METHODOLOGY FOR INTEGRATING AND EVALUATING
SEDIMENT CHEMISTRY AND BIOLOGICAL DATA HOUSED IN
THE NATIONAL SEDIMENT INVENTORY
AN ISSUE PAPER
June 21, 1995
Prepared for
United States Environmental Protection Agency
Office of Science and Technology
Standards and Applied Science Division
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METHODOLOGY FOR INTEGRATING AND EVALUATING
SEDIMENT CHEMISTRY AND BIOLOGICAL DATA HOUSED IN
THE NATIONAL SEDIMENT INVENTORY
AN ISSUE PAPER
June 21, 1995
Prepared for
United States Environmental Protection Agency
Office of Science and Technology
Standards and Applied Science Division
US EPA Region 4 Library
SNAFC 9T25
61 Forsyth Street SW
Atlanta, GA. 30303
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CONTENTS
Page
TABLES v
1. INTRODUCTION 1
Background 1
Purpose and Content of This Document 3
2. ASSESSMENT METHODS 5
Aquatic Life Assessments 5
Equilibrium Partioning Approaches 7
Sediment Quality Criteria 8
Sediment Quality Benchmarks 10
Acid Volatile Sulfide Concentration 10
Biological Effects Correlation Approaches 12
Effects Range-Medians and Effects Range-Lows 12
Probable Effects Levels and Threshold Effects Levels 13
Apparent Effects Thresholds 14
Sediment Toxicity Tests 15
Human Health and Wildlife Assessments 16
Theoretical Bioaccumulation Potential 16
FDA Action Levels 19
EPA Risk Levels 19
EPA Wildlife Criteria 21
Tissue Levels of Contaminants 22
3. ORIGINAL APPROACH RECOMMENDED BY NSI WORKSHOP 23
High Probability of Adverse Effects to Aquatic Life or Human Health 23
Medium-High Probability of Adverse Effects to Aquatic Life
or Human Health 25
Medium-Low Probability of Adverse Effects to Aquatic Life 26
Low Probability of Adverse Effects to Aquatic Life and Human Health 26
Unknown Probability of Adverse Effects 26
Modifications to Workshop Approach 26
4. FINAL PROPOSED APPROACH 29
Evaluation of Sediment Chemistry Data 29
Sediment Chemistry Values Exceed EPA Sediment Quality Criteria 29
Comparison of AVS to SEM Molar Concentrations 31
Sediment Chemistry Values Exceed Threshold Levels 32
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• -NaT. FQR-DlSIBJ&tfHeN
Page
Sediment Chemistry Values for Polychlorinated Biphenyls (PCBs)
Exceed 50 ppm 33
Sediment Chemistry TBPs Exceed Threshold Criteria 33
Evaluation of Tissue Residue Data 36
Tissue Levels Exceed FDA Action Levels, EPA Risk Levels, or
EPA Wildlife Criteria 36
Evaluation of Toxicity Data 36
Aggregation of Data 37
5. UNCERTAINTIES AND LIMITATIONS OF APPROACH 39
Derivation of Sediment Chemistry Threshold Levels 39
Derivation of Fish Tissue Threshold Levels 40
Quality of Data 40
Other Limitations 41
6. REFERENCES CITED 43
APPENDICES
A. Derivation of Sediment Quality Benchmarks Using the Equilibrium
Partitioning Approach A-l
B. Method for Selecting Biota-Sediment Accumulation Factors and Percent
Lipids in Fish Tissue Used for Deriving Theoretical Bioaccumulation
Potentials B-l
C. Threshold Values for Chemicals Subject to Evaluation C-l
D. Species Characteristics Related to NSI Bioaccumulation Data D-l
E. Test Species Used in Toxicity Tests Whose Results Are Presented
in the NSI E-l
F. List of Attendees - National Sediment Inventory Workshop,
April 26-27, 1994 F-l
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TABLES
Table Page
1. Original Approach Recommended by NSI Workshop (April 1994) 24
2. Final Proposed Evaluation Approach (June 1995) 30
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1. INTRODUCTION
In 1994 the U.S. Environmental Protection Agency (EPA) issued its Contaminated Sediment
Management Strategy, which committed the Agency to developing a national inventory of
contaminated sediment sites. Also, in 1992, Congress passed the Water Resources Development
Act (WRDA), which required EPA, in consultation with the National Oceanic and Atmospheric
Administration (NOAA) and the U.S. Army Corps of Engineers (COE), to conduct a
comprehensive national survey of data regarding aquatic sediment quality in the United States.
In an effort to help meet the objectives of EPA's Contaminated Sediment Management Strategy
and to comply with the mandates of the WRDA, EPA's Office of Science and Technology (OST)
initiated the development of the National Sediment Inventory (NSI). The NSI will provide EPA
with the ability to conduct a screening assessment of the extent and severity of sediment
contamination across the country. Such an assessment will include the identification of sites that
should be considered as targets for future, more intensive study either (1) to justify and
recommend regulatory actions for those sites which pose an obvious risk to the environment
and/or human health or (2) to gather additional information for those sites which appear to be
contaminated but for which there are insufficient data to reach a definitive conclusion. The NSI
will also provide valuable information to assist EPA in achieving other, long-term goals of its
Contaminated Sediment Management Strategy concerning pollution prevention, remediation, and
dredged material management.
OST will use the data currently compiled for the NSI to prepare the first Report to Congress on
the extent and severity of sediment contamination across the country. WRDA 1992 requires EPA
to report to Congress every 2 years on the condition of the Nation's sediments. New data to
supplement future reports will be added to the NSI over time. Eventually, all compiled data will
be incorporated into the new, modernized STORET, where it will be permanently stored. In the
meantime, EPA is in the process of developing an NSI data management strategy that will enable
access to the data in either dBASE or SAS data file format. The dBASE tables will facilitate use
with data base management software (e.g., dBASE, FOXPRO) or visualization tools (e.g.,
ArcView). As part of the overall NSI effort, OST is also conducting inventories of point and
nonpoint sources of sediment contaminants.
Background
OST initiated work several years ago on the development of the NSI through pilot inventories
in EPA Regions 4 and 5 and the Gulf of Mexico Program. Based on lessons learned from the
three pilot inventories, OST developed a document entitled Framework for the Development of
the National Sediment Inventory (USEPA, 1993a), which describes the general format for
compiling sediment-related data and an overall approach for evaluating the data. The format and
overall approach were then presented, modified slightly, and agreed upon at an Interagency
Workshop held in March 1993 in Washington, D.C.
Following the March 1993 workshop, EPA began compiling and evaluating data for the NSI.
Data from the following databases were included as a part of this effort:
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• Selected data sets from EPA's Storage and Retrieval System (STORET)
— COE
— U.S. Geological Survey (USGS)
— EPA
— States
• NOAA's Coastal Sediment Inventory (COSED)
• EPA's Ocean Data Evaluation System (ODES)
• EPA Region 4's Sediment Quality Inventory
• Gulf of Mexico Program's Contaminated Sediment Inventory
• EPA Region 10/COE Seattle District's Sediment Inventory
• EPA Region 9's Dredged Material Tracking System (DMATS)
• EPA's Great Lakes Sediment Inventory
• EPA's Environmental Monitoring and Assessment Program (EMAP)
• USGS (Massachusetts Bay) Data
• EPA's National Point Source Inventory
Data from each of these sources that have been collected since 1980 (i.e., 1980-1993) will be
evaluated for the first Report to Congress, although data older than 1980 are still maintained in
the NSI. The minimum data requirements for a data set to be included in the NSI are that the
data set be in computerized format and that they include the following:
• Locational information
• Sampling date
• Latitude/longitude
• Measurement units.
The types of data contained in the NSI include sediment chemistry, tissue residue, benthic
abundance, toxicity, histopathology, and fish abundance data. Not all of these data types (i.e.,
benthic abundance, histopathology, and fish abundance), however, will be evaluated for the first
Report to Congress (as described in Chapter 4).
In the spring of 1994, OST conducted a preliminary evaluation of NSI sediment chemistry data
only. The purpose of this assessment was to identify waterbodies throughout the United States
where measured values of sediment pollutants exceeded sediment chemistry levels of concern.
The results of this assessment were presented in The National Sediment Inventory: Preliminary
Evaluation of Sediment Chemistry Data (USEPA, 1994b). Both national and regional results of
the Preliminary Evaluation were then distributed to the EPA Regional offices for their review.
The Regional offices were asked to review the Preliminary Evaluation to:
• Verify sites targeted as areas of concern;
• Identify sites that were targeted as potential areas of concern but might not be;
• Identify potential areas of concern that were not targeted but should have been; and
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• Provide EPA Headquarters with additional sediment quality data that should be
included in the NSI to make it more accurate and complete.
The EPA Regional offices' review of the preliminary evaluation was completed during the winter
of 1994/1995. Regional comments on the preliminary evaluation results are currently being
incorporated into a comment field in the NSI database. New data sets identified by the Regions
will be included in the NSI and will be used in the national assessment for the second Report to
Congress. Some reviewers identified potential areas of concern that were not targeted in the
preliminary evaluation but should have been. In most cases, the reviewers provided references
to reports and/or data documenting the existence of additional locations of contaminated
sediment. For the purposes of the first Report to Congress, the additional locations will be
extracted from the comments and presented as "Other Identified Areas of Concern" either
narratively or graphically (the preferred option).
In April 1994, EPA Headquarters held the Second National Sediment Inventory Workshop
(USEPA, 1994e). The purpose of the workshop was to bring together experts in the field of
sediment quality assessment to recommend an approach for integrating and evaluating sediment
chemistry and biological data housed in the NSI. A list of workshop participants is presented
in the appendices. The purpose of the approach is to identify sites of known and suspected
sediment contamination based on data currently included in the NSI. The NSI is limited in terms
of (1) the number and types of data sets included and (2) the amount of information available
in those data sets concerning other characteristics of sites (i.e., other than sediment chemistry)
necessary to more accurately describe the potential for impacts to aquatic life and human health.
These other factors include the percent of sediment organic carbon; acid volatile sulfide content
of sediments; and fish tissue residue, toxicity, benthic abundance, and histopathology data.
During the workshop, three separate workgroups were charged with the task of recommending
approaches for evaluating the NSI data. The three workgroups were then brought together to
reach consensus on a single recommended approach. The final approach recommended by
workshop participants formed the basis for the proposed approach presented in this issue paper.
Purpose and Content of This Document
The purpose of this issue paper is to present and describe an approach for evaluating the NSI
data that builds on the approach recommended at the April 1994 workshop. Previous drafts of
this issue paper were reviewed by EPA Headquarters staff, sediment quality assessment experts
from the EPA laboratories, and other government experts. These reviewers include Dr. Rick
Swartz of the EPA Environmental Research Laboratory (ERL) in Newport, Oregon; Dr. Dave
Hansen of the EPA ERL in Narragansett, Rhode Island; and Drs. Nelson Thomas, Gary Ankley,
and Phil Cook of the EPA ERL in Duluth, Minnesota. The comments and recommendations of
these reviewers are reflected in the final proposed evaluation methodology.
It is particularly important to note that this methodology is designed for the purpose of a
screening-level assessment of sediment quality only. There is a considerable amount of
uncertainty associated with the site-specific measures, assessment techniques, exposure scenarios,
and default parameter selections. Therefore, the results of evaluating particular sites based on
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this methodology should be followed up by more intensive efforts when appropriate (e.g., when
sites have been targeted as having a high or medium probability of adverse effects).
The remainder of this document presents the proposed approach for evaluating NSI data for the
first Report to Congress. Chapter 2 of this document describes the assessment techniques that
will be used in the evaluation of NSI data. Chapter 3 presents an overview of the NSI evaluation
approach agreed on at the April 1994 workshop. Chapter 4 describes in detail how the NSI data
will be evaluated to place contaminated sediment sites into one of four categories using the final
proposed approach. Chapter 5 presents the uncertainties and limitations associated with the
evaluation approach. Threshold values, other parameter values proposed for comparison with and
evaluation of the NSI data, and other related information are presented in the appendices.
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2. ASSESSMENT METHODS
This chapter describes several assessment methods whose appropriateness for use in the NSI
evaluation requires additional explanation. The proposed application of these sediment chemistry,
tissue residue, and toxicity evaluation parameters is presented with the discussion of the
evaluation approach recommended by participants at the April 1994 National Sediment Inventory
Workshop (Chapter 3) and the discussion of the final proposed approach (Chapter 4).
Aquatic Life Assessments
To evaluate the potential threat to aquatic life from chemical contaminants detected in sediments,
measured concentrations of contaminants will be compared to sediment chemistry threshold
levels. The results of toxicity tests to indicate the actual toxicity of sediment samples to species
of aquatic organisms, when available, will also be evaluated for the NSI.
Sediment chemistry threshold levels are reference values above which sediment contaminant
concentrations could pose a significant threat to aquatic life. Several different approaches, based
on causal or correlative methodologies, have been developed for deriving threshold levels of
sediment contaminants. Each of these approaches attempts to predict adverse effect levels to
benthic species, which are extrapolated to represent the entire aquatic community for this
evaluation. For the purpose of this analysis, the threshold levels selected include the following:
• EPA's sediment quality criteria (SQCs) for five nonionic organic chemicals, developed
using an equilibrium partitioning approach (USEPA, 1992b, 1993i).
• Sediment quality benchmarks (SQBs) for selected nonionic organic chemicals,
developed using an equilibrium partitioning approach (USEPA, 1992b, 1993i).
• The sum of simultaneously extracted divalent transition metals concentrations minus
the acid volatile sulfide concentration (SEM-AVS), also based on an equilibrium
partitioning approach.
• Effects range-median (ERM) and effects range-low (ERL) values for selected nonionic
organics and metals developed by Long et al. (1995).
• Probable effects levels (PELs) and threshold effects levels (TELs) for selected
nonionic organics and metals developed by the Florida Department of Environmental
Protection (FDEP, 1994).
• Apparent effects thresholds (AETs) for selected nonionic organics and metals
developed by Barrick et al. (1988).
It is important to note that the certainty with which sediment toxicity can be predicted for each
chemical using the various threshold levels identified above can vary significantly based on the
quality of the available data and the appropriateness of exposure assumptions. For example,
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i^fmc?ggJSTsTRiBuYrg^'
sediment quality criteria and sediment quality benchmarks are not equivalent even though they
were developed using the same methodology. EPA has proposed sediment quality criteria for
five chemicals based on the highest quality toxicity and octanol/water partitioning data, which
have been reviewed extensively. However, as discussed in Appendix A, data used to derive
sediment quality benchmarks for additional chemicals came from limited sources and have
undergone only limited peer review. The sediment quality benchmarks are not sediment quality
criteria and should not be used as such. Data sets on which the ERLs, ERMs, TELs, PELs, and
AETs were developed were limited in geographic range to specific regions of the United States
and are limited in scope to specific and different biological effects, which might not be applicable
to all sediments in the United States.
Another concern is the application of threshold values based on freshwater data (SQCs, SQBs)
and those based on saltwater data alone (ERLs, ERMs, TELs, PELs, AETs) to evaluate sediment
contaminant concentrations in the NSI from both freshwater and saltwater habitats. Freshwater
organisms exhibit tolerance to toxic chemicals similar to that of saltwater species when tested in
their respective water; however, estuarine organisms might be less tolerant if osmotically stressed
(Rand and Petrocelli, 1985). Thus, the relative toxicity of a chemical in water (i.e., its chronic
threshold water concentration) is usually within an order of magnitude for saltwater and
freshwater species, although final chronic values and sediment quality criteria values are usually
slightly higher for saltwater species. Because of limitations of time and resources, sampled sites
in the NSI were not classified by salinity regime, and further site-specific evaluations will be
required to properly assess the toxicity at these various sites. However, the application of several
different threshold values should provide a reasonable estimate of potential risks to aquatic life
in freshwater, estuarine, and marine habitats.
An additional source of false positive and false negative classification of potential risks to aquatic
life from sediment contaminant concentrations is the application of a default value for organic
carbon content (foc) for all sediment samples that lack a corresponding measure of organic carbon
content (total organic carbon, or TOC). The derivation of SQCs and SQBs is based on the
partitioning of chemical between organic carbon in the sediment and pore water at equilibrium.
Because the organic carbon content of most sediment samples in the NSI is unknown, these
sediment samples were assumed to contain 1 percent organic carbon. TOC can range from less
than 1 percent in sandy sediments to 1 to 4 percent in silty harbor sediments and 10 to 20 percent
in navigation channel sediments (Clarke and McFarland, 1991). Long et al. (1995) reported an
overall mean TOC concentration of 1.2 percent from data compiled from 350 publications for
their biological effects database for sediments. Default SQC and SQB values for selected
chemicals were derived using foc = 0.01 to convert (ig/g^- to ^ig/g dry weight (ppm) sediment for
these evaluations, i.e., SQC or SQB = (SQCoc or SQBoc)(foc). Sediments having higher or lower
organic carbon content might be classified incorrectly.
Thus, because the methodologies and exposure conditions associated with the different threshold
levels vary considerably, these levels might be overprotective or underprotective for benthic
organisms at a particular site. However, EPA believes that the use of this suite of values is
appropriate for this nationwide screening-level assessment of sediment quality.
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The principles behind the development of each of these sediment chemistry threshold values and
uncertainties associated with the methodologies are discussed below. The sediment toxicity tests
are also briefly described in this section.
Equilibrium Partitioning Approaches
The potential toxicity of sediment-associated nonionic organic chemicals and divalent metals
depends on the amount of the contaminant that is uncomplexed or freely available in the
interstitial (pore) water. The bioavailability and toxicity of nonionic organic chemicals and
divalent metals in sediments are mediated by several physical, chemical, and biological factors,
including sediment grain size, particulate and dissolved organic carbon, and sulfide produced by
sulfate-reducing bacteria (Di Toro et al., 1991, 1992; Howard and Evans, 1993). For nonionic
organic chemicals, sorption to the organic carbon dissolved in the interstitial water and bound
to sediment particles is the most important factor affecting bioavailability. Sulfide, specifically
the reactive solid-phase sulfide fraction that can be extracted by cold hydrochloric acid (acid
volatile sulfide or AVS), appears to control the bioavailability of most divalent metal ions
because of the sulfide ions' high affinity for divalent metals, resulting in the formation of
insoluble metal sulfides.
When the concentrations of nonionic organic chemicals and divalent metals are measured in
interstitial water extracted from spiked sediment used in toxicity tests, biological effects in those
tests occurred at similar concentrations, even when using different types of sediments, typically
within a factor of 2 (Di Toro, 1991, 1992). Biological effects were also correlated when
concentrations of nonionic organics were expressed on an organic carbon basis or when the molar
concentration of simultaneously extracted metals (SEM) exceeded the acid volatile sulfide molar
concentration in the range of 1.5 to 12.5 |imol of SEM per ^mol of AVS. Most importantly, the
effects concentrations were the same as, or could be predicted from, the effects concentrations
determined in water-only exposures to these chemicals. However, most measurements of
sediment chemical concentrations are made from whole sediment samples and converted to units
of chemical per dry weight of sediment, because of the difficulties in extracting the interstitial
water. When dry weight concentrations of nonionic organics and metals were used in analyses,
biological effects occurred at different dry weight concentrations when measured in different
sediments (Luoma, 1983; USEPA, 1993i). To develop criteria or benchmarks for comparing the
toxicity of different chemicals in different sediments, it was necessary to examine the role of
organic carbon and other complexing factors in the bioavailability of chemicals.
In sediment, the partitioning of a nonionic organic chemical between organic carbon and pore
water and the partitioning of a divalent metal between the solid and solution phases are assumed
to be at equilibrium. The fugacity (activity) of the chemical in each of these phases is the same
at equilibrium. Fugacity describes mathematically the rates at which chemicals diffuse or are
transported between phases (Mackay, 1991). Hence, an organism in the sediment is assumed to
receive an equivalent exposure from water only or from any equilibrated phase. The pathway
of exposure might include pore water (respiration), sediment carbon (ingestion), sediment
organism (ingestion), or a mixture of routes. The biological effect is produced by the chemical
activity of the single phase or the equilibrated system (Di Toro et al., 1991). The equilibrium
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N/xr-Kftfr'refgTOBUTION
partitioning approach uses this partitioning theory to relate the dry weight sediment concentration
of a particular chemical that causes an adverse biological effect to the equivalent free chemical
concentration in pore water and to that sorbed to sediment organic carbon or bound to sulfide.
The theoretical causal resolution of chemical bioavailability in relation to chemical toxicity in
different sediments differentiates equilibrium partitioning approaches from purely empirical
correlative assessment methods (described later in this chapter).
The processes that govern the partitioning of chemical contaminants among sediments, pore
water, and biota are better understood for some kinds of chemicals than for others. Partitioning
of nonionic hydrophobic organic compounds between sediments and pore water is highly
correlated with the organic carbon content of sediments, but it does not account for all of the
toxicity variation observed between sediment and water-only experimental exposures. Other
factors can affect biological responses that are not considered in the model. The equilibrium
partitioning approach has been tested using only nonionic organic chemicals with log Kows
between 3.8 and 5.3; however, because the theory should be applicable to nonionic organic
chemicals with log K^s from 2.0 to 5.5 (Dave Hansen, EPA/ORD-Narragansett, pers. commun.,
April 17, 1995), nonionic organic chemicals with log Kows in this range will be evaluated for the
initial NSI. For trace metals, concentrations of sulfides and organic carbon have been identified
as important factors that control the phase associations and, therefore, the bioavailability of trace
metals in anoxic sediments. However, models that can use these factors to predict the
bioavailability of trace metals in sediments are not fully developed (see below). Mechanisms that
control the partitioning of nonionic and nonpolar organic compounds with log Kows of less than
2.0 or greater than 5.5 and polar organic compounds in sediments, and affect their toxicity to
benthic organisms, are less well understood. Models for predicting biological effects from
concentrations of such compounds have not yet been developed; therefore, these chemicals will
not be evaluated using equilibrium partitioning approaches.
Sediment Quality Criteria
The equilibrium partitioning model was selected for the development of sediment quality criteria
because it can be applied to predict biological effects based on the toxicity of individual nonionic
organic chemicals—and hence can protect benthic aquatic life in bedded, permanently inundated,
or intertidal sediments—while accounting for the range of different sediment characteristics that
affect the bioavailability of the chemical (Di Toro et al., 1991; USEPA, 1993i).
The partitioning of a chemical between the interstitial water and sediment organic carbon is
explained by the sediment/pore water partition coefficient for a chemical, Kp, which is equal to
the organic carbon content of the sediment (f^) multiplied by the particle organic carbon partition
coefficient (K^.). Normalizing the dry-weight concentration of the chemical in sediment to
organic carbon is better than using the interstial water concentration of the chemical because
dissolved organic carbon in the sediment can also bind the chemical and affect its bioavailibity
and toxicity. The particle organic carbon partition coefficient (Koc) is related to the chemical's
octanol/water partition coefficient (K^J by the following equation (Di Toro, 1991):
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logK c = 0.00028 ~ 0.983(logKJ
The octanol/water partition coefficient for each chemical, which represents the affinity of the
chemical to complex or sorb to organic carbon, must be measured with modern experimental
techniques to provide the most accurate estimate of this parameter. The concentration of the
chemical on sediment particles (Cs) is then equal to the dissolved concentration of chemical (Cd)
multiplied by the organic carbon content of the sediment (foc) and the particle organic carbon
partition coefficient (Koc), when foc is greater than 0.2 percent (USEPA, 1993i), thus normalizing
the dry-weight sediment concentration of the chemical to the organic carbon content of the
sediment.
The criterion threshold sediment concentration is derived from the final chronic value (FCV) of
the U.S. Environmental Protection Agency's water quality criteria (USEPA, 1985). Freshwater
and saltwater FCVs are based on the results of acceptable laboratory tests conducted to determine
the toxicity of a chemical in water to a variety of species of aquatic organisms, and they
represent the highest levels of a chemical to which organisms can be exposed without producing
toxic effects. This level is predicted to protect approximately 95 percent of aquatic life under
certain conditions. An evaluation of data from the water quality criteria documents and benthic
colonization experiments demonstrated that benthic species have chemical sensitivities similar to
those of water column species (Di Toro et al., 1991). Thus, if the concentration of a chemical
in sediment, measured with respect to the sediment organic carbon content, does not exceed the
sediment quality criterion, then no adverse biological effects from that chemical would be
expected (USEPA, 1992b, 1993i).
EPA has developed and published draft freshwater sediment quality criteria (SQCs) for the
protection of aquatic life for five contaminants: acenaphthene, dieldrin, endrin, fluoranthene, and
phenanthrene. These SQCs are based on the equilibrium partitioning approach (USEPA 1993d,
1993e, 1993f, 1993g, 1993h) using the aquatic life water quality criterion final chronic value
(FCV, in (Jg/L) and the partition coefficient between sediment and pore water (Kp, in L/g
sediment) for the chemical of interest (Di Toro et al., 1991; USEPA, 1993i). Thus, SQC =
FCV. On a sediment organic carbon basis, the sediment quality criterion, SQCoc, is:
sQCoc Mgoc) = FCV (ng/L) x K0C (L/kg) * (10'3kgjgoc)
where:
SQC^ = calculated sediment quality criterion;
FCV = EPA aquatic life water quality criterion final chronic value; and
= organic carbon-water partitioning coefficient.
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NAT EOft.ni.siPii&m®^
Koc is presumed to be independent of sediment type for nonionic organic chemicals, so that the
SQCoc is also independent of sediment type. Using a site-specific organic carbon fraction, foc
(goc/g sediment), the SQCoc can be expressed as a sediment-specific value, the SQC.
Uncertainty associated with the equilibrium partitioning theory for developing sediment quality
criteria includes the degree to which the equilibrium partitioning model explains the available
sediment toxicity data (USEPA, 1993i). An analysis of variance, using freshwater and saltwater
organisms in water-only and sediment toxicity tests (using different sediments) that were
conducted in support of the sediment criteria development effort, indicated that varying the
exposure media resulted in an estimate of variability that should be used for computing
confidence limits for the SQCoc. The degree of uncertainty associated with the sediment quality
criterion can also be influenced by the methodology used to derive the log Kow and the FCV for
a chemical. Differences in the response of water column and benthic organisms, and limitations
in understanding the relationship of individual and population effects to community-level effects,
have also been noted (Mancini and Plummer, 1994). Site-specific modifications to threshold
levels derived using the equilibrium partitioning model have been recommended to better address
chemical bioavailability and species sensitivities (USEPA, 1993b).
Sediment Quality Benchmarks
EPA intends to develop sediment quality criteria for additional chemicals in the future. In the
interim, and for the sole purpose of this evaluation, EPA's Office of Science and Technology
developed equilibrium partitioning-based sediment quality benchmarks (SQBs) using the
following equation:
SQB0C (vglgj = [FCV, SCV (|ig/L)] x Koc (L/kg) x (1(T'kgJgJ
where:
SQB^ = calculated sediment quality benchmark;
FCV, SCV = EPA aquatic life chronic criterion (final chronic value, FCV), or other
chronic threshold water concentration (secondary chronic value, SCV);
and
K^. = organic carbon-water partitioning coefficient.
A detailed discussion of the methodology used to derive SQBs for selected nonionic organic
chemicals and associated uncertainties is presented in Appendix A.
Acid Volatile Sulfide Concentration
The use of the total concentration of a trace metal in sediment as a measure of its toxicity and
its ability to bioaccumulate is not supported by field and laboratory studies because different
sediments exhibit different degrees of bioavailability for the same total quantity of metal (Di Toro
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3bts,trlbi jtton
et al., 1990; Luoma, 1983). These differences have recently been reconciled by relating
organism toxic response (mortality) to the metal concentration in the sediment pore water (Adams
et al., 1985; Di Toro et al., 1990). iMetals form insoluble complexes with the reactive pool of
solid-phase sulfides in sediments (iron and manganese sulfides), restricting their bioavailability.
The metals that can bind to these sulfides have sulfide solubility parameters smaller than those
of iron sulfide and include nickel, zinc, cadmium, lead, copper, and mercury. Acid volatile
sulfide (AVS) is one of the major chemical components that control the activities and availability
of metals in the pore (interstitial) waters of anoxic sediments (Meyer et al., 1994).
AVS is operationally defined as the sulfide liberated from a sediment sample to which
hydrochloric acid has been added at room temperature under anoxic conditions (Meyer et al.,
1994). The metals concentrations that are extracted during the same analysis are termed the
simultaneously extracted metals (SEM). SEM is operationally defined as those metals which
form less soluble sulfides than do iron or manganese (i.e., the solubility products of these sulfides
are lower than that of iron or manganese sulfide) and that are at least partially soluble under the
same test conditions in which the AVS content of the sediment is determined (Di Toro et al.,
1992; Allen et al., 1993; Meyer et al., 1994).
Laboratory studies using spiked sediments and field-collected metal-contaminated sediments
demonstrated that when the molar ratio of SEM to AVS was less than 1 (excess AVS remained),
no acute toxicity (mortality greater than 50 percent) was observed in any sediment for any
benthic test organism. When SEM/AVS was greater than 1 (excess metal remained), the
mortality of sensitive species (e.g., amphipods) increased in the range of 1.5 to 2.5 |imol of SEM
per |omol AVS (Casas and Crecelius, 1994; DiToro et al., 1992).
Experimental studies indicate that the lower limit of applicability for AVS is
approximately 1 pmol AVS/g sediment and possibly lower; other sorption phases, such as organic
carbon, probably become important for sediments with smaller AVS concentrations and for
metals with large partition coefficients and large chronic water quality criteria (Di Toro et al.,
1990). In addition, studies indicate that copper, as well as mercury, might be associated with
another phase in sediments, such as organic carbon, and AVS alone might not be the appropriate
partitioning phase for predicting its toxicity. Pore-water concentrations of metals should also be
evaluated (Allen et al., 1993; Ankley et al., 1993; Casas and Crecelius, 1994). The AVS
approach requires that all toxic SEMs present in amounts that would contribute significantly to
the SEM sum be measured to correctly predict only acute toxicity, so incomplete analyses of
metals would compromise the results (Di Toro et al., 1992); however, mercury presents special
problems and is not included in this evaluation. If the AVS content of sediment is low, as in
fully oxidized sediments, the metal-binding capacity of the sediment decreases and the method
will not work (Adams et al., 1992; Zhuang et al., 1994). Most benthic macroorganisms,
including those used in toxicity tests, survive in sediments that have a thin oxidized surface layer
and then an anoxic layer. The anoxic layer can have significant AVS concentrations that would
reduce the metal activity to which these organisms are exposed (Di Toro et al., 1992). AVS
varies spatially in sediment—vertically with depth and horizontally where patches of an
appropriate carbon source occur under low oxygen conditions for the sulfate-reducing bacteria.
AVS can also vary when sediments are oxgenated during physical disturbance and seasonally as
11
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changes in the productivity of the aquatic ecosystem alter the oxidation state of sediment and
oxidize metal sulfides, so that the toxicity of the metals present in the sediment changes over
time (Howard and Evans, 1993). However, the AVS approach can be used to predict when a
sediment contaminated with metals is not acutely toxic (Ankley et al., 1993; Di Toro et al.,
1992).
Biological Effects Correlation Approaches
Biological effects correlation approaches are based on the evaluation of paired field and
laboratory data to relate incidence of adverse biological effects to the dry-weight sediment
concentration of a specific chemical at a particular site. Researchers use these data sets to
identify level of concern chemical concentrations based on the probability of observing adverse
effects. Exceedance of the identified level of concern concentrations is associated with a
likelihood of adverse organism response, but it does not demonstrate that a particular chemical
is solely responsible. Consequently, correlative approaches do not indicate direct cause-and-effect
relationships. In fact, a given site typically contains a mixture of chemicals that contribute to
observed adverse effects to some degree. These and other potentially mitigating factors tend to
make thresholds based on correlative approaches conservative.
Effects Range-Medians and Effects Range-Lows
The effects range approach for deriving sediment quality guidelines involves matching dry-weight
sediment contaminant concentrations with associated biological effects data. Long and Morgan
(1990) originally developed informal guidelines using this approach for evaluation of NOAA's
National Status and Trends (NS&T) data. Data from equilibrium partitioning modeling,
laboratory, and field studies conducted throughout North America were used to determine the
concentration ranges that are rarely, sometimes, and usually associated with toxicity for marine
and estuarine sediments (Long et al., 1995). Effects range-low (ERL) and effects range-median
(ERM) values were derived by Long et al. (1995) for 28 chemicals: 9 trace metals, total PCBs,
13 individual polynuclear aromatic hydrocarbon (PAHs), 3 classes of PAHs (total low molecular
weight, total high molecular weight, and total PAH), and 2 pesticides (p,p'-DDE and total DDT).
For each chemical, sediment concentration data with incidence of observed adverse biological
effects were identified and ordered. Data entered into this biological effects database for
sediments (BEDS) were expressed on a dry-weight basis.
The authors identified the lower lOth-percentile concentration as the ERL and the 50th-percentile
concentration as the ERM. In terms of potential biological effects, sediment contaminant
concentrations below the ERL are said to be in the "minimal-effects range," values between the
ERL and ERM are in the "possible-effects range," and values above the ERM are in the
"probable-effects range."
The accuracy of these guidelines was evaluated based on the data in the database by noting
whether the incidence of effects was less than 25 percent in the minimal-effects range, increased
consistently with increasing chemical concentrations, and was greater than 75 percent in the
probable-effects range. Long et al. (1995) reported that these sediment quality guidelines were
12
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most accurate for copper, lead, silver, and all classes of PAHs and most of the individual PAHs;
however, accuracy was low for nickel, chromium, mercury, total PCBs, and DDE and DDT. The
guidelines generally agreed within factors of 2 to 3 with other guidelines, including the national
sediment quality criteria and freshwater effects-based criteria from Ontario. The authors
attributed variability in the database to differences in sensitivities of different taxa and physical
factors that affect bioavailability, but they argued that because of the synergistic effects of
multiple toxicants the inclusion of data from many field studies in which mixtures of chemicals
were present in sediments could make the guidelines more protective than guidelines based on
a single chemical. The authors also emphasized that ERLs and ERMs were intended to be used
as informal screening tools only.
Probable Effects Levels and Threshold Effects Levels
A method slightly different from that used by Long et al. (1995) to develop ERMs and ERLs was
used by the Florida Department of Environmental Protection (FDEP, 1994) to develop similar
weight-of-evidence, effects-based guidelines for Florida coastal waters. Modifications to the
Long et al. (1995) approach increased the relevance of the resultant guidelines to Florida coastal
sediments by making information in the database more consistent and by expanding the
information used to derive sediment quality assessment guidelines with additional data from other
locations in the United States and Canada, particularly Florida and the southeastern and Gulf of
Mexico regions (FDEP, 1994). Three effects ranges were developed with a method that used
both the chemical concentrations associated with biological effects (the "effects" data) and those
associated with no observed effects (the "no-effects" data). In this method, a threshold effects
level (TEL) was calculated first as the square root of the product of the lower 15th-percentile
concentration associated with observations of biological effects (the ERL) and the 50th-percentile
concentration of the no-observed-effects data (the NER-M). A safety factor of 0.5 was applied
to the TEL to define a no-observable-effects level (NOEL). Next, a probable-effects level (PEL)
was calculated as the square root of the product of the 50th-percentile concentration of the effects
data (the ERM) and the 85th-percentile concentration of the no-observed-effects data (the NER-
M). TELs and PELs were developed for 33 chemicals: 9 trace metals, total PCBs, 13 individual
polynuclear aromatic hydrocarbon (PAHs), 3 classes of PAHs (total low molecular weight, total
high molecular weight, and total PAH), 6 pesticides (chlordane, dieldrin, p,p'-DDD, p,p'-DDE,
p,p'-DDT) and total DDT.
As was the case with the Long et al. (1995) approach, in the FDEP (1994) approach the lower
of the two guidelines for each chemical (i.e., the TEL) was assumed to represent the
concentration below which toxic effects rarely occurred. In the range of concentrations between
the two values (i.e., the TEL and PEL) effects occasionally occurred. Toxic effects usually or
frequently occurred at concentrations above the upper guideline value (i.e., the PEL). TEL and
PEL values were developed on a sediment dry-weight basis.
Although the extensive database and evaluation of effects data make this approach applicable to
many areas of the country, the available data still have limitations. FDEP (1994) also noted that
there is a potential for underprotection or overprotection of aquatic resources if the bioavailability
of sediment-associated contaminants and other factors affecting toxicity are not included. Most
13
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of the TELs and PELs were within a factor of 2 to 3 of other sediment quality guideline values.
Most were deemed reliable (PELs having a lower reliability than TELs) for evaluating sediment
quality in Florida coastal waters, with less confidence in the values for mercury, nickel, total
PCBs, chlordane, lindane, and total DDT. The ability of the TELs and PELs to correctly predict
the toxicity of sediment, based on an evaluation of independent sets of field data from Florida,
the Gulf of Mexico, California and New York which were not included in the expanded database,
was 86 percent and 85 percent, respectively. These limitations should be considered in the
application of TELs and PELs.
Apparent Effects Thresholds
The AET approach is another empirical data approach similar to the effects range approaches
developed by Long et al. (1995) and FDEP (1994). Barrick et al. (1988) reported that AETs can
be developed for any measured chemical (organic or inorganic) that spans a wide concentration
range in the data set used to generate the AET. The AET concept was applied to matched field
data for sediment chemistry and any observable biological effects (e.g., bioassay responses,
infaunal abundances at various taxonomic levels, bioaccumulation). By using these different
biological indicators, application of the resulting sediment quality values enabled a wide range
of biological effects to be addressed in the management of contaminated sediments. Using
sediment samples from Puget Sound in Washington State, AET values were determined for 52
chemicals: 10 trace metals, 15 individual polynuclear aromatic hydrocarbon (PAHs), 3 pesticides
(p,p'-DDD, p,p'-DDE, p,p'-DDT), 6 halogenated organics, and 18 other compounds.
The focus of the AET approach is to identify concentrations of contaminants that are associated
exclusively with sediments exhibiting statistically significant biological effects relative to
reference sediments. AET values were based on measured chemical concentrations per dry
weight of sediment. AETs for each chemical and biological indicator were developed using the
following steps (Barrick et al., 1988).
1. Collected "matched" chemical and biological effects data—Conducted chemical and
biological effects testing on subsamples of the same field sample.
2. Identified "impacted" and "nonimpacted" stations—Statistically tested the significance
of adverse biological effects relative to suitable reference conditions for each sediment
sample and biological indicator.
3. Identified the AET using only "nonimpacted" stations—For each chemical, the AET
was identified for a given biological indicator and the highest detected concentration
among sediment samples that did not exhibit statistically significant effects.
4. Checked for a preliminary AET—Verified that statistically significant biological
effects were observed at a chemical concentration higher than the AET; otherwise, the
AET was only a preliminary minimum estimate.
5. Repeated steps 1-4 for each biological indicator.
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mS-EQ&SA SXRIRTOOK
For a given data set, the AET value for a chemical is the sediment concentration above which
a particular adverse biological effect for individual biological indicators (amphipod bioassay,
oyster larvae bioassay, Micortox bioassay, and benthic infaunal abundance) is always statistically
significantly different relative to appropriate reference conditions. Two thresholds were
recognized, when possible, based on the different indicators: (1) AET-L was the lowest
concentration for which a particular indicator showed an effect and (2) AET-H was the highest
concentration at which effects were observed for another indicator. AET values based on
Microtox bioassays were not used for the NSI evaluation.
Because the AET values to be used in this evaluation were based on empirical data from Puget
Sound, direct application of values from Puget Sound to a specific site or region in another part
of the country might be overprotective or underprotective of the resources in other areas.
Extensive collection of data and analyses would be required to develop AETs for other sites. The
AET does not establish cause-and-effect relationships, results might be affected by unmeasured
contaminants, and a protocol that ensures representative sampling is required (Calabrese and
Baldwin, 1993). EPA's Science Advisory Board (SAB, 1989) noted that the AET approach is
appropriate for deriving site-specific sediment quality guidelines, but should not be used to
develop general, nationally applicable sediment quality guidelines. However, EPA believes that
the use of AETs as one of several techniques for this screening-level assessment is appropriate.
Sediment Toxicity Tests
Methods for testing the acute and chronic toxicity of sediment samples to benthic freshwater and
marine organisms have been developed (see reviews in Burton et al., 1992, Lamberson et al.,
1992; API, 1994) and used primarily for dredged material evaluation (USEPA and USCOE,
1994). The NSI data contain acute sediment toxicity test results in which organisms were
exposed to potentially contaminated field-collected sediments and mortality or sublethal effects
on the organisms were recorded. Results of whole sediment and elutriate toxicity tests will be
used in the evaluation of the NSI.
Variations in sediment toxicity observed in tests of the same sediment sample may be attributed
to the relative sensitivities of the species used in the tests; disruption of geochemistry and kinetic
activity of bedded sediment contaminants during sampling, handling, and bioturbation; and
laboratory-related confounding factors (Lamberson et al., 1992). Recent studies indicate that
aqueous representations of whole sediment (e.g., elutriate) do not accurately predict the
bioavailability of some contaminants compared to whole-sediment exposures (Harkey et al.,
1994). Acute sediment toxicity tests have been widely accepted by the scientific and regulatory
communities and the results can be readily interpreted, although more work is needed on chronic
testing (Thomas et al., 1992). Sediment toxicity tests provide important information on the
effects of multiple chemical exposures to assist in the evaluation of sediment quality, but they
cannot be used alone.
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Ml, mini ii aim I mim riBin
NQiE^ffffBlSTRIBUTION
Human Health and Wildlife Assessments
In the evaluation of NSI data, two primary evaluation parameters will be used to assess potential
human health and wildlife impacts from sediment contamination: (1) sediment chemistry
theoretical bioaccumulation potential and (2) tissue levels of contaminants in demersal,
nonmigratory species. Each of these evaluation parameters is described below.
Theoretical Bioaccumulation Potential
The theoretical bioaccumulation potential (TBP) is an estimate of the equilibrium concentration
of a contaminant in tissues if the sediment in question were the only source of contamination to
the organism (USEPA and USACOE, 1994). The TBP calculation is used as a screening
mechanism to represent the magnitude of bioaccumulation likely to be associated with nonpolar
organic contaminants in the sediment. At present, the TBP calculation can be performed only
for nonpolar organic chemicals; however, methods for TBP calculations for metals and polar
organic chemicals are under development (USEPA and USACOE, 1994).
The environmental distribution of nonpolar organic chemicals is controlled largely by their
solubility in various media. Therefore, in sediments they tend to occur primarily in association
with organic matter (Karickhoff, 1981) and in organisms they are found primarily in the body
fats or lipids (Bierman, 1990; Geyer et al., 1982; Konemann and van Leeuwen, 1980; Mackay,
1982). Bioaccumulation of nonpolar organic compounds from sediment can be estimated from
the organic carbon content of the sediment, the lipid content of the organism, and the relative
affinities of the chemical for sediment organic carbon and animal lipid content (USEPA and
USACOE, 1994). It is possible to relate the concentration of a chemical in one phase of a two-
phase system to the concentration in the second phase when the system is in equilibrium. The
TBP calculation focuses on the equilibrium distribution of a chemical between the sediment and
the organism. By normalizing nonpolar organic chemical concentration data for lipid in
organisms, and for organic carbon in sediment, it is possible to estimate the preference of a
chemical for one phase or the other (USEPA and USACOE, 1994).
The TBP can be calculated relative to the biota-sediment accumulation factor (BSAF), as in the
following equation (USEPA and USACOE, 1994):
TBP = BSAF (CJfJf,
where TBP is expressed on a whole-body basis in the same units of concentration as Cs and
TBP = theoretical bioaccumulation potential (ppm);
Cs = concentration of nonpolar organic chemical in sediment (ppm);
BSAF = biota-sediment accumulation factor (ratio of the concentration of a chemical
in tissue, normalized to lipid, to the concentration of the chemical in surface
sediment, normalized to organic carbon (in kg sediment organic carbon/kg
lipid));
16
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foc = total organic carbon (TOC) content of sediment expressed as a decimal
fraction (i.e., 1 percent = 0.01); and
f, = organism lipid content expressed as a decimal fraction (i.e., 3 percent = 0.03)
of fillet or whole-body dry weight.
As discussed in USEPA and USACOE (1994), several assumptions are made in calculating TBPs.
The TBP calculation assumes that various lipids in different organisms and organic carbon in
different sediments are similar and have similar distributional properties. Other simplifying
assumptions are that chemicals are freely exchanged between the sediments and tissues and that
compounds behave conservatively. In reality, physical-chemical processes (e.g., diffusion through
porous media and sediment mixing) can limit the rate at which chemicals can exchange with
bottom sediments. Uptake of contaminants by aquatic organisms is also a kinetic (rate-
controlled) process that can be slowed, for example, by awkward passage of a bulky molecule
across biological membranes. Another important assumption implicit in the TBP calculations is
that there is no metabolic degradation or biotransformation of the chemical. Field-measured
BSAFs effectively incorporate these realities, although field-measured BSAFs will vary from site
to site due to variations in sediment properties, hydrodynamic mixing conditions, and species of
aquatic organism. Organic-carbon-normalized contaminant concentrations are used so that the
sediment-associated chemical can be characterized as totally bioavailable to the organism. The
approach also assumes that sediment does not move, that contaminant exposures from sources
other than sediment are negligible, that fish migration does not occur, and that exposure is
consistent. Calculations based on these assumptions yield an environmentally conservative TBP
value for the sediment if the sediment in question is the only source of the contaminant for the
organism. Note that TBP calculations are not valid for sediments with TOC less than or equal
to 0.2 percent (USEPA and USACOE, 1994).
BSAF values used in the TBP evaluation were derived using three primary sources of
information: data from two EPA Office of Research and Development Environmental Research
Laboratories (EPA/ERLs) and Evaluation of Dredged Material Proposed for Discharge in Waters
of the U.S.—Testing Manual (Draft) (USEPA and USACOE, 1994). The BSAFs from EPA/ERLs
were obtained from the research laboratories at Duluth, Minnesota (Cook, 1995) and
Narrangansatt, Rhode Island (Hansen, 1995). In some cases (i.e., EPA/ORD-Duluth), BSAFs
were provided for specific chemicals; in other cases (i.e., EPA/ORD-Narrangansett), BSAFs were
provided as distributions by chemical class.
BSAF recommendations obtained from EPA/ORD-Duluth included mainly chemical-specific
values for:
• PCB congeners
• Pesticides
• Dioxins/Furans.
BSAFs were also available from this source for three other chlorinated chemicals.
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The recommended values from EPA/ORD-Duluth were based on BSAF data compiled from
various sites and studies. Data were selected based on the following criteria (Cook, 1995):
• The primary source of chemical exposure to food webs was through release of
chemicals in sediments.
• The BSAF was derived for pelagic organisms (i.e., fish).
• Chemicals in sediments and biota were at roughly steady state with respect to
environmental loadings of the chemicals.
Few, if any, steady-state sites were available, however, because environmental loadings of many
of the chemicals are variable or have declined since the 1960s. Barring this limitation, two
sources of BSAF values were used in NSI sediment assessments: 1) BSAF data for Lake Ontario
used to estimate bioaccumulation factors for the Great Lakes Water Quality Inititive (Cook et al„
1994), and 2) values reported for Lake Ontario salmonids (Oliver and Niimi, 1988). The Lake
Ontario BSAFs are based on a large set of sediment and fish samples collected in 1987 (USEPA,
1990a).
EPA/ORD-Narrangansett provided a second source of information for selecting BSAF values.
Probability distribution curves for selecting BSAFs were presented by EPA/ORD-Narragansett
for three chemical classes:
• PAHs
• PCBs
• Pesticides.
EPA/ORD-Narragansett researchers developed probability curves for each chemical class from
their database of BSAFs (Hansen, 1995). The database from which general BSAF
recommendations were summarized included data from laboratory and field studies conducted
with both freshwater and marine sediments. Data must be from species that directly contact
sediments or feed on organisms that live in sediments (i.e., benthic invertebrates and benthically
coupled fishes.)
Overall, the database contained more than 4,000 BSAF observations. Probability curves
summarizing the BSAF data in the database were provided by Hansen (1995) for PAHs, PCBs,
and pesticides. BSAF values were tabulated for several probability percentiles.
The draft Testing Manual (USEPA and USACOE, 1994) recommends a default value of 4 for
the BSAF. The value of 4 is based on field studies with PCBs (Ankley et al., 1992). It represents
the potential contaminant concentration in lipid of biota if sediment is the only source of
contaminant exposure to the organism (USEPA and USACOE, 1994). For the purpose of
evaluation of the NSI data, the default BSAF value of 4 was used only if no chemical-specific
or chemical class-specific BSAF values were available from the other two primary sources.
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A more detailed description of the BSAF values used in this evaluation and how they were
selected is presented in Appendix B.
A fish fillet lipid value of 3 percent is assumed for the TBP calculations to be used in the NSI
data evaluation for human health, based on the current national methodology for the development
of human health water quality criteria. A whole body lipid value of 10.31 is assumed for the
TBP evaluation of potential wildlife impacts, based on the Great Lakes Water Quality Initiative
Technical Support Document for the Procedure to Determine Bioaccumulation Factors (USEPA,
1995). These values are discussed further in Chapter 4.
In both the NSI data evaluation approach recommended by the April 1994 workshop participants
and the revised approach, TBP values are compared to U.S. Food and Drug Administration action
levels, EPA risk levels, and EPA wildlife criteria. These parameters are discussed below.
FDA Action Levels
The U.S. Food and Drug Administration (FDA) is responsible for the safety of the Nation's
foods, including fish and shellfish, for human consumption. Under the authority of the Federal
Food, Drug and Cosmetic Act (FFDCA), the FDA ensures that regulated products are safe for
use by consumers. The FFDCA authorizes the FDA to conduct assessments of the safety of
ingredients in foods. The key element of the FFDCA, and the source of FDA's main tools for
enforcement, is the prohibition of the "adulteration" of foods. The FDA can prescribe the level
of contaminant that will render a food adulterated and, therefore, can initiate enforcement action
based on scientific data. The establishment of action levels (informal judgments about the level
of a food contaminant to which consumers can be safely exposed) or tolerances (regulations
having the force of law) is the regulatory procedure employed by FDA to control environmental
contaminants in food.
FDA established action levels for several pesticides before they were banned. At the time (i.e.,
during the 1970s), the available detection limits were considered to demonstrate elevated
contamination and were used as action levels. Since that time, FDA has focused on developing
risk-based standards. These standards have been derived by individually considering each
chemical and the species of fish it is likely to contaminate. FDA also considered (1) the amount
of potentially contaminated fish eaten and (2) the average concentrations of contaminants
consumed. The FDA has established action levels in fish for 19 pesticides, polychlorinated
biphenyls (PCBs), 5 metals, and methylmercury.
EPA Risk Levels
Potential impacts on humans are evaluated by estimating potential carcinogenic risks and
noncarcinogenic hazards associated with the consumption of chemically contaminated fish tissue.
In this assessment it is assumed that the only source of contamination to fish is contaminated
sediment. The procedures for estimating human health risks due to the consumption of
chemically contaminated fish tissue are based on Risk Assessment Guidance for Superfund
19
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JJpT FOR npi'STRIB'UTON
(USEPA, 1989) and Guidance for Assessing Chemical Contamination Data for Use in Fish
Advisories, Volume II: Development of Risk-Based Intake Limits (USEPA, 1994c).
EPA human health risk assessment methods are used in this assessment to determine the levels
of contamination in fish that might result in a 10"5 cancer risk or a noncancer hazard in humans.
A 10"5 risk level exceeds the lower bound (i.e., 10"6) but is lower than the upper bound (i.e., 10"4)
of the risk range accepted by EPA (USEPA, 1990b).
Human health cancer risks and noncancer hazards are based on the calculation of the chronic
daily intake (CDI) of contaminants of concern:
_ (EPQ(IK)(EF)(ED)
(BW)(AD
where:
CDI = chronic daily intake (mg/kg/day);
EPC = exposure point concentration (contaminant concentration in fish);
IR = ingestion rate (6.5 g/day);
EF = exposure frequency (365 days/year);
ED = exposure duration (70 years);
BW = body weight (70 kg); and
AT = averaging time (70 years x 365 days/year).
These are the same parameter values used by EPA to develop human health water quality criteria.
Carcinogenic risks are then quantified using the equation below:
Cancer riski = CDIt x SF
where:
Cancer risk, = the potential carcinogenic risk associated with exposure to chemical i
(unitless);
CDI; = chronic daily intake for chemical i (mg/kg/day); and
SFj = slope factor for chemical i (mg/kg/day)"1
The hazard quotient, which is used to quantify the potential for an adverse noncarcinogenic effect
to occur, is calculated using the following equation:
CDI
HQ. = -
m
where:
HQ; = hazard quotient for chemical i (unitless);
CDI, = chronic daily intake for chemical i (mg/kg/day); and
20
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RfD, = reference dose for chemical / (mg/kg/day).
If the hazard quotient exceeds unity (i.e., 1), an adverse health effect might occur. The higher
the hazard quotient, the more likely that an adverse noncarcinogenic effect will occur as a result
of exposure to the chemical. If the estimated hazard quotient is less than unity, an adverse
noncarcinogenic effect is highly unlikely to occur.
Using these formulas, the fish tissue concentration (EPC) of a contaminant that equates to a
cancer risk of 10"5 or a hazard quotient that exceeds unity can be back-calculated.
Cancer risk:
(10"5)(flWO(^7)(Cj)
= =
(/i?)(£F)(£D)(SF.)
Noncancer hazard:
(BW)(AD(RfD)(C,)
£rC =
(IK)(EF)(ED)
where:
C, = conversion factor (103 g/kg).
EPA Wildlife Criteria
EPA has developed Great Lakes Water Quality Wildlife Criteria for four chemicals: DDT,
mercury, 2,3,7,8-TCDD, and PCBs. A Great Lakes Water Quality Wildlife Criterion (GLWC)
is the concentration in the water of a substance that, if not exceeded, protects avian and
mammalian wildlife populations from adverse effects resulting from the ingestion of surface
waters and aquatic prey (USEPA, 1993c). Wildlife values are calculated using the equation
presented below:
(NOAEL x SSF) x Wt.
WV = d
WA + (Fa x BAF)
where:
WV = wildlife value (mg/L);
NOAEL = no-observed-adverse-effect level as derived from mammalian or avian
studies (mg/kg-d);
WtA = average weight for the representative species identified for protection
(kg);
21
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.Mas^EQBjMgiHaBffpray
WA = average daily volume of water consumed by the representative species
identified for protection (L/d);
SSF = species sensitivity factor, an extrapolation factor to account for the
difference in toxicity between species;
Fa = average daily amount of food consumed by the representative species
identified for protection (kg/d); and
BAF = bioaccumulation factor (L/kg), the ratio of the concentration of a
chemical in tissue, normalized to lipid, to the concentration in ambient
water. Chosen using guidelines for wildlife presented in appendix B to
part 132, Methodology for Development of Bioaccumulation Factors
(Federal Register, Vol. 58, No. 72, April 16, 1993).
In the development of the four GLWCs, wildlife values for five representative Great Lakes basin
wildlife species (bald eagle, osprey, belted kingfisher, mink, and river otter) were calculated, and
the geometric mean of these values within each taxonomic class was determined. The GLWC
is the lower of two class-species means (USEPA, 1993c).
The wildlife values are considered to be generally protective of wildlife species. However, it
should be noted that the approach is not based on the most sensitive wildlife species, but rather
a typical class of either avian or mammalian piscivores. Despite this, this approach is still
considered appropriate and conservative because of the many conservative assumptions used to
derive these wildlife values (e.g., species sensitivity factors, assumption that animals consume
only contaminated fish).
Tissue Levels of Contaminants
In addition to sediment chemistry TBP values, measured levels of contaminants in the tissues of
resident aquatic species can be used to assess potential human health risk and potential impacts
to wildlife from sediment contamination. As was the case with the evaluation of TBP values,
both the evaluation approach recommended by the April 1994 workshop participants and the
revised approach presented in Chapter 4 of this document suggest comparing contaminant tissue
levels to FDA action levels, EPA risk levels, and EPA wildlife criteria. Each of these parameters
was discussed in the previous section. In such a comparison it is assumed that contaminant
concentrations in tissue are due to bioaccumulation from contaminants in the sediment.
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MQ3^fiQR4DIS-XRIBUJIQN_
3. OVERALL APPROACH RECOMMENDED BY NSI WORKSHOP
The original proposed approach for the integration and evaluation of NSI sediment chemistry and
biological data was developed at the Second National Sediment Inventory Workshop held on
April 26 and 27, 1994, in Washington, D.C. The workshop approach has been modified,
however, to address inconsistencies found in trying to implement the approach and to address the
concerns of the many experts in the field of sediment quality assessment who commented on the
workshop approach. This chapter of the issue paper presents the NSI data evaluation approach
developed by the April 1994 workshop participants. Chapter 4 presents the revised approach that
EPA has proposed for the data evaluation.
Using the approach recommended by workshop participants, sediment sites were to be placed into
one of the following five categories based on an evaluation of data compiled for the NSI:
• High probability of adverse effects to aquatic life or human health
• Medium-high probability of adverse effects to aquatic life or human health
• Medium-low probability of adverse effects to aquatic life
• Low probability of adverse effects to aquatic life or human health
• Unknown probability of adverse effects to aquatic life or human health.
Using the workshop approach, contaminated sediment sites would be placed into one of these five
categories based on an evaluation of the following types and combinations of data:
• Sediment chemistry data alone
• Toxicity data alone
• Tissue residue data alone
• Sediment chemistry and tissue residue data
• Sediment chemistry and histopathological data
° Sediment chemistry, sediment toxicity, and tissue residue data.
The overall approach developed by workshop participants is summarized in Table 1 and is
described below.
High Probability of Adverse Effects to Aquatic Life or Human Health
Based on the evaluation approach developed by the April 1994 workshop participants, a site can
be classified as having a high probability of adverse effects to aquatic organisms or human health
based on sediment chemistry data alone, toxicity data alone, tissue residue data alone, or a
combination of sediment chemistry and tissue residue or histopathological data.
For a site to be classified as one with a high probability of adverse effects based on sediment
chemistry data alone, at least one of three criteria must be met: (1) sediment chemistry values
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Table 1. Original Approach Recommended by NSI Workshop (April 1994)
Data Used to Determine Classifications
Category of Site
Classifications
Sediment Chemistry
(site is identified by any one of
the following characteristics)
Tissue Residue/
Histopathology
Toxicity
High Probability of
Adverse Effects to
Aquatic Life or
Human Health
Sediment chemistry values
exceed sediment quality
criteria for any one of the five
chemicals for which criteria
have been developed by EPA
(based on measured TOC)
Human health thresholds
for dioxin or PCBs are
exceeded in resident
species (not a consensus
agreement—participants
evenly divided on this
Toxicity demonstrated by
two or more acute
toxicity tests (one of
which must be a solid-
phase nonmicrobial test)
Sediment chemistry values
exceed all relevant AETs
(high), ERMs. PELs, and
SQBs for any one chemical
(can use default TOC)
OR
issue)
OR
Sediment chemistry values
>50 ppm for PCBs
Sediment chemistry TBP
exceeds FDA action levels.
EPA risk levels, or wildlife
criteria
AND
Tissue levels in resident
species exceed FDA
action levels or EPA risk
levels, or wildlife criteria
Elevated sediment chemistry
concentrations of PAHs
AND
Presence of fish tumors
Medium-High
Probability of
Adverse Effects to
Aquatic Life or
Human Health
Sediment chemistry values
exceed at [east two of the
sediment upper threshold
criteria (i.e., ERM, SQB, PEL.
high AET) (can use default
TOC—SQBs for metals cannot
be used unless with measured
AVS)
OR
Tissue levels in resident
species exceed FDA
action levels or wildlife
criteria
OR
Toxicity demonstrated by
a single-species toxicity
test (solid-phase,
nonmicrobial)
Sediment chemistry TBP
exceeds FDA action levels or
wildlife criteria
Medium-Low
Probability of
Adverse Effects to
Aquatic Life
Sediment chemistry values
exceed one of the lower
threshold criteria (ERL, SQB,
TEL, lower AET) (can use
default TOC and AVS)
OR
Toxicity demonstrated by
a single species toxicity
test (elumate-phase,
nonmicrobial)
Low Probability of
Adverse Effects to
Aquatic Life or
Human Health
No exceedance of lower
threshold values
and
No sediment chemistry TBP
exceedances of FDA action
levels or wildlife criteria
AND
Tissue levels in resident
species are lower than
FDA action levels or
wildlife criteria
AND
No toxicity demonstrated
in tests using at least two
species and at least one
solid-phase test using
amphipods
Unknown
Not enough data to place a site in any of the other categories
24
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exceed the sediment quality criteria (SQCs) developed by EPA for acenaphthene, dieldrin, endrin,
fluoranthene. or phenanthrene; (2) sediment chemistry values exceed all appropriate threshold
values for a given chemical (i.e., high apparent effects thresholds (AETs), effects range-medians
(ERMs), probable effects levels (PELs), and sediment quality benchmarks (SQBs)); and/or
(3) sediment chemistry values exceed 50 ppm for polychlorinated biphenols (PCBs). When
comparing sediment chemistry values to the SQCs, measured total organic carbon (TOC) must
be used. Workshop participants suggested using default TOC values in the comparison of
sediment chemistry values to SQBs if actual measured TOC values are not available. However,
if default TOC values are used in a comparison of sediment chemistry measurements to SQCs,
the highest that a site could be classified would be medium-high potential for adverse effects.
For a site to be classified as having a high probability of adverse effects based on a combination
of sediment chemistry and tissue residue data, sediment chemistry theoretical bioaccumulation
potential (TBP) and tissue levels in resident, nonmigratory species must exceed FDA action
levels, EPA risk levels, or EPA wildlife criteria. Workshop participants also recommended that
a site be classified as having a high probability of adverse effects if fish tumors are present in
resident species and elevated sediment chemistry concentrations for polynuclear aromatic
hydrocarbons (PAHs) are present (see Harshbarger and Clark, 1990; Myers et al., 1990;
Vogelbein et al., 1990).
The workshop participants were evenly divided on whether a site could be classified as having
a high probability of adverse effects based solely on the exceedance of human health thresholds
for dioxins or PCBs in resident fish species. Participants did agree that benthic community data
in combination with sediment chemistry data could be used in the future, but not for the current
evaluation, to classify sediment sites. Methods are currently not adequate to establish a direct
causal relationship between benthic community changes and sediment contamination at specific
sites without additional data such as dissolved oxygen content of surface water.
For a site to be classified as having a high probability of adverse effects based on toxicity data
alone, toxicity must be demonstrated by two or more acute toxicity tests, at least one of which
must be a solid-phase, nonmicrobial test.
Medium-High Probability of Adverse Effects to Aquatic Life or Human Health
Workshop participants suggested that a site could be classified as having a medium-high
probability of adverse effects on aquatic life or human health based on sediment chemistry data
alone, toxicity data alone, or tissue residue data alone.
For a site to be classified as having a medium-high probability of adverse effects based on
sediment chemistry data alone, the site must meet at least one of two criteria: (1) sediment
chemistry values exceed at least two of the sediment chemistry upper threshold values (i.e.,
appropriate ERMs, SQBs, PELs, or high AETs), or (2) sediment chemistry TBP exceeds FDA
action levels or EPA wildlife criteria. In the comparison of sediment chemistry values to SQBs,
default TOC values can be used. Workshop participants suggested that SQBs for metals could
be used only with measured acid volatile sulfide (AYS) values.
25
-------
A site could also be classified as having a medium-high probability of adverse effects if toxicity
is demonstrated by a single-species, nonmicrobial toxicity test using the solid phase as the testing
medium or if actual fish tissue residue levels exceed FDA action levels or EPA wildlife criteria.
Medium-Low Probability of Adverse Effects to Aquatic Life
Workshop participants suggested that a site could be classified as having a medium-low
probability of adverse effects to aquatic life based on either sediment chemistry data alone or
toxicity data alone. A site could be classified as having a medium-low probability of adverse
effects if sediment chemistry values exceed at least one of the lower sediment chemistry
threshold values (i.e., effects range-low (ERL), threshold effects level (TEL), SQB, or lower
AET). Workshop participants suggested that default TOC and AVS values could be used in SQB
assessments. To classify a site as having a medium-low probability of adverse effects, toxicity
would be demonstrated by a single species, nonmicrobial toxicity test using the elutriate phase
as the test medium. Workshop participants did not propose any human-health-related criteria for
placing a site in the medium-low probability of adverse effects category.
Low Probability of Adverse Effects to Aquatic Life and Human Health
Using the workshop approach, for a site to be classified as having a low probability of adverse
effects on aquatic life and human health, all of the following criteria must be met: (1) there are
no exceedances of the lower sediment chemistry threshold values (i.e., ERL, TEL, SQB, or lower
AET); (2) there is no toxicity demonstrated in tests using at least two species and at least one
solid-phase test using amphipods; (3) there are no TBP exceedances of FDA action levels and
EPA wildlife criteria; and (4) tissue levels of resident species are below FDA action levels and
EPA wildlife criteria.
Unknown Probability of Adverse Effects
Sites of unknown probability for causing adverse effects are those sites for which there are
inadequate data to place them in any of the other categories. Sediments at the sites might or
might not cause adverse impacts to aquatic life or human health.
Modifications to Workshop Approach
As mentioned previously, the approach for evaluating NSI data recommended by the April 1994
workshop participants provides the framework for the final proposed evaluation approach
presented in this issue paper. Workshop participants had less than 4 hours to reach consensus
on their recommendations for the approach following a day and a half of debate covering many
challenging issues. As a result, some of the specific issues concerning how data were to be
evaluated to place sites into the five categories remained unresolved. For example, "elevated
sediment chemistry concentrations of PAHs" together with the presence of fish tumors is one
criterion for placing a site in the high probability of adverse effects category. However, how
"elevated" do sediment chemistry concentrations of PAHs have to be to meet this criterion? As
another example, sediment chemistry values that exceed all relevant AETs, ERMs, PELs, and
26
-------
N^POR^-SMBUXIQN
SQB values for any one chemical are sufficient to place a site in the high probability category,
and exceedance of any two of these values is sufficient to place a site in the medium-high
probability category. But what if there are only two relevant threshold values for a given
contaminant? Does a site at which both values are exceeded for a given chemical belong in the
high or medium-high probability category? In the following chapter, these and other details
concerning the evaluation approach are discussed, and recommendations are made for refining
the overall approach. Also discussed are the assumptions made in arriving at the final proposed
approach.
27
-------
-------
MQT^EQR-gBJSJAIB.LLXIQN,
4. FINAL PROPOSED APPROACH
This chapter presents the detailed final proposed methodology for classifying each sampling
station as to the probability of adverse effects to aquatic life and human health from sediment
contamination. The classification scheme relies on sediment chemistry, toxicity, and tissue
residue data. Available fish liver histopathology data were very limited, and therefore this
evaluation parameter was not considered further. Table 2 presents a modified version of the
classification scheme proposed by participants at the April 1994 National Sediment Inventory
Workshop. A significant modification is the reduction in the number of categories from five to
four, eventually combining the medium-high and medium categories proposed in the workshop
approach. In Table 2 each evaluation parameter has been numbered to allow the reader to follow
the discussion in the text more easily. In the text the number associated with each parameter is
presented in brackets following the parameter heading.
The general approach for analyzing the NSI data is to evaluate each parameter in Table 2 on a
station-by-station and sample-by-sample basis. After all of the parameters have been evaluated
for all data amenable to analysis, each station is classified into a probability of adverse effects
category by combining parameters as indicated in Table 2. Each individual measurement is
considered independently (except for divalent metals, whose concentrations are summed) such
that a single measure of elevated concentration can place a site into the high probability category.
In general, the methodology is constructed such that there must be a relatively large set of data
(e.g., TOC, AVS, tissue residue data, sediment chemistry data, multiple toxicity tests) or a highly
elevated sediment concentration of a chemical whose threshold level has been well characterized
using multiple assessment techniques, for a site to be classified as having a high probability of
adverse effects. Less stringent means are applied to placement in the medium probability
category, whereas placement in the low probability category requires a substantial minimum data
set. Each numbered evaluation parameter is described below.
Evaluation of Sediment Chemistry Data
Sediment Chemistry Values Exceed EPA Sediment Quality Criteria [T1
This evaluation parameter is used to assess potential effects of sediment contamination on benthic
species. Sediment quality criteria (SQCoc) have been developed by EPA using the final chronic
values (FCVs, |ig/L) from aquatic life water quality criterion documents and the organic carbon
partition coefficient of the chemical (Koc, L/kg sediment).
SQCX (M/Sj = FCV fcig/i) * Kx (L/kg) x W'kgJgJ
At this time, EPA has proposed SQCs for the following five chemicals:
• Acenaphthene (CAS = 000083329)
• Dieldrin (CAS = 000060571)
29
-------
Table 2. Final Proposed Evaluation Approach (June 1995) (with numbered parameters)
Category of Site
Classifications
Data Used to Determine Classifications
Sediment Chemistry
Tissue Residue
Toxicity
High Probability of
Ad\erse Effects to
Aquatic Life or
Human Health
Sediment chemistry values
exceed sediment quality
criteria for any one of the five
chemicals for which criteria
have been developed by EPA
(based on measured TOC) 1
OR
Tissue levels of dioxin or
PCBs in resident species
exceed EPA risk levels 10
OR
Toxicity demonstrated by
two or more nonmicrobial
acute toxicity tests (one
of which must be a solid-
phase test) 14
SEM-AVS > 5 for the sum of
molar concentrations of Cd.
Cu. Ni. Pb. and Zn 2
Sediment chemistry values
exceed two or more of the
relevant upper thresholds
(ERMs. AETs (high). PELs,
SQBs) for any one chemical
(other than Cd. Cu, Ni. Pb.
and Zn) (can use default TOC)
3
Sediment chemistry values
>50 ppm for PCBs 4
Sediment chemistry TBP
exceeds FDA action levels.
EPA risk levels, or wildlife
criteria 5
AND
Tissue levels in resident
species exceed FDA action
levels, EPA risk levels, or
wildlife criteria 11
Medium Probability
of Adverse Effects
to Aquatic Life or
Human Health
SEM-AVS = 0 to 5 for the
sum of molar concentrations of
Cd, Cu, Ni. Pb. and Zn 6
OR
Tissue levels in resident
species exceed FDA action
levels, EPA risk levels, or
wildlife criteria 12
OR
Toxicity demonstrated by
a single-species
nonmicrobial toxicity test
15
Sediment chemistry values
exceed any one of the relevant
lower thresholds (ERLs. AETs
(low), TELs. SQBs) for any
one chemical (can use default
TOO 7
Sediment chemistry TBP
exceeds FDA action levels,
EPA risk levels, or wildlife
criteria 8
Low Probability of
Adverse Effects to
Aquatic Life or
Human Health
SEM-AVS < 0 for the sum of
molar concentrations of Cd,
Cu, Ni, Pb, and Zn
OR 9a
No exceedance of any
threshold values for chemicals
other than Cd. Cu. Ni, Pb, and
Zn 9b
AND
Tissue levels of resident
species are lower than FDA
action levels. EPA risk
levels, and wildlife criteria
13
AND
No toxicity demonstrated
by a single-species solid-
phase toxicity test using
standardized EPA test
species 16
AND
No sediment chemistry TBP
exceedances of FDA action
levels. EPA risk levels, and
wildlife criteria 9c
Insufficient Evidence to Determine Probability of Adverse Effects
30
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• Endrin (CAS = 000072208)
• Fluoranthene (CAS = 000206440)
• Phenanthrene (CAS = 000085018)
The SQCocs for these chemicals are presented in Appendix C. The methodology requires that
only those sediment chemistry measurements with accompanying measured TOC values may be
used in the comparison of NSI data to the SQCs for these five chemicals. Prior to comparing
NSI data to the SQCs for these chemicals, the SQCs will be adjusted to account for the actual
TOC measured in the sample (if available), where TOC is expressed as a percent (foc):
SQC = (SQCJ (fj
NSI sediment chemistry data for the five chemicals of concern will then be compared to their
corresponding TOC-adjusted SQCs. Any station at which one observation for any of the five
chemicals exceeds the TOC-adjusted SQC will be classified as having a high probability of
causing adverse effects to aquatic life from contaminated sediments. If a sample for one of the
five contaminants for which SQCs have been developed does not have accompanying TOC data,
it will be compared to the SQC obtained using the default value of foc = 0.001. A sample site
that does not have accompanying TOC data cannot be classified as having a high probability of
adverse effects regardless of the measured contaminant concentration. The highest it could be
classified would be medium probability of adverse effects. If SQCs are not exceeded, and data
exists for each of the five chemicals, there is presumed to be a low probability of adverse effects
if the sample in question also meets the other requirements needed to place a site in the "low"
probability of adverse effects category (i.e., parameters 9a, 9b, 9c, 13, and 16).
Comparison of AYS to SEM Molar Concentrations [2, 6, 9al
This evaluation parameter is used to assess potential effects of metal contaminated sediment on
benthic species. For this evaluation parameter the molar concentration of acid volatile sulfide
(AVS) is compated to the sum of simultaneously extracted metal (SEM) molar concentrations for
five metals: cadmium (Cd), copper (Cu), nickel (Ni), lead (Pb), and zinc (Zn).
Selection of an SEM-AVS difference sufficiently high to place a sediment in the high probability
of adverse effects category requires careful consideration because the relationship between
organism response and the SEM-AVS difference of sediment depends on the amount and kinds
of other binding phases present. Using freshwater and saltwater sediment amphiod toxicity data,
researchers at EPA's Environmental Research Laboratory in Narragansett, Rhode Island, plotted
SEM-AVS versus the percentage of sediments with a higher SEM-AVS value that were toxic.
For this analysis, the researchers defined toxicity as greater than 24 percent mortality. Analysis
of this data reveals that between 80 percent and 90 percent of the sediment are toxic at SEM-
AVS equal to 5. The running average mortality at this level is between 44 percent and 62
percent (Hansen, 1995). EPA's Office of Science and Technology selected SEM-AVS equal to
5 as the demarcation line between the high and medium probability categories.
31
-------
For the purpose of this evaluation, where SEM-AVS > 5, there is presumed to be a high
probability of adverse effects to aquatic life. If SEM-AVS = 0 to 5, there is presumed to be a
medium probability of adverse effects. If SEM-AVS < 0, there is presumed to be a low
probability of adverse effects if the sample in question also meets the other requirements needed
to place a site in the low probability of adverse effects category (i.e., parameters 9b, 9c, 13,
and 16).
Sediment Chemistry Values Exceed Threshold Values T3. 7. 9bl
This evaluation parameter is used to assess the potential effects on benthic species of sediment
concentrations of chemicals without sediment quality criteria. The threshold levels selected for
comparison with measured sediment levels are the sediment quality benchmarks (SQBs)
(Appendix A) for freshwater aquaitc life; the effects range-medians (ERMs) and effects range-
lows (ERLs) developed by Long et al. (1995); the probable effects levels (PELs) and threshold
effects levels (TELs) developed by the Florida Department of Environmental Protection (FDEP,
1994); and the apparent effects thresholds (AETs)(Barrick et al., 1988). The chemical-specific
threshold values used in this analysis are presented in Appendices A and C. Those chemicals
with no available threshold values will not be evaluated at this time.
For the purpose of this evaluation, the upper threshold values are considered to be the ERM,
PEL, SQB, and AET-high for a given chemical. The lower threshold values are considered to be
the ERL, TEL, SQB, and AET-low for a given chemical. The single freshwater aquatic life SQB
value for a given chemical serves as both a high and low threshold value. Because SQBs are
empirically-based correlative values, a high/low distinction is not relevant.
For a site to be classified as having a high probability of adverse effects, one chemical
measurement for a chemical of concern must exceed at least two of the upper threshold values
(i.e., ERM, AET-high, PEL, or SQB) for chemicals other than those with EPA sediment quality
criteria or for Cd, Cu, Ni, Pb, and Zn (which are evaluated based on the SEM/AVS comparison.)
If a sediment chemistry measurement for any given chemical of concern exceeds any one of the
lower threshold values, (i.e., ERL, AET-low, TEL, or SQB) the site will be classified as having
a medium probability of adverse effects. For a site to be classified as having a low probability
of adverse effects, no sediment chemistry measurements can exceed any threshold value and
measurements at the site must meet all other requirements to place a site in the low category (i.e.,
parameters 9a, 9c, 13, and 16).
It should be noted that under this proposed approach a site can be classified as having a high
probability of adverse effects from Cd, Cu, Ni, Pb, or Zn only based on a comparison of SEM
to AVS (i.e., sites cannot be classified as having a high probability of adverse effects from high
concentrations of these metals based on an exceedance of two upper threshold values). However,
a site can be classified as having a medium probabililty of adverse effects from these five metals
based on an exceedance of one of the lower threshold values.
It should also be noted that currently relatively few AVS data are included in the NSI.
Therefore, few sites will be classified in the first Report to Congress as having a high probability
32
-------
of adverse effects because of Cd, Cu, Ni, Pb, and Zn contamination. It is anticipated that future
monitoring programs will report AVS more frequently along with metals data, and thus future
Reports to Congress will include evaluations of additional sites based on SEM/AVS.
Sediment Chemistry Values for Polvchlorinated Biphenyls (PCBs) Exceed 50 ppm |"31
All stations with at least one PCB observation exceeding 50 ppm will be classified as having a
high probability of adverse effects. This is the concentration at which the Toxic Substance
Control Act (TSCA) regulates the disposal of wastes containing PCBs.
Sediment Chemistry TBPs Exceed Threshold Criteria [5, 8, 9cl
This evaluation parameter addresses risk to consumers of organisms exposed to sediment
contaminants. In this portion of the analysis, theoretical bioaccumulation potentials (TBPs) for
nonpolar organic chemicals will be compared to U.S. Food and Drug Administration (FDA)
action levels, EPA risk levels, and EPA wildlife criteria. FDA action levels and EPA risk levels
are used to assess potential human health impacts, and EPA wildlife criteria are used to assess
potential impacts to higher trophic level organisms such as birds and mammals.
TBPs (expressed in parts per million, or ppm) can be computed for nonpolar organic chemicals
as a function of sediment concentration (Cs, ppm), the bioaccumulation potential of fish from
exposure to contaminated sediments (biota/sediment accumulation factor, BSAF), the TOC
fraction of sediment (foc), and the lipid content fraction of tissue (f,) (USEPA and USACOE,
1994):
TBP = BSAF (Cs I fj ft
Nonpolar organic chemicals to be evaluated in this portion of the analysis are identified in
Appendix C. If TOC measurements are not available, foc will be assumed to be 0.01 (1 percent).
The BSAF represents the preference of a chemical for the lipid content in organisms rather than
the organic carbon in sediment. EPA is using a variety of BSAF values in its calculation of TBP
values for the NSI evaluation. Chemical- or chemical-class-specific BSAF values (expressed on
a lipid and organic carbon basis) will be used for dioxins, PCBs, pesticides, PAHs, and
halogenated compounds. A discussion of the sources of these BSAFs and their values are
presented in Appendix B. For all other chemicals a default BSAF of 4 will be used in the
calculation of TBPs. The draft Testing Manual (USEPA and USACOE, 1994) recommends use
of a BSAF value of 4 for calculating the TBP for benthic invertebrates. Other studies (e.g.,
Dorkin et al., 1987) indicate that a BSAF range of 2-4 for fish is reasonable. Because
assignment of BSAFs for a given chemical involves selecting a level from a continuous
distribution of values, applying a safety factor, or using a default value (see Appendix B for
details), a risk management decision is necessary. To be consistent with the level of
conservatism inherent in other evaluation parameters (e.g., SEM-AVS difference, use of criteria
meant to be protective of 95 percent of the species), EPA opted for rather conservative BSAF
33
-------
not tor msTOgTOOfr
assignments. However, because there is a substantial conservative element already present in the
toxicity assessment (e.g., the slope factor and reference dose for EPA risk levels), EPA might
also evaluate the NSI data using a central tendency BSAF assignment approach for comparison.
For the evaluation of NSI data, EPA has selected a 3 percent lipid content in fish fillets for the
TBP calculation for assessing human health effects from the consumption of contaminated fish.
Lipid normalization is now part of the EPA guidance on bioaccumulation, and the current
national methodology uses a 3 percent value for human health assessments. The Great Lakes
Water Quality Initiative Technical Support Document for the Procedure to Determine
Bioaccumulation Factors (USEPA, 1995) uses a 3.10 percent lipid value for trophic level 4 fish
and 1.82 percent for trophic level 3 fish in its human health assessments. For the TBP
calculation for assessing wildlife effects due to the consumption of contaminated fish, EPA has
selected a percent lipid content in whole body fish of 10.31. This value is based on USEPA
(1995), which uses a 10.31 percent lipid value for trophic level 4 fish consumed by wildlife and
6.46 percent for trophic level 3 fish.
As part of the NSI TBP evaluation, EPA also evaluated percent lipid measurements included in
the STORET database, the National Study of Chemical Residues in Fish (NSCRF) (USEPA,
1992a), and other published sources and compared these values to the values selected for the NSI
evaluation (Appendix B). The mean fillet percent lipid content for various groups of fish species
in the STORET database ranged from 0.753 to 4.49 percent. In the NSCRF, mean fillet values
ranged from 1.6 to 4.9 percent. The mean whole body percent lipid content for various groups
of fish species in the STORET database ranged from 3.8 to 6.0 percent. In the NSCRF mean
whole body values ranged from 4.6 to 8.8 percent.
If a calculated sediment chemistry TBP value exceeds the EPA risk level, the FDA action level,
or the EPA wildlife criterion, the station is classified as having a medium probability of adverse
effects. If a corresponding tissue residue level for the same chemical for a resident species also
exceeds one of those thresholds, the station is classified as having a high probability of adverse
effects. Elevated sediment chemistry levels (i.e., those exceeding TBP values) without
corresponding elevated tissue residue levels leads to a medium probability classification.
Sediment chemistry TBP values must not exceed the EPA risk levels, the FDA action levels, or
the EPA wildlife criteria to classify the station as having a low probability of adverse effects.
All samples at that station must also meet the other requirements needed to place a site in the
"low" probability of adverse effects category (i.e., parameters 9a, 9b, 13 and 16). Individual
chemical risk levels are considered independently (i.e., risks from multiple contaminants at a
single site are not added). FDA action levels, contaminant-specific fish tissue concentrations
equivalent to a cancer risk of 10"5 and a noncancer hazard quotient of unity, and EPA wildlife
criteria are presented in Appendix C.
The EPA cancer risk and noncancer hazard values presented in Appendix C were developed using
the approach described in Chapter 2 of this document. It should be noted that many chemicals
have both a slope factor and an RfD, and thus fish tissue concentrations resulting in both a cancer
risk of 10"5 and noncancer hazard of unity can be calculated for these chemicals. In these cases,
34
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MQM^vBl^T.RmUjriON
the more stringent of the two fish tissue concentrations is compared to calculated TBPs for the
contaminant. This will almost always be the cancer-risk-based concentration.
Wildlife values to be used in the evaluation of NSI data were derived using a slightly modified
version of the approach presented in Chapter 2. Wildlife criteria based on fish tissue
concentrations were derived using methods similar to those employed for deriving EPA wildlife
criteria, as presented in the proposed Great Lakes Water Quality Initiative Criteria Documents
for the Protection of Wildlife (USEPA, 1993c). EPA has proposed wildlife criteria for four
contaminants: DDT, mercury, 2,3,7,8-TCDD, and PCBs.
Proposed EPA wildlife criteria are based on surface water contaminant levels protective of
potential wildlife exposure. Thus, the proposed EPA wildlife criteria cannot be compared directly
to the NSI fish tissue concentrations (either the derived TBPs or actual fish tissue monitoring
data). Therefore, it was necessary to develop an approach for estimating wildlife criteria for fish
tissue based on the same toxicity and exposure parameter assumptions that were used to derive
the surface water wildlife criteria. First, wildlife values (i.e., fish tissue concentrations protective
of wildlife) were derived for the most sensitive mammalian species (i.e., otter and mink) and
avian species (i.e., kingfisher, osprey, and eagle)—the same species used to derive the proposed
EPA wildlife criteria. The equation used to estimate wildlife values for fish tissue is presented
below. (Exposure assumptions used for each species are presented in Great Lakes Water Quality
Initiative Criteria Documents for the Protection of Wildlife, USEPA, 1993c.)
[NOAEL x SSF] x Wt,
where:
WVpsh = wildlife value for fish tissue (mg/kg);
NOAEL = no-observed-adverse-effect level (mg/kg-day);
SSF = species sensitivity factor;
WrA = average weight of animal in kilograms (kg); and
Fa = average daily amount of food consumed (kg/day).
Secondly, the geometric mean of the wildlife values was calculated for the mammal group, as
well as for the avian group. Finally, the lower of the two geometric mean values was considered
the wildlife criterion for fish tissue for a given chemical.
It should be noted that direct ingestion of surface water was included when developing proposed
EPA wildlife criteria for surface water. This exposure route, however, was not considered when
evaluating NSI data, even though sediment contamination might result in contamination of
surface water available for wildlife consumption. A sensitivity analysis was conducted to
evaluate the impact of excluding the surface water ingestion exposure route. Based on this
analysis, ingestion of surface water contributes less than 0.0001 percent of the total exposure (i.e.,
35
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NQiP'FQR'
ingestion of fish and water). Therefore, excluding the water ingestion exposure route will have
no significant impact on the evaluation of NSI data with regard to potential wildlife impacts.
Wildlife criteria derived for DDT, mercury, 2,3,7,8-TCDD, and PCBs based on fish tissue
concentration are presented below.
Fish Tissue
Chemical Criterion (mg/kg)
DDT 1.26E-3
Mercury 1.43E-2
2,3,7,8-TCDD 7.70E-7
PCBs 2.31E-2
Evaluation of Tissue Residue Data
Tissue Levels Exceed FDA Action Levels. EPA Risk Levels, or EPA Wildlife Criteria
[10, 11, 12, 13]
Sampling stations at which human health threshold levels for dioxin and PCBs are exceeded in
resident fish species are categorized as having a high probability of adverse effects on human
health. That is, these chemicals do not require corroborating sediment chemistry data. For the
purpose of this evaluation, fish tissue concentrations of dioxin and PCBs equivalent to a 10"5
cancer risk are used as a threshold value for comparison to measured values.
Sampling stations at which tissue residue levels of any chemical in resident, demersal species
exceed FDA action levels, EPA risk levels, or EPA wildlife criteria and at which sediment
chemistry TBP values exceed those same levels are categorized as having a high probability of
adverse effects. Individual chemical risk levels are considered separately (i.e., risks from
multiple contaminants are not added). Both sediment chemistry and tissue residue samples must
be taken from the same sampling location. Appendix D presents tissue residue test species
included with NSI data. It identifies each species as demersal or pelagic and as resident or
migratory. If tissue residue levels exceed FDA action levels, EPA risk levels, or EPA wildlife
criteria but TBP values are not exceeded at the same station (or there are no sediment chemistry
data from that station), the sampling location is identified as having a medium probability of
adverse effects. If tissue levels in demersal, resident species are lower than FDA action levels,
EPA risk levels, and EPA wildlife criteria and if parameters 9a, 9b, 9c, and 16 are met, the
station is categorized as having a low probability of adverse effects. The sediment chemistry,
toxicity, and tissue residue data must all come from the same sampling location.
Evaluation of Toxicity Data [14, 15, 16]
Toxicity data will be used alone or in combination with sediment chemistry and tissue residue
data to classify sediment sites. Acute sediment (solid-phase) and elutriate nonmicrobial toxicity
tests in which the endpoint was mortality will be evaluated. Toxicity data will be screened to
36
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MQfe£QRaElISXRlBXJXIQN
determine whether control data were reported; if a test is lacking control data or the control had
greater than 20 percent mortality (less than 80 percent survival), that test will be excluded from
further consideration. A review of American Society for Testing and Materials (ASTM) and other
protocols for sediment toxicity tests collected by the API (1994) indicates that mortality in
controls can range from 10 to 30 percent, depending on the species, to have an acceptable test
result. Current amphiphod test requirements indicate that controls should have less than 10
percent mortality (API, 1994; USEPA, 1994d).
For the purpose of this evaluation, significant toxicity is indicated if there is a difference of 20
percent in survival from control survival (e.g., if control survival was 100 percent and 80 percent
or less of the test organisms survived, or if control survival was 80 percent and 60 percent or less
of test organisms survived, then significant toxicity is indicated). Although a number of different
test species and protocols have been used in the tests to be evaluated, this threshold should
provide a preliminary indication of sediment toxicity for classifying sediment sites.
Toxicity demonstrated by two or more single-species nonmicrobial acute toxicity tests (at least
one of which must be a solid-phase test) will place a site in the high probability of adverse
effects category. A sampling location will be categorized as having medium probability of
adverse effects if toxicity is demonstrated by a single-species nonmicrobial toxicity test.
If no toxicity is demonstrated in tests using at least one solid-phase test using standardized EPA
test species (i.e., freshwater = Hyalella azteca, Chironomus tentans, Chironomus riparius;
saltwater = Ampelisca abdita. Leptocheirus plumulosus, Eohaustorius estuarius, Rhepoxynius
abronius), the sampling station will be categorized as having a low probability of adverse
effects. To be classified as a site with low probability of adverse effects, parameters 9a, 9b, 9c
and 13 must also be met.
Appendix E presents the test species used for toxicity tests associated with NSI data, as well as
the type of test (e.g., elutriate or solid phase) with which each organism is typically associated.
If it is necessary, the test species will be used to identify the type of test conducted.
Aggregation of Data
Data for this approach will be analyzed at the station level. With the exception of toxicity
measurements, a single observation at a station can be used to place a site in a given category,
including the high probability of adverse effects category. When a site can be classified based
on multiple evaluation parameters and/or for multiple contaminants, the evaluation parameter or
chemical that places the site in the highest category will be used. For example, if the evaluation
of sediment chemistry data places a site in the high category for metals and AVS and in the
medium category for PCBs, the site will be placed in the high category. Correspondingly, if a
site is categorized as having a medium probability of adverse effects based on all sediment
chemistry data, but is categorized as having a high probability of adverse effects based on
toxicity data, the site will placed in the high category.
37
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The results of the NSI evaluation will be aggregated by state or other geographic region. For
each geographic region, the Report to Congress and other presentations will identify the number
of stations classified in each of the four categories.
38
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5. UNCERTAINTIES AND LIMITATIONS OF APPROACH
The approach proposed in this issue paper for the evaluation of NSI data provides a screening-
level assessment of national data. It is not intended to definitively identify all contaminated
sediment sites throughout the country. Such an assessment would require a significant amount
of site-specific data for each site being assessed. Rather, this approach is designed to identify
sites that should be considered as targets for future, more intensive study, either to justify and
recommend regulatory actions for those sites which pose an obvious risk to the aquatic
environment and/or human health or to gather additional information for those sites which appear
to be contaminated, but for which there are insufficient data to reach a definitive conclusion.
Many of the assumptions and limitations associated with this analysis were discussed in Chapter
2. Others are discussed below.
Derivation of Sediment Chemistry Threshold Levels
Only those chemicals for which sediment chemistry threshold levels (i.e., SQCs, SQBs,
ERLs/ERMs, PELs/TELs, and AETs) are available were used in the evaluation of NSI data.
However, numerous uncertainties are associated with the use of the various sediment chemistry
threshold values used to assess levels of sediment contamination. Sediment chemistry threshold
levels developed using the equilibrium partitioning approach do not address possible synergistic,
antagonistic, or additive effects of contaminants. The equilibrium partitioning approach is
designed to be used in conjunction with site-specific organic carbon fractions and water quality
criteria. However, for this study the organic carbon content of sediment at every site is not
known, and water quality criteria do not exist for a large number of the chemicals of concern.
Therefore, an organic carbon content of 1 percent was assumed for many sites. For those
chemicals without available chronic water quality criteria, acute and chronic toxicity test data for
individual aquatic species were assumed to be representative of general aquatic life toxicity.
However, sufficient water-only toxicity data do not exist for all contaminants of concern.
The effects range approaches to assessing sediment quality (i.e., ERLs/ERMs, PELs/TELs, and
AETs) do not account for such factors as organic matter content, AVS concentration, and particle
size distribution, which can mitigate bioavailability and, therefore, toxicity of contaminants in
sediment. In addition, in using these approaches possible synergistic, antagonistic, or additive
effects of contaminants may be ascribed to a single chemical.
Based on the theoretical calculations used to compute SQB values, it is possible that SQBs might
be orders of magnitude larger or smaller than the biologically based thresholds (ERLs, ERMs,
PELs, TELs, and AETs). This might be due to the lack of aquatic toxicity data needed to
develop SQB values for some of the contaminants for which water quality criteria have not been
developed, rather than a problem with the approach itself. In these instances, it has been
determined that some SQB values should not be used. The approach used to develop SQBs and
to determine for which chemicals SQBs could not be developed is presented in Appendix A.
39
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Derivation of Fish Tissue Threshold Levels
TBPs were assumed to be equivalent to levels detectable in fish tissue. However, this approach
might not account for biomagnification in the food chain. In addition, it is assumed that fish do
not migrate. Also, a conservative BSAF of 4 was used to estimate TBPs for many nonpolar
organics. This BSAF might overestimate bioaccumulation potential for certain nonpolar organics
that have less potential to bioaccumulate than PCBs. Because of these factors, actual residue
levels in fish resulting from direct and/or indirect exposure to contaminated sediment might be
higher or lower. Therefore, there is uncertainty regarding site classifications based on
comparison of estimated TBPs with FDA action levels, EPA risk levels, and wildlife criteria.
TBPs could not be derived for polar organic compounds or heavy metals. Therefore, sites could
not be classified using FDA action levels, EPA risk levels, or wildlife criteria for these chemicals
using a TBP approach (although fish tissue monitoring data might be available for certain sites).
EPA wildlife criteria have been proposed for only four chemicals: mercury, PCBs, 2,3,7,8-
TCDD, and DDT. Because fish tissue wildlife criteria used to evaluate NSI data were developed
for only these chemicals, potential impacts associated with wildlife exposure to other chemicals
were not considered in this analysis. Thus, certain sites that might have an adverse effect on
wildlife might not have been identified.
Wildlife criteria were based on potential exposure to the most sensitive mammalian species (i.e.,
otter and mink) or avian species (i.e., kingfisher, osprey, bald eagle) that ingest significant
quantities of fish. It might not be appropriate to use such criteria in many instances to evaluate
sites where such species would not occur due to a lack of appropriate prey species and/or
physical habitat.
Uncertainties and numerous conservative assumptions are associated with exposure parameters
and toxicity criteria used to derive EPA risk levels and FDA action levels. For EPA risk levels,
for example, it is assumed that an individual consumes on average 6.5 g/day of fish caught from
the same site over a 70-year period. However, individuals might not be exposed to such levels
over a lifetime. Generally, the exposure assumptions and safety factors incorporated into toxicity
criteria tend to overestimate risks to the general population associated with sediment
contamination, but may underestimate risks to sensitive subpopulations of subsistence fishers.
Quality of Data
There is a general lack of some data parameters throughout the NSI database. For example, very
few site-specific TOC data are available, and for many of the tissue data the species is not
identified. There is also a lack of matched data, which are required to place sites in the "low
probability of adverse effects" category. Also, high detection limits precluded the analysis of
some data.
The NSI data are geographically biased. Most data are fixed-station-based. As a result,
establishing the percent of waters with contaminated sediment is not possible. It is difficult to
40
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assess the geographic extent to which a site represents a larger segment of a waterbody. Also,
if Puget Sound has 20 sites identified as having a "high probability of adverse effects" and New
Jersey Harbor has only 2, does that make Puget Sound 10 times more contaminated? It should
also be noted that latitudes and longitudes for sites were not verified.
Other Limitations
This analysis does not include a temporal assessment of data. For example, sampling data from
the late 1980s might indicate that a site has a "high probability of adverse effects." However,
remediation/dredging or siltation since that time might have resulted in much lower current
sediment contaminant concentrations. In addition, there is currently no highly reliable way to
determine causality with point source or with historical or nonpoint sources. Finally, data
included in the NSI were developed from studies with different purposes. For example, the
purpose of some studies might have been to identify "hot spots," whereas the purpose of others
is to identify the status and trends of sediment quality.
41
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N©$=£©f^©kS=miBMG N
Appendix A
Derivation of Sediment Quality Benchmarks Using the
Equilibrium Partitioning Approach
A.l Introduction
The derivation of sediment quality benchmarks using the equilibrium partitioning approach
(USEPA, 1993) was described in Section 2. This appendix describes in detail the approach and
the sources of data used to calculate the values used in the sediment quality benchmark
equations: log Kows and chronic threshold water concentrations.
Sediment quality benchmarks for the NSI were developed in conjunction with other programs at
EPA (established under the Resource Conservation and Recovery Act, RCRA, and the Superfund
Amendments and Authorization Act, SARA) to provide the same values for conducting
screening-level evaluations of sediment toxicity for these programs. EPA's Office of Research
and Development (ORD), including staff from Environmental Research Laboratory, Athens, GA;
Environmental Research Laboratory, Duluth, MN; and Environmental Research Laboratory,
Narragansett, RI, provided guidance and assisted in the development of the necessary values.
Table A-l at the end of this appendix provides information on the nonionic organic chemicals
that will be evaluated in the NSI, as determined by ORD. Information that was used to exclude
certain chemicals from consideration for the sediment chemistry toxicity screen included the
number of positive results (those sample measurements for which chemical concentrations were
obtained that were greater than the detection limit). If the number of positive results was less
than 20, then that chemical was eliminated. If the new log Kow value (recommended by
EPA/ORD-Athens) was less than 2.0 or greater than 5.5, that chemical was also eliminated from
development of an equilibrium partitioning-based benchmark because the equilibrium partitioning
model has not been tested for chemicals outside the range of log Kow = 3.8 to 5.3 (Dave Hansen,
EPA/ORD-Narragansett, pers. comm. April 17, 1995). Other chemicals were excluded during
a preliminary discussion with ORD representatives. Chemicals that were not excluded were then
examined to determine whether the log Kow and chronic threshold water concentration could be
obtained. The "Status/Issues" column of Table A-l explains the outcome of work performed
to determine whether a benchmark could be developed or the benchmark value obtained.
Benchmarks for a number of chemicals are still in preparation.
A.2 Method for Determination of Log Kows
Log KoW values can be experimentally determined only for an individual chemical, not a mixture
(USEPA, 1994). A log Kow value can be assigned to a mixture by one of several methods: assign
the value for a major component, or assign the arithmetic average of log Kow values for several
major components or the geometric mean of Kow values.
A-l
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A.2.1 Sources of Data for Chemicals
Log Kow values were initially identified in summary texts on physical-chemical properties, such
as Mackay et al. (1992) and Howard (1990), and accompanying volumes. Additional compendia
of log Kow values were also evaluated, including Stephan (1993), Isnard and Lambert (1989),
Noble (1993), De Kock and Lord (1987), De Bruijn et al. (1989), Klein et al. (1988), Doucette
and Andren (1988), and Leo (1993). To supplement these sources, on-line database searches
were conducted in ChemFate, TOXLINE, and Hazardous Substances Data Bank (HSDB)
(National Library of Medicine); Internet databases such as CARL UNCOVER; and EPA
databases such as ASTER, OLS, and the ORD BBS. Original references were identified for the
values, and additional values were 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. Values identified from all of these
sources and the method used to obtain each log Kow value were compiled for each chemical. A
few chemicals lacked experimentally measured log Kows, and no log Kow data were available from
any source for butachlor, DCPA/Dacthal, and Ethion/Bladen.
A.2.2 Evaluation of Log Data
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 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
considered to be outliers and were not used in the calculation.
A.2.3 Selection of Recommended Log Kows
For each chemical, the available value based on one of these 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 (USEPA, 1994). Recommended log Kows were finalized by ORD-Athens based
on recommended criteria, and the justification for selection of each value was included in the
report (Karickhoff and Long, 1995).
A.3 Hierarchy for Selection of Chronic Toxicity Values
A hierarchy of sources for chronic toxicity values to develop the sediment quality benchmarks
was prepared. The following sources were identified and ranked from most to least confidence
in the chronic values to be used:
1. Sediment quality criteria.
2. Final chronic values from the Great Lakes Initiative (GLI, 1995).
3. Final chronic values from the National Ambient Water Quality Criteria documents.
A-2
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?40^peR"MST-RmTifrroN
4. Final chronic values from draft freshwater criteria documents.
5. Final chronic values developed from data in AQUIRE and other sources.
6a. Secondary chronic values developed from data in AQUIRE and other sources.
6b. Secondary chronic values from Suter and Mabrey (1994)
As noted in Chapter 2, EPA draft sediment quality criteria were available for five chemicals:
acenapthene, dieldrin, endrin, fluoranthene, and phenanthrene. There were no final chronic values
(FCVs) obtained by the aquatic life criteria methodology (referred to as "Tier I") described in
GLI (1995) available for the remaining chemicals in the NSI. Two sediment quality benchmark
values were based on the FCVs from National Ambient Water Quality Criteria documents, for
gamma-BHC/Lindane and toxaphene. No FCVs were available from draft criteria documents.
Thirteen sediment quality benchmark values were based on work conducted by Oak Ridge
National Laboratories (Suter and Mabrey 1994) using the GLI (1995) methodology for obtaining
secondary chronic values ("Tier II"). This methodology was developed to obtain whole-effluent
toxicity screening values based on all available data, but the SCVs could also be calculated with
fewer toxicity data than are required for the criteria methodology. The SCVs are generally more
conservative than those which can be produced by the FCV methodology, reflecting greater
uncertainty in the absence of additional toxicity data. The minimum requirement for deriving
an SCV is toxicity data from a single taxonomic family (Daphnidae), provided the data are
acceptable. Only those values from Suter and Mabrey (1994) which included at least one
daphnid test result in the calculation of the SCV were included for the NSI. SCVs from Suter
and Mabrey (1994) were used to develop sediment quality benchmarks for the following
chemicals:
benzene
BHC, delta-
chlorobenzene
dibenzofuran
diethyl phthalate
di-n-butyl phthalate
ethylbenzene
napthalene
tetrachloroethane, 1,1,2,2-
tetrachloroethene
toluene
trichloroethane, 1,1,1-
trichloroethene
A-3
-------
A.4 Method for Derivation of New Final Chronic Values and Secondary Chronic Values
A preliminary search of data records in EPA's Aquatic Toxicity Information Retrieval database
(AQUIRE) indicated that the following chemicals might have sufficient toxicity data for the
development of SCVs:
biphenyl
bromophenyl phenyl ether, 4-
butyl benzyl phthalate
diazinon
dichlorobenzene, 1,2-
dichlorobenzene, 1,3-
dichlorobenzene, 1,4-
endosulfan mixed isomers
endosulfan, alpha-
endosulfan, beta-
fluorene
hexachlorethane
maJathion
methoxychlor
pentachlorobenzene
tetrachloromethane
tribromomethane
trichlorobenzene, 1,2,4-
trichloromethane
xylene, m-
Insufficient toxicity test data were found in AQUIRE for acenapthylene, endosulfan sulfate,
heptachlor epoxide, and trichlorofluoromethane. In addition, review of AQUIRE data records
indicated that no daphnid acute toxicity tests had been conducted for hexachlorobutadiene. These
chemicals were dropped from further development of sediment quality benchmarks.
A.4.1 Sources of Literature Values
Because of various constraints,
1. The only acute toxicity data used were for freshwater species, whereas acute-chronic
ratios for both freshwater (FW) and saltwater (SW) species were used.
2. Only the following were used as sources of references:
a. AQUIRE
A-4
-------
MQ^P@fe-a.I-S^R.TRI JTION
b. Tables in existing documents from EPA's Office of Research and Development,
Environmental Research Laboratory, Duluth, Minnesota.
The initial search of AQUIRE records was based on the strategy: Media = FW, Site = Lab, Dc
(AQUIRE documentation code) = 1 or 2 (only 1 and 2 were used for convenience because of
various contraints), Endpt = a reported endpoint, not left blank. All test results found using this
procedure were printed and reviewed manually using a list of reasons to reject test results based
on the information that was provided by AQUIRE.
For each test result not rejected, a copy of the original paper was obtained from the AQUIRE
archives. Tables in existing documents from ORD-Duluth were also examined if applicable, and
copies of pertinent references were obtained.
A.4.2 Review of Original Papers
A data rejection checklist covering the content of the report, test chambers, test material, test
organisms, controls, dilution water, and test conditions was used to review the acceptability of
results of aquatic toxicity tests on nonionic organic chemicals for use in conjunction with the
NSI. This checklist was used to review the acceptability of all test results, regardless of whether
the reference was obtained from AQUIRE and passed the review of records from AQUIRE or
was obtained from another source. This review was performed using the original publication and
sources of supplemental information.
This review covered both the quality of the test result and whether it was the kind of result that
was specified for use in this process. A test result that was deemed unacceptable for use in this
project might be acceptable for another use. A result that was deemed unacceptable is not
necessarily an incorrect result; it might just be too questionable to use. For example, an LC50
obtained using an unacceptable methodology might be the same as an LC50 obtained using an
acceptable methodology. The LC50 from the test using the unacceptable methodology, however,
was unacceptable for use here 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., 24-hr LC50) might be unacceptable whereas another (e.g., a 48-hr LC50) might be
acceptable.
A test result was assumed acceptable if the test was conducted at an EPA Environmental
Research Laboratory (ERL) in Corvallis, Duluth, Gulf Breeze, or Narragansett; was conducted
at the U.S. Fish and Wildlife Service laboratory in La Crosse, Wisconsin; was contained in
Mayer and Ellersieck (1986); was conducted at the U.S. Department of the Interior laboratory
in Columbia, Missouri, after the period covered by the report published by Mayer and Ellersieck
(1986); or was contained in the University of Wisconsin Superior data summary volumes
(Brooke et al., 1984; Geiger et al., 1985, 1986, 1988, 1990). Most results from these sources
were obtained using acceptable methods. The reports usually contain information concerning
A-5
-------
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.
A test result was considered provisionally acceptable if it was reported that the test was
conducted according to procedures described by such ASTM standards as:
• ASTM Standard E 729, Guide for Conducting Acute Toxicity Tests with Fishes,
Macroinvertebrates, and Amphibians
• 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, European Economic Commission (EEC),
International Standards Organization (ISO), or Organization for Economic Cooperation and
Development (OECD), and if the description of the methodology at least mentioned such things
as acclimation, temperature control, controls, solvent (if any), solvent control (if used), source
of water, randomization, and duplication. Results in this category were rejected only if a major
problem was known to exist.
Other test results were in a third category. Whether they were accepted or rejected depended
entirely on the information available concerning the methodology and results. The result was
rejected if very little information was available, if there was a major problem, or if there were
several minor problems.
This review process required many judgments, starting with decisions about what items to include
on the data rejection checklist 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 use of surfactants, test results from the
sources listed in the first category above were given the benefit of the doubt, but it was a mark
against other test results. If a test result had three or more marks against it, it was usually
rejected.
Based on this review, no acceptable papers were found for 2-methylnapthalene and pyrene.
These chemicals were not considered further.
A-6
-------
A.4.3 Compilation of Data
Acceptable freshwater acute test results from the original papers were compiled for each chemical
and entered into a table, similar to Table 1 of the National Ambient Water Quality Criteria
Documents. The species mean acute value (SMAV) was derived as described in USEPA (1985)
and also entered into this table. If the available data indicated that one or more life stages were
at least a factor of two more resistant than one or more other life stages of the same species, the
data for the more resistant life stages were not used in the calculation of the SMAV because a
species can be considered protected from acute toxicity only if all life stages are protected. 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 an 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 were not used in calculations.
Acceptable freshwater and saltwater chronic test results, as described in USEPA (1985), were
entered in taxonomic order in a table. Chronic values were obtained 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) which 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) which 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 (USEPA, 1985).
Acceptable freshwater and saltwater acute-chronic ratios and the test results on which they were
based were entered in taxonomic order in a table. For each chronic value for which at least one
corresponding appropriate acute value was available, an acute-chronic ratio was calculated, using
for the numerator the geometric mean of the results of all acceptable flow-through (except static
is acceptable for daphnids) acute tests in the same dilution water and in which the concentrations
were measured. For fish, acute test(s) that had been conducted with juveniles and were part of
the same study as the chronic test were used if available. If the acute test had not been conducted
as part of the same study, an acute test 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 acute-chronic ratio was not calculated. If chronic test data for a life-cycle or
partial life-cycle test were available for a species, these data were used instead of data from an
early life-stage test for the same species (USEPA, 1985).
A-7
-------
fcFPieN
A.4.4 Calculation of Acute and Chronic Values
To derive a freshwater final acute value (FAV), 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 of any phylum not already represented.
If all eight of the acute freshwater minimum data requirements (MDRs) were not satisfied, a
freshwater secondary acute value (SAV) was calculated. If all eight of the MDRs were satisfied,
on FAV was calculated using the computer program given on page 98 of the USEPA (1985). 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.
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 genus mean acute value (GMAV) and the
secondary acute factor (SAF) corresponding to the number of minimum data requirements that
were satisfied:
SAV~ l°west GMAV
SAF
A-8
-------
N^F&R^ISM&UXION^
The secondary acute factors were (GLI, 1995):
Number of MDRs
Satisfied
SAP
7
6
5
4
3
2
4.3
5.2
6.1
7.0
8.0
13.0
21.9
If the necessary data were available (see page 40, USEPA, 1985), the FCV was calculated
using the.computer program used to calculate the FAV (USEPA, 1985). If the data were not
available to allow use of the computer program, a final acute-chronic ratio (FACR) was
calculated if acceptable acute-chronic ratios were available for at least one species of aquatic
animal in at least three different families (see page 24, USEPA, 1985). If the MDRs for
calculation of a FACR were satisfied, the FACR was obtained in one of four ways, depending
on the data available (USEPA, 1985).
If the available species mean acute-chronic ratios (SMACRs) did not fit one of the four cases,
a FACR could not be obtained and a secondary acute-chronic ratio (SACR) was derived if
possible. If insufficient ACRs were available to meet the minimum requirements for
derivation of a 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).
Either an FCV or an SCV was calculated, as appropriate:
A-9
-------
NeTTPfTEffSTRffitiaQN
scv=-SAV
FACR
scv=-SAV
SACR
A.4.5 Calculation of Sediment Quality Benchmarks
The sediment quality benchmark for the NSI was calculated according to the following
equations:
SQB-(FCV or SCV)HKX).(W3 kgjgj
where:
FCV or SCV was in (ag/L;
SQB0C was in |ug/goc; and
was in L/kgoc = lOlogKoc and log Koc = 0.00028 + 0.983 (log K^).
In addition, for the NSI, an SQB was calculated:
SQB=(SQBJ(f0C)
where:
SQB applies to a particular sediment;
SQB0C is generic for the chemical; and
foc is the fraction organic carbon in the particular sediment.
If foc was not known for a sediment sample, it was assumed to be 0.01 goc/g dry weight sediment.
A-10
-------
rNHT nnnBBtS^P'«"Tir>jM
Tabic A-l. Summary of Information for Sediment Chemistry Toxicity Screening for the
National Sediment Inventory, Revised 6/1/95
The "Chemical Information" columns contain the class of compound, CAS number, and name of nonpolar organic chemicals to be evaluated in the NSI, as determined by ORD
"Record Order" is an internal tracking system number.
The next three columns contain information that was used to exclude certain chemicals from consideration for the sediment chemistry toxicity screen. The number of positive
results includes those sample measurements for which chemicul concentrations were obtained that were greater than the detection limit. If the number of positive results was less
than 20, then that chemical was eliminated. If the log Kow value (recommended by CPA/ORD-Athens) was less than 2.0 or greater than 5.5, that chemical was eliminated from
development of an equilibrium partitioning-based benchmark (equilibrium partitioning model not tested for chemicals outside the range of log K0„ = 3.8 to 5.3 (Dave Hansen,
EPA/ORD-Narragansett, pers. comm.)). A "Dec. Code" (decision code, listed below) was given to certain chemicals during a preliminary discussion with ORD representatives,
which excluded chemicals from further development of an equilibrium partitioning-based screening benchmark.
The last three columns contain information for determining the type of equilibrium partitioning based benchmark to be used in screening the sediment chemistry data for those
chemicals which were not previously eliminated. "Data Source Code" is taken from the hierarchy of data sources for calculating benchmarks. "Data Source for:" column describes
the derivation of the chronic threshold water concentration used to calculate the equilibrium partitioning-based benchmark. "Status/Issues" column explains the outcome of work
performed to determine whether a benchmark could be developed, or the benchmark value obtained. (N,R) = NSI and RCRA; (N,R,S) = NSI, RCRA, and Supcrfund, all need
same SQB.
The "Chemical Subject to Evaluation" column is checked if an SQB is available for a chemical
Decision (Dec ) Codes (from ORD conference call, first screen for chemicals of potential concern using old log K„„, values and information from the Source Inventory):
4 = Log K„w value less than 2
6 = Log Kow value exceeds 5.5
7 = Compound name represents a group of chemicals whose properties may or may not be similar
9 = Kow and/or toxicity data probably unavailable
10 = equilibrium partitioning value will not be used in the evaluation of NSI data, on recommendation of ORD
11 = equilibrium partitioning value was based on QSAR and may not be accurate
12 - equilibrium partitioning value will not be used in the evaluation of NSI data; there were <20 positive results (sample measurements that were less thans or nondctccts)
for this chemical in the NSI database
NEW Lou K Codes (second screen for chemicals of potential concern):
R = Recommended by EPA/ORD-Athcns; usually derived from measured values
C = CLOGP derivation
5 = SPARC model derivation
? = Wailing for final recommendation of Log K<,w from EPA
A-l 1
-------
not fop ni^TPinuTimi
Table A-l. Summary of Information for Sediment Chemistry Toxicity Screening for the
National Sediment Inventory, Revised 6/1/95
Chemical Subject to Evaluation Codes:
= Not interested in evaluating for NSI
X-K = Need Log K„„
X-T = Need FCV or SCV
* = Cannot calculate SQB (>2() positive
** = Cannot calculate SQB (>20 positive
y = SQB calculated
Data Source Codes:
1 = EPA Sediment Quality Criterion (SQC)
2 = Great Lakes Initiative (GL1) Tier I final chronic value (FCV) for chronic threshold water concentration to derive sediment quality benchmark (SQB)
3 = National Ambient Water Quality Criteria (NAWQC) FCV to derive SQB
4 = Draft NAWQC FCV to derive SQB
5 = Tier I methodology and AQU1RE data for development of FCV to derive SQB
6a = Tier II methodology and AQUIRE data for development of secondary chronic value (SCV) to derive SQB
6b = Oak Ridge National Laboratories SCV based on GLl Tier II methodology to denve SQB (Suter and Mabry, 1994)
(<20 positive results, new log Kow less than 2 0 or greater than 5.5)
results, 5.5 > log Kow < 2.0, but insufficient toxicity data)
results, but no log Kow data)
A-12
-------
Table A-l. Summary of Information for Sediment Chemistry Toxicity Screening for the
National Sediment Inventory, Revised 6/1/95
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
or
Positive
Results
Log K„„
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
1
PAH
83329
Acenaphthcnc
2053
3.92
R
1
EPA-SQC
(N,R)
SQCX =
ISOpg/g^
2
PAH
208968
Accnaphthylcnc
1679
3 95
S
7
11
0 screened
toxicity data
records in
AQUIRE
Insu ITicicnt
toxicity data
in AQUIRE
so cannot
calculate
SQB
*
3
Other
67641
Acetone
95
-0.24
R
4
-
4
98862
Acctophenonc
1
1.64
R
4,11,12
-
5
Pesticide
107028
Acrolein
15
-0.01
R
4,12
-
A-13
-------
NOTaEQfigfilil STO1 .BUffH#!
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log K„w
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
6
Contains
N,S, or P
107131
Acryloniirile
22
0.25
R
4
-
7
Pesticide
15972608
Alachlor / Lasso
2
12
-
9
Pesticide
309002
Aldrin
716
6.50
R
(N,R,S)
Log K„w >
5 5,
equilibrium
partitioning
not
appropriate
15
PAH
120127
Anthracene
1988
4.55
R
6b
ORNL-Tier 11
SCV
Did not use
a daphmd
test so will
not use this
SCV to
derive an
SQB
A-14
-------
'NQ^EQR-DISTRIRIITION
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
+*~ ~+
Chemical
Subject
to
Evalua-
tion
*****
21
Other
71432
Benzene
200
2.13
R
6b
ORNL-Ticr II
SCV
= 45.5 ng/L
(N,R,S)
SQB„ =
5.7ng/g«
~
24
Other
106514
Bcnzoquinone, p-
0
4, 12
-
25
Halogenated
98077
Bcnzoinchloridc
-1
12
-
26
PAH
56553
Benzo(a)anlhracene
4000
5.70
R
(N,R,S)
Log Kow >
5.5,
equilibrium
partitioning
not
appropriate
A-15
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log K„„
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
27
PAH
50328
Benzo(a)pyrcne
4017
6.11
R
(N,R,S)
-
Log >
5 5,
ci|uilibriu m
partitioning
not
appropriate
28
PAH
205992
Bcnzo(b)fluoranthcne
1529
6.20
R
(N,R,S)
Log K,„ >
5.5,
equilibrium
partitioning
not
appropriate
A-16
-------
5 5,
equilibrium
partitioning
not
appropriate
30
PAH
207089
Bcnzo(k)fluoranthcne
131 1
6 20
R
Log >
5 5,
equilibrium
partitioning
not
appropriale
31
Halogcnatcd
100447
Benzyl chloride
(alpha-chlorotoluenc)
-1
2.30
R
12
-
32
Halogenated
25168052
Chloromethylbcnzene
-1
9, 12
-
33
Pesticide
319846
BHC, alpha-
(HCH, alpha-)
243
3.80
R
10
fr,
-
A-17
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
or
Positive
Results
Log Kow
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
**»«»
Chemical
Subject
to
Evalua-
tion
*****
34
Pesticide
319857
BHC, beta-
(HCH, beta-)
276
3.81
R
10
-
35
Pesticide
319868
BHC, delta-
128
No log K11W
data-use
arith. mean
of alpha,
beta, gamma
= 3 78
(ORD-
Dululh)
6b
ORNL-Tier II
SCV
= 2.44 (jg/L
|BHC (other)|
SOB,, =
~
36
Pesticide
58899
BHC, gamma- / Lindane
(HCH, gamma-)
1085
3 73
R
2
3
GLl-Tier 1
could not
calculate FCV
NAWQC
FCV = 0.08
Mg/L
(N,R)
SQB„ =
0.37Mg/gw
~
A-18
-------
reSTTPR- DISTRIBUTION
Tabic A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
L°S K„.
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
37
Pesticide
608731
BHC, technical grade
167
No log Kow
data
10
38
PAH
92524
Biphcnyl
951
3.95
S
7
new data
not QA'd yet
5 or
6a
14 screened
data records
in AQUIRE
SQB^ =
To Be Done
X-K
X-T
40
Halogenated
111911
Bis(2-chloroethoxy)
methane
-1
9, 12
-
41
Halogenated
111444
Bis(2-chloroethyl) ether
3
1.21
R
4, 12
-
42
Halogenated
108601
Bis(2-chloroisopropyl)
ether
0
2 58
R
4,11,
12
-
43
Other
117817
Bis(2-ethylhexyl)
phthalate
(Dicthylhcxyl phthalate)
2835
7.30
R
6,10
(N,R,S)
-
A-19
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log Kow
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Conccntratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
**+»*
Chemical
Subject
to
Evalua-
tion
*****
44
Halogcnated
542881
Bis(chloromethyl)ethcr
-1
4,12
-
45
35400432
Bolstar / Sulprofos
0
12
-
47
Halogenatcd
75274
Bromodichloromethane
10
2.10
R
11,12
-
48
Halogcnated
74839
Bromomcthane
4
4,12
-
49
Halogcnated
101553
Bromophenyl phenyl
ether, 4-
21
5.00
R
6a
2 screened
data records
in AQUIRE
To Be Done
X-T
51
Pesticide
23184669
Butachlor
43
No log Kow
data
No log Kow
data so
cannot
calculate
SQB
++
52
123864
Butyl acetate, n-
0
4,12
A-20
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log Kow
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
53
Other
85687
Butyl benzyl phihalaie
546
4.84
R
5 or
6a
19 screened
data records
in AQUIRE
(N,R,S)
sqb,k =
To Be Done
X-T
59
786196
Carbophcnolhion /
Tnthion
16
12
-
62
Pesticide
57749
Chlordane
2258
6.32
R
(N,R,S)
log >
5.5 so
equilibrium
partitioning
not
appropriate
63
1067
Chlorinated naphthalene,
NOS
-1
7,9,
11,12
-
A-21
-------
"WUT'WK. Drem*8feaaaM
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log Kow
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
csili-iil'.itc
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
~ ****
Chemical
Subject
to
Evalua-
tion
*****
64
Halogenated
108907
Chlorobenzene
80
2.86
R
6b
ORNL-Tier 11
SCV
= 127 (Jg/L
SQB^ =
H2Mg/gc,
~
66
Halogcnaicd
74975
Chlorobromomethanc
0
4,11,12
-
67
Halogenated
75003
Chlorocthane
2
4,11,12
-
68
Halogenated
75014
Chloroethene
4
1.50
R
4,11,12
"
69
Halogenated
110758
Chloroethylvinyl ether,
2-
3
4,11,12
70
Halogenated
74873
Chloromeihane
14
4,11,12
-
72
PAH
91587
Chloronaphthalene, 2-
9
1 1,12
-
74
Halogenated
7005723
Chlorophenylphenyl
ether, 4-
10
4.95
R
11,12
A-22
-------
N,rvr
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log K„.
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
75
Pesticide
2921882
Chlorpyrifos / Dursban
5
5.26
R
12
-
78
PAH
218019
Chryscnc
4380
5.70
R
11
(N,R)
Log >
5 5 so
equilibrium
partitioning
not
appropriate
87
Other
98828
Cumcne
(Isopropyl benzene)
0
3 58
R
12
-
90
Other
110827
Cyclohexane
0
11,12
-
A-23
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log Kow
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
92
Pesticide
1861321
DCPA/Dacthal
76
No log Kow
data
No log K01l
data so
cannot
calculate
SQB
**
93
Pesticide
72548
DDD
4706
6.10
R
log Kow >
5 5 so
equilibrium
partitioning
not
appropriate
94
Pesticide
72559
DDE
6310
6.76
R
10
log Kow >
5.5 so
equilibrium
partitioning
not
appropriate
A-24
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log K0„
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
95
Pesticide
50293
DDT
3471
6.53
R
(N,R)
log Kow >
5.5 so
equilibrium
partitioning
not
appropi lale
96
Pesticide
1163195
Dccabromodiphenyl
oxide
-1
6,11,12
-
98
78488
DEF
-1
9,12
-
A-25
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
***»»
SCV) to
Chemical
calculate
Subject
Number
equilibrium
to
of
Data
partitioning
Evalua-
Record
Positive
Dec.
Source
Benchmark
Status/
tion
Order
CLASS
CAS
Chemical Name
Results
Log K0„
Codes
Code
(SQB)
Issues
*~»**
101
Pesticide
333415
Diazinon / Spcctracide
275
4 30
S
•>
log Kow data
not QA'd yet
5 or 6a
Draft WQC
document
(9/2/89): not
enough data,
AJC ratios
wide range,
ORD work
and review
needed to
calculate
FCV; 232
screened data
records in
AQUIRE
SQBX =
To Be Done
X-K
X-T
A-26
-------
Tabic A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log Kolr
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
102
Other
132649
Dibcnzofuran
764
4.10
S
7
log
Kow data not
QA'd yet
6b
ORNL-Ticr 11
SCV
SQB,* =
To Be Done
X-K
= 20.4 pg/L
103
PAH
53703
Dibcnzo(a,h)anihracenc
3459
6.69
R
11
(N,R)
-
log Kow >
5 5 so
equilibrium
partitioning
not
appropriate
104
96128
Dibromo-3-chloro-
propanc, 1,2-
0
2.34
R
11,12
-
105
Halogenated
124481
Dibromochloromeihane
(Chlorodibromomethane)
18
2.17
R
11,12
-
A-27
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log K„„
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
108
Halogenated
25321226
Dichlorobenzencs
13
7,12
-
109
Halogenated
95501
Dichlorobcnzenc, 1,2-
155
3 43
R
5 or 6a
38 screened
data records
in AQUIRE
SQB^. =
To Be Done
X-T
110
Halogenated
541731
Dichlorobenzenc, 1,3-
162
log
Kow data not
QA'd yct-
usc arith.
mean
of 1,2- and
1,4- = 3.43
(ORD-
Duluth)
5 or 6a
23 screened
daia records
in AQUIRE
SQBX =
To Be Done
X-T
111
Halogenated
106467
Dichlorobenzene, 1,4-
366
3 42
R
5 or 6a
55 screened
data records
in AQUIRE
SQB^
To Be Done
X-T
A-28
-------
r^grTOR=&t«TRiBUTiaN»
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log K0„
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (hCV or
SCV) lo
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
113
Halogcnatcd
75718
Dichlorodifluoro-
mcthanc
0
2.16
R
11,12
-
114
Halogcnatcd
75343
Dichlorocthane, 1,1-
26
1 79
R
4,11
-
115
Halogcnatcd
107062
Dichloroclhanc, 1,2-
29
1.47
R
4
-
16
Halogcnatcd
75354
Dichlorocthcnc, 1,1-
(Dichlorocthylcnc, 1,1-)
11
2.13
R
11,12
-
117
Halogcnatcd
156605
Dichlorocthcnc,
trans-1,2-
(Dichlorocthylcnc,
trans-1,2-)
34
2.07
R
6b
ORNL-Ticr II
SCV
(N,R,S)
Did not use
a daphnid
test so will
not use this
SCV to
derive an
SQB
*
A-29
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Conccntratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*»*~*
Chemical
Subject
to
Evalua-
tion
118
156592
Dichlorocthylenc,
cis-1,2-
(Dichloroethenc,
cis-1,2-)
0
1.86
R
4,11,12
"
119
Halogenated
75092
Dichloromethane
(Methylene chloride)
900
1.25
R
4
-
122
Hulogcnalcd
78875
Dichloropropane, 1,2-
36
1.97
R
log Kow <2,
equilibrium
partitioning
not
appropriate
123
Halogenated
5635442
Dichloropropene, 1,2-
-1
9,12
-
124
Halogenated
542756
Dichloropropenc, 1,3-
11
2.00
R
4,12
-
126
Halogenated
10061015
Dichloropropene,
cis-1,3-
2
4,12
~
-
A-30
-------
-"MOXJaQRaBJ fi Tft143 U.T.I Qfei
Table A-l. Continued
Chemical Inrormation
Exclusion Considerations
Screening Benchmark Inrormation
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log K0„
Dec.
Codes
Data
Source
Code
Data Source
Tor: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*»*»*
Chemical
Subject
to
Evalua-
tion
127
Halogcnated
10061026
Dichloropropcnc,
trans-1,3-
1
4,12
-
129
Pesticide
62737
Dichlorvos
0
4,12
-
131
Pesticide
60571
Dieldrin
3241
5 37
R
1
EPA-SQC
SQC at 1 %
OC)
(N,R)
SQCX =
"Mg^oc
~
132
Other
84662
Diethyl phthalatc
511
2.50
R
6b
ORNL-Tier II
SCV
= 220 pg/L
(N,R,S)
SQEL. =
63pg/goc
~
135
PAH
28804888
Dimethyl naphthalene
-1
9,12
-
136
Other
131113
Dimethyl phthalatc
304
1.57
R
4
A-31
-------
-^^re^F©RaE)!^PR:tgBBFTie^
Tabic A-l. Continued
Chemical Information
Exclusion Considerations
Screening; Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log K0„
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
139
Other
84742
Di-n-butyl phthalate
1411
4 61
R
6b
ORNL-Ticr II
SCV
= 32 7 ng/L
SQBoc =
HlOHB/goc
y
147
Other
117840
Di-n-octyl phthalate
743
8.06
R
(N,R,S)
log K,„ >
5 5 so
equilibrium
partitioning
not
appropriate
149
78342
Dioxathion
0
12
-
151
298044
Disulfoton
0
12
-
A-32
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log Kow
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
152
Pesticide
115297
Endosulfan mixed
isomers
81
4 10
R
5 or
6a
506 screened
data records
in AQUIRE
(N,R,S)
SQB^
To Be Done
X-T
153
Pesticide
1031078
Endosulfan sulfate
96
3.25
S
?
0 screened
data records
in AQUIRE
Cannot
calculate
SQB since
insufficient
toxicity data
available
*
154
Pesticide
959988
Endosulfan, alpha-
92
3 83
R
5 or
6a
[AWQC FCV
was same as
for
endosulfanl
Use same
SCV as for
endosulfan
mixed
isomers
sqbm =
To Be Done
X-T
A-33
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log K0„
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Conccntrutio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
155
Pesticide
33213659
Endosulfan, beta-
273
4.52
R
5 or
6a
| AWQC FCV
was same as
for
endosulfan)
Use same
SCV as for
endosulfan
mixed
isomers
SQB^. =
To Be Done
X-T
156
Pesticide
72208
Endrin
327
5.06
R
1
EPA-SQC
(SQB =
SQC at 1%
OC)
(N,R)
SQC„ =
4-2|Jg/goc
/
157
7421934
Endrin aldehyde
37
4.00
R
10
-
158
Halogenated
76131
Ethane,
1,1,2-trichIoro-1,2,2-
-1
11,12
-
A-34
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log Kow
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
160
563122
Ethion / Bladan
43
No log K„w
data
No log Kow
data so
cannot
calculate
SQB
**
161
13194484
Ethoprophos
-1
9,12
-
162
141786
Eihyl aceiatc
0
0.69
R
4,12
-
163
Other
100414
Ethylbenzene
137
3.14
R
6b
ORNL-Ticr 11
SCV
= 389 ng/L
(N,R,S)
SQB^
475 ng/goc
~
164
Halogenaicd
106934
Ethylene dibromidc
(Ethyl dibromidc)
0
11,12
-
165
115902
Fensulfothion / Dcsanit
0
12
-
A-35
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log K„»
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
166
55389
Fcnthion / Baylex
0
12
-
167
PAH
206440
Fluoranthene
5501
,5.12
R
1
EPA-SQC
(SQB =
SQC at 1 %
OC)
(N,R)
sQC„c =
620|jg/g„.
S
168
PAH
86737
Fluorenc
2905
4.21
R
5 or
6a
13 screened
data records
in AQUIRE
SQBX =
To Be Done
X-T
170
Pesticide
944229
Fonofos
0
12
-
A-36
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log K„„
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
173
Pesticide
76448
Heptaehlor
732
6.26
R
(N,R,S)
-
log K,m >
5 5 so
equilibrium
partitioning
not
appropriate
174
Pesticide
1024573
Heptachlor epoxide
1018
500
R
RTI reported
dataset
insufficient
(N,R,S)
Cannot
calculate
SQG since
insufficient
toxicity data
*
A-37
-------
lf®ife&QR JDISIRlBXmO&J
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log Kow
Dec.
Codes
Data
Source
Code
- Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
175
Halogenated
118741
Hexachlorobenzene
1537
5 89
R
WQC Draft
Documcni-no
toxicity
observed at
levels soluble
in water
log >
5 5 so
equilibrium
partitioning
not
appropriate
176
Halogcnalcd
87683
Hcxachlorobutadiene
(Hcxachloro-1,3-
butadienc)
163
4.81
R
5 or
6a
20 screened
data records
in AQUIRE
No
acceptable
daphnid test
results
available so
will not
calculate
SQB
*
177
Halogenatcd
77474
Hexachlorocyclopenta-
diene
-1
5.39
R
12
-
A-38
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log K„
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
178
Halogcnatcd
67721
Hexachloroclhane
25
4.00
R
5 or
6a
67 screened
daia records
in AQUIRE
SQB^ =
To Be Done
X-T
180
51235042
Hexazinone
0
4,12
-
182
PAH
193395
Indeno( 1,2,3-cd)pyrene
2380
6 65
R
11
(N,R,S)
log K,m >
5.5 so
equilibrium
partitioning
not
appropriaie
185
Other
78591
Isophorone
56
1.70
R
4
-
188
Olhcr
120581
Isosafrole
0
11,12
-
A-39
-------
wQ5rsF9RBEnrrrTm rnnni
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log K0„
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
»~»»*
Chemical
Subject
to
Evalua-
tion
*****
192
Pesticide
121755
Malathion
54
3.20
S
?
log Kow daia
not QA'd yet
5 or 6a
WQC Draft
document not
complete,
need more
testing to
meet
minimum
database, A/C
tests needed;
645 screened
data records
in AQUIRE
SQEL. =
To Be Done
X-K
X-T
197
Pesticide
72435
Mcthoxychlor
180
5.08
R
5 or 6a
190 screened
data records
in AQUIRE
(N,R)
SQB,, =
To Be Done
X-T
199
Other
78933
Methyl ethyl ketone
35
0.28
R
4,11
-
A-40
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log K0„
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Conccntratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
+»~»*
Chemical
Subject
to
Evalua-
tion
~***»
200
Olhcr
108101
Methyl isobulyl ketone
3
1.19
R
4,12
-
201
953173
Methyl trithion
-1
9,12
-
202
PAH
90120
Methylnaphthalene, 1-
-1
9,12
-
203
PAH
91576
Methylnaphthalene, 2-
1436
7
9,11
3 screened
data records
in AQUIRE
No
acceptable
toxicity data
available so
can not
calculate
SQB
206
7786347
Mcvinphos / Phosdrin
2
4,12
-
A-41
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log K„
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concent ratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
207
Pesticide
2385855
Mircx / Dcchlorane
554
6.89
R
(N,R,S)
log K0„ >
5.5 so
equilibrium
partitioning
not
appropriate
209
PAH
91203
Naphthalene
3512
3.36
R
6b
ORNL-Ticr II
SCV
= 23 4 pg/L
(N,R,S)
SQB,,. =
!46pg/goc
~
226
PAH
1000
PAH Compounds
-1
7,12
-
230
PCB/Dioxin
12674112
PCB-1016
68
10
-
231
PCB/Dioxin
11104282
PCB-1221
8
12
-
A-42
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log Kow
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
232
PCB/Dioxin
1 1141165
PCB-1232
15
12
-
233
PCB/Dioxin
53469219
PCB-1242
544
10
-
234
PCB/Dioxin
12672296
PCB-1248
642
10
-
235
PCB/Dioxin
11097691
PCB-1254
1513
10
-
236
PCB/Dioxin
11096825
PCB-1260
1117
10
-
238
Halogcnaicd
608935
Pcntachlorohcnzcnc
57
5.26
R
5 or 6a
27 screened
data records
in AQUIRE
(N,R,S)
SQB„ =
To Be Done
X-T
241
72560
Perthane/Elhylan
13
12
-
242
PAH
85018
Phcnanthrcnc
5024
4.55
R
1
EPA-SQC
(SQB=
SQC at 1%
OC)
SQCX =
180Mg/goc
S
A-43
-------
JM6»TM 'OR'"
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
or
Positive
Results
Log Kow
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
~»*»*
Chemical
Subject
to
Evalua-
tion
*****
244
Pesiicidc
298022
Phoratc / Famophos /
Thimct
0
3.81
R
248
1336363
Polychlorinated
biphcnyls
3719
7,10
(N,R,S)
-
255
Pcsiicidc
1918167
Propachlor
0
-
257
PAH
129000
Pyrcnc
5527
5.11
R
II
5 or
6a
8 screened
data records
in AQUIRE
(N,R,S)
No
acceptable
toxicity test
results
available so
can not
calculate
SQB
*
258
Contains
N,S, or P
91225
Quinoline
0
A-44
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log Kow
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
261
94597
Safrolc
0
2 66
R
-
268
Other
100425
Styrene
16
2.94
R
-
271
Pesticide
13071799
Tcrbufos / Counter
0
-
273
Halogenated
95943
Tctrachlorobcn/enc,
1,2,4,5-
1
464
R
-
274
PCB/Dioxin
5)207319
Tetrachlorodibcnzo-
furan, 2,3,7,8-
64
10
(N.R.S)
-
275
PCB/Dioxin
1746016
Tctrachlorodibcnzo-p-
dioxin, 2,3,7,8-
61
6.53
R
10
(N,R,S)
-
276
Halogenated
79345
Teirachloroethanc,
1,1,2,2-
52
2.39
R-
6b
ORNL-Ticr II
SCV
= 719 M8/L
SQB^ =
161 ng/g,„
~
277
Halogenated
25322207
Tetrachloroethane, NOS ;
0
'
-
A-45
-------
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log K*
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
. Chemical
Subject
to
Evalua-
tion
*~*»+
278
Halogenatcd
127184
Tetrachloroethene
129
2.67
R
6b
ORNL-Tier II
SCV
= 125 ng/L
(N,R,S)
sqbk =
53|Jg/goc
~
279
Halogcnated
56235
Telrachloromcthane
(Carbon tetrachloride)
27
2.73
R
X
5 or 6a
25 screened
data records
in AQUIRE
SQBX =
To Be Done
X-T
281
Pesticide
961115
Tetrachlorvinphos /
Gardona
0
-
282
Other
109999
Tetrahydroluran
-1
-
287
Other
108883
Toluene
467
2.75
R
6b
ORNL-Tier II
SCV
= 176 jig/L
(N,R,S)
SQB^ =
89(Jg/goe
~
A-46
-------
Tabic A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log K„-
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) lo
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
290
Pesticide
8001352
Toxaphcnc
114
5.50
R
3
NAWQC
FCV =
0.039 (jg/L
(N,R,S)
SQBoc =
'OMg/gcx:
~
91
Halogcnated
75252
Tribromomethane
(Bromoform)
46
2.35
R
5 or
6a
6 screened
data records
in AQUIRE
SQB^ =
To Be Done
X-T
92
Halogenatcd
12002481
Trichlorobenzencs
2
-
293
87616
Trichlorobcnzcne, 1,2,3-
17
4.10
R
-
A-47
-------
"•"ffiOT-MJK 'Umft I
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
I og K„.
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
*****
294
Halogcnatcd
120821
Trichlorobenzcnc, 1,2,4-
123
4.01
R
5 or
6a
WQC
document
draft was in
preparation
10/18/88, no
ORD review;
62 screened
data records
in AQUIRE
SQB^. =
To Be Done
XT
295
Halogcnated
25323891
Trichloroethane
2
-
296
Halogcnatcd
71556
Trichloroethane, 1,1,1-
92
2.48
R
6b
ORNL-Tier 11
SCV
= 62 1 ng/L
SQBoc =
'7ng/goc
~
297
Halogcnatcd
79005
Trichloroethane, 1,1,2-
14
2.05
R
-
A-48
-------
iMQa^QR-DISTRilRI ITlOfrl
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log Kow
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*»~»*
Chemical
Subject
to
Evalua-
tion
*****
298
Halogenated
79016
Tnchlorocthcnc
105
2.71
R
6b
ORNL-Tier II
SCV
= 465 pg/L
(N,R,S)
SQB^ =
215Mg/goo
~
299
Halogenated
75694
Trichlorofluoroniethane
29
2.53
R
5 or
6a
0 screened
data records
in AQUIRE
No toxicity
data
available
*
301
Halogenatcd
67663
Trichloromethane
(Chloroform)
208
1.92
R
131 screened
data records
in AQUIRE
Log Kow <2,
equilibrium
partitioning
not
appropriate
*
08
Halogenated
95636
Trimethylbcnzene, 1,2,4-
1
-
311
Contains
N,S, or P
115866
Triphcnyl phosphate
7
-
A-49
-------
F0R~D1^TW,m,rmj)w
Table A-l. Continued
Chemical Information
Exclusion Considerations
Screening Benchmark Information
Results
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Results
Log K„.
Dec.
Codes
Data
Source
Code
Data Source
for: SQC or
Chronic-
Threshold
Water
Concentratio
n (FCV or
SCV) to
calculate
equilibrium
partitioning
Benchmark
(SQB)
Status/
Issues
*****
Chemical
Subject
to
Evalua-
tion
312
126727
Tris(2,3-dibromo-
propyl)phosphate
0
3.5!
R
-
317
Other
108054
Vinyl acetate
0
0.73
R
-
318
Other
1330207
Xylenes
93
7
6b
ORNL-Ticr II
SCV
Daphnid
test not
available so
can not use
this SCV to
derive an
SQB
*
319
Other
108383
Xylene, m-
31
3.20
R
5 or
6a
6 screened
data records
in AQUIRE
SQB^ =
To Be Done
X-T
320
Other
95476
Xylene, o-
2
3.13
R
-
A-50
-------
iaQX«gQELPlgTP|R' IT-"3N
Table A-l. Continued
Chemical Inrormation
Exclusion Considerations
Screening Benchmark Information
Results
Data Source
for: SQC or
Chronic
Threshold
Water
Concentratio
n (FCV or
*****
SCV) to
Chemical
calculate
Subject
Number
equilibrium
to
of
Data
partitioning
Evalua-
Record
Positive
Dec.
Source
Benchmark
Status/
tion
Order
CLASS
CAS
Chemical Name
Results
Log Kow
Codes
Code
(SQB)
Issues
321
Other
106423
Xylene, p-
2
3.17
R
A-51
-------
A.5 References
Brooke, L.T., D.J. Call, D.L. Geiger, and C.E. Northcott, eds. 1984. Acute toxicities of organic
chemicals to fathead minnows (Pimephales promelas), Vol. 1. Center for Lake Superior
Environmental Studies, University of Wisconsin, Superior, WI.
De Bruijn et al. 1989. Determination of octanol/water partition coefficients for hydrophobic
organic chemicals with the "slow-stirring" method. [To be completed]
De Kock and Lord. 1987. A simple procedure for determining octanol-water partition
coefficients using reverse phase high performance liquid chromatography (RPHPLC).
[To be completed]
Doucette and Andren. 1988. Estimation of octanol/water partition coefficients: Evaluation of six
methods for highly hydrophobic aromatic hydrocarbons. [To be completed]
Geiger, D.L., C.E. Northcutt, D.J. Call, and L.T. Brooke, eds. 1985. Acute toxicities of organic
chemicals to fathead minnows (Pimephales promelas), Vol. 2. Center for Lake Superior
Environmental Studies, University of Wisconsin, Superior, WI.
Geiger, D.L., S.H. Poirier, L.T. Brooke, and D.J. Call, eds. 1986. Acute toxicities of organic
chemicals to fathead minnows (Pimephales promelas), Vol. 3. Center for Lake Superior
Environmental Studies, University of Wisconsin, Superior, WI.
Geiger, D.L., D.J. Call, and L.T. Brooke, eds. 1988. Acute toxicities of organic chemicals to
fathead minnows (Pimephales promelas), Vol. 4. Center for Lake Superior Environmental
Studies, University of Wisconsin, Superior, WI.
Geiger, D.L., L.T. Brooke, and D.J. Call, eds. 1990. Acute toxicities of organic chemicals to
fathead minnows (Pimephales promelas), Vol. 5. Center for Lake Superior Environmental
Studies, University of Wisconsin, Superior, WI.
GLI. 1995. Final water quality guidance for the Great Lakes System. Final rule. U.S.
Environmental Protection Agency, Great Lakes Initiative, 40 CFR Part 132.
Howard. 1990. Handbook of environmental fate and exposure data for organic chemicals. [To
be completed]
Isnard and Lambert. 1989. Aqueous solubility and n-octanol/water partition coefficient
correlations. [To be completed]
A-53
-------
Karickhoff, S.W., and J.M. Long. 1995. Internal report on summary of measured, calculated,
and recommended log Knw values. Prepared for Elizabeth Southerland, Chief, Risk
Assessment and Management Branch, Standards and Applied Science Division, Office of
Science and Technology, U.S. Environmental Protection Agency, Washington, DC. April.
Klein et al. 1988. Updating of the OECD test guideline 107 "partition coefficient n-
octanol/water": OECD laboratory intercomparison test on the HPLC method. [To be
completed]
Leo .1993. Calculating log Pocfrom structures. [To be completed]
Mackay et al. 1992. Illustrated handbook of physical-chemical properties and environmental fate
for organic chemicals, Vols, l-lll. [To be completed]
Mayer, F.L., and M.R. Ellersieck. 1986. Manual of acute toxicity: Interpretation and database
for 410 chemicals and 66 species of freshwater animals. Resource Pub. 160. U.S.
Department of the Interior, Fish and Wildlife Service.
Mount, D.I., and C.E. Stephan. 1967. A method for establishing acceptable limits for fish-
malathion and the butoxyethanol ester of 2,4-D. Trans. Am. Fish. Soc. 96:185-193.
Noble (1993) Partition coefficients (n-octanol-water) for pesticides. [To be completed]
Stephan (1993) Derivation of proposed human health and wildlife bioaccumulation factors for
the Great Lakes Initiative. [To be completed]
Suter, G.W. II, and J.B. Mabrey. 1994. Toxicological benchmarks for screening potential
contaminants of concern for effects on aquatic biota: 1994 revision. ES/ER/TM-96/R1.
Prepared for U.S. Department of Energy, Office of Environmental Restoration and Waste
Management, Washington, DC, by Oak Ridge National Laboratory, Environmental
Sciences Division, Oak Ridge, TN.
USEPA. 1985. Guidelines for deriving numerical national water quality criteria for the
protection of aquatic organisms and their uses. PB85-227049. National Technical
Information Service, Springfield, VA.
USEPA. 1993. Proposed technical basis for establishing sediment quality criteria for nonionic
organic chemicals using equilibrium partitioning. EPA 822/R-93-011. U.S.
Environmental Protection Agency, Office of Science and Technology, Health and
Ecological Criteria Division, Washington, DC.
A-54
-------
USEPA. 1994. Great Lakes water quality initiative technical support document for the
procedure to determine bioaccumulation factors July 1994. EPA-822-R-94-002. U.S.
Environmental Protection Agency, Office of Water, Office of Science and Technology,
Washington, DC.
A-55
-------
Appendix B
Method for Selecting Biota-Sediment Accumulation Factors and Percent Lipids in Fish
Tissue Used for Deriving Theoretical Bioaccumulation Potentials
B.l Introduction
Theoretical bioaccumulation potentials (TBPs) are empirically derived potential concentrations
that might occur in the tissues of fish exposed to contaminated sediments. TBPs are computed
for nonpolar organic chemicals as a function of sediment concentrations, fish tissue lipid contents,
and sediment organic carbon contents. Four separate pieces of information are required to
compute the TBP for nonpolar organic chemicals:
1. Concentration of nonpolar organic compound in sediment
2. Organic carbon content of the sediment
3. Biota-sediment accumulation factor (BSAF)
4. Lipid content in fish tissue.
The details of the TBP calculations and related assumptions are found in the main section of this
issue paper. This appendix describes the approach used to develop the BSAFs (Section B.2) and
to evaluate fish tissue lipid content data from selected information sources for comparison to the
values used in the NSI evaluation (Section B.3). TBPs calculated using the values for the BSAFs
and fish tissue lipid contents will be used to augment available tissue residue data used in
sediment classifications.
Chemicals that do not have at least one screening threshold available and for which the sum of
the number of positive sediment results plus the number of positive tissue results is greater than
20 were not considered for fish tissue residue evaluation in the NSI.
B.2 Method for Selecting BSAFs
Biota-sediment accumulation factors (BSAFs) are transfer coefficients that relate concentrations
in biota to concentrations in sediment. They are calculated as the ratio of the concentration of
nonpolar organic chemical in fish tissue (normalized by lipid content) to the concentration of
nonpolar organic chemical in sediment (normalized by organic carbon content). At equilibrium,
BSAFs are in theory approximately 1.0. In practice, BSAFs can be greater than or less than 1.0
depending on the disequilibrium between fish and water, and that between water and sediment.
Although the TBP calculation approach taken here addresses mainly the effects of chemical
properties, BSAFs can differ depending on the biota, dynamics of chemical loadings to the water
body, food chain effects, and rate of sediment-water exchange. Thus, actual BSAFs will depend
on many site-specific variables including hydraulic, biological, chemical, and ecological factors
that affect bioavailability.
B-l
-------
BSAPs were assigned to nonpolar chemicals in the NSI. This section describes how the actual
BSAP values used for the bioaccumulation risk classification assessment were selected from
recommended values for specific chemicals.
B.2.1 Sources of Recommended BSAPs.
BSAPs used to assess risks associated with bioaccumulation were obtained from two major
sources:
• Two EPA Office of Research and Development Environmental Research Laboratories
(EPA/ORD)
• USEPA and USCOE (1994).
The BSAPs from EPA/ORD were obtained from the research laboratories at Duluth, Minnesota
(Cook, 1995) and Narragansett, Rhode Island (Hansen, 1995). In some cases (i.e., EPA/ORD-
Duluth) BSAPs were provided for specific chemicals. In other cases (i.e., EPA/ORD-
Narragansett) BSAFs were provided by chemical class. Recommended BSAFs from each
laboratory are described below.
B.2.1.1 EPA Environmental Research Laboratory, Duluth
BSAF recommendations obtained from EPA/ORD-Duluth included mainly chemical-specific
values for:
• PCB congeners
• Pesticides
• Dioxins/Furans.
BSAFs were also available from this source for three of other chlorinated chemicals
(hexachlorobenzene, pentachlorobenzene, and 1, 2, 3, 4 trichlorobenzene).
The recommended values from EPA/ORD-Duluth were based on BSAP data compiled from
various sites and studies. Data were selected based on the following criteria (Cook, 1995):
• The primary source of chemical exposure to food webs was through release of
chemicals in sediments.
• The BSAF was derived for pelagic organisms (i.e., fish).
• Chemicals in sediments and biota were at roughly steady state with respect to
environmental loadings of the chemical.
B-2
-------
M^PQfeEaSTRIBUTION.,
Few, if any, steady-state sites were available, however, because environmental loadings of many
of the chemicals are variable or have declined since the 1960s. Barring this limitation, the BSAF
data for Lake Ontario that were used to estimate bioaccumulation factors (BAFs) for the Great
Lakes Water Quality Initiative were recommended (USEPA, 1994a; Cook, 1995). The Lake
Ontario BSAFs (Cook et al., 1994) are the primary source of values used in NSI sediment
assessments. Another source for BSAFs was the set of values reported for Lake Ontario
salmonids (Oliver and Niimi, 1988). The Lake Ontario BSAFs are based on a large set of
sediment and fish samples collected in 1987 (USEPA, 1990).
B.2.1.2 EPA Environmental Research Laboratory, Narragansett
EPA/ORD-Narragansett provided a second source of information for selecting BSAF values.
Probability distribution curves for selecting BSAFs were presented by EPA/ORD-Narragansett
for three chemical classes:
• PAHs
• PCBs
• Pesticides.
EPA/ORD-Narragansett researchers developed cumulative probability curves for each chemical
class from their database of BSAFs (Hansen, 1995). The database from which general BSAF
recommendations were summarized included data from laboratory and field studies conducted
with both freshwater and marine sediments. Data must be from species that directly contact
sediments or feed on organisms that live in sediments, i.e., benthic invertebrates and benthically
coupled fishes.
Overall the database contained over 4,000 BSAF observations. Cumulative probability curves
summarizing the BSAF data in the database were provided by Hansen (1995) for PAHs, PCBs,
and pesticides. BSAF values were tabulated for several probability percentiles.
B.2.1.3 Evaluation of Dredged Material Proposed for Discharge in Waters of the
U.S.—Testing Manual (USEPA and USCOE, 1994).
A value of 4 for the BSAF was recommended as a default value by the USEPA and USCOE
(1994) draft Testing Manual. The value of 4 was based on field studies with PCBs (Ankley et
al., 1992). It represents the potential contaminant concentration in lipid of biota if sediment is
the only source of contaminant exposure to the organism (USEPA and USCOE, 1994).
B.2.2 Approach for Choosing BSAFs from Recommended Values
The general approach for choosing a BSAF for a chemical follows:
B-3
-------
MPT FjQB-^XRjWPieN
• Use a chemical-specific value for the BSAF, if available.
• If no chemical-specific value is available, use a BSAF derived for a chemical
category.
• For chemicals having no specific information on the BSAF, use the default value (i.e.,
4) from USEPA and USCOE (1994).
Exceptions, including exactly how the BSAFs were chosen, follow.
The EPA/ORD-Narragansett values for the BSAF were selected to achieve the 90th-percentile
protection level (Table B-l). The choice of the 90th-percentile protection level is equivalent to
multiplying the median (i.e., the 50th-percentile values in Table B-l) for chemical classes by a
safety factor of between 4 and 6.
The BSAF values from EPA/ORD-Duluth were averages rather than 90th-percentile values.
Therefore, for consistency with the level of conservatism contained in the 90th-percentile BSAFs
from EPA/ORD-Narragansett, the BSAFs from EPA/ORD-Duluth were multiplied by a safety
factor of 4. This approach was necessary to apply a consistent level of conservatism among
recommended BSAF values from the different sources.
Since there was some overlap between the categories of chemicals for which BSAF values were
recommended, the following approach was used to assign BSAFs to specific chemicals in the
NSI. For dioxins and furans, chemical-specific values recommended by EPA/ORD-Duluth were
applied (Table B-2); for PCBs, congener-specific values recommended by EPA/ORD-Duluth were
Table B-l. BSAF (kg sediment organic carbon/kg lipid)
Probability
Percentile
Chemical Class
PAILs
PCBs
Pesticides
50
0.29
1.11
1.80
70
0.55
2.26
3.34
80
0.94
3.66
4.61
90
1.71
5.83
7.31
95
2.84
9.15
10.61
99
4.19
16.46
22.63
B-4
-------
M#¥-raR*DIS;ERJB-UJJ€>N^
Table B-2. Conventions for Assigning BSAFs to Nonpoiar Organic Compounds in NSI
Category of
Chemical
Source of BSAF
Safety Factor
Applied
Dioxins
EPA/ORD-Dulutha "pelagic," risk-based,
congener-specific BSAF
4.0
PCBs
EPA/ORD-Dulutha "pelagic," risk-based,
congener-specific BSAF
4.0
Pesticides
• log Kow < 5.5
• log Kow < 5.5
EPA/ORD-Narragansettb "benthic"
class-specific BSAF for 90th percentile
protection level (i.e., 7.31)
1.0
• log Kow > > = 5.5
log Kow > 5.5
Use EPA/ORD-Dulutha "pelagic," risk-
based, chemical-specific BSAF if
available; otherwise, use EPA/ORD-
Narragansettb value
4.0
PAHs
EPA/ORD-Narragansettb "benthic," risk-based,
class-specific BSAF for 90th percentile
protection level (i.e., 1.71)
1.0
Halogenated and
other compounds
Use USEPA and USCOE (1994) default value
(i.e., 4) unless a chemical-specific value is
available from EPA/ORD-Duluth.a
1.0
(unless using value
recommended by
Duluth)
"Cook, 1995; USEPA, 1994a.
bHansen, 1995.
used. When using BSAFs from USEPA (1994a), values from the study by Cook et al. (1994)
were preferred over values reported by Oliver and Niimi (1988) unless the values by Oliver and
Niimi (1988) were all that were available, as recommended by Cook (1995). A safety factor of
4 was applied to all BSAF values obtained from USEPA (1994a) as discussed above.
B-5
-------
Pesticides received recommendations from both laboratories. The BSAFs developed by
EPA/ORD-Naragansett were for benthic organisms and demersal fishes. The BSAFs developed
by EPA/ORD-Duluth, on the other hand, were for benthically coupled pelagic fishes. BSAFs
from EPA/ORD-Naragansett were used for pesticides having log Kow values less than 5.5. For
pesticides having log Kow values greater than or equal to 5.5, the BSAF values from EPA/ORD-
Duluth were used. BSAF values selected by this approach are expected to be more conservative
because food web transfer to pelagic fishes is a more important process for chemicals having
high log Kow values. Exposure through environmental media, as in direct contact with sediments
by benthic organisms, is a more important process for chemicals having low log values.
For PAHs the 90th percentile protection class-specific BSAF equal to 1.71 was used based on
recommendation by EPA/ORD-Narragansett (Hansen, 1995). No safety factor was applied
because conservatism was already built into the BSAF through use of the 90th percentile.
For compounds other than those for which recommendations were available from EPA/ERLs, the
recommended value of 4 from USEPA and USCOE (1994) was used. Chemicals having no BSAF
values available included halogenated compounds; compounds containing nitrogen, sulfur, or
phosphorus; and other compounds.
BSAF values were assigned to all nonpolar organic chemicals in the NSI having available
screening thresholds (Table B-3). These thresholds are risk-based concentrations (RBCs)
developed either from carcinogenic potency slopes (carcinogenic RBCs in Table B-3) or from
oral reference doses (noncarcinogenic RBCs in Table B-3). Carcinogenic potency slopes and
reference doses were obtained from IRIS (USEPA, 1995) and HEAST (USEPA, 1994b). Other
thresholds that will be used for screening tissue data and RBCs are FDA action levels and EPA
wildlife criteria (Table B-3). Table B-3 includes nonpolar organic chemicals only. For each
chemical the number of positive sediment results and number of positive tissue results are given.
Chemicals subject to evaluation in Table B-3 are those for which at least one screening threshold
is available and for which the sum of the number of positive sediment results and the number
of positive tissue results is greater than 20.
B.3 Evaluation of Tissue Lipid Content
Fish tissue lipid content enters the risk screening assessment as the normalizing factor in the
numerator of the TBP equation. Normalizing by organic carbon content removes much of the
site-to-site variation in the sorption of nonpolar organic chemicals by sediments (Karickhoff et
al., 1979). In a similar manner, normalizing by lipid content can eliminate much site and species
variation in organisms' tendency to bioaccumulate nonpolar organic compounds (Esser, 1986).
Lipid contents can vary naturally with species, site, season, age and size of fish, and trophic
status. In addition, reported lipid contents can vary significantly depending on the analytical
method (Randall et al., 1991).
B-6
-------
hi not
Table B-3. Summary of Information for Modeling and Screening Tissue Residue Data for the National Sediment Inventory
Chemical Information
Exclusion Criteria
Fish Tissue Residue Screening Information
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Tissue
Results
Number
of
Positive
Sediment
Results
Log
Kow
Available Screening Thresholds (ppm)
BSAF
*****
Chemical
Subject to
Evaluation
*****
EPA (RBC)
Other
Carcino-
genic
Risk 10'
Non-
carcino-
genic
FDA
Action
Level
EPA
Wildlife
Crit.
1
PAH
83329
Accnaphthenc (EqP=SQC at 1% OC)
292
2053
3 92
650
1.71"
~
2
PAH
208968
Acenaphthylcne
1679
3.95
3
Other
67641
Acetone
95
-0.24
1 100
4 0C
S
4
Olhcr
98862
Acctophenone
1
1.64
1100
5
Pesticide
107028
Acrolein
15
-0.01
220
6
Contains
N,S, or P
107131
Acrylonilrilc
22
0.25
0.2
11
4.0C
~
7
Pesticide
15972608
Alachlor/Lasso
1
2
1.3
110
9
Pesticide
309002
Aldrin
801
716
6.50
6 3E-03
0.32
0.3
7.31"
~
15
PAH
120127
Anthracene
314
1988
4.55
3200
1 71"
~
21
Other
71432
Benzene
96
2(X>
2.13
3.7
4.0'
~
24
Other
106514
Bcnzoquinone, p-
0
25
Halogenated
98077
Bcnzotrichloridc
-1
8.3E-03
26
PAH
56553
Benzo(a)anthracene
339
4000
5.70
0.15
1.71"
~
27
PAH
50328
Benzo(a)pyrene
313
4017
6.11
0.015
1.7 lb
~
B-7
-------
^NeMQfeatSTRI BLITlQtJ,
Table B-3. (continued)
Chemical Information
Exclusion Criteria
Fish Tissue Residue Screening Information
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Tissue
Results
Number
of
Positive
Sediment
Results
l«g
K„w
Available Screening Thresholds (ppm)
BSAF
*****
Chemical
Subject to
Evaluation
*****
EPA (RBC)
Other
Carcino-
genic
Risk 10'
Non-
carcino-
genic
FDA
Action
l.evel
EPA
Wildlife
Crit.
28
PAH
205992
Bcn/o(h)fluorunlhcne
57
1529
6 20
0 15
1 71"
~
29
PAH
191242
Benzo(ghi)pcrylcne
2495
6.70
30
PAH
207089
Benzo(k)fluoranlhcne
53
1311
6.20
1.5
1.71b
~
31
Halogcnaled
100447
Benzyl chloride
-1
2.30
0.63
32
Halogcnaied
25168052
Chloromethylbenzene
-1
33
Pesticide
319846
BHC, alpha-
1832
243
3.80
0.017
7.31"
~
34
Pesticide
319857
BHC, bcta-
215
276
3 81
0.060
7.31"
~
35
Pesticide
319868
BHC, delta-
0
128
3.78
36
Pesticide
58899
BHC, gamma- Lindane
1639
1085
3.73
0.083
3 2
7.31"
~
37
Pesticide
608731
BHC, technical grade
36
167
0 060
0.3
7 31"
~
38
PAH
92524
Biphcnyl
395
951
3 95
540
1.7 lb
S
40
Halogenaled
111911
Bis(2-chloroethoxy) methane
-1
41
Halogenatcd
111444
Bis(2-chloroethyl) ether
3
1.21
0.098
42
Halogenaled
108601
Bis(2-chloroisopropyl) ether
0
2.58
1.54
430
B-8
-------
Table B-3. (continued)
Chemical Information
Exclusion Criteria
Fish Tissue Residue Screening Information
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Tissue
Results
Number
of
Positive
Sediment
Results
Log
Available Screening Thresholds (ppm)
BSAF
*****
Chemical
Subject to
Evaluation
»~»*»
EPA (RBC)
Other
Carcino-
genic
Risk 10 s
Non-
carcino-
genic
FDA
Action
Level
EPA
Wildlife
Crit.
43
Other
117817
Bis(2-ethylhcxyl) phthalatc
2835
7 30
7 7
220
4.0C
~
44
Halogenatcd
542881
Bis(chloromethyl)cthcr
-1
4 9E-04
45
35400432
Bolstar/Sulprofos
0
47
Halogenatcd
75274
Bromodichloromethane
4
10
2.10
1 7
220
48
Halogenatcd
74839
Bromomethane
4
15
49
Halogenatcd
101553
Bromophcnyl phenyl ether, 4-
21
5 00
620
4.0C
~
51
Pesticide
23184669
Butachlor
0
43
52
123864
Butyl acetate, n-
0
53
Other
85687
Butyl benzyl phthalate
5
546
4.84
2200
4.0"
~
59
786196
Carbophcnothion/Trithion
16
62
Pesticide
57749
Chlordane
4225
2258
6 32
0.083
0.65
0.3
12.0M
~
63
1067
Chlorinated naphthalene, NOS
-1
64
Halogenatcd
108907
Chlorobenzene
18
80
2.86
220
4.0C
~
66
Halogenatcd
74975
Chlorobromomethane
0
B-9
-------
NQ^FQR^RtS^RttUJXLQM
Tabic B-3. (continued)
Chemical Information
Exclusion Criteria
Fish Tissue Residue Screening Information
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Tissue
Results
Number
of
Positive
Sediment
Results
Log
K„
Available Screening Thresholds (ppm)
BSAF
*****
Chemical
Subject to
Evaluation
*****
EPA (RBC)
Other
Carcino-
genic
Risk 105
Non-
carcino-
genic
FDA
Action
Level
EPA
Wildlife
Crit.
67
Halogcnated
75003
Chloroethane
2
1.50
4300
68
Halogenatcd
75014
Chloroethene
4
0 057
69
Halogcnated
110758
Chloroethylvinyl ether, 2-
3
270
70
Halogcnated
74873
Chloromcthanc
14
83
72
PAH
91587
Chloronaphthalene, 2-
9
860
74
Halogenatcd
7005723
Chlorophenylphenyl ether, 4-
10
4.95
75
Pesticide
2921882
Chlorpyrifos/Dursban
207
5
5.26
32
7.31"
~
78
PAH
218019
Chryscnc
334
4380
5.70
15
1.71"
~
87
Other
98828
Cumene
0
3.58
430
90
Other
110827
Cyclohexane
0
92
Pesticide
1861321
DCPA/Dacthal
688
76
110
7.31"
~
93
Pesticide
72548
DDD, p, p'-
2665
4706
6.10
0.45
1 12a
~
94
Pesticide
72559
DDE, p, p'-
6335
6310
6.76
0 32
5
30.8a
S
95
Pesticide
50293
DDT, p, p'-
1882
3471
6.53
0.32
5.4
5
1.26E-03
6 68"
S
B-10
-------
_ NOT FnR_DJ^i3EiR»tBJ4XlQN.
Tabic B-3. (continued)
Chemical Information
Exclusion Criteria
Fish Tissue Residue Screening Information
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Tissue
Results
Number
of
Positive
Sediment
Results
Log
K„.
Available Screening Thresholds (ppm)
BSAF
*»~»*
Chemical
Subject to
Evaluation
*****
EPA (RBC)
Other
Carcino-
genic
Risk 10 s
Non-
carcino-
genic
FDA
Action
Level
EPA
Wildlife
Crit.
96
Pesticide
1163195
Decabromodiphcnyl oxide
-1
110
98
78488
DEF
-1
101
Pesticide
333415
Diazinon/Spectracide
0
275
4.30
97
7.3 lb
~
102
Other
132649
Dibenzofuran
0
764
4 10
43
4 03c
~
103
PAH
53703
Dibcnzo(a,h)anthraccne
0
3459
6 69
0015
1 71"
/
104
Mulogcnated
96128
Dibromo-3-chloropropane, 1,2-
0
2.34
0 077
105
Halogenatcd
124481
Dibromochloromethane
1
18
2.17
1.3
220
108
Halogcnatcd
25321226
Dichlorobcnzencs
0
13
960
109
Halogenatcd
95501
Dichlorobcnzenc, 1,2-
2
155
3.43
970
4.0C
~
110
Halogcnatcd
541731
Dichlorobenzenc, 1,3-
0
162
3.43
960
4 0C
S
111
Halogcnatcd
106467
Dichlorobcnzene, 1,4-
3
366
3.42
4.5
4.0°
S
113
Halogcnatcd
75718
Dichlorodifluoromethanc
0
2.16
2200
114
Halogcnatcd
75343
Dichloroethanc, 1,1-
26
1.79
1100
4.0C
115
Halogcnated
107062
Dichloroethane, 1,2-
29
1.47
1.2
4.0C
~
B-l 1
-------
Table B-3. (continued)
Chemical Information
Exclusion Criteria
Fish Tissue Residue Screening Information
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Tissue
Results
Number
of
Positive
Sediment
Results
Log
Kow
Available Screening Thresholds (ppm)
BSAF
*****
Chemical
Subject to
Evaluation
*****
EPA (RBC)
Other
Carcino-
genic
Risk 105
Non-
curcino-
genic
FDA
Action
Level
EPA
Wildlife
Crit.
116
Halogenated
75354
Dichloroethcne, 1,1-
3
11
2.13
0 18
97
117
Halogenatcd
156605
Dichloroethcnc, trans-1,2-
3
34
2.07
220
4.0C
~
118
Halogenated
156592
Dichlorocthylcnc, cis-1,2-
0
1.86
110
119
Halogenatcd
75092
Dichloromcthane
900
1.25
14
650
4.0C
~
122
Halogenated
78875
Dichloropropanc, 1,2-
2
36
1.97
1.6
4.0C
~
123
Halogenated
5635442
Dtchloropropcnc, 1,2-
-1
124
Halogenatcd
542756
Dichloropropcnc, 1,3-
11
2.00
0.62
3 2
125
Halogenated
78886
Dichloropropene, 2,3-
-1
126
Halogenated
10061015
Dichloropropenc, cis-1,3-
2
127
Halogenatcd
10061026
Dichloropropcnc, trans-1,3-
1
129
Pesticide
62737
Dichlorvos
0
0 37
5.4
131
Pesticide
60571
Dieldrin (EqP=SQC at 1% OC)
5389
3241
5.37
6.7E-03
0.54
0.3
731"
~
132
Other
84662
Diethyl phthalate
4
511
2.50
8600
4.0C
~
135
PAH
28804888
Dimethyl naphthalene
-1
B-12
-------
UTIQN.
Table B-3. (continued)
Chemical Inrormation
Exclusion Criteria
Fish Tissue Residue Screening Information
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Tissue
Results
Number
of
Positive
Sediment
Results
Log
K„„
Available Screening Thresholds (ppm)
BSAF
*****
Chemical
Subject to
Evaluation
*****
El*A (RUC)
Other
Carcino-
genic
Risk 105
Non-
carcino-
genic
FDA
Action
Level
EPA
Wildlife
Crit.
136
Other
131113
Dimethyl phthalate
0
304
1 57
110000
139
Other
84742
Di-n-butyl phthalate
65
1411
4.61
1100
4.0C
~
147
Other
117840
Di-n-octyl phthalate
0
743
8.06
220
4.0C
y
152
Pesticide
115297
Endosulfan mixed isomers
14
81
4.10
65
7.31"
~
153
Pesticide
1031078
Endosulfan sulfate
0
96
3.25
154
Pesticide
959988
Endosulfan, alpha-
0
92
3.83
155
Pesticide
33213659
Endosulfan, bcta-
0
273
4.52
156
Pesticide
72208
Endnn (EqP=SQC at 1% OC)
1081
327
5 06
3.2
7.31"
y
157
7421934
Endrin aldehyde
37
4.00
158
Halogenated
76131
Ethane, 1,1,2-trichloro-1,2,2-
-1
160
Pesticide
563122
Ethion/Bladan
0
43
5.4
7.31b
~
161
13194484
Ethoprophos
-1
162
141786
Ethyl acetate
0
0.69
9700
163
Other
100414
Ethylbenzene
58
137
3.14
1100
4.0C
~
B-13
-------
UTIQM
Tabic B-3. (continued)
Chemical Information
Exclusion Criteria
Fish Tissue Residue Screening Information
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Tissue
Results
Number
of
Positive
Sediment
Results
Log
Kow
Available Screening Thresholds (ppm)
BSAF
*****
Chemical
Subject to
Evaluation
*****
EPA (RBC)
Other
Carcino-
genic
Risk 105
Non-
carcino-
genic
FDA
Action
Level
EPA
Wildlife
Crit.
164
Halogcnatcd
106934
Ethylene dibromide
0
1.3E-03
165
115902
Fensulfothion/Desanii
0
166
55389
Fcnthion/Baytex
0
167
PAH
206440
Fluoranthcnc (EqP=SQC at 1 % OC)
378
5501
5.12
430
1.71"
~
168
PAH
86737
Fluorcnc
31
2905
4.21
430
1.71"
~
170
Pesticide
944229
Fonofos
0
22
173
Pesticide
76448
Heptachlor
1352
732
6.26
0.024
5.4
0.3
7.31b
~
174
Pesticide
1024573
Heplachlor epoxide
2824
1018
5.00
0.012
0.14
0.3
7.3 lb
~
175
Halogcnatcd
118741
Hcxachlorobcnzcne
1892
1537
5.89
0 067
8.6
0.36"
~
176
Halogenatcd
87683
Hexachlorobutadiene
92
163
4.81
1.4
2.2
4.0C
~
177
Halogcnatcd
77474
Hexachlorocyclopcntadiene
-1
5.39
75
178
Halogcnatcd
67721
Hexachlorocthanc
1
25
400
7.7
11
4.0C
~
180
Pesticide
51235042
Hexazinone
0
360
182
PAH
193395
Indeno( 1,2,3-cd)pyrcne
2380
6.65 .
0 15
1 71"
~
B-14
-------
Table B-3. (continued)
Chemical Information
Exclusion Criteria
Fish Tissue Residue Screening Information
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Tissue
Results
Number
of
Positive
Sediment
Results
Log
K„.
Available Screening Thresholds (ppm)
liSAF
*****
Chemical
Subject to
Evaluation
EPA (RBC)
Other
Carcino-
genic
Risk HI*
Non-
carcino-
gcnic
FDA
Action
Level
EPA
Wildlife
Cril.
1X5
Other
78591
Isophoronc
56
1 70
1 10
2200
4.01
y
188
Oihcr
120581
Isosafrole
0
192
Pesticide
121755
Malathion
2
54
3.20
220
7.31"
y
197
Pesticide
72435
Methoxychlor
144
180
5.08
54
7.31"
y
199
Other
78933
Methyl ethyl ketone
35
0.28
6500
4 0°
y
2()0
Other
108101
Methyl isobutyl ketone
3
1.19
860
201
953173
Methyl trithion
-1
202
PAH
90120
Methylnaphthalenc, 1-
-1
203
PAH
91576
Methylnaphthalene, 2-
1436
206
7786347
Mcvinphos/Phosdrin
2
207
Pesticide
2385855
M irex/Dechloranc
1 131
554
6.89
0.060
2 2
0.1
5.24*
y
209
PAH
91203
Naphthalene
32
3512
3.36
430
1.71"
y
226
PAH
1000
PAH Compounds
-1
230
PCB/Dioxin
12674112
PCB-1016
15
68
0.014
0.75
2
0.0231
7.40*d
y
B-15
-------
NOTJOELD1 gTD.Dimrui
Table B-3. (continued)
Chemical Information
Exclusion Criteria
Fish Tissue Residue Screening Information
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Tissue
Results
Number
of
Positive
Sediment
Results
Log
K
Available Screening Thresholds (ppm)
BSAF
Chemical
Subject to
Evaluation
EPA (RBC)
Other
Carcino-
genic
Risk 1«"5
Non-
carcino-
genic
FDA
Action
I-evel
EPA
Wildlife
Crit.
231
PCB/Dioxin
11104282
PCB-1221
2
8
0 014
2
0 0231
232
PCB/Dioxin
11141165
PCB-1232
1
15
0.014
2
0.0231
233
PCB/Dioxin
53469219
PCB-1242
235
544
0014
2
0.0231
7.40"d
~
234
PCB/Dioxin
12672296
PCB-1248
764
642
0.014
2
0 0231
7.40°d
~
235
PCB/Dioxin
11097691
PCB-I254
3569
1513
0.014
0.22
2
0.0231
7.40"d
~
236
PCB/Dioxin
11096825
PCB-1260
3847
1117
0.014
2
0.0231
7.40"d
~
238
Halogenated
608935
Pcntachlorobcnzcne
0
57
5.26
8.6
0.16"
~
241
72560
Pcrthane\Ethylan
13
242
PAH
85018
Phcnanthrcne (EqP=SQC al 1% OC)
0
5024
4.55
244
Pesticide
298022
Phorate/Famophos/Thimcl
0
3.81
2.2
248
PCB/Dioxin
1336363
Polychlonnatcd biphenyls
7631
3719
0.014
2
0.0231
7.40ae
~
255
Pesticide
1918167
Propachlor
0
140
257
PAH
129000
Pyrene
370
5527
5.11
320
1.71c
~
258
Contains
N,S, or P
91225
Quinoline
0
9.0E-03
B-16
-------
Table B-3. (continued)
Chemical Information
Exclusion Criteria
Fish Tissue Residue Screening Information
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Tissue
Results
Number
of
Positive
Sediment
Results
Log
Kow
Available Screening Thresholds (ppm)
BSAF
*****
Chemical
Subject to
Evaluation
*****
EPA (RBC)
Other
Carcino-
genic
Risk 105
Non-
carcino-
genic
FDA
Action
Level
EPA
Wildlife
Crit.
261
94597
Safrole
0
2.66
268
Oiher
100425
Slyrene
16
2.94
2200
271
Pesticide
13071799
Terbufos/Counter
0
0 27
273
Halogcnaied
95943
Tctrachlorobcnzenc, 1,2,4,5-
83
1
4.64
3.2
0.04"
~
274
PCB/Dioxin
51207319
Teirachlorodibcnzo-furan, 2,3,7,8-
0
64
275
PCB/Dioxin
1746016
Tctrachlorodibcnzo-p-
dioxin, 2,3,7,8-
552
61
6.53
6 9E-07
7.7E-07
0 24"
~
276
Halogcnaied
79345
Tetrachlorocthanc, 1,1,2,2-
33
52
2.39
0.54
4.0L
~
277
Halogenated
25322207
Tetrachloroethane, NOS
0
278
Halogcnaied
127184
Tctrachlorocihcne
54
129
2.67
2 1
110
4.0°
~
279
Halogenated
56235
Telrachloromethane
4
27
2.73
0.83
7.5
4.0C
~
281
Pcsiicide
961115
Tetrachlorvinphos/Gardona
0
4.5
320
282
Other
109999
Tetrahydrofuran
-1
287
Other
108883
Toluene
132
467
2.75
2200
4.0C
~
290
Pesticide
8001352
Toxaphcne
685
114
5.50
0.098
5
7.31"
~
B-17
-------
Table B-3. (continued)
Chemical Information
Exclusion Criteria
Fish Tissue Residue Screening Information
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Tissue
Results
Number
of
Positive
Sediment
Results
Log
K„
Available Screening Thresholds (ppm)
BSAF
*****
Chemical
Subject to
Evaluation
*****
EPA (RBC)
Other
Carcino-
genic
Risk 105
Non-
carcino-
genic
FDA
Action
Level
EPA
Wildlife
Crit.
291
Halogenated
75252
Tribromomethane
12
46
2.35
14
220
4 0c
~
292
Halogenated
12002481
Trichlorobenzenes
2
293
87616
Trichlorobenzcnc, 1,2,3-
17
4.10
294
Halogenated
120821
Trichlorobenzenc, 1,2,4-
87
123
4.01
110
4 ()c
~
295
Halogenaicd
25323891
Tnchloroethane
2
296
Halogenated
71556
Trichloroethane, 1,1,1-
27
92
2.48
970
4.0C
~
297
Halogenated
79005
Triehloroethane, 1,1,2-
7
14
2 05
1 9
43
4.0C
~
298
Halogenated
79016
Trichlorocthene
105
2.71
9.8
65
4 0'
~
299
Halogenated
75694
T richlorofluoromcthane
18
29
2.53
3200
4.0C
~
301
Halogenated
67663
Trichloromethane
43
208
1.92
18
110
4.0C
~
308
Halogenated
95636
Trimethylbenzene, 1,2,4-
1
5.4
311
Contains
N,S, or P
115866
Triphenyl phosphate
7
312
126727
Tris(2,3-dibromopropyl)phosphate
0
3.51
317
Other
108054
Vinyl acetate
0
0.73
11000
B-18
-------
Table B-3. (continued)
Chemical Information
Exclusion Criteria
Fish Tissue Residue Screening Information
Record
Order
CLASS
CAS
Chemical Name
Number
of
Positive
Tissue
Results
Number
of
Positive
Sediment
Results
Log
K„
Available Screening Thresholds (ppm)
liSAF
*****
Chemical
Subject to
Evaluation
*****
EPA (RBC)
Other
Carcino-
genic
Risk 10'
Non-
carcino-
genic
FDA
Action
Level
EPA
Wildlife
Cril.
318
Other
1330207
xylenes
0
93
3 17
22000
4.0C
S
319
Other
108383
xylene, m-
0
31
3.20
22000
4.0C
~
320
Other
95476
xylene, o-
2
3 13
22000
4.0"
321
Other
106423
xylenc, p-
2
3.17
"Cook, 1995.
"Hansen, 1995.
CUSEPA and USCOE, 1994.
dAnlhmctic mean of BSAFs for different congeners.
eBSAF for total PCBs.
B-19
-------
MOT TOR DISTRIBUTION
The purpose of this section is to evaluate the percent fish lipid content data from various sources
and compare these values to those selected for use in the NSI evaluation (i.e., 3.0 percent for
fillets for human health TBP evaluations and 10.31 percent for whole-body wildlife TBP
evaluations).
The remainder of this section describes the lipids data sources evaluated and analysis of the lipid
content data.
B.3.1 Sources of Lipids Data
Lipid data considered in the evaluation of the default value for TBP calculations were obtained
from three major sources:
• EPA's water monitoring database, STORET
• National Study of Chemical Residues in Fish (NSCRF) USEPA (1992)
• USDA's (1990) Composition of Foods (Dickey, 1990).
Additional sources included examples of whole fish and fillet lipid contents taken from the recent
literature.
Each of the three major sources is described in the following paragraphs.
B.3.1.1 STORET
The STORET database was the single largest source of reported data on fish tissue lipid contents.
The data source referred to here as "STORET" included STORET lipids data. Data stored under
various parameter codes for lipid content in STORET were converted into units of percentage.
Some screening of the data was performed as follows:
• Records were retrieved from January 1990 to March 1995.
• Reported lipid contents greater than 35 percent were eliminated because they were
significantly greater than the 90th percentile.
• Only records having an anatomy code of "whole organism" or "fillet" were included.
Records indicated as "fillet/skin" or "edible portion" were excluded.
• Data that appeared reversed (i.e., fillet percent lipid was greater than whole organism
lipid) were also not considered.
B-20
-------
£tQT EQELDISgKffiOTFBfrfr
• Also considered suspect were records in which the minimum and maximum were
equal, or very nearly equal, when the number of observations was large.
There is less consistency in the data obtained from STORET relative to the NSCRF data since
the analyses in STORET were conducted by numerous laboratories around the nation. Data
reported under different parameter codes (i.e., different methods for lipids) were grouped for the
analysis. Moreover, the quality of the data in STORET is unknown. STORET data are compiled
by species in Tables B-4. The fishes are divided by trophic level and habitat into four tables
(Table B-4, a-d) for the combinations of trophic levels 3 and 4 and epibenthic (bottom-dwelling)
and pelagic (water column-dwelling) habitat.
B.3.1.2 National Study of Chemical Residues in Fish
The second largest database on fish tissue lipid content was available from the NSCRF (USEPA,
1992) (Table B-4). This set of lipid analysis data was taken in conjunction with analyses for
dioxins/furans. An advantage of this database is that all of the lipid measurements were
performed by the same laboratory using the same method. The data were screened to exclude
data for fish species for which two or fewer observations were made (USEPA, 1992).
Table B-4a. Lipid Contents of Trophic Level 3, Epibenthic Fishes.
Species Name
Common Name
Whole Fish Lipid
Content,
Percent (size )
Fillet Lipid
Content, Percent
(size)
Reference,
Comments
Aplodinotus grunniens
freshwater drum
mean = 1.9 (1.3 to
2.5, 3 obs)
USEPA (1992)
Aplodinotus grunniens
freshwater drum
mean = 4.93,
standard error =
0.103, 905 obs)
Exler (1987)
Carpoides carpio
river carpsucker
mean = 5.8
(0.5 to 15.0, 3865
obs)
mean = 4.4 (1.8 to
9.2, 184 obs)
STORET
Carpoides cyprinus
quillback
mean = 5.1
(0.3 to 13.0, 780
obs)
mean = 3.2
(0.4 to 4.89, 78 obs)
STORET
Catostomus ardens
Utah sucker
mean = 3.5 (1.1
to 8.2, 356 obs)
mean = 1.6
(0.1 to 6.7, 695 obs)
STORET
Catostomus catostomus
longnose sucker (FW)
0.8 to 3.8
(not given)
Owens et al.
(1994)
Catostomus catostomus
longnose sucker
mean = 3.9 (2.5
to 7.2, 298 obs)
mean = 7.05 (6.4 to
7.7, 32 obs)
STORET
B-21
-------
NOT rOCTfSTKTBITFEOft
Table B-4a. (continued)
Species Name
Common Name
Whole Fish Lipid
Content,
Percent (size )
Fillet Lipid
Content, Percent
(size)
Reference,
Comments
Catostomus columbianus
bridgelip sucker
mean = 4.6 (0.7
to 10.4. 309 obs)
STORET
Colostomas commersoni
white sucker
5.41 ± 1.18 9
1.07 ± 0.23 9
1.36 ± 0.17 9
0.99 ± 0.22 tf
2.25 ± 0.65 cf
(not given)
Servos et al.
(1994)
Catostomus commersoni
white sucker
mean = 6.1
(1.4 to 21.8, 39 obs)
USEPA (1992)
Catostomus commersoni
white sucker
mean = 4.3 (0.2
to 12.0, 4102 obs)
mean = 1.7
(0.2 to 9.1, 586 obs)
STORET
Catostomus commersoni
white sucker
mean = 2.32
(standard error =
0.069, 157 obs)
Exler (1987)
Catostomus
macrocheilus
largescale sucker
mean = 6.7 (0.3
to 13.0, 752 obs)
mean = 1.6 (0.1 to
5.26, 482 obs)
STORET
Catostomus occidentalis
Sacramento sucker
mean = 9.8
(1.7 to 18.5, 3 obs)
USEPA (1992)
Cottus cognatus
sculpin (FW)
8 (5.4 a)
USEPA (1994)
Cyprinus carpio
carp
9 (15 g)
Cook et al.
(1991)
Cyprinus carpio
carp
18.7 (69.5 g)
15.7 (56.0 g)
13.0 (37.5 g)
16.6 (36.5 g)
17.5 (29.0 g)
Kuehl et al.
(1987)
Cyprinus carpio
carp
mean = 9.3
(0.5 to 25.1, 145
obs)
mean = 9.0
(2.0 to 19.6, 6 obs)
USEPA (1992)
Cyprinus carpio
carp
mean = 6.5 (0.3
to 17.0, 70002 obs)
mean = 4.3
(0.02 to 21.6, 16139
obs)
STORET
Cyprinus carpio
carp
mean = 5.60
(standard error =
0.207, 163 obs)
Exler (1987)
B-22
-------
Table B-4a. (continued)
Species Name
Common Name
Whole Fish Lipid
Content,
Percent (size )
Fillet Lipid
Content, Percent
(size)
Reference,
Comments
Enmyzon oblongus
creek chubsucker
mean = 3.9
(3.9 to 4.0, 3 obs)
US EPA (1992)
Hypentehum nigricans
northern hogsucker
mean = 4.4 (0.8
to 8.98, 637 obs)
mean = 0.7 (0.5 to
0.99, 70 obs)
STORET
Icialurus furcatus
blue catfish
mean = 7.3
(5.3 to 10.4, 5 obs)
mean = 2.7
(2.0 to 3.0, 4 obs)
USEPA (1992)
Ictalurus furcatus
blue catfish
mean = 6.0
(1.5 to 12.0, 56 obs)
STORET
Icialurus melus
(Ameiurus melas)
black bullhead
mean = 2.9
(0.9 to 6.2, 911 obs)
mean = 1.4
(0.15 to 5.1, 573
obs)
STORET
Icialurus natalis
(Ameiurus natalis)
yellow bullhead
mean = 2.8 (0.5
to 7.5, 235 obs)
mean = 0.96 (0.1 to
3.2, 294 obs)
STORET
Ictalurus nebulosus
(Ameiurus nebulosus)
brown bullhead
mean = 22 (1.3
to 4.1, 133 obs)
mean = 1.5 (0.4 to
3.3, 107 obs)
STORET
Ictalurus punctatus
channel catfish
mean = 9.8
(3.4 to 23.0, 22 obs)
mean = 5.1
(1.1 to 11.5, 17 obs)
USEPA
(1992)
Ictalurus punctatus
channel catfish
mean = 7.1 (0.3
to 15.0, 7512 obs)
mean = 5.1 (0.2 to
17.3, 20655 obs)
STORET
Ictalurus punctatus
channel catfish
mean = 4.26
(standard error =
0.417, 59 obs)
Exler (1987)
Ictiobus bubalus
smaJlmouth buffalo
mean = 5.7
(2.2 to 11.9, 6 obs)
USEPA (1992)
Ictiobus bubalus
smallmouth buffalo
mean = 9.7 (2.8
to 17.3, 886 obs)
mean = 4.8 (0.2 to
14.5, 595 obs)
STORET
Ictiobus cyprinellus
bigmouth buffalo
mean =15.1
(5.7 to 22.6, 3 obs)
USEPA (1992)
Ictiobus cyprinellus
bigmouth buffalo
mean = 5.8 (0.4 to
16.2, 675 obs)
mean = 4.1 (0.3 to
15, 1678 obs)
STORET
Ictiobus niger
black buffalo
mean = 3.5 (1.2 to
7.1, 42 obs)
STORET
Minytrema melanops
spotted sucker
mean = 4.5
(0.9 to 7.4, 9 obs)
USEPA (1992)
B-23
-------
Mrfj rpp ^^fgfgOTTON
Table B-4a. (continued)
Species Name
Common Name
Whole Fish Lipid
Content,
Percent (size )
Fillet Lipid
Content, Percent
(size)
Reference,
Comments
Minytrema melartops
spotted sucker
mean = 3.7 (0.7 to
5.9, 188 obs)
mean = 1.5 (0.9 to
3.2, 197 obs)
STORET
Moxostoma amsurum
silver redhorse
mean = 8.2 (6.2
to 8.5, 180 obs)
mean = 2.1 (1.3 to
2.7, 7 obs)
STORET
Moxostoma carinatum
river redhorse
mean = 51 (1.9
to 5.9, 193 obs)
mean = 1 3 (0.5 to
2.4, 170 obs)
STORET
Moxostoma duquesnei
black redhorse
mean = 5.0 (0.3
to 9.7, 1774 obs)
mean = 0.97 (0.7 to
1.8, 58 obs)
STORET
Moxostoma erythrurum
golden redhorse
mean = 6.0
(0.8 to 16.1, 2018
obs)
mean = 1.8 (0.6 to
2.8, 154 obs)
STORET
Moxostoma
macrolepidotum
shorthead redhorse
mean = 19.8 (10.8
to 31.9, 4 obs)
US EPA (1992)
Moxostoma
macrolepidotum
shorthead redhorse
mean = 6.5 (0.4
to 10.9, 683 obs)
mean = 3.0 (1.4 to
13.5, 342 obs)
STORET
Mugil cephalus
striped mullet
mean = 3.79
(standard error =
0.357, 43 obs)
Exler (1987)
Mylocheilus caurinus
peamouth
mean = 11.0 (9.36
to 12.91, 162 obs)
STORET
Ptychocheilus oregoni
northern squawfish
mean = 5.6 (0.8
to 12.0, 812 obs)
mean = 1.3 (0.7 to
3.0, 117 obs)
STORET
Ptychocheilus
squawfish
mean = 2.2
(0.5 to 3.0, 7 obs)
US EPA
(1992)
Scaphirhynchus
platorhynchus
shovelnose sturgeon
mean = 7.4 (1.1 to
20.3, 392 obs)
STORET
B-24
-------
Table B-4b. Lipid Contents of Trophic Level 3, Pelagic Fishes
Species Name
Common Name
Whole Fish Lipid
Content,
Percent (size )
Fillet Lipid
Content, Percent
Reference,
Comments
Acipenser sp
sturgeon (unknown)
mean = 4.04 (7 obs)
Exler (1987)
Acrocheilus aluiaceus
chiselmouth
mean = 5.0
(3.2 to 6.8, 47 obs)
mean = 0.55
(0.19 to 1.00, 91
obs)
STORET
Alosa pseudoharengus
alewife
7 (32 g)
USEPA (1994)
Alosa pseudoharengus
alewife
mean = 89
(3.7 to 15.2, 128
obs)
STORET
Alosa sapidissima
American shad
mean = 6.55 (5.9 to
7.6, 270 obs)
STORET
Alosa sapidissima
American shad
mean = 13.77
(standard error =
1.00, 11 obs)
Exler (1987)
Anguilla rostrata
American eel
mean = 11.66,
standard error =
0.885, 14 obs)
Exler (1987)
Aplodinotus grunniens
freshwater drum
mean = 5.5 (1.0
to 19.7, 574 obs)
mean = 4.8 (0.3 to
21.2, 459 obs)
STORET
Archosargus
probatocephalus
sheepshead
mean = 2.41
(standard error =
0.040, 5 obs)
Exler (1987)
Coregonus artedii
Cisco (lake herring)
mean =1.91
(standard error =
0.149, 69 obs)
Exler (1987)
Coregonus clupeaform
lake whitefish
mean = 5.86
(standard error =
0.451, 68 obs)
Exler (1987)
Coregonus hoyi
bloater
mean = 21.1 (16
to 25.5, 52 obs)
mean = 8.3 (3.2 to
17.0, 98 obs)
STORET
Dorosoma cepedianum
gizzard shad
mean = 7.4 (1.3 to
18.0, 189 obs)
STORET
Dorosoma petenense
threadfin shad
mean = 3.0
(0.5 to 18.0, 9 obs)
STORET
Gadus macrocephalus
true or Pacific cod
mean = 0.63
(standard error =
0.031, 18 obs)
Exler (1987)
B-25
-------
Table 4b. (continued)
Species Name
Common Name
Whole Fish Lipid
Content.
Percent (size )
Fillet Lipid
Content, Percent
Reference,
Comments
Hiodon alosoides
goldeye
mean = 3.2 (3.5 to
2.8, 74 obs)
STORET
Platygobia (Hybopsis in
database) gracilis
flathead chub
mean = 3.3 (0.68 to
8.14, 75 obs)
STORET
Lepomis aurms
redbreast sunfish
mean = 3.6 (1.3
to 8.1, 550 obs)
STORET
Lepomis cyanellus
green sunfish
mean = 3.2 (2.2
to 7 8. 376 obs)
STORET
Lepomis gibbosus
pumpkinseed
mean = 3.9
(2.2 to 7.7, 126 obs)
STORET
Lepomis gibbosus
pumpkinseed
mean = 0.70
(standard error =
0.071, 8 obs)
Exler (1987)
Lepomis megalotis
longear sunfish
mean = 2.8 (1.0
to 7.2, 536 obs)
STORET
Osmerus mordax
rainbow smelt
4 (16 g)
USEPA (1994)
Osmerus mordax
rainbow smelt
mean = 2.42
(standard error =
0.107, 52 obs)
Exler (1987)
Pimephales promelas
fathead minnow
19 (1 g)
Cook et al.
(1991)
Lepomis macrochirus
bluegill sunfish
mean = 3.5
(2.4 to 4 6, 4 obs)
USEPA
(1992)
Lepomis macrochirus
bluegill sunfish
mean = 4.4 (0.1
to 8.7, 1034 obs)
STORET
Lota lota
burbot
0.35 to 0.7
Owens et al.
(1994)
Lota lota
burbot
mean = 0.2 (0.1 to
0.3, 18 obs)
STORET
Lota lota
burbot
mean = 0.81
(standard error -
0.059, 13 obs)
Exler (1987)
Oryzias latipes
medaka
8(0.175 g)
Schmieder et
al. (1992)
B-26
-------
Table 4b. (continued)
Species Name
Common Name
Whole Fish Lipid
Content,
Percent (size )
Fillet Lipid
Content, Percent
Reference,
Comments
Phoxmus erythrogaster
southern redbelly dace
mean = 5.6 (2.2
to 10.0. 762 obs)
STORET
Pomoxis annularis
white crappie
mean = 1.0 (0.5 to
2.0, 7 obs)
USEPA (1992)
Pomoxis annularis
white crappie
mean = 2.1 (0.4
to 5.8, 622 obs)
mean = 0.4 (0.08 to
2.6, 936 obs)
STORET
Pomoxis nigromaculatus
black crappie
mean =1.1 (0.5 to
1.5, 3 obs)
USEPA
(1992)
Pomoxis nigromaculatus
black crappie
mean = 2.7 (0.7
to 8.4, 457 obs)
mean = 1.4 (0.13 to
5.3, 118 obs)
STORET
Prosopium williamsoni
mountain whitefish
mean = 8.5 (0.5
to 13.8, 327 obs)
mean = 1.6, (0.2 to
4.1, 532 obs)
STORET
Prosopium williamsoni
mountain whitefish
3.4 to 11.8
(not given)
Owens et al.
(1994)
Richardsonius balteatus
redside shiner
mean = 0.9 (0.85 to
0.96, 50 obs)
STORET
Sebastes aunculatus
brown rockfish
mean = 1.57 (81
obs)
Exler (1987)
Sebastes marinus
redfish
mean = 1.63
(standard error =
0.092, 208 obs)
Exler (1987)
Semotilus atromacula
creek chub
mean = 3.9 (1.0
to 5.0, 815 obs)
STORET
Semoiilus corporalis
fallfish
mean = 1.9 (0.25
to 3.9, 100 obs)
STORET
B-27
-------
Table B-4c. Lipid Contents of Trophic Level 4, Epibenthic Fishes
Species Name
Common Name
Whole Fish Lipid
Content,
Percent (size)
Fillet Lipid
Content, Percent
Reference,
Comments
Pylodictis olivaris
flathead catfish
mean = 3.1 (0.5
to 8.1, 829 obs)
mean = 3.0 (0.2 to
21.1, 1315 obs)
STORET
Pylodicns olivaris
flathead catfish
mean =60
(1.6 to 8.7, 3 obs)
mean = 1.9
(0.6 to 3.1, 4 obs)
US EPA (1992)
Table B-4d. Lipid Contents of Trophic Level 4, Pelagic Fishes
Species Name
Common Name
Whole Fish Lipid
Content,
Percent (size)
Fillet Lipid
Content, Percent
(size)
Reference,
Comments
Ambloplites rupestris
rock bass
mean = 1.0
(0.8 to 1.2, 3 obs)
US EPA (1992)
Ambloplites rupestris
rock bass
mean = 2.3
(0.6 to 4.4, 759 obs)
mean = 0.7
(0.4 to 0.98, 129
obs)
STORET
Amia calva
bowfin
mean = 0.5
(0.04 to 1.4,
230 obs)
STORET
Centropristis striata
black sea bass
mean = 2.00
(standard error =
0.221, 40 obs)
Exler (1987)
Esox lucius
northern pike
mean = 1.4
(0.6 to 2.6, 5 obs)
USEPA (1992)
Esox lucius
northern pike
mean = 1.9
(0.1 to 9.8, 810 obs)
STORET
Esox lucius
northern pike
mean = 0.69
(standard error =
0.005, 224 obs)
Exler (1987)
Esox niger
chain pickerel
mean = 1.3
(0.6 to 2.0, 5 obs)
USEPA (1992)
Leiostomus xanthurus
spot
mean = 5.2
(3.3 to 7.9, 300 obs)
STORET
Leiostomus xanthurus
spot
mean = 4.90
(standard error =
2.93, 10 obs)
Exler (1987)
B-28
-------
N6S«gQR^Smi-BW?ieN^
Table 4d. (continued)
Species Name
Common Name
Whole Fish Lipid
Content,
Percent (size)
Fillet Lipid
Content, Percent
(size)
Reference,
Comments
Lutjanus campechanus
red snapper
1.34 (55 obs)
Exler (1987)
Micropogonias
undulatus
Atlantic croaker
3.17 (standard error
= 0.529, 8 obs)
Exler (1987)
Micropterus dolomieu
smallmouth bass
mean = 1.6
(0.8 to 4.4, 19 obs)
US EPA
(1992)
Micropterus dolomieu
smallmouih bass
mean = 3.4 (0 3
to 8.8, 1166 obs)
mean = 0.6 (0.01 to
2.3, 848 obs)
STORET
Micropterus punctulatus
spotted bass
mean = 2.8 (0.9 to
4.5, 4 obs)
US EPA (1992)
Micropterus punctualius
spotted bass
mean = 2.4 (0.6
to 4.9, 322 obs)
mean = 0.7 (0.1 to
1.8, 353 obs)
STORET
Micropterus salmoides
largemouth bass
mean = 1.6
(0.4 to 7.6, 54 obs)
USEPA (1992)
Micropterus salmoides
largemouth bass
mean = 4.1 (0.3 to
10.6, 2924 obs)
mean = 0.7 (0.04
to 9.2, 4548 obs)
STORET
Morone amencana
white perch
mean = 4.5 (2.6 to
7.1, 249 obs)
STORET
Morone chrysops
white bass
mean = 2.7
(0.7 to 4.8, 11 obs)
USEPA
(1992)
Morone chrysops
white bass
mean = 46 (0.3 to
15.4, 615 obs)
mean = 3.9
(0.01 to 8.1, 847
obs)
STORET
Morone saxatilis
striped bass
mean = 2.33
(standard error =
0.381, 14 obs)
Exler (1987)
Oncorhynchus
gorbuscha
pink salmon
mean = 3.45
(standard error =
0.141, 144 obs)
Exler (1987)
Oncorhynchus kisutch
coho salmon
mean = 2.7 (0.4 to
10.7, 383 obs)
STORET
Oncorhynchus kisutch
coho salmon
mean = 5.92
(standard error =
0.162, 217 obs)
Exler (1987)
Oncorhynchus mykiss
rainbow trout
11 (35 g)
Branson et al.
(1985)
B-29
-------
FHP
Table 4d. (continued)
Species Name
Common Name
Whole Fish Lipid
Content,
Percent (size)
Fillet Lipid
Content, Percent
(size)
Reference,
Comments
Oncorhynchus mykiss
rainbow trout
mean = 5.0
(4.1 to 5.6, 3 obs)
US EPA (1992)
Oncorhynchus nerka
sockeye salmon
mean = 8.56
(standard error =
0.392, 48 obs)
Exler (1987)
Oncorhynchus
tshawytscha
chinook salmon
mean = 3.7 (2.4 to
5.1, 52 obs)
mean = 2.2
(0.04 to 17.7, 1957
obs)
STORET
Oncorhynchus
tshawytscha
Chinook salmon
mean = 10.44
(standard error =
1.692, 10 obs)
Exler (1987)
Perca flavescens
yellow perch
mean = 3.6 (1.2 to
9.1, 112 obs)
mean = 0.5 (0.1 to
4.6, 280 obs)
STORET
Pomatomus saltatrix
bluefish
mean = 4.27 (3 obs)
Exler (1987)
Salmo clarki
(Onchorhynchus clarki)
cutthroat trout
mean = 1.0 (0.2 to
1.7, 378 obs)
STORET
Salmo gairdneri
(Onchorhynchus mykiss)
rainbow trout
mean = 3.36
(standard error =
0.256, 24 obs)
Exler (1987)
Salmo salar
Atlantic salmon
mean = 6.34
(standard error =
1.72, 7 obs)
Exler (1987)
Salmo trutta
brown trout
mean = 4.0
(1.6 to 8.1, 6 obs)
USEPA
(1992)
Salmo trutta
brown trout
mean = 6.0 (1.5 to
8.9, 112 obs)
mean = 5.0 (0.14
to 14.8, 741 obs)
STORET
Salvelinus namaycush,
Oncorhynchus mykiss,
Oncorhynchus spp.
salmonids
11 (2410 g)
USEPA (1994)
Salvelinus malma
Dolly Varden
mean = 7.1
(2.1 to 9.9, 3 obs)
USEPA (1992)
Salvelinus namaycush
lake trout
mean = 15.9 (12.6
to 18.3, 42 obs)
mean = 7.8 (2.5 to
20.0, 1883 obs)
STORET
Scomberomorus cavall
king mackerel
mean = 2.00
(standard error =
0.188, 6 obs)
Exler (1987)
B-30
-------
Table 4d. (continued)
Species Name
Common Name
Whole Fish Lipid
Content,
Percent (size)
Fillet Lipid
Content, Percent
(size)
Reference,
Comments
Scomberomorus macula
Spanish mackerel
mean = 6.30
(standard
error=3.810, 3 obs)
Exler (1987)
Slizosiedion canadense
sauger
mean = 6.0 (0.8
to 16.3, 139 obs)
mean = 1.7 (0.3 to
10.0. 195 obs)
STORET
Stizostedion vitreum
walleye
0.6 to 0.7
Owens et al.
(1994)
Stizostedion vitreum
walleye
mean = 6.2 (0.3 to
15, 1089 obs)
mean = 1.3 (0.3 to
6.0, 440 obs)
STORET
Stizostedion vitreum
walleye
mean = 1.22
(standard error =
0.162, 14 obs)
Exler (1987)
Stizostedion vitreum
vitreum
walleye
mean =1.6
(0.7 to 2.6, 13 obs)
USEPA (1992)
B.3.1.3 USDA Report on Composition of Foods
A summary of a relatively small database on the composition of fish and shellfish foods and food
products was available from USDA (Dickey, 1990). The section on fish and shellfish in the
report coordinated by Dickey (1990) came from an earlier USDA report by Exler (1987). Data
presented by Exler (1987) for various fish species were summarized from the USDA's Nutrient
Data Bank (NDB). Records in the NDB are based primarily on published scientific reports and
technical journal articles. To a lesser extent, the NDB contains unpublished data from industrial,
government, and academic institutions under contract with the Human Nutrition Information
Service. Lipids data are given in percentage of edible portion, where "edible portion" is the
part of food customarily considered edible in the United States. Records were available for 32
fishes (Table B-4). These were entered under the column "fillet."
B.3.2 Analysis of Lipids Data
Lipids data were analyzed for comparison with the values selecting for the NSI evaluation by
computing averages. Eight averages of data for fishes of the following categories for data in
STORET (Table B-5a) and the NSCRF (Table B-5b) were computed (and labeled A-H):
B-31
-------
Table B-5a. Lipid Analysis - STORET
Analysis
Matrix of Fishes Included in Average
Tissue/
Organ
Lipid Content, %
Trophic Level
Position in Water
Column
Mobility
Habitat
Mean
Standard
Error
Number
of
Obser-
vations
Range
3
4
Demer-
sal
Pelagic
Resi-
dent
Migra-
tory
Fresh-
water
Salt-
water
A
•
•
•
•
a
•
•
•
whole
5.97
113,978
0.1-
26.7
B
•
•
•
•
•
•
whole
5.97
0.010
110,998
0.1-
26.7
C
•
•
•
•
•
•
fillet
2.5
13,293
0.01-
20
D
•
•
•
•
fillet
0.753
0.010
6793
0.01-
10
E
•
•
•
•
•
whole
6.33
0.011
91867
0.22-
26.7
F
•
•
•
•
•
whole
3.757
0.020
13025
0.10-
16.3
G
•
•
•
•
•
fillet
4.49
0.018
42687
0.02-
24
H
•
•
•
•
•
fillet
1.06
0.021
9378
0.01-
21.07
B-32
-------
JMQ3i»EeR»B< STP liBilil.T.LUN
Table B-5b. Lipid Analysis - NSCRF
Analysis
Matrix of Fishes Included in Average
Tissue/
Organ
Lipid Content, %
Trophic Level
Position in Water
Column
Mobility
Habitat
Mean
Standard
Error
Number
of
Obser-
vations
Range
3
4
Demer-
sal
Pelagic
Resi-
dent
Migra-
tory
Fresh-
water
Salt-
water
A
•
•
•
•
•
•
•
•
whole
8.5
249
0.5-
31.9
B
•
•
•
•
•
•
whole
8.6
0.328
246
0.5-
31.9
C
•
•
•
•
•
•
fillet
1.9
122
0.4-
8.1
D
•
•
•
•
fillet
1.6
0.116
103
0.4-
7.6
E
•
•
•
•
•
whole
8.8
0.338
233
0.5-
31.9
F
•
•
•
•
•
whole
4.6
1.02
7
1.6-
8.7
G
•
•
•
•
•
fillet
4.9
0.697
34
0.5-
19.6
H
•
e
•
•
•
fillet
1.6
0.106
117
0.4-
7.6
B-33
-------
Ne'p^f^sTR'mtmeN'
A. Trophic levels 3 and 4, whole body
B. Trophic levels 3 and 4, whole body, excluding migratory and saltwater fishes
C. Trophic level 4, pelagic, fillet
D. Trophic level 4, pelagic, fillet, excluding migratory and saltwater fishes
E. Resident, freshwater, demersal fishes, whole body
F. Resident, freshwater, pelagic fishes, whole body
G. Resident, freshwater, demersal fishes, fillet
H. Resident, freshwater, pelagic fishes, fillet.
Samples for fillets and whole fish were kept separate. All analyses except "A" were of fishes
in the NSI exclusively. Summary statistics reported include the mean, standard error, range,
and number of observations. The matrix in Tables B-5 a, b indicates the categories of fishes
averaged. The average of edible portions from USDA data was 4.1 percent lipid.
B-34
-------
B.4 References
Ankley, G.T., P.M. Cook, A.R. Carlson, D.J. Call, J.K. Swenson, H.F. Corcoran, and R.A.Hoke.
1992. Bioaccumulation of PCB from sediments by oligochates and fishes. Can. J. Fish
Aquat. Sci. 49:2080-2085.
Branson, D.R., I.T. Takahashi, W.M. Parker, and G.E. Blau. 1985. Bioconcentration of 2,3,7,8-
tetrachlorodibenzo-p-dioxin in rainbow trout. Environ. Toxicol. Chem. 4:779-788.
Cook, P.M., D.M. Kuehl, M.K. Walker, and R.E. Petersen. 1991. Bioaccumulation and toxicity
of TCDD and related compounds in aquatic ecosystems. Banbury Report 35: Biological
basis for risk assessment of dioxins and related compounds, pp. 143-167. Cold Spring
Harbor Laboratory Press, Plainview, NY.
Cook, P.M., G.T. Ankley, R.J. Erickson, B.C. Butterworth, S.W. Kohlbry, P. Marquis, and H.
Corcoran. 1994. The biota-sediment accumulation factor (BSAF): evaluation and
application to assessment of organic chemical bioaccumulation in the Great Lakes. (In
preparation).
Cook, P.M. 1995. Pelagic BSAFs for NSI methodology. Memorandum from P. M. Cook, ERL,
Duluth, to C. Fox, EPA, Office of Water, March 29, 1995.
Dickey, L.E. 1990. Composition of foods, raw, processed, prepared—1990 supplement.
Agriculture Handbook No. 8, 1990 Supplement. U.S. Department of Agriculture, Human
Nutrition Information Service.
Esser, H.O. 1986. A review of the correlation between physicocherhical properties and
bioaccumulation. Pestic. Sci. 17:265-276. (as cited by Randall et al., 1991).
Exler, J. 1987. Composition of foods: Finfish and shellfish products. Agriculture Handbook No.
8-15. U.S. Department of Agriculture, Human Nutrition and Information Service.
Flint, R.W. 1986. Hypothesized carbon flow through the deep water Lake Ontario food web.
J. Great Lakes Res. 12:344-354.
Hansen. 1995. Assessment tools that can be used for the National Sediment Inventory.
Memorandum from D.J. Hansen, ERL, Narragansett, to C. Fox, Office of Water, February
28, 1995.
Karickhoff, S.W., D.S. Brown, and T.A. Scott. 1979. Sorption of hydrophobic pollutants on
natural sediments. Water Res. 13: 241-248.
B-35
-------
mot FerrCTSTCreOT'roN"*-
Kuehl, D.W., P.M. Cook, A.R. Batterman, D.B. Lothenbach, and B.C. Butterworth. 1987.
Bioavailability of polychlorinated dibenzo-p-dioxins and dibenzofurans from contaminated
Wisconsin River sediment to carp. Chemosphere 18:1997-2014.
Oliver, B.G., and A.J. Niimi. 1988. Trophodynamic analysis of polychlorinated biphenyl
congeners and other chlorinated hydrocarbons in the Lake Ontario ecosystem. Environ.
Sci. Technol. 22:388-397.
Owens, J.W., S.M. Swanson, and D.A. Birkholz. 1994. Bioaccumulation of 2,3,7,8-
tetrachlorodibenzo-p-dioxin, 2,3,7,8-tetrachlorodibenzofuran and extractable organic
chlorine at a bleached kraft mill site in a northern Canadian river system. Environ.
Toxicol. Chem. 13:343-354.
Randall, R.C., H. Lee II, R.J. Ozretich, J.L. Lake, and R.J. Pruell. 1991. Evaluation of selected
lipid methods for normalizing pollutant bioaccumulation. Environ. Toxicol. Chem.
10:1431-1436.
Schmeider, P., D. Lothenbach, R. Johnson, R. Erickson, and J. Tietge. 1992. Uptake and
elimination kinetics of 3H-TCDD in medaka. Toxicologist 12:138.
Servos, M.R., S.Y. Huestis, D.M. Whittle, G.J. Van Der Kraak, and K.R. Munkittrick. 1994.
Survey of receiving-water environmental impacts associated with discharges from pulp
mills. 3. Polychlorinated dioxins and furans in muscle and liver of white sucker
{Catostomus commersoni). Environ. Toxicol. Chem. 13:1103-1115.
USEPA. 1990. Lake Ontario TCDD bioaccumulation study—Final report. U.S. Environmental
Protection Agency, Region 2, New York, NY.
USEPA. 1992. National study of chemical residues in fish. 2 vols. EPA 823-R-92-008a,b. U.S.
Environmental Protection Agency, Office of Science and Technology, Washington, DC.
USEPA. 1994a. Great Lakes Water Quality Initiative technical support document for the
procedure to determine bioaccumulation factors—July 1994. EPA-822-R-94-002. U.S.
Environmental Protection Agency, Office of Water, Office of Science and Technology,
Washington, DC.
USEPA, 1994b. Health effects assessment summary tables FY 1994. Supplement number 2.
EPA/540/R-94/114, NTIS PB94-921102. U.S. Environmental Protection Agency, Office
of Solid Waste and Emergency Response, Washington, DC. November.
B-36
-------
USEPA, 1995. Integrated Risk Information System (IRIS). Online. U.S. Environmental
Protection Agency, Office of Health and Environmental Assessment, Environmental
Criteria and Assessment Office, Cincinnati, OH.
USEPA and USCOE. 1994. Evaluation of dredged material proposed for discharge in waters of
the U.S.—Testing Manual. Draft. EPA-823-B-94-002. Department of the Army, U.S. Army
Corps of Engineers, and U.S. Environmental Protection Agency.
B-37
-------
Appendix C
Threshold Values for Chemicals Subject to Evaluation
Appendix C presents the threshold values used in the evaluation of NSI sediment chemistry data.
Values listed in this table are in parts per million (ppm) except for the values for EPA sediment
quality critieria (SQC^) and sediment quality benchmarks (SQB^), which are in micrograms per
gram (|ig/g) organic carbon. These values were multiplied by the organic carbon content (f^)
of the sediment sample, when known, or the default value if unknown (f^ = 0.01). SQBs used
in this analysis were calculated specifically for use in the screening analysis of NSI data. These
values_were not developed for regulatory purposes and should be used with caution (if at all) for
purposes other than the evaluation of NSI data. ERLs and ERMs were taken from Long et al.
(1995). AET-L and AET-H values listed are values that have been normalized to dry weight.
AET-Ls and AET-Hs were taken from Barrick et al. (1988). TELs and PELs were taken from
FDEP (1994).
The last four columns in Appendix C present fish tissue concentrations. EPA cancer values were
calculated for both a human health cancer risk of 10"5 and a noncancer hazard quotient of 1
(USEPA, 1994, 1995). FDA action levels where obtained from the FDA. An asterisk in the
FDA Action Level column indicates that the value is a guideline, not an action level. EPA
wildlife criteria represent values based on fish consumption only. EPA wildlife values were
obtained from EPA Great Lakes Water Quality Wildlife Criteria (USEPA, 1993a).
NOTE: SQBs were still under development at the time this issue paper was distributed.
Therefore, only SQBs based on secondary chronic values (SCVs) from Suter and Mabrey
(1994) are presented in Appendix C.
C-l
-------
-------
TWFTOR°mS^PR*DlsJ.T4QM-
Appendix C. Threshold Values (ppm) for Chemicals Subject to Evaluation
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICALS
May Be Over- or Underprotective of Sediment at a Given Ixtcallon Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Fish Tissue Concentration (ppm)
SQC„
(Mg/gJ
ER-L
(ppm)
ER-M
(ppm)
AET-L
(ppm)
AET-H
(ppm)
SQB^
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 10 s
EPA Non
Cancer
Hazard
Quotient -
1
FDA
Action
Level
EPA
Wildlife
Criterion
83329
Acenaphthene
1
130
.016
.5
.5°
2'
0.007
0.089
650
208968
Acenaphlhylene
1
.044
.64
1 3*-6
1 3*-b
0006
0.128
67641
Acetone
1
1100
98862
Acclophenone
1
1100
107028
Acrolein
1
220
107131
Acrylonilrile
1
0.2
11
15972608
Alachlor/Lasso
1
1 3
110
116063
Aldicarb/Temik
11
309002
Aldrin
1
0.0063
0.32
0.3
117793
Aminoanlhraquinone,
2-
97563
Aminoazotoluene, o-
62533
Aniline
19
120127
Anthracene
1
0853
1.1
96°
13"
0 047
0.245
3200
C-3
-------
0R°P 13TR IB IffHON
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICAL
May Be Over- or Underprotective or Sediment at a Given Location Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Fish Tissue Concentration (ppm)
SQC,*
ER-L
(ppm)
ER-M
(ppm)
AET-L
(ppm)
AET-H
(ppm)
SQB.
Wsu.)
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 10!
EPA Non
Cancer
Hazard
Quotient -
1
FDA
Action
l>evel
EPA
Wildlife
Criterion
7440360
Antimony
2
25
ISO"
200*
4 3
7440382
Arsenic
2
8.2
70
57"
700°
7 24
41.6
0.062
3 2
68
1912249
Alrazine
0.49
380
92875
Benzidine
4.7E-04
32
71432
Benzene
1,4
5.7
3.7
56553
Benzo(a)anihracene
1
.261
1.6
1.6°
5.1*-"
0.075
0.693
0 15
50328
Bcnzo(a)pyrene
1
.43
1 6
1.6°
3.6"
0.089
0.763
0.015
205992
Benzo(b)fluoranlhene
1
0.15
191242
Benzo(ghi)perylene
1
.72°
2.6"
207089
Benzo(k)fluoranthene
1
1.5
65850
Benzoic acid
.65°-b
.76'
43000
106514
Benzoquinone-p
1
98077
Benzotrichloride
1
8.3E-03
100516
Benzyl alcohol
.073°
00
f
3200
100447
Benzyl chloride
1
0.63
C-4
-------
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICAL
May Be Over- or Underprotective of Sediment ut a Given location Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Fish Tissue Concentration (ppm)
SQC.,
(MgfeJ
ER-L
(ppm)
ER-M
(ppm)
AET-I,
(ppm)
AET-H
(ppm)
SQB.,
(Mgfeoc)
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 105
EPA Non
Cancer
Hazard
Quotient -
FDA
Action
Level
EPA
Wildlife
Criterion
319846
BHC, alpha-
1
0.017
319857
BHC, bcta-
1
0.060
319868
BHC, della-
1,4
13
58899
BHC, gamma-/Lindane
1.4
0.37
0.0003
0.00099
0.083
3 2
608731
BHC, technical grade
1
0.060
03
92524
Biphenyl
1.5
540
111444
Bis(2-chloroethyl)elher
1
0.098
108601
Bis(2-chloroisopropyl)
elher
1
1.5
430
117817
Bis(2-ethylhexyl)
phthalate
1,5
1 3"
1 9°
0.182
2.65
7.7
220
542881
Bis(chloromelhyl)ether
4 9E-04
35400432
Bolstar/Suprofos
1
75274
Bromodichloromelhane
1
1 7
220
74839
Bromomc thane
1
15
C-5
-------
-NQXgEQfeBfSTRIB UTIQN
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICAI.S
May Be Over- or Underprotective of Sediment at a Given location Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Fish Tissue Concentration (ppm)
SQC.,
(Mg/gJ
ER-L
(ppm)
ER-M
(ppm)
AET-L
(ppm)
AET-H
(ppm)
SQB„
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 10'
EPA Non
Cancer
Hazard
Quotient =
1
FDA
Action
Level
EPA
Wildlife
Criterion
101553
Bromophenyl phenyl
clher, 4-
1,5
620
1689845
Bromoxynil
220
23184669
Butachlor
1
123864
Butyl acetale, n-
1
85687
Butyl benzyl phlhalale
1,5
(j*.b
(J!.b
2200
7440439
Cadmium
2
1.2
96
5.1"
9.6°
0.68
4.21
5.4
3
63252
Carbaryl/Sevin
1100
1563662
Carbof uran/furadan
54
75150
Carbon disulfide
1100
786196
Carbophenothion/
Trithion
1
133904
Chloramben
160
57749
Chlordane
1,2
0 002
0.005
0.083
0.65
0.3
108907
Chlorobcnzene
1,4
82
220
510156
Chlorobenzilate
0.40
220
C-6
-------
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICALS
May Be Over- or Underprotective of Sediment at a Given Location Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Fish Tissue Concentration (ppm)
SQC,*
(Mg/gJ
ER-L
(ppm)
ER-M
(ppm)
AET-1.
(ppm)
AET-H
(ppm)
SQB.,
(Mg/fU,)
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 105
EPA Non
Cancer
Hazard
Quotient =
1
FDA
Action
I^evel
EPA
Wildlife
Criterion
74975
Chlorobromomethane
1
75003
Chloroe thane
1
4300
75014
Chloroethene
1
0 057
110758
Chloroelhylvinyl
elhcr, 2-
1
270
74873
Chloromelhane
1
83
91587
Chloronaphthalene, 2-
1
860
95578
Chlorophenol, 2-
54
7005723
Chlorophenylphenyl
ether, 4-
1
2921882
Chlorpyrifos/Dursban
1
32
7440473
Chromium
2
81
370
260"
270*
52.3
160
54
11
218019
Chrysene
1
.384
2.8
2.8°
9 2*-b
0.108
0.846
15
7440508
Copper
34
270
390°
1300*
18.7
108
400
108394
Cresol, tri-
540
95487
cresol, 0
63'°
.72"
540
C-7
-------
-MOT TOR EMSEBmimgM
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICAL
May Be Over- or Underprotective of Sediment at a Given lx>cation Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Fish Tissue Concentration (ppm)
SQC„
(Mfi/gJ
ER-L
(ppm)
ER-M
(ppm)
AET-L
(ppm)
AET-H
(ppm)
SQB,
(Mg/g-i
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 10 s
EPA Non
Cancer
Hazard
Quotient =
FDA
Action
Level
EPA
Wildlife
Criterion
106445
Cresol, p-
.67°-°'
3.6'
54
1319773
Cresols
54
98828
Cumene
1
430
21725462
Cyanazine
0.13
22
57125
Cyanide
220
110827
Cyclohexane
1
1861321
DCPA/Dacthal
1
110
72548
DDD, p, p'-
1
016"
.043'
0.001
0 008
0.45
72559
DDE, p, p'-
1,2
.0022
.027
,009b
.015'
0 002
0.004
0.32
5
50293
DDT, p. p'-
1.2
034"
.034"
0.001
0.005
0.32
54
5
DDT (Total)
1,2
.00158
0461
0.004
0.052
0.32
54
5
.00126
1163195
Decabromodiphenyl oxide
1
110
84742
Di-n-bu(yl phthalate
1,4
1 4"
1 4"
1110
1100
117840
Di-n-oc(yl phlhalale
1
6.2"
6.2"
220
95807
Diaminotoluene 2,4
C-8
-------
^^EQfe=F)IS.TPiinilTin^
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICAL
May Be Over- or Underprotective of Sediment at a Given Location Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Fish Tissue Concentration (ppm)
SQC«
(MBfeJ
ER-L
(ppm)
ER-M
(ppm)
AET-L
(ppm)
AET-H
(ppm)
SQB,
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 105
EPA Non
Cancer
Hazard
Quotient =
1
FDA
Action
Level
EPA
Wildlife
Criterion
333415
Diazinon/Speclracide
1,5
97
53703
Dibenzo(a,h)anthracene
1
.0634
.26
.23°
.97"
0.006
0.135
0.015
132649
Dibenzofuran
1,5
.54°
1.7'
43
96128
Dibromo-3-chloropropane,
1,2-
1
0 077
124481
Dibromochloromelhane
1
1.3
220
1918009
Dicamba
320
95501
Dichlorobenzene, 1,2-
1.5
0 05o,b
0.05°-b
970
541731
Dichlorobenzene, 1,3-
1,5
>. 17"'b
> 1 T"°,h
960
106467
Dichlorobenzcne, 1,4-
1,5
.11"
.12*-°
4.5
25321226
Dichlorobenzenes
1
4.5
960
91941
Dichlorobenzidine,
3,3'-
0.24
75718
Dichlorodifluoromethane
1
2200
75343
Dichloroethane 1,1-
1
1100
107062
Dichloroethane 1,2-
1
1 2
C-9
-------
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICAI.S
May Be Over- or Underprotective of Sediment at a Given Location Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Fish Tissue Concentration (ppm)
SQC«
0»g/e~)
ER-L
(ppm)
ER-M
(ppm)
AET-L
(ppm)
AET-H
(ppm)
sQB„c
(MB/g«)
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 10 s
EPA Non
Cancer
Hazard
Quotient =
I
FDA
Action
l^evel
EPA
Wildlife
Criterion
75354
Dichloroethene, 1,1-
1
0.18
97
156605
Dichlorocthene,
lians-1,2-
1
220
156592
Dichloroelhylene,
cis-1,2-
1
110
75092
DichloromeUiane
1
14
650
120832
Dichlorophenol, 2,4-
32
94751
Dichlorophenoxyacelic
acid
94757
Dichlorophenoxy acet ic
acid, 2,4-
3
110
1
94826
Dichlorophenoxybulanoic
acid, 2,4-
86
78875
Dichloropropane,
1,2-
1
1.6
542756
Dichloropropene,
1,3-
1
0.62
32
10061015
Dichloropropene,
cis-1,3-
1
C-10
-------
¦*reerTFeR»&is-TiuD utiqn
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICALS
May Be Over- or UnderprotectJve of Sediment at a Given lx>cation Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration (
Fish Tissue Concentration (ppm)
-SQC„
(Mg^g-)
ER-L
(ppm)
ER-M
(ppm)
AET-L
(ppm)
AET-H
(ppm)
SQB^
(MS/goO
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 105
EPA Non
Cancer
Hazard
Quotient =
1
FDA
Action
Level
EPA
Wildlife
Criterion
10061026
Dichloropropene,
trans-1,3-
1
120365
Dichlorprop
62737
Dichlorvos
1
0.37
54
115322
Dicofol/Kelthane
0.24
60571
Dieldnn
1,2,4
11
11
0.'0007
0.004
.0067
.54
.3
84662
Diethyl phthalate
1.4
0.2"
0.2b
63
8600
64675
Diethyl sulfate
119904
Dimethoxybenzidine,3,3'-
7.7
131113
Dimethyl phthalate
1
0 16°
0.16°
110000
75183
Dimethyl sulfide
105679
Dimelhylphenol, 2,4-
029°
,21b
220
534521
Dinitro-o-cresol, 4,6-
528290
Dinitrobenzene, 1,2-
4.3
99650
Dinitrobenzene, 1,3-
1.1
C-ll
-------
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICALS
May Be Over- or Underprotective of Sediment at a Given Location Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Fish Tissue Concentration (ppm)
SQC^
(Mg/eJ
ER-L
(ppm)
ER-M
(ppm)
AET-L
(ppm)
AET-H
(ppm)
SQB.
(Hgfe~)
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 10'
EPA Non
Cancer
Hazard
Quotient =
1
FDA
Action
l>evel
EPA
Wildlife
Criterion
100254
Dinilrobenzcne, 1,4
4.3
51285
Dinitrophenol, 2,4-
22
121142
Dinilrotolucne, 2,4-
22
606202
Dinilrotoluene, 2,6-
11
88857
Dinoseb/DNBP
11
78342
Dioxathion
1
122667
Diphenylhydrazine, 1,2-
0.13
298044
Disulfolon
1
0.43
959988
Endosulfan, alpha-
1,5
33213659
Endosulfan, beia-
1.5
115297
Endusulfan mixed isomers
1.5
65
1031078
Endosulfan sulfate
1
72208
Endnn
1.5
42
3 2
7421934
Endnn aldehyde
1
C-12
-------
«N0trmtrpiiSTRiDuiH«^
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICAL
May Be Over- or Underprotective of Sediment at a Given Location Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Fish Tissue Concentration (ppm)
SQCX
0»g/gJ
ER-L
(ppm)
ER-M
(ppm)
AET-L
(ppm)
AET-H
(ppm)
SQB„
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 109
EPA Non
Cancer
Hazard
Quotient =
FDA
Action
l^evel
EPA
Wildlife
Criterion
76131
Ethane, 1,1,2-trichloro-
1,2,2-
1
112345
Elhanol, 2-(2-Butoxyelhoxy)
563122
Ethion/Bladen
1
54
13194484
Ethoprofos
1
141786
Ethyl acetate
1
9700
100414
Ethylbenzene
1,4
01"
.037°
475
1100
106934
Ethylene dibromide
1
.0013
115902
Fensulfothion/Desanit
1
55389
Fenihion/Baytex
1
206440
Fluoranthene
1
620
.6
5.1
2.5°
30'
0 113
1.49
430
86737
Fluorene
1,5
019
54
.54°
3.6'
0.021
0.144
430
944229
Fonofos
1
22
76448
Heptachlor
1.2
0.024
54
.3
1024573
Heptachlor epoxide
1,2
0.012
0.14
.3
C-13
-------
-MMLEQB nigcmain;inp
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICALS
May Be Over- or Underprotectlve of Sediment at a Given I^ocation Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Fish Tissue Concentration (ppm)
SQC„.
(ne/gj
ER-L
(ppm)
ER-M
(ppm)
AET-L
(ppm)
AET-H
(ppm)
SQB..
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk I05
EPA Non
Cancer
Hazard
Quotient =
FDA
Action
I^vel
EPA
Wildlife
Criterion
118741
Hexachlorobenzene
1
022"
.23°
0.067
8.6
87683
Hexachlorobuladiene
1
.01 lb
.27°
1.4
2.2
74474
Hexachlorocyclopentadiene
1
75
67721
Hexachloroe thane
1,5
77
11
680319
Hexameihylphospharamid
51235042
Hexazinone
1
360
123319
Hydroquinone
430
193395
Indeno( 1,2,3-cd)pyrene
1
69°
2.6"
0.15
78591
Isophorone
1
110
2200
33820530
Isopropalin
160
67630
Isopropanol
120581
Isosafrole
1
7439921
Lead
2
46.7
218
450b
660*-°
30.2
112
1.3
121755
Malathion
1,5
220
108316
Maleic anhydnde
1100
C-14
-------
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICAL
May Be Over- or Underprotective of Sediment at a Given Location Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Fish Tissue Concentration (ppm)
SQC..
(Mg/gJ
ER-L
(ppm)
ER-M
(ppm)
AET-L
(ppm)
AET-H
(ppm)
SQB,*.
(mk/k»,
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 105
EPA Non
Cancer
Hazard
Quotient =
1
FDA
Action
Level
EPA
Wildlife
Criterion
7439976
Mercury
15
71
59°
2 I*-"
0 13
0.70
3.2
.0143
72435
Mclhoxychlor
1,5
54
78933
Methyl ethyl ketone
1
6500
108101
Methyl isobutyl ketone
1
860
22967926
Methyl Mercury
2
1
120718
Methyl-o-anisidine, 5-
91576
Methylnaphthalene, 2-
1
.07
.67
67°
1.9"
0.020
0.201
21087649
Metribuzin
270
7786347
Mevlnphos/Phosdnn
1
2385855
Mirex/Dechlorane
1,2
0.060
2.2
0 1
91203
Naphthalene
1,4
.16
2.1
2.1°
2.7"
146
0.035
0.391
430
134327
Naphthylamine, 1-
91598
Naphthylamine, 2-
8.3E-4
7440020
Nickel
2
20.9
51.6
>140"-b
>140"-b
15.9
42.8
220
70
99592
Nitro-o-ansidine, 5
C-15
-------
NQtHgQR^Smify-lXlQM
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICALS
May Be Over- or Underprotective of Sediment at a Given Location Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Fish Tissue Concentration (ppm)
SQC^
(Mg/g-)
ER-L
(ppm)
ER-M
(ppm)
AET-L
(ppm)
AET-H
(ppm)
SQB..
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 10 s
EPA Non
Cancer
Hazard
Quotient =
FDA
Action
Level
EPA
Wildlife
Criterion
98953
Nitrobenzene
5.4
92933
Nilrobiphenyl, 4-
1836755
Nitrofen/TOK
88755
Nitrophenol, 2
100027
Nilrophenol, 4
670
924163
Nitrosodi-n-butylamine,
N-
0.020
621647
Nitrosodi-n-propylamine,
N-
0.015
55185
Nitrosodmiethylamine,
N-
0.0021
86306
Nitrosodiphenylamine,
N-
,028b
.13°
22
100754
Nitrosopipendine
101804
Oxydianiline, 4,4'-
59507
Parachlorometacresol
56382
Parathion ethyl
65
C-16
-------
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICAL
May Be Over- or Underproleclive of Sediment at a Given lx>cation Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Fish Tissue Concentration (ppm)
SQC«
(Mg/gJ
ER-L
(ppm)
ER-M
(ppm)
AET-L
(ppm)
AET-H
(ppm)
SQB„
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 10 s
EPA Non
Cancer
Hazard
Quotient =
1
FDA
Action
I>evel
EPA
Wildlife
Criterion
298000
Paralhion methyl
12674112
PCB-1016
1
.0227
.180
1.0"
3 1"
0.022
0.189
0014
0 75
2
.0231
11104282
PCB-1221
1
.0227
.180
1.0"
3 1'
0.022
0 189
0014
2
.0231
11141165
PCB-1232
1
0227
.180
1.0"
3.1*
0.022
0.189
0.014
2
.0231
53469219
PCB-1242
1
.0227
.180
1.0"
3 1"
0.022
0 189
.0014
Jl
.0231
12672296
PCB-1248
1
.0227
.180
1 0"
3.1*
0 022
0.189
0014
2
.0231
11097691
PCB-1254
1
.0227
.180
1.0"
3 1*
0.022
0.189
0014
0 22
2
0231
11096825
PCB-1260
1
.0227
180
1.0"
3.1*
0.022
0.189
0.014
2
.0231
608935
Pentachlorobenzene
1,5
8.6
82688
Pentachloromuobenzene/
Quimozene
041
32
87865
Peniachlorophenol
.36'
.69"
0.90
320
72560
Perthane/Elhylan
1
85018
Phenanthrene
1
180
0.240
1.5
1 5°
6.9'
0 087
0.544
108952
Phenol
.42"
6500
C-17
-------
Ntn^TORTffsr^&yaa^N
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICAL
May Be Over- or Underprutective of Sediment at a Given Location Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Fish Tissue Concentration (ppm)
SQC«
(MR/Ro,)
ER-L
(ppm)
ER-M
(ppm)
AET-L
(ppm)
AET-H
(ppm)
SQB^
(Mg/go.)
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 10 s
EPA Non
Cancer
Hazard
Quotient =
1
FDA
Action
l^evel
EPA
Wildlife
Criterion
298022
Phorate/Famophos/Th i met
1
22
85449
Phthalic anhydride
22000
88891
Picric acid
1336363
Polychlonnatcd biphenyls
1
0.0227
0 180
1.0"
3.r
0.022
0.189
0.014
2
.0231
1610180
Prometon/Pramitol
160
7287196
Promelym/Caparol
43
23950585
Pionamide
810
1918167
Propachlor
140
129000
Pyrene
1
665
2.6
3 3°
16*-b
0.153
1 40
320
91225
Quinoline
1
9 0E-03
108463
Resorcinol
94597
Safrole
1
7440224
Silver
1
3.7
6.1*
6.1*
0 73
1.77
54
122349
Simazine
3
0.90
54
12
100425
Styrene
1
2200
C-18
-------
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICALS
May Be Over- or Underprotective of Sediment at a Given l.ocation Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Fish Tissue Concentration (ppm)
SQC«
(mb/bJ
ER-L
(ppm)
ER-M
(ppm)
AET-L
(ppm)
AET-H
(ppm)
SQB^
(fg/goc)
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 105
EPA Non
Cancer
Hazard
Quotient =
1
FDA
Action
Level
EPA
Wildlife
Criterion
13071799
Terbufos/Counter
1
0 27
886500
Tcrbulryn
11
95943
Tetrachlorobenzene,
1,2,4,5-
1
32
1746016
Tetrachlorodibenzo-p-dioxin,
2,3,7,8-
1
6 9E-7
.00000077
51207319
Tetrachlorodibenzofuran,
2,3,7,8-
1
79345
Tetrachloroe thane,
1,1,2,2-
1,4
161
0.54
25322207
Telrachloroethanc, NOS
1
127184
Tetrachloroethene
1,4
.057"
.14°
53
2 1
110
56235
Tetrachloromethane/Carbon
Telrachlonde
1,5
0.83
7 5
58902
Telrachlorophenol, 2,3,4,6-
320
961115
Tetrachlorvinphos/Gardona/
Stirofos
1
4.5
320
109999
Tclrahydrofuran
1
C-19
-------
rrirm.
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICAL
May Be Over- or Underprotective of Sediment at a Given 1 vocation Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Pish Tissue Concentration (ppm)
SQC^
Wb~)
ER-L
(ppm)
ER-M
(ppm)
AET-I,
(ppm)
AET-H
(ppm)
SQB^
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 10®
EPA Non
Cancer
Hazard
Quotient -
I
FDA
Action
l^evel
EPA
Wildlife
Criterion
119937
Tolidine, o-
108883
Toluene
1,4
89
22(X)
95534
Toluidine, o
8001352
Toxaphene
1,4
10
.098
75252
T ribromomeUiane/Bromoform
1,5
14
220
87616
Trichloroben/.cne, 1,2,3-
1
120821
Trichlorobenzene, 1,2,4-
1,5
.051'
.064°
110
12002481
Trichlorobenzenes
1
25323891
Tnchloroeltiane
1
71556
Trichloroethane, 1,1,1-
1,4
17
970
79005
Trichloroclhanc, 1,1,2-
1
1.9
43
79016
Trichloroelhene
1,4
215
9.8
65
75694
Trichlorofluoromethane
1
3200
52686
T richlorofon/Dylox
67663
T richloromethane/Chloroform
1
18
110
C-20
-------
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICAL
May Be Over- or Underprotective of Sediment at a Given Location Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Fish Tissue Concentration (ppm)
SQC„
0>g/g«)
ER-L
(ppm)
ER-M
(ppm)
AET-L
(ppm)
AET-H
(ppm)
SQB«
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 10 s
EPA Non
Cancer
Hazard
Quotient =
\
FDA
Action
l^evel
EPA
Wildlife
Criterion
25167822
Tnchlorophenol
95954
Tnchlorophenol, 2,4,5-
1100
88062
Trichlorophenol, 2,4,6-
98
93765
Trichlorophenoxyacctic acid,
2,4,5-
110
93721
T nchlorophenoxy propionic
acid, 2,4,5-
86
1582098
Trifluralin/Treflan
14
81
95636
Trimethylbcnzcne, 1,2,4-
1
5.4
118967
Trinitrotoluene
36
5.4
115866
Triphenyl phosphate
1
126727
Tris(2,3-dibromopropyl)
phosphate
1
51796
Urethane
108054
Vinyl acetate
1
11000
108383
Xylene, m-
1,5
220(K)
C-21
-------
Appendix C. (continued)
GUIDELINE VALUES INTENDED ONLY FOR SCREENING LEVEL HAZARD COMPARISON AMONG CHEMICALS
May Be Over- or Underprotective of Sediment at a Given location Depending on Site Specific Conditions
CAS
Number
Chemical Name
CODE
Sediment Concentration
Fish Tissue Concentration (ppm)
SQC„
(pg/eJ
ER-L
(ppm)
ER-M
(ppm)
AET-L
(ppm)
AET-H
(ppm)
SQB«
TEL
(ppm)
PEL
(ppm)
Concen.
= EPA
Risk 10 s
EPA Non
Cancer
Hazard
Quotient =
1
FDA
Action
l^evel
EPA
Wildlife
Criterion
95476
Xylene, o-
1
22000
106423
Xylene, p-
1
1330207
Xylenes
1
04"
.12°
22000
7440666
Zinc
150
410
410"
1600°
124
271
3200
Codes: 1. Chemical is a nonpolar organic.
2. FDA criterion is a guideline, not an action level
3. Fish tissue action level set by USEPA, 40 CFR 180.
4. Preliminary SQB^ developed for this chemical has not yet been reviewed.
5. SQB^ is currently being developed for this chemical
AET Criteria: a. Sediment concentration based on amphipods.
b. Sediment concentration based on benthic organisms,
o. Sediment concentration based on oysters.
C-22
-------
NOT FOP, BjSSKffilgEHQM.
C.l. References
Barrick, R., S. Becker, L. Brown, H. Beller, and R. Pastorok. 1988. Sediment quality values
refinement: 1988 update and evaluation of Puget Sound AET. Vol.1. Prepared for the
Puget Sound Estuary Program, Office of Puget Sound.
FDEP. 1994. Approach to the assessment of sediment quality in Florida coastal waters, Vol.
1. Development and evaluation of sediment quality assessment guidelines. Prepared for
Florida Department of Environmental Protection, Office of Water Policy, Tallahassee, FL,
by MacDonald Environmental Sciences Ltd., Ladysmith, British Columbia.
Long, E.£.., D.D. MacDonald, S.L. Smith, and F.D. Calder. 1995. Incidence of adverse
biological effects within ranges of chemical concentrations in marine and estuarine
sediments. Environ. Manage. 191( 1):81-97.
Suter, G.W. II, and J.B. Mabrey. 1994. Toxicological benchmarks for screening potential
contaminants of concern for effects on aquatic biota: 1994 revision. ES/ER/TM-96/R1.
Prepared for U.S. Department of Energy, Office of Environmental Restoration and Waste
Management, Washington, DC, by Oak Ridge National Laboratory, Environmental
Sciences Division, Oak Ridge, TN.
USEPA. 1993. Great Lakes Water Quality Initative criteria documents for the protection of
wildlife (proposed). EPA-822-R-93-007. U.S. Environmental Protection Agency, Office
of Science and Technology, Washington, DC.
USEPA. 1994. Health Effects Assessment Summary Tables FY 1994. Supplement Number 2.
EPA/540/R-94/114, NTIS PB94-921102. U.S. Environmental Protection Agency, Office
of Solid Waste and Emergency Response, Washington, DC. November.
USEPA. 1995. Integrated RISK Information System (IRIS). Online. U.S. Environmental
Protection Agency, Office of Health and Environmental Assessment, Environmental
Critieria and Assessment Office, Cincinnati, OH.
C-23
-------
Appendix D
Species Characteristics Related to NSI Bioaccumulation Data
Appendix D presents the species used in tissue residue analyses whose results are included in the
NSI. For each species listed. Appendix D identifies the species as being resident or migratory
(or either) and demersal or pelagic (or either) and specifies whether the species might be
consumed by humans (i.e., recreational or subsistence anglers). A species is considered either
resident or migratory if it stays predominately in one location as long as food and habitat are
available but is capable of traveling long distances to find food and suitable habitat. A species
is considered either demersal or pelagic if it spends much of its time in the water column but is
likely to feed off the bottom.
If a specks is identified as either resident or migratory, it is considered resident for the purpose
of this analysis. If a species is identified as either demersal or pelagic, it is considered demersal.
D-l
-------
D-2
-------
Appendix D. Species Characteristics Related to Tissue Residue Data
Species Code
Scientific Name
Common Name
Resident/Migratory*
Demersal/Pelagicb
Potentially Eatable
615301010400
Acanlhomysis Macropsis
Mysid Shrimp
E
E
611829010000
Acartia Spp.
Copepod (Unknown Species)
M
P
872901010000
Acipenser Spp.
Sturgeon (Unknown Species)
M
B
Y
872901010600
Acipenser Fulvescens
Lake Sturgeon
R
B
Y
872901010500
Acipenser Oxyrhynchus
Atlantic Sturgeon
M
B
Y
872901010300
Acipenser Transmonlanus
White Sturgeon
M
B
Y
877601200100
Acrocheilus Alutaceus
Cluselmouth
R
P
875503060100
Allosmerus Elongatus
Whitebait Smelt
M
P
Y
874701010200
Alosa Aestivalis
Blueback Herring
M
P
Y
874701010600
Alosa chrysochlons
Skipjack herring
M
P
Y
874701010300
Alosa mediocris
Hickory shad
M
P
Y
874701010500
Alosa pseudoharengus
Alewife
M
P
Y
874701010100
Alosa sapidissima
American shad
M
P
Y
883516020200
Ambloplites cavifrons
Roanoke bass
R
P
Y
883516020100
Amblopliles rupesuis
Rock bass
R
P
Y
877702060100
Ameiurus brunneus
Snail bullhead
R
B
Y
877702060200
Ameiums calus
While catfish
R
B
Y
877702060300
Ameiurus melas
Black bullhead
R
B
Y
877702060400
Ameiurus natalis
Yellow bullhead
R
B
Y
877702060500
Ameiurus nebulosus
Brown bullhead
R
B
Y
D-3
-------
R1 fTIOM
Appendix D. (continued)
Species Code
Scientific Name
Common Name
Resident/Migratory'
Demersal/Pelagicb
Potentially Eatable
877702060600
Ameiuius platycephalus
Ral bullhead
R
B
Y
877702060700
Ameiunis serracanlhus
Spoiled bullhead
R
B
Y
873401010100
Amla calva
Bowfin
R
E
Y
884202010200
Anarhichas dcnticulatus
Northern wolffish
R
B
Y
874101010100
Anguilla rostraia
American eel
M
P
Y
883544260100
Aplodinoius grunniens
Freshwater drum
M
E
Y
883516090100
Archoplites interruptus
Sacramento perch
R
P
Y
883543030100
Archosargus probatocephalus
Sheepshead
M
P
Y
551539010100
Arclica lslandica
Ocean quahog
R
B
Y
877718020200
Anus relis
Hardhead catfish
M
B
Y
883102040500
Artedius notospilotus
Bonehead sculpin
R
B
618102000000
Astacidae
Crayfish (family)
R
B
Y
551519010000
Astane spp.
R
B
551519011300
Asiarte undala
Waved astane
R
B
883561010100
Aslronotus ocellatus
Oscar
R
P
Y
810601051100
Astropecten vernlli
Margined seasiar
R
B
877718010100
Bagre marlnus
M
E
Y
883544030100
Bairdiella chrysoura
Silver perch
M
P
Y
550000000000
Bivalvia
Clam (order)
R
B
Y
550701160100
Brachiodonles recurvus
Hooked mussel
R
B
Y
D-4
-------
Appendix D. (continued)
Species Code
Scientific Name
Common Name
Resident/Migratory'
Demersal/Pelagic"
Potentially Eatable
874701040000
Brevoortia spp.
Menhaden (unknown species)
M
P
Y
874701040100
Brevoonia tyrannus
Atlantic menhaden
M
P
Y
618901030100
Callinectes sapid us
Blue crab
M
B
Y
618105010600
Cam bams barloni
Crayfish
R
B
Y
877601140100
Campostoma anomalum
Central stoneroller
R
E
618803010400
Cancer magister
Dungeness crab
M
B
Y
883528030300
Caran* hippos
Crevalle jack
M
P
Y
877601030100
Carassius auraius
Goldfish
R
E
870802050100
Carcharhinus obscurus
Dusky shark
M
E
Y
870802050300
Carcharhinus plumbeus
Brown shark (sandbar)
M
E
Y
877604020000
Carpiodes spp
Carpsucker (unknown species)
R
B
Y
877604020200
Carpiodes carpio
River carpsucker
R
B
Y
877604020100
Carpiodes cyprinus
Quillback
R
B
Y
877604020300
Carpiodes velifer
Highfin carpsucker
R
B
Y
877604010000
Catostomus spp.
Sucker (unknown sp)
R
B
Y
877604010500
Catostomus ardens
Utah sucker
R
B
Y
877604010100
Catostomus catostomus
Longnose sucker
R
B
Y
877604010400
Caloslomus columbianus
Bndgelip sucker
R
B
Y
877604010200
Catoslomus commersoni
White sucker
R
B
Y
877604011200
Catostomus latipinnis
Rannelmouth sucker
R
B
Y
D-5
-------
Appendix D. (continued)
Species Code
Scientific Name
Common Name
Resident/Migratory*
Demersal/Pelagicb
Potentially Ratable
877604010300
Calostomus macrocheilus
Largescale sucker
R
B
Y
877604011500
Calostomus occidentals
Sacramento sucker
R
B
Y
877604011600
Catostomus platyrhynchus
Mountain sucker
R
B
Y
877604012000
Calostomus snyderi
Klamath largescale sucker
R
B
Y
877604012100
Catostomus tahoensis
Tahoe sucker
R
B
Y
883516000000
Centrarchidae
Sunftsh family
R
P
Y
883516030100
Centrarchus macropterus
Flier
R
P
Y
883501010500
Centropomus undecimalis
Common snook
M
P
Y
883502030100
Centropnstis striata
Black sea bass
M
P
Y
900201010100
Chelydra serpentina
Snapping turtle
R
E
Y
648933000000
Chironomidae
Midge family
R
B
648960063300
Chironomus riparius
Midge
R
B
883561090100
Cichla ocellaris
Peacock cichlid
R
P
Y
885703010100
Citharichlhys sordidus
Pacific sanddab
E
B
885703011100
Citharichthys xanthostigma
Longfin sanddab
E
B
877712010200
Clarias fuscus
Wlutespotted clarias
M
B
Y
877601070100
Clinostomus lunduloides
Rosyside dace
R
P
551545020100
Corbtcula manilensis
Asiatic clam
R
B
Y
875501010800
Coregonus artedii
Cisco (lake herring)
M
P
Y
875501010600
Coregonus clupeaformis
Lake whitefish
M
P
Y
D-6
-------
Appendix D. (continued)
Species Code
Scientific Name
Common Name
Resident/Migratory'
Demersal/Pelagicb
Potentially Eatable
875501010900
Coregonus lioyi
Bloater
M
P
Y
883102000000
Coiudae
Sculpin family
R
B
Y
883102080000
Cotius spp.
Sculpin (unknown species)
R
B
883102080100
Coitus aleuticus
Coastrange sculpin
R
B
883102080700
Cottus hairdi
Mottled sculpin
R
B
883102080900
Coitus carolinae
Banded sculpin
R
B
883102080200
Coilus cognatus
Slimy sculpin
R
B
551002010000
Crassoslrea spp.
Oysters (unknown species)
R
B
Y
551002010100
Crassostrea gigas
Pacific oyster
R
B
Y
551002010200
Crassoslrea virgimca
Eastern oyster
R
B
Y
877601230100
Ctenopharyngodon idella
Grass carp
R
E
Y
877604060100
Cycleptus elongatus
Blue sucker
M
B
Y
883544010200
Cynoscion nebulosus
Spotted sea trout
R
P
Y
883544010300
Cynoscion nothus
Silver sea trout
M
P
Y
883544010400
Cynoscion regalis
Weakfish
M
P
Y
877601761400
Cyprinella lulrensis
Red shiner
R
P
877601761900
Cyprinella spiloptera
Spoifin shiner
R
P
877601000000
Cyprinidae
Carp/goldfish (hybrid)
R
E
Y
877601010100
Cyprinus carpio
Common carp
R
B
Y
871305010500
Dasyalis sahina
Atlannc stingray
M
B
Y
D-7
-------
Appendix D. (continued)
Species Code
Scientific Name
Common Name
Resident/Migratory'
Demersal/Pelagicb
Potentially Ratable
874701050100
Dorosoma cepedianum
Gizzard shad
M
P
874701050200
Dorosoma petenense
Threadfin shad
M
P
551202030100
Elllptio complanam
Freshwater clam
?
B
Y
885704040300
Eopsetta exilis
Slender sole
E
B
Y
883544120500
Equetus punctatus
Spotted drum
R
B
877604030000
Erimyzon spp.
Chubsucker (unknown species)
R
E
877604030200
Erimyzon oblongus
Creek chubsucker
R
E
877604030100
Erimyzon sucetta
Lake chubsucker
R
E
875801000000
Esocidae
Pike
R
P
Y
875801010201
Esox americanus americanus
Redfin pickerel
R
P
Y
875801010202
Esox americanus vermiculatus
Grass pickerel
R
P
Y
875801010100
Esox lucius
Northern pike
R
P
Y
875801010400
Esox masquinongy
Muskellunge
R
P
Y
875801010300
Esox niger
Chain pickerel
R
P
Y
883520016700
Ettieostoma radiosum
Orangebelly darter
R
B
883520010900
Etheostoma spectabile
Orangethroat darter
R
B
883520017600
Ethcostoma sligmaeum
Speckled darter
R
B
883520018700
Eihcosloma whipplei
Redfin darter
R
B
883520018800
Etheostoma zonale
Banded darter
R
B
880404021000
Fundulus zebrinus
Plains killifisli
R
P
D-8
-------
r^NOiP«PeffrDTSTRTgOTt0N
Appendix D. (continued)
Species Code
Scientific Name
Common Name
Resident/Migratory"
Demersal/Pelagicb
Potentially Eatable
880404021100
Fundulus olivaceus
Blackspotted lopnunnow
R
P
879103040100
Gailus macrocephalus
Pacific cod
M
E
Y
870802020100
Galeocerdo cuvier
Tiger shark
M
E
Y
880408010100
Gambusia alfinis
Western mosquitofish
R
P
883544020100
Genyonemus lineatus
White croaker
M
E
Y
877601260000
Gila spp.
Chub (unknown species)
R
E
877601261500
Gila robusta
Roundtail chub
R
E
883551020100
Girella nigricans
Opaleye
M
P
885704350100
Glyptocephalus zachi
Rex sole
E
B
551202060100
Gonidea angulala
Freshwater mussel
R
B
Y
874701000000
Glupeidae
Hernng family
M
P
Y
622003030000
Hexagenia spp.
Burrowing mayfly (unknown
species)
R
B
622003030700
Hexagenia limbaia
Mayfly
R
B
875101010100
Hiodon alosoides
Goldeye
M
P
Y
875101010200
Hiodon tergisus
Mooneye
M
P
Y
885703110200
Hippoglossina stomata
Bigmouth sole
M
B
Y
885704060100
Hippoglossoides elas
Flathead sole
M
B
Y
885704060300
Hippoglussoides platessuidcs.
American plaice
M
B
Y
616923040100
Hyulella azteca
Freshwaler ainphipod
R
E
D-9
-------
Appendix D. (continued)
Species Code
Scientific Name
Common Name
Resident/Migratory*
Demersal/Pelagic*
Potentially Ratable
877601050300
Hybognathus placiius
Plains minnow
R
P
871602010100
Hydrolagus colliei
Spotted rat fish
M
B
877604050100
Hypenlelium nigricans
Northern hog sucker
R
B
Y
875503010100
Hypomesus pretiosus
Surf smelt
M
P
Y
885704220100
Hypsopsetta guttulata
Diamond turbol
?
B
Y
877702000000
Iclaluridae
Bullhead catfish family
R
B
Y
877702010000
Ictalurus spp.
Catfish (unknown species)
R
B
Y
877702010200
Ictalurus furcalus
Blue caifish
R
B
Y
877702010500
Ictalurus punctalus
Channel catfish
R
B
Y
877604070100
Ictiobus bubalus
Smallmouth buffalo
R
E
Y
877604070200
Icliobus cyprinellus
Bigmouth buffalo
R
E
Y
877604070300
Ictiobus niger
Black buffalo
R
E
Y
883543020100
Lagodon rhomboides
Pinfish
E
P
870600000000
Lamniformes
Shark
M
P
Y
877601300100
Lavinia exilicauda
Hitch
R
P
883544040100
Leiostomus xanthums
Spot
M
P
Y
884701030100
Lepidogobius lepidus
Bay goby
R
P
873201010000
Lepisosteus spp.
Gar (unknown species)
E
P
Y
873201010200
Lepisosteus oculatus
Spotted gar
E
P
Y
873201010100
Lepisosteus osseus
Longnose gar
E
P
Y
D-10
-------
Appendix D. (continued)
Species Code
Scientific Name
Common Name
Resident/Migratory'
Demersal/Pelagic*
Potentially Eatable
873201010300
Lepisosieus platoslomus
Shortnose gar
E
P
Y
873201010500
Lepisosieus plalyrhincus
Florida gar
E
P
Y
873201010400
Lepisosieus spatula
Alligator gar
E
P
Y
883516050000
Lepomis spp.
Sunfish (unknown species)
R
P
Y
883516050100
Lepomis aurilus
Redbreast sunfish
R
P
Y
883516050200
Lepomis cyanellus
Green sunfish
R
P
Y
883516050500
Lepomis gibbosus
Pumpkinseed
R
P
Y
883516050300
Lepomis gulosus
Warmouth
R
P
Y
883516050600
Lepomis humilis
Orangespoued sunfish
R
P
Y
883516050400
Lepomis macrochirus
Bluegill
R
P
Y
883516050700
Lepomis marginatus
Dollar sunfish
R
P
Y
883516050800
Lepomis megalolis
Longear sunfish
R
P
Y
883516050900
Lepomis microlophus
Redear sunfish
R
P
Y
883516051000
Lepomis punctalus
Spotted sunfish
R
P
Y
879103080100
Lota lota
Burbot
M
E
Y
618701150200
Loxorhynchus grandis
R
B
500501010300
Lumbriculus variegatus
Aqauatic worm
R
B
883536010700
Luljanus campechanus
Red snapper
M
B
Y
877601780400
Luxilus chrysocephalus
Striped shiner
R
P
877601780600
Luxilus comutus
Common shiner
R
P
D-l 1
-------
1 'tiU'tolgEKIBWieM
Appendix D. (continued)
Species Code
Scientific Name
Common Name
Resident/Migratory*
Demersal/Pelagic6
Potentially Eatable
885704110100
Lyopsetla exilis
Slender sole
M
B
Y
814802010600
Lytechinus anamesus
R
B
551531013600
Macoma irus
Clam (macoma)
R
B
Y
551531011400
Macoma nasula
R
B
877601800200
Macrhybopsis gelida
Sturgeon chub
R
E
551202430300
Megalonaias gigantea
Washboard mussel
R
B
Y
551547110100
Mcrcenaria mercenaria
Quahog
R
B
Y
883544070100
Micropogonias undulats
Atlantic croaker
M
P
Y
883516060000
Microptenis spp
Bass (unknown species)
R
P
Y
883516060500
Micropterus coosae
Redeye bass
R
P
Y
883516060100
Micropterus dolomieu
Smallmouth bass
R
P
Y
883516060600
Micropterus notius
Swannee bass
R
P
Y
88351606cu00
Micropterus oculatus
R
P
Y
883516060300
Micropterus punctulalus
Spotted bass
R
P
Y
883516060200
Micropterus salmoides
Largemouth bass
R
P
Y
877604080100
Minytrema melanops
Spotted sucker
E
B
Y
883502010000
Morone spp.
Temperate bass (unknown species)
E
P
Y
883502010100
Morone americana
White perch
M
P
Y
883502010400
Morone chrysops
White bass
M
P
Y
883502010500
Morone mississippiensis
Yellow bass
M
P
Y
D-12
-------
Appendix D. (continued)
Species Code
Scientific Name
Common Name
Resident/Migratory*
Demersal/Pelagic"
Potentially Ratable
883502010200
Morone saxatilis
Striped bass
M
P
Y
883502010300
Morone chrysops x saxatilis
Hybrid striped bass (whue/slnped)
E
P
Y
877604040000
Moxostoma spp.
Redhorse (unknown species)
R
B
Y
877604040400
Moxosloma anisurum
Silver redhorse
R
B
Y
877604040700
Moxostoma carinatum
River redhorse
R
B
Y
877604040200
Moxostoma congestum
Gray redhorse
R
B
Y
877604040900
Moxosloma duquesnei
Black redhorse
R
B
Y
877604041000
Moxosloma erythrurum
Golden redhorse
R
B
Y
877604040100
Moxosloma macrolepidotum
Shorthead redhorse
R
B
Y
877604041400
Moxostoma pappillosum
V-lip redhorse
R
B
Y
877604040300
Moxosloma poecilurum
Blacktail redhorse
R
B
Y
877604041700
Moxostoma rupiscanes
Striped jumprock
R
B
Y
883601010100
Mugil cephalus
Striped mullet
M
E
Y
883601010200
Mugil curema
White mullet
M
E
Y
870802040100
Mustelus cams
Smooth dogfish
M
E
Y
551701020100
Mya arenaria
Soft clam
R
B
Y
877601170100
Mylocheilus caurinus
Peainoulh
R
E
877601350100
Mylopharodon conocephalus
Hardhead
R
E
550701010000
Mylilus
Mussel
R
B
Y
550701010200
Mytilus califomianus
California mussel
R
B
Y
D-13
-------
mrt r^r ra&E&mjyTir)^
Appendix D. (continued)
Species Code
Scientific Name
Common Name
Resident/Migratory"
Demersal/Pelagic*
Potentially Eatable
550701010100
Mytilus edulis
Blue mussel
R
B
Y
500124030500
Ncan the s arenaceodentata
Sand worm
R
B
500168040100
Neoamphitrile robusta
R
B
500125011900
Nephtys caecoides
Sand worm
R
B
500125011500
Nephlys incisa
R
B
877601100300
Nocomis aspei
Redspot chub
R
E
877601100200
Nocomis leplocephalus
Bluehead chub
R
E
877601100100
Nocomis micropogon
River chub
R
E
877601060100
Notemigonus crysoleucas
Golden shiner
M
P
877601501000
Notropis amblops
Bigeye chub
R
E
877601114100
Notropis boops
Bigeye shiner
R
P
8776011U 400
Notropis buchanani
Ghost shiner
R
P
877601110600
Notropis hudsonius
Spottail shiner
R
P
877601118100
Notropis nubilus
Ozark minnow
R
E
877601112300
Notropis stranuneus
Sand shiner
R
P
877702020200
Noturus insignis
Margined madlrom
R
B
877702021800
Notums miurus
Brindled madlom
R
B
877702022000
Noturus phaeus
Brown madlom
R
B
870703010100
Odontaspis laurus
Sand tiger
M
E
Y
500300000000
Oligochaeles
Aquatic worms
R
B
D-14
-------
N0TTOlTT!ffST^fBt^QN
Appendix D. (continued)
Species Code
Scientific Name
Common Name
Resident/Migratory"
Demersal/Pelagic1'
Potentially Eatable
875501020800
Oncorhynchus clarki
Cutthroat trout
E
P
Y
875501020100
Oncorhynchus gorbuscha
Pink salmon
M
P
Y
875501021100
Oncorhynchus mykiss
Rainbow trout
E
P
Y
875501020300
Oncorhynchus kisutch
Coho salmon
M
P
Y
875501020500
Oncorhynchus nerka
Sockeye salmon
M
E
Y
875501020600
Oncorhynchus tshawytscha
Chinook salmon
M
E
Y
878301020000
Opsanus spp.
Toadfish (unknown species)
R
B
618105030000
Orconectes spp.
Crayfish
R
B
Y
877601360100
Orthodon microlepidotus
Sacramento blackfish
R
P
883540020100
Orthopristis chrysoptcra
Pigfish
R
P
Y
875503000000
Osmeridae
Smelt (species unknown)
M
P
Y
875503030200
Osmcrus mordax
Rainbow smell
M
P
Y
618102020100
Pacifastacus leniusculus
Crayfish
R
B
Y
617918010100
Pandalus borealis
R
B
883502160400
Paralabrax nebulifer
Barred sand bass
E
B
Y
885703030900
Paralichthys califomicus
California halibut
M
B
Y
885703030100
Paralichthys dentatus
Summer flounder (fluke)
M
B
Y
885703030400
Paralichthys lelhosngma
Southern flounder
M
B
Y
817502010100
Parastichopus califomicus
R
B
500166030400
Peclinaria californiensis
Sand worm
R
B
D-15
-------
Appendix D. (continued)
Species Code
Scientific Name
Common Name
Resident/Migratory'
Demersal/Pelagic1*
Potentially Ratable
617701010000
Penaeus spp.
Shrimp
R
B
Y
617701010100
Penaeus aztecus
Brown shrimp
R
E
Y
617701010300
Penaeus setiferus
While shrimp
R
E
Y
883520020100
Perca flavescens
Yellow perch
R
P
Y
883520030900
Percina copelandi
Channel darter
R
B
883560050100
Phanerodon furcalus
While seaperch
R
P
Y
877601370300
Phoxinus erylhrogaster
Soulhem redbelly dace
R
P
877601160200
Pimephales promelas
Fathead minnow
R
P
811703050100
Pisaster brevispinus
Starfish
R
B
550905090100
Placopecten magellanicus
R
B
885704140100
Platichthys stellatus
Starry flounder
M
B
Y
877601840100
Platygobio gracilis
Flathead chub
R
E
885704151000
Pleuronecles bilinealus
Rock sole
E
B
Y
885704130100
Pleuronectes vetulus
English sole
M
B
Y
885704000000
Pleuronecudae
Righteye flounder family
M
B
Y
885704160200
Pleuronichthys decunens
Curlfin sole
M
B
Y
885704160400
Pleuronichihys vertical!*.
Homyhead turbot
M
B
Y
880408110200
Poecilia vittata
Cuban limia
E
P
883544080100
Pogonias cromis
Black drum
M
P
Y
872902010100
Polyodon spalhula
Paddlefish
M
P
Y
D-16
-------
Appendix D. (continued)
Species Code
Scientific Name
Common Name
Resident/Migratory'
Demersal/Pelagic11
Potentially Ratable
883525010100
Pomatomus sallauix
Bluefish
M
P
Y
883516070000
Pomoxis spp.
Crappie (unknown species)
R
P
Y
883516070100
Pomoxis annularis
White crappie
R
P
Y
883516070200
Pomoxis nigromaculalus
Black crappie
R
P
Y
882602010100
Prionolus carolinus
Northern searobin
R
B
Y
875501060100
Prosopium cylindraceum
Round whilefish
M
P
Y
875501060200
Prosopium williamsoni
Mounlain whilefish
M
P
Y
551547070100
Protolhaca siaminea
Clam (pacific lillleneck)
R
B
Y
885704150400
Pleuronectes americanus
Winter flounder
M
B
Y
877601180000
Ptychocheilus spp.
Squawfish
R
E
Y
877601180100
Ptychocheilus oregonensis
northern squawfish
R
E
Y
877702030100
Pylodictis olivans
Flathead catfish
R
E
Y
871304010300
Raja binoculata
Winter skate
M
B
Y
890302010600
Rana catesbeiana
?
P
Y
551525040100
Rangia cuneata
Brackish water clam
R
B
Y
877601090000
Rliinichthys spp.
Dace (unknown species)
R
B
877601190100
Richardsonius balteatus
Redside shiner
R
P
875501030000
Salino spp.
Trout (unknown species)
E
P
Y
875501030500
Salmo salar
Atlantic salmon
M
P
Y
875501030600
Salino trutla
Brown trout
E
P
Y
D-17
-------
^Airvr E?r>p nKTPlRl
Appendix D. (continued)
Species Code
Scientific Name
Common Name
Resident/Migratory"
Demersal/Pelagic1*
Potentially Ratable
875501000000
Salmon! dac
Trout (family)
E
P
Y
875501040000
Salvelinus hybrid
Splake (hybrid)
E
P
Y
875501040400
Salvelinus fontinalis
Brook trout
E
P
Y
875501040100
Salvelinus malma
Dolly varden
E
P
Y
875501040300
Salvelinus namaycush
Lake trout
E
P
Y
551547020100
Saxidomus giganleus
Clam (smooth Washington)
R
B
Y
872901020200
Scaphirhynchus platorynchus
Shovelnose sturgeon
M
B
Y
883544000000
Sciaenidae
Drum family
M
E
Y
883544090100
Sciaenops ocellatus
Red ilium
M
E
Y
885003030100
Scomber japonicus
Chub mackerel
M
P
Y
885003050100
Scomberomorus cavalla
King mackeral
M
P
Y
885003050200
Scomberomorus maculaius
Spanish mackerel
M
P
Y
885703040100
Scophlhalmus aquosus
Windowpane
M
B
Y
882601061600
Scorpaena gullala
California scorpionfish
R
B
Y
883102310100
Scorpaenichthys marmoraius
Cabezon
R
B
882601010300
Sebastes auriculalus
Brown rockfish
M
P
Y
882601012000
Sebastes maliger
Quillback rocknsh
M
P
Y
882601013900
Sebastes norvegicus
Golden redfish
M
P
Y
882601012100
Sebastes melanops
Black rockfish
M
P
Y
882601012700
Sebastes paucispinis
Bocaccio
M
P
Y
D-18
-------
¦NQT-FQR-DIG-TIU&fcm&W
Appendix D. (continued)
Species Code
Scientific Name
Common Name
Resident/Migratory*
Demersa I/Pelagic1'
Potentially Eatable
882601013000
Sebastes pronger
Redsiripe rockfish
M
P
Y
877601080200
Semotilus airomaculatus
Creek chub
R
E
877601080100
Semolilus corporal is
Fallfish
R
E
877601080300
Semotilus lumbee
Sandhills crab
R
E
617704010900
Sicyonia ingentis
R
B
551529020100
Solen sicarius
Razor clam
R
B
871001020100
Squalus acanihias
Spiny dogfish
M
E
Y
883520040200
Slizosiedion canadense
Sauger
R
P
Y
883520040100
Sti/.osledion vitreum
Walleye
R
P
Y
880302020100
Strongylura manna
Atlantic needlefish
M
P
885703130300
Syacium papillosum
Dusky flounder
M
B
Y
885802011600
Symphurus auicauda
California tonguefish
M
B
876202010100
Synodus foetens
Inshore lizardfish
R
B
885003040400
Thunnus atlanticus
Blackfin luna
M
P
Y
875501070100
Thymallus arcticus
Arctic grayling
E
P
Y
883561400100
Tilapia mossambica
Mozambique tilapia
R
E
Y
883561040500
Tilapia zillii
Redbelly tilapia
R
E
Y
551525020100
Tresus capax
Horse clam
R
b
Y
870802090200
Triakis semifasciata
Leopard shark
M
E
Y
884701300100
Tridenliger trigonocephaly
Chameleon goby
R
B
D-19
-------
N€gaFgRaEFFS5FR1BWfefe]
Appendix D. (continued)
Species Code
Scientific Name
Common Name
Resident/Migratory*
Demersal/Pelagic1'
Potentially Eatable
885801010100
Trinectes maculatus
Hogchoker
M
B
880302030200
Tylosurus crocodilus
M
E
Y
875802010200
Umbra limi
Central mudminnow
R
E
050601010000
Vaucheria
Macroalgae
?
E
'Fish species is considered
R = resident
M = migratory
E = either resident or migratory
? = unknown
bFish species is considered
B = demersal
P = pelagic
E = either
? = unknown
D-20
-------
Appendix E
Test Species Used in Toxicity Tests Whose Results Are Presented in the NSI
Appendix E presents a list of species used in toxicity tests whose results are included in the NSI.
Appendix E also presents the type of toxicity test for which each species is generally used (i.e.,
liquid phase, elutriate phase, suspended particulate phase, sediment/solid phase). In many cases
the data recorded in the NSI identified the test phase used for the toxicity test. In many cases
the test species used was given but the test phase was not. In these latter cases, best professional
judgment based on test species was used to determine the test phase.
The data presented in Appendix E are the basis for determining whether the toxicity test of
concern was conducted using the solid or elutriate phase [criteria 14, 15, and 16] and whether
the test species used was a standardized EPA test species [criterion 16]. A "Y" entered on the
Appendix E table indicates that the phase was given with the test results; an "E" indicates that
the phase was estimated using best professional judgment based on the species used in the
toxicity test.
E-l
-------
D131"KIBU ITQN
E-2
-------
""NQT-rok
Appendix E. Test Species Used in Biotoxicity Test Results Included in the NSI
Species
Code
Species
Name
Liquid
(I-)
Elutriat
e
(E)
Particul
ate
(P)
Solid
(S)
C
(L most common)
(L or E)
D
(L,E, or
P)
A
(1-,E,P, or
S)
Unknown
080509070600
E
616902010800
A. abdua
Y,E
615301010900
Acanlhomysis costata
Y
Y
615301010400
Acanlhomysis macropsis
Y
Y
Y
615301010700
Acanlhomysis sculpia
Y
E
611829010000
Acartia spp.
Y
Y
616902010800
Ampelisca abdila
Y,E
616800000000
Amphipods
Y
610401010100
Anemia salina
Y
Y
616302070900
Asellus iniermedius
E
650508331700
Chironomus riparius
E
650508330100
Chironomus tenlans
E
885703010200
Citharichthys sLigmaeus
Y
616915021500
Corophium spimcorne
Y,E
617922010000
Crangon spp.
Y
Y
Y
551002010100
Crassosirea gigas
Y
Y
E
551002010200
Crassoslrea virginica
Y
880404010100
Cypnnodon variegaius
Y
Y
610902010900
Daphnia magna
E
610902010100
Daphnia pulex
E
815501010100
Dcndrasier exceniricus
E
E-3
-------
Appendix E. (continued)
Species
Code
Species
Name
Liquid
(I')
F.lutriat
e
(E)
Particul
ate
(P)
Solid
(S)
C
(L most common)
(L or E)
D
(L,E, or
P)
A
d ,F.,P, or
S)
Unknown
61692202GLNP
Diaporeia sp.
E
880404020700
Fundulus grandis
Y
Y
881801010100
Gasterosteus aculeatus
E
616915090200
Grandidierella japonica
Y
622003030700
Hexagcnia limbata
E
615301010700
Holmesimysis sculpta
Y
Y
Y
E
616923040100
Hyalella azlcca
E
616923040100
Hyallclla azlcca
E
500501010300
Lumbriculus vanegatus
E
814802010200
Lylcchinus pictus
Y
Y
551531011600
Macoma ballhica
E
551531011400
Macoma nasuta
Y
Y,E
551531010000
Macoma spp.
E
615303140600
Metamysidopsis elongata
Y
Y
Y
651530100000
Mysid shrimp
Y
Y
Y
615301210200
Mysidopsis bahia
Y
Y
550701010100
Mytilus edulis
Y
Y
E
500124030500
Neanthes arenacedonla
Y
500124030500
Neanthes
arenaccodeniata
E
500124030000
Neanthes spp.
E
500125011900
Ncphtys caecoides
Y,E
E-4
-------
tf5':^eTaFgR=PiyfgTffB^
Species
Code
Species
Name
Liquid
(10
Elutriat
e
(E)
Particul
ate
(P)
Solid
(S)
C
(L most common)
(l41r E)
D
(L,E, or
P)
A
(L,E,P, or
S)
Unknown
500124030200
Nereis virens
Y
551706040100
Panopea generosa
E
Paratanylarsus
parthogcnelic
E
617701010200
Penaeus duorarum
Y
MICROTOX
Photobacterium
phosphoreum
E
877601160200
Pimephales promales
Y
E
551547070100
Proiolhaca staminea
Y
616942150400
Rhepoxynius ahronius
Y,E
885703010200
Sandab speckled
Y
Y
080309070600
Selenaslrum
capricornulum
E
881801010100
Stickleback three-spine
E
814903020400
Slrongylocentrotus
purpuratus
Y
Y
E
611910030100
Tigriopus californicus
E
E-5
-------
NeSnPOB-rPtSXR-mUXTGM
Appendix F
List of Attendees - National Sediment Inventory Workshop
April 26-27, 1994
Sid Abel
EPA/OPPT (7406)
401 M Street, SW
Washington, DC 20460
(202) 260-3920; Fax (202) 260-0981
Jim Andreasen
EPA ORD-EMAP (8205)
401 M. Street, SW
Washington, DC 20460
(202) 260-5259; Fax (202) 260-4346
Gary Ankley
ERL-Duluth
6201 Congdon Blvd.
Duluth, MN 55804
(218) 720-5603
Tom Armitage
EPA/OST (4305)
401 M Street, SW
Washington, DC 20460
(202) 260-5388
Bev Baker
EPA/OST (4305)
401 M Street, SW
Washington, DC 20460
(202) 260-7037
Rich Batiuk
EPA Chesapeake Bay Program Office
410 Severn Ave.
Annapolis, MD 21403
(410) 267-5731; Fax (410) 267-5777
Paul Baumann
National Biological Survey
Ohio State University
2021 Coffey Rd.
Columbus, OH 43210
(614) 469-5701
Candy Brassard
EPA/OPP
7507C
410 M Street, SW
Washington, DC 20460
(703) 305-5398
Barry Burgan
EPA/OWOW (4503F)
401 M Street, SW
Washington, DC 20460
(202) 260-7060
Allen Burton
Biological Science Department F3301
Wright State University
Dayton, OH 45435
(513) 873-2201
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Scott Carr
National Biological Survey
NFCR Field Research Station
TAMU-CC, Campus Box 315
6300 Ocean Dr.
Corpus Christi, TX 78412
(512) 888-3366; Fax (512) 888-3443
Charlie Chandler
USFWS/DEC
4401 N. Fairfax Dr., Suite 330
Arlington VA 22203
(703) 358-2148; Fax (703) 358-1800
Peter Chapman
EVS Consultants
195 Pemberton Ave.
N. Vancouver, B.C.
Canada V7P2R4
(604) 986-4331
Tom Chase
EPA/OWOW (4504F)
401 M Street, SW
Washington, DC 20460
(202) 260-1909; Fax (202) 260-9960
email: chase.tom@epamail.epa.gov
Greg Currey
EPA/OWEC (4203)
401 M Street, SW
Washington, DC 20460
(202) 260-1718
Kostas Daskalakis
NOAA/ORCA 21
1305 East Hwy.
Silver Spring, MD 20910
(301) 713-3028
Dom DiToro
Manhattan College
Environmental Engineering
Bronx, NY 10471
(718) 920-0276; Fax (718) 543-7914
Bob Engler
COE-WES
3909 Halls Ferry Road
Vicksburg, MS 39180-6199
(601) 634-3624
Jay Fields
NOAA/HAZMAT
7600 Sand Point Way, NE
Seattle, WA 98115
(206) 526-6404
Catherine Fox
EPA/OST (4305)
401 M Street, SW
Washington, DC 20460
(202) 260-1327; Fax (202) 260-9830
Tom Fredette
COE New England District
424 Trapels Rd.
Waltham, MA 02254
(617) 647-8291; Fax (617) 647-8303
Marilyn Gower
EPA Region 3
2530 Riva Rd., Suite 300
Annapolis, MD 21401
(410) 224-0942
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Dave Hansen
EPA ERL-Narragansett
27 Tarzwell Dr.
Narragansett, RI 02882
(401) 782-3027; Fax (401) 782-3030
Jon Harcum
Tetra Tech, Inc.
10306 Eaton PL, Ste. 340
Fairfax, VA 22030
(703) 385-6000; Fax (703) 385-6007
Rick Hoffmann
EPA/OST (4305)
401 M Street, SW
Washington, DC 20460
(202) 260-0642; Fax (202) 260-9830
Bob Hoke
SAIC
411 Hackensack Ave.
Hackensack, NJ 07601
(201) 489-5200; Fax (201) 489-1592
Chris Ingersoll
NBS
Midwest Science Center
4200 New Haven Rd.
Columbia, MO 65201
(314) 875-5399
Doug Johnson
EPA Region 4
345 Courtland Street, NE
Atlanta, GA 30365
(404) 347-1740; Fax (404) 347-1797
Ken Klewin
EPA Region 5 (WS-16J)
77 W. Jackson Blvd.
Chicago, IL 60604
(312) 886-4679; Fax (312) 886-7804
Fred Kopfler
Gulf of Mexico Program
Bldg. 1103
Stennis Space Center, MS 39529
(601) 688-3726; Fax (601) 688-2709
Paul Koska
EPA Region 6
1445 Ross Ave.
Dallas, TX 75115
(214) 655-8357
Mike Kravitz
EPA/OST
401 M Street, SW
Washington, DC 20460
(202) 260-8085
Peter Landrum
Great Lakes ERL
2205 Commonwealth Blvd.
Ann Arbor, MI 48105
(313) 741-2276
Matthew Liebman
EPA Region 1
JFK Federal Bldg., WQE
Boston, MA 02203
(617) 565-4866; Fax (617) 565-4940
email; bays@epamail.epa.gov
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Ed Long
NOAA (N/OMA 34)
7600 Sand Point Way, NE
Seattle, WA 98115
(206) 526-6338
Don MacDonald
MacDonald Environmental Sciences Ltd.
2376 Yellow Point Rd.
Ladysmith, BC
Canada VORZEO
(604) 72^-3631
John Malek
EPA Region 10
1200 Sixth Ave., WD-128
Seattle, WA 98101
(206) 553-1286; Fax (206) 553-1775
Audrey Massa
EPA Region 2
Marine and Wetlands Protection Branch
26 Federal Plaza
New York, NY 10278
(212) 264-8118; Fax (212) 264-4690
Deirdre Murphy
MD Dept. of Environment
2500 Broening Hwy.
Baltimore, MD 21224
(410) 631-3906; Fax (410) 633-0456
Arthur Newell
New York DEC
Division of Marine Resources
Bldg. 40, SUNY
Stony Brook, NY 11790-2356
(516) 444-0430; Fax (516) 444-0434
Tom O'Connor
NOAA Status and Trends Program
Bldg. SSMCY
1305 East West Highway
Silver Spring, MD 20901
(301) 713-3028
Robert Paulson WR/2
Wisconsin DNR
P.O. Box 7921
Madison, WI 53707-7921
,(608) 266-7790; Fax (608) 267-2800
Mary Reiley
EPA/OST (4304)
401 M Street, SW
Washington, DC 20460
(202) 260-9456; Fax (202) 260-1036
John Scott
SAIC
165 Dean Knauss Dr.
Narragansett, RI 02882
(401) 782-1900; Fax (401) 782-2330
Thomas Seal
Florida DEP
Mail Station 46
3900 Commonwealth Blvd.
Tallahassee, FL 32399-3000
(904) 488-0784
Mohsin Siddique
Water Quality Control Branch
2100 MLK Jr. Ave., SE
Ste. 203
Washington, DC 20020
(202) 404-1129
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Gail Sloane
Florida DEP
Mail Station 46
3900 Commonwealth Blvd.
Tallahassee, FL 32399-3000
(904) 488-0784
Sherri Smith
Environment Canada
351 Street, Joseph Blvd., 8th Floor
Hull, Quebec KIAOH3
(819) 953-3082; Fax (819) 953-0461
Betsy Southerland
EPA/OST (4305)
401 M Street, SW
Washington, DC 20460
(202) 260-3966
Mark Sprenger
EPA ERT (MS 101)
2890 Woodbridge Ave.
Edison, NJ 08837
(908) 906-6826
Jerry Stober
ESD-Athens
College Station Rd.
Athens, GA 30113
(706) 546-2207; Fax (706) 546-2459
Rick Swartz
EPA ERL-Newport
Hatfield Marine Science Center
Marine Science Drive
Newport, OR 97365
(503) 867-4031
Nelson Thomas
EPA/ERL-Duluth
6201 Congdon Blvd.
Duluth, MN 55804
(218) 720-5702
Rachel Friedman-Thomas
Washington Dept. of Ecology
Mail Slot 47703
Olympia, WA 98504-7703
(206) 407-6909; Fax (206) 407-6904
Burnell Vincent
EPA/ORD
401 M Street, SW
Washington, DC 20460
(202) 260-7891; Fax (202) 260-6932
Mark Wildhaber
NBS
Midwest Science Center
4200 New Haven Rd.
Columbia, MO 65201
(314) 876-1847
Craig Wilson
California SWRCB
901 P Street,
Sacramento, CA 95814
(916) 657-1108
Drew Zacherle
Tetra Tech, Inc.
10306 Eaton PL, Ste. 340
Fairfax, VA 22030
(703) 385-6000; Fax (703) 385-6007
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Chris Zarba
EPA/OST (4304)
401 M Street, SW
Washington, DC 20460
(202) 260-1326
Xiaochun Zhang, WR/2
Wisconsin DNR
P.O. Box 7921
Madison, WI 53707
(608) 264-8888; Fax (608) 267-2800
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