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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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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vi

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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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{^^F0R%-E)I-SSRI&yTIQ¥

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

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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));

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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);

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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

23

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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

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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

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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

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-------
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

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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

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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

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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.

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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.

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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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6. REFERENCES CITED

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Howard, D.E., and R.D. Evans. 1993. Acid-volatile sulfide (AVS) in a seasonally anoxic
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USEPA. 1992b. Sediment classification methods compendium. EPA 823-R-92-006. U.S.
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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

-------
?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

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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

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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

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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

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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

F-l

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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

F-2

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NQ^jEQfeBI-SfER'IBUTION

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

F-3

-------


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

F-4

-------
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

F-5

-------
MOT FHD -EUSffflBTTTRftf

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

QE

SI I

. u ^

crrt Liorary hegion A

l/oo

F-6

-------