C
N
C
N
C
N
Dry Weight
Sediment
Concentration
0.2% TOC
2.2
0.006
1.3
0.044
1.3
0.19
2.0
Dry Weight
Sediment
Concentration
1.0% TOC
11
0.03
6.6
0.22
6.5
0.94
9.8
Dry Weight
Sediment
Concentration
5.0% TOC
55
0.15
33
1.1
33
4.7
49
3-14
-------
Sediment Benchmark Values
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
KQW 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 etal. 2005).
4.2 Considerations in the Application and
Interpretation of ESBs
4.2.1 Relationship ofESBji^ 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.
4-1
-------
Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
4.2.2 Use ofEqP 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 K0c values, thereby
making the ESBs under protective. If such a
situation is encountered, the applicability of
literature K0c 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 K0c 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 site-
specific ESB should be considered (see U.S.
EPA 200Ic, 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
200Ic), 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.
4-2
-------
Sediment Benchmark Values
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 co-
occur 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
4-3
-------
Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
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 ESBr^s 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
4-4
-------
Sediment Benchmark Values
in a short-term toxicity test. Second, a GLI-
based 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 exposure-
response 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:
(ig chemical/L = (|ig chemical/goc) '
(103goc/Kgoc-K0c) (4-1)
For chemicals with log K0w 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
4-5
-------
Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
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, site-
specific 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
4-6
-------
Sediment Benchmark Values
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 fsoiids 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 ESBTler2s. 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
4-7
-------
Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
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 lexicologically 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).
4-8
-------
Sediment Benchmark Values
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
fsoiids 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 fSoiids for
benzene, 1,1,2,2-tetrachloroethane and tetrachloroethene are shown rather than ESBTier2 values in
Table 3-1.
Sediment A
Benzene
Ethylbenzene
Toluene
m-Xylene
Chlorobenzene
1 ,2-Dichlorobenzene
Pentachlorobenzene
Tetrachloromethane
1,1,2,2-
Tetrachloroethane
Hexachloroethane
Trichloroethene
Tetrachloroethene
Diazinon
Alpha-Endosulfan
Malathion
Sum Narcosis
ESBTUs
Conventional
*ESB
((ig/goc)
28
8.9
5
94
41
33
70
120
190
100
22
50
3.6
0.051
0.11
Narcosis*
ESB
((ig/goc)
1100
970
810
980
570
780
1600
770
1200
1400
650
1000
A
A
A
Sediment
Concentration
((ig/goc)
0.95
0.23
0.32
0.42
0.67
1.2
2.3
1.5
1.3
0.89
0.51
0.53
0.02
0.01
0.01
Sediment
Concentration/
Conventional
ESB
0.0339
0.0258
0.0640
0.0045
0.0163
0.0364
0.0329
0.0125
0.0068
0.0089
0.0232
0.0106
0.0056
0.1961
0.0909
Sediment
Concentration/
Narcosis ESB
0.0009
0.0002
0.0004
0.0004
0.0012
0.0015
0.0014
0.0019
0.0011
0.0006
0.0008
0.0005
A
A
A
0.0111
Sediment B
Benzene
Ethylbenzene
Toluene
m-Xylene
Chlorobenzene
1,2-
Dichlorobenzene
Pentachlorobenzene
Conventional
*ESB
((ig/goc)
28
8.9
5
94
41
33
70
Narcosis*
ESB
((ig/goc)
1100
970
810
980
570
780
1600
Sediment
Concentration
((ig/goc)
0.95
0.23
0.32
0.42
0.67
1.2
2.3
Sediment
Concentration/
Conventional
ESB
0.0339
0.0258
0.0640
0.0045
0.0163
0.0364
0.0329
Sediment
Concentration/
Narcosis ESB
0.0009
0.0002
0.0004
0.0004
0.0012
0.0015
0.0014
4-9
-------
Equilibrium Partitioning Sediment Benchmarks (ESBs): Compendium
Tetrachloromethane
1,1,2,2-
Tetrachloroethane
Hexachloroethane
Trichloroethene
Tetrachloroethene
Diazinon
Alpha-Endosulfan
Malathion
Sum Narcosis
ESBTUs
120
190
100
22
50
3.6
0.051
0.11
770
1200
1400
650
1000
A
A
A
1.5
1.3
0.89
0.51
0.53
13.9
0.01
1.2
0.0125
0.0068
0.0089
0.0232
0.0106
3.8611
0.1961
10.9091
0.0019
0.0011
0.0006
0.0008
0.0005
A
A
A
0.0111
Sediment C
Benzene
Ethylbenzene
Toluene
m-Xylene
Chlorobenzene
1,2-
Dichlorobenzene
Pentachlorobenzene
Tetrachloromethane
1,1,2,2-
Tetrachloroethane
Hexachloroethane
Trichloroethene
Tetrachloroethene
Diazinon
Alpha-Endosulfan
Malathion
Sum Narcosis
ESBTUs
Conventional
*ESB
((ig/goc)
28
8.9
5
94
41
33
70
120
190
100
22
50
3.6
0.051
0.11
Narcosis*
ESB
((ig/goc)
1100
970
810
980
570
780
1600
770
1200
1400
650
1000
A
A
A
Sediment
Concentration
(Hg/goc)
120
45
38
31
1.3
3.7
8.8
1.1
0.66
0.43
0.19
0.21
0.02
0.01
0.01
Sediment
Concentration/
Conventional
ESB
4.2857
5.0562
7.6000
0.3298
0.0317
0.1121
0.1257
0.0092
0.0035
0.0043
0.0086
0.0042
0.0056
0.1961
0.0909
Sediment
Concentration/
Narcosis ESB
0.1091
0.0464
0.0469
0.0316
0.0023
0.0047
0.0055
0.0014
0.0006
0.0003
0.0003
0.0002
A
A
A
0.2493
Sediment D
Benzene
Ethylbenzene
Toluene
Conventional
*ESB
((ig/goc)
28
8.9
5
Narcosis*
ESB
((ig/goc)
1100
970
810
Sediment
Concentration
((ig/goc)
410
320
290
Sediment
Concentration/
Conventional
ESB
14.6429
35.9551
58.0000
Sediment
Concentration/
Narcosis ESB
0.3727
0.3299
0.3580
4-10
-------
Sediment Benchmark Values
m-Xylene
Chlorobenzene
1,2-
Dichlorobenzene
Pentachlorobenzene
Tetrachloromethane
1,1,2,2-
Tetrachloroethane
Hexachloroethane
Trichloroethene
Tetrachloroethene
Diazinon
Alpha-Endosulfan
Malathion
Sum Narcosis
ESBTUs
94
41
33
70
120
190
100
22
50
3.6
0.051
0.11
980
570
780
1600
770
1200
1400
650
1000
A
A
A
360
250
140
87
12
16
31
27
15
0.02
0.01
0.01
3.8298
6.0976
4.2424
1.2429
0.1000
0.0842
0.3100
1.2273
0.3000
0.0056
0.1961
0.0909
0.3673
0.4386
0.1795
0.0544
0.0156
0.0133
0.0221
0.0415
0.0150
A
A
A
2.2081
* = See Section 2.3 for definition.
A = Not Reported.
4-11
-------
-------
Section 5
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5-6
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Appendix A
Description of the Derivation of Conventional Freshwater Chronic Toxicity
Values using the Great Lakes Water Quality Initiative
(GLI1995) Approach
-------
A.I 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,
orF).
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-2
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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
etal. (1985):
Chironomus riparius
Gila elegans
Gillia attilis
Lestes congener
Sigara alternata
Stenonema
interpunctatum
Umbra pygmaea
midge
bonytail
buffalo pebblesnail
damselfly
water boatman
mayfly
eastern mudminnow
Examples of nonresident species not in Stephan
etal. (1985):
Anguilla anguilla
Anodonta anatina
Anodonta cyanea
Barbus ticto
Carassius carassius
Ghana punctatus
or gachua
Cirrhinus mrigala
Heteropneustes fossilis
Macrobrachiu
rosenbergii
Mystus vittatus
Notopterus notopterus
common eel
(assumed nonresident)
fresh-water mussel
swan mussel
two-spotted;
tic tac toe barb
Crucian carp
snake-head catfish
carp, hawkfish
Indian catfish
giant freshwater prawn
catfish
featherback
Paratelphusa
jacquemontii
Rasbora heteromorpha
Spicodiaptomus
chilospinus
crab (probably)
harlequinfish/red
rasbora
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-3
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l.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
etal.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-4
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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, reagent-
grade, 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-5
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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-6
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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 second-
er 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
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 flow-
through 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-7
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A.3 Compilation of Chronic Values
Results of three kinds of chronic toxicity tests
were used:
I.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 offish 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 offish 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-8
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A.4 Compilation of Acute-Chronic Ratios
Acceptable freshwater and saltwater ACRs
and the test results on which they were based
were recorded.
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 acute-
chronic 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.
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:
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 (SAP)
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):
A-9
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Number of MDRs Satisfied SAP
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).
A-10
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