f/EPA
em
H ^ United States Office of Science and Technology
MS^ Environmental Protection Agency Health and Ecological Criteria Div.
cj Office of Water & Washington. DC 20460
Office or Research and Development
EPA juu/x-xx-w«
November 1991
WATER
cv
Proposed Sediment Quality
Criteria for the Protection
of Benthic Organisms:
ACENAPHTHENE
CM
CJ
HEADQUARTERS LiHRARY
ENVIRONMENTS S-'ROTECTION AGENCY
WASHINGTON, D.C.204&C
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r
CONTENTS
PAGE
Foreword
Acknowledgments
Tables .......
Figures
u
iii
v
vi
Introduction 1-1
Partitioning. 2-1
Toxicity of Acenaphthene: Water Exposures 3-1
Toxicity of Acenaphthene (Actual and Predicted): Sediment Exposures 4-1
Criteria Derivation for Acenaphthene 5-1
Criteria Statement 6-1
References 7-1
Appendix A: Summary of Acute Values for Acenaphthene for Freshwater and Saltwater
Species A-l
Appendix B: Evaluation of Octanol-Water Partition Coefficient for Acenaphthene . B-l
Appendix C: Summary of Data from Sediment Spiking Experiments with
Acenaphthene. C*l
\.s.
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FOREWORD
Under the Clean Water Act (CWA) the U.S. Environmental Protection Agency
(U.S. EPA) is responsible for protecting the chemical, physical, and biological integrity of the
nation's waters. Section 104 of the CWA authorizes the Administrator to conduct and promote
research into the causes, effects, extent, prevention, reduction, and elimination of pollution, and
to publish relevant information. Section 104(n)(l) in particular provides for study of the effects
of pollution, including sedimentation, in estuaries on aquatic life. Section 304(a)(l) directs the
Administrator to develop and publish "criteria" reflecting the latest scientific knowledge on the
kind and extent of effects on plankton, fish, shellfish, and wildlife which may be expected from
the presence of pollutants in any body of water, including ground water, the concentration and
dispersal of pollutants, or their byproducts, through biological, physical and chemical processes;
and the effects of pollutants on biological community diversity, productivity, and stability.
Section 304(a)(2) directs the administrator to develop and publish information on the factors
necessary . for the protection and propagation of shellfish, fish, and wildlife for classes and
categories of receiving waters.
To meet this objective, in 1980 EPA published ambient water quality criteria
(WQC) for 64 of the 65 toxic pollutants or pollutant categories designated as toxic under
Section 307(a)(l) of the CWA. Additional water quality documents that update criteria. for
selected consent decree chemicals and new criteria have also been published since 1980. In
addition to the development of water quality criteria and to continue to comply with the
of the CWA, EPA has conducted efforts to develop and publish sediment quality criteria for
some of the 65 toxic pollutants or toxic pollutant categories.
Toxic contaminants in bottom sediments of the nations' s lakes, rivers, wetlands,
and coastal waters create the potential for continued environmental degradation even where
water column contaminant levels comply with established water quality criteria. In addition,
contaminated, sediments can lead to water quality degradation, even when pollutant sources are
stopped. It is intended that sediment quality criteria be used to assess the extent of sediment
contamination, to aid in implementing measures to limit or prevent additional contamination and
to identify and implement appropriate remediation activities when needed.
The criteria presented in this document are the U.S. Environmental Protection
Agency's best recommendation of the concentrations of a substance in sediment that will not
unacceptably affect benthic organisms. These criteria are applicable to a variety of freshwater
and marine sediments because they are based on the biologically available concentration of the
substance in sediments. These criteria do not protect against additive, synergistic or
antagonistic effects of contaminants or bioaccumulative effects to aquatic life or human health.
The criteria and derivation methods outlined in this document are proposed to
provide protection of benthic organisms from biological impacts from chemicals associated with
sediments. Recommendations on the use of these criteria will follow completion of the public
response process. In the interim, until final Sediment Quality Criteria are promulgated, these
criteria should only be used to support site specific assessments for sediments that are consistent
with assumptions of equilibrium partitioning theory on which these Sediment Quality Criteria
are developed.
Guidelines and guidance have been developed by EPA to assist in the application
of criteria presented in this document, in the development of sediment quality standards, and
in other water-related programs of this Agency.
ii
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ACKNOWLEDGEMENTS
Principal Author
David I. Hansen
Coauthors
Walter J. Berry
Dominic M. Di Toro
Paul Paquin
Laurie Davanzo
Frank E. Stancil, Jr.
Heinz P. KoUig
Technical and Clerical Support
Glen Thursby
Dinalyn Spears
Charito Paruta
Betty Anne Calise
U.S. EPA, Environmental Research Laboratory,
Narragansett, RI
Science Applications International Corporation,
Narragansett, RI
Manhattan College, Bronx, NY;
HydroQual, Inc., Mahwah, NJ
HydroQual, Inc.,
Mahwah, NJ
HydroQual, Inc.,
Mahwah, NJ
U.S. Environmental Research Laboratory,
Athens, GA
U.S. Environmental Research Laboratory,
Athens, GA
Persons who have made significant contributions to the development of the approach and
supporting science used in the derivation of sediment criteria for non-ionic organic contaminants
are as follows:
Herbert E. Allen
Gerald Ankley
Christina E. Cowan
Dominic M. Di Toro
David J. Hansen
Paul R. Paquin
University of Delaware, Newark, DE
U.S. EPA, Environmental Research Laboratory,
Duluth, MN •
Battelle, Richland, WA
HydroQual, Inc., Mahwah, NJ;
Manhattan College, Bronx, NY
U.S. EPA, Environmental Research Laboratory,
Narragansett, RI
HydroQual, Inc., Mahwah, NJ
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Spyros P. Pavlou
Richard C. Swartz
Nelson A. Thomas
Christopher S. Zarba
Ebasco Environmental, Bellevue, WA
U.S. EPA, Environmental Reserach Laboratory,
Newport, OR
U.S. EPA, Environmental Research Laboratory,
Duluth, MN
U.S. EPA Headquarters, Office of Water, Washington, DC
IV
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, ... TABLES
Table 2-1. Summary of measured and estimated Kow values for acenaphthene from the U.S.
EPA, Environmental Research Laboratory, Athens, GA.
Table 3-1. Acute sensitivity of freshwater and saltwater benthic species to acenaphthene.
Table 3-2. Chronic sensitivity of freshwater and saltwater organisms to acenaphthene.
Test specific data.
Table 3-3. Summary of acute and chronic values, acute-chronic ratios and freshwater and
saltwater final acute values, final acute-chronic ratios, and final chronic values
for acenaphthene.
Table 3-4. Kolmogorov-Smirnov test for the equality of freshwater and saltwater LC50
distributions for acenaphthene. Kolmogprov-Smimov test for the equality of
benthic and water column LC50 distributions.
Table 4-1. Summary of tests with acenaphthene-spiked sediment
Table 4-2. Water-only and sediment LCSOs used to test the applicability of the equilibrium
partitioning theory for acenaphthene.
Table 5-1. Sediment quality criteria for acenaphthene.
Table 5-2. Analysis of variance for derivation of sediment quality criteria confidence limits
for acenaphthene.
Table 5-3. Sediment quality criteria confidence limits for acenaphthene.
APPENDIX
Appendix A. - Acenaphthene: summary of acute values for freshwater and saltwater species.
Appendix B. - The octanol-water partition coefficient, KQW for acenaphthene.
Appendix C. - Summary of data from sediment spiking experiments, with acenaphthene that
were used to calculate KOC 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).
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FIGURES
Figure 1-1. Chemical structure and physical-chemical properties of acenaphthene.
Figure 2-1. Observed versus calculated (equation 2-4) partition coefficients for non-ionic
organic chemicals (acenaphthene datum is highlighted).
Figure 2-2. Organic carbon-normalized sorption isotherm for acenaphthene (top) and
probability plot of KOC (bottom) from sediment toxicity tests conducted by Swartz
Figure 3-1. Comparison of acenaphthene water only LC50 probability distributions for
freshwater (0) and saltwater (*) species (top panel). Cumulative distribution
functions for calculating the K-S statistic (bottom panel).
Figure 3-2. Comparison of acenaphthene water only LC50 probability distributions
for water column (0) and benthic (*) freshwater and saltwater species (top panel).
Cumulative distribution functions for calculating the K-S statistic (bottom panel).
Figure 4-1. Percent mortality of amphipods in sediments spiked with acenaphthene or
phenanthrene (Swartz, 1991), cadmium (Swartz et al., 1985), endrin (Nebeker
et al., 1989; Schuytema et al., 1989), or fluoranthene (Swartz et al., 1990), and
midge in kepone-spiked sediments (Adams et al., 1985) relative to pore water
toxic units. Pore water toxic units are ratios of concentrations of chemicals
measured in individual treatments divided by the water-only LC50 value from
water-only tests. (See Appendix C in this SQC document, Appendix C in the
endrin, dieldrin and phenanthrene SQC documents, and original references for
raw data.)
Figure 4-2. Percent mortality of amphipods in sediments spiked with acenaphthene or
phenanthrene (Swartz, 1991), dieldrin (Hokeand Ankley, 1991), endrin (Nebeker
et al., 1989; Schuytema et al., 1989) or fluoranthene (Swartz et al., 1990)
relative to "predicted sediment toxic units." Predicted sediment toxic units are
the ratios of measured treatment concentrations for each chemical in sediments
(Mg/goc) divided by the predicted LC50 (pg/goc) in sediments (K^ x Water-only
LC50, /ig/L). (See Appendix C in this document and Appendix C in the dieldrin,
endrin, fluoranthene, and phenanthrene SQC documents for raw data).
Figure 5-1. Probability distribution of concentrations of acenaphthene in sediments from
streams (n-681), lakes (n=56) and estuaries (n=74) in the United States from
1986 to 1990 (0) from the STORET (U.S. EPA, 1989c). database compared to
the acenaphthene SQC values of 14 /ig/g in freshwater sediments having TOC
= 10% and 1.4 pg/g in freshwater sediments having TOC - 1%; SQC values
for saltwater sediments are 24 pg/g when TOC =10% and 2.4 pg/g when
TOC=1 %. The upper dashed line on each figure represents the SQC value when
TOC = 10%, the lower dashed line represents the SQC when TOC = 1%.
Figure 5-2. Probability distribution of concentrations of acenaphthene in sediments from
coastal and estuarine sites from 1984 to 1989 as measured by the National Status
and Trends Program (NOAA, 1991). The horizontal line is the SQC value of
240
VI
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DISCLAIMER
This report has been reviewed by the Health and Ecological Criteria- Division, Office
of Science and Technology, U.S. Environmental Protection Agency, and approved for
publication. Mention of trade names or commercial products does not constitute endorsement
or recommendation for use.
AVAILABILITY NOTICE
This document is available to the public through the National Technical Information
Service (NTIS), 5285 Port Royal Road, Springfield, VA 22161. NTIS Accession Number
xxxx-xxxxxx.
vu
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SECTION 1
INTRODUCTION
I.I GENERAL INFORMATION
Under the Clean Water Act (CWA) the U.S. Environmental Protection Agency (U.S.
EPA) is responsible for protecting the chemical, physical and biological integrity of the nation's
waters. In keeping with this responsibility, U.S. 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 criteria for selected consent decree
chemicals and new criteria have been published since 1980. These water quality criteria are
numerical concentration limits that are the U.S. EPA's best estimate of concentrations protective
of human health and the presence and uses of aquatic life. While these water quality criteria
play an important role in assuring 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 water quality criteria. 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 quality criteria (SQC) makes it difficult to accurately assess the extent of
the ecological risks of contaminated sediments and to identify, prioritize and implement
appropriate clean up activities and source controls. As a result of the need for a procedure to
assist regulatory agencies in making decisions concerning contaminated sediment problems, a
U.S. EPA Office of Science and Technology, Health and Ecological Criteria Division
1-1
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(OST/HEC) research team was established 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 SQC derivation in all situations (U.S. EPA, 1989a). The equilibrium
partitioning (EqP) approach was selected for non-ionic organic chemicals because it presented
the greatest promise for generating defensible national numerical chemical-specific sediment
quality criteria applicable across a broad range of sediment types. The three principal
observations that underlie the EqP method of establishing sediment quality criteria are:
1. The concentrations of non-ionic organic chemicals in sediments, expressed on an
organic carbon basis, and in pore waters correlate to observed biological effects
on sediment dwelling organisms across a range of sediments.
2. Partitioning models can relate sediment concentrations for non-ionic organic
chemicals on an organic carbon basis to pore water concentrations.
3. The distribution of sensitivities of benthic and water column organisms to
chemicals are similar; thus, the currently established water quality criteria final
chronic value (FCV) can be used to define the acceptable effects concentration
of a chemical freely dissolved in pore water.
The EqP approach, therefore, assumes that: (1) the partitioning of the chemical between
sediment organic carbon and interstitial water is stable at equilibrium; (2) the concentration in
either phase can be predicted using appropriate partition coefficients and the measured
concentration in another phase; (3) organisms receive equivalent exposure from water-only
exposures or from any equilibrated phase: either from pore water via respiration, from sediment
via ingestion or from a mixture of both exposure routes; (4) for non-ionic chemicals, effect
concentrations in sediments on an organic carbon basis can be predicted using the organic
carbon partition coefficient (Koc) and effects concentrations in water, and (5) the FCV
concentration is an appropriate effects concentration for freely-dissolved chemical in interstitial
water; and (6) the SQC 0*g/goc) derived as the product of the K^ and FCV is protective of
1-2
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benthic organisms. Sediment quality criteria concentrations presented in this document are
expressed as pg cbemical/g sediment organic carbon and not on an interstitial water basis
because: (a) pore water is difficult to adequately sample; and (b) significant amounts of the
dissolved chemical may be associated with dissolved organic carbon; thus, interstitial
concentrations may overestimate exposure.
The data that support the equilibrium partitioning approach for deriving SQC for non-
ionic organic chemicals are reviewed by Di Toro et al (1991) and in the sediment quality
criteria guidelines (U.S. EPA, 1992a). Data supporting these observations for acenaphthene are
presented in this document.
Sediment quality criteria generated using the equilibrium partitioning method are suitable
for use in providing guidance to regulatory agencies because they are:
1. numerical values;
2. chemical specific;
3. applicable to most sediments;
4. predictive of-biological effects; and
5. protective of benthic organisms.
As is the case with water quality criteria, the sediment quality criteria reflect the use of
available scientific data to: 1) assess the likelihood of significant environmental effects to
benthic organisms from chemicals in sediments; and 2) to derive regulatory requirements which
will protect against these effects.
It should be emphasized that these criteria are intended to protect benthic organisms from
the effects of ^hf»^ji«^>ia associated with sediments. SQC are intended to apply to sediments
permanently inundated with water, intertidal sediment and to sediments inundated periodically
for durations sufficient to permit development of benthic assemblages. They do not apply to
occassionaUy inundated soils containing terrestrial organisms. In spills where chemical
equilibrium between water and sediments has not yet been reached, sediment chemical
1-3
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concentrations in excess of SQC indicate benthic organisms may be at risk. This is because for
spills, disequilibrium concentrations in interstitial and overlying water may be proportionally
higher relative to sediment concentrations. In spills, sediments having concentrations less than
SQC may also pose risks to benthic organisms. These criteria do not address the question of
possible contamination 'of upper trophic level organisms or the synergistic, additive or
antagonistic effects of multiple chemicals. SQC addressing these issues may result in values
lower or higher than those presented in this document. The SQC presented in this document
represent the U.S. Environmental Protection Agency's best recommendation at this time of the
concentration of a chemical in sediment that will not unacceptably affect benthic organisms.
SQC values may be adjusted to account for future data or site specific considerations.
This document presents the theoretical basis and the supporting data relevant to the
derivation of the sediment quality criterion for acenaphthene. An understanding of the
"Guidelines for Deriving Numerical National Water Quality Criteria for the Protection of
Aquatic Organisms and Their Uses" (Stephan et aL, 1985), response to public comment (U.S.
EPA, 1985) and "Guidelines for Deriving Numerical National Sediment Quality Criteria for
Non-ionic Organic Chemicals for .the Protection of Benthic Organisms" (U.S. EPA, 1992a) is
necessary in order to understand the following text, tables and calculations. Guidance into the
acceptable use of SQC values is contained in U.S. EPA, 1992b.
1.2 GENERAL INFORMATION: ACENAPHTHENE:
Acenaphthene is a member of the polycyclic aromatic hydrocarbon (PAH) group of
organic compounds. It occurs both naturally in coal tar, and as a by product of manufacturing
.processes such as petroleum refining, shale oil processing and coal tar distilling (Verschueren,
1983). Other man made sources of acenaphthene include its generation as a by product of the
combustion of tobacco, and its presence in asphalt and in soots generated by the combustion of
aromatic fuels amended with pyridine (Verschueren, 1983). Acenaphthene is used in
1-4
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manufacturing processes to produce dyes, plastics, insecticides and fungicides (Windhoitz et
al., 1983). Some PAHs are of environmental concern because they are known to be
carcinogens and/or mutagens (Brookes, 1977). With an increase in fossil fuel consumption in
the United States an increase in emissions of PAHS to the environment can be expected over
the next several decades (Eadie et al., 1982).
Acenaphthene has a two ring bridged structure (Figure 1-1). It has a solubility in water
at 25°C of 3.94 mg/1 (Miller et al., 1985), and is a solid at room temperature (melting point
of 116°C). Two significant processes which can influence the fate of acenaphthene in sediment
are sorption and biodegradation (U.S. EPA, 1980). Sorption of acenaphthene onto solids in the
water column and subsequent settling, as well as partitioning onto organics in the sediment, can
significantly affect acenaphthene transport. Bioaccumulation is a short-term process in which
PAHs with 4 rings or less are metabolized and long-term partitioning into biota is not
considered a significant fate process (U.S. EPA, 1980); Other processes found to have little
or no effect on the fate of acenaphthene in the sediment are oxidation, hydrolysis and
volatilization (U.S. EPA, 1980).
The acute toxicity of acenaphthene from individual toxicity tests ranges from 120.0 to
2,045 Mg/L for freshwater and 160 to 16,440 /tg/L for saltwater organisms (Appendix A).
Differences between concentrations of acenaphthene causing acute lethality and chronic toxicity
are small; acute-chronic ratios range from 1.5 to 6.7 (Table 3-3). Although acenaphthene
bioaccumutates in aquatic biota, the associated health or ecological risks are unknown.
1.3 OVERVIEW OF DOCUMENT:
The goal of this document is to provide a brief review of the equilibrium partitioning
methodology, a summary of the physical-chemical properties and aquatic toxicity of
acenaphthene, and the technical basis for setting the SQC for acenaphthene. Section 2 reviews
a variety of methods and data useful in deriving partition coefficients for acenaphthene and
1-5
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MOLECULAR FORMULA
MOLECULAR WEIGHT
DENSITY
MELTING POINT
PHYSICAL FORM
VAPOR PRESSURE
154.21
1.069 g/cc @ 20°C
90-95"C
Orthorhombic
bipyramidal needles
0.0026 mPa (25°C)
CAS NUMBER:
CHEMICAL NAME:
83-32-9
1,2-Dihydroacenaphthylene;
periethylenenaphthalene;
1,8-ethy lenenaphthalene
Figure 1-1. Chemical structure and physical-chemical properties of acenaphthene.
16
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includes the KOC recommended for use in the derivation of the acenaphthene SQC. Section
3 reviews aquatic toxicity data contained in the acenaphthene WQC document (U.S. EPA, 1980)
and new data that were used to derive the Final Chronic Value (FCV) used in this document
to derive the SQC concentration. In addition, the comparative sensitivity of benthic and water
column species is examined as the justification for the use of the FCV for acenaphthene in the
derivation of the SQC. Section 4 reviews data on the toxicity of acenaphthene in sediments,
the need for organic carbon normalization of acenaphthene sediment concentrations and the
accuracy of the EqP prediction of sediment toxicity using K^ and an effect concentration in
water. Data from Sections 2, 3 and 4 are used in Section 5 as the basis for the derivation of
the SQC for acenaphthene and its uncertainty. The SQC for acenaphthene is then compared to
STORE! (U.S. EPA, 1989b) and National Status and Trends (NOAA, 1991) data on
acenaphthene's environmental occurrence in sediments. Section 6 concludes with the criteria
statement for acenaphthene. The references used in this document are listed in Section 7. ~
1-7
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SECTION 2.
PARTITIONING
2.1 DESCRIPTION OF THE EQUILIBRIUM PARTITIONING METHODOLOGY:
Sediment quality criteria are the numerical concentrations of individual chemicals which
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 consequence, they can be used in much the same way as
water quality criteria; ie., the concentration of a chemical which is protective of the intended
use such as aquatic life protection. For non-ionic organic chemicals, SQC are expressed as
pg chemical/g organic carbon and apply to sediments having £ 0.2% organic carbon by dry
weight. A brief overview follows of the concepts which underlie the equilibrium partitioning
methodology for deriving sediment quality criteria. The methodology is discussed in detail in
the "Guidelines for Deriving Numerical National Sediment Quality Criteria for Non-ionic
Organic Chemicals for Protection of Benthic Organisms" (U.S. EPA, 1992a), hereafter referred
to as the SQC Guidelines.
Bioavailability of a chemical at a particular sediment concentration often differs from one
sediment type to another. Therefore, a method is necessary for determining a sediment quality
criterion based on the bioavailable chemical fraction in a sediment. For non-ionic 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 0*g chemical/liter
pore water) and not to the sediment chemical concentration 0*g 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 pore water chemical concentration, or predict it from the total sediment
concentration and the relevant sediment properties, then that concentration could be .used to
2-1
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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 sediment quality criteria. It is for this reason that the methodology described
below is called the equilibrium partitioning (EqP) method.
It is shown in the SQC Guidelines (U.S. EPA, 1992a) that benthic and water column
species from freshwater and saltwater environments exhibit similar sensitivities to a wide range
of chemicals. The data for acenaphthene are presented in Section 3. Thus, a sediment quality
criteria can be established using the final chronic value (FCV) derived using the Water Quality
Criteria Guidelines (Stephan et al., 1985) as the effect concentration, and the partition
coefficient can be used to relate the pore water concentration (FCV) to the sediment quality
criteria via the partitioning equation.
The calculation is as follows. Let FCV (/tg/L) be the no effect concentration in water
for the chemical of interest; then the sediment quality criteria, SQC (pg/kg sediment), is
computed using the partition coefficient, K, (L/kg sediment), between sediment and water
SQC = K, FCV (2-1)
This is the fundamental equation used to generate the sediment quality criterion. Its utility
depends upon the existence of a methodology for quantifying the partition coefficient, K,,.
For acenaphthene, and other hydrophobic non-ionic organic chemicals, the chemical
property of importance is the octanol-water partition coefficient, K^. It is empirically related
to the partition coefficient via !£«. (Equation 2-5), the organic carbon partition coefficient, and
foe, the weight fraction of organic carbon in the sediment (gbc/g sediment). Organic carbon
appears to be the predominant sorption phase for non-ionic organic chemicals in naturally
occurring sediments. The relationship is as follows:
K, = focKoc (2-2)
It follows that:
FCV (2-3)
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where SQCoc is the sediment quality criterion on a sediment organic carbon basis. The next
section reviews the available information for KOW.
2.2 DETERMINATION OF KQW FOR ACENAPHTHENE:
Several approaches have been used to determine KQW for derivation of a SQC, as
discussed in the SQC Guidelines. At the U.S. EPA, Environmental Research Laboratory at
Athens, GA (ERL,A), two methods were selected for measurement and two for estimation of
KOV'S. The measurement methods were shake-centrifugation and generator column, and the
estimation methods were SPARC and CLOGP (Appendix B). Data were also extracted from
the literature (Appendix B). The shake-centrifugation method is a standard procedure in the
Organization for Economic Cooperation and Development (OECD) guidelines for testing
chemicals, therefore, it has regulatory precedence.
Only one primary reference for acenaphthene was found, with a measured log10KoW
value of 3.92 (Banerjee et al., 1980). Preliminary experience with the SPARC program
suggests that the program can compute values for partition coefficients for high log P chemical
which may be more reliable and accurate than laboratory measurements which may suffer from
errors inherent in many methodologies. However, the program needs more validation by
comparison with laboratory-measured data for a wide range .of chemical structures before it is
recommended as a basis for computing partition coefficients for regulatory purposes. The
SPARC estimated log10KoW value for acenaphthene is 3.88. The CLOGP program estimate of
the log10KoW value for acenaphthene using structure activity relationships is 4.07.
The two measurement methods provide additional data from which to define KOW for
acenaphthene (Table 2-1; Appendix B). The shake-centrifugation method yielded logIOKoW =
3.84 ± 0.022 (n=4) and the generator column method yielded log10Kov = 4.17 ± 0.007
(n=4). There is no clear-cut best value from the data that has been developed. Considering
the agreement among the one measured value in the literature, the SPARC estimated value, and
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the average for the values measured by the shake-centrifugation method .under carefully
controlled conditions in the ERL,A Laboratory, 3.84 is the recommended logIOKoV value for
deriving the sediment quality criterion. The range of of the four logi0Kow value from the
shake-centrifugation measurements is 3.82 to 3.88.
TABLE 2-1. SUMMARY OF MEASURED AND ESTIMATED K«w VALUES FOR
ACENAPHTHENE FROM THE U.S. EPA, ENVIRONMENTAL RESEARCH
LABORATORY, ATHENS, GA.
Measurement
Technique
Shake-
Centrifugation
Generator Column
SPARC
CLOGP
Number of
Analyses
4
4
.
'
»
Mean
3.84
4.17 '
3.88
4.07
irK-nv
SD
0.022
0.007
-
-
2.3 DERIVATION OF K^. FROM ADSORPTION STUDIES:
Several types of experimental measurements of the organic carbon partition coefficient
are available. The first type involves experiments which were designed to measure the partition
coefficient in particle suspensions. The second type of measurement is from sediment toxicity
tests in which sediment acenaphthene and pore water acenaphthene concentrations were used
to compute
2.3.1 Koe 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 a particle interaction
effect. This effect suppresses the partition coefficient relative to that observed for undisturbed
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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 K,:
*oc
(2-4)
1+ mf
oc
where:
m = particle concentration in the suspension (kg/L)
= 1.4, an empirical constant (unitless).
The other quantities are defined previously. In this expression, the organic carbon partition
coefficient is given by:
0.00028 + 0.983 log^ (2-5)
Figure 2-1 compares observed partition coefficient data for the reversible component
with calculated values estimated with the particle interaction model (Equation 2-4 and Equation
2-5) for a wide range of compounds (Di Toro, 1985). The observed partition coefficient for
acenaphtbene using adsorption data (Mihelcic and Luthy, 1988) is highlighted on this plot. The
measured value reflects significant particle interaction effects (the partition coefficient about
a factor of four lower than the value expected in the absence of particle effects.)
_, In the absence of particle effects, K^. is related to KOW via Equation 2-5, shown above.
For log Kg* = 3.84 (ERL,A mean measured value), this expression results in an estimate of
log KOC = 3.78
2.3.2 KOC FROM SEDIMENT TOXKTIY TESTS:
Measurements of KOC are available from sediment toxicity tests using acenaphthene
(Swartz, 1991). These tests were with different saltwater sediments having a range of organic
2-5
-------
Partition Coefficient
Reversible Component
^J
a
XL
O
w
5
CO
-2
-2
6
Predicted log 10 Kp (L/kg)
Figure 2-1. Observed versus calculated (equation 2;4) partition coefficients for non-ionic
organic chemicals (acenaphthene datum is highlighted).
2-6
-------
carbon contents of 1.02 to 4.37 percent (Table 4-1; Appendix C). Acenaphtene concentrations
were measured in sediments and pore waters providing the data necessary to calculate the
partition coefficient for an undisturbed sediment. The pore water measurements did not increase
at values greater than 1,000 /ttg/L suggesting that the limit of aqueous solubility was being
approached. These tests were run at 15 °C, but a literature search for acenaphthene revealed
no solubility data at this temperature. Solubility for acenaphthene is reported as 3.94 mg/L
at 25 °C (Miller et ah, 1985), supporting the idea of saturation limitation. As a result,
computations for the partition coefficient did not include treatments where pore water
concentrations were greater than 1,000 pg/L.
Figure 2-2 is a plot of the organic carbon-normalized sorption isotherm for acenaphthene
where the sediment acenaphthene concentration (pg/goc) is plotted versus pore water
concentration 0*g/L). The data used to make this plot are included in Appendix C. Data from
treatments where pore water concentrations were greater than 1,000 /ig/L were not included on
the plot. The line of unity slope corresponding to the log10Koc = 3.78 is compared to the data.
A probability plot of the observed experimental log10Koe values is shown in Figure 2-
2. The logtoKoc values are approximately normally distributed with a mean of logs^Koc - 3.58
and a standard error of the mean of 0.012. This value is statistically indistinguishable from
= 3.78, which was computed from the experimentally determined acenaphthene
of 3.84 (Equation 2-5). Complexation with pore water DOC has not been accounted
for in the experimentally based estimate of logloKoc -3.58. Though it is not expected to be
a major factor, consideration of DOC effect would increase the estimate of logu^ relative to
the value based on total pore water concentrations. If this uncorrected value was used to set
the SQC, the SQC concentration would tend to be environmentally conservative.
2.4 SUMMARY OF DERIVATION OF K^ FOR ACENAPHTHENE:
The KOC selected to calculate the sediment quality criteria for acenaphthene is based on
2-7
-------
the regression of iog10Koc fr°m logloKoW (Equation 2-5), using the acenaphthene log10KoW of
3.84 recently measured by ERL,A. This approach was adopted because the regression equation
*
is based on the most robust data set available that spans a broad range of chemicals and particle
types, thus encompassing a wide range of KQW and f^.. The regression equation yields a
logtoKoc = 3.78. This value is in very good agreement with the logtoKoc of 3.58 measured in
the sediment toxicity tests.
2-8
-------
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Figure 2-2. Organic carbon-normalized sorption isotherm for acenaphthene (top) and
probability plot of K^ (bottom) from sediment toxitity tests conducted by Swartz
(1991).
2-9
-------
-------
SECTION 3
ToxicrrY OF ACENAPHTHENE: WATER EXPOSURES
3.1 TOXICITY OF ACENAPHTHENE IN WATER: DERIVATION OF ACENAPHTHENE
WATER QUALITY CRITERIA:
The equilibrium partitioning method for derivation of sediment quality criteria uses (he
acenaphthene water quality criteria Final Chronic Value (FCV) and partition coefficients (Koc)
to estimate the maximum concentrations of non-ionic 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 classed as benthic are either species that live in the sediment
(infauna) or on the sediment surface (epibenthic) and obtain their food from either the sediment
or water column (U.S.EPA^ 1989c). In this section (1) the FCV from the acenaphthene WQC
document (U.S. EPA, 1980) is revised using new aquatic toxicity test data, and (2) the use of
this FCV is justified as the effects concentration for SQC derivation.
3.2 ACUTE TOXICITY-WATER EXPOSURES:
Twenty standard acute toxicity tests with acenaphthene have been conducted on 10
freshwater species from 10 genera (Appendix A). Overall genus mean acute values (GMAVs)
range from 120 to 2,045 ng/L. Three invertebrates and two fishes were among the most
sensitive species; overall GMAVs for these taxa range from 120 to 670 pg/L. Tests on the
benthic life-stages of 5 species from S genera are contained in this database (Table 3-1;
Appendix A). Benthic organisms were among both the most sensistive, and most resistant,
freshwater genera to acenaphthene. Three epibenthic species, stoneflies, a snail and channel
catfish, were tested; GMAVs range from 240 and > 2,040 /tg/L. Two infaunal species were
tested, including the amphipod, Gammanis minus (LCSO = 460 pg/L), and the midge,
Paratanvtarsus sp. (LCSO = 2,045 Mg/L). The Final Acute Value derived from the overall
GMAVs (Stephan et al., 1985) for freshwater organisms is 80.01 (Table 3*3).
3-1
-------
TABLE 3-1. - ACUTE SENSITIVITY OF FRESHWATER AND SALTWATER BENTHIC SPECIES TO
ACENAPHTHENE.
RANK1
HMAV
GENUS
2
3
8
9
10
1
2
3
5
6
9
LIFE2 HAS-3
COMMON/SCI. NAME STAGE ITAT
FRESHWATER SPECIES
Stonefly, X E
Paltooerla maria
Amphipod, X I
Gamnarua mlnua
Channel catfish, J B
Ictalurua punctatua
Snail, A B
Aplexa hvunorun'
Midge, XI
Paratamrtarsua ao .
SALTWATER SPECIES
Sand shrimp, X E
Cranaon aaptemapinoaua
My aid, J B'
Mvaidopaia bahia
Amphipod, A I
Amphipod, J I
Ampeliaca abdita
Sheepehead minnow, J B,W
Cvorinodon yariaqatua
Annelid worm, J I
HMAV A
SPECIES4 GENUS5 ^P
240 240
460 460
1,720 1,720
>2,040 >2,040
2,045 2,045
245.0 245.0
317.7 317.7
S89.4 589.4
1,125 1,125
3,100 3,100
7,693 7,693
3-2
-------
TABLE 3-1. (Cont'd)
*Rank of HMAVs by genus ara from Appendix A which included benthic and water column
species.
Life atagei A • adult, J * juvenile, L * larvae, E - embryo, U * life stage and habitat
unknowiui, X « life stage unknown but habitat known.
cHabitat: Z - infauna, B * epibenthic, w » water column.
dHMAV speciest Geometric mean of acute values for benthic (habitat) life stages of each
species. (See Appendix A).
*HMAV genus: Geometric mean of HMAV for species within a genus.
3-3
-------
Twenty-one acute toxicity tests have been conducted on 10 saltwater species from 10 genera
(Appendix A). Overall GMAVs range from 245.0 to 8,163 pg/L. Crustaceans were most
sensitive; GMAVs range from 245.0 to 1,125 /ig/L. Benthic life-stages from 6 species from
6 genera have been tested (Table 3-1; Appendix A). They are among both the most sensitive,
and most resistant, saltwater genera to acenaphthene. The most sensitive benthic species is the
sand shrimp, Crangon septemspinosus. with a 96-hour LC50 of 245.0 pg/L based on
unmeasured concentrations. The mysid, Mvsidopsis bahia. has a similar sensitivity with an
average, flow-through 96-hour LC50 of 317.7 /ig/L based on measured concentrations. Other
benthic species for which there are data appear less sensitive; GMAVs range from 589.4 to
7,693 /ig/L- The Final Acute Value for saltwater species derived from the overall GMAVs
(Stephan et al., 1985) is 140.8 /tg/L (Table 3-3).
3.3 CHRONIC TOXICITY - WATER EXPOSURES:
Life cycle tt)xicity tests have been conducted with the freshwater midge (Paratanytarsus sp.)
and the saltwater mysid (M. bahial and early life stage tests have been conducted with the
fathead minnow fPjmephales promelasl and sheepshead minnow fCyprinodon variegatus) (Table
3-2; 3-3). For each of these species, except for fathead minnows, one or more benthic life
stages were exposed to acenaphthene. Other chronic toxicity tests have been conducted with
these two freshwater species (Lemke, 1984; Lemke et al.,1983; Lemke and Anderson, 1984)
but insufficient documentation is available to permit use of these results (Thursby, 199la).
Two acceptable life cycle toxicity tests have been conducted with midges (Northwestern
Aquatic Sciences, 1981). In the first test there was a 59% reduction in growth and an 85%
reduction in reproduction in 575 ng/L relative to control animals (Table 3-2). Eggs produced
by animals in this first test failed to hatch at 575 /ig/L. There was no significant effect on
parents or egg hatchability in acenaphthene concentrations from 32 to 295 pg/L. In the second
test with midges, there was a 21 % reduction in survival in 315 /ig/L relative to control animals;
3-4
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egg hatchability was not affected at the highest concentration tested (676 ng/L); although
survival of hatched midge larvae was reduced 64% in this concentration.
A total of six early life-stage toxicity tests have been conducted with the fathead minnow
as part of a round-robin test series ; two each from three laboratories .(Table 3-2). The effect
concentrations across laboraotories and tests ranged from 98 to 509 /ig/L, a factor of 5.2.
Growth (dry weight), survival or both growth and survival were reduced. Only one of these
test pairs had a suitable measured acute value, allowing calculation of an acute-chronic ratio
(Cairns and Nebeker, 1982). The concentration-response relationships were similar for these
two tests. Parental fish were unaffected in the first test at acenaphthene concentrations ranging
from 67 to 332 /tg/L, while fish exposed to 495 /tg/L had a 54% reduction in growth relative
to control fish. Cairns and Nebeker (1982) observed a 30% reduction in growth in parental fish
in 509 fig/L while there was no effect on fish exposed to 197 to 345 /tg/L.
Data from three saltwater chronic toxicity tests are available, two with mysids and one
with sheepshead minnows. Mysid reproduction was affected by acenaphthene in two tests from
two different laboratories. In the first test (Home et al., 1983) there was a 93% decrease in
reproduction in 340 /tg/L relative to control mysids; all mysids in 510 /tg/L died. No effects
were observed at 100 or 240 /*g/L in the parental generation, and juveniles released in >_ 340
/tg/L were not affected. In the second test (Thursby et al., 1989b) there was a 41 % decrease
in growth in 168 /tg/L and 96% increase in mortality at 354 /tg/L. There was a 91 % decrease
in reproduction in mysids exposed to 91.8 /tg/L and mysids exposed to 168 and 354 /tg/L did
not reproduce. Mysids exposed to ^. 44.6 /ig/L were not affected.
Sheepshead minnows exposed to acenaphthene in an early life stage test (Ward et al.,
1981) were affected at acenaphthene concentrations of ^.970 /tg/L (Table 3-2). There was a
70% reduction in survival of fish hatched in 970 /tg/L. Fewer than 10% of the embryos at _>.
2,000 /tg/L hatched and all fish that hatched died. There was no effect on either survival or
growth in fish exposed to 240 or 520/tg/L.
3-9
-------
The difference between acute and chronic toxicity of acenaphthene is small (Table 3-3).
Species mean acute-chronic ratios are 1.475 for fathead minnows, 3.424 for mysids, 4.365 for
sheepshead minnows and 6.683 for midges. The Final Acute-Chronic Ratio, the geometric
mean of these four values, is 3.484.
The Final Chronic Values (Table 3-3) are used as the effect concentrations for
calculating the sediment quality criteria for protection of benthic species. The Final Chronic
Value for freshwater organisms of 22.96 /*g/L is the quotient of the Final Acute Value of 80.01
pg/L and the Final Acute Chronic Ratio of 3.484. Similarly, the Final Chronic Value for
saltwater organisms of 40.41 /*g/L is the quotient of the Final Acute Value of 140.8 pg/L and
the Final Acute-Chronic Ratio of 3.484.
3.4 APPLICABILITY OF THE WATER QUALITY CRITERION AS THE EFFECTS
CONCENTRATION FOR DERIVATION OF THE ACENAPHTHENE SEDIMENT
QUALITY CRITERION:
The use of the Final Chronic Value (the chronic effects-based water quality criteria
concentration) as the effects concentration for calculation of the equilibrium partitioning-based
sediment quality criterion assumes similar sensitivities of benthic (infauna and epibenthic)
species and species tested to derive the water quality criteria concentration. Data supporting
the reasonableness of this assumption over all chemicals for which there are published or draft
water quality criteria documents are presented in Di Toro et al. (1991) and U.S. EPA (1989c,
1992a). The conclusion of similarity of sensitivity is supported by comparisons between acute
values: (1) for the most sensitive benthic and water column species for all chemicals; (2) all
species across all chemicals after standardizing the LC50 'values; and (3) individual chemical
comparisons for benthic and water column species. Only in this last comparison are
acenaphthene-specific comparisons in sensitivity of benthic and water-column species conducted.
The following paragraph examines the data for acenaphthene.
An initial test of the difference between the probability distributions of freshwater and
saltwater acenaphthene LC50s for all species (water column and benthic) is presented in Figure
3-10
-------
3-1. The top panel is a log probability plot of the two LC50 distributions on a log scale versus
the rank order on a probability scale. The natural way to judge the equality of these
distributions is to compare the LCSOs at a particular probability, for example a comparison of
the medians at 50% probability. The Kolmogorov-Smimov test compares another difference
(Conover, 1980). This is illustrated on the bottom plot which presents the same data but in a
slightly different way. The rank order, as a percent, is plotted versus the LCSOs. The points
are connected with straight lines to form the empirical cumulative distribution functions from
the two data sets. The Kolmogorov-Smirnov test is based on the maximum difference in
probability between these two distributions, as indicated on the figure. Note that this difference
is the horizontal distance on the top plot in Figure 3-1 (if the probability scale were linear).
Table 3-4 presents the number of LC50s in each distribution, the maximum difference (0.500),
and die probability (0.948) that a value of this magnitude or less cannot occur given that these
two samples came from the same distribution. The method of computation for this probability
value is given in Massey (1951). Since the probability is less than 0.95, the hypothesis that the
samples came from the same distribution is accepted at a 95% confidence level. Therefore for
acenaphthene, comparisons of LC50s for benthic and water column species are conducted for
combined freshwater and saltwater LC50 values.
The probability distributions of combined freshwater and saltwater acenaphthene LCSOs
for the water column and benthic species are presented in Figure 3-2. Table 3-4 presents the
number of LCSOs in each distribution, the maximum difference (0.300), and the probability
"(0.759) that a value of this magnitude or less cannot occur given that these two samples came
from the same distribution. This analysis of the relative sensitivities of benthic and water
column organisms that have been tested indicates they are from the same probability distribution
ofLCSO's. Therefore they have similar acute sensitivities. This suggests that the final chronic
value (FCV) for acenaphthene is an appropriate effects concentrations for both benthic and
water column organisms.
3-11
-------
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3-12
-------
TABLE 3-4. KOLMOGOROV-SMIRNOV TEST FOR THE
EQUALITY OF FRESHWATER AND SALTWATER LC50
DISTRIBUTIONS FOR ACENAPHTHENE. KOLMOGOROV-
SMIRNOV TEST FOR THE EQUALITY OF BENTfflC AND
WATER COLUMN LC50 DISTRIBUTIONS.
Compar-
Habitat or Water Type* K-S Statistic*
Fresh
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Benthic
Fresh (10) Salt (10)
Benthic (10) Water (10)
0.500
0.300
0.948
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Column
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bK-S statistic = maximum difference between the cumulative
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-------
SECTION 4
TOXICITY OF ACENAPHTHENE (ACTUAL AND PREDICTED):
SEDIMENT EXPOSURES
4.1 TOXICITY OF ACENAPHTHENE IN SEDIMENTS:
The toxicity of acenaphthene spiked into sediments has been tested with two saltwater
amphipod species. Freshwater benthic species have not been tested in acenaphthene-spiked
sediments. All concentrations of acenaphthene in sediments or interstial water where effects
were observed in benthic species (Table 4-1) are greater than SQC or FCV concentrations
reported in this document. Details about exposure methodology are provided because, unlike
aquatic toxicity tests, sediment testing methodologies have not been standardized.
Generalizations across species or sediments are limited because of the limited number of
experiments. Therefore, insights into relative sensitivities of, aquatic species to acenaphthene
can only be obtained from results of water-only tests (Section 3). Data are available from a
number of experiments using both field and laboratory sediments contaminated with mixtures
of PAHs and other compounds which include acenaphthene. Data from these studies have not
been included here because it is not possible to determine the contribution of acenaphthene to
toxicity observed.
Swartz (1991) exposed the amphipods Eohaustorius estnarinK and Leptocheuns,
plumulosus to three acenaphthene-spiked sediments with total organic carbon content (TOC) of
1.0%, 2.6%, and 4.4%. Sediments were rolled (1) for four hours in acenaphthene-coated
bottles, (2) stored at 4°C for either 72 hours (experiments with SL ffftTOTJI'ft) or overnight
(experiments with Lj, plumolosua). (3) rolled for an additional four hours, and (4) then stored
for 7 days at 4°C. The 10-day LCSO's for both species increased slightly with increasing
organic carbon concentration when the acenaphthene concentration was expressed on a dry
4-1
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weight basis, but decreased for gj estuarius and no pattern was apparent for L- olumulosus
when concentration was expressed on an organic carbon basis. LCSO's normalized to dry
weight differed by less than a factor of 1.6 (43.3 to 68.4 jtg/g) for IL estuarius and less than
a factor of 1.9 for J^. olumulosus over a 4.3-fold range of TOC. The organic carbon
normalized LCSO's for E. estuarius differed by a factor of 2.6 (1,600 to 4,180 Mg/goc) while
for L- plumulosus they differed by a factor of > 2.2 (10,890 to > 23,500 Mg/gbc)-
Overall, the need for organic carbon normalization of the concentration of non-ionic
organic chemicals in sediments is presented in the SQC Guidelines (U.S. EPA, 1992a). The
need for organic carbon normalization for acenaphthene is somewhat supported by the results
of spiked-sediment toxicity tests described above. Although it is important to demonstrate that
organic carbon normalization is necessary if SQC are to be derived using the EqP approach,
it is fundamentally more important to demonstrate that K^ and water only effects concentrations
can be used to predict effects concentrations for acenaphthene and other non-ionic organic
chemicals on an organic carbon basis for a range of sediments. Evidence supporting this
prediction for acenaphthene and all SQC chemicals follows in Section .4.3.
4.2 CORRELATION BETWEEN ORGANISM RESPONSE AND PORE WATER
CONCENTRATION:
i
One corollary of the EqP theory is that pore-water LCSO's for a given organism should
be constant across sediments of varying organic carbon content (U.S. EPA, 1989a). Pore-
water LCSO values are available for two species (Table 4-1; 4-2). Swaitz (1991) found 10-
day LCSO values based on pore-water concentrations varied by a factor of 1.4 (623 to 8S1
fig/L) for St flffifflriflft and by a factor of > 1.2 (1,400 to > 1,720 pg/L) for L- plumulosus.
This variability is somewhat less than that shown when-either dry weight (factors of 1.6 and
1.9) or organic caibon (factors of 2.6 and 2.2) normalization axe used to determine LCSOs
based on acenaphthene concentration in sediments.
A more.detailed evaluation of the degree to which the response of benthic organisms can
4-3
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be predicted from toxic units of substances in pore water can be made utilizing results from
toxicity tests with sediments spiked with other substances, including acenaphthene and
phenanthrene (Swartz, 1991), cadmium (Swartz et al., 198S), endrin (Nebeker et al., 1989;
Schuytema et al., 1989), fluoranthene (Swartz et al., 1990), or kepone (Adams et al., 1985)
(Figure 4-1; Appendix C). Tests with acenaphthene and phenanthrene used two saltwater
amphipods fL. plumulosus and £. estuarius) and marine sediments. Tests with cadmium and
fluoranthene used the saltwater amphipod (Rhepoxynuiy abrom'us) and marine sediments.
Freshwater sediments spiked with endrin were tested using the amphipod Hvalella azte^a; while
the midge, ffijyro|MflnouS tentans.f was tested using kepone-spiked sediments. Figure 4-1
presents the percentage mortalities of the benthic species tested in individual treatments for each
chemical versus "pore water toxic units" for all sediments tested. Pore water toxic units are
the concentration of the chemical in pore water (pg/L) divided by the water only LCSO (pg/L).
In this normalization, 50% mortality should occur at one interstitial water toxic unit. In
general, this comparison supports the concept that interstitial water concentrations can be used
to predict the response of an organism to a chemical that is not sediment-specific. This pore
water normalization was not used to derive sediment quality criteria in this document because
of the complexation of non-ionic organic chemicals with pore water DOC (Section 2) and the
difficulties of adequately sampling pore waters. Data from the dieldrin experiments (Hoke and
Ankley, 1991) are not included because more knowledge of the pore water DOC will be
required because dieldrin has a high KOC value.
4.3 TESTS OF THE EQUILIBRIUM PARTITIONING PREDICTION OF SEDIMENT
Toxicrrv:
Sediment Quality Criteria derived using the equilibrium partitioning approach utilize
partition coefficients and final chronic values from water quality criteria documents to derive
the sediment quality criteria concentration for protection of benthic organisms. The partition
coefficient (K^) is used to normalize sediment concentrations and predict biologically available
4-5
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concentrations across sediment types. Data are available to test the normalization for
acenaphthene in sediments. Testing of this component of SQC derivation requires three
elements: (1) a water-only effect concentration, such as a 10-day LC50 value in /*g/L, (2) an
identical sediment effect concentration on an organic carbon basis, such as a 10-day LC50 value
m A*g/Soc> and (3) a partition coefficient for the chemical, KOC in L/Kgoc- This section presents
evidence that the observed effect concentration in sediments (2) can be predicted utilising the
water effect concentration (1) and the partition coefficient (3).
The observed 10-day LC50 values from acenaphthene-spiked sediment tests on a
basis with IL. estuarius and L*. plumulosus were predicted (Table 4-2) using the value of
(10371) from Section 2 of this document and the 10-day water-only LCSO values in Swartz
(1991). Ratios of predicted to actual LCSOs for acenaphthene averaged 1.01 (range 0.64 to
1.64) for IL gstifflTifflt and 3.09 (range 1.83 to >5.09) for LL plumulosm. The overall mean
for both species was 2.05. .
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 ampmpods
exposed to sediments spiked with acenaphthene, phenanthrene, dieldrin, endrin, or fluoranthene.
Data from the kepone experiments are not included because we do not have a KQW for kepone
from ERL, Athens. Swartz (1991) exposed the saltwater amphipods 2L fStflHTifli! and JU.
plumulosus to acenaphthene and phenanthrene in three maT"K? sediments having 1.02, 2.61 and
4.37% organic carbon. Swartz et al. (1990) exposed the saltwater amphipod B* abroniiis to
fluoranthene in three marine sediments having 0.18, 0.31 and 0.48% organic carbon. Hoke
and Ankley (1991) exposed the amphipod Hyalella azteca to three dieldrin-spiked freshwater
sediments having 1.7, 3.0 and 8.5% organic carbon. Nebeker et at (1989) and Schuytema et
al. (1989) exposed H- azteca to three endrin-spiked sediments having 3.0, 6.1 and 11.2%
organic carbon. Figure 4-2 presents the percentage mortalities of ampmpods in individual
treatments of each chemical versus "predicted sediment toxic units" for each redrnimf treatment.
4-7
-------
Predicted sediment toxic units arc the concentration of the chemical in sediments
divided by the predicted LCSO Otg/goc) in sediments (the product of KOC and the 10-day water-
only LC50). In this normalization, 50% mortality should occur at one predicted sediment toxic
unit. Endrin and fluoranthene data indicate a slight under prediction, and acenaphthene, dieldrin
and phenanthrene a slight over prediction, of the observed mortality. In general, however, this
comparison 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. These are two fundamental propositions that underlie
the EqP method for deriving sediment quality criteria.
4-8
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4-9
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SECTION 5
j
CRITERIA DERIVATION FOR ACENAPHTHENE
5.1 CRTTERIA DERIVATION:
The equilibrium partitioning method for calculating sediment quality criteria is based
on the following procedure. If FCV (/tg/L) is the Final Chronic Value, which is the chronic
effects concentration from the water quality criteria for the chemical of interest, then the
sediment quality criteria, SQC (pg/g sediment), is computed using the partition coefficient, Kp
(L/g sediment), between sediment and pore water
SQC = KP FCV (5-1)
On a sediment organic carbon basis, the sediment quality criteria, SQC. (Mg/gJ, is:
SQCoc = KocFCV (5-2)
where KOC is the organic carbon partition coefficient for the chemical.
Since this quantity is presumably independent of sediment type for non-ionic organic chemicals,
so also is SQCoc. Table 5-1 contains the calculation of the acenaphthene sediment quality
criteria.
TABLE 5-1. SEDIMENT QUALITY CRITERIA FOR ACENAPHTHENE.
Type of
Water Body
Freshwater
Salt Water
LogioKow
(L/kg)
3.84
3.84
LogioK«
(L/kg)
3.78
3.78
FCV
0*g/D
23.0
40.4
SQCoc
138
243
(10s71 L/kgoc)«(10-'Tsoc/g0c)«(23.0 Mg acenaphthene/L) - 138
acen
oc
- (Mr* L/kgocWIO* kgoe/gocW^O^ PS acenaphthene/L) = 243
acenaphthene/goc
5-1
-------
5.2 UNCERTAINTY ANALYSIS:
Some of the uncertainty in the calculation of the acenaphthene sediment quality criteria can
be estimated from the degree to which the equilibrium partitioning model, which is the basis
for the criteria, can rationalize the available sediment toxicity data. The EqP model asserts that
(1) the bioavailability of non-ionic organic chemicals from sediments is equal on an organic
.. carbon basis; and (2) that the effects concentration in sediment Otg/gbc) can be estimated from
the product of the effects concentration from water-only exposures (pg/L) and the partition
coefficient KOC (L/kg). The uncertainty associated with the sediment quality criteria 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 the water-only and sediment toxicity tests that
have been conducted in support of the sediment criteria development effort. 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 - organism - exposure media
treatment. These data were analyzed using an analysis of variance (ANOVA) to estimate the
uncertainty (i.e. the variance) associated with varying the exposure media and that associated
with experimental error. If the EqP model were perfect, then there would be only experimental
error. Therefore, the uncertainty associated with the use of EqP is the variance associated with
. ",: varying exposure media.
< : The data used in the uncertainty analysis are the LCSOs from the water only and sediment
exposures illustrated in Figure 4-2 in Section 4. The EqP model can be used to normalize the
data in order to put it on a common basis. The LC50 for sediment on an organic carbon basis,
LC50JOC, is related to the LC50 obtained from a water-only exposure, LC50w via the
partitioning equation:
(5-3)
Therefore, KQC can be used to define the equivalent sediment toxicity based on free
5-2
-------
concentration in pore water
LC50S)OC
LC50PW » _ (5-4)
Hie EqP model asserts that toxicity of sediments expressed as the free pore water concentration
equals toxicity in water only tests.
LC50W = LC50W (5-5)
Therefore, either LC5CU or LC50W are estimates of the true LC50 for this chemical - organism
pair. In this analysis, the uncertainty of KOC, u not treated separately. Any error associated
with KOC 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 5-5 are subject to various sources
of random variations. A number of chemicals and organisms have been tested. Each chemical
- organism pair was tested in water-only exposures' -aiid in different sediments; -Let a represent
the random variation due to this source. Also, each experiment is replicated. Let € represent
the random variation due to this source. If the model were perfect, there would be no random
variations other than that due to experimental error which is reflected in the replications. Hence
a represents the uncertainty due to the approximations inherent in the model and e represents
the experimental error. Let (oj* and (k, are either InQLCSOw) or !n(LC50,.oc) corresponding to a water-only or
sediment exposure; ^ are the population of ln(LC50) for chemical - organism pair i. The error
structure is assumed to be lognonnal which corresponds to assuming that the errors are
proportional to the means, e.g. 20%, rather than absolute quantities, e.g. 1 mg/L. The
5-3
-------
statistical problem is: estimate p, and the variances of the model error, (
-------
TABLE 5-3. SEDIMENT QUALITY CRITERIA
CONFIDENCE UMTS FOR ACENAPHTHENE
~"~~ Sediment Quality Criteria
95 % Confidence kfrnfo fi
Type of SQCoc
Water Body Mg/goc Lower Upper
Fresh Water 140
Saltwater 240
64 300
110 520
The organic carbon normalized sediment quality criteria is applicable to sediments with
an organic carbon fraction of foe at 0.2%. For sediments with f^. < 0.2%, organic carbon
normalization does not apply and the sediment quality criteria do not apply.
5.3 COMPARISON OF ACENAPHTHENE SQCTO STORET AND STATUS AND
TRENDS DATA FOR SEDIMENT ACENAPHTHENE:
A STORET (U.S. EPA, 1989a) data retrieval was performed to obtain a preliminary
,»
assessment of the concentrations of acenaphthene in the sediments of the nation's water bodies.
Log probability plots of acenaphthene concentrations on a dry weight basis in sediments since
1986 are shown in Figure 5-1. Acenaphthene is found at detectable concentrations in sediments
from rivers, lakes and near coastal water bodies in the United States. Median concentrations are
generally at about 0.1 pg/g in each of these three types of water bodies. Acenaphthene
concentrations in sediments range over seven orders of magnitude throughout the country.
The SQC for acenaphthene can be compared to existing concentrations of acenaphthene
in sediments of natural water systems in the United States as contained in the STORET database
(U.S. EPA,. 1989a). These data are generally reported on a dry weight basis, rather than an
organic carbon normalized basis. Therefore, SQC values corresponding to sediment organic
5-5
-------
STREAM
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o.ooet
O.OOOU
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Figure 5-1. Probability distribution of concentrations of acenaphthcne in sediments from
streams (n=681), lakes (n=56) and estuaries (n=»74) in the United States from
1986 to 1990 (0) from the STORET (U.S. EPA, 1989c) database compared to
die acenaphthene SQC values of 14 /*g/g in freshwater sediments having TOC
» 10% and 1.4 pg/g in freshwater sediments having TOC => 1%; SQC values
for saltwater sediments are 24 /*g/g when TOC =10% and 2.4 /ig/g when
TOC=1%. The iroper dashed line on each figure represents the SQC value when
TOC » io%t the lower dashed line represents the SQC when TOC = 1%.
5-6
-------
carbon levels of 1 to 10 percent are compared to acenaphthene's distribution in sediments as
examples only. For fresh water sediments, SQC values are 1.4 pg/g in sediments having 1 %
organic carbon and 14 jug/g dry wt. in sediments having 10% organic carbon; for marine
sediments SQC are 2.4 /*g/g and 24 /ig/g, respectively. Figure 5-1 presents the comparisons
of these SQC to probability distributions of observed sediment acenaphthene levels for streams
and lakes (fresh water systems, shown on the upper panels) and estuaries (marine systems,
lower panel). For both streams (n = 681) and lakes (n = 56), the SQC of 1.4 pg/g for 1 %
organic carbon sediments is exceeded by about 4 % of the data; the 14 pg/g criteria for 10%
organic carbon freshwater sediments is exceeded in about 2 % of the samples and none of the
lake samples. In estuaries, the data (n = 74) indicate that neither of the criteria of 2.4 /ig/g
dry weight for sediments having 1 % organic carbon or 24 /*g/g dry weight for sediments
having 10 % organic carbon are exceeded, although the STORE! database for marine sediments
is not as extensive as the database for freshwater sediments..
A second database developed as part of die National Status and Trends Program
(NOAA, 1991) is also available for assessing contaminant levels in marine sediments that are
representative of areas away from sources of contamination. The probability distribution for
these data, which can be directly expressed on an organic carbon basis, is compared to the
saltwater SQC for acenaphthene (240 Mg/goc) on Figure 5-2. Data presented are from sediments
with 0.20 to 31.9% organic carbon. None of these samples (n—288) exceeded the criteria.
Hence, these results are consistent with die preceding comparison of the marine SQC to
STORET data.
Regional differences in acenaphthene concentrations may affect the above conclusions
concerning expected criteria 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 sampling in different
study areas. It is presented as an aid in assessing the range of reported acenaphthene sediment
5-7
-------
concentrations and the extent to which they may exceed the sediment quality criteria.
5-8
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5-9
-------
-------
SECTION 6
CRITERIA STATEMENT
The procedures described in the "Guidelines for Deriving Numerical National Sediment
* .
Quality Criteria for Nonionic Organic Chemicals for the Protection of Benthic Organisms" (U.S.
EPA, 1992a) indicate that, except possibly where a locally important species is very sensitive
or sediment organic carbon is < 0.2%, bentbic organisms should be acceptably protected in
freshwater sediments containing jg. 140 /*g acenaphthene/g organic carbon and saltwater
sediments containing <_ 240 pg acenaphthene/g organic carbon.
These concentrations are the U.S. EPA's best scientific judgement at this time of the
acceptable concentration of acenaphthene in sediments. Confidence limits of 64 to 300 pg/goc
for freshwater sediments and 110 to 520 pg/goc for saltwater sediments are provided as an
estimate of the uncertainty associated with the degree to which the observed concentration in
sediment 0*g/goc)» which may be toxic, can be predicted using the KQC 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, the partitioning and toxicity of acenaphthene, and sound judgement
are required in the regulatory use of sediment quality criteria and their confidence limits. The
upper confidence limit might be interpreted as a concentration above which impacts on bentbic
species would be highly likely. The lower confidence limit might be interpreted as a
concentration below which impacts on benthic species would be unlikely.
6-1
-------
-------
SECTION?
REFERENCES
Academy of Natural Sciences, 1981. Early life stage studies using the fathead minnow
(PjJmepMes. promelast to assess the effects of isophorone and acenaphthene. Final
report to U.S. EPA, Cum., OH. Academy of Natural Sciences, Philadelphia, PA. 26
pp.
Adams, W.J., R.A. Kimerle and R.C. Mosher. 1985. Aquatic safety assessment of chemicals
sorbed to sediments. In: Aquatic Toxicology and Hazard Assessment: Seventh
Symposium. Eds: R.D. Cardwell, R. Purdy and R.C. Banner. Amer. Soc. Testing and
Materials, Philadelphia, PA. STP 854. pp. 429-453.
Banerjee, S.; S.H. Yalkowsky, and S.C. Valvani, 1980. Water solubility and octanol/water
partition coefficients of organics: Limitations of the solubility-partition coefficient
correlation. Environ. Sci. Technol. 14(10): 1227-1229.
Brookes, P. 1977. Mutagenicity of polycyclic aromatic hydrocarbons. Mutation Res. 39:257-
284.
Buccafusco, R.J., SJ. Ells and G.A. LeBlanc. 1981. Acute toxicity of priority pollutants to
bluegill fLeopomis n^cmchinift- Bull. Environ. Contain. Toxicol. 26:446-452.
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7-1
-------
EG&G Bionomics. 1982. Acute toxicity of selected chemicals to fathead minnow, water flea
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j
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7-2
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Milhelcic, J.R., and R.G. Luthy. 1988. Microbial degradation of polycyclic aromatic
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7-3
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Thursby, G.B., 1991b. Re-analyses of data from Home et al., 1983. Memorandum to Walter
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Rahway, NJ. 1463 pp + appendices.
7-4
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APPENDIX B: THE OCTANOL-WATER PARTITION COEFFICIENT, KOW FOR
ACENAPHTHENE.
B.I GENERAL INFORMATION
Partitioning between water and natural soils, sediments, and aquifer materials is an
important process affecting transformation rates, toxicity, and the ultimate disposition of organic
chemicals in the environment. Extensive research, focusing on the partitioning of neutral
organic compounds, has shown that adsorption of these compounds generally is controlled by
hydrophobic interactions. As a result, the affinity that a natural sorbent has for neutral organic
solutes, in most cases, can be reliably estimated from the hydrophobicity of the solute and the
sorptive capacity of the sorbent. Organic carbon content has been used almost exclusively as
a measure of the sorptive capacity of natural sedimentary material. (Organic matter or volatile
solids content has.also been used but not as widely.) To quantitatively characterize the
hydrophobic nature of organic compounds, researchers have used various measurable
parameters, including octanol/water partition coefficients (Kgw), water solubility (corrected for
crystal energy), reverse phase HPLC retention, and topological parameters of the compounds
»
such as calculated surface area. Generally, octanol/water partition coefficients have been used
more extensively, not only for estimating the partitioning of organic compounds to sedimentary.
materials, but also for estimating bioaccumulation of organic compounds to aquatic organisms.
The KQW is defined as the ratio of the equilibrium concentration of a dissolved substance
in a system consisting of n-octanol and water and is ideally dependent only on temperature and
pressure:
KOW = (WCw (B-l)
where COT is the concentration of the substance in n-octanol and Cw is the concentration of the
substance in water. The K^ is used in estimating the organic carbon-normalized sediment-
B-l
-------
water partition coefficient (Koc) and is frequently reported in the form of its logarithm to base
ten as log P.
B.2 LITERATURE DATA
An extensive literature search was performed for acenaphthene and two standard reference
compounds, biphenyl and pyrene. Generally, problems encountered in compiling and reporting
fate constants from published data and from databases during the last several years have ranged
from retrieval of misquoted numbers to resolution of nested citations (Kollig, 1988). Some
citations were three or more authors removed from the original work or contained data that
were referenced as unpublished data or as personal communication. The same problems were
experienced during this literature search. The largest difference in misquoting numbers was six
orders of magnitude. For these reasons, ERL-Athens obtains data from the primary sources
and releases values coming only from these primary sources.. Unpublished data or,data which
originated through personal communication are rejected as well as data that are insufficiently
documented to determine their credibility and applicability or reliability.
Tables B-l and B-2 show the measured and estimated KQW values, respectively, retrieved
by this literature search. Each of the measured values was experimentally determined by the
researcher using one of several laboratory methods. The individual experimental methods are
not identified here. The estimated literature values were computed by the researchers by one.
of several published techniques. The individual computational techniques also are not identified
here.
B.3 ERL-ATHENS MEASURED DATA:
To enhance confidence in the measured K
-------
method involves adding a layer of octanol containing the compound of interest onto the surface
of water contained in a centrifuge tube. Both phases are mutually presaturated before beginning
the measurements. Equilibration is established by gentle agitation and any emulsions formed
are broken by centriftigation. The concentration in each phase is determined usually by a
chromatographic method and the KQW value calculated using Equation B-l.
TABLE B-l. MEASURED LOGtoKoW VALUES FOUND IN THE LITERATURE
Chemical
Log10KoW value
Reference.
Acenaphthene
Biphenyl
Pyrene
3.92
3.16
3.63
3.75
3.76
3.79
3.89
4.008
4.01
4.04
4.09
4.10
4.96
5.05
5.09
5.18
5.22
5.52
Banerjee, et al., 1980
Rogers and Cammarata, 1969
De Kock and Lord, 1969
Veith et al., 1979
Miller et al., 1984
Rapaport and Eisenreich, 1984
Woodbum et al., 1984
De Bruijn et al., 1989
Eadsforth, 1986
Banerjee et al., 1980
Ellington and Stancil, 1988
Bruggeman et al., 1982
Rapapaport and Eisenreich, 1984
Ellington and Stancil, 1988
Means et al., 1980
Karickhoffetal., 1979
Bruggeman et al., 1982
Burkhard et al., 1985
The original GCol method, limited to compounds with KQW values of less than 10*, was
modified (Woodburn et al., 1984) and used to determine KO* values up to 10*. Briefly, the
method requires the packing of a 24-cm length of tubing with silanized Chromosorb W.
Octanol, containing the chemical in a known concentration; is then pulled through the dry
support by gentle suction until the octanol appears at the exit of the column. Water is then
B-3
-------
pumped through the column at a rate of less than 2 ml per minute to allow equilibration of the
chemical between the octanol and water. The first 100 ml are discarded followed by collection
of an amount of water sufficient to determine the chemical concentration. The KQW is calculated
using Equation B-l.
TABLE B-2. ESTIMATED LOG10KoW VALUES FOUND IN THE LITERATURE
Chemical
Reference
Acenaphthene
Biphenyl
Pyrene
3.70
3.92
3.98
4.03
4.15
4.22
4.33
4.43
3.79
3.95
3.98
4.14
4.25
4.42
4.50
4.85
4.88
4.90
5.12
5.22
5.32
Yalkowsky et al., 1983
Miller et al., 1985
Mabey etal., 1982
Yalkowsky et al., 1979
Mackay et al., 1980
Kamlet et al., 1988
Callahan et al., 1979
Arbuckle 1983
Yalkowsky etal., 1983
Miller.et al.,. 1985
Kamlet etal., 1988
Mackay et al., 1980
Arbuckle, 1983
Doucette and Andren, 1987
D'Amboise and Hanai, 1982
Kamlet etal., 1988
Lyman et al., 1982
Mabey et al., 1982
Mackay etal., 1980
Yalkowsky et al., 1983
Callahan et al., 1979
When repetitive measurements are made in the Athens laboratory, a protocol is established
to assure compatibility with future experiments. These protocols describe the entire
experimental scheme including planning, sample requirements, experimental set up and chemical
analysis, handling of data, and quality assurance. Only established analytical methods for solute
concentration measurement are applied and the purity and identity of the chemical are
determined by spectroscopic means. The name on the label of the chemical's container is not
B-4
-------
proof of the identity.
Standard reference compounds (SRCs) are tested with each experiment. SRCs are
compounds that are used as quality assurance standards and as references in inter-laboratory
generation of data. The value of the process constant(s) has been established by repetitive
measurements for an SRC and serves as baseline information for evaluating all experimental
techniques and all aspects of quality assurance. Because the SRC is taken through the entire
experimental scheme, its acceptable result will assure the experimenter that equipment and
measurement methods are functioning satisfactorily. Table B-3 shows the KOW values for
acenaphthene and the SRCs, biphenyl and pyrene, measured at the Athens laboratory by the
methods, SC, and GCol. The SRCs were not measured by the GCol or SSF method.
TABLE B-3. INDIVIDUAL LOG^ VALUES MEASURED
BY SHAKE CENTRIFUGATION (SC), SLOW-STIR-FLASK
(SSF), AND GENERATOR COLUMN (GCOL).
Chemical
SC
GCol
Acenaphthene 3.84
Biphenyl 4.06
Pyrene 5.17
4.17
The logm of the average of eight previous measurements of KQW by the shake-centrifugation
method for biphenyl is 4.09. The logloKoW of the average of thirteen previous measurements
by the shake centrifugation method for pyrene is 5.05. These values are in good agreement
with the SRC shake-centrifugation measurements made concurrently with the acenaphthene
measurements.
B.4 ESTIMATED DATA:
A promising new computational method for predicting chemical reactivity is the computer
expert system SPARC (SPARC Performs Automated Reasoning in Chemistry) being developed
by Samuel W. Karickhoff, at ERL.A, and other scientists at the University of Georgia
B-5
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(Karickhoff et al., 1989). The system has the capability of crossing chemical boundaries to
cover all organic chemicals and uses algorithms based on fundamental chemical structural theory
to estimate parameters. Organic chemists have, in the past, established the types of structural
groups or atomic arrays that impart certain types of reactivity and have described, in
"mechanistic" terms, the effects on reactivity of other structural constituents appended to the
site of reaction. To encode this knowledge base, Karickhoff and his associates developed a
classification scheme that defines the role of structural constituents in affecting or modifying
reactivity. SPARC quantifies reactivity by classifying molecular structures and selecting
appropriate "mechanistic" models. It uses an approach that combines principles of quantitative
structure-activity relationships, linear free energy theory (LFET), and perturbed molecular
orbital (PMO) or quantum chemistry theory. In general, SPARC utilizes LFET to compute
thermal properties and PMO theory to describe quantum effects such as delocalization energies
or polarizabilities of pi electrons.
SPARC computes KQ* values from activity coefficients in the octanol( — IQ) and water ( - lw)
phases using Equation B-2.
log10Kow - Iog10(~lw/~y + log.oCMo/NU (B-2)
where MQ and Mw are solvent molecularities of octanol and water, respectively. SPARC
computes activity coefficients for any solvent/solute pair for which the structure parser can
process the structure codes. Ultimately, any solvent/solute combination can be addressed. New
solvents can be added as easily as solutes by simply providing a Simplified Molecular
Interactive Linear Entry System (SMILES) string (Anderson et at., 1987, Weininger, 1988).
Activity coefficients for either solvent or solute are computed by solvation models that are built
from structural constituents requiring no data besides the structures.
A goal for SPARC is to compute a value that is as accurate as a value obtained
experimentally for a fraction of the cost required to measure it. Because SPARC does not
B-6
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depend on laboratory operations conducted on compounds with structures closely related to that
of the solute of interest, it does not have the inherent problems of phase separation encountered
in measuring highly hydrophobic compounds (logtoKow > 5). For these compounds, SPARC's
computed value should, therefore, be more reliable than a measured one. Reliable experimental
data with good documentation are still necessary, however, for further testing and validation
ofSPARC.
CLOGP (Chou and Jurs, 1979) is a computerized program that estimates the log K^, based
on Leo's Fragment Constant Method (Lyman et al., 1982). CLOGP provides an estimate of
LogtoKow using fragment constants (Q and structural factors (F) that have been empirically
derived for many molecular groups. The estimated logloKow is obtained from the sum of
constants and factors for each of the molecular subgroups comprising the molecule using
Equation B-3.
F,) (B-3)
The method assumes mat logtoKw is a linear additive function of the structure of the solute
and its constituent parts and that the most important structural effects are described by available
factors. The structure of the compound is specified using the SMILES notation. The CLOGP
algorithm is included in the database QSAR1 located at EPA's Environmental Research
Laboratory at Duluth, Minnesota. All CLOGP values reported here were obtained through
QSAR.
Table B-4 shows the estimated logloKoW values that were computed with SPARC and
CLOGP.
B-7
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TABLE B-4. LOG10KoW VALUES ESTIMATED BY SPARC AND CLOGP
Chemical
SPARC
CLOGP
Acenaphthene
Biphenyl
Pyrene
3.88
4.25
5.13
4.07 .
4.03
4.95
'Quantitative Structure-Activity Relationships (QSARj is an interactive chemical database
and hazard assessment system designed to provide basic information for the evaluation of the
fate and effects of chemicals in the environment. QSAR was developed jointly by the U.S.
EPA Environmental Research Laboratory, Duluth, Minnesota, Montana State University Center
for Data System and Analysis, and the Pomona College Medicinal Chemistry Project.
B-8
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. REFERENCES (APPENDIX B)
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B-9
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coefficients. Pest. Sci. 17:311-325.
Ellington, J.J., and F.E. Stancil, Jr. 1988. Octanol/water partition coefficients for evaluation
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Karickhoff, S.W., D.S Brown, and T.A. Scott. 1979. Sorption of hydrophobic pollutants on
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Rogers, K.S.,and A. Cammarata. 1969. Superdelocalizability and charge density: A
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