Puget Sound Estuary Program
Briefing Report to the
EPA Science Advisory Board
THE APPARENT EFFECTS
THRESHOLD APPROACH
September 1988
Prepared for
U.S. Environmental Protection Agency
Region 10 - Office of Puget Sound
Seattle, Washington
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BRIEFING REPORT TO THE
EPA SCIENCE ADVISORY BOARD:
THE APPARENT EFFECTS THRESHOLD APPROACH
Submitted by
Office of Puget Sound
Puget Sound Estuary Program
U.S. Environmental Protection Agency, Region 10
1200 6th Avenue
Seattle, Washington 98101
Prepared by
PTI Environmental Services
3625 132nd Avenue SE
Suite 301
Bellevue, Washington 98006
under Battelle Columbus Division
EPA Contract No. 68-03-3534
PTI Contract No. C714-01
September 1988
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CONTENTS
LIST OF FIGURES iv
LIST OF TABLES v
1. INTRODUCTION 1
EPA REGION 10 CHARGE TO THE EPA SCIENCE ADVISORY BOARD 1
REGULATORY NEEDS FOR SEDIMENT QUALITY VALUES 2
SELECTION OF A SEDIMENT QUALITY VALUE APPROACH
FOR PUGET SOUND 4
EVALUATION OF RELIABILITY 6
2. THE CONCEPT OF AET 9
DESCRIPTION OF THE AET APPROACH 9
INTERPRETATION OF AET 10
Relationships Among Chemical-Specific AET 10
Dose-Response Relationships and AET 12
Influence of Environmental Factors on AET Interpretation 15
Interactive Effects and AET 17
Unmeasured Chemicals and AET 17
Matrix Effects and Bioavailability 18
3. GENERATION OF AET VALUES FOR PUGET SOUND 19
PUGET SOUND DATABASE 19
Biological Data 20
Bioassay Tests 20
Benthic Infauna Analyses 26
Chemical Data 27
Guidelines for Data Treatment 28
ii
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Bioassay Data 28
Benthic Infauna Analyses 29
Chemical Data 29
VALIDATION TEST METHODS 30
VALIDATION RESULTS AND DISCUSSION 31
Characteristics of Biologically Impacted Stations
Predicted as Nonimpacted by AET 38
Amphipod Bioassay Stations 38
Benthic Infauna Stations 43
Relative Performance of Dry Weight- and TOC-Normalized AET 44
Sediment-Water Contaminant Exchange 46
The Uniformity of Organic Matter 47
4. APPLICATION OF AET IN PUGET SOUND SEDIMENT
MANAGEMENT PROGRAMS 48
COMMENCEMENT BAY NEARSHORE/TIDEFLATS
SUPERFUND INVESTIGATION 49
PUGET SOUND DREDGED DISPOSAL ANALYSIS 49
URBAN BAY TOXICS ACTION PROGRAM 50
PUGET SOUND WATER QUALITY MANAGEMENT PLAN 50
PROPOSED STATE SEDIMENT QUALITY STANDARDS 51
5. SUMMARY 52
6. REFERENCES 53
111
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FIGURES
Number Page
1 Measures of reliability (sensitivity and efficiency) 7
2 The AET approach applied to sediments tested for lead and 4-methyl
phenol concentrations and toxicity response during bioassays 11
3 Hypothetical example of dose-response relationship resulting from
laboratory exposure to single chemicals X and Y 13
4 Hypothetical example of toxic response resulting from exposure to
environmental samples of sediment contaminated with chemicals X and Y 14
5 Hypothetical example of AET calculation for chemical X based on
classification of significant and nonsignificant responses for
environmental samples contaminated with both chemicals X and Y 16
6 Location of sampling sites for Apparent Effects Threshold data sets
in Puget Sound 23
7 Sensitivity of dry-weight and total organic carbon-normalized AET 45
IV
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TABLES
Number Page
1 Summary of data sets used to evaluate Puget Sound AET 21
2 Summary of selected chemical concentrations and key sediment
characteristics for biological stations from reference and
nonreference areas of Puget Sound 24
3 1988 Puget Sound AET for selected chemicals (normalized to dry weight) 32
4 1988 Puget Sound AET for selected chemicals (normalized to
total organic carbon) 35
5 Sensitivity and efficiency results for four validation tests
conducted with Puget Sound AET (normalized to dry weight- and total
organic carbon) 39
6 Characteristics of stations at which significant amphipod mortality
was found but no effects were predicted 41
7 Characteristics of stations at which significant benthic effects
were found but no effects were predicted 42
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1. INTRODUCTION
In response to growing concerns about widespread biological impacts associated
with chemically contaminated sediments in Puget Sound, the Washington Department of
Ecology (Ecology) and U.S. Environmental Protection Agency (EPA) Region 10, have
been actively pursuing the development of numerical sediment quality standards. This
effort has involved the identification and evaluation of a variety of methods that could
be used as the basis for sediment management decision-making.
The Apparent Effects Threshold (AET) approach is a tool for deriving empirical
sediment quality values for a range of biological indicators used to assess contaminated
sediments. The purpose of this briefing report is to describe the AET approach, how
the method has been used to develop sediment quality values, and how these sediment
quality values are being used to make regulatory decisions in a variety of programs in
Puget Sound. The overall goal of these programs is to develop technically defensible
and publicly acceptable tools for sediment management.
EPA REGION 10 CHARGE TO THE EPA SCIENCE ADVISORY BOARD
Based on the predictive capabilities of the AET method, and its applicability to
existing or planned regulatory activities, Ecology has concluded that the AET approach
could provide a technically defensible and publicly acceptable basis for the establishment
of state sediment quality standards. Subject to the provisions of Section 303 of the
Clean Water Act, the proposed standards will be submitted to EPA Region 10 for
review and comment. It is currently anticipated that state sediment quality standards
will be submitted to EPA in draft form by January 1989.
Although the AET approach has undergone regional peer review, Region 10 and
Ecology believe that an additional evaluation by an independent review board is warranted.
A Science Advisory Board (SAB) review is appropriate because the development of sediment
criteria and standards represents a relatively new and still evolving science. In addition,
the AET approach is already being considered by other state and federal agencies for
use in sediment management. The results of an SAB review will be important in
determining the extent to which the development of AET values should be encouraged
for other geographic locations.
Based upon these considerations, Region 10 has charged the SAB to undertake a
review of the AET approach. As part of this review, it was requested that the SAB
evaluate the method from two distinct perspectives:
First, the AET approach should be evaluated as a technical concept,
without consideration of the specific regulatory applications of the
method in Puget Sound or the extent of the database used to generate
Puget Sound AET.
Second, the AET approach should be reviewed specifically as applied in
Washington to generate sediment quality values for Puget Sound.
1
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During review of the AET approach, both conceptually and as applied in Puget
Sound, it is requested that the SAB specifically address the following questions.
1) Is the use of a statistically-based, empirical approach (i.e., field and laboratory
observations) to establishing quantitative relationships between sediment contaminants
and biological effects a technically acceptable means of developing sediment
quality values?
2) Are the guidelines for data treatment used in generating Puget Sound AET technically
appropriate?
3) Does the AET approach enable generation of sediment quality values for a wide
range of the chemical contaminants that could be considered problematic in marine
sediments?
4) Does the AET approach adequately incorporate consideration of a range of biological
organisms and ecological endpoints?
5) Does the AET approach adequately incorporate direct measures of sediment toxicity?
6) Are the biological indicators used in Puget Sound for the development of AET
values appropriate for the assessment of sediment contamination?
7) Does the AET approach adequately incorporate, either by design or default, the
influences of complex mixtures of contaminants typically found in environmental
samples?
8) Is the AET approach likely to generate sediment quality values that are applicable
to field conditions?
9) Is the approach used to evaluate the predictive reliability of AET values, as applied
to field data, scientifically defensible?
10) Is the AET approach technically defensible and appropriate for use in regulatory
decision-making?
In addition, it was requested that the SAB provide recommendations to the region
concerning the following technical issues:
1) Appropriateness of normalization factors (e.g., organic carbon) for the development
of sediment quality standards.
2) The need for, and role of, site-specific biological testing as a means of verifying
AET predictions in the context of regulatory programs.
REGULATORY NEEDS FOR SEDIMENT QUALITY VALUES
Sediment in many areas of Puget Sound is contaminated with potentially toxic
substances such as petroleum-derived compounds, chlorinated organic compounds, and
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metals. Sources of these contaminants include runoff from urban streets, industrial
discharges, and municipal sewage treatment plants. Shallow sills at the north and
south ends of Puget Sound inhibit the exchange of water and promote recirculation of
contaminants. It is estimated that less than 20 percent of the contaminants discharged
to Puget Sound are transported seaward to the Strait of Juan de Fuca; most of the
persistent contaminants are deposited in urban embayments within Puget Sound. Sediment
contamination in Puget Sound has been associated with impacts to benthic infauna, and
development of tumors and other abnormalities in bottom-dwelling fish (Long and
Chapman 1985; Barrick et al. 1985, 1986; Malins et al. 1982, 1984; Swartz et al. 1982).
In addition, fish, crabs, and bivalves in contaminated areas have been observed to
accumulate pollutants in their muscle tissue and organs (Dexter et al. 1982; Gahler et
al. 1982; Barrick et al. 1985; Yake and Norton 1986; Ginn and Barrick 1988; Beller et al.
1988a; Pastorok et al. 1988). In several of these areas (e.g., Elliott Bay, Commencement
Bay, and Eagle Harbor), local health departments have advised local residents to limit
their consumption of seafood.
Pollution control programs in Puget Sound have traditionally focused on protecting
water quality through effluent discharge limits and water quality standards. Such
controls have generally not been effective in preventing sediment contamination. The
control of sediment contamination is currently limited because no benchmarks in the
form of guidelines or standards have been available to assess adverse biological impacts
of contaminated sediments. In remedial action programs, such tools are needed to
address the following specific regulatory needs:
Identify problem chemicals
Establish a link between contaminated sediments and sources
Provide a predictive tool for cases in which site-specific biological testing
results were not available
Enable designation of problem areas within the site
Provide a consistent basis on which to evaluate sediment contamination
and to separate acceptable from unacceptable conditions
Provide an environmental basis for triggering sediment remedial action
Provide a reference point for establishing a cleanup goal.
In addition to remedial activities, several other regulatory programs require decision-
making tools to enable characterization and management of contaminated sediments.
For example, identification of problem areas and trend analyses is an integral part of
ambient water quality monitoring. The evaluation of potential biological impacts associated
with the disposal of dredged material is an important component in the designation of
disposal sites and review of disposal permits for dredged material. Sediment quality
values can provide useful tools for assessing the need for further chemical and biological
testing and evaluation of sediment. The use of sediment quality values is a cost-
effective alternative to extensive series of case-by-case biological testing or monitoring
and is a complement to biological testing (e.g., enables source identification using chemical-
specific values).
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Source control efforts have also required consideration of sediment management
tools. For example, chemical-specific sediment quality values have been identified as
one useful tool in developing National Pollutant Discharge Evaluation System (NPDES)
permit requirements associated with the maximum allowable concentration of contaminants
in effluent particulate material. Such requirements are intended to ensure that the
accumulation of effluent particulate material in sediments will not threaten the survival
and reproductive potential of aquatic organisms. Sediment criteria must be translated from
the ambient sediment quality goal into a source control limit.
SELECTION OF A SEDIMENT QUALITY VALUE APPROACH FOR PUGET SOUND
In the past decade, several federal, regional, and state agencies have developed
numerical criteria or assessment methods for evaluating contamination in sediments and
dredged material. Most early efforts at developing criteria were based on comparing
chemical concentrations in contaminated areas to those in reference areas, and did not
consider biological effects. More recently, approaches to evaluating sediment quality
have focused on determining relationships between sediment contaminant levels and
adverse biological impacts. Much of the information and analysis presented in this
section is contained in recent reviews of approaches to sediment quality value development
(e.g., Beller et al. 1986; Lyman et al. 1987; Battelle 1988; and Chapman in review).
Based on these documents, the following approaches were reviewed for possible application
in Puget Sound programs:
Field-Based Approaches
-Reference Area
-Field-Collected Sediment Bioassay
-Screening Level Concentration (SLC)
-Sediment Quality Triad (Triad)
-Apparent Effects Threshold (AET)
Laboratory/Theoretically-Based Approaches
-Water Quality Criteria/Interstitial Water (WQC)
-Equilibrium Partitioning (sediment-water)
-Equilibrium Partitioning (sediment-biota)
-Spiked Sediment Bioassay.
Field-based approaches rely on empirical chemical and/or biological measurements
of sediments to establish sediment quality values. Some of these approaches are purely
chemical (reference area approach) or biological (field-collected sediment bioassay
approach) in nature. Other approaches such as SLC, Triad, and AET associate biological
responses (e.g., field-collected sediment bioassays, in situ biological effects observed in
organisms living in or on sediments) and chemical concentrations measured in sediments
to develop sediment quality values. Laboratory/theoretically-based approaches rely on
extrapolation of water quality criteria to sediments, models of environmental interactions
(e.g., sediment-water equilibrium partitioning), or extrapolation of laboratory cause-
effect studies to develop sediment quality values.
As part of the evaluation of these approaches, emphasis was placed on the following
management considerations relevant to the development of Puget Sound standards:
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Applicability to existing and planned sediment management programs in
Puget Sound
Feasibility of implementation in the near term
Environmental protectiveness and cost effectiveness (i.e., reliability in
predictions of adverse effects)
Regulatory defensibility (i.e., supporting weight of evidence)
Cost of initial sediment quality value development
Cost of routine application as a regulatory tool.
In addition, each approach was evaluated according to the following technical considerations:
Data requirements for initial sediment quality value development
Data requirements for routine application as a regulatory tool
Ability to develop chemical-specific sediment quality values
Ability to develop sediment quality values for a wide range of chemicals
Current availability of values for a wide range of Puget Sound problem
chemicals
Incorporation of influence of chemical mixtures in sediments
Incorporation of a range of biological indicator organisms
Incorporation of direct measurement of sediment biological effects
Applicability of predictions to historical sediment chemistry data
Ease and extent of field verification in Puget Sound.
These criteria include key features of most of the available approaches to developing
sediment quality values (e.g., as advantages or limitations of the approaches). The AET
approach scored favorably on these criteria except with respect to data requirements
and cost of initial development. The AET approach has relatively extensive data
requirements (e.g., sediment chemistry, one or more in situ biological effects measurements,
and one or more laboratory bioassays) for sediment quality values development. However,
the current additional cost of AET development is minimal because a large Puget Sound
database has already been compiled and a wide range of AET values is available for
use. The cost of routine application of the AET approach is comparable to that for
other approaches because its implementation requires only the collection of sediment
chemistry data for comparison to chemical-specific standards developed for the approach.
Field verification using diverse environmental samples was an important element of
the evaluation of each approach for current use in Puget Sound because none of the
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available approaches is fully capable of addressing all concerns over interactive effects
among chemicals. Such effects may occur when organisms are exposed to multiple
chemicals present in sediment. Using the three most promising approaches (Screening
Level Concentration, AET, and sediment-water Equilibrium Partitioning), sediment
quality values were generated and applied to biological effects data from Puget Sound
to assess their ability to predict observed adverse impacts in actual environmental samples.
Based on consideration of the management and technical criteria and the results
of the field verification exercise, the AET approach was selected by the Puget Sound
regulatory agencies as the currently preferred method for developing sediment quality
standards in Puget Sound (other approaches will still be considered as they are developed
or tested). The AET approach can be used to provide sediment quality values for the
greatest number and widest range of chemicals of concern in Puget Sound. The approach
also incorporates the widest range of biological indicators that are directly applicable
to sediment conditions. The approach taken for conducting the field verification
exercise is described in the following section.
EVALUATION OF RELIABILITY
Environmental factors such as matrix effects or chemical interactions can affect
the ability of chemical-specific criteria to correctly predict adverse biological effects
in environmental samples. The only way to definitively test the chemical-specific
predictions (i.e., whether particular biological effects are always observed above a
given sediment quality value) is to conduct controlled laboratory spiking studies.
However, the binary (impacted/nonimpacted) predictions of sediment quality values are
most pertinent to sediment management and are testable using data sets that have matched
chemical and biological data. Tests using such data are applicable to and recommended
for assessing environmental predictions of any approach to developing sediment criteria
as part of management performance objectives. The basic requirements of such tests
of reliability are described in this section.
To meet the needs of most sediment quality management programs, an ideal sediment
criteria approach would perform well on both of the following measures of reliability,
which are evaluated with actual field data:
Sensitivity in detecting environmental problems (i.e., are all biologically
impacted sediments identified by the predictions of the chemical sediment
criteria?)
Efficiency in screening environmental problems (i.e., are only biologically
impacted sediments identified by the predictions of the chemical sediment
criteria?).
As a measure of reliability, sensitivity is defined as the proportion of all stations
exhibiting adverse biological effects that are correctly predicted using sediment quality
values. Efficiency is defined as the proportion of all stations predicted to have adverse
biological effects that actually are impacted. The concepts of sensitivity and efficiency
are illustrated in Figure 1.
Sensitivity and efficiency are independent measures of reliability. For example, a
sediment criteria approach that sets values for a wide range of chemicals near their
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analytical detection limits will probably be sensitive but inefficient. That is, it will
predict a large percentage of sediments with biological effects but will also predict
many biologically unimpacted sediments with only slightly elevated chemical concentrations.
Such an approach may be environmentally protective but also may result in overregulation
that would not be cost effective.
Conversely, a sediment criteria approach that sets values at the upper end of the
range of environmental concentrations may be efficient but insensitive. That is, a high
percentage of the stations with predicted impacts may indeed be biologically impacted,
but the approach may fail to predict other biologically impacted stations with moderate
to high chemical concentrations. Such an approach may be cost-effective and defensible
in pursuing high priority remedial actions (i.e., would not overregulate) but would not
be environmentally protective.
The overall reliability of any sediment criteria approach addresses both components
of sensitivity and efficiency. This measure is defined as the proportion of all stations
for which correct predictions were made for either the presence or absence of adverse
biological effects:
All stations correctly predicted as impacted "I
.- .. ....^ LAI! stations correctly predicted as nonimpactedl
Overall reliability =
[Total number of stations evaluated]
High reliability results from correct prediction of a large percentage of the impacted
stations (i.e., high sensitivity; few false negatives) and correct prediction of a large
percentage of the nonimpacted stations (i.e., high efficiency; few false positives).
These measures of reliability were important considerations in assessing the
suitability for regulatory application of sediment quality values calculated by the AET
approach. An assessment of reliability has recently been conducted using a large
database comprising samples from 13 Puget Sound embayments (not all biological indicators
are available in all embayments). In at least 85 percent of the available samples for
each biological indicator, the approach either correctly classifies as impacted samples
that exhibit adverse biological effects or correctly classifies as not impacted samples
that do not exhibit adverse biological effects. Detailed results of the reliability evaluation
for the AET approach are described in Section 3. The underlying concept of the AET
approach is described in the following section.
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2. THE CONCEPT OF AET
An AET is defined as the sediment concentration of a given chemical above which
statistically significant (P<0.05) biological effects (e.g., depressions in the abundances
of indigenous benthic infauna) are always expected. If any chemical exceeds its AET
for a particular biological indicator, an adverse biological effect is predicted for that
indicator. If all chemical concentrations are below their AET for a particular biological
indicator, then no adverse effect is predicted.
In this section, AET generation is described and the AET concept is discussed as
it relates to the interpretation of chemical and biological data in field-collected sediments.
AET generation is a conceptually simple process and incorporates the complexity of
biological-chemical interrelationships in the environment without relying upon a priori
assumptions as to the mechanistic nature of these interrelationships. The concept of
the AET is presented in this section with little reference to specific chemicals, specific
biological tests, or specific chemical normalizations, because the approach is not inherently
limited to specific subsets of these variables. The specific use of the AET concept to
generate AET values from Puget Sound data is described in Section 3.
DESCRIPTION OF THE AET APPROACH
The focus of the AET approach is to identify concentrations of contaminants that
are associated exclusively with sediments exhibiting statistically significant biological
effects relative to reference sediments. The calculation of AET for each chemical and
biological indicator is straightforward:
1. Collect "matched" chemical and biological effects data--Conduct chemical
and biological effects testing on subsamples of the same field sample (to
avoid unaccountable losses of benthic organisms, benthic infaunal and
chemical analyses are conducted on separate samples collected concurrently)
2. Identify "impacted" and "nonimpacted" stations--Statistically test the
significance of adverse biological effects relative to suitable reference
conditions for each sediment sample and biological indicator; suitable
reference conditions are established by sediments containing very low or
undetectable concentrations of any toxic chemicals
3. Identify AET using only "nonimpacted" stations--For each chemical, the
AET can be identified for a given biological indicator as the highest
detected concentration among sediment samples that do not exhibit
statistically significant effects (if the chemical is undetected in all
nonimpacted samples, no AET can be established for that chemical and
biological indicator)
4. Check for preliminary AET--Verify that statistically significant biological
effects are observed at a chemical concentration higher than the AET;
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otherwise the AET is only a preliminary minimum estimate (or may not
exist).
5. Repeat Steps 1-4 for each biological indicator.
A pictorial representation of the AET approach for two example chemicals is
presented in Figure 2 based on results for a toxicity bioassay. Two subpopulations of
all sediments analyzed for chemistry and subjected to a bioassay are represented by
bars in the figure and include:
Sediments that did not exhibit statistically significant (P>0.05) toxicity
relative to reference conditions ("nonimpacted" stations)
Sediments that exhibited statistically significant (P<0.05) toxicity in
bioassays relative to reference conditions ("impacted" stations).
The horizontal axis in each figure represents sedimentary concentrations of chemicals
(lead or 4-methylphenol) on a log scale. Dry weight normalized data are presented in
Figure 2, although the AET approach is not limited to any particular normalization.
For the toxicity bioassay under consideration, the AET for lead is the highest lead
concentration corresponding to sediments that did not exhibit significant toxicity (the
top bar for lead in Figure 2). Above this lead AET, significant toxicity was always
observed in the data set. The AET for 4-methylphenol was determined analogously.
INTERPRETATION OF AET
An AET corresponds to the sediment concentration of a chemical above which all
samples for a particular biological indicator were observed to have adverse effects.
Thus, the AET is based on noncontradictory evidence of biological effects. Data are
treated in this manner to reduce the weight given to samples in which factors other
than the contaminant examined (e.g., other contaminants, environmental variables) may
be responsible for the biological effect.
Relationships Among Chemical-Specific AET
Using Figure 2 as an example, sediment from Station SP-14 exhibited severe
toxicity, potentially related to a greatly elevated level of 4-methylphenol (7,400 times
reference levels). The same sediment from Station SP-14 contained a relatively low
concentration of lead that was well below the AET for lead (Figure 2). Despite the
toxic effects associated with the sample, sediments from many other stations with
higher lead concentrations than SP-14 exhibited no statistically significant biological
effects. These results were interpreted to suggest that the effects at Station SP-14
were potentially associated with 4-methylphenol (or a substance with a similar environ-
mental distribution) but were less likely to be associated with lead.
A converse argument can be made for lead and 4-methylphenol in sediments from
Station RS-18. In this manner, the AET approach helps to identify measured chemicals
that are potentially associated with observed effects at each biologically impacted site
and eliminates from consideration chemicals that are far less likely to be associated
with effects (i.e., the latter chemicals have been observed at higher concentrations at
10
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11
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other sites without associated biological effects). Based on the results for lead and 4-
methylphenol, effects at 4 of the 28 impacted sites shown in the figures may be associated
with elevated concentrations of 4-methylphenol, and effects at 7 other sites may be
associated with elevated concentrations of lead (or similarly distributed contaminants).
These results illustrate that the occurrence of biologically impacted stations at
concentrations below the AET of a single chemical does not imply that AET in general
are not protective against biological effects, only that single chemicals may not account
for all stations with biological effects. By developing AET for multiple chemicals, a
high percentage of all stations with biological effects are accounted for with the AET
approach (reliability results are presented in Section 3 of this briefing document).
AET can be expected to be more predictive when developed from a large, diverse
database with wide ranges of chemical concentrations and a wide diversity of measured
chemicals. Data sets that have large concentration gaps between stations and/or do
not cover a wide range of concentrations must be scrutinized carefully (e.g., to discern
whether chemical concentrations in the data set exceed reference concentrations)
before generation of AET is appropriate.
Dose-Response Relationships and AET
The AET concept is consistent with empirical observations in the laboratory of
dose-response relationships between increasing concentrations of individual toxic chemicals
and increasing biological effects. A simple hypothetical example of such single-chemical
relationships is shown for chemicals X and Y in Figure 3. In the example, data are
shown for laboratory exposures of a test organism to sediment containing only increasing
concentrations of chemical X, and independently, for exposures to sediment containing
only increasing concentrations of chemical Y. The magnitude of toxic response in the
example differs for the two chemicals and occurs over two different concentration
ranges. It is assumed that at some level of response, for example >25 percent, the two
different responses can be distinguished from reference conditions (i.e., responses
resulting from exposure to sediments containing very low or undetectable concentrations
of any toxic chemicals).
These single-chemical relationships cannot be proven in the field because organisms
are exposed to complex mixtures of chemicals in environmental samples. In addition,
unrelated discharges from different sources can result in uncorrelated distributions of
chemicals in environmental samples. To demonstrate the potential effects of these
distributions, response data are shown in Figure 4 for a random association of chemicals
X and Y using the same concentration data as in Figure 3. The data have been plotted
according to increasing concentrations of chemical X, and the same dose-response
relationship observed independently for the two chemicals in the laboratory has been
assumed. The contributions of chemicals X and Y to the toxic response shown for
these simple mixtures is intended only for illustration purposes to enable direct comparison
to the relationships shown in Figure 3, but are analogous to an additive toxic response.
Other interactive effects are not considered in this example.
In Figure 4, a significant response relative to reference conditions would result
whenever elevated concentrations of either chemical X or chemical Y occurred in a
sample. Because of the random association of Y with X in these samples, the significant
responses would appear to occur randomly over the lower concentration range of
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14
-------
chemical X. The classification of the responses shown in Figure 4 into significant and
nonsignificant groups (i.e., >25 percent response for either chemical) results in generation
of Figure 5.
Figure 5 represents the appearance of the environmental results when ranked
according to concentration of chemical X using these data. Below the AET for chemical
X, significant toxicity is produced by elevated concentrations of chemical Y, which is
randomly associated with the distribution of chemical X. Above the AET for chemical
X, significant toxicity is always produced by elevated concentrations of chemical X,
although in some samples, elevated concentrations of chemical Y also contribute to the
overall toxicity. The AET for chemical X corresponds conceptually, in this simple
example, to the concentration in Figure 3 at which a significant difference in response
was observed in the laboratory for chemical X.
In environmental samples that contain complex mixtures of chemicals, a monotonic
dose-response relationship such as in this simple two-chemical example may not always
apply. For example, a consistently increasing biological response may not always occur
at increasing concentrations of a chemical above its AET. Such observations could
indicate that the AET is coincidental (i.e., that the observed toxicity in some or all
samples above the AET is unrelated to the presence of that chemical), or that changing
environmental factors in samples exceeding an AET obscure a monotonic dose-response
relationship. Such factors are discussed in the following section.
Influence of Environmental Factors on AET Interpretation
Although the AET concept is simple, the generation of AET values based on
environmental data incorporates many complex biological-chemical interrelationships.
For example, the AET approach incorporates the net effects of the following factors
that may be important in field-collected sediments:
Interactive effects of chemicals (e.g., synergism, antagonism, and additivity)
Unmeasured chemicals and other unmeasured, potentially adverse variables
Matrix effects and bioavailability [i.e., phase associations between
contaminants and sediments that affect bioavailability of the contaminants,
such as the incorporation of polycyclic aromatic hydrocarbons (PAH) in
soot particles].
The AET approach cannot distinguish and quantify the contributions of interactive
effects, unmeasured chemicals, or matrix effects in environmental samples, but AET
values may be influenced by these factors. To the extent that the samples used to
generate AET are representative of samples for which AET are used to predict effects,
the above environmental factors may not detract from the predictive reliability of AET.
Alternatively, the infrequent occurrence of the above environmental factors in a data
set used to generate AET could detract from the predictive reliability of those AET
values. If confounding environmental factors render the AET approach unreliable, this
should be evident from validation tests in which biological effects are predicted in
environmental samples. Tests of AET values generated from Puget Sound data (see
Section 3) indicate that the approach is relatively reliable in predicting biological
effects despite the potential uncertainties of confounding environmental factors.
15
-------
LU
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Although the above environmental factors can influence the generation of field-
based sediment quality values such as AET, they also may influence the application of
all sediment quality value approaches for the prediction of adverse biological effects.
For example, sediment quality values based on laboratory sediment bioassays spiked with
single chemicals would not be susceptible to the effects of the environmental factors
listed above. However, in applying such values to field-collected samples, predictions of
biological effects could be less successful to the extent that interactive effects, unmeasured
chemicals, and matrix effects occur in the environment.
The nature of the relationships between AET values and confounding environmental
factors is discussed in the remainder of this section.
Interactive Effects and AETAET uncertainty is increased by the possibility of
interactive effects; the increase in uncertainty is expected to be less pronounced when
large data sets collected from diverse areas are used to generate AET. Additivity and
synergism can produce a comparatively low AET for a given chemical by causing impacts
at concentrations that would not cause impacts in the absence of these interactive
effects. This would effectively reduce the pool of nonimpacted stations used to generate
AET. This effect should be reduced if a diverse database is used such that chemicals
occur over a wide range of concentrations at stations where additivity and synergism
are not operative. For chemicals that covary regularly in the environment (e.g., fluor-
anthene and pyrene), even a large, diverse database will not reduce the effects of
additivity and/or synergism on AET generation. The resulting AET values for such
chemicals may be reliable in predicting biological effects in environmental samples
although not representative of the toxicities of the chemicals acting independently.
Antagonism will produce comparatively high AET values if (and only if) the AET is
established at a station where antagonism occurs. A large, diverse database could not
rectify this elevation of AET if the station at which antagonism occurred was the
nonimpacted station with the highest concentration (i.e., the station setting an AET).
An AET set by a station at which antagonism occurred would not be representative of
the toxicity of the chemical acting independently. Hence, if antagonism did not occur
widely, such antagonistic effects would cause the AET to be less sensitive in predicting
adverse effects in the environment.
Empirical approaches such as the AET do not provide a means for characterizing
interactive effects. Only laboratory-spiked sediment bioassays offer a systematic and
reliable method for identifying and quantifying additivity, synergism, and antagonism.
A great deal of research effort would be required to test the range of chemicals
potentially occurring in the environment (both individually and in combination), a
sufficiently wide range of organisms, and a wide range of sediment matrices to establish
criteria. In addition, the applicability of bioassays conducted with laboratory-spiked
sediments to environmentally-contaminated sediments requires further testing.
Unmeasured Chemicals and AET--Another source of uncertainty for AET and other
field-based approaches is the possibility of effects being caused by unmeasured, covarying
chemicals. Such chemicals would not be expected to substantially decrease the ability
of AET to predict biologically impacted stations (excluding interactive effects discussed
above). If an unmeasured chemical (or group of chemicals) varies consistently in the
17
-------
environment with a measured chemical, then the AET established for the measured
contaminant will indirectly apply to, or result in the management of, the unmeasured
contaminant. In such cases, a measured contaminant would act as a surrogate for an
unmeasured contaminant (or group of unmeasured contaminants). Because all potential
contaminants cannot be measured routinely, management strategies must rely to some
extent on "surrogate" chemicals.
If an unmeasured toxic chemical (or group of chemicals) does not always covary
with a measured chemical (e.g., if a certain industry releases an unusual mixture of
contaminants), the effect should be mitigated if a sufficiently large and diverse data
set is used to establish AET. Use of a large data set comprising samples from a
variety of areas with wide-ranging chemical concentrations would decrease the likelihood
that an unrealistically low AET would be set. Because AET are set by the highest
concentration of a given chemical in samples without observed biological effects, AET
will not be affected by less contaminated samples in which unmeasured contaminants
cause biological effects.
If an unmeasured toxic chemical does not covary with any of the measured chemicals,
it is unlikely that the AET (or any other chemical-specific approach) could predict
impacts at stations where the chemical is inducing toxic effects. The frequency of
occurrence of stations with biological effects but no chemicals exceeding AET is the
subject of validation tests (see Section 3 of this briefing document).
Matrix Effects and Bioavailability--Geochemical associations of contaminants with
sediments that reduce bioavailability of those contaminants would affect AET analogously
to antagonistic effects (i.e., they would increase AET relative to sediments in which
this factor was not operative). Sediment matrices observed in Puget Sound that may
reduce bioavailability of certain contaminants include slag material (containing high
concentrations of various metals and metalloids, such as copper and arsenic) and coal
or soot (which may contain high concentrations of largely unavailable PAH, as opposed
to oil or creosote, in which PAH would be expected to be far more bioavailable; e.g.,
Harrington and Teal 1982). Many kinds of matrices may occur in the environment and
a large proportion may be difficult to classify based upon appearance or routinely
measured sediment variables. Hence, the use of matrix-specific data sets to generate
AET, although desirable, would be difficult to implement.
To address this concern from a technical perspective (i.e., representativeness of
data used in AET generation), the AET database could be screened for sediment with
chemical concentrations that are anomalously high relative to those in other nonimpacted
sediments from different geographic areas. From a management perspective, this
guideline would generate more protective (sensitive) sediment quality standards that
may also be less efficient in only identifying problem sediments. These sediments
would be considered nonrepresentative and not used in AET generation unless and until
additional data could substantiate that they are representative. Such data treatment
methods are discussed in the following section.
18
-------
3. GENERATION OF AET VALUES FOR PUGET SOUND
The AET approach was developed for projects conducted in the Puget Sound area
and has thus far incorporated only Puget Sound data. An extensive database of biological
and chemical data from numerous Puget Sound projects has been compiled for AET
generation and validation tests (over 300 samples, four biological effects indicators, and
over 125 chemicals although some chemicals were detected infrequently). The generation
of AET values for Puget Sound has necessarily made use of available data, although the
AET concept is not intrinsically limited to the biological effects indicators or chemicals
used in Puget Sound. A brief history of the generation of AET values for Puget Sound
projects is included below, followed by a description of the chemical and biological
data in the existing Puget Sound database.
PUGET SOUND DATABASE
AET values were originally generated for a combined measure of sediment toxicity
[i.e., either amphipod mortality (Swartz et al. 1985) or oyster larvae abnormality (Chapman
and Morgan 1983)] and depressions in the abundance of benthic infauna (at phylum or
class levels of taxonomic classification). These AET values were based on data from 50
to 60 stations sampled during the 1984-85 remedial investigation of Commencement Bay
(a heavily industrialized embayment adjacent to Tacoma, Washington). In a 1986 project
for the Puget Sound Dredged Disposal Analysis (PSDDA) and Puget Sound Estuary
Program (PSEP), AET values were generated with a larger Puget Sound database consisting
of 188 samples and including the previous Commencement Bay data. Biological indicators
included individual measures of toxicity [i.e., amphipod mortality, oyster larvae abnormality,
and Microtox bioassays (Williams et al. 1986)] and benthic infaunal depressions (at
phylum or class levels). Matched biological and chemical data for 10 additional stations
from a joint state and federal investigation of creosote contamination in Eagle Harbor
(Barrick et al. 1986) have also been incorporated. Most recently, biological and chemical
data for over 100 stations from Elliott Bay and Everett Harbor (Seller et al. 1988a;
Pastorok et al. 1988) have been added to the database for generation of AET values.
Elliott Bay is a highly urbanized embayment adjacent to Seattle, Washington. Everett
Harbor is an urban embayment adjacent to Everett, Washington and is characterized by
pulp industry activities.
Based on recent studies conducted for PSEP (see Barrick et al. 1988), the following
strategy was recommended for developing reliable AET:
1. Collect chemical and biological effects data from preferably 50 stations
or more
2. Bias the positioning of stations to ensure sampling of a variety of
contaminant sources (e.g., an urban environment impacted by multiple
contaminant sources and preferably multiple geographic areas at which
AET predictions will be applied) over a range of contaminant concentrations
(preferably over at least one to two orders of magnitude)
19
-------
3. Conduct chemical tests for a wide range of chemical classes and ensure
that <100 ppb detection limits (lower if possible) are attained for
organic compounds (metals detection limits do not appear to be a
problem).
The data included in the existing 334-sample Puget Sound data set are character-
ized in Table 1 and conform to these recommendations. The geographic distribution of
samples in this data set is presented in Figure 6. A summary of concentration ranges
of selected chemicals and key sediment characteristics [i.e., total organic carbon (TOC),
fine-grained sediment content, sulfides] is provided in Table 2 for two groups of these
samples: sediments sampled from reference areas (nonurban embayments) and from
nonreference areas of Puget Sound (frequently from industrialized, urban embayments).
Reference areas in Puget Sound are generally removed from the direct influence of
contaminant sources in nonurbanized areas of the sound; almost all of these stations
are nonimpacted. Most data for nonreference areas are from industrialized urban
embayments and include both nonimpacted and impacted stations.
Biological Data
Two major kinds of biological tests are commonly used for environmental assessment
of chemical contamination: sediment bioassays and evaluations of indigenous biota.
Sediment bioassays involve the controlled exposure of test organisms (usually a single
sensitive species) to test sediment for a fixed period of time. Although bioassays can
be conducted in situ, most are conducted in the laboratory. Bioassays have at least
two major advantages over evaluations of indigenous biota. First, because most experimental
conditions can be controlled during bioassays (e.g., temperature, dissolved oxygen,
lighting, sediment grain size, predation), measured effects can be attributed to chemical
toxicity (i.e., the uncontrolled variable of interest) with reasonable confidence. Second,
bioassays generally are considerably less expensive to conduct than evaluations of
indigenous biota. A major disadvantage of most sediment bioassays is the lack of
knowledge as to how the results correspond to potential impacts on diverse species
under variable field conditions (Long and Chapman 1985; Swartz et al. 1985; Chapman
et al. 1987). Part of this uncertainty can be evaluated by comparing bioassay responses
with effects on indigenous biota.
Evaluations of sediment toxicity to indigenous biota can involve any kind of
organism but usually are focused on benthic macroinvertebrates. These organisms are
preferred because they live in close contact with bottom sediments, are relatively
stationary, can be sampled quantitatively, and have been found to exhibit predictable
patterns in response to environmental stress. Unlike bioassays, many environmental
variables cannot be controlled during evaluations of indigenous biota. The relationship
between measured effects on indigenous biota is therefore less certain than for bioassays.
However, because effects on indigenous biota are measured in the field, there are no
limitations encountered with extrapolating laboratory results to field situations. Specific
analytical and statistical procedures for each of the biological tests used to develop
AET are presented in the following sections.
Bioassay TestsCurrently, AET have been generated for three kinds of bioassays
used in Puget Sound as acute lethal or sublethal indicators of sediment toxicity. The
AET concept can be applied to other bioassays as they are developed.
20
-------
TABLE 1. SUMMARY OF DATA SETS USED TO EVALUATE
PUGET SOUND AET
Embayment
Bellingham Bay
Carr Inlet
Case Inlet
Central Puget
Sound Basin
Commencement
Bay
Dabob Bay
Eagle Harbor
Elliott
Bay
Everett
Harbor
Port Susan
Samish Bay
Sequim Bay
Numbei
Survey of Bio
Codea Sam
EIGHTBAY
CBMSQS
EIGHTBAY
ALKI
EHCHEM
CBBLAIR
CBMSQS
EIGHTBAY
EHCHEM
EBCHEM
ALKI
TPPS3AB
DUWRIV1
DUWRIV2
EIGHTBAY
EVCHEM
EVERETT 1
EIGHTBAY
EBCHEM
EVCHEM
EIGHTBAY
EIGHTBAY
DUWRIV1
DUWRIV2
8 /
4 /
4 /
4 /
2 /
6 /
42 /
2 /
2 /
4 /
8 /
71 /
24 /
4 /
7 /
27 /
8 /
30 /
8 /
13 /
13 /
3 /
6 /
8 /
5 /
3 /
4 /
4 /
1 /
1 /
r/Kind
effect
plesb t
A
BAOM
A
B
BA
BAG
BAOM
AOM
B OM
A
BA
BA
A
B
B
B
A
A
A
BA
A
B
A
A
BA
BA
A
A
A
A
Chemical
\cid
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Base
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Neut.
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Analyses Conductedc
PCB
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Pest.
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
VGA
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Metal
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
X
Misc
X
X
X
X
X
X
X
X
X
Sinclair Inlet
EIGHTBAY 8 / A
21
-------
TABLE 1. (Continued)
a Puget Sound samples are derived from multiple surveys, which provided data for varying
numbers of chemicals and biological indicators. The surveys include:
ALKI Metro survey of Alki Point, Seattle (Osborn et al. 1985; Trial and Michaud
1985)
CBBLAIR Port of Tacoma dredging survey of Blair Waterway in Commencement Bay
(data analyzed integrated with CBMSQS data during the Superfund project;
see Barrick et al. 1985)
CBMSQS Commencement Bay Nearshore/Tideflats Superfund project; Carr Inlet reference
area (Barrick et al. 1985)
DUWRIV1 PSDDA dredging study in the Duwamish River, Seattle (Phase I); Sequim Bay
reference area (Chan et al. 1985)
DUWRIV2 PSDDA dredging study in the Duwamish River, Seattle (Phase II); Sequim
Bay reference area (Chan et al. 1986)
EBCHEM PSEP survey of Elliott Bay; Port Susan reference area (Beller et al. 1988a)
EHCHEM Ecology Preliminary Investigation of Eagle Harbor; Blakely Harbor reference
area in Central Puget Sound (Barrick et al. 1986)
EIGHTBAY EPA survey of eight urban and nonurban embayments in Puget Sound
(Battelle 1985)
EVCHEM PSEP survey of Everett Harbor; Port Susan reference area (Pastorok et
al. 1988)
EVERETT1 U.S. Navy preliminary dredging study in Everett Harbor (U.S. Navy 1985)
TPPS3AB Toxic Pretreatment Planning Study conducted in Central Puget Sound and
Elliott Bay by Metro (Romberg et al. 1984).
Station locations for each survey are summarized in Appendix B of Barrick et al. (1988).
b 334 distinct samples (including 12 repeated samplings) at a total of 322 locations:
(B) 201 benthic infaunal analyses; (A) 287 amphipod mortality bioassays; (O) 56 oyster
larvae abnormality bioassays; (M) 50 Microtox (saline extract) bioassays. The seven amphipod
bioassay stations excluded as biological anomalies and the three benthic infauna and eight
amphipod bioassay stations excluded as chemical anomolies (see text) are not included in
these totals.
c Chemical analyses conducted for U.S. EPA priority pollutant acid, base, neutral, PCB,
pesticide, and volatile organic compounds, metals, and miscellaneous compounds not recognized
as EPA priority pollutants (e.g., resin acid compound data for the EVCHEM survey, and
tentatively identified organic compounds).
22
-------
EVERETT
:i,-,;. HARBOR '
':'.<.
Dtbob Bay
'.MADISON-* 3
7 L»*» Wtihlngton
Ship Ctnit
.'.EAGLE
'. HARBOR -
f»/ort
*
;': SEATTLE
Figure 6. Location of sampling sites for Apparent Effects Threshold data sets
in Puget Sound.
23
-------
TABLE 2. SUMMARY OF SELECTED CHEMICAL CONCENTRATIONS AND
KEY SEDIMENT CHARACTERISTICS FOR BIOLOGICAL STATIONS FROM
REFERENCE AND NONREFERENCE AREAS OF PUGET SOUNDa
Reference Areab
Non-Reference Areac
Chemical
Minimum Maximum Minimum Maximum
Metals (mg/kg dry weight; ppm)
Antimony
Arsenic
Cadmium
Chromium
Copper
Lead
Mercury
Nickel
Silver
Zinc
0.13
1.9
0.047
9.6
4.9
0.4
0.016
11
0.02
15
2.86
22
1.9
255
74
23
0.134
141
0.78
102
0.1
0.34
0.3
5.4
3.6
0.79
0.06
6.9
0.013
18.4
1,370
9,700
184
555
11,400
71,100
52
118
8.27
6,010
Organic Compounds (ug/kg dry weight; ppb)
Low molecular weight PAH
High molecular weight PAH
1,4-Dichlorobenzene
Hexachlorobenzene (HCB)
Hexachlorobutadiene
N-Nitrosodiphenylamine
4-Methylphenol
Phenol
Total PCBs
2.5
22
U5
U0.3
U1.3
U5
2
13
2.7
55
140
U160
U800
U820
U2,500
290
560
37
1.3
7.5
1
0.05
1
4
3
0.9
0.5
630,000
3,200,000
31,000
730
730
610
100,000
2,900
9,600
Conventional Sediment Variables (dry weight)
Total organic carbon (%)
Fine-grained material (%)
Sulfides (mg/kg; ppm)
0.19
7.4
2.2
2.69
88
31
0.06
2.7
1
29.4
95.5
7,610
a Ranges are based only on biological stations used in the evaluation of Puget
Sound AET. Higher concentrations for some chemicals have been detected in
sediment samples for which there are no biological data, including several
samples collected at depth. "U" indicates undetected in all samples over the
detection limit range shown; otherwise the minimum value is the lowest detected
concentration and the maximum value is the highest detected concentration (detection
frequencies are not indicated but are less that 100 percent for most chemicals
except metals).
b Reference areas in Puget Sound are generally removed from the direct influence
of contaminant sources in nonurbanized areas of the sound; almost all of these
stations are nonimpacted.
c Most data for nonreference areas are from industrialized urban embayments;
nonreference data include both nonimpacted and impacted stations.
24
-------
The amphipod mortality bioassay (Swartz et al. 1985) is an indicator of acute lethal
toxicity in whole sediments. Significant mortalities of the adult amphipod Rhepoxynius
abronius were determined by statistically comparing results of tests on sediments from
potentially impacted sites with those from a reference area. All comparisons were
made within studies (i.e., data were not compared among studies).
The oyster larvae abnormality bioassay (modified for sediments; Chapman and
Morgan 1983) is an indicator of acute sublethal toxicity in sediment elutriates. Significant
abnormalities in the larvae of the Pacific oyster Crassostrea gigas were determined by
statistically comparing results of tests on sediment elutriate samples from potentially
impacted sites with those from a reference area. Oyster larvae bioassay data were
available for 56 stations from Commencement Bay and Carr Inlet in Puget Sound.
Change in bacterial luminescence is an indicator of acute sublethal effects in
sediment elutriates (Williams et al. 1986), although the response may also reflect acute
lethal effects. The Microtox bioassay (Beckman Instruments 1982; Bulich et al. 1981)
using Photobacterium phosphoreum was applied in these tests. Significant Microtox
toxicity for samples from Commencement Bay was assessed by statistically comparing
the predicted decrease in luminescence in the presence of a 15-g sediment sample to
that observed for a 15-g sample from a reference area (Carr Inlet).
The following statistical procedures were applied to test results from the amphipod
bioassay:
All replicates from all stations in the reference area used for each study
were pooled, and a mean bioassay response and standard deviation were
calculated
Results from each potentially impacted site were then compared statistically
with the reference conditions using pairwise analysis
An Fmax-test (Sokal and Rohlf 1969) was used to test for homogeneity
of variances between each pair of mean values
If variances were homogenous, a t-test was used to compare the two
means
If variances were not homogenous, an approximate t-test (Sokal and Rohlf
1969) was used to compare means
Statistical significance was tested with a pairwise error rate of 0.05 to
ensure consistency among studies of differing sample sizes.
Oyster larvae bioassay results were treated similarly to the amphipod test results,
except that a t-test was always used to compare mean results. The following procedure
was used for Microtox results (Williams et al. 1986):
For each sample, decrease in luminescence for a 15-g sample was
predicted with a least-squares regression of the percent decrease in
luminescence versus the logarithm of the standardized sample dilution,
25
-------
where five serial dilutions of supernatants from samples of 13.0-26.4 g
were used as values for the independent variable
Statistical significance of the difference between the predicted luminescent
response and the response of control sediment was determined using a
t-test with a comparison-wise error rate of 0.001, which yielded an
experiment-wise error rate of 0.05 (Zar 1974) for the single Commencement
Bay study that was available.
Benthic Infauna Analyses--AET were also developed using field data on benthic
infauna abundances. Depressions in the abundances of indigenous benthic infauna,
unlike laboratory bioassays, are in situ measurements of chronic and/or acute effects in
sediments.
Significant depressions of the abundances of polychaetes, molluscs, crustaceans, and
total benthic infauna were determined separately by comparing values from potentially
impacted sites with those from reference areas. Comparisons were made within respective
studies unless appropriate reference data were not available for a particular study. In
those cases, comparisons were made among studies. Reference data for each potentially
impacted site were categorized so that comparisons were made with samples collected
during the same season, at a similar depth, and whenever possible, in sediments with
similar particle size characteristics (i.e., percentage of particles <64 um) as those of
the potentially impacted site. In this manner, comparisons were stratified by three of
the major natural variables known to influence the abundance and distribution of
benthic macroinvertebrates.
The AET approach does not require the analysis of benthic infaunal data at any
particular taxonomic level, but the data discussed in this report apply to higher level
taxa only. As discussed by Beller et al. (1986; Appendix H), higher level taxa were
used initially in the development of AET values for two major reasons. First, because
the AET approach is based on pair-wise statistical comparisons with reference conditions,
the benthic taxa must either be abundant enough or have a low enough variance to
allow major depressions in abundance to be discriminated statistically. These criteria
were best met by use of higher level taxa abundances. Second, comparisons with
bioassay results (i.e., amphipod mortality and oyster larvae abnormality) suggested that
benthic comparisons based on higher taxa were as sensitive as the bioassays in identifying
problem sediments, although different species may differ widely in their sensitivity to
individual chemicals present as a complex mixture in contaminated sediments.
Use of higher level taxa does not allow compensatory shifts in species abundances
to be evaluated explicitly within each higher level taxon, but does allow an evaluation
of the net effects of such shifts on the total abundance of each higher level taxon.
Use of higher level taxa also does not allow impacts on pollution-sensitive indicator
species to be evaluated explicitly. Such species are frequently characterized by relatively
low abundances and high variability and, therefore, are not always amenable to the
determination of statistically significant reductions in abundance even when they are
considered explicitly.
In a limited test conducted using species-level data from Commencement Bay in
Puget Sound (Beller et al. 1988), 10 species or genera were sufficiently abundant to
enable statistical analysis of the benthic data. These species-level benthic AET were
26
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similar in magnitude to higher taxa benthic AET (generally within a factor of two)
although they were based on considerably fewer data.
Stations tested for benthic infaunal abundances were evaluated for statistically
significant benthic depressions as follows:
AH abundances were Iog10-transformed
All replicates from each set of reference conditions were pooled, and a
mean and standard deviation were calculated for each of the four benthic
groups (i.e., total benthos, Polychaeta, Mollusca, and Crustacea)
The Iog10-transformed mean abundance of each benthic group at each
potentially impacted site was then treated as described for the amphipod
bioassay results (i.e., pairwise comparisons by the Fmax-test followed by
the t-test or approximate t-test).
Chemical Data
Chemical measurements of sediments are particularly useful for identifying specific
problem chemicals, for comparing historical sediment concentrations with existing sediment
quality values in the absence of biological data or for developing new sediment quality
values, and for identifying the potential sources of contaminating chemicals. The
chemical data available in Puget Sound for different studies have not all been generated
using the same analytical method or laboratory, but a general quality assurance review
has been conducted to assess their applicability for development of sediment quality
values. This general review is described by Seller et al. (1986) and was carried out in
three basic steps:
All available data sets were reviewed for synoptic collection of data
(i.e., matched chemical and biological measurements at each station),
and only matched chemical and biological data sets were considered
further. [Note: a matched data set was defined as one for which
toxicity data were collected on the same sediment homogenate used for
sediment chemistry, and replicate benthic infaunal samples were collected
at the identical station location and time, or at nearly the same time,
as sediment chemistry samples.]
Each data set was reviewed for documentation of quality assurance
methods and summaries of quality assurance review (such documentation
was typically provided in the reports in which the data were presented)
Data were subjected to a more detailed review that focused on issues
related to data comparability.
Overall, matched data were considered to provide the most reliable basis for
deriving or validating sediment quality values with site-specific biological field data.
Matched data sets were used to reduce the possibility that uneven (spatially variable)
sediment contamination could result in associating biological and chemical data that are
based on dissimilar sediment samples. Because the toxic responses of stationary organisms
(e.g., bioassay organisms confined to a test sediment, or infaunal organisms largely
27
-------
confined to a small area) were assumed to be affected by direct association with
contaminants in the surrounding environment, it was considered essential that chemical
and biological data be collected from nearly identical subsamples from a given station.
In the quality assurance review of chemical data, analytical techniques, detection
limits, and the chemical scope of contaminants analyzed (e.g., ionizable and nonionic
semivolatile organic compounds, metals, volatile organic compounds) were assessed and
summarized. The availability of a wide diversity of chemical data increases the probability
that toxic agents (or chemicals that covary in the environment with toxic agents) can
be included in interpreting observed biological impacts.
AET were developed for over 60 chemicals frequently detected in the environment,
including 16 PAH; several alkylated PAH and related nitrogen-, sulfur-, and oxygen-
containing heterocycles; polychlorinated biphenyls (PCBs, reported as total PCBs); 5
chlorinated benzenes; 6 phthalate esters; 3 chlorinated hydrocarbon pesticides; phenol
and 4 alkyl-substituted and chlorinated phenols; and 11 metals and metalloids. Data for
other miscellaneous chemicals that were less frequently detected or analyzed for were
also evaluated for their potential use in developing AET (e.g., resin acids and chlorinated
phenols that have recently been measured in selected sediments from Everett Harbor,
an area influenced by pulp and paper mill activity).
AET were developed for chemical concentrations normalized to sediment dry
weight and sediment organic carbon content (expressed as percent of dry weight sediment).
Using a 188-sample data set, AET were also developed for data normalized to fine-grained
particle content (expressed as the percent of silt and clay, or <64-um particulate
material, in dry weight of sediment). These latter AET values did not appear to offer
advantages in predictive reliability over the more commonly used dry weight and TOC
normalizations (Beller et al. 1986) and will not be discussed here.
Guidelines for Data Treatment
Before generating AET values, options were developed to address the following
factors that can affect AET uncertainty (in addition to factors discussed previously, such
as interactive effects and unmeasured chemicals):
Low statistical power and Type I statistical error in biological tests
Distributions of chemical concentrations (i.e., ranges and continuity of
concentrations)
Chemical analysis variability
Anomalous stations with relatively high chemical concentrations but without
statistically significant biological effects (possibly relating to bioavailability
and matrix effects).
Discussion of these options for biological or chemical analyses is presented in the
following sections.
28
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Bioassay DataSeveral modifications were adopted to improve the consistency of
the results among the various studies pooled for amphipod bioassay results. Similar
modifications were not made for the oyster larvae abnormality bioassay and the Microtox
bioassay because each of these indicators is represented by only a single study area in
the database used to generate AET.
The first modification addressed the level of significance at which pairwise comparisons
between impacted and reference sites were judged significant. A level of P<0.05 pairwise
was consistently used for all comparisons between stations, instead of using an experiment-
wise error rate that would result in variable alpha levels for pairwise station comparisons
depending on the sample size of different studies [see Appendix C of Barrick et al. (1988)].
The second modification considered screening criteria and power analyses for the
amphipod tests conducted in the Elliott Bay and Everett Harbor surveys conducted by
PSEP [discussed in detail in Appendix C of Barrick et al. (1988)]. This modification
resulted in the exclusion of seven potentially nonimpacted stations for which there was
inadequate power to distinguish significant effects relative to reference conditions.
The excluded stations were Stations DR-05, DR-08, EW-03, and NS-04 in Elliott Bay,
and Stations EW-14, SD-02, and SR-07 in Everett Harbor. Impacted stations were
defined as those that exhibited statistically significant mortality (P<0.05) relative to
reference conditions and exceeded 25 percent mortality (used for this study as a minimum
level of concern).
Benthic Infauna Analyses--Power analyses have not been conducted for benthic
infaunal data used to develop AET in Puget Sound. In lieu of a power analysis, and
analogous to the amphipod bioassay guideline, a guideline was developed to ensure that
benthic effects were of sufficient magnitude to be of regulatory concern as adverse
impacts and to be discriminated statistically in most cases. Thus, only significant
effects (P<0.05) that also exceeded a 50-percent reduction in major taxa abundance
were considered impacts. This guideline was derived partly from consideration of the
natural variability of benthic infauna in relatively undisturbed environments of Puget
Sound. Based on a summary of data from Lie (1968), Nichols (1975), and Word et al.
(1984) in Tetra Tech (1987), the abundances of selected major taxa (Polychaeta, Mollusca,
Crustacea) and total infauna may vary seasonally by roughly a factor of two (i.e.,
lowest mean abundances are roughly 50 percent of the highest mean abundances). In
most cases, >50 percent reductions in mean abundance can be detected statistically
(P<0.05), whereas <30 percent reductions cannot be detected (P»0.05). Finally, the
guideline of 50 percent reduction in benthic infauna abundances provided a level of
environmental protectiveness with a reasonable balance between underprotection due to
tolerance of major effects and overprotectiveness due to misclassification of nonimpacted
sites as impacted.
Chemical Data--All detected chemical data entered in the sediment quality database
after quality assurance review were included in AET calculations. These calculations
were based on biological effect stations that passed the biological screening criteria
summarized in the previous section.
Anomalous stations with relatively high chemical concentrations but without
statistically significant biological effects were considered to indicate the possibility of
unusual bioavailability or matrix effects. AET values based on such anomalous stations
29
-------
are not necessarily unreliable, but may be unrepresentative of Puget Sound conditions.
The inclusion of these anomalous stations in the generation of AET may increase AET
values solely in response to a localized condition. Alternatively, such stations may
simply indicate the need for additional data to confirm an increase in AET values that
is representative of regional environmental conditions.
In recent updates of AET, an option was implemented to exclude anomalous chemical
data from AET calculations until they could be confirmed (i.e., by another nonimpacted
station with chemical concentrations within a factor of 3 of the currently anomalous
station) [for more detailed discussion see Appendix C of Barrick et al. (1988)]. The
purpose of this option is to reduce the possibility that Puget Sound AET might be set
based on nonrepresentative data for exceptional chemical matrices (e.g., slag, coal) or
unusual biological conditions (e.g., extremely tolerant species under localized conditions).
For the amphipod bioassay, this procedure affected 8 of the 296 amphipod stations
that and resulted in changes to the AET for nine chemicals where the ratio of the
anomalous station to the nonimpacted station with the next highest concentration
ranged from 3.2 to 14. For benthic infauna, this procedure affected 4 of 206 benthic
stations and resulted in changes to the AET for eight chemicals [including high molecular
weight PAH (HPAH) as a class) where the ratio of the anomalous station to the nonimpacted
station with the next highest concentration ranged from 3.0 to 20. By implementing
this option, the sensitivity of the amphipod bioassay and benthic infauna AET each
increased by 11 percent, yielding values of 58 and 75 percent, respectively. Data
currently identified as anomalous will be reevaluated if and when confirming data
become available.
VALIDATION TEST METHODS
The reliability of AET generated from Puget Sound data was evaluated with tests
of sensitivity and efficiency (defined in Section 2). Tests of the sensitivity and efficiency
of the AET approach were carried out in several steps, as described below:
The chemical database was subdivided into groups of stations that were
tested for the same biological effects indicators.
Specifically, all chemistry stations with associated amphipod bioassay data were grouped
together (287 stations), all chemistry stations with associated benthic infaunal data
were grouped together (201 stations), all chemistry stations with associated oyster
larvae bioassay data were grouped together (56 stations), and all chemistry stations
with associated Microtox bioassay data were grouped together (50 stations). Stations
with more than one biological indicator were included in each appropriate group.
The stations of each group were classified as impacted or nonimpacted
based on the appropriate statistical criteria (i.e., Fmax-tests and t-tests
at alpha = 0.05).
Several tests of reliability were conducted at this point:
Test 1 - AET (dry weight) were generated with the entire Puget Sound
database available in 1988 (see Table 1 for the distribution of samples for
individual indicators) and were then tested against the same database for
30
-------
each biological indicator. Stations predicted to have a particular biological
effect (i.e., stations with one or more chemicals exceeding AET for the
biological indicator) were compared to those stations known to have the
predicted biological effect. This test provides a useful assessment of sensitivity
but results in 100 percent efficiency by definition (i.e., AET are defined such
that all stations with chemical concentrations above AET are biologically
impacted). This test directly assesses, for data available in 1988, the number
of biologically impacted stations that the AET approach could not account
for with any chemicals (e.g., as a result of interactive effects or unmeasured
chemicals; see Section 2, Interpretation of AET).
Test 2 - The test described above was repeated in two parts: (a) using
TOC-normalized AET for nonionic organic compounds and dry weight-normalized
AET for all other compounds (i.e., ionizable organic compounds, metals, and
metalloids); and (b) using TOC-normalized data for all chemicals. Test 2
allowed for a posteriori evaluation of the relative success of dry weight and
TOC normalization for nonionic organic chemicals.
Test 3 - Because the efficiency of the AET based on the entire Puget
Sound database is 100 percent by constraint (as in Tests 1 and 2), predictive
efficiency was estimated by the following procedure. For each biological
indicator, a single station was sequentially deleted from the total database,
AET were recalculated for the remaining data set, and biological effects were
predicted for the single deleted station. The predictive efficiency was then
the cumulative result for the sequential deletions of single stations. For
example, the 287-sample database for amphipod bioassay results can be used
to provide a 286-sample independent database for predicting (in sequence)
effects on all 287 samples.
Test 4 - In this test, independent data sets were used to generate and
test AET to confirm the sensitivity and efficiency measurements in Tests 1 and
3. AET (dry weight) generated in 1986 with 188 stations from diverse
geographic regions in Puget Sound were later tested with an independent set
of 146 Puget Sound stations (from Blakely Harbor, Eagle Harbor, Elliott Bay,
Everett Harbor, and Port Susan). These 1986 AET are distinct from the 1988
AET discussed in Test 1. Results were also compiled for comparisons of the
1986 AET to the entire database (i.e., including stations used to calculate
these AET; hence, this latter test is not completely independent but provides
a comparison for the identical total number of stations used in Test J).
Details of these validation tests and other tests that have been conducted are reported
by Barrick et al. (1988) and Beller et al. (1986).
VALIDATION RESULTS AND DISCUSSION
Selected AET generated from the 334-station database are presented in Table 3
(dry weight-normalized) and Table 4 (organic carbon-normalized). The chemicals presented
in Tables 3 and 4 are among the most commonly measured and detected chemicals in
Puget Sound sediments. A complete list of 1988 AET used in validation tests is provided
in Appendix F in Barrick et al. (1988).
31
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TABLE 3. 1988 PUGET SOUND AET
FOR SELECTED CHEMICALS (normalized to dry weight)3
Chemical
Amphipod Oyster
AETb AETC
Benthic Microtox
AETd AETe
Metals (mg/kg dry weight; ppm)
Antimony
Arsenic
Cadmium
Chromium
Copper
Lead
Mercury
Nickel
Silver
Zinc
Organic Compounds (ug/kg dry weight;
Low molecular weight PAH
Naphthalene
Acenaphthylene
Acenaphthene
Fluorene
Phenanthrene
Anthracene
2-Methylnaphthalene
High molecular weight PAH
Fluoranthene
Pyrene
Benz(a)anthracene
Chrysene
Benzofluoranthenes
Benzo(a)pyrene
Indeno(l ,2,3-c,d)pyrene
Dibenzo(a,h)anthracene
Benzo(g,h,i)perylene
Chlorinated benzenes
1 ,3-Dichlorobenzene
1 ,4-Dichlorobenzene
1 ,2-Dichlorobenzene
1 >2,4-TrichIorobenzene
Hexachlorobenzene (HCB)
Total PCBs
~~~~^ -
^ ^ ^ ,^^.«_
200«
93
6.7
270*
1300*
660
2.1f
>140*
6.1f«
960*
ppb)
24,0008
2,400«
1,3008
2,000*
3,6008
6,900f8
13,000f8
1,9008
69,000f8
30,000f8
16,000f8
5,100f8
9,200f8
7,8008
3,0008
1,800*
540f8
I,400f8
>170
120h
>110h
51
130
3,100f8
~ .
i
700
9.6
-_
390
660
0.59
__
>0.56
1,600
5,200
2,100
>560
500
540
1,500
960
670
17,000
2,500
3,300
1,600
2,800
3,600
1,600
690
230
720
>170
120
50
64
230
1,100
1508
57h
5.1*
2608
5308
4508
2.18
>140e
>6.18
41Q8
13,000f8
2,7008
1,300*
7308
1,000*
5,400f8
4,400f8
1,4008
69,000f8
24,000f8
16,000f8
5,100f8
9,200f8
9,900f8
3,600^
2,600ft
970th
2,600^
>170
110h
50
22h
l,000h
~" .
700
9.6
390
530
0.41
_ __
>0.56
1,600
5,200
2,100
>560
500
540
1,500
960
670
12,000
1,700
2,600
1,300
1,400
3,200
1,600
600
230
670
>170
110
35
31
70
130
32
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TABLE 3. (Continued)
Chemical
Phthalates
Dimethyl phthalate
Diethyl phthalate
Di-n- butyl phthalate
Butyl benzyl phthalate
Bis(2-ethylhexyl)phthalate
Di-n-octyl phthalate
Phenols
Phenol
2-Methylphenol
4-Methylphenol
2,4-Dimethyl phenol
Pentachlorophenol
Miscellaneous Extractables
Benzyl alcohol
Benzoic acid
Dibenzofuran
Hexachlorobutadiene
N-Nitrosodiphenylamine
Volatile Organics
Tetrachloroethene
Ethylbenzene
Total xylenes
Pesticides
p,p'-DDE
p,p'-DDD
p,p'-DDT
Amphipod
AETb
> 1,4008
> 1,2008
l,400h
900«
>3,100
>2,10Q8
I,200f8
63
3,6008
72«
3608
8708
7608
1,7008
180h
48h
>210
>50
>160
15
43
>270«
Oyster
AETC
160
>73
1,400
>470
1,900
>420
420
63
670
29
>140
73
650
540
270
130
140
37
120
>6
Benthic
AETd
> 1,400*
200*
>5,100
900«
1 ,300h
6,200h
1,200
72g
1,8008
2108
6908
8708
650
700*
llh
28h
57h
10h
40h
9
168
34«
Microtox
AETe
71
>48
1,400
63
1,900
1,200
>72
670
29
>140
57
650
540
120
40
140
33
100
--
--
defined AET could not be established because there were
no "effects" stations with chemical concentrations above the highest concen-
tration among "no effects" stations. "--" indicates AET data not available.
b Based on 287 stations (including recent surveys in Eagle Harbor, Elliott Bay,
and Everett Harbor not included in the previous generation of 1986 AET).
c Based on 56 stations (all from Commencement Bay Remedial Investigation and
Blair Waterway dredging study); no additional stations added since 1986.
33
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TABLE 3. (Continued)
d Based on 201 stations (including recent surveys in Eagle Harbor, Elliott Bay,
and Everett Harbor not included in the previous generation of 1986 AET).
e Based on 50 stations (all from Commencement Bay Remedial Investigation); no
additional stations added since 1986.
f The value shown exceeds AET established from Commencement Bay Remedial
Investigation data (Barrick et al. 1985) because of addition of Puget Sound data
presented in Beller et al. (1986).
8 The value shown exceeds AET presented in Beller et al. (1986) because of
addition of Puget Sound data from the Eagle Harbor, Elliott Bay, or Everett
Harbor surveys.
h The value shown is less than AET presented in Beller et al. (1986) because
of the exclusion of chemically anomalous stations from the AET dataset and the
application of power analyses to assess significantly impacted stations (P<.05)
(see text and Barrick et al. 1988).
34
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TABLE 4. 1988 PUGET SOUND AET FOR
SELECTED CHEMICALS (normalized to total organic carbon)a
Amphipod Oyster Benthic Microtox
Chemical AETb AETC AETd AETe
Nonionic Organic Compounds (mg/kg organic carbon; ppm)
Low molecular weight PAH 2,200 370 780 >530
Naphthalene 220 99 170 >170
Acenaphthylene 66 >27 66 >27
Acenaphthene 200 16 57 >57
Fluorene 360 23 79 >71
Phenanthrene 690 120 480 >160
Anthracene 1,200 >79 220 >79
2-Methylnaphthalene >120 --- 64
High molecular weight PAH 5,300 960 7,600 1,500
Fluoranthene 3,000 160 1,200 >190
Pyrene 1,000 >210 1,400 >210
Benz(a)anthracene 270 110 650 >160
Chrysene 460 110 850 >200
Benzofluoranthenes 450 230 1,500 >430
Benzo(a)pyrene 210 99 > 1,300 >140
Indeno(l,2,3-c,d)pyrene 88 33 900 >87
Dibenzo(a,h)anthracene 47 120 89 33
Benzo(g,h,i)perylene 78 31 > 1,200 >67
Chlorinated benzenes
1,3-Dichlorobenzene >15 >15 >15 >15
1,4-Dichlorobenzene 9 3.1 16 >16
1,2-Dichlorobenzene >5.8 2.3 2.3 2.3
1,2,4-Trichlorobenzene 1.8 2.7 --- 0.81
Hexachlorobenzene (HCB) 4.5 9.6 0.38 2.3
Total PCBs 190 >46 65 12
Phthalates
Dimethyl phthalate 53 >22 53 >19
Diethyl phthalate >110 >5.3 61 >5.3
Di-n-butyl phthalate 260 260 1,700 220
Butyl benzyl phthalate 42 >9.2 64 4.9
Bis(2-ethylhexyl)phthalate 78 60 60 47
Di-n-octyl phthalate 58 >57 4,500
35
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TABLE 4. (Continued)
Chemical
Miscellaneous Extractables
Dibenzofuran
Hexachlorobutadiene
N- nitrosodipheny lamine
Volatile Organics
Tetrachloroethene
Ethylbenzene
Total xylenes
Pesticides
p,p'-DDE
p,p'-DDD
p,p'-DDT
lonizable Organic Compounds (mg/kg
Amphipod
AETb
>170
6.2
>11
>22
>3.8
>12
0.81
2.2
>16
organic carbon;
Oyster
AETC
15
11
>11
>22
>3.8
>12
--
--
ppm)
Benthic
AETd
58
6.9
11
>22
>3.8
>12
0.31
1.0
3.7
Microtox
AETe
>58
3.9
>11
>22
>3.8
>12
Phenols and Miscellaneous Extractables
Phenol
2-Methylphenol
4-Methylphenol
2,4-Dimethyl phenol
Pentachlorophenol
Benzyl alcohol
Benzoic acid
Metals (mg/kg organic carbon; ppm)
Antimony
Arsenic
Cadmium
Chromium
Copper
Lead
Mercury
Nickel
Silver
Zinc
440
3.1
780
6.5
24
73
>170
>55,000
32,000
1,100
> 150,000
100,000
110,000
210
>4 1,000
170
>39
3.1
37
>1.3
>11
5.0
>170
3,300
88,000
1,200
49,000
66,000
210
>100
210,000 >200,000
>140
10
250
2.6
66
>73
>170
5,500
4,400
580
65,000
13,000
18,000
120
31,000
490
48,000
33
>10
81
0.63
>11
5.0
>170
3,300
88,000
1,200
48,000
66,000
77
100
>200,000
36
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TABLE 4. (Continued)
a ">" indicates that a defined AET could not be established because there were
no "effects" stations with chemical concentrations above the highest concen-
tration among "no effects" stations (normalized to TOC). "--" indicates AET
data not available.
b Based on 287 stations (including recent surveys in Eagle Harbor, Elliott Bay,
and Everett Harbor not included in the previous generation of 1986 AET).
c Based on 56 stations (all from Commencement Bay Remedial Investigation and
Blair Waterway dredging study); no additional stations added since 1986.
d Based on 201 stations (including recent surveys in Eagle Harbor, Elliott Bay,
and Everett Harbor not included in the previous generation of 1986 AET).
e Based on 50 stations (all from Commencement Bay Remedial Investigation); no
additional stations added since 1986.
37
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Results of validation tests 1 through 4 are summarized in Table 5. Using dry
weight-normalized AET calculated from all available data (Test 1), sensitivity ranged
from 58 to 93 percent, depending on the biological indicator, and efficiency was 100
percent (100 percent efficiency is attained by definition when AET are generated and
tested with the same data set of nonimpacted stations). The sensitivity for dry-weight
AET in Test 1 was largely confirmed by Tests 3 and 4, which relied on independent
data sets (Table 5; sensitivity ranged from 57 to 93 percent). For independent data
sets, efficiency of dry weight AET generally ranged from 55 to 75 percent (except
Microtox AET Test 3, which was 37 percent efficient).
For AET sets in which nonionic organic chemical concentrations were normalized to
TOC (and other chemicals normalized to dry weight; see Test 2), sensitivity ranged
from 55 to 77 percent and efficiency was 100 percent by constraint. A more detailed
analysis of the results of these and other validation tests is presented by Barrick et al.
(1988). Only two aspects of these results are discussed in detail below:
Characteristics of biologically nonimpacted stations not predicted by AET
The performance of dry weight AET vs. that of TOC-normalized AET
(Test 1 vs. Test 2).
Characteristics of Biologically Impacted Stations Predicted as Nonimpacted by AET
The purpose of this section is to identify the characteristics of biologically impacted
stations for which no identified chemical exceeded the AET for that biological indicator.
In this case, the results from Test 1 are being considered. In the 334-station database,
biological effects were found at 49 amphipod bioassay or benthic infauna stations at
which no chemical concentration exceeded a 1988 AET. These incorrect predictions
included 29 of 287 stations for the amphipod mortality bioassay (Table 6) and 25 of 201
stations for effects on benthic macroinvertebrate communities (Table 7). Both kinds of
effects were found at five of the impacted stations that were not predicted as impacted
by AET. Chemical and biological data for each of these stations were reviewed to
assess possible reasons for the incorrect predictions including the following:
The indicated adverse biological effect resulted from factors other than
toxic chemical exposures (e.g., physical disruption, grain size distribution)
Unidentified chemicals accounted for the sediment toxicity
High chemical detection limits precluded an assessment of whether the
AET was exceeded
The biological effect was incorrectly classified as significant because of
a Type I statistical error.
Amphipod Bioassay Stations--DeWitt et al. (1986) have shown that elevated mortality
can result in the amphipod mortality bioassay by exposing test organisms to sediments
having a high percentage of fine-grained material. These responses were found to
occur in the absence of apparent chemical contamination and were thought to result
from the physical characteristics of the sediment or some other natural variable that
38
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TABLE S. SENSITIVITY AND EFFICIENCY RESULTS FOR
VALIDATION TESTS CONDUCTED WITH PUGET SOUND AET
{normalized to dry weight (DW) or total organic carbon (TOC)|
Validation Testa
and AET Dataset
Number of
Stations
Evaluated Sensitivity
Overall
Efficiency Reliability
Benthic Infaunal Abundance
1: 1988 AET (DW)
2x 1988 AET (mixed DW/TOC)
2b: 1988 AET (TOC)
3: Independent AETC (DW)
4a: 1986 AET (DW); independent data
4b: 1986 AET (DW); all data
1: 1988 AET (DW only)
2a: 1988 AET (mixed DW/TOC)
2b: 1988 AET (TOC only)
3: Independent AETC (DW)
4a: 1986 AET (DW); independent
4b: 1986 AET (DW); all data
1: 1986 AETd (DW only)
2a: 1986 AET (mixed DW/TOC)
2b: 1986 AET (TOC only)
3: Independent AETC (DW)
4: not applicable*3
201
201
201
201
iata 109
201
Amphipod
287
287
287
287
data 146
287
75% (81/108)
77% (83/108)
76% (82/108)
75% (81/108)
83% (59/71)
76% (82/108)
Mortality Bioassay
58% (62/106)
55% (58/106)
45% (48/106)
57% (60/106)
68% (36/53)
56% (59/106)
100% (81/81)b
100% (83/83)b
100% (82/82)b
72% (81/112)
75% (59/79)
82% (82/100)
100% (62/62)b
100% (58/58)b
100% (48/48)b
67% (60/90)
55% (36/66)
69% (59/86)
Microtox Bioassay
50
50
50
50
93% (27/29)
93% (27/29)
83% (24/29)
93% (27/29)
100% (27/27)b
100% (27/27)b
100% (24/24)b
61% (27/44)
87% (174/201)
88% (176/201)
87% (175/201)
71% (143/201)
71% (77/109)
78% (157/201)
85% (243/287)
83% (239/287)
80% (229/287)
74% (211/287)
68% (99/146)
74% (213/287)
96% (48/50)
96% (48/50)
90% (45/50)
62% (31/50)
Oyster Larvae Abnormality
1:
2a:
2b:
3:
4:
1986 AETd (DW only)
1986 AETd (mixed DW/TOC)
1986 AET (TOC only)
Independent AETC (DW)
not applicable11
56
56
56
56
88%
88%
71%
88%
(15/17)
(15/17)
(12/17)
(15/17)
100%
100%
100%
37%
(15/15)b
(15/15)b
(12/12)b
(15/41)
96%
96%
91%
50%
(54/56)
(54/56)
(51/56)
(28/56)
See text (Validation Test Methods) for a complete description of the following tests:
Test 1: Dry weight-normalized AET generated and tested using the same database of
nonimpacted and impacted stations (note: the concentration at which an AET
value is set is determined only by nonimpacted stations).
39
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TABLE 5. (Continued)
Test 2: TOC-normalized AET generated for nonpolar, nonionic organic compounds and dry
weight-normalized AET generated for the remaining chemicals (Test 2a) or TOC-
normalized AET calculated for all chemicals (Test 2b). Predictions tested against
the same database of nonimpacted and impacted that was used to generate the AET.
Test 3: Dry weight-normalized AET generated independently of each station used to test
predictions (see footnote c and text for description of iterative procedure used).
Test 4: Dry weight-normalized AET generated in 1986 using approximately half of the
amphipod bioassay and benthic infauna stations now available in 1988. Predictions
tested using the remaining independent stations only (Test 4a) or all stations (i.e.,
the stations used to calculate AET plus the remaining independent stations).
b By definition, efficiency is 100 percent because all Puget Sound stations for each indicator
were included in the calculation of these AET.
c Cumulative results for (1) deleting a station from the AET database; (2) recalculating AET
using remaining stations; (3) predicting effects at deleted station; (4) restoring the deleted
station to the AET database; (5) repeating for each station in the database (see text for
discussion of why this test affects efficiency more than sensitivity).
d No new data were available to update the 1986 AET for oyster larvae and Microtox bioassays;
validation tests were conducted using the 1986 AET although more chemicals (e.g., including
tentatively identified organic compounds and conventional sediment variables such as TOC,
grain size, sulfides) were used for these tests than used previously by Beller et al. (1986).
40
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TABLE 6. CHARACTERISTICS OF STATIONS AT WHICH SIGNIFICANT
AMPHIPOD MORTALITY WAS FOUND BUT NO EFFECTS WERE PREDICTED
Embayment Surveya
Elliott Bay EBCHEM
Sinclair Inlet EIGHTBAY
Case Inlet
Dabob Bay
Samish Bay
Everett Harbor
Bellingham Bay
Everett Harbor EVCHEM
Everett Harbor EVERETT1
Station3
DR-14
EW-10
KG-02
KG-03
KG-09e
KG- 11
NH-02
NH-09
NH-11
NS-08e
WW-08e
SC-08
SC-17
SC-18
CS-01
CS-11
CS-15
CS-17
DB-07
DB-15
SM-03
SM-07
SM-20
EV-02
EV-11
BH-05
BH-23
NG-06
EV-24
Percent
Mortality15
32
58
37
27
33
32
45
58
55
82
41
38
26
32
28
28
43
41
26
36
47
25
31
29
26
34
58
43
40
Key Distinguishing Factorsc>d
% fines = 80.6
% fines = 80.3; DL
DL ( 6% fines)
DL (49% fines)
DL (51% fines)
DL ( 8% fines)
DL (31% fines)
DL (11% fines)
no obvious factors (29% fines)
% fines = 83.9; DL
DL (58% fines)
% fines = 89.8; DL
% fines = 78.2; DL
% fines = 77.8; DL
% fines = 89.4; DL
DL (39% fines)
% fines = 81.3; DL
% fines = 78.1; DL
DL (49% fines)
% fines = 89.7; DL
% fines = 80.9; DL
% fines = 84.9; DL
% fines = 87.2; DL
% fines = 83.1; DL
no obvious factors (69% fines)
% fines = 96.6; DL
% fines = 95.3; DL
no obvious factors (7% fines)
few chemicals measured (63% fines)
a Surveys listed in Table 1; see Appendix B in Barrick et al. (1988) for station locations.
b Percent mortality observed at each anomalous station.
c Percent fine-grained material (i.e., <63 um).
d DL = Detection limits of at least one chemical exceeded the 1988 amphipod bioassay
AET for that chemical.
e Station predicted by 1986 Puget Sound amphipod AET but not by 1988 AET.
41
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TABLE 7. CHARACTERISTICS OF STATIONS AT WHICH SIGNIFICANT
BENTHIC EFFECTS WERE FOUND BUT NO EFFECTS WERE PREDICTED
Embayment Survey*
Elliott Bay EBCHEM
Everett Harbor EVCHEM
Eagle Harbor EHCHEM
Alki Pt. ALKI
Elliott Bay TPPS3AB
Station*
AB-03
KG-07d
KG-086
KG- 11
MG-01
MG-02
MG-03
MG-04
NH-01*
NH-02e
NH-11
NS-08e-f
WW-01
WW-03
WW-086
WW-176
SD-01
EH-02
EH-03
AP-04
EB-38
(3/15/82)
EB-38
(7/15/82)
WP-03
(7/15/82)
WP-08
(7/15/82)
WP-16
(3/15/82)
Taxonb
P
M
M
M
P
P
P
P
M
M
P
T,M,C
M
T,P,M,C
M,C
M
T,P,M,C
M
T,M
M
M
T,P,M
P
M
P
Key Distinguishing Factorsc'd
% coarse = 95.3; DL
% coarse = 83.3; DL
% coarse = 90.8; DL
% coarse = 92.5; DL
DL (25% coarse)
% coarse = 95.5; DL
% coarse = 77.5; DL
DL (14% coarse)
% coarse = 81.1; DL
DL (69% coarse)
% coarse = 71.3; DL
DL; (16% coarse)
no obvious factors (60% coarse)
% coarse = 93.4
no obvious factors (42% coarse)
% coarse = 94.7
% coarse = 95.5
% coarse = 89.3; DL
% coarse = 92.1; DL
% coarse = 95.9
no obvious factors (13% coarse)
no obvious factors (38% coarse)
% coarse = 92.4; DL
% coarse = 92.6
no obvious factors (4% coarse)
a Surveys listed in Table 1; see Appendix B in Barrick et al. (1988) for station locations.
b Taxa showing significant depressions. T = total taxa, P = Polychaeta, M = Mollusca,
C = Crustacea.
c Percent coarse-grained material (i.e., >63 um).
d DL = Detection limits of at least one chemical exceeded proposed benthic infauna
AET for that chemical.
e Station predicted by 1986 Puget Sound amphipod AET but not 1988 AET.
f Station NS-08 is located near the Pier 91 naval dock. Tributyltin contamination is
possible in this area but has not been tested.
42
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correlated with the physical characteristics. In the Puget Sound database, significant
amphipod mortality was associated with 35 of 74 stations (47 percent) with a relatively
high percentage (approximated as >75 percent) of fine-grained sediment. In contrast,
significant mortality was associated with less than 30 percent of the remaining stations.
Sixteen of the 29 impacted amphipod bioassay stations (55 percent) that were not
predicted by AET were characterized by sediments having a relatively high percentage
of fine-grained material. In the Battelle (1985) survey (Table 6), 81 percent of the impacted
stations that were not predicted were consistent with this factor. A significant depression
in benthic infaunal abundance was found at only one of the 29 fine-grained stations
[Station NS-08 (Beller et al. 1988a)]. However, adequate benthic infaunal data were
not available at all amphipod bioassay stations [e.g., only amphipod bioassay data were
included from the Battelle (1985) survey].
Elevated detection limits precluded an assessment of whether one or more AET
were exceeded at nearly all of the impacted amphipod bioassay stations that were not
predicted. Aside from detection limit concerns or the possible presence of unmeasured
chemicals, no obvious factors account for the apparent incorrect predictions at 12 of
the 29 stations (41 percent). Most of these amphipod bioassay stations were found in
or near the mouth of the Duwamish River in Seattle, an industrial area contaminated
with a variety of chemical classes, suggesting that the biological effects may have resulted
from unmeasured chemicals or from interactive effects among the numerous chemicals
present at most of those stations.
Benthic Infauna Stations--The characteristics of benthic macroinvertebrate assemblages
are influenced, in part, by sediment grain size distribution. Coarse-grained sediments
may be suboptimal habitats for many benthic species because they are generally low in
organic content and are indicative of high-energy environments. Thus, the food supply
for benthic infauna may be limited, and organisms may have difficulty maintaining
burrows, tubes, or position in the shifting sediment. In the present study, 16 of the
25 impacted benthic infauna stations (64 percent) that were not predicted by AET were
characterized by sediments having a relatively high percentage (i.e., >70 percent) of
coarse-grained sediment. For example, the observed depression of benthic infaunal
abundance at Station SD-01 in Everett Harbor is potentially attributable to the location
of this station in a current-swept channel on the Snohomish River delta, rather than
toxic effects. Elevated detection limits precluded an assessment of whether one or
more AET were exceeded at nearly all of the impacted stations that were not predicted
(Table 7).
Aside from potential concerns over detection limits, there was no other obvious
factor that might explain apparent incorrect predictions at 9 of the 25 stations (36
percent). As discussed above for amphipod bioassay stations, most of these potentially
unexplained stations occurred in or near the mouth of the lower Duwamish River in
Seattle. Various dredging projects have occurred in this area and may have disturbed
benthic assemblages sufficiently to result in depressions of major taxa. However, detection
limits, unmeasured chemicals, or chemical synergism are the most likely factors at
these stations, especially considering that four of the five incorrectly predicted stations
at which both the amphipod bioassay and benthic infauna indicators were significant
were from this area [i.e., Stations KG-11, NH-02, NH-11, and WW-08 from Beller et al.
(1988a)]. The fifth such station (Station NS-08) is located near Pier 91 in Elliott Bay.
Potential (as yet untested) tributyltin contamination from historical naval ship operations
43
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may account for the substantial amphipod mortality and benthic infaunal depressions
observed at this station.
Although unmeasured chemicals or other factors may account for some of the
impacted stations that were not predicted by AET, sediment grain size appears to be a
dominant factor at the majority of these stations. The fact that fine-grained sediments
dominate such amphipod bioassay stations and that coarse-grained sediments dominate
such benthic infauna stations reinforces this conclusion. Only 17 percent of the impacted
amphipod bioassay stations that were not predicted had a relatively high percentage of
coarse-grained material, and only 16 percent of the impacted benthic infauna stations
that were not predicted had a relatively high percentage of fine-grained sediments. No
correction factor is recommended for grain size, other than matching reference area
sediments as closely as possible with sediments from the study site. The 1988 AET are
efficient with respect to not predicting effects for stations at which grain size or
associated factors may dominate over toxic effects.
Relative Performance of Dry Weight- and TOC-Normalized AET
An interesting result of validation tests with Puget Sound data was the roughly
equivalent predictive success of dry weight-normalized AET and organic carbon-normalized
AET (Table 5 and Figure 7). This finding was unexpected in light of a body of laboratory
bioassay and sorption data that strongly supports the use of TOC normalization for
nonionic organic chemicals. Possible explanations for the relative performance of dry
weight- and organic carbon-normalized AET are presented in this section.
Dry weight-normalization simply assumes that the overall burden of a contaminant
in sediment is a predominant factor influencing toxicity to exposed organisms (although
organic carbon content may be a secondary factor). Because dry weight-normalization
does not focus on any specific solid fraction of the sediment (e.g., organic matter, fine
particles), it essentially averages among sediment fractions in terms of sorptive affinity
and relationship to bioavailability. If specific sediment fractions consistently mediate
toxicity in most samples, then averaging across all sediment fractions potentially reduces
the representativeness of dry weight-normalized AET. Alternatively, if specific sediment
fractions do not consistently mediate toxicity in most samples, normalization to dry
weight may better account for the variability of contaminant-toxicity relationships
among environmental samples than normalization to these sediment fractions.
Organic carbon normalization assumes that organic matter in sediments is a generic
sink for nonionic organic contaminants and is a predominant factor influencing the
bioavailability and toxicity of these compounds to exposed organisms. Laboratory
bioassay and sorption studies provide a mechanistic rationale for organic carbon normal-
ization. Simply stated, bioavailability and toxicity of nonionic organic chemicals in
sediments appear to correspond to interstitial water concentrations, and, under equilibrium
conditions, the distribution of nonionic organic compounds between sedimentary organic
matter (represented by organic carbon content) and interstitial water should be constant
(and can be expressed as Koc). For sediments with a given bulk concentration of a
nonionic organic chemical, increases in organic carbon content should correspond to
proportional decreases in interstitial water concentrations of that chemical. Hence, as
sediment organic carbon content increases, toxicity "threshold" values expressed per
gram of bulk sediment should decrease. If contaminant concentrations are normalized
to organic carbon content, threshold values should be constant for that contaminant in
44
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all sediments regardless of organic carbon content. Thus, use of TOC-normalized data
could be expected to result in a more consistent estimation of sediment toxicity thresholds
than use of dry weight-normalized data for generation of AET for nonionic organic
compounds.
A study by Adams et al. (1985) illustrates the rationale for organic carbon normal-
ization. Adams et al. (1985) conducted a series of bioassays in which freshwater
midges Chironomus tentans) were exposed to water, sediments (with various levels of
organic carbon content), and food contaminated with Kepone. No-effect concentrations
based on total sediment Kepone concentrations increased in proportion to total organic
carbon content of sediments, whereas no-effect levels based on interstitial water
Kepone concentrations were relatively constant regardless of sediment concentration.
The authors suggested that no-effect concentrations should be based on interstitial
water concentrations and sediment organic carbon content, not on bulk sediment weight.
The AET approach is empirical and does not favor one mechanistic explanation
over any other but can operate whether one or a combination of assumptions is appropriate.
The interpretation of operative mechanisms is, for the AET approach, an a posteriori
inference based on the results of validation tests. For contaminated sediments in the
environment, organic carbon normalization might not offer advantages in predictive
success over dry weight normalization if the following hypotheses are applicable to
environmental sediment samples:
Sediment/interstitial water systems are not typically at equilibrium in
the environment as a result of impeded contaminant exchange
Sediment organic matter occurring in the environment does not have
uniform affinity for nonionic organic compounds.
These hypotheses are discussed further in the following sections.
Sediment-Water Contaminant ExchangeBased on the mechanistic rationale for organic
carbon normalization, an assumed advantage of TOC-normalized AET is the constant
relationship between sedimentary organic matter, interstitial water concentration, and
sediment toxicity that should exist under equilibrium conditions. Based in part on
evidence from laboratory studies, it is plausible that equilibrium could be difficult to
attain in the environment because of kinetic aspects of sorption/desorption processes.
The attainment of equilibrium requires a relatively rapid transfer of a contaminant between
various phases in a system. Studies of sorption/desorption have demonstrated that
attainment of equilibrium of a nonionic organic compound between sediment and aqueous
phases can take weeks, months, or longer (e.g., Karickhoff 1984, Karickhoff and Morris
1985b). The existence of reversible (rapidly exchangeable) and irreversible (highly
retarded) components of contaminant loadings in sediments has been postulated by
several investigators based on hysteresis in sorption/desorption isotherms or direct
observation of desorption kinetics (e.g., DiToro and Horzempa 1982; Karickhoff and Morris
1985b). In laboratory-spiked sediments studied by Karickhoff and Morris (1985b), one
half or more of the total sorbed contaminant concentration was irreversible. For
highly hydrophobic compounds and systems with high solids concentrations, the irreversible
fraction increased to >90 percent in some cases (Karickhoff and Morris 1985b). For
the irreversible component, the attainment of equilibrium distributions could be very
slow, on the order of years for highly hydrophobic compounds (i.e., relatively widespread
46
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contaminants such as PAH with five or more rings and PCB congeners with six or more
chlorine atoms) (Karickhoff and Morris 1985b).
Very few studies have been conducted with field-collected sediments to examine
the kinetic aspects of contaminant exchange between sediment and ambient water.
However, in diffusion studies with field-contaminated sediments, Fisher et al. (1983)
reported apparent diffusion coefficients for trichloro-, tetrachloro-, and pentachlorobiphenyls
that were one to three orders of magnitude lower than observed for laboratory-spiked
hexachlorobiphenyl (DiToro et al. 1985); the laboratory-spiked PCB congener appeared
to exhibit fully reversible behavior. DiToro et al. (1985) proposed that the low apparent
diffusion of PCB congeners observed by Fisher et al. (1983) could be explained by the
fact that 90 to 99.9 percent of the sediment loading of PCBs was irreversibly sorbed in
those field-collected sediments. Such a proportion of irreversibly sorbed contaminants
in the environment could result in considerable deviations from equilibrium conditions.
Relatively large and variable deviations from equilibrium in environmental samples
would result in considerable variability in the relationship between organic carbon
content and bioavailability or toxicity on a sample-by-sample basis, reducing the potential
advantage of TOC normalization.
Physical explanations for retarded sediment/water exchange of contaminants and
deviations from equilibrium include entrainment or trapping of contaminants in refractory
matrices such as fecal pellets (Karickhoff and Morris 1985a) and humic matter (Freeman
and Cheung 1981). In a study of sediments collected in Puget Sound, Prahl and Carpenter
(1983) observed that PAH were disproportionately concentrated in certain fractions of
refractory sedimentary organic matter (e.g., charcoal fragments and vascular plant
detritus, such as lignin). This disproportionality suggests that PAH may not have been
at equilibrium within the sediment phase or, alternatively, that different kinds of
organic matter may have different affinities for PAH.
The Uniformity of Organic MatterFor a given nonionic organic chemical, consistent
partitioning between organic matter and interstitial water in sediments from different
areas requires that organic matter have a consistent affinity for the chemical. A
number of studies indicate that organic matter can be considered uniform to a first
approximation, based on the derivation of single Koc values for ranges of sediments
and soils (e.g., Karickhoff 1984 and references therein). However, direct studies of the
associations of nonionic organic compounds with dissolved (Gauthier et al. 1987; Carter
and Suffet 1985) and particulate (Diachenko 1981) humic materials indicate that affinities
can vary considerably as a function of the source and properties of the organic matter.
For example, Koc values for pyrene in dissolved humic materials from various sources
differed by as much as an order of magnitude (Gauthier et al. 1987). The aromatic vs.
aliphatic character of organic matter has been related to binding affinity (Diachenko
1981; Gauthier et al. 1987) and is likely an important structural difference between
humic materials derived from terrestrial vs. marine sources (e.g., Hatcher et al. 1980,
1981) in estuarine sediments. Variability in organic matter alone may not account for
the roughly equivalent performance of dry weight- and organic carbon-normalized AET,
as variability within the sedimentary pool of organic matter does not necessarily favor
normalization to bulk sediment rather than bulk organic carbon.
47
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4. APPLICATION OF AET IN PUGET SOUND
SEDIMENT MANAGEMENT PROGRAMS
The reliability of the AET approach (particularly AET normalized to dry weight
for a broad range of chemicals) at predicting biological effects indicates its potential
utility as a tool for sediment quality management. Uses for which the AET approach
is well suited include:
Determination of the extent and relative priority of potential problem
areas to be managed
Identification of potential problem chemicals in impacted sediments and,
as a result, potential sources of contaminants
Prioritization of laboratory studies for determining cause-effect relationships
With appropriate safety factors or other modifications, use in regulatory
programs and in screening decisions on the need for further chemical
or biological testing of sediments.
Proposed regulations for sediment contamination are currently under review in
Puget Sound and may include use of AET to develop sediment standards. These regulations
are the culmination of cooperative planning and scientific investigations that were
initiated by several federal and state agencies in the early and mid-1980s, including:
Commencement Bay Superfund Investigations
Puget Sound Dredged Disposal Analysis (PSDDA)
Urban Bay Toxics Action Program
Puget Sound Water Quality Authority (Authority) Management Plan.
Each program and particular application of the AET approach is described further
below. A key decision in many of these programs was to develop two sets of sediment
quality values, focusing separately on the sensitivity and efficiency concepts of reliability
discussed in Section 1 (see Figure 1). This management decision was made because it
was determined that none of the available approaches for developing sediment quality
values would result in 100 percent sensitive and 100 percent efficient values. For
these programs, direct biological testing is used to resolve the differences in predictions
of the two sets of sediment quality values (i.e., prediction of adverse biological effects
by highly sensitive sediment quality values, which at lower chemical concentrations are
not predicted by highly efficient sediment quality values).
48
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COMMENCEMENT BAY NEARSHORE/TIDEFLATS SUPERFUND INVESTIGATION
Commencement Bay is a heavily industrialized harbor in Tacoma, Washington.
Recent surveys have indicated over 281 industrial activities in the nearshore/tideflats
area. Comprehensive shoreline surveys have identified over 429 point and nonpoint
source discharges in the study area, consisting primarily of seeps, storm drains, and
open channels. Only 27 of the point sources were identified as NPDES-permitted
discharges. A remedial investigation under Superfund, started in 1983, revealed 25
major sources contributing to sediment contamination. The magnitude of sediment
contamination was characterized using chemical analyses and biological effects indicators.
Comparisons of chemical concentrations in various waterways of Commencement Bay
with concentrations in relatively uncontaminated areas, along with the presence of
measurable biological effects provided a basis for ranking problem areas. No single
chemical accounts for this contamination. Concentrations of several different chemicals
were found at greater than 1,000 times reference area concentrations, primarily in
sediment adjacent to major chemical manufacturing, pulp mill, shipbuilding and repair,
or smelter plant operations. Adverse biological effects were found in each of these areas.
During the course of the remedial investigation, the AET approach was developed
to assign values to sediment quality. For the Commencement Bay study, biological
effects included depressions in the number of individual benthic taxa, presence of
tumors and other abnormalities in bottomfish, and several laboratory toxicity tests
(amphipod mortality, oyster larvae abnormality, bacterial bioluminescence). At the
Commencement Bay site, AET are currently being used to evaluate cleanup alternatives.
Optional biological testing can be used by potentially responsible parties to appeal site-
specific predictions of adverse biological effects.
PUGET SOUND DREDGED DISPOSAL ANALYSIS
In 1985, PSDDA was initiated to develop environmentally safe and publicly acceptable
options for open-water unconfined disposal of dredged material. PSDDA is a cooperative
program conducted under the direction of the U.S. Army Corps of Engineers Seattle
District (Corps), EPA Region 10, Ecology, and the Washington Department of Natural
Resources (WDNR).
In 1988, PSDDA produced a management plan and an environmental impact statement
specifying procedures for disposal site management and evaluation of dredged material
and identifying recommended open-water unconfined disposal sites in central Puget
Sound. Ongoing activities of PSDDA are focused on designating sites for open-water,
unconfined disposal in south and north Puget Sound. AET were used by PSDDA as
tools to develop chemical-specific guidelines for evaluating the need for biological
testing of contaminated dredged material.
In PSDDA, a chemical screening level was established above which biological testing
would be required to determine the suitability of dredged material for unconfined,
open-water disposal. Above a higher maximum level of contaminant concentrations,
additional biological testing was considered unnecessary to determine that the dredged
material was unsuitable, although an extensive series of biological tests could be conducted
to demonstrate the suitability for unconfined, open-water disposal.
49
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URBAN BAY TOXICS ACTION PROGRAM
The national program for estuarine studies and pollution abatement is implemented
through EPA regional offices under the guidance of the Office of Marine and Estuarine
Protection (OMEP). Region 10, through the Office of Puget Sound, is responsible for the
development and implementation of the Puget Sound Estuary Program (PSEP). The
Urban Bay Toxics Action Program is a major component of PSEP, and was begun in
1984 by EPA's Office of Puget Sound and Ecology. Substantial participation has also
been provided by the Authority and other state agencies and local government. Major
funding and overall guidance for the program is provided by EPA/OMEP. The Urban Bay
Toxics Action Program consist of the identification of problem areas in urban bays
(predominantly based on sediment contamination), identification of potential sources,
development of an action plan for source control, and formation of an action team for
plan implementation.
In PSEP urban bay programs, AET are used in conjunction with site-specific
biological tests during the assessment of sediment contamination to define and rank
problem areas. Actions to date have focused on Elliott Bay, Everett Harbor, and Budd
Inlet adjacent to the cities of Seattle, Everett, and Olympia. Source control actions
are well underway, but sediment remediation has not yet begun at any of the sites.
PUGET SOUND WATER QUALITY MANAGEMENT PLAN
The Puget Sound Water Quality Management Plan (Plan) was published by the
Authority in 1987. The Plan presents programs and plans for 12 issue areas. The Plan
identifies the following goal for the contaminated sediments program: "To reduce and
ultimately eliminate adverse effects on biological resources and humans from sediment
contamination throughout the sound by reducing or eliminating discharges of toxic
contaminants and by capping, treating, or removing contaminated sediments." The
strategy to achieve this goal is:
To establish a quality standard that will classify sediments that cause
adverse biological effects
To implement soundwide controls on sources of contaminants causing
sediments to fail the classification criteria
To provide rules and sites for disposal of dredged material
To conduct remedial actions for existing areas of high sediment contamina-
tion levels.
The strategy to develop classification criteria requires Ecology to develop and adopt
regulations establishing criteria for identifying and designating sediments that have
adverse effects on biological resources or pose a significant health risk to humans.
Ongoing efforts to develop sediment quality standards are focused by the requirements
of the Authority's Plan toward producing legally enforceable tools for preventing
sediment contamination and managing contaminated sediment. Development of state
50
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sediment standards by Ecology in response to the Authority's Plan is described in the
following section.
PROPOSED STATE SEDIMENT QUALITY STANDARDS
Ecology is currently developing multiple categories of sediment management standards,
based in part on AET values. Development of these standards relies heavily on the
past and ongoing efforts described above and involves active participation by Ecology,
EPA, the Authority, WDNR, the Corps, and a variety of public interest groups. The
draft regulation currently under development affects only sediment in Puget Sound,
although the adopted regulation will be broadened, and modified as necessary, to include
the entire state at a future date.
Ecology has convened several public workshops in 1988 for interested parties such
as environmental and public interest groups, ports, industry, state and federal agencies,
local governments, and Indian tribes. In addition, a Sediments Advisory Group provides
technical and policy review of the standards development. Ecology will adopt the
regulations following formal public review processes beginning in January 1989. The
current schedule for adoption of standards and guidelines is outlined below:
Sediment Quality Standards
Effluent Particulate Limits
Standards for Unconfined
Disposal of Dredged Material
Standards for Confined Disposal
of Dredged Material
Sediment Remedial Action
Guidelines
Method for Ranking Contaminated
Sediment Sites
Inventory of Sites with
Adverse Effects
Priority List of Contaminated
Sites and Investigation Schedule
Draft by December 31, 1988
Final by June 30, 1989
Interim by July 30, 1988
Final by June 30, 1989
Central Puget Sound by September
1988; north and south Puget Sound
by September 1989
Interim by September 1989
Final by July 1990
Final by January 1991
By June 1, 1990
Initial inventory by
October 1, 1990
By December 31, 1990
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5. SUMMARY
Ideally, sediment quality values would be supported by a complete understanding of
the physical, chemical, and biological interactions that comprise a dynamic ecosystem.
However, extensive research is required to understand the complex relationships that
drive such a system. The near-term needs for enhanced regulation and environmental
protection in Puget Sound are not compatible with the probable long-term development
of sediment criteria based on such complete understanding. In Washington state, the
development of sediment quality values is viewed as an iterative process in which the
best available information is integrated into an appropriate management framework.
The sediment quality values that have been developed for Puget Sound using the
AET approach provide decision tools that have the following characteristics:
Developed empirically from field data in Puget Sound
Developed to provide chemical-specific values
Supported by a variety of biological indicators including acute lethal and
sublethal bioassays and in situ benthic infaunal analyses reflecting acute
and/or chronic effects
Driven by statistically significant adverse effects relative to Puget Sound
reference conditions
Supported by noncontradictory evidence of adverse effects within a
database incorporating approximately 300 samples from 13 embayments in
Puget Sound (including 287 amphipod bioassay stations, 201 benthic
infauna stations, 56 oyster larvae bioassay stations, and 50 Microtox
bioassay stations).
For this database, AET are from 85 to 96 percent reliable in predicting adverse
effects when they do occur and in not predicting adverse effects when none are observed.
Viewed as an environmental risk management tool, the application of AET in sediment
programs enhances the ability to characterize and clean up existing sediment contamination
and to prevent future contamination from occurring. The AET approach is currently
used in several regional programs and is proposed as the basis for developing state
sediment quality standards.
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6. REFERENCES
Adams, W.J., R.A. Kimerle, and R.G. Mosher. 1985. Aquatic safety assessment of
chemicals sorbed to sediments. pp. 429-453. In: Aquatic Toxicology and Hazard
Assessment: Seventh Symposium. American Society for Testing and Materials, Philadelphia,
PA.
Barrick, R., S. Becker, D. Weston, and T. Ginn. 1985. Commencement Bay nearshore/
tideflats remedial investigation. Final Report. Prepared by Tetra Tech, Inc. for Washington
Department of Ecology and U.S. Environmental Protection Agency. Tetra Tech, Inc.,
Bellevue, WA.
Barrick, R., H. Beller, and M. Meredith. 1986. Eagle Harbor Preliminary Investigation.
Final Report. Prepared by Tetra Tech, Inc. for Black & Veatch/Washington Department
of Ecology. Tetra Tech, Inc., Bellevue, WA.
Barrick, R., S. Becker, R. Pastorok, L. Brown, and H. Beller. 1988. Sediment quality values
refinement: 1988 update and evaluation of Puget Sound AET. Prepared by PTI Environ-
mental Services for Tetra Tech/U.S. Environmental Protection Agency Region 10, Office
of Puget Sound. PTI Environmental Services, Bellevue, WA.
Battelle 1985. Detailed chemical and biological analyses of selected sediment from
Puget Sound. Draft Final Report. U.S. Environmental Protection Agency Region 10,
Seattle, WA. 300 pp.
Battelle. 1988. Overview of methods for assessing and managing sediment quality.
Prepared for U.S. Environmental Protection Agency, Office of Water, Office of Marine
and Estuarine Protection, Washington DC. Battelle Ocean Sciences, Duxbury, MA. 30 pp.
Beckman Instruments, Inc. 1982. Microtox system operating manual. Carlsbad, CA.
Beller, H., R. Barrick, and S. Becker. 1986. Development of sediment quality values
for Puget Sound. Prepared by Tetra Tech, Inc. for Resource Planning Associates/U.S.
Army Corps of Engineers, Seattle District for the Puget Sound Dredged Disposal Analysis
program. Tetra Tech, Inc., Bellevue, WA.
Beller, H., R. Pastorok, S. Becker, G. Braun, G. Bilyard, and P. Chapman. 1988a.
Elliott Bay action program: analysis of toxic problem areas. Final Report. Prepared
for U.S. Environmental Protection Agency Region 10, Office of Puget Sound. PTI
Environmental Services and Tetra Tech, Inc., Bellevue, WA. July, 1988.
Beller, H., R. Barrick, L. Jacobs, and S. Becker. 1988b. Commencement Bay Nearshore/
Tideflats Feasibility Study: Development of sediment cleanup goals. Public Review
Draft. Prepared by PTI Environmental Services for Tetra Tech, Inc./Washington Department
of Ecology and U.S. Environmental Protection Agency, Region 10. PTI Environmental
Services, Bellevue, WA.
53
-------
Bulich, A.A., M.W. Greene, and D.L. Isenberg. 1981. Reliability of the bacterial lumi-
nescence assay for determination of the toxicity of pure compounds and complex effluent.
pp. 338-347. In: Aquatic Toxicology and Hazard Assessment: Proceedings of the
Fourth Annual Symposium. D.R. Branson and K..L. Dickson (eds). ASTM STP 737.
American Society for Testing and Materials, Philadelphia, PA.
Carter C.W., and I.H. Suffet. 1985. Quantitative measurements of pollutant binding to
dissolved humic materials compared with bulk properties of humic materials. Org.
Geochem. 8:145-146.
Chan, S., M. Schiewe, and D. Brown. 1985. Analysis of sediment samples for U.S.
Army Corps of Engineers Seattle harbor navigation project, operations and maintenance
sampling and testing of Duwamish River sediments. Draft Report. 15 pp. + appendices.
Chan, S. M. Schiewe, K. Grams, A. Friedman, R. Bogar, U. Varanasi, W. Reichert, P.O.
Plesha, S.J. Demuth, and D.W. Brown. 1986. East, West, and Duwamish Waterways
Navigation Improvement Project: physical/chemical/biological analyses of sediments
proposed for dredging. Final Report. Prepared by NOAA, National Marine Fisheries
Service for U.S. Army Corps of Engineers, Seattle District. 106 pp.
Chapman, P.M. In Review. Current approaches to developing sediment quality criteria.
Submitted to Environmental Toxicology & Chemistry.
Chapman, P.M., and J.D. Morgan. 1983. Sediment bioassays with oyster larvae. Bull.
Environ. Contam. Toxicol. 31:438-444.
Chapman, P.M., R.N. Dexter, and E.R. Long. 1987. Synoptic measures of sediment
contamination, toxicity and infaunal community composition (the Sediment Quality Triad)
in San Francisco Bay. Mar. Ecol. Prog. Ser. 37:75-96.
DeWitt, T.H., G.R. Ditsworth, and R.C. Swartz. (1988). Effects of natural sediment
features on survival of the phoxocephalid amphipod Rhepoxynius abronius. Mar. Environ.
Res. 25:99-124.
Diachenko, G.W. 1981. Sorptive interactions of selected volatile hydrocarbons with
humic acids from different environments. PhD Dissertation, University of Maryland.
Dexter, R.N., D.E. Anderson, E.A. Quinlan, L.S. Goldstein, R.M. Strickland, S.P. Pavlou,
J.R. Clayton, Jr., R.M. Kocan, M. Landolt. 1982. A summary of knowledge of Puget
Sound related to chemical contaminants. NOAA Technical Memorandum. OMPA-13.
NOAA/OMPA, Boulder, CO, 435 pp.
DiToro, D.M. and L.M. Horzempa. 1982. Reversible and resistant components of PCB
adsorption-desorption: isotherms. Environ. Sci. Technol. 16:594-602.
DiToro, D.M., J.S. Jeris, and D. Ciarcia. 1985. Diffusion and partitioning of hexachloro-
biphenyl in sediments. Environ. Sci. Technol. 19:1169-1176.
Farrington, J.W. and J.M. Teal. 1982. Pollutant chemical measurements and biological
availability: a lesson to be learned from fossil fuel hydrocarbons. Trans. Am. Geophys.
Union. 53:86.
54
-------
Fisher, J.B., R.L. Petty, and W. Lick. 1983. Release of polychlorinated biphenyls from
contaminated lake sediments: flux and apparent diffusivities of four individual PCBs.
Environ. Pollut. (Ser. B) 5:121-132.
Freeman, D.H. and L.S. Cheung. 1981. A gel partition model for organic desorption
from a pond sediment. Science (Wash., DC) 214:790-792.
Gahler, A.R., J.M. Cummins, J.N. Blazevich, R.H. Riech, R.L. Arp, C.E. Gangmark, S.V.W.
Pope, and S. Filip. 1982. Chemical contaminants in edible non-salmonid fish and crabs
from Commencement Bay, WA. U.S. Environmental Protection Agency 910/9-82-093.
EPA Region 10, Seattle, WA. 117 pp.
Gauthier, T.D., W.R. Seitz, and C.L. Grant. 1987. Effects of structural and compositional
variations of dissolved humic materials on pyrene Koc values. Environ. Sci. Technol.
21:243-248.
Ginn, T.C., and R.C. Barrick. 1988. Bioaccumulation of toxic substances in Puget
Sound organisms. Proc. Fifth International Ocean Disposal Symposium. pp. 157-168.
In: Oceanic Processes in Marine Pollution, Volume 5: Urban Wastes in Coastal Marine
Environments. D.A. Wolfe and T.P. O'Conner (eds). Robert E. Krieger Publishing Co.,
Malabar, FL.
Hatcher, P.G., R. Rowan, and M.A. Mattingly. 1980. *H and 13C NMR of marine humic
acids. Org. Geochem. 2:77-85.
Hatcher, P.G., G.E. Maciel, and L.W. Dennis. 1981. Aliphatic structure of humic acids;
a clue to their origin. Org. Geochem. 3:43-48.
Karickhoff, S.W. 1984. Organic pollutant sorption in aquatic systems. J. Hydraulic
Engin. 110:707-735.
Karickhoff, S.W., and K.R. Morris. 1985a. Impact of tubificid oligochaetes on pollutant
transport in bottom sediments. Environ. Sci. Technol. 19:51-56.
Karickhoff, S.W., and K.R. Morris. 1985b. Sorption dynamics of hydrophobic pollutants
in sediment suspensions. Environ. Toxicol. Chem. 4:469-479.
Lie, U. 1968. A quantitative study of benthic infauna in Puget Sound, Washington,
U.S.A., in 1963-64. FiskDir. Skr., (Ser Havunders.). 14:229-556.
Long, E.R., and P.M. Chapman. 1985. A sediment quality triad: Measures of sediment
contamination, toxicity and infaunal community composition in Puget Sound. Mar.
Pollut. Bull. 16:405-415.
Lyman, W.J., A.E. Glazer, J.H. Ong, and S.F. Coons. 1987. An overview of sediment
quality in the United States. Final Report. Prepared for U.S. Environmental Protection
Agency, Office of Water Regulations and Standards, Monitoring and Data Support
Division, Washington, D.C. Arthur D. Little, Inc., Cambridge MA. 112 pp. w/appendices.
Malins, D.C., B.B. McCain, D.W. Brown, A.K. Sparks, H.O. Hodgins, and S.L. Chan.
1982. Chemical contaminants and abnormalities in fish and invertebrates from Puget
55
-------
Sound. Technical Memorandum OMPA-19. National Oceanic and Atmospheric Administration,
Seattle, WA.
Malins, D.C., B.B. McCain, D.W. Brown, S.L. Chan, M.S. Myers, J.T. Landahl, P.G.
Prohaska, A.J. Friedman, L.D. Rhodes, D.G. Burrows, W.D., Gronlund, and H.O. Hodgins.
1984. Chemical pollutants in sediments and diseases of bottom-dwelling fish in Puget
Sound, Washington. Environ. Sci. Technol. 18:705-713.
Nichols, F.H. 1975. Dynamics and energetics of three deposit-feeding benthic inver-
tebrate populations in Puget Sound, Washington. Ecol. Monogr. 45:57-82.
Osborn, J.G., D.E. Weitkamp, and T.H. Schadt. 1985. Alki wastewater treatment plant
outfall improvements predesign study. Tech. Rep. No. 6.0, Marine Biology. Municipality
of Metropolitan Seattle. 50 pp.
Pastorok, R., H. Beller, S. Becker, T. Ginn, L. Jacobs, N. Musgrove, G. Braun, and P.
Chapman. 1988. Everett Harbor action program: analysis of toxic problem areas.
Final Report. Prepared for U.S. Environmental Protection Agency Region 10, Office of
Puget Sound. PTI Environmental Services and Tetra Tech, Inc., Bellevue, WA. September,
1988.
Prahl, F.G., and R. Carpenter. 1983. PAH-phase associations in Washington coastal
sediment. Geochim. Cosmochim. Acta 47:1013-1023.
Romberg, G.P., S.P. Pavlou, and E.A. Crecelius. 1984. Presence, distribution, and fate
of toxicants in Puget Sound and Lake Washington. METRO Toxicant Program Report
No. 6A. Toxicant Pretreatment Planning Study Technical Report Cl. Municipality of
Metropolitan Seattle, Seattle, WA. 231 pp.
Sokal, R.R., and F.J. Rohlf. 1969. Biometry. W.H. Freeman and Company, San Francisco,
CA. 776 pp.
Swartz, R.C., W.A. Deben, K.A. Sercu, and J.O. Lamberson. 1982. Sediment toxicity and
the distribution of amphipods in Commencement Bay, Washington, U.S.A. Mar. Pollut.
Bull. 13:359-364.
Swartz, R.C., W.A. DeBen, J.K.P. Jones, J.O. Lamberson, and F,A. Cole. 1985. Phoxocephalid
amphipod bioassay for marine sediment toxicity. pp. 284-307. In: Aquatic Toxicology
and Hazard Assessment: 7th Symposium, ASTM STP 854. R.D. Cardwell, R. Purdy, and
R.C. Banner (eds). American Society for Testing and Materials, Philadelphia, PA.
Tetra Tech. 1987. Recommended season for sampling subtidal benthic macroinvertebrates
during Puget Sound monitoring. Draft Report. Prepared for U.S. Environmental Protection
Agency, Region 10. Tetra Tech, Bellevue, WA. 22 pp.
Trial, W., and J. Michaud. 1985. Alki wastewater treatment plant outfall improvements
predesign study. Tech. Rep. No. 8.3, Water Quality. Municipality of Metropolitan
Seattle. 89 pp.
U.S. Department of the Navy. 1985. Final environmental impact statement. Carrier
Battle Group Puget Sound region ship homeporting project. Tech. Appendix. Vol. 2.
56
-------
Prepared for U.S. Department of the Navy, Western Division, Naval Facilities Engineering
Command, San Bruno, CA.
Williams, L.G., P.M. Chapman, and T.C. Ginn. 1986. A comparative evaluation of
marine sediment toxicity using bacterial luminescence, oyster embryo, and amphipod
sediment bioassays. Mar. Environ. Res. 19:225-249.
Word, J.Q., P.L. Striplin, K. Keeley, et al. 1984. Renton sewage treatment plant project.
Seahurst baseline study. Volume V. Section 6. Subtidal benthic ecology. University
of Washington Fisheries Research Institute, Seattle, WA. 461 pp.
Yake, W., and D. Norton. 1986. Memorandum, July 1, 1986: Chemical contamination of
groundwater, intertidal seepage, and sediments on and near Wyckoff Company property;
Eagle Harbor, Bainbridge Island. Water Quality Investigations Section, Washington
Department of Ecology, Olympia, WA 60 pp.
Zar, J.H. 1974. Biostatistical analysis. Prentice-Hall, Inc. Englewood Cliffs, NJ.
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