EFA
United States
Environmental Protection
Agency
Office of Science and Technology and
Office of Research and Development
Washington, DC 20460
Equilibrium Partitioning
Sediment Guidelines (ESGs)
for the Protection of Benthic
Organisms: Dieldrin
DRAFT
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Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
Foreword
Under the Clean Water Act (CWA). the U S. Environmental Protection Agency (EPA) and the
States develop programs for protecting the chemical, physical, and biological integrity of the
nation's waters. To meet the objectives of the CWA, EPA has periodically issued ambient water
quality criteria (WQC) beginning with the publication of "Water Quality Criteria. 1972" (NAS,
1973). The development of WQC is authorized by Section 304(a)(l) of the CWA. which directs the
Administrator to develop and publish "criteria" reflecting the latest scientific knowledge on (1)
the kind and extent of effects on huma'n health and welfare, including effects on plankton, fish.
shellfish, and wildlife, that may be expected from the presence of pollutants in any body of water.
including ground water, and (2) the concentration and dispersal of pollutants on biological
community diversity, productivity, and stability. All criteria guidance through late 1986 was
summarized in an EPA document entitled "Quality Criteria for Water, 1986" (U.S EPA, 1987a).
Updates on WQC documents for selected chemicals and new criteria recommendations for other
pollutants have been more recently published as "National Recommended Water Quality Criteria-
Correction" (U.S EPA. 1999). EPA will continue to update the nationally recommended WQC as
needed in the future.
In addition to the development of WQC and to continue to meet the objectives of the CWA, EPA
has conducted efforts to develop and publish equilibrium partitioning sediment guidelines (ESGs)
for some of the 65 toxic pollutants or toxic pollutant categories. Toxic contaminants in bottom
sediments of the nation's lakes, rivers, wetlands, and coastal waters create the potential for
continued environmental degradation even where water column contaminant le\ els meet
applicable water quality standards. In addition, contaminated sediments can lead to water quality
impacts, even when direct discharges to the receiving water have ceased. These guidelines are
authorized under Section 304(a)(2) of the CWA, which directs the Administrator to develop and
publish information on, among other things, the factors necessary to restore and maintain the
chemical, physical, and biological integrity of all navigable waters.
The ESGs and associated methodology presented in this document are EPA's best
recommendation as to the concentrations of a substance that may be present in sediment while
still protecting benthic organisms from the effects of that substance. These guidelines are
applicable to a variety of freshwater and marine sediments because they are Based on the
biologically available concentration of the substance in the sediments. These ESGs are intended
to provide protection to benthic organisms from direct toxicity due to this substance. In some
cases, the additive toxicity for specific classes of toxicants (eg, metal mixtures or polycychc
aromatic hydrocarbon mixtures) is addressed. The ESGs do not protect against synergistic or
antagonistic effects of contaminants or bioaccumulative effects to benthos. They are not
protective of wildlife or human health endpomts.
EPA recommends that ESGs be used as a complement to existing sediment assessment tools, to
help assess the extent of sediment contamination, to help identify chemicals causing toxicity. and
to serve as targets for pollutant loading control measures. EPA is developing guidance to assist
in the application of these guidelines in water-related programs of the States and this Agency.
This document provides guidance to EPA Regions. States, the regulated community, and the
public. It is designed to implement national policy concerning the matters addressed. It does not.
however, substitute for the CWA or EPA's regulations, nor is it a regulation itself. Thus, it cannot
impose legally binding requirements on EPA. States, or the regulated community. EPA and State
decisionmakers retain the discretion to adopt approaches on a case-by-case basis that differ from
this guidance where appropriate. EPA may change this guidance in the future.
iii
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Foreword
This document has been reviewed by EPA's Office of Science and Technology (Health and
Ecological Catena Division. Washington, DC) and Office of Research and Development (Mid-
Continent Ecology Division. Duluth. MN, Atlantic Ecology Division, Narragansett. RI). and
approved for publication.
Mention of trade names or commercial products does not constitute endorsement or
recommendation of use.
Front cover image provided by Wayne R. Davis and Virginia Lee.
IV
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Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
Contents
Acknowledgments ,x
Executive Summary xi
Glossary of Abbreviations xw
Section 1
Introduction 1-1
1.1 General Information 1-1
12 General Information: Dieldrin T .7. 1-2
13 Applications of Sediment Guidelines ... 14
14 Overview 14
Section 2
Partitioning 2-1
2.1 Description of EqP Methodology 2-1
22 Determination of KOW for Dieldrin 2-2
23 Derivation of K^ from Adsorption Studies 22
2.3.1 KQC from Particle Suspension Studies 2-2
232 KQC from Sediment Toxicity Tests 2-3
2.4 Summary of Derivation of Af^. for Dieldrin 24
Section 3
Toxicity of Dieldrin in Water Exposures 3-1
3.1 Derivation of Dieldrin WQC 3-1
32 Acute Toxicity in Water Exposures 3-1
33 Chronic Toxicity in Water Exposures 3-1
3.4 Applicability of the WQC as the Effects Concentration for Derivation of the
DieldrinESG - 3-6
Section 4
Actual and Predicted Toxicity of Dieldrin
in Sediment Exposures 4-1
4.1 Toxicity of Dieldnn in Sediments 4-1
42 Correlation Between Organism Response and Interstitial Water Concentration 4-3
43 Tests of the Equilibrium Partitioning Prediction of Sediment Toxicity 4-6
Section 5
Guidelines Derivation for Dieldrin 5-1
5.1 Guidelines Derivation - 5-1
52 Uncertainty Analysis 5-2
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Contents
53 Comparison of Dieldrin ESG and Uncertainty Concentrations to Sediment
Concentrations that are Toxic or Predicted to be Chronically Acceptable 54
5.4 Comparison of Dieldrm ESG to STORET. National Status and Trends, and
Corps of Engineers, San Francisco Bay Databases for Sediment Dieldnn 5-6
5.5 Limitations to the Applicability of ESGs .5-10
Section 6
Guidelines Statement 6-1
Section 7
References 7-1
Appendix A A-I
Appendix B =. ~ B-I
VI
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Equilibrium Partitioning Sediment Guidelines (ESGsj: Dieldrin
Tables
Table 2-1. Dieldrin measured and estimated log IO/LOW values 2-2
Table2-2 Summaryof Af^ values for dieldnn derived from literature sorption isotherm data 24
Table 3-1. Test-specific data for chronic sensitivity of freshwater and saltwater organisms to dieldrin 34
Table 3-2. Summary of freshwater and saltwater acute and chronic values, acute-chronic ratios, and
derivation of final acute values, final acute-chronic ratios, and final chronic values 3-5
Table 3-3. Results of the approximate randomization (AR) test for the equality of freshwater and
saltwater FAV distributions for dieldnn and AR test for the equality of benthic and
combined benthic and water column (WQC) FAV distributions 3-7
Table 4-1. Summary of tests with dieldnn-spiked sediment .... ..., ....'. 4-2
s'
Table 4-2. Water-only and sediment LC50 values used to test the applicability
of the EqP theory for dieldnn 4-5
Table 5-1. Equilibrium partitioning sediment guidelines (ESGs) for dieldnn .5-1
Table 5-2. Analysis of variance for denvation of confidence limits of the ESGs for dieldrin 5-3
Table 5-3. Confidence limits of the ESGs for dieldrin 5-3
Figures
Figure 1-1. Chemical structure and physical-chemical properties of dieldrin 1-3
Figure 2-1. Observed versus predicted partition coefficients for nonionic
organic chemicals 2-3
Figure 2-2. Organic carbon-normalized sorption isotherm for dieldrin and probability
plot of KQC from sediment toxicity tests 2-5
Figure 3-1. Genus mean acute values from water-only acute toxicity tests using
freshwater species versus percentage rank of their sensitivity 3-2
Figure 3-2. Genus mean acute values from water-only acute toxicity tests
using saltwater species versus percentage rank of their sensitivity .3-3
Figure 3-3 Probability distribution of FAV difference statistics to compare water-only data from
freshwater versus saltwater and benthic versus WQC data 3-8
Figure 4-1. Percent mortalities of amphipods in sediments spiked with acenaphthene or phenanthrene,
endnn. or fluoranthene. and midge in sediments spiked with dieldnn or kepone relative
to interstitial water toxic units ....4-3
Figure 4-2 Percent mortalities of amphipods in sediments spiked with acenaphthene or
phenanthrene. dieldnn. endrin, or fluoranthene. and midge in sediments spiked with
dieldrin relative to predicted sediment toxic units 44
VII
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Contents
Figure 5-1 Predicted genus mean chronic values calculated from water-only toxicity values
using freshwater species versus percentage rank of their sensitivity. 5-4
Figure 5 -2. Predicted genus mean chronic values calculated from water-only toxicity
values using saltwater species versus percentage rank of their sensitivity 5-5
Figure 5-3 Probability distribution of concentrations of dieldnn in sediments from streams, lakes, and
estuaries m the United States from 1986 to 1990 from the STORET database compared with
the dieldnn ESG values 5-7
Figure 5-4 Probability distribution of concentrations of dieldnn in sediments from coastal and estuarme
sites from 1984 to 1989 as measured by the National Status and Trends Program 5-8
Figure 5-5. Probability distribution of organic carbon-normalized sediment dieldnn concentrations
from the U.S. Army Corps of Engineers (1991) monitoring program of San Prancisco Bay 5-9
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Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
Acknowledgments
Coauthors
Walter! Berry*
David J Hansen
DomJnicM DiToro
Laurie D. De Rosa
Heidi E. Bell*
MaryC.Reiley
Frank E.Stancil, Jr.
Christophers Zarba
Robert L.Spehar
U.S EPA. NHEERL. Atlantic Ecology Division. Narragansett, RI
HydroQual. Inc.. Mahwah. NJ, Great Lakes Environmental Center,
Traverse City. MI (formerly with U.S. EPA)
Manhattan College. Riverdale. NY; HydroQual. Inc.. Mahwah. NJ
HydroQual.'Inc.. Mahwah. NJ
U S. EPA. Office of Water. Washington, DC
U S. EPA. Office of Water. Washington. DC
U S. EPA. NERL, Ecosystems Research Division, Athens. GA
U S. EPA, Office of Research and Development, Washington, DC
U.S. EPA, NHEERL. Mid-Continent Ecology Division, Duluth. MN
Significant Contributors to the Development of the Approach and Supporting Science
Herbert E.Allen
Gerald T.Ankley
Christina E. Cowan
Dominic M. Di Toro
David J. Hansen
Paul R. Paquin
Spyros P Pavlou
Richard C.Swartz
Nelson A. Thomas
University of Delaware, Newark, DE
U S. EPA, NHEERL, Mid-Comment Ecology Division, Duluth, MN
The Proctor & Gamble Co.. Cincinnati, OH
Manhattan College, Riverdale, NY; HydroQual. Inc.. Mahwah. NJ
HydroQual, Inc., Mahwah, NJ; Great Lakes Environmental Center,
Traverse City, MI (formerly with U.S. EPA)
HydroQual, Inc., Mahwah, NJ
Ebasco Environmental, Bellevue, WA
Environmental consultant (formerly with U.S. EPA)
U.S. EPA. NHEERL, Mid-Continent Ecology Division. Duluth. MN
(retired)
Christopher S. Zarba U.S. EPA. Office of Research and Development. Washington. DC
Technical Support and Document Review
Patricia DeCastro
Robert A. Hoke
HeinzP.Kollig
Tyler K. Linton
Robert L. Spehar
OAO Corporation, Narragansett, RI
E.I. DuPont deNemours and Company. Newark, DE
U.S. EPA. NERL. Ecosystems Research Division, Athens, GA
Great Lakes Environmental Center. Columbus, OH
U.S. EPA. NHEERL. Mid-Continent Ecology Division, Duluth. MN
*PnncipalUS EPA contact
IX
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Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
Executive Summary
This equilibrium partitioning sediment guideline (ESG) document recommends a sediment
concentration for the insecticide dieldnn that is EPA's best estimate of the concentration
protective of the presence of benthic organisms. The equilibrium partitioning (EqP) approach was
chosen because it accounts for the varying biological availability of chemicals in different
sediments and allows for incorporation of the appropriate biological effects concentration. This
provides for the derivation of a guideline that is causally linked to the specific chemical.
applicable across sediments, and appropriately protective of benthic organisms
EqP theory asserts that a nonionic chemical in sediment partitions between sediment organic
carbon, interstitial (pore) water, and benthic organisms. At equilibrium, if the concentration in any
one phase is known, then the concentration in the others can be predicted. The ratio of the
concentration in water to the concentration in organic carbon is termed the organic carbon
partition coefficient (K^). which is a constant for each chemical The ESG Technical Basis
Document (U.S EPA, 2000a) demonstrates that biological responses of benthic organisms to
nonionic organic chemicals in sediments are different across sediments when the sediment
concentrations are expressed on a dry weight basis, but similar when expressed on a ^g
chemical/g organic carbon basis (Mg/ggc)- Similar responses were also observed across sediments
when interstitial water concentrations were used to normalize biological availability. The
Technical Basis Document further demonstrates that if the effect concentration in water is known,
the effect concentration in sediments on a Mg/g^ basis can be accurately predicted by
multiplying the effect concentration in water by the chemical's Kx. Because the water quality
criteria (WQC) represent the concentration of a chemical in water that is protective of the presence
of aquatic life, and is appropriate for benthic organisms, the product of the final chronic value
(FCV) from the WQC and K^. is the concentration in sediments that, on an organic carbon basis.
is protective of benthic organisms. For dieldrin this concentration is 12 Mg dieldrin/g^, for
freshwater sediments and 28 Mg/g^ for saltwater sediments. Confidence limits of 5 4 to 27 Mg/go,-
for freshwater sediments and 12 to 62 Mg/goc for saltwater sediments were calculated using the
uncertainty associated with the degree to which toxicity could be predicted by multiplying the Kx
and the water-only effects concentration. The ESG should be interpreted as a chemical
concentration below which adverse effects are not expected In comparison, at concentrations
above the ESG effects are likely, and above the upper confidence limit effects are expected if the
chemical is bioavailable as predicted by EqP theory. A sediment-specific site assessment would
provide further information on chemical bioavailability and the expectation of toxicity relative to
the ESG and associated uncertainty limits.
These guidelines do not protect against additive, synergistic. or antagonistic effects of
contaminants or bioaccumulative effects to aquatic life, wildlife, or human health. The Agency
and the EPA Science Advisory Board do not recommend the use of ESGs as stand-alone, pass- fail
criteria for all applications; rather. ESGs could trigger additional studies at sites under
investigation. This ESG applies only to sediments having sO.2% organic carbon.
EPA has developed both Tier 1 and Tier 2 ESGs to reflect the differing degrees of data availability
and uncertainty. Requirements for a Tier 1 ESG include a Kow, FCV. and sediment toxicity tests to
venfy EqP assumptions. In comparison, a Tier 2 ESG requires a KQVf and a FCV or secondary
chronic value (SCV), sediment toxicity tests are recommended but not required. The ESGs derived
for dieldrin in this document, as well as the ESGs for endnn. metal.mixtures (Cd, Cu, Pb. Ni. Ag.
Zn). and polycyclic aromatic hydrocarbon (PAH) mixtures represent Tier 1 ESGs (US. EPA,
2000d.e.f). Information on how EPA recommends ESGs be applied in specific regulatory programs
is described in the "Implementation Framework for the Use of Equilibrium Partitioning Sediment
Guidelines (ESGs)" (EPA. 2000c)
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Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
Glossary of Abbreviations
ACR Acute-chronic ratio
ANOVA Analysis of vanance
AR Approximate randomization
Cd Freely-dissolved interstitial water chemical concentration
Cw Total interstitial water chemical concentration (includes freely -dissolved and
DOC-complexed)
GOE U.S. Army Corps of Engineers
CFR Code of Federal Regulations . . ' "
CWA Clean Water Act
DOC Dissolved organic carbon
EC50 Chemical concentration estimated to cause adverse affects to 50% of the test
organisms within a specified time period
EPA United States Environmental Protection Agency
EqP Equilibrium partitioning
ESG(s) Equilibrium partitioning sediment guideline(s); for nonionic organics. this term
usually refers to a value that is organic carbon-normalized (more formally ESG
unless otherwise specified
Dry weight-normalized equilibrium partitioning sediment guideline
Organic carbon-normalized equilibrium partitioning sediment guideline
FACR Final acute-chronic ratio
FAV Final acute value
KV Final chronic value
FDA U.S. Food and Drug Administration
/of. Fraction of organic carbon in sediment
FRV Final residue value
GMAV Genus mean acute value
goc Gram organic carbon
HECD U S EPA. Health and Ecological Catena Division
HMAV Habitat mean acute value
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Glossary
IUPAC International Union of Pure and Applied Chemistry
IWTU Interstitial water toxic unit
^DOC Dissolved organic carbon partition coefficient
Koc Organic carbon-water partition coefficient
KOw Octanol-water partition coefficient
Kp Sediment-water partition coefficient
LC50 The concentration estimated to be lethal to 50% of the test organisms within a
specified time period
Organic carbon-normalized LC50 from sediment exposure
LC50 from water-only exposure
mDoc Measured DOC concentration
NAS National Academy of Sciences
NERL U S. EPA. National Exposure Research Laboratory
NHEERL U.S. EPA. National Health and Environmental Effects Research Laboratory
NOAA National Oceanographic and Atmospheric Administration
NOEC No observed effect concentration
NTIS National Technical Information Service
OC Organic carbon
OBC Observed effect concentration
OST U.S. EPA, Office of Science and Technology
PAH Polycyclic aromatic hydrocarbon
PGMCV Predicted genus mean chronic value
PSTU Predicted sediment toxic unit
SD Standard deviation
SE Standard error
SMACR Species mean acute-chronic ratio
STORET EPA's computerized database for STOrage and RETneval of water-related data
TOC Total organic carbon
TU Toxic unit
WQC Water quality criteria
xiv
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Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrtn
Section 1
Introduction
1.1 General Information
Under the Clean Water Act (CWA) the U.S.
Environmental Protection Agency (EPA) is responsible
for protecting the chemical, physical. and biological
integrity of the nation's waters. In keeping with this
responsibility. EPA published ambient water quality
criteria (WQC) in 1980 for 64 of the 65 toxic pollutants
or pollutant categories designated as toxic in the CWA.
Additional water quality documents that update en ten a
for selected consent decree chemicals and new criteria
have been published since 1980. These WQC are
numerical concentration limits that are EPA's best
estimate of concentrations protective of human health
and the presence and uses of aquatic life. Although
these WQC play an important role in ensuring a
healthy aquatic environment, they alone are not
sufficient to ensure the protection of environmental or
human health.
Toxic pollutants in bottom sediments of the
nation's lakes, rivers, wetlands, estuaries, and marine
coastal waters create the potential for continued
environmental degradation even where water column
concentrations comply with established WQC. In
addition, contaminated sediments can be a significant
pollutant source that may cause water quality
degradation to persist, even when other pollutant
sources are stopped. The absence of defensible
sediment guidelines makes it difficult to accurately
assess the extent of the ecological risks of
contaminated sediments and to identify, prioritize, and
implement appropriate cleanup activities and source
controls.
As a result of the need for a procedure to assist
regulatory agencies in making decisions concerning
contaminated sediment problems, the EPA Office of
Science and Technology. Health and Ecological Criteria
Division (OST/HECD) established a research team to
review alternative approaches (Chapman. 1987). All of
the approaches reviewed had both strengths and
weaknesses, and no single approach was found to be
applicable for guidelines derivation in all situations
(U.S. EPA. 1989a). The equilibrium partitioning (EqP)
approach was selected for nomonic organic chemicals
because it presented the greatest promise for
generating defensible, national, numerical chemical-
specific guidelines applicable across a broad range of
sediment types. The three principal observations that
underlie the EqP approach of establishing sediment
guidelines are as follows:
1 The concentrations of nomonic organic chemicals
in sediments, expressed on an organic carbon
basis, and in interstitial waters correlate to
observed biological effects on sediment-dwelling
organisms across a range of sediments. '
2. Partitioning models can relate sediment
concentrations for nomonic organic chemicals on
an organic carbon basis to freely-dissolved
chemical concentrations in interstitial water.
3. The distribution of sensitivities to chemicals of
benthic organisms is similar to that of water column
organisms; thus, the currently established WQC
final chronic values (FCV) can be used to define
the acceptable effects concentration of a chemical
freely-dissolved in interstitial water.
The EqP approach, therefore, assumes that
(1) the partitioning of the chemical between sediment
organic carbon and interstitial water is at or near
equilibrium; (2) the concentration in either phase can be
predicted using appropriate partition coefficients and
the measured concentration in the other phase
(assuming the freely-dissolved interstitial water
concentration can be accurately measured); (3)
organisms receive equivalent exposure from water-only
exposures or from any equilibrated phase: either from
interstitial water via respiration, from sediment via
ingestion or other sediment-integument exchange, or
from a mixture of both exposure routes; (4) for nomonic
chemicals, effect concentrations in sediments on an
organic carbon basis can be predicted using the
organic carbon partition coefficient (AT^) and effects
concentrations in water; (5) the FCV concentration is an
appropriate effects concentration for freely-dissolved
chemical in interstitial water; and (6) the equilibrium
partitioning sediment guideline (ESG), derived as the
product of the K^ and FCV, is protective of benthic
organisms. ESG concentrations presented in this
document are expressed as ^g chemical/g sediment
1-1
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Introduction
organic carbon t^g/g^) and not on an interstitial water
basis because (1) interstitial water is difficult to sample
and (2) significant amounts of the dissolved chemical
may be associated with dissolved organic carbon; thus,
total chemical concentrations in interstitial water may
overestimate exposure.
Sediment guidelines generated using the EqP
approach (i.e.. ESGs) are suitable for use in providing
guidance to regulatory agencies because they are:
1 Numerical values
Z Chemical specific
3. Applicable to most sediments
4 Predictive of biological effects
5. Protective of benthic organisms
ESGs are derived using the available scientific data to
assess the likelihood of significant environmental
effects to benthic organisms from chemicals in
sediments in the same way that the WQC are derived
using the available scientific data to assess the
likelihood of significant environmental effects to
organisms in the water column. As such. ESGs are
intended to protect benthic organisms from the effects
of chemicals associated with sediments and. therefore,
only apply to sediments permanently inundated with
water, to intemdal sediment, and to sediments
inundated periodically for durations sufficient to permit
development of benthic assemblages. ESGs should not
be applied to occasionally inundated soils containing
terrestrial organisms, nor should they be used to
address the question of possible contamination of
upper trophic level organisms or the synergistic,
additive, or antagonistic effects of multiple chemicals
The application of ESGs under these conditions may
result in values lower or higher than those presented in
this document.
The ESG values presented herein represent EPA's
best recommendation of the concentration of dieldnn in
sediment that will not adversely affect most benthic
organisms. EPA recognizes that these ESG values may
need to be adjusted to account for future data. They
may also need to be adjusted because of site-specific
considerations. For example, in spill situations, where
chemical equilibrium between water and sediments
has not yet been reached, sediment chemical
concentrations less than the ESG may pose nsks to
benthic organisms. This is because for spills.
disequilibrium concentrations in interstitial and
overlying water may be proportionally higher relative to
sediment concentrations Research has shown that the
source or "quality" of total organic carbon (TOC) in the
sediment does not affect chemical binding (DeWitt et
al., 1992) However, the physical form of the chemical in
the sediment may have an effect. At some sites
concentrations in excess of the ESG may not pose nsks
to benthic organisms, because the compound may be a
component of a paniculate, such as coal or soot, or
exceed solubility such as undissolved oil or chemical
In these situations, the national ESG would be overly
protective of benthic organisms and should not be
used unless modified using the procedures outlined in
"Methods for the Derivation of Site-Specific
Equilibrium Partitioning Sediment Guidelines (ESGs) for
the Protection of Benthic Organisms" (U.S EPA.
2000b). The ESG may be underprotective where the
toxicity of other chemicals are additive with the ESG
chemical or where species of unusual sensitivity occur
at the site.
This document presents the theoretical basis and
the supporting data relevant to derivation of the ESG
for dieldnn. The data that support the EqP approach
for deriving an ESG for nomonic organic chemicals are
reviewed by Di Toro et al (1991) and EPA (US. EPA.
2000a). Before proceeding through the following text.
tables, and calculations, the reader should consider
reviewing "Guidelines for Denving Numerical National
Water Quality Criteria for the Protection of Aquatic
Organisms and Their Uses" (Stephan et al.. 1985).
"Response to Public Comnient" (U.S. EPA, 1985). ar 1
'Technical Basis for the : 'envation of Equilibrium
Partitioning Sediment Gu. -Unes (ESGs) for the
Protection of Benthic Org~ usms: Nonionic Organics
(U.S. EPA. 2000a). Guidance for acceptable use of ESG
values is contained in "Implementation Framework for
the Use of Equilibrium Partitioning Sediment Guidelines
(ESGs)" (U-S. EPA, 2000c).
1.2 General Information: Dieldrin
Dieldnn is the common name of a persistent,
nonsystemic organochlorine insecticide used for
control of public health insect pests, termites, and
locusts. It is formulated for use as an emulsifiable
concentrate, as a wettable and dustable powder, or as a
granular product. Another source of dieldnn in the
environment other than from direct use of dieldnn
stems from the quick transformation of aldrin. also an
organochlorine pesticide, to dieldnn. Both dieldrin and
aldnn usage peaked in the mid-1960s and declined until
the early 1970s All dieldrin products were canceled
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Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
(including aldrin) in a PR notice. 71-4. dated March 18.
1971. See also Code of Federal Regulations (CFR)
notice 37246. dated October 18.1974.
Structurally, dieldnn is a cyclic hydrocarbon
having a chlorine substituted methanobndge (Figure
1-1). It is similar to endnn. an endo-endo stereoisomer,
and has similar physicochemical properties, except that
it is more difficult to degrade in the environment
(Wang. 1988) Dieldnn is a colorless crystalline solid at
room temperature, with a melting point of about 176 °C
and specific gravity of 1 75 g/cc at 20°C. It has a vapor
pressure of 0.4 mPa (20°C) (Hartley and Kidd. 1987).
Dieldrin is considered to be toxic to aquatic
organisms, bees, and mammals (Hartley and Kidd,
1987). The acute toxicity of dieldnn ranges from genus
mean acute values (GMAVs) of 0.50 to 740 /^g/L for
freshwater organisms and 0.70 to 640 Mg/L for saltwater
organisms (Appendix A). Differences between dieldnn
concentrations causing acute lethality and chronic
toxicity in species acutely sensitive to this insecticide
MOLECULAR FORMULA
MOLECULAR WEIGHT
DENSITY
MELTING POINT
PHYSICAL FORM
VAPOR PRESSURE
CAS NUMBER:
TSL NUMBER:
COMMON NAME:
TRADE NAME:
CI
380.93
1.75 g/cc (20°Q
176°C
Colorless crystal
0.40 mPa (20 °C)
60-57-1
1015750
Dieldrin (also dieldrine and ndieldrin)
Endrex (Shell); Hexadrin
CHEMICAL NAME: 1,2^,4,10,10, hexachloro-lR, 4S, 4aS, 5R, 6R, 7S, 8SR, 8aR-
octahydro-6,7-epoxy-l, 4:5,8-dimethanoaphthalene (IUPAC)
Figure 1-1. Chemical structure and physical-chemical properties of dieldnn (from Hartley and Kidd, 1987).
1-3
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Introduction
are small; acute-chronic ratios (ACRs) range from 1.189
to 11 39 for three species (see Table 3-2 in Section 3.3).
Dieldnn bioconcentrates in aquatic animals from 400 to
68.000 times the concentration in water (U.S. EPA,
1980a). The WQC for dieldnn (U.S. EPA, 1980a) is
derived using a Final Residue Value (FRY) calculated
using bioconcentration data and the Food and Drug
Administration (FDA) action level to protect
marketability of fish and shellfish: therefore, the WQC
is not "effects based " In contrast, the ESG for dieldrin
is effects based. It is calculated from the FCV derived -
in Section 3.
1.3 Applications of Sediment Guidelines
ESGs are meant to be used with direct toxicity
testing of sediments as a method of evaluation. They
provide a chemical-by-chemical specification of what
sediment concentrations are protective of benthic
aquatic life. The EqP method should be applicable to
nomonic organic chemicals with a ATOW above 3.0.
Examples of other chemicals to which this methodology
applies include endnn, metal mixtures (Cd, Cu. Pb. Ni,
Ag. Zn), and polycyclic aromatic hydrocarbon (PAH)
mixtures.
EPA has developed both Tier 1 and Tier 2 ESGs to
reflect the differing degrees of data availability and
uncertainty. The minimum requirements to derive a Tier
1 ESG include (1) an octanol-water partitioning
coefficient (KQV/) of the chemical, measured with
current experimental techniques, which appears to
remove the large variation in reported values; (2)
derivation of the FCV. which should also be updated to
include the most recent toxicological information; and
(3) sediment toxicity "check" tests to verify EqP
predictions. Check experiments can be used to verify
the utility of EqP for a particular chemical. As such, the
ESGs derived for nonionic organics. such as dieldnn
and endrin, metal mixtures, and PAH mixtures represent
Tier 1 ESGs (US. EPA. 2000d.e.f). In comparison, the
minimum requirements for a Tier 2 ESG include a Kow
for the chemical (as described above) and the use of
either a FCV or secondary chronic value (SCV). The
performance of sediment toxicity tests is recommended.
but not required for the development of Tier 2 ESGs
Therefore, m comparison to Tier 1 ESGs. the level of
protection provided by the Tier 2 ESGs would be
associated with more uncertainty due to the use of the
SCV and absence of sediment toxicity tests Examples
of Tier 2 ESGs for nomomcs are found in US EPA
(2000g). Information on how EPA recommends ESGs be
applied in specific regulatory programs is described in
the "Implementation Framework for the Use of
Equilibrium Partitioning Sediment Guidelines (ESGs)"
(EPA,2000c).
1.4 Overview
Section 1 provides a brief review of the EqP
methodology and a summary of the physical-chemical
properties and aquatic toxicity of dieldnn. Section 2
reviews a variety of methods and data useful in
denving partition coefficients for dieldrin and includes
the KQC recommended for use in deriving the dieldnn
ESG. Section 3 reviews aquatic toxicity data contained
in the dieldnn WQC document (U.S. EPA. 1980a) and
new data that were used to denve the FCV used in this
document to denve the ESG concentration. In addition.
the comparative sensitivity of benthic and water
column species is examined, and justification is
provided for use of the FCV for dieldnn in the
derivation of the ESG. Section 4 reviews data on the
toxicity of dieldrin in sediments, the need for organic
carbon normalization of dieldrin sediment
concentrations, and the accuracy of the HqP prediction
of sediment toxicity using K^ and an e ect
concentration in water. Data from Secti rs 2, 3, and 4
are used in Section 5 as the basis for the uen vation of
the ESG for dieldnn and its uncertainty. The ESG for
dieldrin is then compared with three databases on
dieldnn's environmental occurrence in sediments
Section 6 concludes with the guideline statement for
dieldrin. The references cited in this document are
listed in Section 7.
1-4
-------
Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
Section 2
Partitioning
2.1 Description of EqP Methodology
ESGs are the numerical concentrations of
individual chemicals that are intended to be predictive
of biological effects, protective of the presence of
benthic organisms, and applicable to the range of
natural sediments from lakes, streams, estuaries, and
near-coastal marine waters. As a result, they can be
used in much the same way as WQC, that is. the
concentration of a chemical that is protective of the
intended use, such as aquatic life protection. For
nonionic organic chemicals, ESGs are expressed as ^g
chemical/goc and apply to sediments having 20.2%
organic carbon by dry weight. A brief overview
follows of the concepts that underlie the EqP
methodology for deriving ESGs. The methodology is
discussed in detail in "Technical Basis for the
Derivation of Equilibrium Partitioning Sediment
Guidelines (ESGs) for the Protection of Benthic
Organisms: Nonionic Organics" (U.S. EPA. 2000a).
hereafter referred to as the ESG Technical Basis
Document.
B loavailabihty of a chemical at a particular
sediment concentration often differs from one sediment
type to another. Therefore, a method is necessary for
determining ESGs based on the bioavailable chemical
fraction in a sediment. For nonionic organic chemicals.
the concentration-response relationship for the
biological effect of concern can most often be
correlated with the interstitial water (i.e., pore water)
concentration (^g chemical/L interstitial water) and not
with the sediment chemical concentration (/ig chemical/
g sediment) (Di Toro et al.. 1991) From a purely
practical point of view, this correlation suggests that if
it were possible to measure the interstitial water
chemical concentration, or predict it from the total
sediment concentration and the relevant sediment
properties, then that concentration could be used to
quantify the exposure concentration for an organism.
Thus, knowledge of the partitioning of chemicals
between the solid and liquid phases in a sediment is a
necessary component for establishing ESGs. For this
reason, the methodology described below is called the
EqP method
The ESG Technical Basis Document shows that
benthic species, as a group, have sensitivities similar to
all benthic and water column species tested (taken as a
group) to derive the WQC concentration for a wide
range of chemicals. The data showing this for dieldrin
are presented in Section 3.4. Thus, an ESG can be
established using the FCV, calculated based on the
WQC Guidelines (Stephan et al.. 1985). as the
acceptable effect concentration in interstitial or
overlying water (see Section 5). The partition
coefficient can then be used to relate the interstitial
water concentration (i.e., the calculated FCV) to the
sediment concentration via the partitioning equation.
This acceptable effect concentration in sediment is the
ESG
The ESG is calculated as follows. Let FCV (Mg/L) be
the acceptable concentration in water for the chemical of
interest, then compute the ESG using the partition
coefficient, Kp QJk%xaaaem), between sediment and water
ESG = KfFCV
(2-1)
This is the fundamental equation used to generate the
ESG. Its utility depends on die existence of a
methodology for quantifying Kp.
Organic carbon appears to be the dominant
sorption phase for nonionic organic chemicals in
naturally occurring sediments and, thus, controls the
bioavailability of these compounds in sediments.
Evidence for this can be found in numerous toxicity
tests, bioaccumulation studies, and chemical analyses
of interstitial water and sediments (Di Toro et al., 1991).
The evidence for dieldrin is discussed in this section
and in Section 4. The organic carbon binding of a
chemical in sediment is a function of that chemical's
/LOC and the weight fraction of organic carbon in the
sediment (/or-). The relationship is as follows
(2-2)
(2-3)
It follows that
2-1
-------
Partitioning
where ESG^ is the ESG on a sediment organic carbon
basis For nonionic organics, the ESG term usually
refers to a value that is organic carbon-normalized
(more formally ESG^-) unless otherwise specified.
KQC is not usually measured directly (although it
can be done, see Section 2.3). Fortunately, Af^ is
closely related to the octanol-water partition
coefficient (Kow). which has been measured for many
compounds and can be measured very accurately. The
next section reviews the available information on the
K for dieldrin.
2.2
Determination of KQVV for Dieldrin
Several approaches have been used to determine
KQW for the derivation of an ESG, as discussed in the
ESG Technical Basis Document. In an examination of -
the literature, primary references were found listing
measured log,0Kow values for dieldrin ranging from
4 09 to 6.20 and estimated log,0Kow values ranging
from 3.54 to 5.40 (Table 2-1). Karickhoff and Long (1995.
1996) established a protocol for recommending KQW
values for uncharged organic chemicals based on the
best available measured, calculated, and estimated data.
The recommended loglo/LOW value of 5.37 for dieldrin
from Karickhoff and Long (1995) will be used to derive
theESGfordieldnn.
2.3 Derivation of KQC from Adsorption
Studies
Two types of experimental measurements of K^
are available. The first type involves experiments
designed to measure the partition coefficient in particle
suspensions. The second type is from sediment
toxicity tests in which measurements of sediment
dieldrin, sediment TOC, and calculated freely-dissolved
concentrations of dieldnn in interstitial water were used
to compute K.
oc-
2.3.1 KQf. from Particle Suspension Studies
Laboratory studies to characterize adsorption are
generally conducted using particle suspensions The
high concentrations of solids and turbulent conditions
necessary to keep the mixture in suspension make data
interpretation difficult as a result of the particle
interaction effect. This effect suppresses the partition
coefficient relative to that observed for undisturbed
sediments (Di Toro, 1985; Mackay and Powers, 1987).
Based on analysis of an extensive body of
experimental data for a wide range of compound types
and experimental conditions, the particle interaction
model (Di Toro, 1985) yields the following relationship
for estimating Kp
(2-4)
where m is the particle concentration in the suspension
(kg/L) and ux, an empirical constant, is 1 4. The K^ is
given by
= O-00028 + °-983 kgio
(2-5)
Figure 2-1 compares observed partition coefficient
data for the reversible component with predicted values
estimated with the particle interaction model (Equations
2-4 and 2-5) for a wide range of compounds (Di Toro,
Table 2-1. Dieldrin
Method
Measured
Measured
Measured
Measured
Measured
Estimated
Estimated
measured and estimated logto£ow values
Log,oA:w
4.09
4.54
465
5.40
620
3.54
540
Reference
Ellington and Stancu, 1988
Brooke etaL, 1986
DeKock and Lord. 1987
De Bruijn et al., 1989
Bnggs. 1981
Mabeyetal., 1982
Kane khoffetal.. 1989
2-2
-------
Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
1985) The observed partition coefficient for dieldnn
using adsorption data (Sharom et al.. 1980) is
highlighted on this plot. The observed log WK of 1.68
reflects significant particle interaction effects. The
observed partition coefficient is more than an order of
magnitude lower than the value expected in the absence
of particle effects (i.e.. Iog10tfp = 3.32 from tiief^K^ =
210017kg). KQC was computed from Equation 2 -5.
Several sorption isotherm experiments with particle
suspensions that provide an additional way to compute,
^oc were found in a comprehensive literature search for
partitioning information for dieldnn (Table 2 -2). The
KQC values derived from these data are lower than KQC
values from laboratory measurements of Kow. The
lower KQC can be explained from the particle interaction
effects. Partitioning in a quiescent setting would result
in less desorption and higher K^. These data are
presented as examples of panicle interaction if 100%
reversibility is assumed in the absence of desorption
studies and actual /LQ,, cannot be computed. In the
absence of particle effects, K^^ is related to Kow via
Equation 2 -5 For log10Kow = 5 37 (Kanckhoff and
Long, 1995), this expression results in an estimate of
2.3.2 Kf^from Sediment Toxicity Tests
Measurements of K^ were available from
sediment toxicity tests using dieldnn (Hoke and
Ankley, 1992). These tests used a sediment having an
-2
DIELDRIN
2
Predicted Iog10«_(L/kg)
Figure 2-1. Observed versus predicted partition coefficients for nonionic organic chemicals, using Equation 2-4
(figure from Di Toro, 1985). Dieldrin datum is highlighted (Sharom et al., 1980).
2-3
-------
Partitioning
Table 2-2. Summary of Koc values for dieldrin derived from literature sorption isotherm data
Observed Log^AT^ (SD)a
4.20(0-14)
4.14(015)
410
n
4
3
1
Solids (SD)a
(g/L)
50
16.4(4.6)
100.0
Reference
Eye. 1968
Betsill. 1990
Bnggs. 1981
aSD = Standard deviation
average organic carbon content of 1.75% (Appendix B).
Dieldrin concentrations were measured in sediments
and m unfiltered interstitial waters, providing the data
necessary to calculate the partition coefficient for an
undisturbed bedded sediment Note that data from
Hoke et al. (1995) were not used to calculate the
partition coefficient because either interstitial water was
not measured or free interstitial water could not be
correctly calculated. Since it is likely that organic
carbon complexing in interstitial water is significant for
dieldrin. organic carbon concentrations were also
measured in interstitial water. Figure 2-2A is a plot of
the organic carbon-normalized sorption isotherm for
dieldnn. where the sediment dieldnn concentration (^g/
gof.) is plotted versus the calculated free (dissolved)
interstitial water concentration (Mg/L). Using interstitial
water dissolved organic carbon (DOC) concentrations,
and assuming ATDOC, the dissolved organic carbon
partition coefficient, is equal to K^. the calculated free
interstitial water dieldnn concentration Cd (^g/L)
presented in Figure 2-2 is given by
cd = -
(2-6)
where Cw is the measured total interstitial water
concentration and mDOC is the measured DOC
concentration (U.S. EPA. 2000a). The data used to
make this plot are included in Appendix B. The line of
unity slope corresponding to the log,,,/^ = 5 28.
derived from the dieldrin log10Afow of 5.37 from
Karickhoff and Long ( 1995), is compared with the data
The data from the sediment toxicity tests fall on the line
of unity slope for log^/^. = 5 .28 (Figure 2-2A).
A probability plot of the observed experimental
Io8io*oc values 1S shown in Figure 2-2B. The log^K^
values were approximately normally distributed with a
mean of log,^^ = 5.32 and a standard error of the
mean (SE) of 0. 109. This value is in agreement with
lognj/^Qj, = 5.28. which was computed from the
Kanckhoff and Long (1995) dieldnn log,0#owof 5.37
(Equation 2-5).
2.4 Summary of Derivation of KQC for
Dieldrin
The KQC selected to calculate the ESG for dieldnn
was based on the regression of log^tf^ to log,0/LOW
(Equation 2-5) using the dieldnn Iog10£ow of 5.37 from
Karickhoff and Long ( 1995). This approach, rather than
the use of the KQ^ from toxicity tests, was adopted
because the regression equation is based on the most
robust dataset available that spans a broad range of
chemicals and particle types, thus encompassing a wide
range of Kow and/Q,-. values. The regression equation
yielded a log,0AToc= 5 28. This value was in agreement
with the lognj^oc of 5.32 measured in the sediment
toxicity tests.
2-4
-------
Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
sxi
3
e
U
*>
«
'5
^
eZ
41
(/]
.Q
o
100000
10000
1000
100
10
I I I I I III I
ins
C A
Hoke and Ankky, 1992
I I I I I I III I I I I I Illl I I I I I I III I I I I I I II
0.1
1 10 100
Free Interstitial Water Concentration (^g/L)
1000
6.00
5.75
5.50
5.25
5.00
4.75
4.50
4.25
4.00
i i mini i M i inn
. B
-
-
i i mini i i 1 1 inn
i i i
i i i
i i i
. *
i i i
inn 1 1 i i mini i i
-
~
-
HUM i i i mini i i
0.1
10 20 50 80 90
Probability
99
99.9
Figure 2-2. Organic carbon-normalized sorption isotherm for dieldrin (A) and probability plot of K^ (B) from
sediment toxicity tests (Hoke and Ankley, 1992). The solid line represents the relationship predicted
with a log of 5.28.
2-5
-------
Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
Section 3
Toxicity of Dieldrin in
Water Exposures
3.1 Derivation of Dieldrin WQC
The EqP method for derivation of the ESG for
dieldnn uses the WQC FCV and K^ to estimate the
maximum concentrations of noniomc organic
chemicals in sediments, expressed on an organic
carbon basis, that will not cause adverse effects to
benthic organisms. For this document, life-stages of
species classified as benthic are either species that live
in the sediment (infaunal) or on the sediment surface
(epibenthic) and obtain their food from either the
sediment or water column (US. EPA, 2000a) In this
section, the FCV from the dieldnn WQC document
(U.S. EPA. 1980a) is revised using new aquatic toxicity
test data, and the use of this FCV is justified as the
effects concentration for the ESG derivation.
3.2 Acute Toxicity in Water Exposures
A total of 116 standard acute toxicity tests with
dieldnn have been conducted on 28 freshwater species
from 21 genera (Figure 3-1. Appendix A). Of these
tests, 38 were from 1 study with the guppy, Poecilla
reticulata (Chadwick and Kiigemagi, 1968). Some of
the values from this study have been omitted because
they came from tests using water from generator
columns that had not yet equilibrated. In some cases
this may have led to toxicity related to unmeasured
compounds, which the authors thought might have
skewed the results. Similar logic was used to choose
appropriate values in the WQC for dieldnn (U.S. EPA.
1980a). Overall GMAVs ranged from 0.5 to 740 Mg/L-
Stoneflies. fishes, isopods, damselflies, glass shrimp,
and annelids were most sensitive; GMAVs for these
taxa range from 0.5 to 21.8 Mg/L- This database
contained 18 tests on 15 benthic species from 13
genera (Figure 3-1, Appendix A).
Benthic organisms were among both the most
sensitive and the most resistant freshwater species to
dieldnn. GMAVs ranged from 0.5 to 740 ng/L. Of the
epibenthic species tested, stoneflies, catfish, mayflies,
isopods. and glass shrimp were most sensitive, GMAVs
ranged from 0.5 to 20 Mg/L- Infaunal species tested
included only the oligochaete Lumbnculus vane gat us
(LC50=21.8 Mg/L) and the stoneflies, Pteronarcys
californica (LC50=0.5 ^g/L) and Pteronarcella badia
(LC50=0 5 Mg/L). The LC50 represents the chemical
concentrations estimated to be lethal to 50% of the test
organisms within a specified time-penod.
A total of 29 acute tests have been conducted on
22 saltwater species from 20 genera (Figure 3-1:
Appendix A). Overall GMAVs ranged from 0 70 to
640 Mg/L. Sensitivities of saltwater organisms were
similar to those of freshwater organisms. Fishes and
crustaceans were the most sensitive. Within this
database there were results from 20 tests on benthic
life-stages of 15 species from 13 genera (Figure 3-2;
Appendix A). Benthic organisms were among both the
most sensitive and the most resistant saltwater genera
to dieldnn. The most sensitive benthic species was the
pink shrimp, Peneaus duorarum, with a measured
flow-through 96-hour LC50 of 0.70 Mg/L. The
American eel, Anquilla rostrata, had a similar
sensitivity to dieldnn, with a 96-hour LC50 of 0.9 /^g/
L. Other benthic species for which there were data
appeared less sensitive, with GMAVs ranging from 45
to>100Mg/L.
3.3 Chronic Toxicity in Water
Exposures
Chronic toxicity tests have been conducted with
dieldnn using three freshwater fish and two saltwater
invertebrates. The fish include rainbow trout.
Oncorhynchus myktss, the guppy, P. reticulata, and the
fathead minnow, Pimephales prvmelas. The
invertebrates include the mysid. Americamysis bahia.
and the polychaete worm, Ophryotrocha diadema
(Table 3-1). Both O. mykiss and/4, bahia have benthic
life-stages.
Brooke (1993a) conducted an early life stage test
with O mykiss. There were reductions of 35% in
survival. 34% in weight, and 13% in length of the
3-1
-------
Toxicity of Dieldrin in Water Exposures
1000
100
4*
I
9
4J
l/l
3
10
0.1
A Arthropods
Other Invertebrates
Fish and Amphibians
Orconectes (A)
Gammarus (A.X)
Sunocephalus (J.X)^
Daphnia (A J.X)j
Bufo
Psuedocru (L) ]
Carassius (J.X)
Micropterus (X)
Palaemonetes (X)
Lepomis (J)
Ictalurus (X)
Pimephales (J)
Ischnura (J)
Tilapia (J)
'Oncorhyncus (J.X)
Lumbriculus (A)
Claassema (J)
' Pteronacella (J)
Pteronarcys (J.N)
20 40 60 80
Percentage Rank of Freshwater Genera
100
Figure 3-1. Genus mean acute values from water-only acute toxicity tests using freshwater species versus percentage
rank of their sensitivity. Symbols representing benthic species are solid; those representing water column
species are open. A=adult, J=juvenile, N=naiads, X=unspecified life-stage.
survivors in the 0.95 ngfL treatment relative to control
fish. O. my kiss were not significantly affected at
concentrations of 0.04 to 0.55 Mg/L- The chronic value
based on these results is 0.7228 Mg/L- Combined with
the 96-hour companion acute value of 8.23 Mg/L
(Brooke, 1993a), the ACR for this species is 11.39
jug/L (Table 3-2).
McCauley (1997) conducted an early life-stage test
with the fathead minnow, P promelas. There was a
91% reduction in survival in the 6 87 /^g/L treatment
relative to control fish. Fathead minnows were not
significantly affected at concentrations of 0.38 to 3.02
Mg/L. There were no effects on growth or reproduction
recorded at any concentration tested. The chronic
value based on these results is 4 555 ^g/L. Two 96-
hour LC50 tests were also conducted in the same
dilution water as this test. One test was done with 30-
day-old juveniles (LC50=4.45 Mg/L), the other test was
done with <24-hour-old larvae (LC50=6.59 /zg/L)
Because the LC50 values were from flow-through
measured tests and were similar, the geometric mean of
3-2
-------
Equilibrium Partitioning Sediment Guidelines (ESGs): Diddrin
1000
100
1
£
V
feri
u
e
M
10
0.1
A Arthropods
Other Invertebrates
Fish and Amphibians
Crassostrea (A)
MuP' W
Palaemoneta (A)
Gasterosteus (J) . _
Palaemon (A)
Mysidopsis W
Micrometnu (A)
Thalassoma (A)
Menidia (J)
Cymatogaster (J)
1 Oncorhynchus (J)
i Anguilla(J)
' Penaeus (A)
20 40 60
Percentage Rank of Saltwater Genera
80
100
Figure 3-2. Genus mean acute values from water-only acute toxicity tests using saltwater species versus percentage
rank of their sensitivity. Symbols representing benthic species are solid; those representing water
column species are open. Asterisk indicates greater than values. A=adult, J=juvenile.
these two values (S.415 ^g/L) was used in the
calculation of the ACR. which is 1.189 Mg/L for this
species (Table 3-2).
Four freshwater chronic tests failed to meet the test
requirement of a measured concentration for use in
deriving WQC because there were no acceptable
companion acute tests from the same dilution water.
Therefore, the results of these tests were not used in the
calculation of the final ACR (FACR). Although an
ACR cannot be calculated from these data, the chronic
results are presented in Tables 3-1 and 3-2 to help
establish the chronic effect levels of dieldrin for these
species. One of these tests was an early life-stage test
conducted with O. mykiss (Chadwick and Shumway,
1969). There were reductions of 97% in survival and
36% in growth of the survivors in the 0 39 ^g/L
treatment relative to control fish, and all fish died at 1 2
Mg/L dieldnn. Oncorhynchus mykiss were not
significantly affected at concentrations of 0 012 to 0.12
Mg/L and no progeny were tested. The other freshwater
chronic test that did not meet the "measured
3-3
-------
Toxicity of Dieldrin in Water Exposures
Table 3-1. Test-specific data for chronic sensitivity of freshwater and saltwater organisms to dieldrin
Habitat
c c
Common Name. (life- Duration NOECs OECs
Scientific Name Test stage) (days) G^g/L) (^g/L)
Freshwater Species
Rainbow trout. ELS W 100 0 012-0 12d ° 39-
Oncorhynchus 1 -^
mykiss
-
Rainbow trout. ELS W 28 0.04-055 095
Oncorhynchus
mykiis
Guppy. LC W 195 005.0.2,
Poecdia l.Qd ~
reticulata
Guppy. LC W 195 0.2.1.0.2.5d ~
Poecdia
reticulata
Guppy. LC W 195 0.2. 2.5d 1.0d
Poecdia
reticulata
Fathead ELS W 30 038302 687
minnow.
Pimephales
promelas
Saltwater Species
Mysid. LC E(J.A) 28 010.049 022.
Amencamysis 1 1. 1.6
bahia
Polychaete LC I (L) 47 0.1 0.3-13
worm.
Oph ryotrocha
diadema
Polychaete PLC I (A) 37 12 2.6-72
worm.
Ophryotrocha
diadema
Observed Effects
(relative to
controls)
97 -100% decrease
in survival.
36% reduction in
growth
35% decrease in
survival.
13% reduction in
length. 34% in
weight
-
42% reduction in
brood size
9 1 % decrease in
survival
24-58% decrease
in survival
34% decrease in
survival.
37-99% reduction
in reproduction.
16-71% decrease
in progeny
survival
63% decrease in
survival.
57-100%
reduction in
reproduction
39- 100% decrease
in progeny
survival
Chronic
Value
G"g/L)
02163
07228
>10
>25
>2.5
4555
0.7342
0.1732
1.766
Reference
Chadwick
and
Shumway.
1969
Brooke.
1993a
" Roelofs.
1971
Roelofs.
1971
Roelofs.
1971
McCauley,
1997
EPA.
1980b
Hooftman
and Vmk.
1980
Hooftman
and Vink.
1980
LC = life-cycle. PLC = partial life-cycle. ELS = early life-stage.
bHabitat: I = infaunal. E = epibenthic. W = water column Life-stage: E = embryo, L = larval, J = juvenile. A = adult.
cNOECs = No observed effect concentration^). OECs = Observed effect concemranon(s)
Nominal, not measured.
^Estimated from graph.
fNominal (less than limit of analytical detection), all other values listed are measured values (there was good agreement between nominal
and measured)
3-4
-------
Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
Table 3-2. Summary of freshwater and saltwater acute and chronic values, acute-chronic ratios, and
derivation of the final acute values, final acute-chronic ratios, and final chronic values for dieldrin
Common Name.
Scientific Name
Acute Value
(96 hour)
(Mg/L)
Chrome
Value
teg/L)
Acute-Chronic
Ratio
(ACR)
Species Mean Acute -
Chronic Ratio
(SMACR)
Freshwater Species
Rainbow trout.
Oncorhynchus mykiss
Rainbow trout.
Oncorhynchus mykiss
Guppy.
Poecdia reticulata
Guppy,
Poecilia reticulata
Guppy.
Poecilia reticulata
Fathead minnow.
Pimephales promelas
Saltwater Species
Mysid,
Americamysis bahia
Polychaete worm.
Ophryotrocha diadema
Polychaete worm.
Ophryotrocha diadema
8.23
5.415
4.5
>100
>100
02163
0722«
>10a
>2-5a
0.447*
4.555
0.7342
01732
1.766
1139
1 189
6.129
>5774
>56 63
1139
1.189
6.129
>5774
aNot used in calculation of SMACR or FACR because acute value from matching dilution water is not available.
bAcute value geometric mean of test with 30-day-old juveniles and test with < 24-hour-old fish in the same dilution water (see text)
cNot used in calculation of SMACR or FACR because ACRs are greater than values. Also because the range of ACRs. if these are
included, is greater than a factor of 10 0. this species is much less acutely sensitive than the other species with available ACRs. and the
FAV derived with the other three ACRs is protective of this species (see text).
Freshwater
Final acute value = 0.2874 ^g/L
Final acute-chronic ratio = 4 362
Final chronic value = 0.06589 ^g/L
Saltwater
Final acute value = 0 6409^g/L
Final acute-chronic ratio = 4 362
Final chronic value = 0 1469 //g/L
concentrations" criteria was a three -generation study
using the guppy, P. reticulata (Roelofs. 1971). Only
data from three tests with the first-generation fish were
included in Tables 3-1 and 3-2 because the test
organisms in the second- and third-generation tests
received some exposure prior to testing. There was no
effect on P. reticulata survival at any dieldrin
concentration in the first test (from 0 05 to 1
in the second test (from 0.2 to 2.5 Mg/L)- In th
test, mean brood size was reduced by 42% at 1
The 32% reduction in growth at 25 //g/L was not
or
statistically significant. Because there were no
statistically significant differences from controls at the
highest concentration, the chronic value from this test
is considered to be >2.5
Saltwater A. bahia exposed to dieldnn in a life-
cycle test (US. EPA. 1987b) were affected at
concentrations similar to those affecting the two
freshwater fish mentioned above. Survival of A. bahia
exposed to 0.22. 11. and 16 ^g/L was reduced by
24%. 35%, and 58%. respectively, relative to control
3-5
-------
Toxicity of Dieldrin in Water Exposures
A. bahia. There were no significant effects at 0 49 Mg/
L. No effects were observed on reproduction at any
concentration tested, and progeny response was not
recorded. Based on these results, the chronic value for
A bahia is 0 7342 A*g/L. Combined with the 96-hour
companion acute value of 4 5 ^g/L (U S. EPA. 1987b).
the ACR for this species is 6 129
Two chronic tests were performed with saltwater
organisms that could not be used in the calculation of
the FACR because definitive companion acute values -
could not be calculated. One life-cycle test and one
partial life-cycle test were conducted with the marine
polychaete worm. O. diadema (Hooftman and Vmk,
1980) (see Tables 3-1 and 3-2) The nominal no
observed effect concentration (NOEC) was 0.1 ^g/L
(below the limit of analytical detection) for the life-
cycle test initiated with larvae and 1 2 ^g/L (based on
measured concentrations) for the partial life-cycle test
initiated with adults. For the life-cycle test with larvae,
there was a 37% to 99% decrease in reproductive
potential (combined effect on number of egg masses
and embryo survival), relative to earner control worms
at 0.3 to 13 i/g/L dieldrin. Progeny survival was
reduced by 35%, 16%. 61%. and 71% at dieldrin
concentrations of 0 3. 1.5. 3.1, and 13 Mg/L.
respectively. At 13 ^g/L dieldnn. larval survival was
reduced to 34% relative to the controls. The chronic
value for this test was 0.1732 Mg/L In the O. diadema
partial life-cycle test, reproductive potential was
reduced by 57%. 92%. 97%. and 100% relative to the
earner control in concentrations of 2.6. 8.0. 23. and 72
Mg/L. respectively. Of adults in 72 Mg/L. 63% died.
Reductions in egg survival were 39%, 70%, 62%, and
100% relative to controls in concentrations of 2 6, 8.0.
23. and 72 Mg/L. respectively. The chrome value for
this test was 1 766 Mg/L- over an order of magnitude
higher than that from the full life-cycle test. The
chronic sensitivity of this species appeared similar to
that of the other species tested chronically, but acute
sensitivity was low: 96-hour LC50 >100 ^g/L for
adults and larvae. The FCV calculated using the ACRs
available from other species is protective of this
species.
The final acute value (FAV) denved from the
overall GMAVs (Stephan et al. 1985) for freshwater
organisms was 0 2874 Mg/L (Table 3-2) The FAV
denved from the overall GMAVs (Stephan et al.. 1985)
for saltwater organisms was 0 6409 Mg/L (Table 3-2).
less than the acute value for the economically important
shrimp. P. duorarum. The available ACRs for three
species were 1.189 for P promelas. 6 129 for A bahia.
and 11.39 for 0. mykiss. The FACR. the geometric
mean of these three values, was 4 362. The FCVs
(Table 3-2) for calculating the ESG for dieldrin were
calculated by dividing both the freshwater and
saltwater FAV by the FACR. The FCV for freshwater
organisms of 0.06589 ^g/L was the quotient of the FAV
of 0.2874 yug/L and the FACR of 4 362. Similarly, the
FCV for saltwater organisms of 0.1469 ng/L was the
quotient of the FAV of 0.6409 Mg/L and the FACR of
4.362.
3.4 Applicability of the WQC as the
Effects Concentration for
Derivation of the Dieldrin ESG
Use of the FCV as the effects concentration for
calculation of the ESG assumes that benthic (infaunal
and epibenthic) species, as a group, have sensitivities
similar to all benthic and water column species tested
to derive the WQC concentration. Di Toro et al
(1991) and the ESG Technical Basis Document (U.S.
EPA, 2000a) present data supporting the
reasonableness of this assumption, over all chemicals
for which there were published or draft WQC
documents. The conclusion of similar sensitivity was
supported by comparisons between (1) acute values for
the most sensitive benthic species and acute values for
the most sensitive water column species for all
chemicals, (2) acute values for all benthic species and
acute values for all species in the WQC documents
across all chemicals after standardizing the LC50
values. (3) FAVs calculated for benthic jcies alone
and FAVs calculated for all species in th WQC
documents, and (4) individual chemical comparisons > *
benthic species versus all species. Only in this last
comparison were dieldrm-specific comparisons of the
sensitivity of benthic and all (benthic and water
column) species conducted. The following paragraphs
examine the data on the similarity of sensitivity of
benthic and all species for dieldrin used in this
comparison.
For dieldrin. benthic species account for 13 out of
21 genera tested in freshwater and 13 of 20 genera
tested in saltwater (Figures 3-1. 3-2, Appendix A). An
initial test of the difference between the freshwater and
saltwater FAVs for all species (water column and
benthic) exposed to dieldnn was performed using the
approximate randomization (AR) method (Noreen.
1989). The AR method tests the significance level of a
test statistic compared with a distnbution of statistics
generated from many random subsamples The test
3-6
-------
Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
statistic in this case was the difference between the
freshwater FAV. computed from the freshwater
(combined water column and benthic) species LC50
values, and the saltwater FAV. computed from the
saltwater (combined water column and benthic) species
LC50 values (Table 3-3) In the AR method, the
freshwater LC50 values and the saltwater LC50 values
(see Appendix A) were combined into one dataset.
The dataset was shuffled, then separated back so that
randomly generated "freshwater" and "saltwater" FAVs
could be computed. The LC50 values were separated
back such that the number of LC50 values used to
calculate the sample FAVs were the same as the number
used to calculate the original FAVs. These two FAVs
were subtracted and the difference used as the sample
statistic. This was done many times so that the sample
statistics formed a distribution representative of the
population of FAV differences (Figure 3-3A). The test
statistic was compared with this distribution to
determine its level of significance. The null hypothesis
was that the LC50 values composing the saltwater and
freshwater databases were not different. If this were
true, the difference between the actual freshwater and
saltwater FAVs should be common to the majority of
randomly generated FAV differences. For dieldnn. the
test statistic occurred at the 16th percentile of the
generated FAV differences. Because the probability
was less than 95%. the hypothesis of no significant
difference in sensitivity for freshwater and saltwater
species was accepted (Table 3-3) Note that in both the
freshwater versus saltwater comparison and benthic
versus WQC comparison, greater than (>) values for
GMAVs (see Appendix A) were omitted from the AR
analysis. This resulted in one dieldnn saltwater benthic
organism being omitted.
Because freshwater and saltwater species showed
similar sensitivity, a test of difference in sensitivity was
performed for benthic and all (benthic and water
column species combined, hereafter referred to as
"WQC") organisms combining freshwater and
saltwater species, using the AR method. For this
purpose, each life-cycle of each test organism was
assigned a habitat (Appendix A) using the criteria
observed by EPA (U.S. EPA. 2000a). The test statistic
in this case was the difference between the WQC FAV.
computed from the WQC LC50 values, and the benthic
FAV, computed from the benthic organism LC50
values. This was slightly different from the previous
test for saltwater and freshwater species in that
saltwater and freshwater species in the first test
represented two separate groups In this test, the
benthic organisms were a subset of the WQC organisms
set. In the AR method for this test, the number of data
points coinciding with the number of benthic organisms
was selected from the WQC dataset and a "benthic"
FAV was computed. The original WQC FAV and the
"benthic" FAV were then used to compute the
difference statistic. This was done many times, and the
resulting distribution was representative of the
population of FAV difference statistics. The test
statistic was compared with this distribution to
determine its level of significance. The probability
distribution of the computed FAV differences is shown
in Figure 3-3B. The test statistic for this analysis
occurred at the 68th percentile, and the hypothesis of
no difference in sensitivity was accepted (Table 3-3).
This analysis suggests that the FCV for dieldnn based
on data from all tested species was an appropriate
effects concentration for benthic organisms.
Table 3-3. Results of approximate randomization (AR) test for the equality of the freshwater and saltwater FAV
distributions for dieldnn and AR test for the equality of benthic and combined benthic and water column
(WQC) FAV distributions
Comparison
Habitat or Water Type
*'
AR Statistic
Probability
Freshwater vs Saltwater
Benthic vs Water Column = Benthic
(WQC)
Fresh (21)
Benthic (26)
Salt (19)
WQC (40)
-0334
0052
16
68
aValues in parentheses are the number of LC50 values used in the comparison.
Note that in both the freshwater vs. saltwater and benthic vs WQC comparisons, greater than (>) values in Appendix A were omitted.
This resulted in one dieldnn saltwater benihic organism being omitted from the AR analysis
CAR statistic = FAV difference between original compared groups
dProbabiiiry that the theoretical AR statistic <; the observed AR statistic, given that the samples came from the same population
3-7
-------
Toricity of Dieldrin in Water Exposures
I
3
W
e
i
5
^.
<
3
"Sb
3
0)
s
i
'c
>
£
5
4
3
2
1
0
-1
-2
-3
-4
iiiiiiiii i ii uiiii i i i i i i i iiiui ii i imnTTT"
~ A I
- Freshwater vs Saltwater ° -
0 -
00
" o -
0°
_ ,.tt-ftr{SP
i.||T|||||j||||r ^**^^
j.iiiTTnnti"1|f"'""
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- o
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_ o
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-
i i mini i i i 1 1 mi i i i i i i i mi 1 1 i i i mini i i
4
3
2
1
0
-1
-2
-3
-4
-5
i i mini iiiiiiiii i i i i i i i mi 1 1 i i i mini i i
i B :
- Benthic vs WQC
i w
~_ ~
_ o° _
-0 °
-
-
-
i i mini iiiiiiiii i i i i i i i iiiiiiiii mini i i
0.1 1 10 20 50 80 90 99 99.9
Probability
Figure 3-3. Probability distribution of FAY difference statistics to compare water-only data from freshwater versus
saltwater (A) and benthic versus WQC (B) data. The solid lines in the figure correspond to the FAV
differences measured for dieldrin.
3-8
-------
Equilibrium Partitioning Sediment Guidelines (ESGs): Diddrin
Section 4
Actual and Predicted Toxicity of
Dieldrin in Sediment Exposures
4.1 Toxicity of Dieldrin in Sediments
The toxicity of dieldrin-spiked clean sediments
was tested with two freshwater species (an amphipod
and a midge) and two saltwater species (a polychaete
and the sand shrimp) (Table 4-1). Therefore,
generalizations of dieldrin's toxicity across species or
sediments are limited. The endpomt reported in these
studies was mortality (with the addition of dry weight
in the midge tests). Details about exposure
methodology are provided because sediment testing
methodologies have not been standardized in the way
that water-only toxicity test methodologies have. Data
were available from many experiments using both
field and laboratory sediments contaminated with
mixtures of dieldrin and other compounds. Data from
these studies were not included here because it was
not possible to determine the contribution of dieldnn
to the observed toxicity.
The effects of sediment from three freshwater
sites in Minnesota spiked with dieldrin on the
freshwater amphipod. H. azteca, were studied by
Hoke et al. (1995) The TOC concentrations in the
three sediments were 1.7%, 2.9%, and 8.7%,
respectively. The sediments were rolled in dieldrin-
coated jars at 4°C for 23 days. Mortality of H.
azteca in these flow-through tests was related to
sediment exposure because dieldrin concentrations in
overlying water were generally below detection limits.
Given the "nonstandard" dose response in many of the
tests with H. azteca, the LC50 values from these tests
need to be examined carefully. In several of these
tests, toxicity increased with concentration up to an
intermediate concentration and then decreased with
further increasing concentration. It may be that the
amphipods were avoiding the sediment in the higher
concentrations by coming out of the sediment, thereby
limiting dieir exposure (R. Hoke. E.I. DuPont
deNemours and Co , Haskell Laboratory, Newark,
DE, personal communication) No dose-response
relationship was observed in the results from the
definitive test with one of the sediments (Airport
Pond) or m the results from further testing with this
sediment using H. azteca (Hoke et al., 1995). In at
least one of the Airport Pond sediment repeat
experiments, mortality seemed to be increasing at a
concentration similar to that causing 50% mortality in
die range-finder test, and then dropped off. For this
reason, only the Airport Pond data from die range-
finder test with diis sediment are used in the analysis
of the toxicity data (Sections 4. 1 , 4.2, 4 3) and in
Figures 4-1 and 4-2. The 10-day LC50 values
increased with increasing TOC when dieldrin
concentration was expressed on a dry weight basis,
but increased only slightly with increasing organic
carbon when dieldrin concentration was expressed on
an organic carbon basis (Table 4-1). Hoke et al.
(1995) calculated organic carbon-normalized
concentrations based on TOC measured in individual
treatments. This leads to the apparent discrepancy
between the experiment mean TOC values and die
organic carbon-normalized concentrations reported in
Tables 4-1 and 4-2 LC50 values normalized to dry
weight differed by a factor of 19.4 (22.8 to 441.8
Mg/g) over a fivefold range of TOC. In contrast, the
organic carbon-normalized LC50 values differed by a
factor of 3.2 (1,322 to 4.272
The effects of dieldrin-spiked sediments on die
fresh water midge, C. tertians, were also reported by
Hokeetal (1995). The TOC contents in the two
sediments were 15% and 20%. The sediments were
rolled in dieldrin-coated jars at 4°C for 30 days,
stored at 4°C for 60 days, and then rolled at 4°C for
an additional 30 days. LC50 values normalized to dry
weight differed by a factor of 3.0 (0.5 to 1.5 Mg/g dry
weight). LC50 values normalized to organic carbon
differed by a factor of 2 .7 (35 1 to 95 3 Mg/goc) II
is not surprising that organic carbon normalization had
little effect, given the small range of TOC (1.5% to
2.0%).
The only saltwater experiments diat tested
dieldrin-spiked sediments were conducted by McLeese
et al (1982) and McLeese and Metcalfe (1980)
These began with clean sediments diat were added to
4-1
-------
Actual and Predicted Toxicity of Dieldrin in Sediment Exposures
dieldrm-coated beakers just before the addition of test
organisms. This is a marked contrast with tests using
freshwater sediments spiked with dieldnn days or
weeks prior to test initiation. As a result, die dieldrin
concentrations in the sediment and overlying water
varied greatly over the course of these saltwater
experiments, and exposure conditions are uncertain.
In addition, transfer of test organisms to freshly
prepared beakers every 48 hours further complicates
interpretation of results of McLeese et al. (1982),
because exposure conditions changed several times
during the course of the test McLeese et al. (1982)
tested the effects of dieldrin on the polychaete worm,
Nereis virens, in sediment with 2% TOC (17% sand
and 83% silt and clay) in 12-day toxicity tests. No
worms died in 13 Mg/g dry weight sediment, the
highest concentration tested. McLeese and Metcalfe
(1980) tested the effects of dieldrin in sand with a
TOC content of 0.28% on the sand shrimp, Crangon
septemspinosa. The 4-day LC50 value was 0 0041
Mg/g dry weight sediment (1.46 Mg/goc)
Concentrations of dieldrin in water overlying the
Table 4-1. Summary of tests with dieldrin-spiked sediment
Sediment Dieldnn
Common Name.
Scientific Name
X
Sediment TOC
Source (%)
LC50
Method,
Duration Dry wt OC
(days) Response (^g/g) (^g/g)
Interstitial
Water
LC50
(Mg/L)
Reference
Freshwater Species
Amphipod.
Hyaletla azteca
Amphipod,
Hyalella azteca
Amphipod.
Hyalella azteca
Midge.
Chironomus
tentans
Midge.
Chironomus
tentans
Saltwater Species
Polychaete
worm. Nereis
virens
Sand shnmp.
Crangon
septemspinosa
Airport
Pond. MN
West
Bearskin
Lake. MN
Pequaywa
n Lake.
MN
Airport
Pond, MN
Airport
Pond. MN
17% sand.
83% silt
and claye
Sand, wet-
sieved
between
1-2 mm
sievese
1.7
29
8.7
20
15"
2.0
0.28
FT. M/10
FT. M/10
FT. M/10
FT. M/10
FT. M/10
R. M/12
R. M/4
LC50
LC50
LC50
LC50
LC50
228
43.4
4418
1.5
05
1.332
1.322V
4.272V
95.3"
35.
543
236
492
05
02
LC50
LC50
>650
0.0041 146
Hoke et al..
1995
Hokeetal.,
1995
Hoke et al..
1995
Hoke et al..
1995
Hoke et al.
1995
McLeese et
al. 1982
McLeese
and
Metcalfe.
1980
"FT = flow-through. M = measured. R = renewed
Mean reported TOC concentration
°CalcuIated using individually measured TOC concentrations s
Interstitial water concentrations estimated from/^. K^. and measured sediment concentrations
'Clean sediment placed in dieldnn-coated beakers at beginning of exposure
4-2
-------
Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
1
100
80
60
40
20
O Endrin
Dieldrin
G Phenanthrene
A Fluoranthene
V Acenaphthene
O Kepone
O
0.01
0.1
10
100
Interstitial Water Toiic Units
Figure 4-1. Percent mortalities of amphipods in sediments spiked with acenaphthene or phenanthrene (Swartz, 1991),
endrin (Nebeker et al., 1989; Schuytema et al., 1989), or fluoranthene (Swartz et al., 1990; DeWitt et al.,
1992), and midge in sediments spiked with dieldrin (Hoke et al., 1995) or kepone (Adams et al., 1985)
relative to interstitial water units.
sediment were 10 times the LC50 in water. The
authors concluded that sediment-associated dieldrin
contributed little to the toxiciry observed.
The need for organic carbon normalization of the
concentration of nomonic organic chemicals in
sediments is presented in the ESG Technical Basis
Document. For dieldrin. this need is supported by the
dieldrin-spiked toxiciry tests described above,
particularly the experiments with H. azteca by Hoke
et al. (1995). Although it is important to demonstrate
that organic carbon normalization is necessary if
guidelines are to be developed using the EqP
approach, it is fundamentally more important to
demonstrate that K^ and water-only effects
concentrations can be used to predict the effects
concentration for dieldrin and other nomonic organic
chemicals on an organic carbon basis for a range of
sediments Evidence supporting this prediction for
dieldrin and other nomonic organic chemicals is
contained in the following sections.
4.2 Correlation Between Organism
Response and Interstitial Water
Concentration
One corollary of the EqP theory is that freely-
dissolved interstitial water LCSO values for a given
organism should be constant across sediments of
varying organic carbon content (U.S. EPA, 2000a).
Measured or estimated interstitial water values were
available from studies with two species (Table 4-2)
Data from tests with water column species were not
considered in this analysis. Hoke et al (1995) found
that 10-day LC50 values for H. azteca based on
measured interstitial water concentrations differed by
a factor of 9.1 (54 3 to 491.6 uglL) for three
4-3
-------
Actual and Predicted Toxicity of Dieldrin in Sediment Exposures
sediments containing from 1.7% to 8.7% TOC
Therefore, interstitial water-normalized LC50 values
provided an improvement over LC50 values for
dieldnn expressed on a dry weight basis which varied
by a factor of 19.4 (22.8 to 441.8 Mg/g) (Table 4-1).
The authors proposed partitioning to DOC to explain
the small disparity between LC50 values based on
interstitial water dieldnn concentrations (Hoke et al ,
1995). They found that the 10-day LC50 values for
C. lemons based on predicted interstitial water
concentrations (the sediment concentration multiplied ,
by the K^; used because measured concentrations
were not available) differed by a factor of 2.8 (0.18 to
0.50). This variability was slightly less than that
shown when dry weight was used (factor of 3.0). but
similar to that shown when organic carbon
normalization was used (factor of 2 7)
/
A more detailed evaluation of the degree to which
the response of benthic organisms can be predicted
from toxic units (TUs) of substances in interstitial
water was made utilizing results from toxicity tests
with sediments spiked with a variety of noniomc
compounds, including acenaphthene and phenanthrene
(Swartz, 1991), dieldrin (Hoke et al , 1995), endrin
(Nebeker et al , 1989, Schuytema et al., 1989),
fluoranthene (Swartz et al., 1990; DeWitt et al.,
1992). and kepone (Adams et al., 1985) (Figure 4-1)
The data included in the following analyses were from
tests conducted at EPA laboratories or from tests that
utilized designs at least as rigorous as those conducted
at EPA laboratories. Tests with acenaphthene and
phenanthrene used two saltwater amphipods
(Leptocheirus plumulosus and Eohaustorius estuans)
and saltwater sediments. Tests with fluoranthene used
a saltwater amphipod (Rhepoxynius abronius) and
saltwater sediments. Freshwater sediments spiked
with dieldrin and endrin were tested using the
amphipod H. azieca, and kepone-spiked sediments and
dieldrin-spiked sediments were tested using the midge,
C. teruans.
Figure 4-1 presents the percent mortalities of the
benthic species tested in individual treatments for each
100
80
£ 60
38
1
* 40
?rt
0
^> Endrin
Dieldrin
O Phenanthrene
A Fluoranthene
^7 Acenaphthene
, ^ *
^£
. «
* &A3giHajij
.
,
1
1
gOjfcdJK
O V
L
a
in ^
A*A^
^f
£, al
Hfi7 IV
^ r*
i
, ,.,,1 _,
^oc> oo
9
^
V
3
,
0.01 0.1 1 10 100
Predicted Sediment Toxic Units With Uncertainty Bars
Figure 4-2. Percent mortalities of amphipods in sediments spiked with acenaphthene or phenanthrene (Swartz, 1991),
dieldrin (Hoke et al., 199S), endrin (Nebeker et al., 1989; Schuytema et al., 1989), or fluoranthene (Swartz
et al., 1990; DeWitt et al., 1992), and midge in sediments spiked with dieldrin (Hoke et al., 1995) relative to
predicted sediment toxic units.
4-4
-------
Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
chemical versus interstitial water TUs (IWTUs) for all
sediments tested with the following caveat for
dieldrin. Only the C. tentans Airport Pond data are
used for dieldrin, in part due to difficulties with die H.
azteca mortality results, as previously discussed
(Figure 4-1). Because DOC plays a significant role in
me partitioning of dieldrin. the free interstitial water
concentration is calculated using Equation 2-6 with the
DOC values reported by Hoke and Ankley (1992) and
the nominal interstitial water concentrations for
Airport Pond sediments. The log^p^ of 4.43 is
taken from Kosian et al. (1995). This same approach
was used for Pequaywan and West Bearskin Lakes
data, with the poor results most likely due to the
effects of DOC complexation (Hoke et al., 1995).
Because only nominal interstitial water values are
available, the dieldnn data shown in Figure 4-1 are
presented to demonstrate the concept that interstitial
water concentrations can be used to predict the
response of an organism to a chemical that is not
sediment specific.
IWTUs are the concentration of the chemical in
interstitial water (^g/L) divided by die water-only
LC50 Gug/L). Theoretically. 50% mortality should
occur at one IWTU At concentrations below one
IWTU there should be less than 50% mortality, and at
concentrations above one IWTU there should be
greater than 50% mortality. Figure 4-1 shows that, at
concentrations below one IWTU, mortality was
generally low and increased sharply at approximately
one IWTU. Therefore, diis comparison supports die
concept diat interstitial water concentrations can be
used to make a prediction, that is not sediment
specific, of the response of an organism to a chemical.
This interstitial water normalization was not used to
derive the ESG in this document because of die
complexation of nonionic organic chemicals with
interstitial water DOC (Section. 2) and the difficulties
of adequately sampling interstitial waters.
Table 4-2. Water-only and sediment LC50 values used to test the applicability of the EqP theory for dieldrin
Common
Name.
Scientific
Name
Amphipod,
Hyalella
azteca
Amphipod.
Hyalella
azteca
Amphipod.
Hyalella
azteca
Midge.
Chironomus
tentans
Midge.
Chironomus
tentans
Method.3
Duration
(days)
FT.M/10
FT.M/10
FT.M/10
FT.M/10
FTM/10
Water-
only
LC50
(Mg/L)
7.3
7.3
7.3
1 1
1.1
Interstitial
Water
LC50 TOC
(Mg/L) (%)
54.3 1.7°
236.1 29C
4916 8.7°
0.50* 20C
0.1 8f 15C
Dieldrin
Sediment
LCSOs
Dry
Wt.
(^g/g)
22.8
434
441 8
1.5
0.5
OC
(Mg/g)
1.332d
1.332d
4.272d
95.3d
35 l"
Predicted
LC50
O^g/goc)
1.391e
1.391e
1.391e
210e
210e
Ratio:
Actual/
Predicted
LC50
0.95
0.95
3.1
0.45
017
Reference
Hokeetal.
1995
Hoke et al..
1995
Hokeetal.
1995
Hokeetal .
1995
Hoke et al..
1995
"FT = flow-through. M = measured
bPredicted LC50 (Mg/goc> = water-only LC50 Ug/L) x Kx (L/kg^-) x 1 kg^lOOO g^-. where KOC = 1032'
cMean reported TOC concentration
Calculated using individually measured TOC concentrations
'Calculated using mean measured TOC concentrations
Interstitial water concentrations estimated from f. Kg,-, and measured sediment concentrations
4-5
-------
Actual and Predicted Toxicity of Dieldrin in Sediment Exposures
4.3 Tests of the Equilibrium
Partitioning Prediction of Sediment
Toxicity
Sediment guidelines derived using the EqP
approach utilize partition coefficients and FCVs from
updated or final WQC documents to derive the ESG
concentration that is protective of benthic organisms.
The partition coefficient AT^ is used to normalize
sediment concentrations and predict biologically
available concentrations across sediment types. The -
data required to test the organic carbon normalization
for dieldrm in sediments were available for two
benthic species Data from tests with water column
species were not included in this analysis. Testing of
this component of the ESG derivation required three
elements: (1) a water-only effect concentration, such
as a 10-day LC50 value, -in Mg/L, (2) an identical
sediment effect concentration on an organic carbon
basis in ^g/g^; and (3) a partition coefficient for the
chemical, KQC, in L/kgQj,. This section presents
evidence that the observed effects concentration in
sediments (2) can be predicted utilizing the water-only
effect concentration (1) and the partition coefficient (3).
Predicted sediment 10-day LC50 values from
dieldnn-spiked sediment tests with H. azteca (Hoke et
al., 1995) were calculated (Table 4-2) using the log,0
KQC value of 5.28 from Section 2 of this document
and the water-only LC50 value (7.3 Mg/L). Ratios of
actual to predicted sediment LC50 values for dieldrin
averaged 1 4 (range 0 95 to 3 1) in tests with three
sediments. Similarly, predicted sediment 10-day
LC50 values for dieldrin-spiked sediment tests with C.
tentans (Hoke et al , 1995) were calculated using the
log10AToc of 5 28 and a 10-day water-only LC50 value
of 1 1 /ug/L (Table 4-2). Ratios of predicted to actual
sediment LC50 values for dieldrin averaged 0.28
(range 0.17 to 0.45) in tests with two sediments. The
overall geometric mean ratio for both species was 0.73.
A more detailed evaluation of the accuracy and
precision of the EqP prediction of the response of
benthic organisms can be made using the results of
toxicity tests with amphipods exposed to sediments
spiked with acenaphthene. phenanthrene, dieldrin,
endnn, or fluoranthene The data included in this
analysis were from tests conducted at EPA
laboratories or from tests that utilized designs at least
as rigorous as those conducted at EPA laboratories
Data from the kepone experiments were not included
because the recommended Kov/ for kepone obtained
from Karickhoff and Long (1995) was evaluated using
only one laboratory measured value, whereas the
remaining chemical Kow values are recommended
based on several laboratory measured values. Swartz
(1991) exposed the saltwater amphipods E. estuarius
and L. plumulosus to acenaphthene in three marine
sediments having organic carbon contents ranging
from 0.82% to 4 2% and to phenanthrene in three
marine sediments having organic carbon contents
ranging from 0.82% to 3.6%. Swartz et al. (1990)
exposed the saltwater amphipod R. abronius to
fluoranthene in three marine sediments having 0 18%,
0.31 %. and 0.48% organic carbon. Hoke et al.
(1995) exposed the amphipod H. azteca to three
dieldnn-spiked freshwater sediments having 1.7%,
2.9%, and 8.7% organic carbon, and also exposed the
midge C. tentans to two freshwater dieldrin-spiked
sediments having 2.0% and 1.5% organic carbon.
Nebeker et al. (1989) and Schuytema et al {1989)
exposed H. azteca to three endhn-spiked sediments
having 3.0%, 6.1%, and 11.2% organic carbon.
Figure 4-2 presents the percent mortalities of
amphipods in individual treatments of each chemical
versus predicted sediment TUs (PSTUs) for each
sediment treatment. PSTUs are the concentration of
the chemical in sediments C-tg/goc) divided by the
predicted sediment LC50 (i e.. the product of Kx and
the 10-day water-only LC50, expressed in ^g/goc)-
In this normalization, 50% mortality should occur at
one PSTU. Figure 4-2 shows that at concentrations
below one PSTU mortality was generally low and
increased sharply at one PSTU. Therefore, this
comparison supports the concept that PSTUs also can
be used to make a prediction, that is not sediment
specific, of the response of an organism to a chemical.
The means of the LC50 values for these tests
calculated on a PSTU basis were 1.55 for
acenaphthene, 0 73 for dieldrin, 0.33 for endrin, 0.75
for fluoranthene. and 1 19 for phenanthrene. The
mean value for the five chemicals was 0.80. The fact
that this value is so close to the theoretical value of
1.0 illustrates that the EqP method can account for the
effects of different sediment properties and properly
predict the effects concentration in sediments using the
effects concentration from water-only exposures.
Data variations in Figure 4-2 reflect inherent
variability in these experiments and phenomena that
have not been accounted for in the EqP model. The
uncertainty of the model is calculated in Section 5 2
of this document. There is an uncertainty of
approximately ±2. The error bars shown in Figure
4-2 are computed as ±1.96 x (ESG uncertainty).
The value of 1.96 is the t statistic, which provides a
95% confidence interval around the ESG.
4-6
-------
Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
Section 5
Guidelines Derivation for Dieldrin
5.1 Guidelines Derivation
The WQC FCV (see Section 3). without an
averaging period or return frequency, is used to
calculate the ESG because the concentration of
contaminants in sediments is probably relatively stable
over time. Thus, exposure to sedentary benthic species
should be chronic and relatively constant. This
contrasts with the situation in the water column, where
a rapid change in exposure and exposures of limited
durations can occur from fluctuations in effluent
concentrations, from dilutions in receiving waters, or
from the free-swimming or planktonic nature of water
column organisms For some particular uses of the
ESG, it may be appropriate to use the areal extent and
vertical stratification of contamination at a sediment
site in much the same way that averaging penods or
mixing zones are used with WQC
The FCV is the value that should protect 95% of
the tested species included in the calculation of the
WQC from chronic effects of the substance. The FCV
is the quotient of the FAV and the FACR for the
substance. The FAV is an estimate of the acute LC50 or
EC50 concentration of the substance corresponding to
a cumulative probability of 0.05 for the genera from
eight or more families for which acceptable acute tests
have been conducted on the substance. The EC50
represents the chemical concentration estimated to
cause effects to 50% of the test organisms within a
specified time period. The ACR is the mean ratio of
acute to chronic toxicity for three or more species
exposed to the substance that meets minimum database
requirements. For more information on the calculation
of ACRs, FAVs, and FCVs, see Section 3 of this
document and the WQC Guidelines (Stephan et al.,
1985). The FCV used in this document differs from the
FCV in the dieldnn WQC document (U.S. EPA. 1980a)
because it incorporates recent data not included in that
document and omits some data that do not meet the
data requirements of the WQC Guidelines (Stephan et
al.. 1985).
The EqP method for calculating ESGs is based on
the following procedure (also described in Section 2.1).
If the FCV (/ig/L) is the chronic concentration from the
WQC for the chemical of interest, then the ESG (^g/g
sediment) is computed using the partition coefficient,
Kp (L/g sediment), between sediment and interstitial
water
ESG=A:PFCV
(5-D
The organic carbon partition coefficient, KQ,,, can be
substituted for Kp, because organic carbon is the
predominant sorption phase for nonionic organic
chemicals in naturally occurring sediments (salinity.
grain size, and other sediment parameters have
inconsequential roles in sorption; see Sections 2.1 and
4.3). Therefore, on a sediment organic carbon basis,
the organic carbon-normalized ESG (ESQ^., in Mg
is
ESGoc=*ocFCV
(5-2)
Because K^ is presumably independent of sediment
type for nonionic organic chemicals, so too is ESGo,,.
Table 5-1 contains the calculation of the dieldnn ESG.
Table 5-1. Equilibrium partitioning sediment guidelines (ESGs) for dieldrin
FCV
Type of Water Body
-------
Guidelines Derivation for Dieldrin
is applicable to sediments with/^
sO.2%. For sediments with/^ <0.2%. organic carbon
normalization and ESGs do not apply
Because organic carbon is the factor controlling
the bioavailabihty of nomonic organic compounds in
sediments. ESGs have been developed on an organic
carbon basis, not on a dry weight basis. When the
chemical concentrations in sediments are reported as
dry weight concentrations and organic carbon data are
available, it is best to convert the sediment concen-
trations to Mg chemical/goc. These concentrations can
then be directly compared with the ESG value This
facilitates comparisons between the ESG and field
concentrations relative to identification of hot spots
and the degree to which sediment concentrations do or
do not exceed the ESG values. The conversion from
dry weight to organic carbon-normalized concentration
can be done using the following formula
Mg chemical/goc = Mg chemical/g^ wt - (% TOC r- 100)
= Mg chemical/g^ wt x 100 - % TOC
For example, a freshwater sediment with a
concentration of 0 1 //g dieldrin/g^ w and 05% TOC
has an organic carbon-normalized concentration of 20
^g/goc (= ° l ^g/Sd wt x 10° + °-5)- which exceeds the
freshwater dieldnn ESG of 12 /ig/goc- Another
freshwater sediment with the same concentration of
dieldnn (0 1 Mg/g,^ wt) but a TOC concentration of
5.0% would have anorganic carbon-normalized
concentration of 2.0 Mg/goc (= 0. 1 Mg/g^ OT x 100 -r
5.0), which is below the freshwater ESG for dieldnn.
In situations where TOC values for particular
sediments are not available, a range of TOC values may
be used in a "worst case" or "best case" analysis. In
this case, the ESQ^- may be "converted" to dry
weight-normalized ESG values (ESG^ vn). This
"conversion" for each level of TOC is
x (% TOC - 100)
For example, the ESG^ w value for freshwater
sediments with 1% organic carbon is 0.12 ug/g
1%TOC- 100=0
This method is used in the analysis of the STORET
data in Section 5 4.
5.2 Uncertainty Analysis
Some of the uncertainty of the dieldnn ESG can be
estimated from the degree to which the available
sediment toxicity data are explained using the EqP
model, which serves as the basis for the guidelines. In
its assertion, the EqP model holds that (1) the
bioavailabihty of nomonic organic chemicals from
sediments is equal on an organic carbon basis and (2)
the effects concentration in sediment (^g/g^) can be
estimated from the product of the effects concentration
from water-only exposures. FCV O^g/L). and the
partition coefficient, KQC (L/kg). The uncertainty
associated with the ESG can be obtained from a
quantitative estimate of the degree to which the
available data support these assertions.
The data used in the uncertainty analysis are from
the water-only and sediment toxicity tests that were
conducted to fulfill the minimum database requirements
for development of the ESG (see Section 4.3 and the
ESG Technical Basis Document). These freshwater and
saltwater tests span a range of chemicals and
organisms, they include both water-only and sediment
exposures, and they are replicated within each
chemical-orgamsm-exposure media treatment. These
data were analyzed using an analysis of variance
(ANOVA) to estimate the uncertainty (i.e., the vanance)
associated with varying the exposure media and that
associated with experimental error. If the EqP model
were perfect then there would be experimental error
only. Therefore, the uncertainty associated with the
use of EqP is the vanance associated with varying
exposure media.
The data used in the uncertainty analysis are
illustrated in Figure 4-2. The data for dieldnn are
summarized in Appendix B . Only data from Hoke et al.
( 1995). as listed in Appendix B. were used in the
uncertainty analysis because of mortality problems
with H. azteca from Airport Pond as discussed in
Sections 4 1 and 4 2. Data from Hoke and Ankley
(1992). which used only Airport Pond sediments, have
been used solely to compute partitioning LC50 values
for sediment and water-only tests were computed from
these data. The EqP model can be used to normalize
the data in order to put it on a common basis. The
LC50 values from water-only exposures (LC50W;
are related to the organic carbon-normalized LC50
values from sediment exposures (LC50
the partitioning equation
via
LC50SOC=A:OCLC50W
(5-3)
5-2
-------
Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
As mentioned above, one of the assertions of the EqP
model is that the toxicity of sediments expressed on an
organic carbon basis equals the toxicity in water-only
tests multiplied by the K^. Therefore, both LC50S ^
and KQC x LC50W are estimates of the true LCSO^ for
each chemical-organism pair. In this analysis, the
uncertainty of AT^. is not treated separately. Any error
associated with K^ will be reflected in the uncertainty
attributed to varying the exposure media.
In order to perform an analysis of variance, a model
of the random variations is required. As discussed
above, experiments that seek to validate Equation 5-3
are subject to various sources of random variations. A
number of chemicals and organisms have been tested.
Each chemical-orga'nism pair was tested in water-only
exposures and in different sediments. Let a represent
the random variation due to this source. Also, each
experiment was replicated. Let e represent the random
variation due to this source. If the model were perfect,
there would be no random variations other than those
from experimental error, which is reflected in the
replications. Hence, a represents the uncertainty due
to the approximations inherent in the model and
represents the experimental error Let (oa)2 and (o£)2 be
the variances of these random variables. Let i index a
specific chemical-organism pair. Let j index the
exposure media, water-only, or the individual
sediments. Let k index the replication of the experiment.
Then the equation that describes this relationship is
Ijk) = Ml
(5-4)
where ln(LC50ujJc) is either ln(LC50w)or ln(LC50s ^
corresponding to a water-only or sediment exposure.
and M, is the population of ln(LC50) for chemical-
organism pair i. The error structure is assumed to be
lognormal, which corresponds to assuming that the
errors are proportional to the means (eg.. 20%). rather
than absolute quantities (e.g . 1 Mg/goc). The statistical
problem is to estimate /^, (o0)2, and (oe)2. The maximum
likelihood method is used to make these estimates
(U.S. EPA. 2000a). The results are shown in Table 5 -2
The last line of Table 5-2 is the uncertainty associated
with the ESG; i.e.. the variance associated with the
exposure media variability.
The confidence limits for the ESG are corfiputed
using this estimate of uncertainty for the ESG. For the
95% confidence interval limits, the significance level is
1 .96 for normally distributed errors. Hence,
(5-5)
(54)
. is applicable to sediments with/Qj.
^0.2%. For sediments with/^ <0.2%, organic carbon
normalization and ESGs do not apply.
) + 1 960^
c) - 1.96^
The confidence limits are given in Table 5-3.
Table 5-2. Analysis of variance for derivation of confidence limits of the ESGs for dieldrin
Source of Uncertainty
Parameter
Value (Mg/goc)
Exposure media
Replication
ESG Sediment Guideline
OESG
041
0.29
0.41
Table 5-3. Confidence limits of the ESGs for dieldrin
ESGoc
95% Confidence Limits (Mg/g
-------
Guidelines Derivation for Dieldrin
5.3 Comparison of Dieldrin ESG and
Uncertainty Concentrations to
Sediment Concentrations that are
Toxic or Predicted to be Chronically
Acceptable
Insight into the magnitude of protection afforded
to benthic species by ESG concentrations and 95%
confidence intervals can be inferred using effect
concentrations from toxicity tests with benthic species
exposed to sediments spiked with dieldnn and sediment
concentrations predicted to be chronically safe to
organisms tested in water-only exposures (Figures 5-1
and 5-2). The effect concentrations in sediments are
predicted from water-only toxicity data and K^ values
(see Section 4) Chronically acceptable concentrations
are extrapolated from GMAVs from water-only, 96-hour
lethality tests using the FACR. These two predictive
1 vvUuv
^ 10000
-S~
-3
u 1000
's
2
.C
U
c
«
V
s
» 100
3
e
V
o
a
41
t*
^W
3
flj
£ »o
a.
: Water-only tests: PGMCV
" A Arthropods t
Other Invertebrates A
Fish and Amphibians
= Sediment 10-day LC50SOC A A
I * C. tentans = 57.8 Mg/goc
range 2 tests = 35.1 to 95.3 T *
* H. azteca = 1959 Mg/goc
range 3 tests = 1 322 to 4272 } '
: A
-
" « 0 A
o w
o
0 A 0
O
- *
r
i r
-
- - j upper, z / A-^/goc
"
P.Sfl- 1 7 /'g''goc
-
1 1 1 1 I 1 1 1 1
0 20 40 60 80 100
Percentage Rank of Freshwater Genera
Figure 5-1. Predicted genus mean chronic values calculated from water-only toxicity values (Equation 5-7;
Appendix A) using freshwater species versus percentage rank of their sensitivity. Lines indicate the
freshwater dieldrin ESG ±95% confidence limits. Solid symbols are benthic genera; open symbols are
water column genera. Sediment 10-day LC50S oc values (calculated from Hoke et al.. 1995; see Table 4-
1) for the amphipods C. tentans (ir) and H. azteca (*) are provided for comparison. Error bars around the
LC50 values indicate the observed range of LCSOs.
5-4
-------
Equilibrium Partitioning Sediment Guidelines (ESGs): Diddrin
values are used to estimate chronically acceptable
sediment concentrations (predicted genus mean
chronic value. PGMCV) for dieldrin from GM AVs
(Appendix A), the FACR (Table 3-2), and the K^
(Table 5-1)
PGMCV = (GMAV -r ACR) K.
oc
(5-7)
Each PGMCV for fishes and amphibians,
arthropods, or other invertebrates tested in water was
plotted against the percentage rank of its sensitivity.
Results from toxicity tests with benthic organisms
exposed to sediments spiked with dieldrin (Table 4-1,
Appendix B) are placed in the PGMCV rank appropriate
to the test-specific effect concentration. For example.
the mean 10-day LC50S ^ for C. tentans, 57 8 Mg/goc. is
placed between the PGMCV of 25.0 Mg/goc for the
stonefly, Claassema, and the PGMCV of 153 Mg/goc for
the fish, Micropterus. Therefore, the LC50 or other
effect concentrations are intermingled in this figure
with concentrations predicted to be chronically safe.
Care should be taken by the reader in interpreting these
data with dissimilar endpomts. The following
discussion of ESGs, organism sensitivities, and
PGMCVs is not intended to provide accurate
predictions of the responses of taxa or communities of
A VVUW
"| 10000
3
-------
Guidelines Derivation for Dieldrin
benthic organisms relative to specific concentrations of
dieldnn in sediments in the field. It is. however,
intended to guide scientists and managers through the
complexity of available data relative to potential risks to
benthic taxa posed by sediments contaminated with
dieldnn.
Figures 5-1 and 5-2 are recreations of Figures 3-1
and 3-2, respectively, with GMAVs taken from Appendix
A to calculate PGMCVs using Equation 5-7. The
freshwater ESG for dieldnn (12 Mg/goc)IS 'ess man anv -
of the PGMCVs or LC50 values from spiked sediment
toxicity tests (Figure 5-1). The PGMCVs for 18 of 21
freshwater genera are greater than the upper 95%
confidence interval of the ESG (27 Mg/goc)- The
PGMCVs for the stoneflies Pteronarcella
Pteronarcys (22 ^g/gf^), and Claassenia
are below the ESG upper 95% confidence interval. This
illustrates why the slope of the species sensitivity
distribution is important. It also suggests that, if the
extrapolation from water-only acute lethality tests to
chronically acceptable sediment concentrations is
accurate, these or similarly sensitive genera may be
chronically affected by sediment concentrations
marginally above the ESG and possibly less than the
95% upper confidence interval. For dieldnn. PGMCVs
range over three orders of magnitude from the most
sensitive to the most tolerant genus (Figure 5-1). A
sediment concentration 20 times the ESG would include
the PGMCVs of 4 of the 13 benthic genera tested
including stoneflies, isopods, and fish.
Tolerant benthic genera such as the amphipod
Gammarus and the crayfish Orconectes may not be
chronically affected in sediments with dieldnn
concentrations up to 1,000 times the ESG (Figure 5-1;
Appendix A). Data from lethality tests with freshwater
organisms exposed to dieldnn-spiked sediments
substantiates this projection; the 10-day LC50 values
from three tests with the amphipod H. azteca ranged
from 110 to 360 times the ESG of 12 Mg/goc-the 10'day
LCSOs from two tests with the midge C. tentans ranged
from 29 to 79 times the ESG (see insert Figure 5-1;
corresponding values from Table 4-1)
The saltwater ESG for dieldrin (28 Mg/goc)1S less
than all of the PGMCVs for saltwater genera (Figure
5-2). The PGMCVs for the penaeid shrimp Penaeus
duorarum (31 Mg/ggc) an<* the fish Anguilla rostrata
(39 ^g/goc) are lower than the upper 95% confidence
interval for the ESG (62 Mg/goc) For dieldnn, PGMCVs
from the most sensitive to the most tolerant saltwater
genus range over two orders of magnitude. A sediment
concentration 17 times the ESG would include the
PGMCVs of 7 of the 13 benthic genera tested including
4 arthropod and 3 fish genera. Other genera of benthic
arthropods, polychaetes. and fishes are less sensitive
and might not be expected to be chronically affected
in sediments with dieldnn concentrations 30 times
the ESG.
5.4 Comparison of Dieldrin ESG to
STORET, National Status and
Trends, and Corps of Engineers, San
Francisco Bay Databases for
Sediment Dieldrin
Dieldnn is frequently measured when samples are
taken to measure sediment contamination, and dieldnn
values are frequently reported in databases of sediment
contamination. This means that it is possible that many
of the sediments from the nation's waterways might
exceed the dieldnn guidelines. In order to investigate
this possibility, the dieldnn guidelines were compared
with data from several available databases of sediment
chemistry.
The following descnption of dieldnn distributions
in Figure 5-3 is somewhat misleading because it
includes data from samples in which the dieldnn
concentration was below the detection limit. These
data are indicated on the plot as "less than" symbols
(<). but are plotted at the reported detection limits.
Because these values represent artificial upper bounds.
not measured values, the percentage of samples in
which the ESG values were actually exceeded may be
less than the percentage reported. Very few of the
measured values from either of the databases exceeds .
theESGs.
A STORET (U.S. EPA, 1989b) data retrieval was
performed to obtain a preliminary assessment of the
concentrations of dieldnn in the sediments of the
nation's water bodies. Log probability plots of dieldrin
concentrations on a dry weight basis in sediments are
shown in Figure 5-3. Dieldnn was found at varying
concentrations in sediments from rivers, lakes, and
near-coastal water bodies in the United States. This
was because of its widespread use and quantity applied
dunng the 1960s and early 1970s It was restricted from
registration and production in the United States in
1974. Median concentrations were generally at or near
detection limits in most water bodies for data after 1986
There was significant variability with dieldnn
concentrations in sediments ranging over nine orders
of magnitude within the country
5-6
-------
Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
2
u
^
3
B
Ol
'
V
to
s
'C
2
"o5
J
**
1/3
.E
2
jS
101
10'
0
10"
10'
10°
10'
10'
10'
Total Samples: 3075
Measured Samples: 590
10'
10' b- B: Lake
^*<'
<, «,|
Total Samples: 457
Measured Samples: 124
1 lui i i i i i lii 1 1.. ,
C: Estuary
< <
< .
<<
-------
Guidelines Derivation for Oieldrin
The ESG for dieldnn can be compared to existing
concentrations of dieldrin in sediments of natural water
systems in the United States as contained in the
STORET database (U.S. EPA. 1989b) These data are
generally reported on a dry weight basis rather than an
organic carbon-normalized basis. Therefore. ESG
values corresponding to sediment organic carbon
levels of 1% to 10% were compared with dieldnn's
distribution in sediments as examples only For
freshwater sediments. ESG values were 0 12 jug/g dry
weight in sediments having 1% organic carbon and 1 2 '
Mg/g dry weight in sediments having 10% organic
carbon; for marine sediments, ESGs were 028 ^g/g dry
weight and 2.8 /^g/g dry weight, respectively. Figure
5-3 presents comparisons of these ESGs with
probability distributions of observed sediment dieldrin
levels for streams and lakes (freshwater systems,
shown on A and B) and estuaries (marine systems, C).
For both streams (n=3,075) and lakes (n=457). the
ESGs of 0 12 Mg/g dry weight for 1% organic carbon
freshwater sediments and of 1.2 Mg/g dry weight for
10% organic carbon freshwater sediments were
exceeded in less than 1% of the samples. In estuaries.
the data (n= 160) indicate that neither guideline. 028
Mg/g dry weight for sediments having 1% organic
carbon nor 28 /zg/g dry weight for sediments having
10% organic carbon, was exceeded by the post 1986
samples Concentrations of dieldnn in sediments from
estuaries were two orders of magnitude below the ESG
value for 1% organic carbon sediments and three orders
of magnitude below the ESG value for sediments with
TOCsoflO%.
A second database developed as part of the
National Status and Trends Program (NO A A, 1991) was
available for assessing contaminant levels in marine
sediments that were reprcsentative-of areas away from
sources of contamination. The probability distribution
for these data, on an organic carbon basis, was
compared with the saltwater ESG for dieldrin (28
) in Figure 5-4. Data presented were from
100
10
'
~
2
~v
5
0.1
0.01
0.001
0.0001
= ' ' """I ' ' ' I I
ESGn
T p
*oc
O -
,ox>o
>0.2%
j i
1 I I I I I I I Illti I I I I
0.1
10 20 50 80 90
Probability
99
99.9
Figure 5-4. Probability distribution of concentrations of dieldrin in sediments from coastal and estuarine sites
from 1984 to 1989 as measured by the National Status and Trends Program (NOAA, 1991). The
horizontal dashed line is the saltwater ESG value of 28
5-8
-------
Equilibrium Partitioning^Sediment Guidelines (ESGs): Dieldrin
sediments with 0 20% to 31.9% organic carbon.
The median organic carbon-normalized dieldrin
concentration (O.OSO/zg/ggc) was two orders of
magnitude below the ESG of 28 Mg/goc None of these
samples (n=408) exceeded the guidelines. Hence, these
results are consistent with the preceding comparison
between the marine ESG and STORE! data.
A third set of data has been analyzed, from the U.S.
Army Corps of Engineers (1991) monitoring program for
a number of locations in various parts of San Francisco -
Bay. For a listing of locations sampled, the number of
observations at each site, and the penod during which
the results were obtained, see U.S. EPA (2000a). These
data were collected to examine the quality of dredged
sediments in order to determine their suitability for
open water disposal. The database did not indicate
what determinations were made concerning their
acceptability for this purpose.
Investigators compared the frequency of
occurrence of a given sediment dieldrin concentration
(in individual samples, not dredge sites) with the ESG
developed using the EqP methodology. A major
portion (93%) of the samples analyzed had/^, >0.2%,
for which the ESG concentrations are applicable. The
concentrations of dieldrin in sediments were normalized
by the organic carbon content, and the results are
displayed as a probability plot in Figure 5-5 to illustrate
the frequency at which different levels are observed.
Nearly all of the samples were less than the varying
detection limits of the analytical tests. Each of the
samples for which actual measurements were obtained
were at least an order of magnitude lower than the ESG
An estimate of the possible frequency distribution of
sediment concentrations of dieldnn was developed by
the application of an analysis technique that accounts
for the varying detection limits and the presence of
nondetected observations (El-Shaarawi and Dolan,
1989). The results are illustrated by the straight line.
which suggests that no appreciable number of
exceedences is expected. However, the virtual absence
of detected concentrations makes the distribution
estimates unreliable. They are presented onlylo
suggest the probable relationship between the levels of
the pesticide in relation to the sediment guidelines.
Regional-specific differences in dieldnn
concentrations may affect the above conclusions
concerning expected guidelines exceedences. This
analysis also does not consider other factors such as
the type of samples collected (i.e.. whether samples
were from surficial grab samples or vertical core
profiles) or the relative frequencies and intensities of
10'
1
M
3
i*
u
,1 I
J li
0.1
10 20
50
Probability
80 90
99
99.9
Figure 5-5. Probability distribution of organic carboo-normaiized sediment dieldrin concentrations from the U.S.
Army Corps of Engineers (1991) monitoring program of San Francisco Bay. Sediment dieldrin
concentrations less than the detection limits are shown as open triangles (V); measured concentrations
are shown as solid circles (). The solid line is an estimate of the distribution developed by accounting
for nondetected observations.
5-9
-------
Guidelines Derivation for Dieldrin
sampling in different study areas. It is presented as an
aid in assessing the range of reported dieldnn sediment
concentrations and the extent to which they may
exceed the ESG
5.5 Limitations to the Applicability of
ESGs
Rarely, if ever, are contaminants found alone in
naturally occurring sediments Obviously, the fact that
the concentration of a particular contaminant does not
exceed the ESG does not mean that other chemicals, for
which there are no ESGs available, are not present in
concentrations sufficient to cause harmful effects.
Furthermore, even if ESGs were available for all of the
contaminants in a particular sediment, there might be
additive or synergistic effects that the guidelines do
not address. In this sense, the ESG represents a "best
case" guideline.
It is theoretically possible that antagonistic
reactions between chemicals could reduce the toxicity
of a given chemical such that it might not cause
unacceptable effects on benthic organisms at
concentrations above the ESG when it occurs with the
antagonistic chemical. However, antagonism has rarely
been demonstrated. More common would be instances
where toxic effects occur at concentrations below the
ESG because of the additive toxicity of many common
contaminants such as heavy metals and polycyclic
aromatic hydrocarbons (PAHs) (Alabaster and Lloyd.
1982). and instances where other toxic compounds for
which no ESGs exist occur along with ESG chemicals.
Care must be used in applying EqP-denved
guidelines in disequilibrium conditions. In some
instances, site-specific ESGs may be required to
address disequilibrium. The ESGs assume that
noniomc organic chemicals are in equilibrium with the
sediment and interstitial water and are associated with
sediment primarily through adsorption to sediment
organic carbon. In order for these assumptions to be
valid, the chemical must be dissolved in interstitial
water and partitioned into sediment organic carbon.
Therefore, the chemical must be associated with the
sediment for a sufficient length of time for equilibrium
to be reached In sediments where particles of
undissolved dieldnn occur, disequilibrium exists and
the guidelines are overprotective. In liquid chemical
spill situations, disequilibrium concentrations in
interstitial and overlying water may be proportionately
higher relative to sediment concentrations. In this case
the guidelines may be underprotective.
Note that the Kx values used in the EqP
calculations described in this document assume that
the organic carbon in sediments is similar in
partitioning properties to "natural" organic carbon
found in most sediments While this has proven true
for most sediments EPA has studied, it is possible that
some sites may have components of sediment organic
carbon with different properties. This might be
associated with sediments whose composition has
been highly modified by industrial activity, resulting in
high percentages of atypical organic carbon such as
rubber, animal processing waste (e.g.. hair or hide
fragments), coal particles, or wood processing wastes
(bark, wood fiber, or chips). Relatively undegraded
woody debns or plant matter (e.g.. roots, leaves) may
also contribute organic carbon that partitions
differently from typical organic carbon (e.g., Fglesias-
Jimenezetal.. 1997; Grathwohl, 1990; Xing etal.. 1994).
Sediments with substantial amounts of these materials
may exhibit higher concentrations of chemicals in
interstitial water than would be predicted using generic
Kx values, thereby making the ESG underprotective. If
such a situation is encountered, the applicability of
literature KQC values can be evaluated by analyzing for
the chemical of interest in both sediment and interstitial
water. If the measured concentration in interstitial
water is markedly greater (e.g., more than twofold) than
that predicted using the Kx values recommended
herein (after accounting for DOC binding in the
interstitial water), then the national ESGs would be
underprotective and calculation of a site-specific ESG
should be considered (see U.S. EPA, 2000b).
The presence of organic carbon in large particles
may also influence the apparent partitioning. Large
particles may artificially inflate the effect of the organic
carbon because of their large mass, but comparatively
small surface area; they may also increase variability in
TOC measurements by causing sample heterogeneity
The effect of these particles on partitioning can be
evaluated by analysis of interstitial water as described
above, and site-specific ESGs may be used if required.
It may be possible to screen large particles from
sediment prior to analysis to reduce their influence on
the interpretation of sediment chemistry relative to
ESGs.
In very dynamic areas, with highly erosional or
depositional bedded sediments, equilibrium may not be
attained with contaminants. However, even high Kow
noniomc organic compounds come to equilibrium in
clean sediment in a period of days, weeks, or months.
Equilibrium times are shorter for mixtures of two
5-10
-------
Guideline (ESGs): Diddrin
sediments that each have previously been at the rule and disequilibrium is less common. In
equilibrium. This is particularly relevant in tidal instances where it is suspected that EqP does not
situations where large volumes of sediments are eroded apply for a particular sediment because of
and deposited, even though near equilibrium disequilibrium discussed above, site-specific
conditions may predominate over large areas. Except methodologies may be applied (U.S. EPA, 2000b).
for spills and paniculate chemical, near equilibrium is
5-11
-------
Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
Section 6
Guidelines Statement
The procedures described in the ESG Technical
Basis Document indicate that benthic organisms should
be acceptably protected from acute and chronic effects
of dieldnn in freshwater sediments containing <. 12 /zg -
dieldrin/goj. and saltwater sediments containing s28 /zg
dieldnn/g^, except possibly where a locally important
species is very sensitive or sediment organic carbon is
Confidence limits of 5.4 to 27 Mg/goc for freshwater
sediments and 12 to 62 Mg/g^ for saltwater sediments
are provided as an estimate of the uncertainty
associated with the degree to which the observed
concentration in sediment (Mg/goc). which may be toxic,
can be predicted using the Kx and the water- only
effects concentration. Confidence limits do not
incorporate uncertainty associated with water quality
criteria. An understanding of the theoretical basis of
the equilibrium partitioning methodology, uncertainty,
and the partitioning and toxicity of dieldrin are required
in the regulatory use of ESGs and their confidence
limits.
The guidelines presented in this document are
EPA's best recommendation of the concentrations of
dieldnn that may be present in sediment while still
protecting benthic organisms from the effects of
dieldrin. These guidelines are applicable to a variety of
freshwater and marine sediments because they are
based on the biologically available concentration of the
substance in those sediments. These guidelines do not
protect against additive, synergistic, or antagonistic
effects of dieldnn or against the bioaccumulative
effects of dieldnn to aquatic life, wildlife, or human
health. The Agency and the EPA Science Advisory
Board do not recommend the use of ESGs as stand-
alone, pass-fail criteria for all applications; rather,
exceedances of ESGs could trigger additional studies at
sites under investigation. The ESG should be
interpreted as a chemical concentration below which
adverse effects are not expected. In comparison, at
concentrations above the ESG effects are likely, and
above the upper confidence limit effects are expected if
the chemical is bioavailable as predicted by EqP theory
A sediment-specific site assessment would provide
further information on chemical bioavailability and the
expectation of toxicity relative to the ESG and
associated uncertainty limits.
6-1
-------
Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
Section 7
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Chadwick GG, Kiigemagi U 1968. Toxicity evaluation of
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DeWitt TH. Ozreuch RJ. S wartz RC. Lamberson JO.
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Hoke RA. Ankley GT, 1992 Results of Airport Pond
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Kanckhoff SW. Carreira LA. Melton C, McDamel VK.
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Kanckhoff SW, Long JM. 1995. Internal report on
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Kom S, Earnest RD. 1974. Acute toxicity of twenty
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7-2
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Equilibrium Partitioning Sediment Guidelines (ESGs): Diddrin
Kosian PA. Hoke RA. Ankley GT. Vandermeiden FM
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organic material in sediment interstitial water using a
reverse-phase separation technique Environ Toxicol
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Mabey WR. Smith JH, Podoll RT. Johnson HL. Mill T.
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D. 1982. Aquatic fate process data for organic priority
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Equilibrium Partitioning Sediment Guidelines (ESGs): Dieldrin
US. Environmental Protection Agency. 2000g. Xing B. McGill WB. Dudas MJ. 1994. Cross-correlation
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State University, Fort Collins. CO.
7-5
-------
Appendix A
Summary of Acute Values for Dieldrin
for Freshwater and Saltwater Species
-------
Equilibrium-Partitioning Sediment Guidelines (ESGs): Endrin
Common Name. Life-
Scientfic Name stag? Habitat"
Freshwater Species
Oligochaete A I
worm.
Lumbriculus
variegatia
Obgochaete A I
worm.
Lumbriculus
variegatia
Cladoceran. X W.E
Simocephalus
serrulatus
Cladoceran, X W.E
Simocephalus
serrulatus
Cladoceran. L W
Daphnia
magna
Cladoceran. L W
Daphnia
magna
Cladoceran. L W
Daphnia
magna
Cladoceran. L W
Daphnia
magna
Cladoceran. L W
Daphnia
magna
Cladoceran. L W
Daphnia
pulex
Ostracod. A I.E
Cypndopsu
sp-
Sowbug, A E
Asellus
brevicaudus
irSO/ECSO- (ng/L)
HMAV
Method' Concentraiorf Test Species' Genus* GMAV Reference
FT M >165 1 POinerand
Cox. 1991
FT M' >1650 >1650 >165.0 >165 0 Brooke.
1993b
S U 26 Sanders
. and Cope.
1966.
Mayer and
Ellersieck.
1986
S U 45 34.20 3420 3420 Sanders
and Cope,
1966:
Mayer and
Ellersieck.
1986
S U 42 Mayer and
Ellersieck.
1986
S U 74 Mayer and
Ellersieck.
1986
S U 41 Mayer and
Ellersieck.
1986
FT M 230 Thurstonet
al., 1985
FT M 88 1423 Thurstonet
al.. 1985
S U 20 20 53.35 5335 Mayer and
Ellersieck.
1986
S U 18 1.8 1.8 18 Mayerard
Ellersieck.
1986
S U 15 1.5 1.5 1-5 Sanders,
1972.
Mayer and
Ellersieck,
1986
A-l
-------
Appendix A
Common Name,
Scientific Name
Scud.
Gammarus
fasciaius
Scud.
Gammarus
fasciatus
Scud.
Gammarus
fasciatus
Scud,
Gammarus
lacustns
Glass shrimp.
Palaemoneies
kadiakensis
Glass shnmp.
Palaemonetes
kadiakensis
Crayfish,
Orconectes
immunis
Crayfish,
Orconectes
nais
Crayfish,
Orconectes
nais
Mayfly,
Baetis sp
Mayfly.
Hexagenta
bilineata
LCSO/ECSO-Cug/L)
, e, HMAV _
stage" Habitat* Method1 Conceniraiort" Test Speaes' Genus" GMAV* Reference
A E ' S U 43 Sanders,
1972:
Mayer and
Ellersieck.
1986
X E S U 1.3 Sanders,
1972,
Mayer and
Ellersieck.
1986
X E FT U 5.5 3.133 Sanders,
1972
A E S .U 3.0 30 3066 3066 Sanders,
1972<
Mayer and
Ellersieck.
1986
A E S U 3.2 Sanders,
1972.
Mayer and
Ellersieck,
1986
X E FT U 05 1.265 1265 1.265 Sanders,
1972,
Mayer and
Ellersieck.
1986
J E FT M >89 >89 -- Thurstonet
al., 1985
XES U 320 Sanders,
1972.
Mayer and
Ellersieck.
1986
J E S U 3.2 3.2 32 71688 Sanders,
1972.
Mayer and
Ellersieck.
1986
j I s U 090 090 090 090 Mayer and
Ellersieck.
1986
X I S U 64 Sanders,
1972
A-2
-------
Equilibrium-Partitioning Sediment Guidelines (ESGs): Endrin
Common Name. Life-
Scientific time stage" Habitat" Method1 Concentraiott1
Stonefly. L W.E S U
Acraneuria sp
Stonefly. L I.E S U
Pteronarcella
badia
Stonefly. A I.E S U
Pleronarcys
californica
Stonefly. J W.E S U
Claaaenia
sabulosa
Stoneny. J W.E S U
Claassenia
sabulosa
Caddis fly. X E FT M
Brachycentrus
americanus
Damesfly, X W.E S U
Ischnuna
verticalus
Damesfly. J W.E S U
Ischnum
verticalus
Damesfly, J W.E S U
Ischnura
verticalus
Midge, L I FT M
Tanytarsus
dissmdis
Dptera. J I.E S U
Tipula sp.
Dptera, J I.E S U
Atherix
variegata
Cohosalmoa J W S U
Oncorhynchus
kisutch
LCSO/ECSOMng/L)
HMAV ^
Test Species' Genus" GMAV
>018 >018 >018 >0 18
054 054 054 0.54
025 0.25 0.25 025
- -
"
076
076 0.2403 0.2403 0.2403
0.34 034 0.34 034
1.8
2.1
24 1086 2086 2.086
083 083 083 0.83
12 12 12 12
46 46 46 4.6
051
Reference
Mayer and
Ellersieck.
1986
Sanders
and Cope.
1968;
Mayer and
Ellersieck.
1986
Sanders
and Cope,
t968.
Mayer and
Ellersieck.
1986
Sanders
and Cope,
1968
Mayer and
Ellersieck.
1986
Anderson
and DeFoe.
1980
Sanders,
1972
Mayer and
Ellersieck.
1986
Mayer and
Ellersieck.
1986
Thurston et
al.. 1985
Mayer and
Ellersieck.
1986
Mayer and
Ellersieck,
IQSA
1 TOO
Katz. 1961
A-3
-------
Appendix A
LC50/EC50* (ug/L)
Scientfic Home stag? Habitat" Method" Conceraraiorr1 Test Speaes' Genus" GMAV"
Coho salmon, J W S U 0089
Oncorhynchus
kisutch
Goto salmon, J W S U 027 02306
Oncorhynchus
kisutch
Cutthroat J W S U >1.0 >1.0
trout,
Oncorhynchus
clarki
Rainbow trout. J W S U 0.74 _ _
Oncorhynchus
my kiss
Rainbow trout. J W S U 075
Oncorhynchus
my kiss
Rainbow trout, J W S U 075
Oncorhynchus
my kiss
Rainbow trout. J W S U 2.4
Oncorhynchus
my kiss
Rainbow trout. J W S U 1.4 _ _ _
Oncorhynchus
mykiss
Rainbow trout. J W S U 1.11
Oncorhynchus
my kiss
Rainbow trout. J W S U 1.1
Oncorhynchus
my kiss
Rainbow trout. J W S U 0.58
Oncorhynchus
my kiss
Rainbow trout. J W S U 0.90
Oncorhynchus
my kiss
Rainbow trout. J W FT M 0.33 033
Oncorhynchus
my kiss
Chinook J W S U 1.2
salmon.
Oncorhvnchus
tshawvtscha
Reference
Mayer and
Ellersieck.
1986
Katzand
Chad wick,
1961
Mayer and
Ellersieck.
1986
. . Mayer and
Ellersieck,
1986
Mayer and
Ellersieck,
1986
Mayer and.
Ellersieck,
1986
Mayer and
Ellersieck.
1986
Mayer and
Ellersieck.
1986
Mayer and
Ellersieck.
1986
Macek et
al. 1969
Katz. 1961
Katzand
Chad wick,
1961
Thurston et
al.. 1985
Katz. 1961
A-4
-------
Equilibrium-Partitioning Sediment Guidelines (ESGs): Endrin
Common Name,
Scientific Name
Chinook
salmon.
Oncorhynchus
tshawytscha
Goldfish,
Carassius
auratus
Goldfish.
Carassius
auratus
Goldfish.
Carassius
auratus
Carp,
Cyprinus
carpio
Fathead
minnow,
Pimephales
promelas
Fathead
minnow,
Pimephales
promelas
Fathead
minnow.
Pimephales
promelas
Fathead
minnow,
Pimephales
promelas
Fathead
minnow.
Pimephales
promelas
Fathead
minnow,
Pimephales
promelas
Fathead
minnow,
Pimephales
promelas
Fathead
minnow,
Pimephales
promelas
LC50/EC50-(Mg/L)
i c, HMAV _
stage- Habitat" Method0 Concentration11 Test Species' Genus" GMAV* Reference
J W S U 092 1051 >0.5318 >05318 Katz and
Chad wick,
1961
J W S U 2 1 Henderson
etal. 1959
JWFT U 044 Mayer and
Ellersieck,
1986
J W FT M 095 095 095 0.95 Thurston et
al., 1985
J W FT U 032 032 032 0.32 Mayer an!
Ellersieck,
1986
J W S. U 1.1 Henderson
etal., 1959
J W S U 1.4 Henderson
etal., 1959
L W S U 07 Jarvinen et
al., 1988
J W S U 1.8 Mayer and
Ellersieck.
1986
j W FT U 024 Mayer and
Ellersieck.
1986
J W FT M 050 Brungsand
Bailey,
1966
U FT M 0.49 Brungsand
Bailey.
1966
j w FT M 040 Brungsand
Bailey.
1966
A-5
-------
Appendix A
Common Name,
Scientific Name
Fathead
minnow.
Punephales
promelas
Fathead
minnow.
Punephales
promelas
Black
bullhead,
laalurus
melas
Black
bullhead.
laalurus
melas
Channel
catfish.
Ictalurus
punctatus
Channel
catfish.
Ictalurus
punctatus
Channel
catfish.
Ictalurus
punctatus
Channel
catfish.
Ictalurus
punctatus
Channel
catfish.
Ictalurus
punctatus
Flagfish,
Jordanella
floridae
Mosquitofish,
Cambusia
affinis
Mosquitofish.
Cambusia
affinis
LC50/EC50-(lig/U
, , HMAV
stag? Habitat6 Method* Concentraiorr1 Test Speaes' Genus1 GMAV* Reference
J W FT M 045 Bnmgsand
Bailey.
1966
J W FT M 064 0.4899 04899 0.4899 Thuiston et
al.. 1985
J W.E S U 1.13 Mayerand
Ellersieck,
1986
.
J W.E FT M -0.45 0.45 Anderson
andDeFbe.
1980
J W.E S U 0.32 Mayerand
EUerswck.
1986
J W.E S U 1.9 Mayerand
Ellersieck.
1986
J W.E S U 0.8 McCorkle
etaL. 1977
J W.E FT M 0.43 Thuiston et
at. 1985
J W.E FT M 041 0.4199 04347 0.4347 Thuiston et
al., 1985
J W FT M 0.85 0.85 0.85 085 Hermanutz,
1978;
Hermanutz
etal., 1985
J W S U 1.1 Mayerand
Ellersieck.
1986
X W S U 0.75 Katzand
Chadwick.
1961
A-6
-------
Eqnflibriom-Partitksning Sed&nent Guidelines (ESGs): Endrin
Common Name,
Scientfic Name
Mosquitofish.
Gambusia
affin'a
Guppy.
Poecilia
reticulata
Guppy.
Poecilia
reticulata
BluegiU.
Lepomis
macrochirus
BluegiU,
Lepomis
macrochirus
BluegiU.
Lepomis
macrochirus
Bluegill.
Lepomis
macrochirus
Bluegill.
Lepomis
macrochirus
BluegiU,
Lepomis
macrochirus
BluegiU,
Lepomis
macrochirus
BluegiU.
Lepomis
macrochirus
BluegiU.
Lepomis
macrochirus
Bluegill.
Lepomis
macrochirus
LCSO/ECSOMng/L)
tjf- HMAV a-cnn
stage1 Habitat" Method5 Concentration1 Test Species' Genus" GMAV" Reference
1 W FT M 069 069 069 069 Thurston et
al.. 1985
X W S U 090 Katzand
Chad wick,
1961
X W S U 1.6 1200 1200 1200 Henderson
etal.. 1959
J W S U 060 Katzand
Chad wick.
1961
J W S U 8.25 Katzand
Chadwick,
1961
J W S U 5.5 Katzand
Chadwick
1961
J W S U 2.4 Katzand
Chadwick,
1961
JWS U 1 65 _ _ _ Katz and
Chadwick.
1961
JWS U 0.86 Katzand
Chadwick,
1961
JWS U 0.33 Katzand
Chadwick,
1961
JW S U 061 Maceket
al.. 1969;
Mayer and
Ellersteck,
1986
JWS U 041 Maceket
al.. 1969;
Mayer and
EUersieck.
1986
JWS U 037 Maceket
al.. 1969.
Mayer and
Ellersieck.
1986
A-7
-------
Appendix A
Common Name, Life
Scientflc Name stage Habitat" Method1 Concentration1
BluegiU. J W S U
Lepomis
macrochirus
BluegiiJ. J W S U
Lepomis
macrochirus
BluegiU. J W S U
Lepomis
macrochirus
BluegiU. J W S U
Lepomis
macrochirus
Bluegill. J W S U
Lepomis
macrochirus
Bluegill, U S U
Lepomis
macrochirus
Bluegill, J W FT M
Lepomis
macrochirus
Bluegill, J W FT M
Lepomis
macrochirus
Largenrmth J W S U
bass.
Micropterus
dolomieu
Yellow perch, J W FT U
Perca
flavescens
Tilapia, J W S U
Tilapia
mossambica
Bullfrog, L E FT M
Rana
caiesbiana
Southern E W FT M
leopard frog.
Rana
sphenocephala
Fowler's toad. L E S U
Bufofowleri
LC50/EC50- (ng/L)
HMAV _.
Test Speaes' Genus" GMAV Reference
0.53 Mayer and
Ellersieck.
1986
0.73 Mayer and
Ellersieck.
1986
0.68 Mayer and
Ellersieck.
1986
0.19 Mayer and
Hlersieck,
1986
0.66 Henderson
et aL. 1959
0.61 Sanders,
1972
0.19 Thurstonet
ai. 1985
0.23 Thurstonet
al.. 1985
0.31 031 031 0.31 Mayer and
Ellersieck.
1986
015 0.15 015 0.15 Mayer and
Ellersieck,
1986
<5.6 <5.6 <5.6 <5.6 Mayer and
Ellersieck.
1986
2.5 25 Thurstonet
al.. 1985
25 25 2.5(E) 7906 Hall and
25(W) Swineford.
1980
120 120 120 120 Mayer and
Ellersieck.
1986
A-8
-------
Equilibrium-Partitioning Sediment Guidelines (ESGs): Endrin
Conmon Name, Life-
Sc tent fie Hone stag? Habitat11 Method' Concentration''
Western L E S U
chorus frog.
Psuedocris
triseriata
Saltwater Species
Eastern oyster. E.L W S U
Craaostrea
virginica
Sand shrimp, A E S U
Crangon
septemspmosa
Hermit crab. A E S U
Pagurus
longicarpus
Korean A W.E S U
shrimp*
Palaemon
macrodactylus
Korean A W.E FT U
shnmp.
Palaemon
macrodactylus
Grass shnmp. L W FT M
Palaemonetes
pugio
Grass shnmp, J W FT M
Palaemonetes
pugio
Grass shnmp. A W.E FT M
Palaemonetes
pugio
Grass shnmp, A W.E FT M
Palaemonetes
pugio
Grass shnmp. A W.E S U
Palaemonetes
vulgar is
Pink shnmp. A I.E FT M
Penaeus
duorarum
American eel. J E S U
Angudla
rostrata
LC50/EC50- dig/a.)
HMAV .
Test Speaes' Genus" GMAV* Reference
180 180 180 180 Mayer and
Ellersieck.
1986
790 790 790 790 Davis and
Hidu, 1969
1.7 17 17 17 Eisler.
1969
. .-
12 12 12 12 Eisler.
1969
4.7 Schoettger.
1970
0.3 1 187 1 187 1 187 Schoettger.
1970
1.2 Tyler-
Schroeder.
1979
035 Tyler-
Schroeder.
1979
0.69 Tyler-
Schroeder.
1979
063 06536 Schimmel
etal.. 1975
1.8 1.8 1085 1085 Eisler.
1969
0.037 0037 0037 0037 Schimmel
etal, 1975
06 06 0.6 06 Eisler.
1969
A-9
-------
Appendix A
Common Name,
Scientific Name
Chinook
salmon.
Oncorhvnchus
tshawytscha
Sheepshead
minnow.
Cypnnodon
vartegatus
Sheepshead
minnow.
Cypnnodon
variegatus
Sheepshead
minnow.
Cypnnodon
variegatus
Sheepshead
minnow.
Cypnnodon
variegatus
Mumrruchog,
Fundulus
heteroditus
Mummichog,
Fundulus
heteroditus
Stnped
killifish.
Fundulus
majalis
Sadfin molly.
Poecilia
latipmna
Atlantic
silverside.
Menida
menida
Threespine
stickleback.
Gasterosteus
aculeatus
Threespine
stickleback.
Gasterosteus
aculeatus
LjC50/EC5»(ng/L)
,., HMAV ^
Lifr- Overall
stage Habitat" Method" Concentration'1 Test Species' Genus" GMAV Reference
J W FT U 0048 0.048 0048 0048 Schoettger.
1970
J W.E FT M 0.37 Hansenet
al.1977
J W.E FT M 0.34 Hansenet
al.. 1977
- -
A W.E FT M 036 Hansenet
al.. 1977
J W.E FT M 038 0.3622 03622 03622 Schimmcl
et al., 1975
A W.E S U 0.6 Eisler.
1970b
A W.E S U 15 09487 Eisler.
1970b
J W.E S U 03 03 0.5334 05334 Eisler.
1970b
A W FT M 0.63 063 063 063 Schimmel
et al.. 1975
j W S U 005 0.05 005 005 Eisler.
1970b
j w.E S U 1.65 Katzand
Chad wick,
1961
j w.E S U 1.50 Katzand
Chadwick.
1961
A-10
-------
Common Name,
Scientific Name
Threespine
stickleback,
Gastemsteus
aculeatus
Threespine
stickleback.
Gastemsteus
Threespine
stickleback,
aculeatus
Threespine
stickleback,
Gastemsteus
aculeatus
Threespine
stickleback,
Gastemsteus
aculeatus
Striped bass,
Morone
saxattlis
Shiner perch.
Cymatogaster
aggnegata
Shiner perch.
Cymatogaster
aggregate
Dwarf perch,
Micrometrus
minimus
Dwarf perch.
minimus
Bluehead,
Thalassoma
btfasctatum
i^qmasmwaa^mfuaKmau^aamiB^&aaeaxaa (issus): Jfrdrm
- - v *'^--*^^J$x3&\jffi'i*ji£jfj*''''- *"
LCSCVECSO-^gfl.)
, , HMAV _
stage1 Habiat" Metho* Concentration1 Test Species' Genus" GMAV* Reference
J W.E S U 1.20 Katzand
Chadwick,
1961
J W£ S U 1.57 Katzand
Chadwick.
1961
J W£ S U 1.57 Kacand
Chadwick.
1961
J W.E S U 0.44 Katz.1961
J W£ S U 0.50 1.070 1.070 1.070 KaJz, 1961
J E FT U 0.094 0.094 0.094 0.094 Komand
Earnest,
1974
J W S U 0.8 Earnest
and
Benville,
1972
J W FT U 0.12 0.3098 0.3098 0.3098 Earnest
and
Benville.
1972
A W S U 0.6 Earnest
and
Benville,
1972
A W FT U 0.13 0.2793 0.2793 0.2793 Earnest
and
Benville,
1972
A W S U 0.1 0.1 0.1 0.1 Eisler.
1970b
A-ll
-------
Appendix A
LC50/EC50 (ng/L)
Scientific Nme stag? Habttat* Method' Concentraion4 Test
Stnped mullet, A E S U 0.3
Mugil
cephalus
Northern AW S U 3.1
puffer.
Sphaeroides
macularus
HMAV
Species' Genus* GMAV* Reference
0.3 03 03 Eisler.
1970b
31 3.1 3.1 Eisler.
1970b
'Life-stage: A = adult. J = juvenile, L = larvae, E = embryo. U = life-stage and habitat unknown. X = life-stage unknown but habitat
known.
"Habitat: I = mfauna. E = epibenihic. W = water column.
'Method: S = static. R = renewal, FT = flow-through.
'Concentration U = unmeasured (nominal). M = chemical measured
'Acute value: 96-hour LC50 or EC50. except for 48-hour EC50 for cladocera. barnacles, and bivalve molluscs (Stephan et'al.,
1985).
HMAV species: Habitat Mean Acute Value Species is the geometric mean of acute values by species by habitat (epibentbic.
infaunal, and water column).
'HMAV genus- Geometric mean of HMAV for species within a genus.
"Overall GMAV Geometric mean of acute values across species, habitats.and life-stages within the genus.
Abnormal development of oyster larvae, or loss of equilibrium of brown shrimp or blue crabs.
'Habitat mean acute values are listed by habitat when habitats differ between life-stages either within a genus or species.
A-12
-------
Appendix B
Summary of Data from Sediment-Spiking Experiments with Dieldrin. Data from
these experiments were used to calculate K^ values (Figure 2-2) and to compare
mortalities of amphipods with interstitial water toxic units (Figure 4-1) and
predicted sediment toxic units (Figure 4-2).
-------
Equilibrium-Partitioning Sediment Guidelines (ESGs): Endrin
Sediment Source,
Species tested
Soap Creek Pond
No 7. OR
Hyalella aaeca
H Mixture Soap
Creek Pond And
Mercer Lake, OR
Hyalella aaeca
Mercer Lake. OR
Hyalella aaeca
Soap Creek
Pond. OR
Hyalella aaeca
Mercer Lake. OR
Hyalella aaeca
Mercer Lake. OR
Hyalella aaeca
Lake Michigan
Diporeia sp.
Mortality
(%)
20
32
90
100
100
9
44
95
100
100
5
2
52
100
100
1.5
8.5
100
100
100
10
5
25
45
100
100
2.5
125
10
100
100
Sediment Concemraion (pg/g)
Dry Waght Organic Grbon
2.2
3.4
81
179
459
1.1
49
17.7
31.7
564
1.1
1.3
6.7
26.8
73.8
3.0
8.7
19.6
40.4
62.1
2.0
53
13.3
13.3
103
267
1.3
13
8.0
20.0
66.7
0.012"
0.171"
0224"
73
113
270
597
1.530
18
80 -
290
520
924
10
12
60
230
65v
100
290
653
1.350
2,070
18
48
121
121
909
- Z430
12
12
73
182
606
17"
31"
13"
Interstitial Water
Concentration4 TOC
(Mg/1) (%)
1.1
1.5
4.7
9.8
238
0.5
17
6.8
106
24.5
0.3
0.3
2.3
7.2
15.6
1.1
3.1
6.1
13.9
22.2
0.4
1.0
2.4
3.2
20.1
65.0
0.3
02
0.8
3.9
10.8
107
2.20
0.63
3.0
30
3.0
3.0
3.0
6.1
6.1
6.1
61
6.1
11.2
11.2
112
11.2
11.2
30
30
3.0
3.0
3.0
11.0
11.0
11.0
11.0
11.0
11.0
11.0
11.0
11.0
110
11.0
0.07
0.55
1.75
LogAToc'
4.82
488
476
4.78
4.81
4.56
467
4.63
469
4.58
4.59
4.60
4.42
4^52
4.63
4.96
4.97
5.03
4.99
4.97
4.65
468
4.70
4.58
4.66
4.57
460
4.60
4.96
4.67
4.75
420
4.15
4.31
References
Nebeker et al ,
1989
Nebeker et al..
1989
Nebeker etal.,
1989
-"~
Schuytemaet
al., 1989
Schuytemaet
al., 1989
Schuvtema et
al.. 1989
Stehly, 1992
MEAN = 4.67
SE = 0.04
'Interstitial water concentrations from Schuytema et al
Sediments were refrigerated prior to testing.
*KX (L/kg) = sediment concentration (nl&K) ~ calculated free interstitial water concentration
(1989) are concentrations of "soluble" endrin in water overlying sediments
x 103 g/kg.
B-1
------- |