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;

-------
           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

                                             12

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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

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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  AET—AET  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

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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

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               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

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     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 Tests—Currently, 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

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             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

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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

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   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

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     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

-------
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  Data—Several  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

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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

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     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 Exchange—Based 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 Matter—For 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
                                            51

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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.
                                            52

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                                   6. REFERENCES
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Barrick, R.,  S. Becker,  D. Weston, and  T. Ginn.   1985.   Commencement  Bay  nearshore/
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Barrick, R.,  H.  Beller, and  M. Meredith.   1986.   Eagle Harbor  Preliminary Investigation.
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Barrick, R., S. Becker, R.  Pastorok, L. Brown, and H. Beller.  1988.  Sediment quality values
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Battelle  1985.    Detailed chemical   and   biological  analyses  of  selected  sediment  from
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Battelle.    1988.    Overview of  methods for  assessing  and  managing  sediment  quality.
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Beckman Instruments, Inc.  1982. Microtox system operating manual.  Carlsbad, CA.

Beller, H.,  R.  Barrick,  and S. Becker.    1986.   Development of sediment  quality values
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Beller, H.,  R.  Pastorok,  S.  Becker, G.   Braun,  G.  Bilyard,  and  P.   Chapman.    1988a.
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Beller, H., R. Barrick,  L. Jacobs,  and S.  Becker.   1988b.  Commencement  Bay Nearshore/
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Bulich,  A.A.,  M.W.  Greene, and  D.L.  Isenberg.   1981.   Reliability of  the  bacterial  lumi-
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Chapman, P.M., R.N.  Dexter,  and  E.R.   Long.    1987.    Synoptic  measures of  sediment
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Diachenko,  G.W.    1981.    Sorptive  interactions  of  selected   volatile  hydrocarbons with
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Fisher,  J.B.,  R.L. Petty,  and W.  Lick.   1983.   Release of polychlorinated  biphenyls  from
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Long,  E.R.,  and P.M. Chapman.   1985.   A  sediment quality  triad:  Measures of sediment
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